The Road Towards 6G: A Comprehensive Survey
Wei Jiang, Bin Han, Mohammad Asif Habibi, Hans Dieter Schotten
11 The Road Towards 6G: A Comprehensive Survey
Wei Jiang,
Senior Member, IEEE , Bin Han,
Member, IEEE ,Mohammad Asif Habibi, and Hans Dieter Schotten,
Member, IEEE
As of today, the fifth generation (5G) mobile communication system has been rolled out in many countries and the number of5G subscribers already reaches a very large scale. It is time for academia and industry to shift their attention towards the nextgeneration. At this crossroad, an overview of the current state of the art and a vision of future communications are definitely ofinterest. This article thus aims to provide a comprehensive survey to draw a picture of the sixth generation (6G) system in termsof drivers, use cases, usage scenarios, requirements, key performance indicators (KPIs), architecture, and enabling technologies.First, we attempt to answer the question of “Is there any need for 6G?” by shedding light on its key driving factors, in whichwe predict the explosive growth of mobile traffic until 2030, and envision potential use cases and usage scenarios. Second, thetechnical requirements of 6G are discussed and compared with those of 5G with respect to a set of KPIs in a quantitative manner.Third, the state-of-the-art 6G research efforts and activities from representative institutions and countries are summarized, and atentative roadmap of definition, specification, standardization, and regulation is projected. Then, we identify a dozen of potentialtechnologies and introduce their principles, advantages, challenges, and open research issues. Finally, the conclusions are drawn topaint a picture of “What 6G may look like?”. This survey is intended to serve as an enlightening guideline to spur interests andfurther investigations for subsequent research and development of 6G communications systems.
Index Terms —5G, 6G, artificial intelligence, blockchain, cell-free MIMO, digital twin, edge computing, holographic-typecommunications, Internet of Everything, Internet of Things, machine learning, mobile networks, non-terrestrial networks, opticalwireless communications, O-RAN, Tactile Internet, Terahertz, visible light communications, wireless communications G LOSSARY first generation two-dimensional three-dimensional third generation Third Generation Partnership Project fourth generation fifth generation Fifth Generation Private Public Partnership sixth generation AI artificial intelligence AoI age of information AR augmented reality AoS age of synchronization
AES advanced encryption standard
ATIS
Alliance for Telecommunications Industry Solutions
CAPEX capital expenditure
CDMA code division multiple access
CoMP coordinated multi-point CR cognitive radio CPU central processing unit CU centralized unit DARPA
Defense Advanced Research Projects Agency
DSA digital signature algorithm
DLT distributed ledge technology
DSM dynamic spectrum management DU distributed unit Corresponding author: Wei Jiang (e-mail: [email protected]).
W. Jiang and H. D. Schotten are with the Intelligent Networking Re-search Group, German Research Center for Artificial Intelligence (DFKI),67663 Kaiserslautern, Germany (e-mails: { wei.jiang, hans dieter.schotten } @dfki.de).B. Han, M. A. Habibi, and H. D. Schotten are with the Division ofWireless Communications and Radio Navigation (WICON), Department ofElectrical and Computer Engineering, University of Kaiserslautern, 67663Kaiserslautern, Germany (e-mails: { binhan, asif, schotten } @eit.uni-kl.de). E2E end-to-end
ECC elliptic curve cryptosystem EI edge intelligence eMBB enhanced mobile broad-band ENI experiential network intelligence ER extended reality ETSI
European Telecommunication Standard Institute
FCC
Federal Communications Commission
FSO free-space optical
GEO geostationary Earth orbit
GDPR
General Data Protection Regulation gNB next-generation NodeB
GSM
Global System for Mobile communications
HAP high-altitude platform
HTC holographic-type communication
IAB integrated access and backhaul
ICT information and communication technology
IDMA interleave division multiple access
IMT
International Mobile Telecommunications
IoE internet of everything
IoIT internet of intelligent things
IoT internet of things IR infrared IRS intelligent reflecting surfaces
ISG industry specification group
ISTN integrated space and terrestrial network
ITU-R
International Telecommunciation Union - Radiocom-munication
ITU-T
International Telecommunciation Union - Telecommu-nication
KPI key performance indicator
LBT listen-before-talk LD Laser diode
LED light-emitting diodes
LEO low Earth orbit a r X i v : . [ ee ss . SP ] F e b LOS line of sight
LTE long term evolution
M2M machine to machine
MBB mobile broadband
MIMO multi-input multi-output ML machine learning mMTC massive machine-type communications mmWave millimeter wave mULC massive ultra-reliable low-latency communication MUSA multi-user shared access
NFMF network function management function
NFV network function virtualization
MANO management and orchestration
NG-RAN next-generation radio access network
NGMN
Next Generation Mobile Networks
NIST
National Institute of Standards and Technology
NOMA non-orthogonal multiple access NR new radio NSSMF network slice subnet management function
OFDM orthogonal frequency-division multipling
OMA orthogonal multiple access
OPEX operational expenditure
O-RAN open radio access network PD power domain PDMA pattern-division multiple access
PNF physical network function
PoP point of presence
PPP
Public-Private Partnership
PRB physical resource block
QoS quality of service
RAN radio access network
RAT radio access technology RF radio frequency RIS reconfigurable intelligent surfaces
RSA
Rivest-Shamir-Adleman RU radio unit SCMA sparse-code multiple access
SDN software-defined networking
SLAM simultaneous localization and mapping
SLM spatial light modulator
SRE smart radio environment
SWIPT simultaneous wireless information and power transfer
TCMA trellis-coded multiple access
TD-SCDMA time division synchronous code division multi-ple access
THz terahertz
UAV unmanned aerial vehicle
ULBC ultra-reliable low-latency broadband communication uMBB ubiquitous mobile broadband
URLLC ultra-reliable low-latency communications
VLC visible light communication
VNF virtual network function VR virtual reality WCDMA wideband code division multiple access
WSN wireless sensor network
WRC
World Radiocommunication ConferenceI. INTRODUCTION T HE mobile telecommunication industry stems from thefirst generation (1G) analog cellular systems representedby Advanced Mobile Phone System in the United States andNordic Mobile Telephone in Europe, which firstly offeredmobile voice-calling service around the year 1980. Since then,a new generation of mobile communications was introduced tomarket nearly every ten years. The 1G analog systems werereplaced by the second generation digital cellular networksin around 1990. Despite of several competing systems, theGlobal System for Mobile Communications known as GSM[1] achieved a great commercial success and allowed morethan one billion of the world’s population to enjoy the con-venience brought by mobile voice, short texting, and low-ratedata services. Exploiting a revolutionary technology namedCode-Division Multiple Access (CDMA), the third generation(3G) systems [2] represented by WCDMA, CDMA2000, andTD-SCDMA, were developed and firstly deployed in 2001to support high-speed data access with a rate of severalmegabits per second. In December 2009, the commercialLong Term Evolution (LTE) networks [3] were launched inthe Scandinavian capitals Stockholm and Oslo, providing theworld’s first fourth generation (4G) mobile broadband service.The 4G system that is empowered by a genius combination ofmulti-input multi-output (MIMO) and orthogonal frequency-division multiplexing (OFDM) spurs the proliferation of smartphones, fostering the mobile Internet industry that is worthtrillions of dollars a year.In April 2019, when South Korea’s three mobile operatorsand U.S. Verizon were arguing with each other about whois the world’s first provider of the fifth generation (5G)communication services, we stepped into the era of 5G. Inthe past two years, the term of 5G has been remaining one ofthe hottest buzzwords in the media, attracting unprecedentedattention from the whole society. It even went beyond thesphere of technology and economy, becoming the focal pointof geopolitical tension. Unlike the previous generations thatfocused merely on improving network capacities, 5G expandsmobile communication services from human to things, andalso from consumers to vertical industries. The potential scaleof mobile subscription is substantially enlarged from merelybillions of the world’s population to almost countless inter-connectivity among humans, machines, and things. It enablesa wide variety of services from traditional mobile broadband toIndustry 4.0, virtual reality (VR), Internet of Things (IoT), andautomatic driving [4]. In 2020, the outbreak of the COVID-19pandemic leads to a dramatic loss of human life worldwide andimposes unprecedented challenges on societal and economicactivities. But this public health crisis highlights the uniquerole of networks and digital infrastructure in keeping societyrunning and families connected, especially the values of 5Gservices and applications, such as remote surgeon, onlineeducation, remote working, driver-less vehicles, unmanneddelivery, robots, smart healthcare, and autonomous manufac-turing.Currently, 5G is still on its way being deployed across theworld, but it is already the time for academia and industry toshift their attention to beyond 5G or the sixth generation (6G)systems, in order to satisfy the future demands for information and communications technology (ICT) in 2030. Even thoughdiscussions are ongoing within the wireless community as towhether there is any need for 6G or whether counting thegenerations should be stopped at 5, adopting the Microsoft’sapproach where Windows 10 is the ultimate version, andeven there is an opposition to talking about 6G [5], severalpioneering works on the next-generation wireless networkshave been initiated. A focus group called
Technologies forNetwork 2030 within the International TelecommunicationUnion Telecommunication (ITU-T) standardization sector wasestablished in July 2018. The group intends to study thecapabilities of networks for 2030 and beyond [6], when itis expected to support novel forward-looking scenarios, suchas holographic-type communications, ubiquitous intelligence,Tactile Internet, multi-sense experience, and digital twin. TheEuropean Commission initiated to sponsor beyond 5G researchactivities, as its recent Horizon 2020 calls - ICT-20
5G LongTerm Evolution and ICT-52
Smart Connectivity beyond 5G – where a batch of pioneer research projects for key 6Gtechnologies were kicked off at the early beginning of 2020.The European Commission has also announced its strategyto accelerate investments in Europe’s “Gigabit Connectivity”including 5G and 6G to shape Europe’s digital future [7]. InOctober 2020, the Next Generation Mobile Networks (NGMN)has launched its new “6G Vision and Drivers” project, in-tending to provide early and timely direction for global 6Gactivities. At its meeting in February 2020, the InternationalTelecommunication Union Radiocommunication sector (ITU-R) decided to start study on future technology trends for thefuture evolution of International Mobile Telecommunications(IMT) [8]. In Finland, the University of Oulu began ground-breaking 6G research as part of Academy of Finland’s flagshipprogram [9] called 6G-Enabled Wireless Smart Society andEcosystem (6Genesis), which focuses on several challengingresearch areas including reliable near-instant unlimited wire-less connectivity, distributed computing and intelligence, aswell as materials and antennas to be utilized in future forcircuits and devices. Besides, other traditional main playersin mobile communications, such as the United States, China,Germany, Japan, and South Korea, already initiated their 6Gresearch officially or at least announced their ambitions andtentative roadmaps. At this crossroad, an overview of thecurrent state of the art and a vision of future communi-cations to provide an enlightening guideline for subsequentresearch and development works is of interest. Recently, thearticles focusing on 6G topics, e.g., use cases, applicationscenarios, requirements, and promising technological pillars,are emerging in the literature, as summarized in the followingsubsection.
A. State-of-the-Art Related Works
The earliest article [10] that discusses the topic of 6G waspublished in September 2018, where David and Berndt triedto address the question of “Is there any need for beyond5G?” by reviewing the key services and innovations fromthe 1G analog system to the virtualized and software-defined5G infrastructure. Nawaz et al. [11] checked the state-of-the-art advances in the fields of machine learning (ML) and quantum computing, and then envisaged their synergies withcommunication networks to be considered in the 6G system. In[12], Rappaport et al. described the challenges and potentialsof terahertz (THz) communications in the development andimplementation of 6G networks. Later, the authors of [13]provided a brief description of vision and potential techniques.In [14], Letaief et al. discussed potential technologies to enableubiquitous Artificial Intelligence (AI) service in 6G networks(i.e., networking for AI) and AI-enabled methodologies forthe design and optimization of 6G (i.e., AI for networking).Zong et al. proposed two candidate system architectures for6G in [15] and identify several 6G technologies includingphotonics-defined radio, holography, and AI. In the context,the authors of [16] aimed to shed light on requirements,network architecture, key technologies, and new applicationsin the upcoming 6G system. In [17], Strinati et al. envisionedfive technology enablers for 6G, i.e., pervasive AI at networkedge, three-dimensional (3D) coverage consisting of terrestrialnetworks, aerial platforms, and satellite constellation, a newphysical layer incorporating sub-
THz and Visible Light Com-munications (VLC), distributed security mechanisms, and anew architecture. Huang et al. surveyed the new architecturalchanges associated with green 6G networks in [18], whichalso briefly introduces several potential technologies suchas ubiquitous 3D coverage, pervasive AI,
THz , VLC, andblockchain. In [19], Jiang and Luo provided a comprehensiveand highly coherent treatment on all the technology aspectsrelated to ML for wireless communications and networks.Since the beginning of 2020, the number of publicationsrelated to 6G grows a bit faster than that of the past two years.In [20], Dong et al. argued that 6G should be human centric,and therefore security, secrecy, and privacy are key features.To support this vision, a systematic framework, requiredtechnologies, and anticipated challenges were outlined. Then,a survey on various ML technologies applied for communica-tion, networking, and security aspects of vehicular networks,and a vision of the ways toward an intelligent 6G vehicularnetwork were provided in [21]. Polese et al. foresaw severalpossible 6G use cases and present a number of technologies,which are considered by the authors as the enablers for theseuse cases [22]. Viswanathan and Mogensen attempted to painta broad picture of communication needs and technologies inthe era of 6G [23], where new themes that are likely to shape6G requirements are presented. Zhang, Xiang, and Xu arguedin their article [24] that 1 000 times price reduction fromthe customer’s view point is the key to success for the 6Gsystem. In [25], Chen et al. contributed a comprehensive dis-cussion that covers visions, requirements, technology trends,and challenges, aiming at clarifying the ways to tackle thechallenges of coverage, capacity, data rate, and mobility of6G mobile communication systems. The authors of [26] sharedtheir viewpoints in terms of applications, technological trends,service classes, and requirements, and then give their identifi-cation on enabling technologies and open research problems.Kato et al. [27] recognized possible challenges and potentialresearch directions of advancing ML technologies into thefuture 6G network from the perspectives of communication,networking, and computing. Guo outlined the core concepts
TABLE IS
UMMARY OF STATE - OF - THE - ART CONTRIBUTIONS RELATED TO COMMUNICATION SYSTEMS
Ref. Public. Time Topics Major Contributions [10] Sept. 2018 Vision Reviews the key services and innovations from 1G to 5G, and provide a vision for 6G.[11] April 2019 ML Reviews the state-of-the-art advances in ML and quantum computing, and proposes a quantum computing-assisted MLframework for 6G networks.[12] June 2019 THz Describes the technical challenges and potentials for wireless communications and sensing above , and presentdiscoveries, approaches, and recent results that will aid in the development and implementation of 6G networks.[13] July 2019 Vision Outlines a number of key technological challenges and the potential solutions associated with 6G.[14] Aug. 2019 AI Discusses potential technologies for 6G to enable ubiquitous AI applications and AI-enabled approaches for the design andoptimization of 6G.[15] Sept. 2019 Vision Proposes two candidate system architectures for 6G and identify several 6G technologies including photonics-defined radio,holography, and AI.[16] Sept. 2019 Survey A survey aiming to identify requirements, network architecture, key technologies, and new applications.[17] Sept. 2019 Technologies Five technology enablers for 6G, including pervasive AI at network edge, 3D coverage consisting of terrestrial networks, aerialplatforms, and satellite constellation, a new physical layer incorporating sub-
THz and VLC, distributed security mechanisms,and a new architecture.[18] Dec. 2019 Green 6G A survey on new architectural changes associated with 6G networks and potential technologies such as ubiquitous 3Dcoverage, pervasive AI,
THz , VLC, and blockchain.[19] Dec. 2019 AI A special issue provides a comprehensive treatment on all the technology aspects related to ML for wireless communications,covering fading channel, channel coding, physical-layer design, network slicing, resource management, mobile edge, fogcomputing, and autonomous network management.[20] Jan. 2020 Vision Argues that 6G should be human-centric, and therefore security, secrecy, and privacy are key features. To support this vision,a systematic framework, required technologies, and challenges are outlined.[21] Feb. 2020 Vehicular Summarizes various ML technologies that are promising for communication, networking, and security aspects of vehicularnetworks, and envisions the ways towards an intelligent 6G vehicular network, including intelligent radio, networkintelligentization, and self-learning.[22] Mar. 2020 Use cases Foresees several possible use cases and key technologies that are considered as the enablers for these 6G use cases.[23] Mar. 2020 Survey New themes including new human-machine interface, ubiquitous computing, multi-sensory data fusion, and precise sensingand actuation. Then, major technology transformations such as new spectrum, new architecture, and new security are presented,with the emphasize of AI’s potentials.[24] Mar. 2020 AI Argues that 1 000 times price reduction from the customer’s view point is the key to success and uses AI-assisted intelligentcommunications to illustrate the drive-force behind.[25] April 2020 Survey A comprehensive discussion of 6G based on the review of 5G developments, covering visions, requirements, technologytrends, and challenges, aiming at clarifying the ways to tackle the challenges of coverage, capacity, data rate, and mobilityof 6G communication systems.[26] May 2020 Survey A vision on 6G in terms of applications, technological trends, service classes, and requirements, as well as an identificationon enabling technologies and open research problems.[27] June 2020 ML Possible challenges and potential research directions of advancing ML technologies into the future 6G network in terms ofcommunication, networking, and computing perspective.[28] June 2020 AI The core concepts of explainable AI for 6G, including public and legal motivations, definitions, the trade-off betweenexplainability and performance, explainable methods, and an explainable AI framework for future wireless systems.[29] Aug. 2020 Survey A survey on 6G in terms of applications, requirements, challenges, and research directions. Some key technologies such asAI,
THz , blockchain, and wireless optical communications are briefly introduced.[30] Aug. 2020 Vision Extends the vision of 5G to more ambitious scenarios in a more distant future and speculates on the visionary technologiesthat can provide the step changes needed for enabling 6G.[31] Sept. 2020 Vision Identifies vision, new application scenarios, and key performance requirements, and proposes a logical mobile networkarchitecture.[32] Oct. 2020 Survey A brief presentation of various 6G issues including core services, use cases, requirements, enabling technologies, architectures,typical use scenarios, challenges, and research directions.[33] Oct. 2020 MIMO An overview of holographic MIMO surface (HMIMOS) communications including the available hardware architectures forre-configuring such surfaces, highlighting the opportunities and key challenges in designing HMIMOS-enabled wirelesscommunications for 6G.[34] Oct. 2020 Survey A comprehensive study of 6G visions, requirements, challenges, and open research issues, outlining seven disruptivetechnologies, i.e., millimeter wave (mmWave) communications,
THz communications, optical wireless communications,programmable meta-surfaces, drone-based communications, back-scatter communications, and Tactile Internet.[35] Nov. 2020 THz Analyzes link budget of THz links with justified estimates of calculus terms, such as the achievable or required noise figure,transmit power, and antenna gain.[36] Nov. 2020 THz Discusses full protocol stack for the realization of end-to-end terahertz 6G mobile networks, from medium access control,network to transport layer.[37] Dec. 2020 Channel A survey of 6G wireless channel measurements and models for full frequency bands, full application scenarios, and fullglobal coverage.[38] Dec. 2020 VLC Presents the prospects and challenges of VLC in 6G, its advances in high-speed transmissions, and recent research interestssuch as new materials and devices, advanced modulation, and underwater VLC.[39] Dec. 2020 UAV Discusses the advantages of unmanned aerial vehicles to improve the coverage and capacity of 6G, and proposes a networksetup utilizing tethered UAVs.[40] Dec. 2020 AI Outlines the concept of trustworthy autonomy for 6G and clarifies how explainable AI can generate the qualitative andquantitative modalities of trust.[41] Dec. 2020 AI/ML Summarizes some intelligent approaches of applying AI and ML tools to optimize 6G networks, including THz communi-cations, energy management, security, mobility management, and resource allocation. of explainable AI for 6G in [28], including public and legalmotivation, definition, the trade-off between explainability andperformance, explainable methods, and an explainable AIframework for future wireless systems. A survey paper [29]provides a comprehensive view of 6G in terms of applica-tions, requirements, challenges, and research directions. Somekey technologies such as AI, terahertz, blockchain, three-dimensional networking, and wireless optical communicationsare briefly introduced. In [30], the authors aimed to extend thevision of 5G to more ambitious scenarios in a more distantfuture and speculate on the visionary technologies that canprovide the step changes needed for enabling 6G. Liu et al.identified the vision of the society development towards 2030and derive key performance requirements from new appli-cations and services. Taken into account the convergence ofinformation and communication technologies, a logical mobilenetwork architecture is proposed to resolve the lessons from5G network design [31]. Guan et al. gave a brief presentationon various 6G issues in [32], including core services, use cases,requirements, enabling technologies, architectures, typical usescenarios, challenges, and research directions. The authorsof [33] provided an overview of holographic MIMO surfacecommunications as a promising technological enabler for 6Gwireless communications.Recently, Bariah et al. gave a comprehensive 6G visionin [34], identifying seven disruptive technologies, associatedrequirements, challenges, and open research issues. From theviewpoints of radio frequency (RF) hardware and antenna,[35] analyzes link budget of THz communication links withjustified estimates of calculus terms, such as the achievable orrequired noise figure, transmit power, and antenna gain. It alsoevaluates communication distances for links implemented withdifferent technologies and complexity at
300 GHz lookingtowards anticipated 6G use scenarios. In [36], Polese et al.provided an overview of the issues that need to be overcome tointroduce the terahertz spectrum in mobile networks, from theperspectives of medium access control, network, and transportlayer, with consideration on the performance of end-to-end(E2E) data flows on terahertz connections. Wang et al. [37]provided a survey of 6G wireless channel measurements andmodels for full frequency bands covering mmWave, THz,and optical wireless communication (OWC) channels, fullcoverage such as satellite, maritime, and underwater acousticcommunication channels, and full application scenarios, e.g.,high-speed train, vehicle-to-vehicle, and industry IoT com-munication channels. Ref. [38] presents the potential of inte-grating VLC in 6G, and discusses its technological advancesincluding new materials and devices, modulation, underwatertransmission, and ML-based signal processing. The authorsof [39] shed light on the advantages of unmanned aerialvehicle (UAV) to improve the coverage and capacity of 6G,and propose a network setup utilizing tethered UAVs. In [40],the authors outline the concept of trustworthy autonomy for6G, clarify how explainable AI can generate the qualitativeand quantitative modalities of trust, and provide associatedkey performance indicators (KPIs) for measuring trust. In[41], Du et al. summarized some intelligent approaches ofapplying AI and ML tools to optimize 6G networks, including THz communications, energy management, security, mobilitymanagement, and resource allocation. To facilitate a clearer il-lustration, the aforementioned works with major contributionsand categorized topics are listed chronologically in Table I.
B. Contributions
It is noticed that most of the aforementioned previous worksfocus merely on one specific aspect of 6G, such as THz [12],AI [14], green networks [18], use cases [22], ML [27], andVLC [38]. There are a few surveys attempting to provide acomplete view, but a comprehensive survey is still missinguntil now. To fill this gap, this article comprehensively surveysthe latest advances of 6G research and provides a broad visionin terms of drivers, requirements, efforts, and enablers. Upon athorough state-of-the-art analysis of related works, this articleis started from envisioning the driving forces, potential usecases, and usage scenarios so as to address the concern on thenecessity of developing 6G. Then, the technical requirementsneeded to support 6G applications and services are clarifiedin terms of a set of KPIs, and promising technologies areidentified and elaborated. The up-to-date research activitiesacross the world are summarized, and the roadmap for re-search, specification, standardization, and development toward2030 is projected. Finally, the conclusions are drawn to painta picture of “What 6G may look like?”.Compared with existing 6G articles, the main contributionsof this article can be listed as follows:1) A thorough state-of-the-art analysis, which provides themost complete summary of related works with latestadvances, is made.2) It attempts to answer the question of “Do we reallyneed 6G?” by shedding light on its key drivers, includ-ing the explosive growth of mobile traffic and mobilesubscriptions until 2030, and disruptive use cases. Itgoes beyond the state of the art by identifying theconsensus of previous works on use cases and proposesnovel use cases that have never been reported, i.e.,Global Ubiquitous Connectability, Enhanced On-BoardCommunications, and Pervasive Intelligence.3) Using a holistic methodology, three novel usage sce-narios for 6G are proposed, i.e., ubiquitous mobileboardband (uMBB), ultra-reliable low-latency broad-band communication (ULBC), and massive ultra-reliablelow-latency communication (mULC).4) It discusses the technical requirements of 6G in termsof a set of KPIs, which are compared with the KPIs of5G quantitatively, if applicable.5) It summarizes the ambitions, efforts, and research activi-ties on 6G across the world, while a tentative roadmap ofdefinition, specification, standardization, and regulationis envisaged. To the best knowledge of the authors, thatis the first time in the literature to provide such aninvestigation from this perspective.6) An architecture of 3D coverage integrating non-terrestrial and terrestrial networks is envisioned andillustrated within envisioned 6G deployment scenarios.
7) Unlike all previous works that simply list technologicalcandidates in a line, we categorize 6G enabling tech-nologies into the following groups: New Spectrum, NewNetworking, New Air Interface, New Architecture, andNew Paradigm. This methodology is the first time beingused in 6G publications.8) It gives a complete view of potential 6G technologies,which identifies the largest set of enablers by far andthe number of identified enablers is far more than anyexisting survey. The principle, advantages, challenges,and open issues for each enabler are elaborated. Someof the technologies are introduced in detail for the firsttime from the perspective of 6G, e.g., large-scale satelliteconstellation and post-quantum security. It includes: new spectrum consisting of mmWave,
THz communi-cations, VLC, OWC, and dynamic spectrum manage-ment (DSM), new networking that covers softwarizationand virtualization, radio access network (RAN) slic-ing, open-RAN (O-RAN), and post-quantum security, new air interface including massive MIMO, intelli-gent reflecting surfaces (IRS), coordinated multi-point(CoMP), cell-free massive MIMO, and new modulationtechniques, new architecture providing 3D coverage bymeans of integrating large-scale satellite constellation,high-altitude platform (HAP), and UAV with traditionalterrestrial networks, and new paradigm empowered bythe convergence of computing-communication resourcesand the integration of mobile networks, AI, blockchain,and digital twin.9) It concludes this article by painting a picture of “What6G may look like?”. The authors envision that 6Gwould be a radio-optical system, a connected intelligentplatform, an integrated space-aerial-terrestrial network,and a smart compute-connect entity to transform thewhole Earth into a huge brain, which fully supports theinformationized and intelligentized society in 2030 andbeyond.
C. Organization of the Article
The rest of this article is organized as follows: Section IIclarifies the key driving forces for the necessity of developing6G, including the explosive growth of mobile traffic andmobile subscriptions, disruptive use cases, and advanced usagescenarios. Section III analyzes the technical requirements forthe 6G system in terms of a number of KPIs. The ambitionsand efforts from the main players in the mobile communica-tion industry are summarized and a development roadmap isestimated in Section IV. Section V provides a complete viewof a dozen of key technologies for 6G. Finally, Section VIconcludes this article by painting a picture about what 6G is.II. D
RIVERS
Since the middle of 2019, commercial 5G mobile networkshave been rolled out across the world and already reached avery large scale in some countries. For example, the numberof deployed 5G base stations in China exceeds
500 000 at theend of 2020, serving more than million 5G subscribers. Following the tradition that a new generation appears everyone decade, it is time for both academia and industry to initiatethe exploration of the successor of 5G. On the road towards6G, however, the first problem we encounter is that there aremany concerns like “
Do we really need 6G? ” or “
Is 5G alreadyenough? ”. To address such questions, we first need to clarifythe key driving forces for 6G.The development of a next-generation system is driven bynot only the exponential growth of mobile traffic and mobilesubscriptions but also new disruptive services and applicationson the horizon. In addition, it is also driven by the intrinsicneed of mobile communication society to continuously im-prove network efficiencies namely cost efficiency, energy ef-ficiency, spectrum efficiency, and operational efficiency. Withthe advent of advanced technologies such as AI,
THz , andlarge-scale satellite constellation, the communication networkis able to evolve towards a more powerful and more efficientsystem to better fulfil the requirements of current services andopen the possibility for offering disruptive services that havehitherto never been seen. In this section, we intend to shedlight on three drivers: i ) the explosive growth of mobile traffic, ii ) disruptive use cases, and iii ) novel usage scenarios. Itstechnological drivers will be discussed in detail in Section V. A. Explosively Growing Mobile Traffic
We are in an unprecedented era where a large number ofsmart products, interactive services, and intelligent applica-tions emerge and evolve in a prompt manner, imposing a hugedemand on mobile communications. It can be foreseen that the5G system is hard to accommodate the tremendous volume ofmobile traffic in 2030 and beyond. Due to the proliferation ofrich-video applications, enhanced screen resolution, machine-to-machine (M2M) communications, mobile cloud services,etc., the global mobile traffic will continuously increase in anexplosive manner, up to per month in the year of2030 compared with
62 EB per month in 2020, according tothe estimation by ITU-R [42] in 2015. A report from Ericsson[43] reveals that the global mobile traffic has reached
33 EB per month at the end of 2019, which justifies the correctnessof ITU-R’s estimation.In the last decade, the number of smartphones and tabletshas experienced an exponential growth due to the proliferationof mobile broadband (MBB). This trend will continue in the2020s since the penetration of smartphones and tablets is notsaturated especially in developing countries. Meanwhile, new-style user terminals, such as wearable electronics and VRglasses, emerge in the market quickly and are adopted byconsumers in a fast pace. It is expected that the total number ofMBB subscribers worldwide will reach . billion by 2030,as shown in Fig. 1. On the other hand, the traffic demandper MBB user continuously raises in the company of therising number of MBB users. That is mainly because of thepopularity of mobile video services such as Youtube, Netflix,and more recently Tik-Tok, as well as the stable improvementof screen resolution on mobile devices. The traffic coming M BB U s e r s [ B illi on ] Estimation of global mobile subscriptions
MBBM2M O v e r a ll t r a ff i c [ EB ] Estimation of global mobile traffic
OverallUser M M U s e r s [ B illi on ] T r a ff i c / U s e r [ G B ] Fig. 1. Estimated global mobile subscriptions and mobile traffic from 2020to 2030. Source: ITU-R Report M.2370-0 [42]. from mobile video services already account for two thirdsof all mobile traffic nowadays [43] and is estimated to bemore dominant in the future. In some developed countries,a strong traffic growth before 2025 is driven by rich-videoservices and a long-term growth wave will continue due to thepenetration of augmented reality (AR) and VR applications.The average data consumption for every mobile user permonth, as illustrated in Fig. 1, will increase from around in 2020 to over
250 GB in 2030. In addition to human-centriccommunications, the scale of M2M terminals will increasemore rapidly and will become saturated no earlier than 2030.It is predicted that the number of M2M subscriptions willreach billion, around times over that of 2020 [42]. Thisserves as another driving force for the explosive growth ofmobile traffic. B. Potential Use Cases
With the advent of new technologies and continuous evo-lution of existing technologies, e.g., holography, robotics,microelectronics, photo-electronics, AI, and space technology,many unprecedented applications can be fostered in mobilenetworks. To explicitly highlight the unique characteristics anddefine the technical requirements of 6G, we foresee severalrepresentative use cases as follows:
Holographic-Type Communication (HTC) : Compared totraditional 3D videos using binocular parallax, true hologramscan satisfy all visual cues of observing 3D objects by thenaked eye as natural as possible. With a significant advanceof holographic display technology in recent years such asMicrosoft’s HoloLens [44], it is envisioned that its applicationwill become a reality in the next decade. Remote renderinghigh-definition holograms through a mobile network willbring truly immersive experience. For example, holographictelepresence will allow remote participants to be projected asholograms into a meeting room or allow the attendee of onlinetraining or education to interact with ultra-realistic objects.However, HTC leads to huge bandwidth demands on the order of terabits per second even with image compression. Inaddition to consider the frame rate, resolution, and color depthin two-dimensional (2D) video, the quality of hologram alsoinvolves the volumetric data such as tilt, angle, and position.If representing an object with images every . ◦ , an image-based hologram with ◦ field of view and a tilt of ◦ needsa 2D array of 3300 separate images [45]. HTC also requiresultra-low latency for true immersiveness and high-precisionsynchronization across massive bundles of interrelated streamsfor reconstructing holograms. Extended Reality (ER) : Combining augmented, virtual,and mixed realities, ER starts stepping into practical appli-cations in the age of 5G, but it is still in its infancy analogueto the video service at the beginning of mobile Internet. Toachieve the same level of image quality, ER devices with ◦ field of view need much higher data throughput in comparisonto 2D video streaming. For an ideal immersion experience, thequality of video with higher resolution, higher frame rate, morecolor depth, and high dynamic range are required, leading to abandwidth demand of over . per device [46]. Similarto video traffic that saturates the 4G networks, the proliferationof ER devices will be blocked by the limited capacity of 5Gwith the peak rate of
20 Gbps , especially at the cell edge.In addition to bandwidth, interactive ER applications suchas immersive gaming, remote surgery, and remote industrialcontrol, low latency and high reliability are mandatory.
Tactile Internet : It provides extremely low E2E latency tosatisfy the 1-millisecond ( ms ) or less reaction time reachingthe limit of human sense [47]. In combination with highreliability, high availability, high security, and sometimes highthroughput, a wide range of disruptive real-time applicationsare enabled. It will play a critical role in the field of real-timemonitoring and remote industrial management for Industry4.0 and Smart Grid. For example, with immersive audio-visual feeds provided by ER or HTC streaming, together withhaptic sensing data, a human operator can remotely control themachinery in a place surrounded by biological or chemicalhazards, as well as remote robotic surgery carried out bydoctors from hundreds of miles away [48]. The typical closed-loop controlling, especially for devices or machinery movingrapidly, is very time-sensitive, where an E2E latency below is expected. Multi-Sense Experience : Human has five senses (sight,hearing, touch, smell, and taste) to perceive external environ-ment, whereas current communications focus only on optical(text, image, and video) and acoustic (audio, voice, and music)media. The involvement of the senses of taste and smell cancreate fully-immersive experience, which may bring some newservices for example in food and texture industries [6]. Fur-thermore, the application of haptic communication will play amore important role and raise a wide range of applicationssuch as remote surgery, remote controlling, and immersivegaming. This use case brings a stringent requirement on lowlatency.
Digital Twin is used to create a comprehensive and detailedvirtual copy of a physical (a.k.a. real) object. The softwarizedcopy is equipped with a wide range of characteristics, informa-tion, and properties related to the original object. Such a twin is then used to manufacture multiple copies of an object withfull automation and intelligence. The early rollouts of digitaltwin have attracted significant attention of a number verticalindustries and manufacturers. However, its full deployment isexpected to be realized with the development of 6G networks.
Pervasive Intelligence : With the proliferation of mobilesmart devices and the emergence of new-style connectedequipment such as robots, smart cars, drones, and VR glasses,over-the-air intelligent services are envisioned to boom. Theseintelligent tasks mainly rely on traditional computation-intensive AI technologies: computer vision, simultaneous lo-calization and mapping (SLAM), face and speech recogni-tion, natural language processing, motion control, to namea few. To overcome stringent computation, storage, power,and privacy constrains on mobile devices, 6G networks willoffer pervasive intelligence in an AI-as-a-Service manner [14]by utilizing distributed computing resources across the cloud,mobile edge, and end-devices, and cultivating communication-efficient ML training and interference mechanisms. For exam-ple, a humanoid robot such as Atlas from Boston Dynamics[49] is possible to off-load its computational load for SLAMtowards edge computing resources, in order to improve motionaccuracy, prolong battery life, and become more lightweightby removing some embedded computing components. In ad-dition to computation-intensive tasks, pervasive intelligencealso facilitates time-sensitive AI tasks to avoid the latencyconstraint of cloud computing when fast decisions or responsesto conditions are required.
Intelligent Transport and Logistics : In 2030 and beyond,millions of autonomous vehicles and drones provide a safe,efficient, and green movement of people and goods. Connectedautonomous vehicles have stringent requirements on reliabilityand latency to guarantee the safety of passengers and pedes-trians. Unmanned aerial vehicles, especially swarm of drones,open the possibility for a wide variety of unprecedentedapplications, while bringing also disruptive requirements formobile networks.
Enhanced On-Board Communications : With the devel-opment of economy, the activity sphere of human and thefrequency of their movement will rapidly increase in the nextdecade. The number of passengers travelling by commercialplanes, helicopters, high-speed trains, cruise ships, and othervehicles, will be very huge, bringing skyrocketing demandson high-quality communication services on board. Despite theefforts in the previous generations until 5G, it is undeniablethat on-board connectivity is far from satisfactory in mostcases due to high mobility, frequent handover, sparse coverageof terrestrial networks, and limited bandwidth and high cost ofsatellite communications. Relying on reusable space launchingtechnologies and massive production of satellites, the deploy-ment of large-scale satellite constellation such as SpaceX’sStarlink [50] becomes a reality, enabling cost-efficient andhigh-throughput global coverage. Keep this in mind, 6G isexpected to be an integrated system of terrestrial networks,satellite constellation, and other aerial platforms to provideseamless 3D coverage, which offers high-quality, low-cost, andglobal-roaming on-broad communication services.
Global Ubiquitous Connectability : The previous genera- tions of mobile communications focused mainly on the densemetropolitan areas, especially indoor scenarios. However, alarge population in remote, sparse, and rural areas even haveno access to basic ICT services, digging a big digital divideamong humans around the world. Besides, more than
70 % ofthe Earth’s surface is covered by water, where the growth ofmaritime applications require network coverage for both watersurface and underwater. However, ubiquitous coverage acrossthe whole planet with sufficient capacity, acceptable quality ofservice (QoS), and affordable cost is far from a reality. On theone hand, it is technically impossible for terrestrial networksto cover remote areas and extreme topographies such as ocean,desert, and high mountain areas, while it is too costly tooffer terrestrial communication services for sparsely-populatedareas. On the other hand, geostationary Earth orbit (GEO)satellites are expensive to deploy and their capacity is limitedto several
Gbps per satellite [51], which is dedicated onlyfor high-end users such as maritime and aeronautic industries.As mentioned above, the deployment of large-scale low Earthorbit (LEO) satellite constellation will enable low-cost andhigh-throughput global communication services [52]. The 6Gsystem is envisioned to make use of the synergy of terrestrialnetworks, satellite constellation, and other aerial platforms torealize ubiquitous connectability for global MBB users andwide-area IoT applications.The connection of the aforementioned use cases with usagescenarios proposed in the next subsection is depicted in Fig.2,while some representative use cases are demonstrated withinenvisaged 6G deployment scenarios, as shown in Fig.3.
URLLC eMBB mMTC mULCULBC uMBB • Tactile Internet • Intelligent Transport & Logistics • Global Ubiquitous Connectability • Digital Twin • Pervasive Intelligence • Enhanced On-Board Communications • Global Ubiquitous
Connectability • HTC • ER • Tactile Internet • Multi-sense Experience • Pervasive Intelligence
Fig. 2. In addition to typical 5G usage scenarios (eMBB, ULRRC, andmMTC), three enhanced scenarios named uMBB, ULBC, and mULC areproposed by the authors of this article for the 6G system in order to supportdisruptive use cases and applications.
C. Usage Scenarios
The 5G system is designed to meet more diverse QoSrequirements arising from a wide variety of vertical applica-tions and services, which have never encountered by mobile
Cell-free Massive MIMO-empowered Private Heterogeneous NetworkCell-free Massive MIMO-empowered Private Heterogeneous NetworkHAPHAP IABIABAccess PointAccess PointIntelligent Transportation and
Logistics
Intelligent Transportation and
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Extended RealityExtended Reality
Pervasive IntelligencePervasive IntelligencePhysical TwinPhysical Twin
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Inter-vehicle OWC link Inter-vehicle OWC link 6G virtual Access Network6G virtual Access Network Industry 4.0Industry 4.0gNBgNB
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BlockchainBlockchain
Cloud Data CenterCloud Data CenterLong-Range Quantum Key
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Slicing
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AI platformAI platform FSO, mm-wave, or THz backhaul
FSO, mm-wave, or THz backhaul CPUCPU
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Digital TwinDigital Twin Holographic-Type CommunicationHolographic-Type Communication Quantum ComputerQuantum Computer6G virtual Core Network6G virtual Core NetworkCloud Data CenterCloud Data Center
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CommunicationSatelliteVLCVLC Intelligent SurfacesIntelligent Surfaces
BlockchainBlockchain
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Distributed
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Fig. 3. An envision of the deployment scenarios and architecture for 6G, demonstrating representative use cases and some of key technological enablers. subscribers in the previous generations. To define 5G, threeusage scenarios were firstly recommended by ITU-R M.2083in 2015 [53]: • enhanced mobile broad-band (eMBB) addresses thehuman-centric applications for a high-data-rate accessto mobile services, multi-media content, and data. Thisscenario fosters new services and applications over smartdevices (smartphones, tablets, and wearable electronics).It emphasizes wide-area coverage to provide seamlessaccess and high capacity in hot spots. • ultra-reliable low-latency communications (URLLC) is adisruptive promotion over the previous generation sys- tems that focus on human users. It opens the possibilityfor mission-critical connectivity for new applications suchas automatic vehicles, Smart Grid, and Industry 4.0,which have stringent requirements on reliability, latency,and availability. • massive machine-type communications (mMTC) supportsdense connectivity with a very large number of connecteddevices typically deployed in IoT scenarios. The devicessuch as sensors are low-cost, low-power consumption buttypically transmitting a low volume of delay-tolerate data.It can be seen that these 5G usage scenarios cannot satisfythe technical requirements of the aforementioned 6G use cases. For instance, an user that wears a lightweight VR glass toplay interactively-immersive games requires not only ultra-high bandwidth but also low latency. Autonomous vehicles onthe road or flying drones need ubiquitous connectivity withhigh throughput, high reliability, and low latency. Althougha few related works discussed potential usage scenarios for6G, their proposed scenarios are simply an enhancementor extension of 5G scenarios. The definition of scenariosare arbitrary and piece-wise, where the interworking among6G scenarios and their relations with 5G scenarios are notcorrectly clarified. In this article, we propose a holistic andmore reasonable methodology to define 6G scenarios throughextending the scope of current usage scenarios, as shownin Fig. 2. Three new scenarios are proposed to meet therequirement of aforementioned use cases, which cover theoverlapping areas of 5G scenarios so as to form a complete set.To support high-quality on-board communications and globalubiquitous connectability, the MBB service should be availableacross the whole surface of the Earth in the era of 6G, called ubiquitous MBB or uMBB. In addition to its ubiquitousness,another enhancement of uMBB is a remarkable boost ofnetwork capacity and transmission rate for hot spots so asto support disruptive services, e.g., a group of users wearinglightweight VR glasses gathering in a small room where adata rate of several
Gbps per user is needed. The uMBBscenario will be the foundation of digital twin, pervasiveintelligence, enhanced on-board communications, and globalubiquitous connectability, as the mapping relationship shownin Fig. 2. In addition to KPIs that are applied to evaluateeMBB (such as peak data rate and user-experienced data rate),other KPIs become as same critical as the others in uMBB,i.e., mobility, coverage, and positioning, as indicated in TableII.
Ultra-reliable low-latency broadband communication alsocalled ULBC supports the applications requiring not onlyURLLC but also extreme high throughput, e.g., HTC-basedimmersive gaming. It is expected that the use cases of HTC,ER, Tactile Internet, multi-sense experience, and pervasiveintelligence will benefit from this scenario. Furthermore, thethird scenario called massive ultra-reliable low-latency com-munication or mULC combines the characteristics of bothmMTC and URLLC, which will facilitate the deployment ofmassive sensors and actuators in vertical industries. Togetherwith eMBB, URLLC, and mMTC, three new scenarios fill thegaps in-between and then a complete set of usage scenariosis formed to support all kinds of use cases and applicationsin 6G, as shown in Fig. 2. Performance requirements (KPIs)required during the design and implementation of such usagescenarios are listed in Table II.III. R
EQUIREMENTS
To well support disruptive use cases and applications in2030 and beyond, the 6G system will provide extreme capac-ity, reliability, efficiency, etc. Like the minimal requirementsfor IMT-2020 specified in [54], a number of quantitative orqualitative KPIs are utilized to indicate the technical require-ments for 6G. Most of the KPIs that are applied for evaluating5G are still valid for 6G while some new KPIs would be introduced for the assessment of new technological features.The first eight KPIs in the following part are considered askey requirements in the definition of 5G, which are brieflyintroduced as follows: • Peak data rate is the highest data rate under idealconditions, in which all available radio resources aretotally assigned to a single mobile station. Traditionally,it is the most symbolic parameter to differentiate dif-ferent generations of mobile systems. Driven by bothuser demand and technological advances such as
THz communications, it is expected to reach up to , tensof times that of 5G, which has the peak rate of
20 Gbps for downlink and
10 Gbps for uplink. • User-experienced data rate is defined as the th per-centile point ( ) of the cumulative distribution functionof user throughput. In other words, a user can get at leastthis data rate at any time or location with a possibilityof . It is more meaningful to measure the perceivedperformance, especially at the cell edge, and reflect thequality of network design such as site density, architec-ture, inter-cell optimization, etc. In the 5G deploymentscenario of dense urban, the target of user-perceived rateis
100 Mbps for downlink and
50 Mbps for uplink. It isexpected that 6G can offer even higher, which is10 times that of 5G. • Latency can be differentiated into user plane and controlplane latency. The former is the time delay induced ina radio network from a packet being sending out atthe source until the destination receives it, assuming amobile station is in the active state. In 5G, the minimumrequirement for user plane latency is for eMBB and for URLLC. This value is envisioned to be furtherreduced to µ s or even µ s . Control plane latencyrefers to the transition time from a most “battery efficient”state (e.g., the idle state) to the start of continuous datatransfer (e.g., the active state). The minimum latency forcontrol plane should be
10 ms in 5G and is expected to bealso remarkably improved in 6G. In addition to over-the-air delay, round-trip or E2E delay is more meaningful butalso complicated due to the large number of network en-tities involved. In 6G, the E2E latency may be consideredas a whole. • Mobility means the highest moving speed of a mobilestation supported by a network with the provisioningof acceptable Quality of Experience (QoE). To supportthe deployment scenario of high-speed trains, the highestmobility supported by 5G is
500 km / h . In 6G, themaximal speed of / h is targeted if commercialairline systems are considered. • Connection density is the KPI applied for the purposeof evaluation in the usage scenario of mMTC. Given alimited number of radio resources, the minimal numberof devices with a relaxed QoS per square kilometer ( km )is in 5G, which is envisioned to be further improved times to per km . • Energy efficiency is important to realize cost-efficientmobile networks and reduce the total carbon emission TABLE IIP
ERFORMANCE REQUIREMENTS (KPI S ) TO SUPPORT THE IMPLEMENTATION OF USAGE SCENARIOS . KPI P ea kd a t a r a t e U s e r- e xp e r i e n ce dd a t a r a t e L a t e n c y M ob ilit y C onn ec ti ond e n s it y E n e r gy e f fi c i e n c y P ea k s p ec t r a l e f fi c i e n c y A r ea t r a f fi cca p ac it y R e li a b ilit y S i gn a l b a nd w i d t h P o s iti on i ng acc u r ac y C ov e r a g e T i m e li n e ss S ec u r it y a ndp r i v ac y C A P E X a nd O P E X Generation Usage Scenario
5G eMBB ⭐ ⭐ ✓ ✓ ✓ ⭐ ⭐ ⭐ ✓ ✓ ⭐
URLLC ⭐ ✓ ⭐ ✓ ✓ ⭐ ⭐ ⭐ mMTC ⭐ ⭐ ✓ ✓
6G uMBB ⭐ ⭐ ✓ ⭐ ✓ ⭐ ⭐ ✓ ⭐ ✓ ⭐ ✓ ⭐ mULC ⭐ ⭐ ⭐ ⭐ ✓ ✓ ⭐ ⭐ ⭐
ULBC ⭐ ⭐ ⭐ ✓ ✓ ⭐ ⭐ ⭐ ⭐ ✓ ⭐ ⭐ ⭐
Legend ✓ : Generic/weak impact ⭐ : Specialized/critical impact for green ICT, playing a critical role from the societal-economic respective. After the early deployment of 5Gnetworks, there is already some complaints about its highenergy consumption although the energy efficiency per bithas been substantially improved in comparison with theprevious generations. In 6G networks, this KPI would be − times better over that of 5G so as to improvethe energy efficiency per bit while reducing the overallpower consumption of the mobile industry. • Peak spectral efficiency is an important KPI to measurethe advance of radio transmission technologies. The min-imum requirement in 5G for peak spectral efficienciesare
30 bps / Hz in the downlink and
15 bps / Hz in theuplink. Following the empirical data, it is expected thatadvanced 6G radio technologies can achieve three timeshigher spectral efficiency over the 5G system. • Area traffic capacity is a measurement of the total mo-bile traffic that a network can accommodate per unit area,relating to the available bandwidth, spectrum efficiency,and network densification. The minimal requirement for5G is
10 Mbps per square meter ( m ), which is expectedto reach / m in some deployment scenarios suchas indoor hot spots.In addition to the aforementioned key capabilities, there areseveral extended or novel KPIs that may be also required soas to properly evaluate the requirements of 6G. • Reliability relates to the capability of transmitting a givenamount of traffic within a predetermined time durationwith high success probability. This requirement is definedfor the purpose of evaluation in the usage scenario ofURLLC. In 5G networks, the minimum requirement forthe reliability is measured by a success probability of − − when transmitting a data packet of bytes within given the channel quality of coverage edge for thedeployment scenario of urban macro environment. It isexpected to improve at least two orders of magnitude, i.e., − − or .
999 99 % in the next-generation system. • Signal bandwidth is the maximum aggregated systembandwidth. The bandwidth may be supported by singleor multiple RF carriers. The requirement for bandwidthin 5G is at least
100 MHz , and 6G will support up to for operation in higher frequency bands or evenhigher in
THz communications or OWC. • Positioning accuracy of the 5G positioning service isbetter than
10 m . Higher accuracy of positioning has astrong demand in many vertical and industrial applica-tions, especially in indoor environment that cannot becovered by satellite-base positioning systems. With theapplication of
THz radio station, which has a strongpotential in high-accuracy positioning, the accuracy sup-ported by 6G networks is expected to reach centimeter( cm ) level. • Coverage in the definition of 5G requirement mainlyfocuses on the received quality of radio signal within asingle base station. The coupling loss, which is definedas the total long-term channel loss over the link betweena terminal and a base station and includes antenna gains,path loss, and shadowing, is utilized to measure the areaserved by a base station. In 6G networks, the connotationof coverage should be substantially extended consideringthat the coverage will be globally ubiquitous and will beshifted from only 2D in terrestrial networks to 3D in aterrestrial-satellite-aerial integrated system. • Timeliness is an emerging time-domain performancerequirement to future communication systems. Typi-cal metrics of timeliness include the well-known age-of-information (AoI) [55], and its recently proposedvariants such like age-of-task (AoT) [56] and age-of-synchronization (AoS) [57]. Differing from the classicalmemoryless metric of latency, which focuses on theoverall delay experienced by all data packets or servicesessions throughout their delivery process, the conceptof timeliness emphasizes the freshness of the latest dataand service that are successfully delivered to the end user. This brings to the system an endogenous birth-timediscrimination against outdated data/service, as well asa memory to its historical state(s), and therewith raisesboth the impact and the complexity of task scheduling insystem optimization. • Security and privacy are necessary for assessing whetherthe operation of a network is secure enough to protectinfrastructure, devices, data, and assets. The main securitytasks for mobile networks are confidentiality that preventssensitive information from being exposing to unautho-rized entities, integrity guaranteeing that information isnot modified illegally, and authentication ensuring thatthe communicating parties are who they say they are. Onthe other hand, privacy becomes a high priority to addressgrowing concern and privacy legislation such as the Gen-eral Data Protection Regulation (GDPR) in Europe. SomeKPIs can be applied to quantitatively measure securityand privacy, e.g., percentage of security threats that areidentified by threat identification algorithms, with whichthe effectiveness of anomaly detection can be evaluated. • Capital and operational expenditure is a critical factorto measure the affordability of mobile services, influenc-ing substantially the commercial success of a mobile sys-tem. The expenditure of a mobile operator can be dividedinto two main aspects: capital expenditure (CAPEX) thatis the cost spent to build communication infrastructureand operational expenditure (OPEX) used for mainte-nance and operation. Due to the network densification,mobile operators suffer from a pressure of high CAPEX.Meanwhile, mobile networks’ troubleshooting (systemsfailures, cyber-attacks, and performance degradations,etc.) still cannot avoid manual operations. A mobileoperator has to keep an operational group with a largenumber of network administrators with high expertise,leading to a costly OPEX that is currently three timesthat of CAPEX and keeps rising [58]. During the designof 6G, the expenditure will be a key factor to consider.To provide a quantitative performance comparison between 5Gand 6G, eight representative KPIs are visualized, as shownin Fig.4. The KPIs required to assess 5G and 6G usagescenarios and the enabling technologies that can support theimplementation of each KPI are summarized in Table II andTable V, respectively.IV. R
OADMAP AND E FFORTS
Even though discussions are ongoing within the wirelesscommunity as to whether there is any need for 6G andwhether counting the generations should be stopped at 5, a fewpioneering works on the next-generation wireless networkshave been initiated. In this section, the up-to-date advanceson 6G research from representative institutions and countriesare summarized, while a tentative roadmap of definition,specification, standardization, and regulation is projected, asdemonstrated in Fig.5. In July 2018, a focus group “
Tech-nologies for Network 2030 ” was established under ITU-T [6].This group intends to study and review existing technologies,platforms, and standards for identifying the gaps and chal-lenges towards the capabilities of networks for the year 2030
Peak Rate(Tbps) User-experience Rate (Gbps) Air-Interface Latency (ms)ReliabilityMobility (km/h)Position Accuracy (m)Connectivity Density (/km )Area Traffic Capacity(Gbps/m ) Fig. 4. Quantitative comparison of the technical requirements between 5G and6G w.r.t eight representative KPIs. The vertices of the inner polygon standsfor the KPIs for 5G, while the vertices of the outer octagon represent thatof 6G. Different dotted circles indicate quantities in an exponential mannerinstead of proportional scale, where the value in a bigger circle stands for oneorder of magnitude “better” than that of the neighboring smaller circle. Forexample, the minimal latency of 5G is defined as in comparison with . expected in 6G, amounting to 10 times better, while the peak rate of6G is envisioned to be that is 50 times over 5G. and beyond, with the emergence of novel forward-lookingscenarios such as holographic applications, Tactile Internet,multi-sense networks, and digital twin. Although it mainlyfocuses on fixed data communication networks, the vision,requirements, architecture, and novel use cases identified inthis group also has reference values for the definition of the6G mobile system. According to the empirical timeline, ITU-R section will initiate the study of 6G vision and will publishthe requirements for IMT for 2030 (as the requirementsof IMT-2020 [54] published in 2017) in the middle of the2020s, and then will step into the evaluation phase afterwards.Considering the successful accomplishments by ITU for theevolution of IMT-2000, IMT-Advanced and IMT-2020, similaractions are proposed for the evolution of IMT towards 2030and beyond. At its meeting in February 2020, ITU-R workingparty 5D decided to start study on future technology trends forthe future evolution of IMT [8]. It is planned to complete thisstudy at the meeting in June 2022. A preliminary draft reportwill be developed and will consider related information fromvarious external organizations and country/regional researchprograms. ITU-R is also responsible for organizing the worldradiocommunication conference (WRC) that governs the fre-quency assignment, being hold every three to four years. InWRC-19 held in 2019, the spectrum allocation issue for the 5Gsystem was determined. It is expected that the WRC probablyscheduled in 2023 (WRC-23) will discuss the spectrum issuesfor 6G and the spectrum allocation for 6G communicationsmay be formally decided in 2017 (WRC-27).In the early of 2019, the third generation partnership project China 6G kick-off
ITU-R
R15 R17R16
6G Study Specification
DeploymentWRC-27 allocate 6G spectrum
WRC-23 discuss 6G spectrum
WRC-19 5G spectrum allocation
Vision
Requirements
Evaluation
IMT-2030 EU FP8: Horizon 2020
ICT-20 call ICT-52 call
FP9: Horizon Europe
Japan 1 st
6G Panel
PPP Smart Network & Services
South Korea 6G planFinland 6G flagship 6G trialUS open Thz Next G AllianceFirst 6G satellite
Fig. 5. The predicted roadmap of research, definition, specification, spectrum regulation, development, and deployment for 6G mobile systems. (3GPP) has frozen the Release 15 (Rel. 15 or R15) specifi-cations, which are the first phase of 5G standards. Rel. 15mainly focuses on eMBB and provides the basis for URLLC,especially in respect of the support of low latency. In July2020, the subsequent release (i.e., Rel. 16) has been completedas the second phase of 5G standards [59]. In addition toenhancements for the existing Rel. 15 features, new featuressuch as non-public network, new radio (NR) unlicensed, NRpositioning, NR-Light, and integrated access and backhaul(IAB) have been introduced so as to fully support URLLCand industrial IoT. Currently, a more advanced version (Rel.17) is being standardized by 3GPP and is expected to becompleted in the early of 2021, in spite of a delay dueto the COVID-19 pandemic. Driven by a multitude of keystakeholders from the traditional mobile industry, a wide rangeof verticals, and the non-terrestrial industry, it is envisionedas the most versatile release in 3GPP history in terms offeatures content, including NR over non-terrestrial networks,NR beyond . , NR sidelink enhancement, networkautomation, etc. 3GPP is expected to standardize severalsubsequent releases to further evolve the 5G system, which canbe called 5G+ or 5G Evolution. According to the experiencesgot in previous generations, 6G will be a disruptive system thatcannot be developed following such a backward-compatiblemanner. In parallel, therefore, 3GPP is expected to initiate thestudy item for 6G around the year 2025, followed by the phaseof specification, to guarantee the first commercial deploymentroll-out of 6G by 2030.In October 2018, the European Commission has initiated tosponsor beyond 5G research activities by opening the ICT-20-2019 call “
5G Long Term Evolution ” under the eighthFramework Programmes for Research and Technological De-velopment (FP8) being named
Horizon 2020 . Eight projectssuch as 5G-COMPLETE [60] and 5G-CLARITY [61] havebeen selected from a total of 66 proposals and kicked off in early 2020. In its recent call ICT-52-2020 “
Smart Con-nectivity beyond 5G ”, the accepted projects selected froma high-competitive evaluation process explicitly shown thattheir ambition is to provide the early research efforts on6G. The details of ICT-20 and ICT-52 research projectsare summarized in Table III. In its upcoming research andinnovation framework program called Horizon Europe or FP9,a large number of efforts and funding will concentrate onthe research and development of 6G and will be organizedin the framework of Public Private Partnership (PPP) “
SmartNetwork & Services ”, following the successful strategy ofthe 5G Infrastructure Public Private Partnership (5G-PPP)under Horizon 2020. Furthermore, the European Commissionhas announced in February 2020 its strategy to accelerateinvestments in Europe’s “Gigabit Connectivity” including 5Gand 6G to shape Europe’s digital future [7].Besides, many countries have announced and are imple-menting ambitious plans to launch 6G research and devel-opment initiatives. In Finland, the University of Oulu be-gan ground-breaking 6G research as part of Academy ofFinland’s flagship program [9] called 6G-Enabled WirelessSmart Society and Ecosystem (6Genesis), which focuses onseveral challenging research areas including reliable near-instant unlimited wireless connectivity, distributed computingand intelligence, as well as materials and antennas to beutilized in future for circuits and devices. As early as 2016, theU.S. Defense Advanced Research Projects Agency (DARPA),along with companies from the semiconductor and defenseindustries, has initiated the joint university microelectronicproject (JUMP), among which the center for converged
THz communications and sensing seeks to develop technologiesfor a future cellular infrastructure. In March 2019, the USspectrum regulator - the Federal Communications Commission(FCC) announced to open up experimental licences for theuse of frequencies between
95 GHz and for 6G and TABLE IIIS
UMMARY OF EU BEYOND -5G
AND RESEARCH PROJECTS
Call Acronym Project Title Major Research Topics
ICT-20 5G-CLARITY Beyond 5G multi-tenant private networks integrating Cellular, WiFi, and LiFi, Poweredby ARtificial Intelligence and Intent Based PolicY Private networks, AI-driven network automa-tion, intent-based network5G-COMPLETE A unified network, Computational and stOrage resource Management framework targetingend-to-end Performance optimization for secure 5G muLti-tEchnology and multi-TenancyEnvironments Computing-storage-network convergence, ar-chitecture, post-quantum cryptosystem, fiber-wireless fronthaul5G-ZORRO Zero-touch security and trust for ubiquitous computing and connectivity in 5G networks Security, privacy, distributed ledge technology(DLT), zero-touch automation, E2E networkslicingARIADNE Artificial Intelligence Aided D-band Network for 5G Long Term Evolution D-band, metasurfaces, AI-based managementINSPIRE-5G+ INtelligent Security and PervasIve tRust for 5G and Beyond Trusted multi-tenancy, security, AI, blockchainLOCUS LOCalization and analytics on-demand embedded in the 5G ecosystem, for Ubiquitousvertical applicationS Localization and analytics, location-as-a-serviceMonB5G Distributed management of Network Slices in beyond 5G Network slice management, zero-touch automa-tion, AI-assisted securityTERAWAY Terahertz technology for ultra-broadband and ultra-wideband operation of backhaul andfronthaul links in systems with SDN management of network and radio resources THz, photonics-defined transceiver, bachhauland fronthaul, network and resource manage-mentICT-52 6G BRAINS Bring Reinforcement-learning Into Radio Light Network for Massive Connections THz, OWC, AI, 3D SLAM, D2D cell-free net-work, reinforcement learningAI@EDGE A secure and reusable Artificial Intelligence platform for Edge computing in beyond 5GNetworks AI for network automation, AI-enabled networkapplications, edge computing, securityDAEMON Network intelligence for aDAptive and sElf-Learning MObile Networks Network intelligence, AI, E2E architectureDEDICAT 6G Dynamic coverage Extension and Distributed Intelligence for human Centric applicationswith assured security, privacy and trust: from 5G to 6G Distributed intelligence, security and privacy,AI, blockchain, smart connectivityHexa-X A flagship for B5G/6G vision and intelligent fabric of technology enablers connectinghuman, physical, and digital worlds High frequency, localization and sensing, con-nected intelligence, AI-driven air interface, 6GarchitectureMARSAL Machine learning-based, networking and computing infrastructure resource managementof 5G and beyond intelligent networks Optical-wireless convergence, fixed-mobile con-vergence, distributed cell-free, O-RAN, AI,blockchain, secured multi-tenant slicingREINDEER REsilient INteractive applications through hyper Diversity in Energy Efficient Ra-dioWeaves technology Intelligent surfaces, cell-free wireless access,distributed radio, computing, and storage, chan-nel measurementRISE-6G Reconfigurable Intelligent Sustainable Environments for 6G Wireless Networks RIS, architecture and operation for multipleRISs, radio propagation modelingTeraFlow Secured autonomic traffic management for a Tera of SDN flows SDN, DLT, ML-based security, cloud-native arc-tecture beyond. In October 2020, the Alliance for TelecommunicationsIndustry Solutions (ATIS) announced the launch of the “
NextG Alliance ” [62], an industry initiative that aims to advanceNorth American mobile technology leadership in 6G over thenext decade. Its ambition it to encompass the full lifecycle of6G research and development, manufacturing, standardization,and market readiness. The founding members include AT&T,T-Mobile, Verizon, Qualcomm, Ericsson, Nokia, Apple, Sam-sung, Google, Facebook, Microsoft, etc. In November 2019,China has officially kicked off the 6G technology research anddevelopment works coordinated by the Ministry of Scienceand Technology, together with five other ministries or nationalinstitutions. A promotion working group from governmentthat is in charge of management and coordination, and anoverall expert group that is composed of 37 experts fromuniversities, research institutes, and industry were establishedat this event. Later, it was announced that China aims toform 6G overall development ideas by the end of 2020. InNovember 2020, China launched what it claimed is the first 6Gexperimental satellite to test communications from space usinghigh-frequency terahertz spectrum. In early 2020, the Japanesegovernment set up a dedicated panel including representativesfrom the private sector and academia to discuss technologicaldevelopment, potential use cases, and policy. Japan reportedly intends to dedicate around $ billion to encourage private-sector research and development for 6G technology. In late2020, the government of South Korea has confirmed a planto carry out a 6G trial in 2026 and is expected to spendapproximately $ million over the course of five years todevelop 6G technology. The trial aims to achieve indata transmission speeds and latency reduction to one-tenthof current 5G services. The government will initially push fortasks in six key areas (hyper-performance, hyper-bandwidth,hyper-precision, hyper-space, hyper-intelligence, and hyper-trust) to preemptively secure next-generation technology.V. T ECHNOLOGICAL E NABLERS
To well support disruptive use cases and applications, ad-vanced technologies on transmission, networking, and com-puting would be developed and then applied in the 6Gsystem. This section provides a complete view of potential6G technological enablers, which are categorized into severalgroups: new spectrum consisting of mmWave,
THz commu-nications, VLC, OWC, and DSM, new networking that coverssoftwarization and virtualization, RAN slicing, O-RAN, andpost-quantum security, new air interface including massiveMIMO, IRS, CoMP, cell-free massive MIMO, and new mod-ulation techniques, new architecture providing 3D coverage by means of integrating large-scale satellite constellation,HAP, and UAV with traditional terrestrial networks, and newparadigm empowered by the convergence of communication,computing, and storage resources, as well as the integrationof AI, blockchain, digital twin, and mobile networks. Theprinciple, advantages, challenges, and open research issues foreach identified technology are introduced. A. New Spectrum
Next generation cellular networks provide a good capabilityof heterogeneous radio access technology (RAT), where thelegacy RAT with low radio frequencies and the line-of-sight(LOS)-dependent RATs (
THz , VLC, and OWC) can co-existwell.
THz , VLC, and OWC may construct a new layerin the hierarchical RAN architecture (e.g., picocells), whereheterogeneous cells with different RAT are overlaying on eachother. The ideology is similar to the introduction of mmWavein the 5G networks.
1) Millimeter Wave
The mmWave technology has been introduced by the 5Gnew radio, and believed to remain as an essential componentin future 6G networks. Compared to legacy RF technologiesworking below , it significantly broadens the availablebandwidth with new carrier frequencies up to
300 GHz . Sucha huge new bandwidth, as Shannon’s theorem reveals, willinflate the radio channel capacity and quench the imminentthirsty for higher data rate. Meanwhile, the shorter wavelengthalso leads to smaller antenna size. This not only improves theportability and integration level of device, but also allows toincrease the dimension of antenna arrays and therewith narrowthe beams [63], which is beneficial to specific applicationssuch like detection radars and physical layer security. Fur-thermore, the atmospheric and molecular absorption exhibithighly variant characteristics at different frequencies across themmWave band, providing potential for diverse use cases. Onthe one hand, low attenuation can be observed at some specialbands such as
35 GHz ,
94 GHz ,
140 GHz , and
220 GHz ,making long-distance peer-to-peer communications possible atthese frequencies; on the other hand, severe propagation lossis experienced at some “attenuation peaks” such as
60 GHz ,
120 GHz , and
180 GHz , which can be exploited by short-rangecovert networks with stringent safety requirements [63], [64].Currently, the standardization efforts in the mmWave fieldare mainly focusing on the
60 GHz band for indoor use, e.g.the ECMA-387 [65], the IEEE 802.15.3c [66], and the IEEE802.11ad [67].Accompanying to the benefits of mmWave technologies,there also come new challenges. First of all, the broad band-width in mmWave band and high transmission power canlead to severe non-linear signal distortions, which proposeshigher technical requirements for the integrated circuits thanthose for RF devices. Meanwhile, since the effective trans-mission range of mmWave, especially in the
60 GHz band, isseverely limited by the atmospheric and molecular absorption,mmWave channels are commonly dominated by the LOS path.This becomes a major drawback that is further magnified bythe poor diffraction at this short wavelength, which causes a strong blockage loss in scenarios with dense presence ofsmall-scale obstacles such as vehicles, pedestrians, or eventhe human body of user itself [68]. The high propagationloss and LOS-dependency also significantly raises the channelstate sensitivity to the mobility, i.e., the impact of fading ismuch stronger than that in the RF bands. The demand foran outstanding mobility management becomes therefore un-precedentedly high. Furthermore, in scenarios with dense linkscoexisting, especially for indoor environments, the interferenceamong different access points will be significant, interferencemanagement approaches are therefore called for [69].
2) Terahertz Communications
Despite of its current abundance in spectral redundancy,mmWave is hardly adequate to tackle down the increasingcravenness on bandwidth for another decade. Looking forwardto the 6G era, wireless technologies operating at even higherfrequencies, such as
THz or optical frequency bands, areexpected to play an important role in the next generation RAN,providing extremely high bandwidth.Similar to mmWave,
THz waves also suffer from high pathloss and therefore highly rely on directive antennas and LOSchannels while providing a very limited coverage. However,when a satisfactory LOS link is available, the high carrierfrequency brings a bandwidth that is significantly higher thanany legacy technology, which makes it possible to simultane-ously provide ultra-high performance in aspects of throughput,latency, and reliability. Moreover, compared to both mmWavesystems working at lower frequencies and wireless optical sys-tems working in higher frequency bands,
THz communicationsystems are insensitive to atmospheric effects, which eases thetasks of beamforming and beam tracking. This shapes
THz communication into a good supplementary solution in additionto the mainstream RF technologies for specific use cases,such as indoor communications and wireless backhaul; and acompetitive option for future cyber-physical applications withextreme QoS requirements, such like real-time VR/AR [70].Furthermore, the high carrier frequency also allows smallerantenna size for higher integration level. It is expected [16]that over 10 000 antennas can be embedded into a single
THz
BS to provide hundreds of super-narrow beams si-multaneously, so as to overcome the high propagation loss,and to simultaneously achieve extremely high traffic capacitytogether with massive connectivity, which assemble to unlockits applications in ultra-massive machine-type communicationssuch as Internet-of-Everything (IoE) [71].Nevertheless, while
THz outperforms mmWave in manyways, it also faces stronger technical challenges, especiallyfrom the aspect of implementing essential hardware circuits,including antennas [72], amplifiers [73], and modulators. Es-pecially, it has been since long the most critical challengefor practical deployment of
THz technologies, to efficientlymodulate baseband signals onto such high frequency carrierswith integrated circuits. To address this issue, a great effort hasbeen made over the past decade, leading to a prosperous set ofdevelopments, most of which are solid state
THz systems thatrely on frequency mixing, such as the one reported in [74].Recently, it has also been discussed to apply spatial directmodulation in
THz systems, so as to directly modulate base- TABLE IVC
ATEGORIZED KEY TECHNOLOGY ENABLERS WITH ADVANTAGES AND CHALLENGES
Category Enabler Advantages Challenges
Spectrum mmWave high bandwidth, narrow beams, high integration level severe attenuation & blockage, low rangeTHzOWC (including VLC) almost unlimited bandwidth, license-free, low cost, secu-rity, health-friendly frail MIMO gain, HW implementation, noise, loss, nonlin-earity, dispersion, pointing errorsDSM coexistence of licensed/unlicensed users all-spectrum sensing, data processing & managementNetworking NFV & SDN high flexibility, low operational cost service heterogeneity, SDN controller placement, auto net-work management and orchestration, E2E QoS controlRAN Slicing flexibility, resource efficiency, security architectural framework supporting multi-use-case verticalsO-RAN efficiency, intelligence, flexibility, dynamic lack of tech. convergence & standardization effortsPost-Quantum Security service-based E2E security AI & ML deploymentAir interface Massive MIMO high capacity, statistical multiplexing gain, high spectralefficiency, low expenditure, low energy consumption extremely-large aperture, channel prediction, intelligent en-vironment aware adaptation, holographic mMIMO, 6D po-sitioning, large-scale MIMO radarIRS, aka. RIS/SRE high MIMO gain, low implementation cost, low power rely on 3 rd party assessments, business frameworkCoMP BS-level spatial diversity, “cell-free” potential clustering, synchronization, channel estimation, backhaulNew Intell. OFDMA online MIMO precoding & resource mapping waveform design, out-of-band radiationmodulation NOMA high power & spec. efficiencies specific D2D interface for cooperative decodingArchitecture Large-scale LEO satellite ubiquitous coverage, resistance to natural disasters, integration with terrestrial networks, launching costconstellation lower channel loss and cost than GEOHAP large coverage, unobstructed, flexible deployment, lowercost, easier access to infrastructure and better channel than channel modelling, deployment, path planning, operationalaltitude, interference, energy limit, reliabilityUAV satellite, new use scenarios security, real-time demandParadigm AI Deep learning automatic featuring, prediction computational complexityFederated learning protection to data privacy communication overheads, heterogeneityTransfer learning quick model adaptation and optimization at local unification, gain measuring, dataset dissimilarityAI as a service low latency AI service for end-user at terminals new distributed AI techniques, new APIsBlock-chain immutability, decentralization, transparency, security andprivacy majority vulnerability, double-spending, transaction privacyleakage, scalability, quantum computingDigital twin improved quality of products, services, processes, devices,etc. in Industry 4.0 and IoT scalability, self-management, lack of models and method-ologies, security and privacyEdge intelligence resolves MEC issue caused by service requirement diver-sity among a massive number of users customized AI algorithms, resource management and taskschedulingCoCoCo convergence resolves timeliness and resilience problems due to the cou-pling between communication, computation, and controlsystems in-loop co-design methodologies & frameworks TABLE VC
ATEGORIZED KEY TECHNOLOGY ENABLERS WITH IMPACT ON
KPI S KPI P ea kd a t a r a t e U s e r- e xp e r i e n ce dd a t a r a t e L a t e n c y M ob ilit y C onn ec ti ond e n s it y N e t w o r k e n e r gy e f fi c i e n c y P ea k s p ec t r a l e f fi c i e n c y A r ea t r a f fi cca p ac it y R e li a b ilit y S i gn a l b a nd w i d t h P o s iti on i ng acc u r ac y C ov e r a g e T i m e li n e ss S ec u r it y a ndp r i v ac y C A P E X a nd O P E X Category Enabler
Spectrum mmWave ⭐ ⭐ ✓ ✓ ⭐ ⭐ ⭐
THz ⭐ ⭐ ✓ ✓ ✓ ⭐ ⭐ ⭐
OWC (incl. VLC) ⭐ ⭐ ✓ ✓ ⭐ ⭐ ⭐
DSM ✓ ⭐ ✓ ✓
Networking NFV & SDN ✓ ✓ ⭐
RAN Slicing ✓ ✓ ✓ ⭐ ⭐
O-RAN ⭐ Post-Quantum Security ✓ ⭐
Air interface Massive MIMO ⭐ ⭐ ✓ ⭐ ✓ ⭐
IRS, aka. RIS/SRE ✓ ⭐ ⭐ ✓ ✓ ⭐
CoMP ✓ ✓ ✓ ✓ ✓ ⭐ ✓ ✓
New modulation Intell. OFDMA ⭐ ⭐ ✓ ✓
NOMA ⭐ ✓ ⭐ ⭐ ⭐ ✓ ✓
Architecture Large-scale LEO satellite constellation ✓ ⭐ ⭐
HAP ✓ ⭐ ⭐
UAV ✓ ⭐ ⭐
Paradigm AI Deep learning ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
Federated learning ⭐ Transfer learning ⭐ ✓
AI as a service ⭐ Block-chain ⭐ Digital twin ✓ ⭐
Edge intelligence ✓ ⭐ ⭐ ✓ ✓ ✓
CoCoCo convergence ⭐ ⭐ ⭐
Legend ✓ : Generic/weak impact ⭐ : Specialized/critical impact7 band signals to THz band without any intermediate frequencystage.
3) Visible Light Communications
VLC works in the frequency range of
400 THz to
800 THz .Differing from the RF technologies in lower
THz range thatuse antennas, VLC relies on illumination sources – espe-cially light-emitting diodes (LEDs) – and image-sensor orphotodiode arrays to implement the transceivers. With thesetransceivers, a high bandwidth can be easily achieved with lowpower consumption (
100 mW for
10 Mbps to
100 Mbps ) with-out generating electromagnetic or radio interference [75]. Thegood power efficiency, the long lifetime (up to 10 years) andlow cost of mainstream LEDs, in addition to the unlicensedaccess to spectrum, makes VLC an attractive solution for usecases sensitive to battery life and access cost, such like massiveIoT and wireless sensor network (WSN). Moreover, VLC alsoexhibits better propagation performance than RF technologiesdo in some non-terrestrial scenarios, such as aerospace andunderwater, which can be important part of the future 6Gecosystem, as we will introduce later in Sec. V-D.Compared to RF, the MIMO gain in VLC, especially inindoor scenarios, is very frail. This roots in the high coherenceamong the propagation paths, i.e. the low spatial diversity.Though this coherence can be somehow reduced by usingspaced LED arrays [76], MIMO-VLC is also challenged by thedesign and implementation of receivers: non-imaging receiversare extremely sensitive to their spatial alignments with thetransmitters, while imaging receivers are not applicable incost-critical use cases for their high prices [77]. Therefore,there has been so far no MIMO method standardized into themainstream VLC physical layer of IEEE 802.15.7, despite ofthe persistent efforts made in academia since a decade [78],[79], [80]. Therefore, the beamforming in VLC, differingfrom the MIMO-based RF beamforming, is implemented bya special optical device known as spatial light modulator(SLM) [81].Similar to mmWave and
THz technologies, VLC also relieson LOS channels, since it has neither ability to penetrate, norsufficient diffraction to bypass common obstacles. Meanwhile,due to the concerns about adjacent cell interference and almostubiquitous environment light noise, VLC systems generally re-quire directive antennas with narrow beams. These facts makeVLC systems highly sensitive to the position and mobilityof users, leading to a high requirement of beam tracking.On the other hand, this feature can be also exploited foradvantages in certain use scenarios, such like better accuracyin indoor positioning [82], and lower interference in vehicularcommunications [83].Another key technical challenge for VLC roots in the openand unregulated (to be more specific, unregulatable ) accessto visible light spectrum, which implies a higher security riskand calls for a more stringent security requirement in VLCsystems, when compared to legacy cellular systems in licensedRF bands. Regarding this, physical layer security has beenextensively investigated as a promising solution [84].
4) Optical Wireless Communications
OWC points to wireless communications [85] that useinfrared (IR), visible light, or ultraviolet (UV) as transmission medium. It is a promising complementary technology fortraditional wireless communications operating over RF bands.OWC systems operating in the visible band are commonlyreferred to as VLC, which attracts much attention recently andis discussed separately in Sec. V-A3. The optical band canprovide almost unlimited bandwidth without the permissionfrom the regulators worldwide. It can be applied to realizehigh-speed access at low cost thanks to the availability ofoptical emitters and detectors. Since the IR and UV waveshave a similar behavior as the visible light, the security risksand interference can be significantly confined and the concernabout the radio radiation to human health can be eliminated. Itis expected to have obvious advantages in deployment scenar-ios such as vehicular communications in smart transportationsystems, airplane passenger lighting, and medical machinesthat are sensitive to electromagnetic interference. Despite itsadvantage, OWC suffers from the impairments such as ambientlight noise, atmospheric loss, nonlinearity of LEDs, multi-pathdispersion, and pointing errors [86].In OWC, LED or laser diode (LD) is applied to convertan electrical signal to an optical signal at the transmitter andthe receiver uses a photodiode (PD) to convert the opticalsignal into electrical current. The information is conveyedby modulating the intensity of optical pulse simply throughwidely-used scheme such as on-off keying or pulse-positionmodulation, as well as advanced multi-carrier schemes [87]such as OFDM to get higher transmission rate. To supportmultiple users in a single optical access point, OWC canapply not only typical electrical multiplexing technologiessuch as time-division, frequency-division, and code-divisionmulti-access, but also optical multiplexing such as wavelength-division multi-access. Optical MIMO technology [88] is alsoimplemented in OWC, where multiple LEDs and multiple PDsare applied, in contrast to the multiple antennas in a typicalMIMO system operating in the RF band.The optical system applying image sensors to detect theoptical pulse also called optical camera system. The imaginesensor can convert the optical signal into the electrical signal,which has the advantage of easier implementation due tothe wide spread of camera-embedded smart phones. On theother hand, terrestrial point-to-point OWC also known asfree-space optical (FSO) communications [89] take place atthe near IR band. Using high-power high-concentrated laserbeam at the transmitter, the FSO system can achieve highdata rate, i.e.,
10 Gbps per wavelength, over long-distance(up to
10 000 km ). It offers a cost-effective solution for thebackhaul bottleneck in terrestrial networks, enables crosslinksamong space, air, and groud platforms, and facilitates high-capacity inter-satellite links for the emerging LEO satelliteconstellation. Furthermore, there has also been a growinginterest on ultraviolet communication [90] as a result of recentprogress in solid state optical transmitter and detector for non-LOS UV communications that offer broad coverage and highsecurity.
5) Dynamic Spectrum Management
Alongside the continuous mining of unused spectrum atever-higher frequencies, there is a second approach towardsour vision of bandwidth prosperity in 6G: to improve the radio resource utilization rate by DSM.The idea of DSM dates back to the well-known listen-before-talk (LBT) protocol applied in IEEE 802.11, whichtreats all users equally in a contention-based control of accessto the spectrum, and one can exploit a band only when itis not occupied by the others. In the unlicensed industrial,scientific and medical (ISM) band, LBT has demonstrated agreat success in collision and interference control. Meanwhile,in the licensed spectrum, as reported by the FCC of the U.S., itis the under-utilization of spectrum caused by regulated access“ a more significant problem than the physical scarcity of spec-trum ” [91]. This fact has raised intense research interest on thetopic of LBT-like dynamic spectrum sharing among varioussystems with heterogeneous RATs and different priorities toaccess licensed/unlicensed bands. Driven by the successfuldevelopment of software-defined radio technologies, theseresearch efforts gave birth to the technology of cognitive radio(CR) [92], which became rapidly mature in the first decade ofthis century. Since the LTE era, it has become a distinguishedtopic in the field of wireless networks to study the DSM incoexistence of licensed cellular systems and unlicensed ISM-band technologies [93].Regarding the future 6G systems, the demand for DSMis becoming unprecedentedly imperative. On the one hand,radio access to ISM bands (especially the IEEE 802.11 bands)is becoming nowadays almost a standard functionality ofmainstream cellular terminals, making it a universal solution toprovide extra network capacity in scenarios with dense users.On the other hand, since it is impossible to reserve the broadbands of 6G new spectrum for licensed use only (saliently thevisible light spectrum), 6G system is foreseen to suffer in theunlicensed part of its spectrum from the ubiquitous existenceof interference by other systems and environmental noises,which are highly dynamic and environment-dependent. 6Gsystems therefore must be able to dynamically and cognitivelyselect the most appropriate operating band with respect to theinstantaneous situation.There are numerous technical challenges that 6G DSMis facing. In perspective of the hardware implementation, itis mainly troubled by the broadness of 6G new spectrumthat leads to a difficulty in designing transceivers capable ofdynamic all-spectrum sensing [94]. The 6G front-end mustbe capable to carry out a rapid and power-efficient spectrumsensing across the ultra-wide 6G bands, so as to enable anonline radio environment cognition and a timely adaptation tospectrum access. On the system level, for better efficiency andsafety of the DSM, the physical layer CR based on spectrumsensing shall be further completed by an awareness of cyber-physical level context information, in order to obtain a deeperunderstanding in the communication environment, includingterrain scenario, traffic pattern, local regulation, etc. This leadsto challenges in various aspects of context-awareness, rangingfrom data provisioning to data ownership [95]. B. New Networking
To deploy the aforementioned use cases utilizing the dis-cussed key enabling technologies, the network infrastructure is expected to be flexible, intelligent, and open to multi-vendorequipment and multi-tenancy. To that aim, softwarization andvirtualization of 6G network is the first and foremost step.Based on such architecture, the network slicing and resourceisolation in both core and RAN domains are considered asnovel mechanisms to decrease complexity in the managementand orchestration operations. These aspects, along with theirprivacy and security concerns, of 6G mobile networks arediscussed in this subsection.
1) Softwarization and Virtualization
Most of the network functions of the 5G core network(5GC) and next-generation RAN (NG-RAN) architecture arevirtualized using network function virtualization (NFV) tech-nology, which provides high flexibility in order to adaptto various scenarios, requirements, and use cases of nextgeneration communication systems [96]. In practice, however,NFV faces some critical challenges that are required to besolved, such as the increased amount of virtual networkfunctions (VNFs), the various requirements of the differenttenants, the resources orchestration of the VNFs in a sharedinfrastructure, the complexity in management and orchestra-tion operations, and others [97]. Therefore, the allocation ofvirtual network resources, the management and orchestrationof the VNFs in a multi-tenant environment require cutting-edge tools and promising solutions to be addressed, such as theAI techniques [58] and ML algorithms [98]. In this context,the European Telecommunication Standards Institute (ETSI)Industry Specification Group (ISG) introduced the ExperientialNetwork Intelligence (ENI) working group in order to improvethe experience of network operators and add value to theteleco provided services [99]. The main objectives of the ENIis to exploit AI and ML techniques in order to adjust theVNFs of the networked services based on dynamic changesin the requirements of the end users, the conditions of theenvironments, and the goals of the business. The currentspecification of the ENI is in its initial phase. Further workis needed to explore the deployment of the AI and ML in theNFV of the beyond 5G and 6G mobile networks.The software-defined networking (SDN) is considered asone of the most critical key enablers of 5G mobile networks,integrated with NFV capabilities, they are able to offer highflexibility in network management and achieve high effective-ness in service modularity [96]. Based on its integral role andperformance in the 5G mobile network, the SDN is goingto be indispensable for the evolution of beyond 5G and 6Gmobile networks as well and will continue to play a crucialrole within their management, orchestration, architectures,etc. [14]. Despite its numerous advantages in 5G, the SDNtechnology has a number of key research problems that areneeded to be addressed in order to thwart full exploitation of itspotentials in the future generation of communication networks.These key challenges that continue to confront SDN in thewake of 6G include, but not limited to: effectively resolvingthe optimal placement of the SDN controller in the future net-works [100], [101], efficiently maintaining the end-to-end andtimely global views of the dynamic network topology and itslinks states [102], exploiting AI/ML techniques for automatednetwork management [103] and orchestration [104], and traffic engineering with guaranteed stringent QoS requirements ofheterogeneous services [105].
2) RAN Slicing
Slicing the RAN architecture, using SDN and NFV tech-nologies, is an emerging research direction towards cloudifi-cation, virtualization, and centralization of RAN resources inbeyond 5G and 6G mobile networks [106]. The slicing-awareNG-RAN architecture helps mobile operators to efficientlyslice the entire infrastructure (or a part of it) based on therequirements of end users and vertical industries [107]. Sucha classification is also applicable in terms of slicing the NG-RAN into eMBB, URLLC, and mMTC subnets. The resourcesrequired by these three types of RAN slices are divided intophysical and virtual resources. The physical resources aremanaged by the 3GPP network slicing management system[108] whereas the virtual resources are managed by the ETSInetwork function virtualization-management and orchestration(NFV-MANO) [109].Towards an efficient RAN slicing, currently, some of theradio processing functionalities of a next-generation NodeB(gNB) in the NG-RAN are accommodated as VNFs [110],namely the centralized unit (CU) and distributed unit (DU),and some others are distributed as physical network function(PNF), namely the radio unit (RU). The VNFs run on pointsof presence (PoPs) [111], while the PNFs are implemented ondedicated hardware in the cellular network sites. In the nextgeneration of mobile networks, the full virtualization of CUand DU, and the partial/full virtualization of RU, can leadto a number of advantages, such as increased performance ofthe RAN architecture, deployment of RAN slice subnets, de-creased network expenditure, simplified operations and man-agement of the network, etc. [112]. We, thus, firmly believethat further studies are needed to address the virtualizationof RU functionalities towards a virtualized and slicing-awareRAN of the 6G mobile networks [113].Focusing on the function split in the NG-RAN, the currentdistribution of the radio processing functions over gNB com-ponents is executed statically without taking into considerationthe type of RAN slices. When supporting a large amountRAN slices in types of eMBB, URLLC, and mMTC, theone-size-fits-all function splitting architecture in NG-RANis not efficient in terms of resource allocation and networkperformance [110]. We strongly believe that a customizedand dynamic distribution of the gNB functionalities is neededin order to satisfy the service requirements of the threeaforementioned types of RAN slices in future networks. Such adynamic distribution of gNB functionalities shall improve theutilization of physical and virtual resources, enhance the NG-RAN performance, and maintain a significant level of isolationand customization among RAN slices of different types whileconsidering the metrics of service level agreements betweenthe mobile operator and tenants [114].The NG-RAN is expected to support a massive amount ofRAN slice subnets. Each type of RAN slice subnet fulfillsthe service requirements of a singe type of use case of asingle tenant. Nevertheless, there is a large number of verticalindustries – such as automobile, manufacturing, power grid,and others – which are consisting of multiple use cases [112]. Providing RAN slice subnets for multiple use cases consistingof vertical industries is a crucial research problem that isneeded to be addressed in the next generation of mobilenetworks. One of the crucial parts of this research problemis to design an extensive architectural framework for the 6GRAN domain in order to support the RAN slice subnets ofmulti-use-case verticals. This management and orchestrationframework shall effectively manage the CU, DU, and RU ofper-vertical per-use-case RAN slices in 6G RAN using AI andML.
3) Open-RAN
The key concepts of O-RAN, including its vision, architec-ture, interfaces, technologies, objectives, and other importantaspects, were introduced for the first time by the O-RANalliance in a white paper [115]. The O-RAN alliance hasthen further studied the use cases leveraging the O-RANarchitecture to demonstrate its capability in real time behaviorin [116]. The main objective of the openness and intelligencein RAN architecture is to build a radio network that is resourceefficient, cost effective, software-driven, virtualized, slicing-aware, centralized, open source, open hardware, intelligent,and therefore more flexible and dynamic than any previousgeneration of mobile networks. To do so, the research commu-nity has introduced the utilization of AI and ML techniqueson every single layer of the RAN architecture to fulfill therequirements of dense network edge in beyond 5G and 6Gmobile communication systems.By opening up the RAN from a singe vendor environmentto a standardized, open, multi-vendor, and ML and AI poweredhierarchical controller structure, it allows third parties and mo-bile operators to dynamically deploy innovative applicationsand emerging services that cannot be deployed or supportedin legacy RAN architectures. In addition, the O-RAN isbuilt upon the NFV-MANO reference architecture proposedby ETSI, which deploys commercial off-the-shelf hardwarecomponents, virtualization techniques, and software pieces.The virtual machines abstracted (or virtualized) from the un-derlying physical resources are easily created, deployed, con-figured, and decommissioned. Such a virtualized environmentand virtual resources, therefore, do not only bring flexibility tothe O-RAN architecture, but also decrease the CAPEX/OPEXand energy consumption towards 6G communication networks.Despite the flexibility and interoperability that O-RANoffers to mobile operators, it also has a number of keyproblems that require further research efforts for its fullrealization in future mobile networks, such as the convergenceof different vendors’ technologies and various operators onthe same platform, the harmonization of different managementand orchestration frameworks to deliver enhanced QoE, lackedstandards for the validation and troubleshooting of perfor-mance issues related to the network, and others. To overcomethese challenges, researchers from industry and academia arealso expected to take part in theoretical analysis and practicalroll-outs of this technology towards an open and intelligentRAN for 6G mobile networks.
4) Post-Quantum Security
In 5G communication systems, security and privacy are con-sidered as the most critical components for business continuity. This issue has even been raised to the stage of internationalpolitics, for example, some countries are proposing sanctionsto ban 5G hardware and software from certain vendors, claim-ing “to protect their networks and citizens”. Focusing on thetechnical aspect of the 5G security, together with user equip-ment, the rise of new business and innovations such as ver-tical industries, mobile virtual network operators, and multi-tenancy, have put a burden on the commercial deployment of5G networks. For instance, mMTC types of communicationservices require lightweight security components while eMBBand URLLC types of communication services demand highefficient security schemes. Another example is multi-tenantaspect, which implies the lack of a central authentication serverso that the subscribers’ identities must be confirmed in eithera decentralised or a collaborative fashion. It is envisioned that6G systems will encounter more challenging security problemsover current 5G systems. Many cutting-edge mechanisms areunder exploration to meet the requirement of high securityand privacy in the next-generation networks, such as E2Esecurity, distributed authentication, and deep learning-basedintrusion detection. To ensure the E2E security for 6G, thedeployment of the AI techniques can play a significant rolein the design, implementation, and optimization of securityprotocols in order to protect network, user equipment, andvertical industries from unauthorized access and threats. Toallow for trustworthy among communication participants, dis-tributed authentication relevant to users authenticating againstgNB, and among network functions (RU, DU, and CU), willbe designed by leveraging blockchain technology.In addition to conventional threats, the rise of quantumcomputing imposes a big challenge on network security.The cryptosystems used today can be divided into two cat-egories: symmetric and asymmetric [117]. The former sharesa common secret key between two communicating parties,and a message is encrypted at the sender and is decryptedat the receiver using this key. An example of symmetriccryptography that is widely used today is advanced encryptionstandard (AES), which has been standardized in 2001 byNational Institute of Standards and Technology (NIST) forconfidentiality and integrity. The process of an exhaustivesearch for all possible keys can be substantially accelerated byGrover’s algorithm, making such cryptosystems insecure oncequantum computers come. In an asymmetric cryptosystem, apublic key is applied to encrypt messages by anybody whileonly the owner of the corresponding private key can decryptcipher-texts. The public key schemes are also employed for theimplementation of digital signature, where a signature is gener-ated from the private key while everyone can utilize the publickey to validate this signature. Current asymmetric cryptogra-phy schemes such as Rivest-Shamir-Adleman (RSA), ellipticcurve cryptosystem (ECC), and digital signature algorithm(DSA) are based on the hardness of solving some number-theoretic problems such as integer factorization and discretelogarithms. However, mathematician Peter Shor [118] revealedthat quantum computers can solve such problems efficiently,which makes all these public-key schemes completely broken.It is still unclear when practical quantum computers willbe available, but recent advances in quantum technologies demonstrate the urgency of exploring post-quantum securityfor communication networks. Since 6G networks will bedeployed around 2030 and will last for several decades, long-term threats arising from quantum computing could be seri-ously taken into account during the design and implementationof 6G systems. Consequently, the research and developmentof quantum-resistant cryptographic algorithms and technolo-gies, also called post-quantum cryptography, which are secureagainst both quantum and classical computers play a vital rolefor the success of 6G. According to the initial recommendationof NIST [119], the cryptographic schemes based on lattices,codes, hash, and multivariate polynomials could be usable inthe quantum era.Moreover, another quantum technology called quantumcommunication [120] can significantly enhance the securitylevel of data transmission, which might have application poten-tial in 6G networks. In terms of the laws of quantum physics, ifan adversary eavesdropper measures the state of superpositionfrom particles, typically photons of light for transmittingdata along optical fibers, their super-fragile quantum state“collapses” to either 1 or 0. Since a single particle carryingqubits is inseparable, the eavesdropper cannot replicate it.It means that the eavesdropper can’t tamper with the qubitswithout leaving behind a telltale sign of the activity. In theory,quantum communication could provide absolute security andoffer new solutions to a high level of security that traditionalcommunication systems are unable to implement [121].
C. New Air Interface
The union of OFDM and small-scale active MIMO antennaarrays has ruled the world of cellular radio access networkover the entire era of 4G, and is still continuously showing itsdominance in recent progresses of 5G. However, the grandiosemarch towards ever-higher carrier frequency, as we haveseen in Sec. V-A, is squeezing the last drop of technicalpotential from this air interface. Facing new challenges suchas high propagation loss and low NLOS path diversity, variousemerging technologies are expected to play their key roles inthe evolution towards the next generation air interface, whichshall be capable to fully exploit the advantages of 6G newspectrum and support future use cases with extreme perfor-mance requirements. This evolution is primarily expected tomake several significant shifts and extensions by means ofMIMO: from small-scale to massive, from active antenna topassive reflective surface, from physical layer to network layer.New modulation and multiplexing schemes, as complements,are also arising on the horizon of the next decade.
1) Massive MIMO
In legacy cellular networks the MIMO is divided into twotypes: the point-to-point MIMO and the multi-user MIMO.In the former, multiple antennas are installed in both userequipment and base station, however a single user equipmentis served at a single time. In the latter, an antenna array isinstalled in the base station which provides connection tomany user equipment under its respective coverage area. Inorder to further enhance user experience, increase throughput,and scale up the statistical multiplexing gain, the concept of massive MIMO was introduced in order to address theshortcomings of conventional multi-user MIMO [96]. Sincethen, the massive MIMO has been considering one of the keyenablers of the legacy wireless communication systems. Inaddition, the massive MIMO is also expected to provide asignificant increase in the system capacity, higher statisticalmultiplexing gain, spectral efficiency, lower CAPEX/OPEX,decreased energy consumption, and many other advantages inbeyond 5G and 6G cellular networks.To commercially deploy massive MIMO, many operatorshave configured base stations with 64 fully digital transceiverchains which have proved its realization in the 5G mobilenetworks [122]. These rollouts proved that limitations due topilot contamination have addressed and for a better spectralefficiency the relevant signal processing methods have beendeveloped and deployed. To pave the way towards the realiza-tion of massive MIMO in beyond 5G and 6G mobile networks,the authors in [122] and [123] have outlined a number ofresearch challenges including the (i) deployment of extremelylarge aperture arrays; (ii) limitation in channel prediction; (iii) implementation of intelligent environment aware adapta-tion; (iv) fundamental limits of wireless communication withholographic Massive MIMO; (v) six-dimensional positioning;and (vi) large-scale MIMO radar. These research problemsgive a chance to researchers working in academia, industry,and standardization organizations to concentrate their attentiontowards further improvement in the realization of massiveMIMO in next generation of communication networks.
2) Intelligent Reflecting Surfaces
While releasing a significant bandwidth to support highthroughput, the use of high frequency bands over
10 GHz also introduces new challenges, such as higher propagationloss, lower diffraction and more blockage. In the frequencyrange of mmWave, massive MIMO has been proven effectivein realizing active beamforming to provide high antenna gainfor overcoming the channel loss. Nevertheless, its capabilitycan be insufficient for the future 6G new spectrum, as we havediscussed earlier in Sec. V-A3. Among all potential candidatesolutions to enhance current beamforming approaches, thetechnology of IRS has been widely considered promising for6G mobile networks.The so-called IRS, a.k.a. reconfigurable intelligent surfaces(RIS) [124], is assembled by a category of programmable andreconfigurable material sheets that are capable of adaptivelymodifying their radio reflecting characteristics. When attachedto environmental surfaces, e.g. walls, glass, ceilings, etc.,IRS enables to convert parts of the wireless environmentinto smart reconfigurable reflectors, known as smart radioenvironment (SRE) [125], and therewith to exploit them fora passive beamforming that can significantly improve thechannel gain, at low costs of implementation and powerconsumption in comparison to active massive MIMO antennaarrays. Moreover, unlike antenna arrays that must be compactenough for integration, SREs are implemented on large-sizesurfaces apart from the UEs, making it easier for them torealize accurate beamforming with ultra-narrow beams, whichare essential for some applications such like physical layersecurity. Furthermore, unlike active mMIMO antenna arrays that must be specifically implemented for every individualRAT, the passive reflection mechanism that IRS is relyingon works almost universal for all RF and optical frequencies,which is especially cost beneficial for the 6G systems thatwork in an ultra broad spectrum.Though IRS is showing a great technical competitivenessin context of the 6G new spectrum, it still lacks maturetechniques for accurate modeling and estimation of the chan-nels and the surface themselves, especially in the near-fieldrange. Moreover, a commercial deployment is only possibleafter addressing the business concern, that IRS relies onexternal assessments such like buildings that do not belongto the MNOs. Therefore, it calls for a thoughtful design andstandardization of framework providing essential interfaces,agreements, and signaling protocols, so that 6G operatorsbecome capable to widely access and exploit IRS-equippedobjects in public and private domains.
3) Coordinated Multi-Point and Cell-Free
CoMP refers to a class of technologies that allow multipleaccess points to jointly serve multiple mobile stations, sothat a network layer MIMO can be realized to increase thespatial diversity on the top of classical physical layer MIMOapproaches. Therefore, it is also known as network MIMO orcooperative MIMO. CoMP was initially introduced by 3GPPin its Release 11 [126] for LTE Advanced systems. With recentevidences of its potentials in mitigating downlink inter-cellinterference and joint user detection in uplink, CoMP is ex-pected to play an important role in 5G [127]. In the upcoming6G era, regarding the new spectrum over
10 GHz , the CoMPtechnologies that make use of base station level diversity willbecome an important complement to the traditional antenna-level spatial diversity, as the latter can be minimized by thedense blockage phenomena in high-frequency bands.Furthermore, since CoMP is generally suggesting every UEto simultaneously hold multiple links to different access points(even when they are of the same RAT), it reveals the feasibilityof a novel “cell-free” RAN architecture, where numeroussingle-antenna access points distributed over the coverage areaare connected to a central processing unit, and jointly servingall UEs by coherent transmission in a CoMP fashion [128].Recent study has shown that such cell-free massive MIMO areable to outperform traditional cellular massive MIMO whilealso reducing the fronthaul signaling [129].As a trade-off for the performance gain originated from itsnature of cooperative decoding, CoMP also has to face somekey technical challenges caused by the same reason. First ofall, the performance of CoMP highly relies on the clusteringof cooperating base stations, so an appropriate clusteringscheme must be found, which has been a focus of researchover the past years [130]. Second, the synchronization amongcooperating base stations have to be accomplished withoutinter-carrier and inter-symbol interference [131]. The channelestimation and equalization also must be carried out in a inter-BS-coherent manner, which greatly increases the computationcomplexity.
4) New Modulation
The 3GPP LTE-Advanced (LTE-A) networks are imple-mented based on orthogonal frequency division multiple ac- cess (OFDMA) [132], which is a typical instance of orthogonalmultiple access (OMA) technologies prohibiting physical re-source block (PRB) sharing by multiple users. In comparisonto CDMA, which is deployed in 3G systems, OFDMA showsa conspicuous superiority in combating multi-path fading bysimple and robust carrier-based channel equalization. Fur-thermore, when combined with MIMO, OFDMA is capableto overwhelmingly outperform CDMA in spectral efficiency.Nevertheless, the full performance of MIMO-OFDM highlyrelies on the MIMO precoding and resource mapping, whichhave to be precisely adapted to the channel condition toachieve the optimum. As the dimension of MIMO increase,from up to × in LTE-A gradually to over × massiveMIMO, and eventually to the future ultra-massive MIMO (e.g. × ), the complexity of MIMO-OFDM adaptation isdramatically increasing. Meanwhile, in response to the demandof supporting higher mobility – which implies higher fadingdynamics – the computation latency constraint to this onlineadaptation procedure is also becoming more and more strict.To cope with these emerging challenges, a new architectureof AI-driven MIMO-OFDM transceivers has been proposedtowards future 6G systems, which relies on AI techniques toefficiently solve the problem of online MIMO precoding andresource mapping [16].Alongside with a further evolution in OFDMA technologies,non-orthogonal multiple access (NOMA) technologies are alsowidely considered as an answer to the new challenges inthe next generation of mobile communication networks. Incontrast to OMA, NOMA allow multiple users to reuse thesame PRB, which can be achieved by complex inter-userinterference cancellation. NOMA approaches can be generallydivided into two categories, namely the power-domain (PD)NOMA and the code-domain NOMA. While PD-NOMA hasbeen recently proposed and is attracting a lot of researchinterest in context of 5G [133], code-domain NOMA has alonger history in legacy systems (e.g. CDMA in 3G), andprovides an alternative to PD-NOMA with numerous varia-tions, such as trellis-coded multiple access (TCMA) [134],interleave division multiple access (IDMA) [135], multi-user shared access (MUSA) [136], pattern-division multi-ple access (PDMA) [137], and sparse-code multiple access(SCMA) [138].Since the beyond 5G and the 6G networks are expectedto simultaneously manage a massive amount of links, e.g. inthe mMTC scenario and its future extensions, NOMA solu-tions appear promising since they provide higher bandwidthefficiency than OMA approaches. Recent studies have alsodemonstrated that NOMA can be effectively exploited in newspectrum, including mmWave, THz , and optical frequencies.Additionally, when deployed together with CoMP, NOMA hasbeen proven as capable to outperform CoMP-OMA in bothpower efficiency and spectral efficiency.Being completely based on successive interference cancel-lation, NOMA has a significantly higher complexity in itsreceiver design than OMA, which increases in polynomialor even exponential order along with the number of users.Especially, in some scenarios that require cooperative decodingacross different UEs, specific D2D interfaces must be reserved for this functionality, and security/trust concerns shall be takeninto account, to enable the deployment of NOMA in 6G.
D. New Architecture
So far, all legacy and existing cellular systems have beendesigned to substantially rely on terrestrial base stations. Formarine, oceanic, as well as wild terrestrial areas, which areimpossible or economically challenging to be covered byterrestrial cellular networks, satellites have been since longthe most common communication solution. Aiming at a bettercoverage rate, deployment of non-terrestrial infrastructures aspart of the 6G network is being treated as an emerging topic,known as the integrated space and terrestrial network (ISTN).An ISTN is expected to consist of three layers: the ground-based layer constructed by terrestrial base stations, the airbornelayer empowered by HAP and UAV, and the spaceborne layerimplemented by satellites. An envision of the architecture forthe 6G systems, demonstrating representative use cases andkey technological enablers, is illustrated in Fig.3.
1) Large-Scale Satellite Constellation
Until now, the coverage of terrestrial networks has onlyreached a small portion of the whole surface of the globe.First, it is technically impossible to install terrestrial basestations for offering large-scale coverage in ocean and desert[51]. Second, it is difficult to cover extreme topographies,e.g., high mountain area, valley, and cliff, while it is notcost-efficient to use a terrestrial network to provide servicesfor sparsely-populated areas. Additionally, terrestrial networksare vulnerable to natural disasters such as earthquake, flood,hurricane, and tsunami, where there is a vital demand ofcommunications but the infrastructure is destroyed or in outageof service. With the expansion of human activity, e.g., thepassengers in commercial planes and cruise ships, the demandof MBB services in uncovered areas increasingly grows. Also,the connectivity demand of IoT deployment scenarios like wildenvironmental monitoring, Offshore wind farm, and smart gridrequire wide-area ubiquitous coverage. Satellite communica-tions have been since long the most common solution forwide coverage but currently the mobile communication serviceoffered by GEO satellites is costly, low data rate, and highlatency due to the expensive cost for launching and its widearea coverage (1/3 surface of Earth per GEO satellite).The satellites in LEO [52] have some advantages overGEO satellite for providing communication services. A LEOsatellite operates in an orbit generally lower than ,which can substantially lower the latency due to the signalpropagation compared to the GEO satellite in the orbit of . Meanwhile, the propagation loss of LEO is muchsmaller, facilitating the direction connectivity to mobile andIoT devices that are strictly constraint by the battery supply.Moreover, a stationary ground terminal like an IoT devicemounted in a monitoring position may suffer from an obstaclein the line of sight from GEO. There is an early attempt toimplement a global satellite mobile communication system,i.e., the Iridium constellation [139] that became commerciallyavailable in November 1998. It consists of 66 LEO satellitesat an altitude of approximately 781 kilometers and provides mobile phone and data services over the entire Earth surface.Even though it fails due to expensive costs and lack ofdemands at that time, it is a great technological breakthrough.It still operates today and the second generation Iridium systemhas been successfully deployed last year.In recent years, the high-tech company SpaceX gains a lotof attention due to its revolutionary development of spacelaunching technologies. Its reusable rocket namely Falcon9 dramatically lower the cost of space launching, openingthe possibility for deploying large space infrastructures. InJanuary 2015, SpaceX announced its ambition called Starlink[140], utilizing a very large-scale constellation with thousandsof LEO satellites to provide global Internet access services[50]. The U.S. FCC has approved its first-stage plan tolaunch 12 000 satellites and another application for deploying30 000 additional satellites is under consideration. With theadvancement of electronic technology, the weight of eachsatellite reduces to approximately
260 kg and a compact, flat-panel design minimizes the volume, allowing for a denselaunch of 60 Starlink satellites to make full use of thecapability of Falcon 9. Each satellite becomes cheap due tothe massive production, in combination with reusable rockets,building a large-scale constellation becomes feasible fromboth commercial and technological perspectives. Since its firstlaunch in May 2019, more than 1000 satellites have beensuccessfully deployed through 17 times launches and the speedof deployment is planned to reach 120 satellites per month.In October 2020, SpaceX started to invite some early usersto join public testing and it was reported that data rate varyfrom
50 Mbit / s to
150 Mbit / s and latency from
20 ms to
40 ms can be expected. Considering its announced monthlyfee of 99 USD for active services and its steadily improvementof capacity and performance with the increasing number ofdeployed satellites, its impact on terrestrial networks shouldbe seriously taken into account. Looking forward to a futureglobal ubiquitous converge that is available anywhere andanytime, it is strongly suggested to integrate satellite networksinto the 6G network as part of it.
2) High Altitude Platform
In general, terrestrial networks and satellite communicationsare two technologies that dominate mobile communications forlong years. HAP, a quasi-stationary aerial platform operating inthe stratosphere at an altitude between
17 km to
22 km abovethe Earth’s surface represents a new alternative to providea multitude of telecommunication services in a cost-efficientway [141]. In comparison with terrestrial base stations, HAPcan cover a larger area, offer unobstructed connectivity withhigh signal arrival angle, and provide the flexibility of quickdeployment with less temporal and spatial constraints [142].Compared to satellite systems, HAP has the following advan-tages: much lower cost of implementation and deploymentdue to the avoidance of space launching, the possibility ofupgrading, repairing, and redeployment, and much shorterpropagation distance that corresponds to higher signal strengthand lower latency [143].An aerial platform can carry on-board base stations of bothterrestrial and satellite segments, providing connectivity tothe terminals of end users transparently. It can keep quasi- stationary, be redeployed, or be moved from one site to anotheron demand. This is therefore an efficient solution to improvethe coverage of terrestrial and satellite systems. The aerialplatform is not only a host of communication services. It welladapts to different applications such as high-definition mul-timedia broadcasting, remote sensing, surveillance, intelligenttransportation, and environmental monitoring. It is also appliedfor navigation and positioning, working standalone or as alocal enhancement component of Global Navigation SatelliteSystem, for a higher accuracy and better availability [144].Last but not least, it has unique value in local temporaryevents, emergence communications, and natural disaster (e.g.,earthquake, flood, and tsunami) relief, where the terrestrialinfrastructure is destroyed or the power grid is in outage ofservices.In 6G systems, the synergy among terrestrial, satellite, andHAP is worth exploring to provide ubiquitous, robust, and re-silient network infrastructure and communication connectivity.For example, using HAP to provide high-throughput backhaullinks for the small cells deployed in the sites that are hard orexpensive to provide wired links, or applying HAP to enhanceor relay the satellite signals. From the perspective of theintegrated terrestrial-HAP-satellite systems, there are severaltechnical challenges to be solved such as the power supplyof the aerial platform, the stability of antenna array, channelmodels, seamless handover, admission control, interferencemanagement, etc. To this end, extensive research on the topicssuch as 3D channel modeling [145], advanced multi-antennatechnologies [146], spectrum-awareness, dynamic spectrummanagement, and FSO [147] has been carried.
3) Unmanned Aerial Vehicle
Alongside the space satellite and HAP, UAV also play anindispensable role, as the last piece of the puzzle that fills thegap of near-Earth altitude, in the foreseen ISTN. Over the pastyears, it has been widely discussed to use UAVs in cellularnetworks as flying BSs or relays [148], [149]. Generally, itmakes a flexible mobile supplement to the fixed terrestrialgNBs and space satellites, offering a possibility to dynamicallyre-plan the RAN by flexibly deploying UAVs to differentlocations. Compared to HAPs, UAVs are deployed closer tothe ground, which not only makes them much cheaper, butalso grants them better channel gain with lower path loss.Especially, upon emergencies (e.g. in disaster reliefs or search& rescue), UAV also provides a low-cost solution of temporarywireless service delivery to inaccessible areas, such like caves,tunnels, and dilapidated buildings in earthquakes/fires, whichcannot be covered by satellites and HAPs.Furthermore, empowered by the latest achievements ofwireless power transmission, UAVs can also be exploited asmobile and automated wireless chargers [150]. Especially,with the simultaneous wireless information and power transfer(SWIPT) technologies, the missions of battery charging andinformation transmission can be accomplished in a seamlessjoint [151]. This significantly raises the feasibility of massivedeployment of battery-life-critical UEs, which is essential insome emerging use scenarios such as dense WSN. With suchrich potentials, UAVs are nowadays widely considered as anessential component of future 6G infrastructure. In addition to its irreplaceable position in the 6G networkinfrastructure, UAV is also expected to contribute to theprosperity of new use cases and emerging applications in 6G.With its well developed integration with multimedia devicessuch as video camera and microphone, UAV has since longbeen widely used in offline photographing and videographing.By nature it is promised to play a larger role in future onlinevideo streaming, and can be enabling remote sensing andmulti-sense experience when equipped with variant sensors.The high flexibility, mobility and continuously decreasing loadcost of UAVs also lead to their foreseeable deployment infuture intelligent logistic applications.
E. New Paradigm
The recent revival of AI technology spurs the discussionsof whether 6G will be an integrated system of AI andmobile networks. The 6G system is expected to support theupsurge of diversified mobile AI applications, and in turnAI will play a critical role in designing and optimizing thewireless architecture [152]. The similar trends are happeningin other fields like blockchain and digital twin, which arerecognized as strong drivers to shape the next generationmobile system. It is foreseen that 6G will transform into ahuge computer, which converges distributed communication,computing, storage, sensing, and controlling resources forprovisioning services of pervasive computing, AI, blockchain,digital twin, etc.
1) Artificial Intelligence
On the list of 6G enabling technologies, AI is recognized asthe most potential one. As mobile networks are increasinglycomplex and heterogeneous, many optimization tasks becomeintractable, offering an opportunity for advanced ML tech-niques. Categorized typically into supervised, unsupervised,and reinforcement learning, ML is being considered as apromising data-driven tool to provide computational radio andnetwork intelligence from the physical layer [153] to networkmanagement [154]. As a sub-branch of ML, deep learning[155] can mimic biological nervous systems and automati-cally extract features, extending across all three mentionedlearning paradigms. It has a wide variety of applications toagainst the big challenges in wireless communications andnetworking, being applied to form more adaptive transmission(power, precoder, coding rate, and modulation constellation)in massive MIMO [156], to enable more accurate estimationand prediction of fading channels [157], [158], to provide amore efficient RF design (pre-distortion for power amplifiercompensation, beam-forming, and crest-factor reduction), todeliver a better solution for intelligent network management[58], and to offer more efficient orchestration for mobileedge computing, networking slicing, and virtual resourcesmanagement [98].In addition to deep learning, a few cutting-edge ML tech-niques represented by federated learning and transfer learningstart showing strong potential in wireless communications.Data-driven methods always have to take into account theissue of data privacy, which limits the manner of processingcollected data. In some scenarios, distributing data is strictly prohibited and only local processing on the device where thedata was collected is allowed. Federated learning is a methodachieving the fulfillment of this requirement by processingthe raw data locally and distributing the processed data in amasked form. The mask is designed such that each of theindividual data processing expose no information, whereastheir cooperation allows for meaningful parameter adjustmentstowards a universal model. While federated learning gives amethod of training ML models from a large number of datasources without ever exposing sensitive data, it creates onlyone shared model for universal applicability. When individualadjustments of models are required for their deployment to besuccessful, transfer learning can be used as a tool enablingthese adjustments and doing so in a manner requiring a muchlower amount of data. By reusing the major part of pre-trainedmodels in a different environment and only adjusting someof the parameters, transfer learning is able to provide quickadaptations using only a low amount of local data.In addition to using AI to assist with the operation of thenetworks (i.e., AI for Networking), it is also important to usethe ubiquitous computing, connectivity, storage resources toprovide mobile AI services to end users in an AI-as-a-Serviceparadigm (i.e., Networking for AI) [14]. Principally, thisprovides deep edge resources to enable AI-based computationfor new-style terminals such as robots, smart cars, drones,and VR glasses, which demand large amount of computingresources but limited by embedded computing componentsand power supply. Such AI tasks mainly means the traditionalcomputation-intensive AI tasks, e.g., computer vision, SLAM,speech and facial recognition, natural language processing, andmotion control.
2) Blockchain
With the great success of a kind of cryptocurrency knownas Bitcoin, the blockchain technology has received enormousattention in both industry and academia [159]. A blockchainis essentially a distributed public ledger spreading across allparticipants deployed typically in a peer-to-peer network. Achain of blocks originates from the first block called thegenesis block. A new block is appended to the chain viaa hash value that is generated according to the informationof its parent block. Each block typically consists of twoparts: the block header and transaction data. In particular,the header mainly contains the following information: blockversion indicating the validation rule, the hash of its parentblock, timestamp, the number of transactions, and MerkelRootthat concatenates the hash values of all the transactions inthis block. A chain continuously grows as blockchain usersperform transactions. A miner records and packs a batch oftransactions into a block by solving a computationally difficultproblem called Proof of Work (PoW). The newly mined blockis then broadcasted to the whole blockchain network and allthe nodes join the consensus process to validate its trustfulnessand update the new block into the chain.The blockchain has the following technological advantages[160]:
Immutability : the transaction data in the blockchainis unchangeable once it is recorded since each block islinked with other blocks via the hash value. The possibilityof breaking the whole chain and modifying the content of all blocks is very limited. Decentralization : it applies theconsensus mechanisms to manage and maintain the distributedledge without the need of a centralized entity or third party.The blocks are replicated and shared over an entire blockchainnetwork, thereby avoiding the risk of single point of failure,enhancing data persistency and security, and providing flexibil-ity.
Transparency : all blockchain participants have equal rightand can access all transaction information of blockchain.
Secu-rity and privacy : the adoption of asymmetric cryptography, theinherit feature of data immutability, consensus mechanism, andanonymous addressing ensure the security, trustworthiness,and privacy of the blockchain. Despite these promising merits,scalability is a key barrier when the blockchain technology iswidely applied from the perspectives of throughput, storageand networking. Enabling technologies [161] related to thenumber of transactions in each block, block interval time, datatransmission, and data storage to realize scalable blockchainsystems are recently studied.Recently, the potential of blockchain in 5G and beyondsystems has been initially investigated in the literature [162]. Itis applied to enhance the technologies such as edge computing,NFV, network slicing, and device-to-device communications,to implement important services, e.g., the sharing of spectrumand radio resource, data storage and sharing, network virtual-ization, security and privacy, in the use case domains of smartcity, smart transportation, smart grid, smart healthcare, andUAV. On the other hand, the deployment of 5G networks canboost the application of blockchain systems. The ubiquitousconnectivity, computing, and storage resources provided bymobile networks can be employed to provide local computingpower for mobile blockchain systems [163] so as to supportsolving PoW puzzles, hashing, encryption, and consensus ex-ecution. It is envisioned that the blockchain will be convergedinto the upcoming 6G system for more flexible, secure, andefficient information infrastructure.
3) Digital Twin
Digital twin is an emerging technology and one significantuse case of 6G communication system. It refers to the logicalcopy (a.k.a., virtual object or softwarized copy) of a physicalobject [164]. The virtual representation shall reflect all thedynamics, characteristics, critical components, and importantproperties of an original physical object that operates and livesthroughout its life cycle [165]. The digital twin is followingthe life cycle of a physical twin. Therefore, its monitoring,controlling, maintenance, prediction, and optimization pro-cesses are started and ended in parallel with its respectivephysical twin. Each digital twin is linked to its respectivephysical twin through a unique key. The unique key is used toidentify the physical twin and allows to establish a bijective(one-to-one) relationship between the digital twin and its realtwin. Recently, digital twin has become the center of attentionand has attracted significant attention from the Industry 4.0,research and development community, manufacturing, andothers due to its importance in the improvement of the qualityof products, services, processes, devices, etc. in a specificcontext using AI techniques.There is a large number of industries such as manufacturingand aviation, which have been developing and commercializ- ing the digital twin in order to optimize their processes sincelast years [166]. In addition, the digital twin is also in its initialstage in healthcare and medicine fields and is expected to befully commercialized with the development and deployment of6G communication networks in the near future [167]. Despite,it is also being extensively applied in the IoT and Industry4.0 domains. In both scenarios, the AI techniques are usedto collect, analyze, and test (in different conditions) the datafrom a physical object to build its softwarized copy [168].The more information about the physical object is provided tothe AI analyzer, the more accurate and better the performanceand prediction of the virtual object will be during its life cycle[169].Towards full utilization of digital twin in 6G communicationsystem and specifically in the context of Industry 4.0 and IoT,there are still a number of very critical research problems,which are needed to be addressed from both academia andindustry. They are, including, but not limited to: dynamicallyscaling up the platform of digital twin to millions and billionsof IoT devices, the deployment of the zero-touch and self-management approaches to the devices and processes, lackof existing models and methodologies in the area of AI tovirtualize the physical object, security and privacy, and manyothers that are thoroughly addressed in [164], [165], and [169].These challenges shall be, first and foremost, explored aimingto develop more suitable digital twin solutions for a wide rangeof IoT deployment scenarios and industrial adaptations in thecoming decade.
4) Intelligent Edge Computing
Edge computing plays a significant role in increasingthe performance of network services, efficient utilization ofnetwork resources (both physical and virtual), decreasingCAPEX/OPEX of a mobile operator, and lowering networkcomplexity (both in control plane and user plane) [170]. How-ever, the existence of a large number of end users, each with adiverse set of business and technical requirements, challengesthe network operator to think on different alternatives in orderto address the existing limitations related to edge computingusing cutting-edge AI tools and modern ML methods. To thatobjective, the edge intelligence (EI) is introduced aiming tointegrate the AI and ML techniques at the edge of the mobilenetworks in order to bring automation and intelligence. TheEI is envisioned to be one of the key enabling technologies forbeyond 5G and 6G communication networks. Thanks to theincreasing number of smart portable devices, user equipment,internet of intelligent things (IoIT), and the proliferation ofintelligent services; there is a strong demand for the EI in theedge of 6G mobile networks to automate its respective tasks[113].One of the major use cases of EI can be the automationof the management and orchestration tasks of the virtualresources in NG-RAN architecture. In this use case, the EIis extended to the NG-RAN in order to automate all tasksrelated to the RAN network slice subnet management func-tion (NSSMF) and network function management functions(NFMFs) in order to lower the management and orchestrationcomplexity. To that aim, the ETSI has launched the ENI ISG toinvestigate and provides recommendations to operators [171]. In each of the use cases, including the aforementioned, theEI is constituted of a set of connected devices which areused to collect, normalize, process, and analyze the data.Subsequently, the processed data is sent back to the assistedsystems in the form of recommendations and/or orders to beexecuted in order to automate the target tasks or functionalities[171].The applications of EI in the context of vertical industrieshave also attracted the attention of both academia and indus-trial organizations. For example, the EI plays significant role inaddressing mission-critical applications and massive and crit-ical mMTC types of services in centralized, semi-centralized,and localized resource allocation scenarios. Despite, the EIalso provides energy-efficient solution which are expectedto reduce the energy consumption of the communicationnetworks. Therefore, it is considered a novel opportunity forboth operators and vertical industries in order to digitize itsapplication and businesses – using personal computing, fogcomputing, urban computing, and other mechanisms – in the6G mobile networks.Despite the aforementioned key advantages, there are stilla number of unsolved research challenges in realising EI inbeyond 5G mobile networks. It is, therefore, crucial to identifyand analyze such open research problems and seek for theirtheoretical and technical solutions. Among others, the mostprominent challenges are: data consistency on every deviceat edge, data scarcity at edge, bad adaptability of staticallytrained model, and data privacy and security. We expect thatmore research efforts are needed to completely realize EI inbeyond 5G and 6G networks upon addressing such challenges.
5) Communication-Computing-Control Convergence
Mobile edge networks provide computing and cachingcapabilities at the network edge, which makes low-latency,high-bandwidth, location-aware pervasive computing servicesa reality. With the proliferation of IoT and Tactile Internet, ahuge number of sensing devices and actuators are connectedto mobile networks. The next-generation system is envisionedto become a huge computer that would converge ubiquitouscommunication, computation, storage, sensing, and controllingas a whole to provide disruptive applications.Due to their superiority in integration and mobility overwired connections, wireless links are gradually relied bymodern and future controlling systems to close the signal loop,giving birth to the use scenario of URLLC. The spirit of systemdesign behind this concept follows the classic methodologyof control & communication independent design: it startsfrom designing the controlling component without concerningthe characteristics of communication system, where a setof communication requirements will be generated regardingthe expected controlling performance; then there follows thedesigning of wireless system, aiming at achieving the targetperformance proposed by the last stage. The KPI requirementsof URLLC, such as . reliability and
10 ms , wereformulated for a generic controlling scenario in this fashion.Nevertheless, recent studies have revealed a necessity of in-loop co-designing of communication and controlling systemstightly coupled to each other. For instance, the close-loop reli-ability of controlling system has been proven exponentially de- creasing along with the AoI over the feedback channel [172],[173]. Meanwhile, the AoI over control/feedback channels,as a communication metric, is convex about the arrival ratesof controlling command and feedback information, whichcorrespond to the sampling rate of sensors and decision rateof controller in the control system [174]. The performance ofcommunication system, is therefore limited by the design ofsensing and controlling systems.Similar issues are also to be addressed in cloud computing.While it occasionally happens that some computing taskoccupies the cloud server for long time, blocking all otherpending tasks in the waiting queue and causing a severecongestion, its source may have re-issued the same task with amore up-to-date status, making the previous task outdated andlack of utility. A preemption of the server, i.e. terminatingthe ongoing task in advance to its completion, will in thiscase help reduce the age of task and improve the quality ofcloud computing service [175]. Furthermore, it is also criticalfor reducing the AoI, to schedule the order of computingtasks from multiple applications to be offloaded to the cloud[56]. Optimal decisions of such preemption and scheduling,however, cannot be solely solved by the computing server,nor by the communication system, but only achievable in ajoint collaboration among the terminal devices, the networkcontroller, and the cloud computing server.With the dramatically increasing demand for wireless-connected industrial automation, and the irreversible trend thatnot only most mobile applications but also the mobile network-ing service itself are gradually cloudified, new approaches aretherefore required in 6G to jointly design and optimize thiscommunication-computing-control symbiosis [176].VI. C
ONCLUSIONS
This article provided a comprehensive survey on the drivers,requirements, efforts, and enablers for the next-generation mo-bile system beyond 5G. It can be concluded that the traditionalevolution of a new generation every decade will not terminateat 5G and the first 6G network is expected to be deployedin 2030 or even earlier taking into account great passionsof developing 6G from both academia and industry. 6G willaccommodate the use cases and applications introduced in 5Gsuch as IoT, Industry 4.0, virtual reality, and automatic drivingwith better quality of experience in a more cost-efficient,energy-efficient, and resource-efficient manner. Meanwhile, itwill enable unprecedented use cases that cannot be supportedby 5G, e.g., holographic-type communications, pervasive intel-ligence, and global ubiquitous connectability, as well as otherdisruptive applications that we are unable to yet imagine. Thetrend of mobile communication services expanded from onlyhuman centric to connecting also machines and things, startedwhen MTC and IoT were introduced in the age of 5G willcontinue, and Internet-of-Everything will be realized when6G comes. The 6G system has to meet extremely stringentrequirements on latency, reliability, mobility, and security, aswell as provisioning a substantial boost of coverage, peak datarate, user experienced rate, system capacity, and connectivitydensity, gaining KPIs generally to times better incomparison with 5G. It is envisioned that 6G will take unprecedented transfor-mations that will make it dramatically distinguishing with theprevious generations. That is: • It will be shifted from a radio communication networkbased on electronic technologies to a radio-optical systemtaking advantage of both electronic and photonic tech-nologies so as to exploit the abundant spectral resourcesin terahertz and visible light bands, especially in indooroptical wireless coverage, to meet the inexorable demandon higher system capacity and peak data rates. • It will become a connected intelligent platform thatmaximizes the synergy between AI and mobile networks.On the one hand, 6G will facilitate the provisioning ofover-the-air AI applications, where AI-as-a-Service is of-fered to end users through pervasive intelligence. On theother hand, AI-driven air interface, algorithms, protocols,and approaches are applied to implement highly-efficienttransmission, optimization, control, and management ofresources and networks. • With the disruptive advances in large-scale LEO satelliteconstellation, the 6G system will go beyond terrestrialnetworks and provide ubiquitous 3D coverage of thewhole surface of our planet through an integrated space-aerial-terrestrial network. • It will be a smart compute-connect entity by means ofconverging distributed communication, computing, stor-age, and big data resources, integrating sensing, localiza-tion, and controlling capabilities, and inter-working withemerging paradigms such as AI, blockchain, digital twin,quantum computing and communications. • It should be an intelligent, green, sustainable, and securesystem to fully support the informationized and intelli-gentized society in 2030 and beyond.In 1926, engineer and inventor Nikola Tesla stated that “
Whenwireless is perfectly applied the whole Earth will be convertedinto a huge brain ”. This prophecy will transform into a realitywhen 6G comes. R
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Wei Jiang (M’09–SM’19) received the Ph.D. degree in Computer Sciencefrom Beijing University of Posts and Telecommunications (BUPT) in 2008.From 2008 to 2012, he was with the 2012 Laboratory, HUAWEI Technologies.From 2012 to 2015, he was with the institute of Digital Signal Processing,University of Duisburg-Essen, Germany. Since 2015, he is a Senior Researcherwith German Research Center for Artificial Intelligence (DFKI), which is thebiggest European AI research institution and is the birthplace of “Industry 4.0”strategy. Meanwhile, he is a Senior Lecturer with University of Kaiserslautern,Germany. He is the author of three book chapters and over 60 conferenceand journal papers, holds around 30 granted patents, and participated in anumber of EU and German research projects:
ABSOLUTE ,
5G COHERENT ,
5G SELFNET , AI@EDGE , TACNET4.0 , and
KICK . He was the Guest Editorfor the Special Issue on “Computational Radio Intelligence: A Key for 6GWireless” in
ZTE Communications (December 2019). He currently serves asan Associate Editor for
IEEE Access and is a Moderator for
IEEE TechRxiv . Bin Han (M’15) received in 2009 his B.E. degree from Shanghai Jiao TongUniversity, M.Sc. in 2012 from Technical University of Darmstadt, and in2016 the Ph.D. degree from Karlsruhe Institute of Technology. Since July2016 he has been with University of Kaiserslautern as a Senior Lecturer,researching in the broad area of wireless communication and networking, withrecent special focus on B5G/6G networks, network slicing, finite blocklengthinformation theory, and information freshness. He is the author of over 30conference and journal papers, and participated in multiple EU collaborativeresearch projects.
Mohammad Asif Habibi received his B.Sc. degree in TelecommunicationEngineering from Kabul University, Afghanistan, in 2011. He obtained theM.Sc. degree in Systems Engineering and Informatics from Czech Universityof Life Sciences, The Czech Republic, in 2016. Since January 2017, hehas been working as a Research Fellow and Ph.D. Candidate at TechnischeUniversit¨at Kaiserslautern, Germany. From 2011 to 2014, he joined HUAWEI,where he was working as a Radio Access Network Engineer. His mainresearch interests include Network Slicing, Network Function Virtualization,Resource Allocation, Machine Learning, and Radio Access Network.