6G for Bridging the Digital Divide: Wireless Connectivity to Remote Areas
Abdelaali Chaoub, Marco Giordani, Brejesh Lall, Vimal Bhatia, Adrian Kliks, Luciano Mendes, Khaled Rabie, Harri Saarnisaari, Amit Singhal, Nan Zhang, Sudhir Dixit, Michele Zorzi
aa r X i v : . [ c s . N I] S e p
6G for Bridging the Digital Divide:Wireless Connectivity to Remote Areas
Abdelaali Chaoub,
Senior Member, IEEE , Marco Giordani,
Member, IEEE , Brejesh Lall,
Member, IEEE ,Vimal Bhatia,
Member, IEEE , Adrian Kliks,
Senior Member, IEEE , Luciano Mendes,Khaled Rabie,
Senior Member, IEEE , Harri Saarnisaari,
Senior Member, IEEE , Amit Singhal,
Member, IEEE ,Nan Zhang,
Member, IEEE , Sudhir Dixit,
Life Fellow, IEEE
Abstract —In telecommunications, network sustainability as arequirement is closely related to equitably serving the populationresiding at locations that can most appropriately be describedas remote. The first four generations of mobile communicationignored the remote connectivity requirements, and the fifthgeneration is addressing it as an afterthought. However, sus-tainability and its social impact are being positioned as keydrivers of sixth generation’s (6G) standardization activities. Inparticular, there has been a conscious attempt to understandthe demands of remote wireless connectivity, which has ledto a better understanding of the challenges that lie ahead.In this perspective, this article overviews the key challengesassociated with constraints on network design and deploymentto be addressed for providing broadband connectivity to ruralareas, and proposes novel approaches and solutions for bridgingthe digital divide in those regions.
This paper has been submitted to IEEE for publication. Copyright may be transferred without notice.
Index Terms —6G; remote areas; digital divide; network sus-tainability; wireless networks.
I. I
NTRODUCTION
In 2018, 55% of the global population lived in urban areas.Further, 67% of the total World’s population had a mobilesubscription, but only 3.9 billion people were using Internet,leaving 3.7 billion unconnected, with many of those living inremote or rural areas [1]. People in these regions are not partof the information era and this digital segregation imposesseveral restrictions to their daily lives. Children growing upwithout access to the latest communication technologies andonline learning tools are unlikely to be competitive in the joband commercial markets. Unreliable Internet connection alsohinders people from remote areas to benefit from online com-merce and engage in the digital world, thereby compoundingalready existing social and economic inequalities.
Abdelaali Chaoub is with the National Institute of Posts and Telecommuni-cations (INPT), Morocco (email: [email protected]). Marco Gior-dani is with the Department of Information Engineering, University of Padova,Padova, Italy (email: [email protected]). Brejesh Lall is with the IndianInstitute of Technology Delhi, India (email: [email protected]). VimalBhatia is with the Indian Institute of Technology Indore, India (email: [email protected]). Adrian Kliks is with the Poznan University of Technology’s In-stitute of Radiocommunications, Poland (email: [email protected]).Luciano Mendes is with the National Institute of Telecommunications (Inatel),Brazil (email: [email protected]). Khaled Rabie is with the ManchesterMetropolitan University, UK (email: [email protected]). Harri Saarnisaariis with the University of Oulu, Finland (email: harri.saarnisaari@oulu.fi).Amit Singhal is with the Bennett University, India (email: [email protected]). Nan Zhang is with the Department of Algorithms, ZTECorporation (email: [email protected]). Sudhir Dixit is with the Ba-sic Internet Foundation and University of Oulu (email: [email protected]).
However, rural areas are now becoming more and moreattractive as the new coronavirus (COVID-19) pandemic hasshown, since it has reshaped our living preferences and pushedmany people to work remotely from wherever makes themmost comfortable [2]. Such agglomerations where people liveand work are referred to as “oases” in this paper. Wirelessconnectivity in rural areas is expected to have a significanteconomic impact too. Hence, the use of technology in farmsand mines will increase the productivity and open new oppor-tunities for local communities. Technology will also providebetter education, higher quality entertainment, increased digi-tal social engagement, enhanced business opportunities, higherincome, and efficient health systems to those living in the mostremote zones.Despite these premises, advances in the communicationstandards towards provisioning of wireless broadband connec-tivity to remote regions have been, so far, relegated to the verybottom, if not entirely ignored. The fundamental challenges arelow return on investment, inaccessibility that hinders deploy-ment and regular maintenance of network infrastructures, andlack of favorable spectrum and critical infrastructure such asbackhaul and power grid, respectively. In these regards, despitebeing in its initial stages, the 6th generation (6G) of wirelessnetworks is building upon the leftover from the previous gen-erations [3], and will be developed by taking into account thepeculiarities of the remote and rural sector, with the objectiveof providing connectivity for all and reach digital inclusion [4].Specifically, the research community should ensure that thiscritical market segment is not overlooked in favor of themore appealing research areas such as artificial intelligence(AI), machine learning (ML), terahertz communications, 3Daugmented reality (AR)/virtual reality (VR), and haptics.Boosting remote connectivity can start by addressing spec-trum availability issues. Licenced spectrum in sub-1 GHz, infact, is a cumbersome and costly resource, and may requirenew frequency reuse strategy in remote regions because oftheir unique requirements. Utilization of locally unexploitedfrequencies and unlicensed bands judiciously may help in re-ducing the overall cost, thereby making remote connectivity aviable business opportunity. Advanced horizontal and verticalspectrum sharing models, along with enhanced co-existenceschemes, are two other powerful solutions to improve sig-nal reach in these areas. Innovative business and regulatormodels may be suitable, to encourage new players, suchas community-based micro-operators, to build and operatethe local networks. Local, flexible and pluralistic spectrum ig. 1: A summary of the challenges for providing wireless connectivity to remote areas with proposed solutions. licensing could be the way forward to boost the remote market.Another issue is that remote areas may not have ampleconnectivity to the power sources. Hence, it is imperativethat 6G solutions for remote areas are designed as self-reliantin terms of their power/energy requirements, and/or with thecapability to scavenge from the surrounding, possibly scarce,resources. Governments can assuage this situation to an extentby making it attractive for the profit-wary service providersto deploy solutions in remote areas. Revised governmentpolicies and appropriate business models should be parallellyexplored as they have direct implications on the technol-ogy requirements. Environmentally-friendly thinking shouldalso be included throughout the chain of energy consumedfrom mining to manufacturing and recycling. Moreover, theabundant renewable sources need to be integrated into powersystems at all scales for sustainable energy provisioning.Remote maintenance of network infrastructures and incor-poration of some degrees of self-healing capability is also veryimportant since it might be difficult to access remote areasdue to a difficult terrain, harsh weather, or lack of transport-connectivity. Suitable specifications for fault tolerance andfallback mechanisms need therefore to be incorporated.Based on the above introduction, the objective of this articleis two-fold: (i) highlight the challenges that hinder progressin the development and deployment of solutions for cateringto the remote areas, and (ii) suggest novel approaches toaddress those challenges. In particular, the paper targets the6G mobile standard, such that these important issues are considered into the design process from the very beginning.We deliberately skip a detailed literature survey, because aclear and comprehensive review is provided in [4]. We focus,rather, on discussing the requirements and the correspondingchallenges, and proposing novel approaches to address someof those issues.A summary of these challenges and possible solutions isshown in Fig 1. The rest of the article is organized as follows.Sec. II discusses the question of how future 6G can deliveraffordable connectivity to remote users. Sec. III provides arange of promising technical solutions capable of facilitatingaccess to broadband connectivity in remote locations. Sec. IVpromotes the use of a variety of dynamic spectrum accessschemes and suggests how they can evolve to meet the surgingneeds in the unconnected areas. Sec. V presents approachesfor integrating infrastructure sharing, renewable sources, andemerging energy-efficient technologies to boost optimal andenvironmentally friendly power provision. Sec. VI presentsinnovative ways to simplify maintenance operations in hard-to-reach zones. Finally, the conclusions are summarized inSec. VII.II. A
FFORDABLE S ERVICE P ROVISIONINGIN R EMOTE S EGMENTS
One of the biggest impediments to connecting the uncon-nected part of the world is the high costs involved and theprevailing low income of the target population. Fortunately, ig. 2: Backhaul connectivity in rural areas. there are many affordable emerging alternatives in 6G whichmay bring new possibilities, as enumerated in this section.
Dedicated remote-centred connectivity layer.
Besides5G’s typical service pillars (i.e., eMBB, ULRRC, and mMTC),6G should introduce a fourth service grade with basic connec-tivity target key performance indicators (KPIs). However, thisremote mode cannot be just a plain version of the urban 6G,since it has to be tailored to the specificities of the remotesector. Some KPIs relevant to remote connectivity scenarioslike coverage and cost-effectiveness need to be expanded,whereas the new service class needs more relaxed constraintsin terms of some conventional 5G performance metrics likethroughput and latency. This novel service class should haveits dedicated slice and endowed with specific and moderatelevels of edge and caching capabilities: the involved data canthen be processed on edge, local or central data centers forbetter scalability, as illustrated in Fig. 2. Accordingly, suchconnectivity services can be charged at reduced prices.
Multiple radio access technologies (RATs) interworking.
Local access in remote areas can be designed to aggregatemultiple and heterogeneous RATs. Remote streams can thenbe split over one or more RATs, thus allowing flexibility andproviding the highest performance possible at minimal costin everyday life and work. At the same time, digitalizationin remote areas calls for large coverage solutions (e.g., TVor GSM white spaces (WSs)) to increase the number of userswithin a base station and helps reduce the network deploymentand management costs, albeit at some performance trade-offs.Radio frequency (RF) solutions can be complemented bythe emerging optical wireless communications (OWCs). In particular, short range visible light communications (VLCs)category operating over the visible spectrum can boost thethroughput in indoor, fronthaul and underwater environments(see Fig. 3) while serving the intuitive goal of illuminationmaking it a cost-efficient technology.
Low-cost networking and end-user devices.
One wayto reduce cost is the exploitation of legacy infrastructure.TV stations can be shared with mobile network operators(MNOs) to provide both tower and electricity. The latestdevelopments in wireless communications can be applied inoutdoor power line communication (PLC) to provide high datarate connectivity over the high and medium voltages powerlines, increasing the capability of the backhaul networks inremote areas. Existing base stations and the already-installedfibers alongside roads or embedded inside electrical cablescan also serve as a backhaul solution for connectivity inrural regions. End-user devices and modems should also beaffordable and usable everywhere, i.e., when people move ortravel to different places under harsh conditions. Therefore, thepossibility to use off-the-shelf equipment at both the user’s andnetwork’s sides is important and integration with appropriatesoftware stacks is welcome to reduce capital and operationalexpenditures (capex and opex).
Adoption of open, virtualized and cloud-native solutions.
The remote infrastructure is likely to be deployed by smallInternet service providers (ISPs) and the cost of specializedhardware equipment is an issue to be overcome. Open sourceapproaches allow MNOs to choose common hardware fromany vendor and implement the radio access network (RAN)and core functionalities using software defined radio (SDR)nd software defined networking (SDN) frameworks. More-over, virtualized and cloudified network functions may reduceinfrastructure, maintenance and upgrade costs [5]. These so-lutions are especially interesting for new players building theremote network from scratch, to foster the inter-operabilityand cost-effectiveness of hardware and software. However,this field still requires further research and development workbefore commercial deployment.III. I
MPROVING S ERVICE A CCESSIBILITYIN R EMOTE A REAS
In order to provide long-lived broadband connectivity, aminimum service quality must be continuously guaranteed.In this perspective, this section reviews potential solutions topromote resilient service accessibility in rural areas.
Multi-hop network elasticity.
The access network has,over generations, become multi-hop to provide flexibility inthe architecture design, despite some increase in complexity.Given the typical geographic, topographic, and demographicconstraints of present scenarios, performance levels (e.g.,coverage, latency, and bandwidth) of individual hops can bemade adaptive. The idea is to extend performance elasticitybeyond air-interface to include other hops in the RAN. Thesame approach can be brought to backhaul connections (seeFig. 2). Similarly, rural cell boundaries experiencing poorcoverage can reap the elasticity benefits through the use ofdevice-to-device (D2D) communications as depicted in Fig. 3.Network protocols should be extended to include static-(e.g., location-based) besides temporal-quality adaptation tohandle variations in channel quality over time.
Wireless backhaul solutions.
Service accessibility in ruralareas involves prohibitive deployment expenditures for net-work operators and requires high-capacity backhaul connec-tions for several different use cases. Fig. 2 provides a compre-hensive overview of potential backhaul solutions envisioned inthis paper to promote remote connectivity. On one side, layingmore fiber links substantially boost broadband access in thoseareas, but at the expense of increased costs. PLC connections,on the other side, provide ease of reach at lower costs makinguse of ubiquitous wired infrastructures as a physical mediumfor data transmission, but some inherent challenges related toharsh channel conditions and connected loads are still to beovercome. Fig. 2 illustrates also how, even though the useof conventional microwave and satellite links can fulfill theperformance requirements of hard-to-reach zones, emerginglong-range wireless technologies, such as TV and GSM WSsystems, are capable of delivering the intended service overlonger distances with less power while penetrating throughdifficult terrain like mountains and lakes.Another recent trend is building efficient cost-effectivebackhaul links using software-defined technology embeddedinto off-the-shelf multi-vendor hardware to connect the uncon-nected remote communities (e.g., Oasis 1 in Fig. 2). Recently,the research community has also investigated integrated ac-cess and backhaul (IAB) as a solution to replace fiber-likeinfrastructures with self-configuring easier-to-deploy relaysoperating through wireless backhaul using part of the accesslink radio resources [6]. For example, the TV WS tower in Fig. 2 may use the TV spectrum holes to provide both accessto Oasis 3 and connection to the backhaul link for Oasis 4. IABhas lower complexity as compared to fiber-like networks andfacilitates site installation in rural areas where cable buildoutis difficult and costly. The potential of the IAB paradigm ismagnified when wireless backhaul is realized at millimeterwaves (mmWaves), thus exploiting a much larger bandwidththan in sub-6-GHz systems. Moreover, mmWave IAB enablesmultiplexing the access and backhaul data within the samebands, thereby removing the need for additional hardwareand/or spectrum license costs.Nowadays, free space optical (FSO) links are being consid-ered as a powerful full-duplex and license-free alternative toincrease network footprint in isolated areas with challengingterrains. However, FSO units are very sensitive to opticalmisalignment. For instance, the HOP1 FSO unit depicted inFig. 2 should be permanently and perfectly aligned with theFSO unit installed in the HOP3 location. In-depth researchin spherical receivers and beam scanning is hence needed toimprove the capability of intercepting laser lights emanatingfrom multiple angles.
Physical-layer solutions for front/mid/backhaul.
Eventhough wireless backhauling can reduce deployment costs,service accessibility in rural regions still requires a minimumnumber of fiber infrastructures to be already deployed. Fibercapacity can hence be increased if existing wavelength di-vision multiplexing networks are migrated to elastic opticalnetworks (EONs) by technology upgradation at nodes; theoutdated technology of urban regions may then be reused toestablish connectivity in under-served rural regions withoutsignificant investment.Besides backhaul, midhaul and fronthaul should also beimproved by AI/ML-based solutions providing cognitive ca-pabilities for prudent use of available licensed and unlicensedspectrum [7]. This is especially useful in remote areas wherethe sparse distribution of users may result in spectrum holes.The unlicensed spectrum, in particular, can provide signifi-cant cost-savings for service delivery and improve networkelasticity. New possibilities including evolved multiple accessschemes and waveforms, like non-orthogonal multiple access(NOMA) for mMTC, should be investigated; this technologyis particularly interesting for Internet of things (IoT) serviceswhere some sensors are close to and some far away froma base station [8]. AI/ML can be also exploited to controlphysical and link layers for smooth and context-aware mod-ulation and coding schemes (MCSs) transitions, even thoughthis approach would need to be lightweight to reduce cost andmaintenance, and optimized for the intended market segment.
Non-terrestrial network solutions.
Network densificationin rural areas is complicated by the heterogeneous terrain thatmay be encountered when installing fibers between cellularstations. To solve this issue, 6G envisions the deployment ofnon-terrestrial networks (NTNs) where air/spaceborne plat-forms like unmanned aerial vehicles (UAVs), high altitudeplatform stations (HAPSs), and satellites, provide ubiquitousglobal connectivity when terrestrial infrastructures are unavail-able [9]. Potential beneficiaries of this trend are shown in ig. 3: Spectrum usage for remote connectivity use cases.
Fig. 3, including inter-regional transport, farmlands, ships,mountainous areas, and remote maintenance facilities. Theevolution towards NTNs will be favored by architecturaladvancements in the aerial/space industry (e.g., through solid-state lithium batteries and Gallium Nitride technologies), newspectrum developments (e.g., by transitioning to mmWaveand optical bands), and novel antenna designs (e.g., throughreconfigurable phased/inflatable/fractal antennas realized withmetasurface material). Despite these premises, however, thereare still various challenges that need to be addressed, includingthose related to latency and coverage constraints. NTNs canalso provide remote-ready, low-cost (yet robust), and long-range backhaul solutions for terrestrial devices with no wiredbackhaul.
Self-organizing networks (SONs).
To explicitly address theproblem of network outages (e.g., due to backhaul failure),which are very common in remote locations, 6G should tran-sition towards SONs implementing network slicing, dynamicspectrum management, edge computing, and zero-touch au-tomation functionalities. This approach provides extra degreesof freedom for combating service interruptions, and improvesnetwork robustness. In this context, AI/ML can help both theradio access and backhaul networks to self-organize and self-configure themselves, e.g., to discover each other, coordinate,and manage the signaling and data traffic.IV. T
OWARDS A F LEXIBLE U SE OF S PECTRUMIN R EMOTE A REAS
We now present some promising solutions to addressspectrum availability issues, which currently pose a seriousimpediment to broadband connectivity in remote areas.
Leveraging cognitive radio networks.
One of the majorbarriers for network deployment in rural areas is spectrumlicensing, since participation in spectrum auction is typicallydifficult, from an economic point of view, for small ISPs.In this perspective, new licensing schemes can prosper the cognitive radio approach, allowing local ISPs to deploy net-works in areas where large operators are not interested inproviding their service [10]. Spectrum awareness mechanisms,e.g., geolocation database and spectrum sensing, can be usedto inform network providers about vacant spectrum in a givenarea, as well as providing protection against unauthorizedtransmissions and unpredictable propagation conditions. Forinstance, Fig. 3 shows how TV and GSM WS towers canexpand the connectivity beyond the rural households to reachmore distant locations like farms and wilderness areas.
Spectrum co-existence.
Sub-6 GHz frequencies remaincritical for remote connectivity thanks to their favourablepropagation properties and wide reach. In these crowdedbands, spectrum re-farming and inter/intra-operator spectrumsharing can considerably increase spectrum availability [10].Nevertheless, coverage gaps and low throughput in the legacybands call for advanced multi-connectivity schemes to com-bine frequencies above and below 6 GHz. Using advancedcarrier aggregation techniques in 6G systems, the resourcescheduling unit can choose the optimal frequency combina-tion(s) according to service requirements, device capabilities,and network conditions. The proposed model offers a scalablebandwidth that maintains service continuity in case of con-nectivity loss in those spectrum bands that are more sensitiveto surrounding relief, atmospheric effects, and water absorp-tion: for example Fig. 3 illustrates a scenario in which vitalfacilities in rural communities enjoy permanent connectivityusing the lower bands in case of communication failure on thehigher bands. Likewise, multi-connectivity provides diversity,improved system resilience, and situation awareness by estab-lishing multiple links from separate sources to one destination.This aggregation can be achieved at various protocol and/orarchitecture levels ranging from the radio link up to the corenetwork, allowing effortless deployments of elastic networksin areas difficult to access.
Utilizing unlicensed bands.
A combination of licensedand unlicensed bands has been acknowledged by many stan-ardization organizations to improve network throughput andcapacity in unserved/under-served rural areas, as depicted inFig. 3. While the FCC has recently released 1.2 GHz in theprecious 6 GHz bands to expand the unlicensed spectrum,the huge bandwidth available at millimeter- and terahertz-wave bands will further support uplink and downlink split,in addition to hybrid spectrum sharing solutions that canadaptively orchestrate network operations in the licensed andunlicensed bands. High frequencies require line of sight (LOS)for proper communication, complicating harmonious operationwith lower bands. Accordingly, time-frequency synchroniza-tion, as well as control procedures and listening mechanisms,like listen-before-talk (LBT), need to evolve towards morecooperative and distributed protocols to avoid misleading spec-trum occupancy. The management of uncoordinated competingusers in unlicensed bands will emerge as important issue, andit needs to be addressed in 6G networks.
Regional licenses and micro-operators.
Deployment ofterrestrial networks for remote areas is challenging due toterrain, lack of infrastructure and personnel. Network operatorswould then rather roam their services from telecommunicationproviders already operating in those areas than building theirown infrastructure. However, such an approach may entailthe need for advanced horizontal (between operators of thesame priorities) and vertical (when stakeholders of variouspriorities coexist) spectrum/infrastructure sharing frameworks.Solutions like license shared access (LSA, in Europe) andspectrum access system (SAS, in the US) are mature ex-amples of such an approach with two-tiers and three-tiersof users, respectively. This can evolve to include n -tiers ofusers belonging to m different MNOs. An example of a four-tiered access is provided in Fig. 3. From the top, we findthe E-safety services with the highest priority, a tier-2 layerdevoted to E-learning sessions and E-government transactions,a middle-priority tier-3 layer for IoT use cases that generatesporadic traffic, and a final lower-priority tier-4 layer thatuses the remainder of the available spectrum (e.g., for E-commerce services). Such solutions, however, need to besupported by innovative business and regulatory models tomotivate new market entrants (e.g., micro-operators, whichare responsible for last-mile service delivery and infrastructuremanagement) to offer competitive and affordable services inremote zones [11].V. P OWERING IN A G REEN AND E FFICIENT W AY Power supply is among the highest expenses of MNOsand a major bottleneck for ensuring reliable connectivity inremote areas. MNOs’ profitability and reliable powering canbe improved following (a combination of) these solutions, assummarized in Fig. 4.
Infrastructure sharing.
Local communication/power op-erators, as well as various stockholders such as companies,manufacturers, governmental authorities and standardizationbodies, should build an integrated design which entails a jointnetwork development process right from the installation phase.In particular, the different players should cooperate to avoiddeploying several power plants for different use cases, thus
Fig. 4: Key enablers for efficient and green powering of rural areas. saving precious (already limited) economic resources for othertypes of expenses.
Efficient and optimal energy usage.
The 6G remote areasolutions should be energy efficient and allow base and relaystations to minimize power consumption while guaranteeingaffordable yet sufficient service for residents [12]. In partic-ular, energy efficiency should target IoT sensors’ design anddeployment, since the increasing use of a massive number ofIoT devices, e.g., to boost farming and other activities such asenvironmental monitoring, is expected to significantly increasein the near future.At the moment, these efforts have been made after thestandardization work was completed, but 6G should includeefficient use of energy during the standardization process itself.Techniques like cell zooming relying on power control andadaptive coverage can be reused at various network levelsfor flexible, energy-saving front/mid/backhaul layouts. AI/MLtechniques can be very helpful in these scenarios. For example,the traffic load statistics on each node can be monitored tochoose the optimal cell sleeping and on/off switching strategiesto deliver increased power efficiency in all the involved stepsof communication.
Technological breakthroughs.
In addition to obvious en-ergy sources such as solar, wind, and hydraulics, energy har-vesting through the ambient resources (e.g., electromagneticsignals, vibration, movement, sound, and heat) could providea viable efficient solution by enabling energy-constrainednodes to scavenge the energy while simultaneous wirelessinformation and power transfer [13].Another recent advancement promoting energy-efficientwireless operations is the use of intelligent reflecting surfaces(IRSs), equipped with a large number of passive elementssmartly coordinated to reflect any incident signal to its in-tended destination without necessitating any RF chain. Al-though still in its infancy, this technology offers significant ad-vantages in making the propagation conditions in harsh remoteareas more favorable with substantial energy savings [14]. ig. 5: A workflow for cost-efficient maintenance operations in remote areas.
VI. I
NTELLIGENT AND A FFORDABLE M AINTENANCE
Operations, administration and management (OAM) func-tionalities and dedicated maintenance for each network com-ponent are of paramount importance to overall system perfor-mance and user experience in traditional commercial 4G/5Gnetworks. This comes at the expense of complicated and costlytasks, especially in hard-to-reach areas. In this section wepresent innovative ideas to enable intelligent and cost-effectivemaintenance in 6G network deployed in rural regions.
Network status sensing and diagnosing.
Traditionally, theOAM system is adopted for network status monitoring witha major drawback, i.e, manual post-processing and reportingtime delay due to huge amounts of gathered data. To enablean intelligent and predictive maintenance, network diagnosticsrelying on AI-based techniques is advised [15]. With the devel-opment of edge computing technologies, multi-level sensingcan be employed to achieve near-real time processing andmulti-dimensional information collection within a tolerablereporting interval. For instance, processing operations relatedto short-term network status could be mostly done at theedge node to ensure fast access to this vital information inrural zones.
Network layout planning and maintenance.
As mentionedin the previous sections, the network in remote areas is mainlycomposed of cost-effective nodes along the path from theaccess to the core parts (e.g., radio, centralized and distributedunits, IAB-donors and relays) that need to be organized ineither single or multiple hops. In this situation, the wholesystem will be harmed if one of these nodes experiences anaccidental failure. To enhance the resilience of such networks,more flexible and intelligent network layout maintenance isrequired. More precisely, using evolved techniques such asSONs (see Sec. III), the link among each couple of nodeswithin the network can be permanently controlled and dy-namically substituted or restored in case of an outage (seeFig. 5). Additionally, since a big part of the next generationmobile network is virtualized, appropriate tools or even adedicated server may be needed for automatic software updatesmonitoring, periodic backups and scheduled maintenance toavoid or at least minimize the need for on-site interventionin those remote facilities. Automatic fallback mechanisms canalso be scheduled to downgrade the connectivity to anothertechnology under bad network conditions, e.g., by implement-ing appropriate multi-connectivity schemes, as described inSec. IV.
Network performance optimization.
Network optimiza-tion in rural areas should take into account remote-specific requirements and constraints. For example, access to the edgeresources, which are finite and costly and can be rapidlyexhausted, should be optimized taking into consideration theintended services, terminal capabilities, and charging policy ofthe network and its operator(s).A summary of the maintenance life cycle in remote andrural areas is shown in Fig. 5. In particular, after intelligentlybuilding and processing relevant system information data sets,maintenance and repair activities (e.g. system updates or op-erational parameters optimization) can be performed remotelyand safely using 3D virtual environments such as AR and VR.VII. C
ONCLUSIONS
The problem of providing connectivity to rural areas willbe a pillar of future 6G standardization activities. In thisarticle we discuss the challenges and possible approaches toaddressing the needs of the remote areas. It is argued thatsuch service should be optimized for providing a minimumfallback capability, while still providing full support for spatio-temporal service scalability and graceful quality degradation.We also give insights on the constraints on network designand deployment for rural connectivity solutions. We claimthat optimally integrating NTN and FSO technologies alongthe path from the end-point to the core element using opensoftware built on the top of off-the-shelf hardware can pro-vide low-cost broadband solutions in extremely harsh andinaccessible environments, and can be the next disruptivetechnology for 6G remote connectivity. Integration of outdatedtechnology should also be provisioned so that they may beinnovatively used to service the remote areas. Such provisionsshould extend to integrate open and off-the-shelf solutions tofully benefit from cost advantage gains. Spectrum, regulatory,and standardization issues are also discussed because of theirimportance to achieve the goal of remote area connectivity. Itis fair to say that including remote connectivity requirementsin the 6G standardization process will lead to a more balancedand universal social as well as digital equality.R
EFERENCES[1] H. Saarnisaari, S. Dixit, S. Alouini, A. Chaoub, M. Giordani, A. Kliks,M. Matinmikko-Blue, and N. Zhang, “ 6G White Paper on Connectivityfor Remote Areas,”
6G Research Visions, No. 5, University of Oulu ,2020.[2] J. Phillipson, M. Gorton, R. Turner, M. Shucksmith, K. Aitken-McDermott, F. Areal, P. Cowie, C. Hubbard, S. Maioli, R. McA-reavey et al. , “The COVID-19 Pandemic and Its Implications for RuralEconomies,”
Sustainability , vol. 12, no. 10, p. 3973, May 2020.[3] M. Giordani, M. Polese, M. Mezzavilla, S. Rangan, and M. Zorzi,“Toward 6G Networks: Use Cases and Technologies,”
IEEE Commu-nications Magazine , vol. 58, no. 3, pp. 55–61, March 2020.[4] E. Yaacoub and M. Alouini, “A Key 6G Challenge and Opportunity –Connecting the Base of the Pyramid: A Survey on Rural Connectivity,”
Proceedings of the IEEE , vol. 108, no. 4, pp. 533–582, Mar. 2020.[5] L. Gavrilovska, V. Rakovic, and D. Denkovski, “From Cloud RAN toOpen RAN,”
Wireless Personal Communications , pp. 1–17, March 2020.[6] M. Polese, M. Giordani, T. Zugno, A. Roy, S. Goyal, D. Castor, andM. Zorzi, “Integrated Access and Backhaul in 5G mmWave Networks:Potential and Challenges,”
IEEE Communications Magazine , vol. 58,no. 3, pp. 62–68, March 2020.[7] K. B. Letaief, W. Chen, Y. Shi, J. Zhang, and Y.-J. A. Zhang, “Theroadmap to 6G: AI empowered wireless networks,”
IEEE Communica-tions Magazine , vol. 57, no. 8, pp. 84–90, Aug 2019.8] Z. Hu, L. Xu, L. Cao, S. Liu, Z. Luo, J. Wang, X. Li, and L. Wang,“Application of non-orthogonal multiple access in wireless sensor net-works for smart agriculture,”
IEEE Access , vol. 7, pp. 87 582–87 592,Jun 2019.[9] N. Cheng, W. Quan, W. Shi, H. Wu, Q. Ye, H. Zhou, W. Zhuang, X. S.Shen, and B. Bai, “A comprehensive simulation platform for space-air-ground integrated network,”
IEEE Wireless Communications , vol. 27,no. 1, pp. 178–185, Feb 2020.[10] W. S. H. M. W. Ahmad, N. A. M. Radzi, F. Samidi, A. Ismail,F. Abdullah, M. Z. Jamaludin, and M. Zakaria, “5G technology: To-wards dynamic spectrum sharing using cognitive radio networks,”
IEEEAccess , vol. 8, pp. 14 460–14 488, Jan 2020.[11] P. Ahokangas, M. Matinmikko-Blue, S. Yrj¨ol¨a, V. Sepp¨anen,H. H¨amm¨ainen, R. Jurva, and M. Latva-aho, “Business models for local5G micro operators,”
IEEE Transactions on Cognitive Communicationsand Networking , vol. 5, no. 3, pp. 730–740, Mar 2019.[12] GSMA Connected Society, “Closing the Coverage Gap – How Innova-tion Can Drive Rural Connectivity,”
White Paper , 2019.[13] M. Gholikhani, H. Roshani, S. Dessouky, and A. Papagiannakis, “Acritical review of roadway energy harvesting technologies,”
AppliedEnergy , vol. 261, p. 114388, Mar 2020.[14] Q. Wu and R. Zhang, “Towards smart and reconfigurable environment:Intelligent reflecting surface aided wireless network,”
IEEE Communi-cations Magazine , vol. 58, no. 1, pp. 106–112, Nov 2019.[15] M. Huang, Z. Liu, and Y. Tao, “Mechanical fault diagnosis and pre-diction in IoT based on multi-source sensing data fusion,”
SimulationModelling Practice and Theory , vol. 102, p. 101981, July 2020.
Abdelaali Chaoub [SM] is an Associate Professor, working at the NationalInstitute of Posts and Telecommunications (INPT) at Rabat (Morocco) since2015. His research interests are related to spectrum sharing for 5G/B5Gnetworks, cognitive radio networks, smart grids, cooperative communicationsin wireless networks, and multimedia content delivery. He is a paper reviewerfor several leading international journals and conferences. He has accumulatedintersectoral skills through work experience both in academia and industry asa Senior VoIP solutions Consultant at Alcatel-Lucent (2007–2015).
Marco Giordani [M’20] received his Ph.D. in Information Engineering in2020 from the University of Padova, Italy, where he is now a postdoctoralresearcher and adjunct professor. He visited NYU and TOYOTA Infotechnol-ogy Center, Inc., USA. In 2018 he received the “Daniel E. Noble FellowshipAward” from the IEEE Vehicular Technology Society. His research focuseson protocol design for 5G/6G mmWave cellular and vehicular networks.
Brejesh Lall [M] received his Ph.D degree from Indian Institute of Tech-nology Delhi in 1999. Earlier, he received his bachelors and masters degreein Electronics and Communications from Delhi College of Engineering in1991 and 1992 respectively. He is currently a Professor in the department ofElectrical Engineering at Indian Institute of Technology Delhi. Previously, heserved in the Digital Signal Processing Group of Hughes Software Systemsfor 8 years. His research interests lie in the areas of signal processing andmachine learning. He has extensively applied signal processing / machinelearning techniques to applications in the broad areas of telecommunicationsand computer vision.
Vimal Bhatia [M’96, SM’12] is currently working as a Professor at IndianInstitute of Technology Indore (IIT-I), Indore, India. He received his Ph.D.degree from Institute for Digital Communications at The University ofEdinburgh (UoE), UK in 2005. During his Ph.D. studies he also receivedthe IEEE fellowship for collaborative research on at Carleton University,Ottawa, Canada. He has authored/co-authored more than 230 peer-reviewedjournals and conferences. His research focuses on optical communicationnetworks, wireless communications, signal processing and in software productdevelopments.
Adrian Kliks [SM] is an assistant professor at Poznan University of Tech-nology’s Institute of Radiocommunications, Poland, and he is a cofounderand board member of RIMEDO Labs company. His research interests includenew waveforms for wireless systems applying either non-orthogonal or non-contiguous multicarrier schemes, cognitive radio, advanced spectrum man-agement, deployment and resource management in small cells, and networkvirtualization.
Luciano Mendes received his Ph.D. on Electrical Engineering from the StateUniversity of Campinas, Brazil in 2007. Since 2001 he is a professor atthe National Institute of Telecommunications (Inatel), Brazil, where he actsas Research Coordinator of the Radiocommunications Reference Center. Hismain research area is physical layer for future mobile networks.
Khaled Rabie [M’15, SM’20], a Fellow of the U.K. Higher EducationAcademy, received his Ph.D. degree from the University of Manchester,UK. He is currently an assistant professor at the Manchester MetropolitanUniversity, UK. His primary research focuses on various aspects of the next-generation wireless communication systems. He received the best studentpaper award at the IEEE ISPLC (TX, USA, 2015) and the IEEE AccessEditor of the month award for August 2019. Khaled is an Editor for IEEECommunications Letters.
Harri Saarnisaari [SM] received his Ph.D degree from the University ofOulu in 2000, where he has been with Centre for Wireless Communicationssince 1994. He is currently a university researcher and his current researchinterest include remote area connectivity, especially in the Arctic areas.
Amit Singhal [M] received his PhD degree in electrical engineering fromthe Indian Institute of Technology Delhi in 2016. He is currently workingas an Assistant Professor at Bennett University, Greater Noida, India. Hisresearch interests include next generation communication systems, Fourierdecomposition method, image retrieval and molecular communications.
Nan Zhang [M] was born in Qingyang, China, in 1990. He received thebachelor degree in communication engineering and the Master degree inintegrated circuit engineering from Tongji University, Shanghai, China, inJuly 2012 and March 2015, respectively. He is now a Senior Engineer at theDepartment of Algorithms, ZTE Corporation and works on the standardizationof LTE and NR system. His current research interests are in the field of 5Gchannel modeling, MIMO, NOMA techniques, satellite/ATG communicationand network architecture.