Kan Zheng

Radio resource allocation in LTE-advanced cellular networks with M2M communications

Machine-to-machine (M2M) communications are expected to provide ubiquitous connectivity between machines without the need of human intervention. To support such a large number of autonomous devices, the M2M system architecture needs to be extremely power and spectrally efficient. This article thus briefly reviews the features of M2M services in the third generation (3G) long-term evolution and its advancement (LTE-Advanced) networks. Architectural enhancements are then presented for supporting M2M services in LTE-Advanced cellular networks. To increase spectral efficiency, the same spectrum is expected to be utilized for human-to- human (H2H) communications as well as M2M communications. We therefore present various radio resource allocation schemes and quantify their utility in LTE-Advanced cellular networks. System-level simulation results are provided to validate the performance effectiveness of M2M communications in LTE-Advanced cellular networks.

Challenges on wireless heterogeneous networks for mobile cloud computing

Mobile cloud computing (MCC) is an appealing paradigm enabling users to enjoy the vast computation power and abundant network services ubiquitously with the support of remote cloud. However, the wireless networks and mobile devices have to face many challenges due to the limited radio resources, battery power and communications capabilities, which may significantly impede the improvement of service qualities. Heterogeneous Network (HetNet), which has multiple types of low power radio access nodes in addition to the traditional macrocell nodes in a wireless network, is widely accepted as a promising way to satisfy the unrelenting traffic demand. In this article, we first introduce the framework of HetNet for MCC, identifying the main functional blocks. Then, the current state of the art techniques for each functional block are briefly surveyed, and the challenges for supporting MCC applications in HetNet under our proposed framework are discussed. We also envision the future for MCC in HetNet before drawing the conclusion.

Heterogeneous Vehicular Networking: A Survey on Architecture, Challenges, and Solutions

With the rapid development of the Intelligent Transportation System (ITS), vehicular communication networks have been widely studied in recent years. Dedicated Short Range Communication (DSRC) can provide efficient real-time information exchange among vehicles without the need of pervasive roadside communication infrastructure. Although mobile cellular networks are capable of providing wide coverage for vehicular users, the requirements of services that require stringent real-time safety cannot always be guaranteed by cellular networks. Therefore, the Heterogeneous Vehicular NETwork (HetVNET), which integrates cellular networks with DSRC, is a potential solution for meeting the communication requirements of the ITS. Although there are a plethora of reported studies on either DSRC or cellular networks, joint research of these two areas is still at its infancy. This paper provides a comprehensive survey on recent wireless networks techniques applied to HetVNETs. Firstly, the requirements and use cases of safety and non-safety services are summarized and compared. Consequently, a HetVNET framework that utilizes a variety of wireless networking techniques is presented, followed by the descriptions of various applications for some typical scenarios. Building such HetVNETs requires a deep understanding of heterogeneity and its associated challenges. Thus, major challenges and solutions that are related to both the Medium Access Control (MAC) and network layers in HetVNETs are studied and discussed in detail. Finally, we outline open issues that help to identify new research directions in HetVNETs.

Survey of Large-Scale MIMO Systems

The escalating teletraffic growth imposed by the proliferation of smartphones and tablet computers outstrips the capacity increase of wireless communications networks. Furthermore, it results in substantially increased carbon dioxide emissions. As a powerful countermeasure, in the case of full-rank channel matrices, MIMO techniques are potentially capable of linearly increasing the capacity or decreasing the transmit power upon commensurately increasing the number of antennas. Hence, the recent concept of large-scale MIMO (LS-MIMO) systems has attracted substantial research attention and been regarded as a promising technique for next-generation wireless communications networks. Therefore, this paper surveys the state of the art of LS-MIMO systems. First, we discuss the measurement and modeling of LS-MIMO channels. Then, some typical application scenarios are classified and analyzed. Key techniques of both the physical and network layers are also detailed. Finally, we conclude with a range of challenges and future research topics.

Challenges of massive access in highly dense LTE-advanced networks with machine-to-machine communications

Machine-to-machine wireless systems are being standardized to provide ubiquitous connectivity between machines without the need for human intervention. A natural concern of cellular operators and service providers is the impact that these machine type communications will have on current human type communications. Given the exponential growth of machine type communication traffic, it is of utmost importance to ensure that current voice and data traffic is not jeopardized. This article investigates the limits of machine type communication traffic coexisting with human communication traffic in LTE-A networks, such that human customer churn is minimized. We show that under proper design, the outage probability of human communication is marginally impacted whilst duty cycle and access delay of machine type communications are reasonably bounded to ensure viable M2M operations.

Big data-driven optimization for mobile networks toward 5G

Big data offers a plethora of opportunities to mobile network operators for improving quality of service. This article explores various means of integrating big data analytics with network optimization toward the objective of improving the user quality of experience. We first propose a framework of Big Data-Driven (BDD) mobile network optimization. We then present the characteristics of big data that are collected not only from user equipment but also from mobile networks. Moreover, several techniques in data collection and analytics are discussed from the viewpoint of network optimization. Certain user cases on the application of the proposed framework for improving network performance are also given in order to demonstrate the feasibility of the framework. With the integration of the emerging fifth generation (5G) mobile networks with big data analytics, the quality of our daily mobile life is expected to be tremendously enhanced.

Toward 5G densenets: architectural advances for effective machine-type communications over femtocells

Ubiquitous, reliable and low-latency machine-type communication, MTC, systems are considered to be value-adds of emerging 5G cellular networks. To meet the technical and economical requirements for exponentially growing MTC traffic, we advocate the use of small cells to handle the massive and dense MTC rollout. We introduce a novel 3GPP-compliant architecture that absorbs the MTC traffic via home evolved NodeBs, allowing us to significantly reduce congestion and overloading of radio access and core networks. A major design challenge has been to deal with the interference to human-type traffic and the large degree of freedom of the system, due to the unplanned deployments of small cells and the enormous amount of MTC devices. Simulation results in terms of MTC access delay, energy consumption, and delivery rate corroborate the superiority of the proposed working architecture.

10 Gb/s hetsnets with millimeter-wave communications: access and networking - challenges and protocols

Heterogeneous and small cell networks (Het- SNets) increase spectral efficiency and throughput via hierarchical deployments. In order to meet the increasing requirements in capacity for future 5G wireless networks, millimeter-wave (mmWave) communications with unprecedented spectral resources have been suggested for 5G HetSNets. While the mmWave physical layer is well understood, major challenges remain for its effective and efficient implementation in Het- SNets from an access and networking point of view. Toward this end, we introduce a novel but 3GPP backwards-compatible frame structure, based on time-division duplex, which facilitates both high-capacity access and backhaul links. We then discuss networking issues arising from the multihop nature of the mmWave backhauling mesh. Finally, system-level simulations evaluate the performance of HetSNets with mmWave communications and corroborate the possibility of having capacities of tens of gigabits per second in emerging 5G systems.

Stochastic Performance Analysis of a Wireless Finite-State Markov Channel

Wireless networks are expected to support a diverse range of quality of service requirements and traffic characteristics. This paper undertakes stochastic performance analysis of a wireless finite-state Markov channel (FSMC) by using stochastic network calculus. Particularly, delay and backlog upper bounds are derived directly based on the analytical principle behind stochastic network calculus. Both the single user and multi-user cases are considered. For the multi-user case, two channel sharing methods among eligible users are studied, i.e., the even sharing and exclusive use methods. In the former, the channel service rate is evenly divided among eligible users, whereas in the latter, it is exclusively used by a user randomly selected from the eligible users. When studying the exclusive use method, the problem that the state space increases exponentially with the user number is addressed using a novel approach. The essential idea of this approach is to construct a new Markov modulation process from the channel state process. In the new process, the multi-user effect is equivalently manifested by its transition and steady-state probabilities, and the state space size remains unchanged even with the increase of the user number. This significantly reduces the complexity in computing the derived backlog and delay bounds. The presented analysis is validated through comparison between analytical and simulation results.

Low power wide area machine-to-machine networks: key techniques and prototype

As one of the fastest growing technologies, machine-to-machine (M2M) communications are expected to provide ubiquitous connectivity. M2M devices can be used for a wide range of emerging applications that have various communications requirements. While M2M communications have been developed for many years, major challenges still remain with their efficient implementation from the perspective of low energy consumption and wide coverage. To address these challenges, low power wide area (LPWA) technology is investigated as one of the potential candidate solutions. In this article, we first introduce some typical LPWA M2M application scenarios. Given their requirements, we highlight key techniques and standards that are explicitly designed for LPWA M2M communications. Finally, we present an LPWA prototype system to evaluate its performance and demonstrate its potential in bridging a technological gap for future Internet-of-Things (IoT) applications.