Sum throughput maximization for heterogeneous multicell networks with RF-powered relays

This paper considers a heterogeneous multicell network where the base station (BS) in each cell communicates with its cell-edge user with the assistance of an amplify-and-forward relay node. Equipped with a power splitter and a wireless energy harvester, the relay scavenges RF energy from the received signals to process and forward the information. In the face of strong intercell interference and limited radio resources, we develop a resource allocation scheme that jointly optimizes (i) BS transmit powers, (ii) power splitting factors for energy harvesting and information processing at the relays, and (iii) relay transmit powers. To solve the highly non-convex problem formulation of sum-rate maximization, we propose to apply the successive convex approximation (SCA) approach and devise an iterative algorithm based on geometric programming. The proposed algorithm transforms the nonconvex problem into a sequence of convex problems, each of which is solved very efficiently by the interior-point method. We prove that our developed algorithm converges to an optimal solution that satisfies the Karush-Kuhn-Tucker conditions of the original nonconvex problem. Numerical results confirm that our joint optimization solution substantially improves the network performance, compared to the existing solution wherein only the received power splitting factors at the relays are optimizedARC Discovery Projects Grant DP14010113

Joint Resource Optimization for Multicell Networks with Wireless Energy Harvesting Relays

This paper first considers a multicell network deployment where the base station (BS) of each cell communicates with its cell-edge user with the assistance of an amplify-and-forward (AF) relay node. Equipped with a power splitter and a wireless energy harvester, the self-sustaining relay scavenges radio frequency (RF) energy from the received signals to process and forward the information. Our aim is to develop a resource allocation scheme that jointly optimizes (i) BS transmit powers, (ii) received power splitting factors for energy harvesting and information processing at the relays, and (iii) relay transmit powers. In the face of strong intercell interference and limited radio resources, we formulate three highly-nonconvex problems with the objectives of sum-rate maximization, max-min throughput fairness and sum-power minimization. To solve such challenging problems, we propose to apply the successive convex approximation (SCA) approach and devise iterative algorithms based on geometric programming and difference-of-convex-functions programming. The proposed algorithms transform the nonconvex problems into a sequence of convex problems, each of which is solved very efficiently by the interior-point method. We prove that our algorithms converge to the locally optimal solutions that satisfy the Karush-Kuhn-Tucker conditions of the original nonconvex problems. We then extend our results to the case of decode-and-forward (DF) relaying with variable timeslot durations. We show that our resource allocation solutions in this case offer better throughput than that of the AF counterpart with equal timeslot durations, albeit at a higher computational complexity. Numerical results confirm that the proposed joint optimization solutions substantially improve the network performance, compared with cases where the radio resource parameters are individually optimized

User Association in 5G Networks: A Survey and an Outlook

26 pages; accepted to appear in IEEE Communications Surveys and Tutorial

Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks

Soaring capacity and coverage demands dictate that future cellular networks need to soon migrate towards ultra-dense networks. However, network densification comes with a host of challenges that include compromised energy efficiency, complex interference management, cumbersome mobility management, burdensome signaling overheads and higher backhaul costs. Interestingly, most of the problems, that beleaguer network densification, stem from legacy networks' one common feature i.e., tight coupling between the control and data planes regardless of their degree of heterogeneity and cell density. Consequently, in wake of 5G, control and data planes separation architecture (SARC) has recently been conceived as a promising paradigm that has potential to address most of aforementioned challenges. In this article, we review various proposals that have been presented in literature so far to enable SARC. More specifically, we analyze how and to what degree various SARC proposals address the four main challenges in network densification namely: energy efficiency, system level capacity maximization, interference management and mobility management. We then focus on two salient features of future cellular networks that have not yet been adapted in legacy networks at wide scale and thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and device-to-device (D2D) communications. After providing necessary background on CoMP and D2D, we analyze how SARC can particularly act as a major enabler for CoMP and D2D in context of 5G. This article thus serves as both a tutorial as well as an up to date survey on SARC, CoMP and D2D. Most importantly, the article provides an extensive outlook of challenges and opportunities that lie at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201

Decoupled UL/DL User Association in Wireless-Powered HetNets with Full-Duplex Small Cells

In this paper, we propose two downlink (DL)-uplink (UL) decoupled (DUDe) user association schemes in wireless-powered full-duplex (FD) heterogeneous networks (HetNets). We consider a two-tier HetNet comprising of half-duplex (HD) massive multi-antenna macrocell base stations (MBSs) and dual-antenna FD small cell base stations (SBSs) to support UL and DL transmissions of FD user equipments (UEs). Each FD UE is first associated to one MBS/SBS, based on the mean maximum received power (MMP) scheme or maximum received power (MRP) to harvest energy. During the consecutive data transmission phase, UEs choose to receive DL traffic from the same MBSs/SBSs as that associated with during energy harvesting phase, and send UL traffic through the same/another SBS. Leveraging tools from the stochastic geometry, we develop an analytical framework to analyze the average harvested energy and derive expressions for the UL and DL coverage probabilities of the proposed DUDe user association schemes. Our results show that there is an optimal value for the SBS density in the wireless-powered FD HetNets, at which both DL and UL coverage probabilities are maximized. Moreover, by applying MMPA and MRPA scheme, wireless-powered FD HetNets with DUDe achieves up to $138.78\%$ and $83.37\%$ energy efficiency gain over the FD HetNets with DL/UL coupled user association scheme and without wireless power transfer, respectively

Towards 6G-Enabled Internet of Things with IRS-Empowered Backscatter-Assisted WPCNs

Wireless powered communication networks (WPCNs) are expected to play a key role in the forthcoming 6G systems. However, they have not yet found their way to large-scale practical implementations due to their inherent shortcomings such as the low efficiency of energy transfer and information transmission. In this thesis, we aim to study the integration of WPCNs with other novel technologies of backscatter communication and intelligent reflecting surface (IRS) to enhance the performance and improve the efficiency of these networks so as to prepare them for being seamlessly fitted into the 6G ecosystem. We first study the incorporation of backscatter communication into conventional WPCNs and investigate the performance of backscatter-assisted WPCNs (BS-WPCNs). We then study the inclusion of IRS into the WPCN environment, where an IRS is used for improving the performance of energy transfer and information transmission in WPCNs. After that, the simultaneous integration of backscatter communication and IRS technologies into WPCNs is investigated, where the analyses show the significant performance gains that can be achieved by this integration

Optimization techniques for reliable data communication in multi-antenna wireless systems

This thesis looks at new methods of achieving reliable data communication in wireless communication systems using different antenna transmission optimization methods. In particular, the problems of exploitation of MIMO communication channel diversity, secure downlink beamforming techniques, adaptive beamforming techniques, resource allocation methods, simultaneous power and information transfer and energy harvesting within the context of multi-antenna wireless systems are addressed