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

Trading Wireless Information and Power Transfer: Relay Selection to Minimize the Outage Probability

This paper studies the outage probability minimization problem for a multiple relay network with energy harvesting constraints. The relays are hybrid nodes used for simultaneous wireless information and power transfer from the source radio frequency (RF) signals. There is a trade-off associated with the amount of time a relay node is used for energy and information transfer. Large intervals of information transfer implies little time for energy harvesting from RF signals and thus, high probability of outage events. We propose relay selection schemes for a cooperative system with a fixed number of RF powered relays. We address both causal and non-causal channel state information cases at the relay--destination link and evaluate the trade-off associated with information/power transfer in the context of minimization of outage probability.Comment: IEEE GlobalSiP, 201

Minimizing Outage Probability by Exploiting CSI in Wireless Powered Cooperative Networks

In this work, we address the relay selection problem for the wireless powered communication networks, where the relays harvest energy from the source radio frequency signals. A single source-destination pair is considered without a direct link. The connecting relay nodes are equipped with storage batteries of infinite size. We assume that the channel state information (CSI) on the source-relay link is available at the relay nodes. Depending on the availability of the CSI on the relay-destination link at the relay node, we propose different relay selection schemes and evaluate the outage probability. The availability of the CSI at the relay node on the relay-destination link considerably improves the performance due to additional flexibility in the relay selection mechanism. We numerically quantify the performance for the proposed schemes and compare the outage probability for fixed and equal number of wireless powered forwarding relays.Comment: accepted in IEEE Globecom 201

Power Allocation for Conventional and Buffer-Aided Link Adaptive Relaying Systems with Energy Harvesting Nodes

Energy harvesting (EH) nodes can play an important role in cooperative communication systems which do not have a continuous power supply. In this paper, we consider the optimization of conventional and buffer-aided link adaptive EH relaying systems, where an EH source communicates with the destination via an EH decode-and-forward relay. In conventional relaying, source and relay transmit signals in consecutive time slots whereas in buffer-aided link adaptive relaying, the state of the source-relay and relay-destination channels determines whether the source or the relay is selected for transmission. Our objective is to maximize the system throughput over a finite number of transmission time slots for both relaying protocols. In case of conventional relaying, we propose an offline and several online joint source and relay transmit power allocation schemes. For offline power allocation, we formulate an optimization problem which can be solved optimally. For the online case, we propose a dynamic programming (DP) approach to compute the optimal online transmit power. To alleviate the complexity inherent to DP, we also propose several suboptimal online power allocation schemes. For buffer-aided link adaptive relaying, we show that the joint offline optimization of the source and relay transmit powers along with the link selection results in a mixed integer non-linear program which we solve optimally using the spatial branch-and-bound method. We also propose an efficient online power allocation scheme and a naive online power allocation scheme for buffer-aided link adaptive relaying. Our results show that link adaptive relaying provides performance improvement over conventional relaying at the expense of a higher computational complexity.Comment: Submitted to IEEE Transactions on Wireless Communication

How to Understand LMMSE Transceiver Design for MIMO Systems From Quadratic Matrix Programming

In this paper, a unified linear minimum mean-square-error (LMMSE) transceiver design framework is investigated, which is suitable for a wide range of wireless systems. The unified design is based on an elegant and powerful mathematical programming technology termed as quadratic matrix programming (QMP). Based on QMP it can be observed that for different wireless systems, there are certain common characteristics which can be exploited to design LMMSE transceivers e.g., the quadratic forms. It is also discovered that evolving from a point-to-point MIMO system to various advanced wireless systems such as multi-cell coordinated systems, multi-user MIMO systems, MIMO cognitive radio systems, amplify-and-forward MIMO relaying systems and so on, the quadratic nature is always kept and the LMMSE transceiver designs can always be carried out via iteratively solving a number of QMP problems. A comprehensive framework on how to solve QMP problems is also given. The work presented in this paper is likely to be the first shoot for the transceiver design for the future ever-changing wireless systems.Comment: 31 pages, 4 figures, Accepted by IET Communication