Throughput maximization for full-duplex energy harvesting MIMO communications

© 2016 IEEE.This paper proposes methods for optimizing bidirectional information rates between a base station (BS) and a wirelessly powered mobile station (MS). In the first phase, the MS harvests energy using signals transmitted by the BS, whereas in the second phase both the BS and MS communicate to each other in a full-duplex mode. The BS-beamformer and the time-splitting parameter (TSP) of energy harvesting scheme are jointly optimized to obtain the BS-MS rate region. The joint optimization is non-convex, however a computationally efficient optimum technique based upon semidefinite relaxation and line-search is proposed to solve the problem. Moreover, a suboptimum approach based upon the zero-forcing (ZF) beamformer constraint is also proposed. In this case, a closed-form solution of TSP is obtained. Simulation results demonstrate the advantage of the optimum method over the suboptimum method, especially for smaller values of BS transmit power and number of transmit antennas at the BS

Throughput maximization for full-duplex energy harvesting MIMO communications

© 2016 IEEE.This paper proposes methods for optimizing bidirectional information rates between a base station (BS) and a wirelessly powered mobile station (MS). In the first phase, the MS harvests energy using signals transmitted by the BS, whereas in the second phase both the BS and MS communicate to each other in a full-duplex mode. The BS-beamformer and the time-splitting parameter (TSP) of energy harvesting scheme are jointly optimized to obtain the BS-MS rate region. The joint optimization is non-convex, however a computationally efficient optimum technique based upon semidefinite relaxation and line-search is proposed to solve the problem. Moreover, a suboptimum approach based upon the zero-forcing (ZF) beamformer constraint is also proposed. In this case, a closed-form solution of TSP is obtained. Simulation results demonstrate the advantage of the optimum method over the suboptimum method, especially for smaller values of BS transmit power and number of transmit antennas at the BS

Beamforming optimization for full-duplex wireless-powered MIMO systems

We propose techniques for optimizing transmit beamforming in a full-duplex multiple-input-multiple-output wireless-powered communication system, which consists of two phases. In the first phase, the wireless-powered mobile station (MS) harvests energy using signals from the base station (BS), whereas in the second phase, both MS and BS communicate to each other in a full-duplex mode. When complete instantaneous channel state information (CSI) is available, the BS beamformer and the time-splitting (TS) parameter of energy harvesting are jointly optimized in order to obtain the BS-MS rate region. The joint optimization problem is non-convex, however, a computationally efficient optimum technique, based upon semidefinite relaxation and line-search, is proposed to solve the problem. A sub-optimum zero-forcing approach is also proposed, in which a closed-form solution of TS parameter is obtained. When only the second-order statistics of transmit CSI is available, we propose to maximize the ergodic information rate at the MS while maintaining the outage probability at the BS below a certain threshold. An upper bound for the outage probability is also derived and an approximate convex optimization framework is proposed for efficiently solving the underlying non-convex problem. Simulations demonstrate the advantages of the proposed methods over the sub-optimum and half-duplex ones

Throughput analysis and optimization of wireless-powered multiple antenna full-duplex relay systems

© 2016 IEEE.We consider a full-duplex (FD) decode-and-forward system in which the time-switching protocol is employed by the multiantenna relay to receive energy from the source and transmit information to the destination. The instantaneous throughput is maximized by optimizing receive and transmit beamformers at the relay and the time-split parameter. We study both optimum and suboptimum schemes. The reformulated problem in the optimum scheme achieves closed-form solutions in terms of transmit beamformer for some scenarios. In other scenarios, the optimization problem is formulated as a semidefinite relaxation problem and a rank-one optimum solution is always guaranteed. In the suboptimum schemes, the beamformers are obtained using maximum ratio combining, zero-forcing, and maximum ratio transmission. When beamformers have closed-form solutions, the achievable instantaneous and delay-constrained throughput are analytically characterized. Our results reveal that beamforming increases both the energy harvesting and loop interference suppression capabilities at the FD relay.Moreover, simulation results demonstrate that the choice of the linear processing scheme as well as the time-split plays a critical role in determining the FD gains