Beamforming Optimization for Full-Duplex Wireless-powered MIMO Systems

We propose techniques for optimizing transmit beamforming in a full-duplex multiple-input-multiple-output (MIMO) 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 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.Comment: 14 pages, accepte

Energy Efficient Delay Sensitive Optimization in SWIPT-MIMO

In this paper, we consider joint antenna selection and optimal beamforming for energy efficient delay minimization. We assume multiple-input multi-output (MIMO) system with full duplex simultaneous wireless information and power transfer (FD-SWIPT) where each sensor is equipped with a power splitting (PS) system and can simultaneously receive both energy and information from the aggregator (AGG). We show that the antenna selection and beamforming power control policies are adaptive to the energy state information (ESI), the queue state information (QSI) and the channel state information (CSI). We develop an analytical framework for energy efficient delay-optimal control problem based on the theory of infinite horizon partially observable Markov decision process (POMDP). The infinite-horizon POMDP problem is transformed into an equivalent value Bellman program and solved by near-optimal point-based Heuristic Search Value Iteration (PB-HSVI) method under specific standard conditions. The proposed solution outcome is a set of sub-optimal antenna selection and beamforming control policies. Simulation results reveal an effective trade-off between the contradictory objectives (i.e. delay and power consumption) and show the enhancement in delay by using FD-SWIPT systems in comparison to Half Duplex (HD)-SWIPT systems