Joint Transceiver Design Algorithms for Multiuser MISO Relay Systems with Energy Harvesting

In this paper, we investigate a multiuser relay system with simultaneous wireless information and power transfer. Assuming that both base station (BS) and relay station (RS) are equipped with multiple antennas, this work studies the joint transceiver design problem for the BS beamforming vectors, the RS amplify-and-forward transformation matrix and the power splitting (PS) ratios at the single-antenna receivers. Firstly, an iterative algorithm based on alternating optimization (AO) and with guaranteed convergence is proposed to successively optimize the transceiver coefficients. Secondly, a novel design scheme based on switched relaying (SR) is proposed that can significantly reduce the computational complexity and overhead of the AO based designs while maintaining a similar performance. In the proposed SR scheme, the RS is equipped with a codebook of permutation matrices. For each permutation matrix, a latent transceiver is designed which consists of BS beamforming vectors, optimally scaled RS permutation matrix and receiver PS ratios. For the given CSI, the optimal transceiver with the lowest total power consumption is selected for transmission. We propose a concave-convex procedure based and subgradient-type iterative algorithms for the non-robust and robust latent transceiver designs. Simulation results are presented to validate the effectiveness of all the proposed algorithms

MIMO Transmission for Single-fed ESPAR with Quantized Loads

Compact parasitic arrays in the form of electronically steerable parasitic antenna radiators (ESPARs) have emerged as a new antenna structure that achieves multipleinput- multiple-output (MIMO) transmission with a single RF chain. In this paper, we study the application of precoding on practical ESPARs, where the antennas are equipped with load impedances of quantized values. We analytically study the impact of the quantization on the system performance, where it is shown that while ideal ESPARs with ideal loads can achieve a similar performance to conventional MIMO, the performance of ESPARs will be degraded when only loads with quantized values are available. We further extend the performance analysis to imperfect channel state information (CSI). In order to alleviate the performance loss, we propose to approximate the ideal current vector by optimization, where a closed-form solution is further obtained. This enables the use of ESPARs in practice with quantized loads. Simulation results validate our analysis and show that a significant performance gain can be achieved with the proposed scheme over ESPARs with quantized loads. Finally, the tradeoff between performance and power consumption is shown to be favorable for the proposed ESPAR approaches compared to conventional MIMO, as evidenced by our energy efficiency results