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

Joint Transceiver Optimization for Multiuser MIMO Relay Communication Systems

In this paper, we address the optimal source, relay, and receive matrices design for linear non-regenerative uplink multiuser multiple-input multiple-output (MIMO) relay communication systems. The minimum mean-squared error (MMSE) of the signal waveform estimation at the destination node is adopted as our design criterion. We develop two iterative methods to solve the highly nonconvex joint source, relay, and receiver optimization problem. In particular, we show that for given source precoding matrices, the optimal relay amplifying matrix diagonalizes the source-relay-destination channel. While for fixed relay matrix and source matrices of all other users, the source matrix of each user has a general beamforming structure. Simulation results demonstrate that the proposed iterative source and relay optimization algorithms perform much better than existing techniques in terms of both MSE and bit-error-rate

Hybrid Transceiver Optimization for Multi-Hop Communications

Multi-hop communication with the aid of large-scale antenna arrays will play a vital role in future emergence communication systems. In this paper, we investigate amplify-and-forward based and multiple-input multiple-output assisted multi-hop communication, in which all nodes employ hybrid transceivers. Moreover, channel errors are taken into account in our hybrid transceiver design. Based on the matrix-monotonic optimization framework, the optimal structures of the robust hybrid transceivers are derived. By utilizing these optimal structures, the optimizations of analog transceivers and digital transceivers can be separated without loss of optimality. This fact greatly simplifies the joint optimization of analog and digital transceivers. Since the optimization of analog transceivers under unit-modulus constraints is non-convex, a projection type algorithm is proposed for analog transceiver optimization to overcome this difficulty. Based on the derived analog transceivers, the optimal digital transceivers can then be derived using matrix-monotonic optimization. Numeral results obtained demonstrate the performance advantages of the proposed hybrid transceiver designs over other existing solutions.Comment: 32 pages, 6 figures. This manuscript has been submitted to IEEE Journal on Selected Areas in Communications (special issue on Multiple Antenna Technologies for Beyond 5G

Optimal Source and Relay Design for Multiuser MIMO AF Relay Communication Systems with Direct Links and Imperfect Channel Information

In this paper, we propose statistically robust design for multiuser multiple-input multiple-output (MIMO) relay systems with direct source-destination links and imperfect channel state information (CSI). The minimum mean-squared error (MMSE) of the signal waveform estimation at the destination node is adopted as the design criterion. We develop two iterative methods to solve the nonconvex joint source, relay, and receiver optimization problem. Simulation results demonstrate the improved robustness of the proposed algorithms against CSI errors

Linear Precoding Designs for Amplify-and-Forward Multiuser Two-Way Relay Systems

Two-way relaying can improve spectral efficiency in two-user cooperative communications. It also has great potential in multiuser systems. A major problem of designing a multiuser two-way relay system (MU-TWRS) is transceiver or precoding design to suppress co-channel interference. This paper aims to study linear precoding designs for a cellular MU-TWRS where a multi-antenna base station (BS) conducts bi-directional communications with multiple mobile stations (MSs) via a multi-antenna relay station (RS) with amplify-and-forward relay strategy. The design goal is to optimize uplink performance, including total mean-square error (Total-MSE) and sum rate, while maintaining individual signal-to-interference-plus-noise ratio (SINR) requirement for downlink signals. We show that the BS precoding design with the RS precoder fixed can be converted to a standard second order cone programming (SOCP) and the optimal solution is obtained efficiently. The RS precoding design with the BS precoder fixed, on the other hand, is non-convex and we present an iterative algorithm to find a local optimal solution. Then, the joint BS-RS precoding is obtained by solving the BS precoding and the RS precoding alternately. Comprehensive simulation is conducted to demonstrate the effectiveness of the proposed precoding designs.Comment: 13 pages, 12 figures, Accepted by IEEE TW

Multiuser Multihop MIMO Relay System Design Based on Mutual Information Maximization

In this paper, we consider multiuser multihop relay communication systems, where the users, relays, and the destination node may have multiple antennas. We address the issue of source and relay precoding matrices design to maximize the system mutual information (MI). By exploiting the linkbetween the maximal MI and the weighted minimal mean-squared error (WMMSE) objective functions, we show that the intractable maximal MI-based source and relay optimization problem can be solved via the WMMSE-based source and relay design through an iterative approach which is guaranteed toconverge to at least a stationary point. For the WMMSE problem, we derive the optimal structure of the relay precoding matrices and show that the WMMSE matrix at the destination node can be decomposed into the sum of WMMSE matrices at all hops. Under a (moderately) high signal-to-noise ratio (SNR) condition, this WMMSE matrix decomposition significantly simplifies the solution to the WMMSE problem. Numerical simulations are performed to demonstrate the effectiveness of the proposed algorithm

Iterative transceiver design for MIMO AF relay networks with multiple sources

This paper addresses the problem of transceiver design for an amplify-and-forward relay network with multiple sources, multiple relays and multiple destinations. Each node in the network is assumed to be equipped with multiple antennas. A general iterative algorithm is proposed based on convex quadratic optimization theory to minimize mean-square-error of the recovered signals at the destinations. Its convergence and extensions to other scenarios are also discussed. Finally, the effectiveness of the proposed iterative algorithm is demonstrated by computer simulations. ©2010 IEEE.published_or_final_versionThe IEEE Military Communications Conference (MILCOM 2010), San Jose, CA., 31 October-3 November 2010. In Proceedings of MILCOM, 2010, p. 369-37