Low-Complexity QL-QR Decomposition Based Beamforming Design for Two-Way MIMO Relay Networks

TL;DR

This paper presents a low-complexity beamforming design for two-way MIMO relay networks using QL-QR decomposition, achieving reduced computational cost while maintaining BER performance comparable to SVD-based methods.

Contribution

It introduces an efficient iterative algorithm based on QL, QR, and Cholesky decompositions for joint source and relay beamforming, optimizing a determinant maximization problem.

Findings

Significantly reduces computational complexity.

Achieves BER performance comparable to SVD-based schemes.

Provides an effective solution for two-way MIMO relay systems.

Abstract

In this paper, we investigate the optimization problem of joint source and relay beamforming matrices for a twoway amplify-and-forward (AF) multi-input multi-output (MIMO) relay system. The system consisting of two source nodes and two relay nodes is considered and the linear minimum meansquare- error (MMSE) is employed at both receivers. We assume individual relay power constraints and study an important design problem, a so-called determinant maximization (DM) problem. Since this DM problem is nonconvex, we consider an efficient iterative algorithm by using an MSE balancing result to obtain at least a locally optimal solution. The proposed algorithm is developed based on QL, QR and Choleskey decompositions which differ in the complexity and performance. Analytical and simulation results show that the proposed algorithm can significantly reduce computational complexity compared with their existing two-way relay systems and have equivalent bit-error-rate (BER) performance to the singular value decomposition (SVD) based on a regular block diagonal (RBD) scheme.