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

TL;DR

This paper proposes efficient linear precoding strategies for multiuser two-way relay systems to optimize uplink performance and manage interference, using convex optimization and iterative algorithms, validated through simulations.

Contribution

It introduces novel linear precoding designs for multiuser two-way relay systems, including a convex optimization approach for BS precoding and an iterative method for RS precoding.

Findings

Optimal BS precoding can be obtained via SOCP.

Iterative algorithm effectively finds local RS precoding solutions.

Proposed methods improve uplink performance and interference management.

Abstract

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.