Symbol-Level Precoding for MU-MIMO System with RIRC Receiver

This paper addresses the design of the receive combining matrix in a multiuser multiple-input multiple-output (MU-MIMO) downlink system, where the base station (BS) employs symbol-level precoding (SLP) to transmit multiple data streams to multiple users with multiple antennas. Unlike in the single-antenna user scenario, the design of the receive combining matrix becomes crucial in this context. To overcome the challenge of the receive combining matrix's dependency on the transmit signals, we propose a practical scheme utilizing the interference rejection combiner (IRC) for signal decoding. However, directly applying the IRC receiver to the considered MU-MIMO system presents challenges due to the rank-one transmit precoding matrix. To address this issue, we propose a new regularized IRC (RIRC) receiver. The problem is tackled by using the alternating optimization (AO) method, enabling the derivation of an optimal solution structure for the transmit precoding matrix. Numerical results demonstrate the substantial performance gain of the practical SLP scheme with the RIRC receiver over conventional Block Diagonalization (BD) based approach.

I. Introduction

Precoding methods have been extensively studied in the context of multiuser multiple-input multiple-output (MU-MIMO) systems. These methods aim to enhance communication performance by mitigating interference among channels and users [1]–[3]. Traditional precoding techniques include zero-forcing (ZF) [4], regularized zero-forcing (RZF) [5], block diagonalization (BD) [6], regularized block diagonal-ization (RBD) [7], and optimization-based schemes [8], [9]. These methods are categorized as block-level precoding (BLP) schemes. However, it is important to note that these approaches overlook the potential benefits and exploitation of interference at the symbol level.