Efficient MMSE Receiver Design for MU-MIMO Systems With Symbol-Level Precoding

Abstract

Symbol-level precoding (SLP) can achieve remarkable gains in multi-user multiple-input-single-output (MU-MISO) systems, while its extension to multi-user multiple-input-multiple-output (MU-MIMO) systems offers even greater potential by exploiting the spatial dimensions at both the transmitter and receiver. However, existing MU-MIMO SLP designs require symbol-dependent receive combining matrices or rely on alternating iterative optimization, resulting in high signaling overhead and complexity. To overcome these limitations, this letter revisits the receiver design for SLP-based MU-MIMO systems from a minimum mean square error (MMSE) perspective. By explicitly exploiting the rank-one structure of the effective channel induced by SLP, it is proven that the MMSE-optimal linear receiver admits a simple matched-filter form with low computational complexity. Furthermore, it is analytically demonstrated that the conventional regularized MMSE (RMMSE) receiver yields identical decoding performance for any choice of the regularization factor under SLP transmission. Simulation results validate the theoretical analysis and demonstrate that the proposed receiver structures achieve superior performance with substantially reduced complexity compared to existing approaches.