Weighted MMSE Precoding for Constructive Interference Region

TL;DR

This paper introduces a novel symbol-level precoding scheme that leverages both channel state information and noise distribution to minimize weighted MSE within the constructive interference region, outperforming existing methods.

Contribution

It proposes a new SLP design using a generic CIR description and formulates it as an NNLS problem, unifying WMMSE and existing SLP as special cases.

Findings

Outperforms state-of-the-art SLP schemes across all SNR ranges

Efficient solution via active-set algorithm for NNLS problem

No additional complexity over conventional SLP

Abstract

In this paper, we propose a symbol-level precoding (SLP) design that aims to minimize the weighted mean square error between the received signal and the constellation point located in the constructive interference region (CIR). Unlike most existing SLP schemes that rely on channel state information (CSI) only, the proposed scheme exploits both CSI and the distribution information of the noise to achieve improved performance. We firstly propose a simple generic description of CIR that facilitates the subsequent SLP design. Such an objective can further be formulated as a nonnegative least squares (NNLS) problem, which can be solved efficiently by the active-set algorithm. Furthermore, the weighted minimum mean square error (WMMSE) precoding and the existing SLP can be easily verified as special cases of the proposed scheme. Finally, simulation results show that the proposed precoding outperforms the state-of-the-art SLP schemes in full signal-to-noise ratio ranges in both uncoded and coded systems without additional complexity over conventional SLP.