Iteratively Weighted MMSE Uplink Precoding for Cell-Free Massive MIMO

TL;DR

This paper proposes an iterative weighted MMSE precoding method for uplink in cell-free massive MIMO systems, enhancing spectral efficiency by optimizing precoding based on channel statistics with a two-layer decoding structure.

Contribution

It introduces a novel I-WMMSE precoding algorithm for uplink spectral efficiency maximization in cell-free massive MIMO systems using only channel statistics.

Findings

I-WMMSE precoding achieves high sum spectral efficiency.

Derived closed-form optimal precoding structures with MR combining.

Numerical results confirm the effectiveness of the proposed method.

Abstract

In this paper, we investigate a cell-free massive MIMO system with both access points and user equipments equipped with multiple antennas over the Weichselberger Rayleigh fading channel. We study the uplink spectral efficiency (SE) based on a two-layer decoding structure with maximum ratio (MR) or local minimum mean-square error (MMSE) combining applied in the first layer and optimal large-scale fading decoding method implemented in the second layer, respectively. To maximize the weighted sum SE, an uplink precoding structure based on an Iteratively Weighted sum-MMSE (I-WMMSE) algorithm using only channel statistics is proposed. Furthermore, with MR combining applied in the first layer, we derive novel achievable SE expressions and optimal precoding structures in closed-form. Numerical results validate our proposed results and show that the I-WMMSE precoding can achieve excellent sum SE performance.