Team-Optimal MMSE Combining for Cell-Free Massive MIMO Systems

TL;DR

This paper introduces a novel team-based MMSE combining method for cell-free massive MIMO systems that reduces CSI sharing costs with minimal spectral efficiency loss, enhancing cooperative communication.

Contribution

It develops a new unidirectional TMMSE scheme based on team theory, balancing CSI sharing costs and spectral efficiency in cell-free massive MIMO systems.

Findings

Unidirectional TMMSE nearly halves CSI sharing costs compared to centralized schemes.

Performance gap decreases with more APs and antennas per AP.

The proposed methods effectively handle channel estimation errors and pilot contamination.

Abstract

Cell-free (CF) massive multiple-input multiple-output (MIMO) systems are expected to implement advanced cooperative communication techniques to let geographically distributed access points jointly serve user equipments. Building on the \emph{Team Theory}, we design the uplink team minimum mean-squared error (TMMSE) combining under limited data and flexible channel state information (CSI) sharing. Taking into account the effect of both channel estimation errors and pilot contamination, a minimum MSE problem is formulated to derive unidirectional TMMSE, centralized TMMSE and statistical TMMSE combining functions, where CF massive MIMO systems operate in unidirectional CSI, centralized CSI and statistical CSI sharing schemes, respectively. We then derive the uplink spectral efficiency (SE) of the considered system. The results show that, compared to centralized TMMSE, the unidirectional TMMSE only needs nearly half the cost of CSI sharing burden with neglectable SE performance loss. Moreover, the performance gap between unidirectional and centralized TMMSE combining schemes can be effectively reduced by increasing the number of APs and antennas per AP.