Team Precoding Towards Scalable Cell-free Massive MIMO Networks

TL;DR

This paper introduces a scalable TMMSE precoding scheme for user-centric cell-free massive MIMO networks with partial message sharing, improving spectral efficiency in industrial IoT scenarios.

Contribution

It extends TMMSE precoding to partial message sharing, enabling scalable, efficient precoding for user-centric cell-free networks with multiple radio stripes.

Findings

TMMSE precoding outperforms competing schemes in spectral efficiency.

The proposed scheme is effective under various power constraints.

Numerical results validate the approach in industrial IoT scenarios.

Abstract

In a recent work, we studied a novel precoding design for cell-free networks called team minimum mean-square error (TMMSE) precoding, which rigorously generalizes centralized MMSE precoding to distributed operations based on transmitter-specific channel state information (CSI). Despite its flexibility in handling different cooperation regimes at the CSI sharing level, TMMSE precoding assumes network-wide sharing of the data bearing signals, and hence it is inherently not scalable. In this work, inspired by recent advances on scalable cell-free architectures based on user-centric network clustering techniques, we address this issue by proposing a novel version of the TMMSE precoding design covering partial message sharing. The obtained framework is then successfully applied to derive a variety of novel, optimal, and efficient precoding schemes for a user-centric cell-free network deployed using multiple radio stripes. Numerical simulations of a typical industrial internet-of-things scenario corroborate the gains of TMMSE precoding over competing schemes in terms of spectral efficiency under different power constraints. Although presented in the context of downlink precoding, the results of this paper may be applied also on the uplink.