Compute-and-Forward in Cell-Free Massive MIMO: Great Performance with Low Backhaul Load

TL;DR

This paper demonstrates that compute-and-forward significantly enhances throughput and reduces backhaul load in cell-free massive MIMO systems with realistic channel conditions.

Contribution

It introduces a low complexity coefficient selection algorithm for C&F and compares its performance with other strategies in realistic dense networks.

Findings

C&F reduces backhaul load effectively.

C&F significantly increases system throughput.

Proposed algorithms outperform existing methods in simulations.

Abstract

In this paper, we consider the uplink of cell-free massive MIMO systems, where a large number of distributed single antenna access points (APs) serve a much smaller number of users simultaneously via limited backhaul. For the first time, we investigate the performance of compute-and-forward (C&F) in such an ultra dense network with a realistic channel model (including fading, pathloss and shadowing). By utilising the characteristic of pathloss, a low complexity coefficient selection algorithm for C\&F is proposed. We also give a greedy AP selection method for message recovery. Additionally, we compare the performance of C&F to some other promising linear strategies for distributed massive MIMO, such as small cells (SC) and maximum ratio combining (MRC). Numerical results reveal that C&F not only reduces the backhaul load, but also significantly increases the system throughput for the symmetric scenario.