Precoding and Power Optimization in Cell-Free Massive MIMO Systems

TLDR

Cell‑free Massive MIMO employs many distributed low‑power single‑antenna access points connected to a central controller, with more AP antennas than users, and serves each user with all APs simultaneously without cell partitioning. The study investigates max‑min power control to equalize throughput across users in this architecture. The authors analyze conjugate beamforming and zero‑forcing precoders, devise a near‑optimal power‑control algorithm for zero‑forcing that is simpler than exact max‑min, and also develop power‑optimization schemes for small‑cell operation. They find that most APs transmit below full power, zero‑forcing markedly outperforms conjugate beamforming, and cell‑free Massive MIMO delivers a five‑to‑ten‑fold increase in 95%-likely per‑user throughput compared to small‑cell operation.

Abstract

Cell-free Massive multiple-input multiple-output (MIMO) comprises a large number of distributed low-cost low-power single antenna access points (APs) connected to a network controller. The number of AP antennas is significantly larger than the number of users. The system is not partitioned into cells and each user is served by all APs simultaneously. The simplest linear precoding schemes are conjugate beamforming and zero-forcing. Max-min power control provides equal throughput to all users and is considered in this paper. Surprisingly, under max-min power control, most APs are found to transmit at less than full power. The zero-forcing precoder significantly outperforms conjugate beamforming. For zero-forcing, a near-optimal power control algorithm is developed that is considerably simpler than exact max-min power control. An alternative to cell-free systems is small-cell operation in which each user is served by only one AP for which power optimization algorithms are also developed. Cell-free Massive MIMO is shown to provide five- to ten-fold improvement in 95%-likely per-user throughput over small-cell operation.