User Selection for Multi-user MIMO Downlink with Zero-Forcing Beamforming

TL;DR

This paper introduces GUSS, a greedy user selection algorithm for multi-user MIMO downlink channels that improves sum rate performance by eliminating redundant users and escaping local optima, with manageable complexity.

Contribution

The paper proposes GUSS, a novel user selection algorithm with delete and swap operations, enhancing sum rate performance over existing methods like ZFS.

Findings

GUSS achieves 99.3% of the sum rate upper bound in simulations.

GUSS maintains similar complexity to ZFS with only linear additional cost.

GUSS outperforms existing algorithms in sum rate across various SNR levels.

Abstract

In this paper, we propose a greedy user selection with swap (GUSS) algorithm based on zero-forcing beamforming (ZFBF) for the multi-user multiple-input multiple-output (MIMO) downlink channels. Since existing user selection algorithms, such as the zero-forcing with selection (ZFS), have `redundant user' and `local optimum' flaws that compromise the achieved sum rate, GUSS adds `delete' and `swap' operations to the user selection procedure of ZFS to improve the performance by eliminating `redundant user' and escaping from `local optimum', respectively. In addition, an effective channel vector based effective-channel-gain updating scheme is presented to reduce the complexity of GUSS. With the help of this updating scheme, GUSS has the same order of complexity of ZFS with only a linear increment. Simulation results indicate that on average GUSS achieves 99.3 percent of the sum rate upper bound that is achieved by exhaustive search, over the range of transmit signal-to-noise ratios considered with only three to six times the complexity of ZFS.