This is the first treatise on multi-user (MU) beamforming designed for achieving long-term rate-fairness in fulldimensional MU massive multi-input multi-output (m-MIMO) systems. Explicitly, based on the channel covariances, which can be assumed to be known beforehand, we address this problem by optimizing the following objective functions: the users' signal-toleakage-noise ratios (SLNRs) using SLNR max-min optimization, geometric mean of SLNRs (GM-SLNR) based optimization, and SLNR soft max-min optimization. We develop a convex-solver based algorithm, which invokes a convex subproblem of cubic time-complexity at each iteration for solving the SLNR maxmin problem. We then develop closed-form expression based algorithms of scalable complexity for the solution of the GMSLNR and of the SLNR soft max-min problem. The simulations provided confirm the users' improved-fairness ergodic rate distributions.
@article{arxiv.2312.05557,
title = {Long-Term Rate-Fairness-Aware Beamforming Based Massive MIMO Systems},
author = {W. Zhu and H. D. Tuan and E. Dutkiewicz and Y. Fang and H. V. Poor and L. Hanzo},
journal= {arXiv preprint arXiv:2312.05557},
year = {2023}
}