Low Complexity Robust Beamforming for Heterogeneous MIMO Rate-Splitting Multiple Access

Abstract

We propose a new two-stage, low-complexity, and robust beamforming (BF) method for heterogeneous MIMO rate splitting multiple access (RSMA) systems. In the proposed method, the phases and powers of the BF weights are designed separately, the first based on a tensor factorization of the channels between the base station (BS) and each user, and the second based on a fractional programming (FP) formulation of the power allocation problem, which is offered in three distinct variations, aimed as sum rate maximization (SRM), minimum rate maximization (MaxMin) and the maximization of the geometric-mean (GMean) of achievable rates, respectively. Thanks to the twostage approach, the proposed method is capable of delivering robustness to both channel state information (CSI) and successive interference cancellation (SIC) errors (incorporated in the phase design), at a low complexity compared to state-of-the-art (SotA) alternatives. Also thanks to the approach, the scheme naturally handles heterogeneity in terms of the number of antennas at each user, which can be arbitrarily distinct. Direct comparisons between SotA and the proposed schemes demonstrate that the contributed method generally outperforms the best alternative at comparable complexity, while approaching the best-performing SotA method of significantly higher complexity. In fact, the computational cost advantage of the proposed technique over the latter is quantified analytically and shown to be proportional to the cube of the number of BS antennas.