Optimal Transmit Power and Channel-Information Bit Allocation With Zeroforcing Beamforming in MIMO-NOMA and MIMO-OMA Downlinks

TL;DR

This paper develops optimal power and channel information bit allocation schemes for MIMO downlinks using zeroforcing beamforming, enhancing fairness and performance in NOMA and OMA systems, with practical grouping and approximation methods.

Contribution

It introduces a geometric programming approach for optimal resource allocation and proposes user grouping and progressive filling schemes to reduce computational complexity.

Findings

NOMA can outperform OMA by up to 3 dB in certain regimes.

Performance gain increases with higher correlation-coefficient thresholds.

Proposed grouping and approximation methods significantly reduce computation time.

Abstract

In downlink, a base station (BS) with multiple transmit antennas applies zeroforcing beamforming to transmit to single-antenna mobile users in a cell. We propose the schemes that optimize transmit power and the number of bits for channel direction information (CDI) for all users to achieve the max-min signal-to-interference plus noise ratio (SINR) fairness. The optimal allocation can be obtained by a geometric program for both non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA). For NOMA, 2 users with highly correlated channels are paired and share the same transmit beamforming. In some small total-CDI rate regimes, we show that NOMA can outperform OMA by as much as 3 dB. The performance gain over OMA increases when the correlation-coefficient threshold for user pairing is set higher. To reduce computational complexity, we propose to allocate transmit power and CDI rate to groups of multiple users instead of individual users. The user grouping scheme is based on K-means over the user SINR. We also propose a progressive filling scheme that performs close to the optimum, but can reduce the computation time by almost 3 orders of magnitude in some numerical examples.