Optimized Beamforming for Multi-Antenna Downlink NOMA With Low-Resolution DACs and ADCs

Non-orthogonal multiple access (NOMA) has emerged as a promising technique for enabling massive connectivity and enhancing spectral efficiency. However, the adoption of low-resolution digital-to-analog converters and analog-to-digital converters in practical systems introduces significant quantization errors, posing challenges for system performance. This paper proposes a novel beamforming design for downlink NOMA systems that accounts for quantization errors caused by low-resolution converters. Leveraging the additive quantization noise model, we derive an expression for the signal-to-interference-plus-noise ratio (SINR) of each user and formulate a power minimization problem under SINR-based quality-of-service constraints. To simplify the problem, we introduce a relaxation method that enables a solution using the Karush-Kuhn-Tucker conditions, leading to near-optimal beamforming vectors. Simulation results reveal that the proposed scheme achieves significant improvements in sum spectral efficiency compared to existing approaches for space-division multiple access and rate-splitting multiple access under identical converters and power constraints, demonstrating its potential for energy-efficient NOMA system design.