Robust beamforming design for NOMA system assisted by STAR-RIS
TL;DR
Numerical results show that the proposed impairment-aware STAR-RIS-NOMA design achieves higher sum rates and lower bit error rates than the considered hardware-impairment-unaware benchmarks.
Abstract
This study investigates the distortion noise and performance degradation caused by residual transmit-side hardware impairments at the base station (BS) and develops an impairment-aware design to improve system robustness. To this end, this paper considers a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-assisted non-orthogonal multiple access (NOMA) system that extends coverage from half-space to full-space. A location-based matching algorithm is developed for subchannel assignment, pairing transmission-region and reflection-region users on each subchannel and determining the decoding order according to their effective channel gains. Furthermore, an alternating optimization framework is developed to optimize the active beamforming vectors via successive convex approximation (SCA), the STAR-RIS transmission/reflection coefficients via the convex upper-bound (CUB) method, and the NOMA power-allocation coefficients via geometric programming (GP). Numerical results show that the proposed impairment-aware STAR-RIS-NOMA design achieves higher sum rates and lower bit error rates than the considered hardware-impairment-unaware benchmarks.