Joint Optimization for Active IRS-Aided Multicluster NOMA Systems
Qi Zhai, Limeng Dong, Wei Cheng, Yong Li, Penglu Liu
Abstract
This article investigates an active intelligent reflecting surface (IRS)-aided multicluster nonorthogonal multiple access network under imperfect successive interference cancellation (ipSIC). We formulate a power minimization problem by jointly optimizing the beamforming vector at the base station and the reflecting matrix at the IRS under the quality-of-service requirement and SIC decoding condition. An efficient algorithm based on alternating optimization is proposed to solve the nonconvex problem. Specifically, the beamforming matrix and reflecting matrix are optimized alternately by successive convex approximation and convex upper bound substitution methods. Through simulations, we verify the superiority of the proposed solution and illustrate the impact of ipSIC on the system performance.