Simultaneous transmission and reflection-reconfigurable intelligent surface (STAR-RIS) can provide expanded coverage compared with the conventional reflection-only RIS. This paper exploits the energy efficient potential of STAR-RIS in a multiple-input and multiple-output (MIMO) enabled non-orthogonal multiple access (NOMA) system. Specifically, we mainly focus on energy-efficient resource allocation with MIMO technology in the STAR-RIS assisted NOMA network. To maximize the system energy efficiency, we propose an algorithm to optimize the transmit beamforming and the phases of the low-cost passive elements on the STAR-RIS alternatively until the convergence. Specifically, we first decompose the formulated energy efficiency problem into beamforming and phase shift optimization problems. To efficiently address the non-convex beamforming optimization problem, we exploit signal alignment and zero-forcing precoding methods in each user pair to decompose MIMO-NOMA channels into single-antenna NOMA channels. Then, the Dinkelbach approach and dual decomposition are utilized to optimize the beamforming vectors. In order to solve non-convex phase shift optimization problem, we propose a successive convex approximation (SCA) based method to efficiently obtain the optimized phase shift of STAR-RIS. Simulation results demonstrate that the proposed algorithm with NOMA technology can yield superior energy efficiency performance over the orthogonal multiple access (OMA) scheme and the random phase shift scheme.
翻译:同时传输和可重构智能面(STAR-RIS)可提供比传统反射式可重构智能面(RIS)更广泛的覆盖范围。本文利用STAR-RIS在多输入多输出(MIMO)启用的非正交多址接入(NOMA)系统中的节能潜力。具体而言,我们主要关注MIMO技术在STAR-RIS辅助的NOMA网络中的能量有效资源分配。为了最大限度地提高系统能量效率,我们提出了一种算法,以交替优化发送波束成形和STAR-RIS上的低成本被动元件的相位,直到收敛。具体而言,我们首先将所制定的能量效率问题分解为波束成形和相移优化问题。为了高效地解决非凸波束成形优化问题,我们利用信号对齐和零强制预编码方法,在每个用户对中将MIMO-NOMA信道分解为单天线NOMA信道。然后,我们利用Dinkelbach方法和双重分解来优化波束成形向量。为了解决非凸相移优化问题,我们提出了基于连续凸逼近(SCA)的方法,以高效地获得STAR-RIS的优化相移。仿真结果表明,在NOMA技术下,所提出的算法比正交多址接入(OMA)方案和随机相移方案具有更高的能量效率表现。