In this paper, the problem of sum-rate maximization for an active reconfigurable intelligent surface (RIS) assisted downlink rate-splitting multiple access (RSMA) transmission system is studied. In the considered model, the active RIS is deployed to overcome severe power attenuation, which is caused by the cumulative product of RIS incidence path loss and the reflection path loss. Since the active RIS can adjust both the phase and the amplitude of the incident signal simultaneously, the RIS control scheme requires delicate design to improve RSMA communication performance. To address this issue, a sum-rate maximization problem is formulated to jointly optimize the beamforming vectors, rate allocation vector, and RIS precoding matrix. To solve this non-convex sum-rate maximization problem, an iterative algorithm based on fractional programming (FP) and quadratic constraint quadratic programming (QCQP) is proposed. In particular, the proposed algorithm firstly decomposes the original problem into two subproblems, namely, 1) beamforming and rate allocation optimization and 2) active RIS precoding optimization. The corresponding variables of the two subproblems are optimized through sequential convex approximation (SCA) and block coordinate descent (BCD), respectively. Numerical results show that the proposed active RIS-aided RSMA system could increase the sum-rate by up to 45% over the conventional passive RIS-aided RSMA system with the same energy consumption.

翻译：本文研究了一种有源可重构智能表面辅助的下行速率分裂多址传输系统中总速率最大化问题。在所考虑模型中，部署有源可重构智能表面旨在克服由可重构智能表面入射路径损耗与反射路径损耗累乘效应导致的严重功率衰减。由于有源可重构智能表面可同时调控入射信号的相位与幅度，其控制方案需精密设计以提升速率分裂多址通信性能。针对该问题，本文建立了一个总速率最大化优化模型，需联合优化波束成形矢量、速率分配矢量及可重构智能表面预编码矩阵。为求解此非凸的总速率最大化问题，提出了一种基于分数规划与二次约束二次规划的迭代算法。该算法首先将原始问题分解为两个子问题：1）波束成形与速率分配联合优化；2）有源可重构智能表面预编码优化。两个子问题的变量分别通过序列凸近似与块坐标下降法进行优化。数值结果表明，在相同能耗条件下，所提有源可重构智能表面辅助的速率分裂多址系统相较于传统无源可重构智能表面辅助的速率分裂多址系统，总速率可提升高达45%。