Active reconfigurable intelligent surface (RIS) is a new RIS architecture that can reflect and amplify communication signals. It can provide enhanced performance gain compared to the conventional passive RIS systems that can only reflect the signals. On the other hand, the design problem of active RIS-aided systems is more challenging than the passive RIS-aided systems and its efficient algorithms are less studied. In this paper, we consider the sum rate maximization problem in the multiuser massive multiple-input single-output (MISO) downlink with the aid of a large-scale active RIS. Existing approaches usually resort to general optimization solvers and can be computationally prohibitive in the considered settings. We propose an efficient block successive upper bound minimization (BSUM) method, of which each step has a (semi) closed-form update. Thus, the proposed algorithm has an attractive low per-iteration complexity. By simulation, our proposed algorithm consumes much less computation than the existing approaches. In particular, when the MIMO and/or RIS sizes are large, our proposed algorithm can be orders-of-magnitude faster than existing approaches.

翻译：有源可重构智能表面（RIS）是一种新型RIS架构，能够反射并放大通信信号。与仅能反射信号的传统无源RIS系统相比，该架构可提供更优的性能增益。然而，有源RIS辅助系统的设计问题比无源RIS辅助系统更具挑战性，其高效算法的研究尚不充分。本文研究基于大规模有源RIS辅助的多用户大规模多输入单输出（MISO）下行链路中的和速率最大化问题。现有方法通常依赖通用优化求解器，在本文所考虑的场景下计算代价极高。我们提出一种高效的块连续上界最小化（BSUM）方法，其每一步更新均具有（半）闭式解，因此所提算法具备单次迭代复杂度低的优势。仿真结果表明，所提算法的计算量远低于现有方法。特别地，当MIMO和/或RIS规模较大时，所提算法的运行速度可比现有方法快数个数量级。