This chapter delves into the critical aspects of optimizing energy efficiency (EE) in active reconfigurable intelligent surface (RIS)-assisted massive MIMO (M-MIMO) wireless communication systems. We develop a comprehensive and unified theoretical framework to analyze the boundaries of EE within M-MIMO systems integrated with active RIS while adhering to practical constraints. Our research focuses on a formulated EE optimization problem aiming to maximize the EE for active RIS-assisted M-MIMO communication systems. Our goal is to strategically find the number of active RIS elements for outperforming the EE attainable by an entirely passive RIS. Besides, the proposed novel solution has been tailored to the innovative problem. The formulation and solution design consider analytical optimization techniques, such as lagrangian dual transform (LDT) and fractional programming (FP) optimization, facilitating the effective implementation of RIS-aided M-MIMO applications in real-world settings. In particular, our results show that the proposed algorithm can provide up to 120% higher EE than the entirely passive RIS. Besides, we found that the active RIS can operate with less than half of the reflecting elements for the entirely passive RIS. Finally, in view of active RIS achieving the complete utilization of amplification power available, it should be equipped with a reasonable number of reflecting elements above N = 49.

翻译：本章深入探讨了优化有源可重构智能表面（RIS）辅助大规模MIMO（M-MIMO）无线通信系统能效（EE）的关键问题。我们构建了一个全面且统一的理论框架，用于分析在满足实际约束条件下，集成有源RIS的M-MIMO系统能效边界。本研究聚焦于一个以最大化有源RIS辅助M-MIMO通信系统能效为目标的优化问题，旨在通过策略性地确定有源RIS元件数量，使其能效超越全无源RIS。此外，我们针对这一创新问题设计了新颖的解决方案。该方案的设计融合了拉格朗日对偶变换（LDT）和分数规划（FP）优化等分析优化技术，从而有效支撑RIS辅助M-MIMO系统在实际场景中的部署。特别地，实验结果表明，所提算法相比全无源RIS可提供高达120%的能效提升。同时，我们发现，有源RIS仅需使用少于半数的反射元件即可达到全无源RIS的性能。最后，考虑到有源RIS需充分利用可用放大功率，其反射元件数量应合理配置在N=49以上。