Reconfigurable intelligent surface (RIS) has been regarded as a promising technique due to its high array gain and low power. However, the traditional passive RIS suffers from the ``double fading'' effect, which has restricted the performance of passive RIS-aided communications. Fortunately, active RIS can alleviate this problem since it can adjust the phase shift and amplify the received signal simultaneously. Nevertheless, a high beamforming gain often requires a number of reflecting elements, which leads to non-negligible power consumption, especially for the active RIS. Thus, one challenge is how to improve the scalability of the RIS and the energy efficiency. Different from the existing works where all reflecting elements are activated, we propose a novel element on-off mechanism where reflecting elements can be flexibly activated and deactivated. Two different optimization problems for passive RIS and active RIS are formulated by maximizing the total energy efficiency. We develop two different alternating optimization-based iterative algorithms to obtain sub-optimal solutions. Furthermore, we consider special cases involving rate maximization problems for given the same total power budget, and respectively analyze the number configuration for passive RIS and active RIS. Simulation results verify that reflecting elements under the proposed algorithms can be flexibly activated and deactivated.

翻译：可重构智能表面（RIS）由于具有高阵列增益和低功率而被视为一种有前途的技术。然而，传统的被动RIS遭受了“双重衰落”的影响，这限制了被动RIS辅助通信的性能。幸运的是，主动RIS可以缓解这个问题，因为它可以同时调整相位移位并放大接收到的信号。然而，高波束成型增益往往需要多个反射元素，这导致了不可忽视的能量消耗，尤其对于主动RIS。因此，一个挑战是如何提高RIS的可扩展性和能量效率。与现有作品不同，我们提出了一种新的元素开关机制，其中反射元素可以灵活地被激活和停用。通过最大化总能量效率，分别为被动RIS和主动RIS制定了两个不同的优化问题。我们开发了两个不同的基于交替优化的迭代算法来获得次优解。此外，我们考虑了特殊情况，涉及为给定相同总功率预算的传输速率最大化问题，并分别分析了被动RIS和主动RIS的数量配置。仿真结果证实，按照所提出算法处理的反射元素可以灵活激活和停用。