Simultaneously transmitting and reflecting \textcolor{black}{reconfigurable intelligent surface} (STAR-RIS) is a promising implementation of RIS-assisted systems that enables full-space coverage. However, STAR-RIS as well as conventional RIS suffer from the double-fading effect. Thus, in this paper, we propose the marriage of active RIS and STAR-RIS, denoted as ASTARS for massive multiple-input multiple-output (mMIMO) systems, and we focus on the energy splitting (ES) and mode switching (MS) protocols. Compared to prior literature, we consider the impact of correlated fading, and we rely our analysis on the two timescale protocol, being dependent on statistical channel state information (CSI). On this ground, we propose a channel estimation method for ASTARS with reduced overhead that accounts for its architecture. Next, we derive a \textcolor{black}{closed-form expression} for the achievable sum-rate for both types of users in the transmission and reflection regions in a unified approach with significant practical advantages such as reduced complexity and overhead, which result in a lower number of required iterations for convergence compared to an alternating optimization (AO) approach. Notably, we maximize simultaneously the amplitudes, the phase shifts, and the active amplifying coefficients of the ASTARS by applying the projected gradient ascent method (PGAM). Remarkably, the proposed optimization can be executed at every several coherence intervals that reduces the processing burden considerably. Simulations corroborate the analytical results, provide insight into the effects of fundamental variables on the sum achievable SE, and present the superiority of 16 ASTARS compared to passive STAR-RIS for a practical number of surface elements.

翻译：同时传输与反射可重构智能表面（STAR-RIS）是实现全空间覆盖的RIS辅助系统的一种有前景方案。然而，STAR-RIS与常规RIS均面临双重衰落效应的影响。为此，本文针对大规模多输入多输出（mMIMO）系统，提出将主动RIS与STAR-RIS相融合的方案（记为ASTARS），并重点研究能量分裂（ES）与模式切换（MS）两种协议。相较于现有文献，我们考虑相关衰落的影响，并基于统计信道状态信息（CSI）的双时间尺度协议进行分析。在此基础上，我们提出一种适用于ASTARS架构且开销更低的信道估计方法。随后，我们以统一方法推导出传输区与反射区两类用户可达和速率的闭式表达式，该方法具有显著的实际优势，例如相较于交替优化（AO）方法，可降低复杂度与开销，从而减少收敛所需的迭代次数。值得注意的是，我们采用投影梯度上升法（PGAM）同时最大化ASTARS的幅度、相移与主动放大系数。该优化方案可在数个相干间隔内执行一次，大幅降低处理负担。仿真结果验证了理论分析，揭示了关键变量对总可达频谱效率的影响，并在实际表面单元数量下展示了16单元ASTARS相较于无源STAR-RIS的优越性能。