Reconfigurable intelligent surface (RIS) is a promising candidate technology of the upcoming Sixth Generation (6G) communication system for its ability to provide unprecedented spectral and energy efficiency increment through passive beamforming. However, it is challenging to obtain instantaneous channel state information (I-CSI) for RIS, which obliges us to use statistical channel state information (S-CSI) to achieve passive beamforming. In this paper, RIS-aided multiple-input single-output (MISO) multi-user downlink communication system with correlated channels is investigated. Then, we formulate the problem of joint beamforming design at the AP and RIS to maximize the sum ergodic spectral efficiency (ESE) of all users to improve the network capacity. Since it is too hard to compute sum ESE, an ESE approximation is adopted to reformulate the problem into a more tractable form. Then, we present two joint beamforming algorithms, namely the singular value decomposition-gradient descent (SVD-GD) algorithm and the fractional programming-gradient descent (FP-GD) algorithm. Simulation results show the effectiveness of our proposed algorithms and validate that 2-bits quantizer is enough for RIS phase shifts implementation.

翻译：可重构智能表面（RIS）作为下一代第六代（6G）通信系统的候选关键技术，因其能够通过无源波束成形实现前所未有的频谱和能量效率提升而备受关注。然而，获取RIS的瞬时信道状态信息（I-CSI）极具挑战性，这迫使我们采用统计信道状态信息（S-CSI）来实现无源波束成形。本文研究了信道相关环境下RIS辅助的多输入单输出（MISO）多用户下行通信系统。随后，我们提出了接入点和RIS的联合波束成形设计问题，以最大化所有用户的累计遍历频谱效率（ESE），从而提升网络容量。由于直接计算累计ESE极其困难，我们采用ESE近似将问题转化为更易处理的形式。接着，提出了两种联合波束成形算法，即奇异值分解-梯度下降（SVD-GD）算法和分式规划-梯度下降（FP-GD）算法。仿真结果表明了所提算法的有效性，并验证了2比特量化器足以实现RIS相位调整。