Reconfigurable intelligent surface (RIS) can be employed in a cell-free system to create favorable propagation conditions from base stations (BSs) to users via configurable elements. However, prior works on RIS-aided cell-free system designs mainly rely on the instantaneous channel state information (CSI), which may incur substantial overhead due to extremely high dimensions of estimated channels. To mitigate this issue, a low-complexity algorithm via the two-timescale transmission protocol is proposed in this paper, where the joint beamforming at BSs and RISs is facilitated via alternating optimization framework to maximize the average weighted sum-rate. Specifically, the passive beamformers at RISs are optimized through the statistical CSI, and the transmit beamformers at BSs are based on the instantaneous CSI of effective channels. In this manner, a closed-form expression for the achievable weighted sum-rate is derived, which enables the evaluation of the impact of key parameters on system performance. To gain more insights, a special case without line-of-sight (LoS) components is further investigated, where a power gain on the order of $\mathcal{O}(M)$ is achieved, with $M$ being the BS antennas number. Numerical results validate the tightness of our derived analytical expression and show the fast convergence of the proposed algorithm. Findings illustrate that the performance of the proposed algorithm with two-timescale CSI is comparable to that with instantaneous CSI in low or moderate SNR regime. The impact of key system parameters such as the number of RIS elements, CSI settings and Rician factor is also evaluated. Moreover, the remarkable advantages from the adoption of the cell-free paradigm and the deployment of RISs are demonstrated intuitively.
翻译:重新配置智能表面(RIS) 可以在一个没有细胞的系统中使用一种低兼容性算法,通过可配置元素创建基站(BSs)向用户提供有利的传播条件。然而,先前的RIS辅助无细胞系统设计工程主要依靠瞬时频道状态信息,由于估计频道的高度,这种信息可能会产生大量的间接费用。为了缓解这一问题,本文件提出了一种通过双级传输协议的低兼容性算法,在这个系统中,通过移动优化框架,使平均加权总和率最大化,从而便利了BSs和RIS的中度参数的联合组合。具体地说,通过统计CSI优化了RIS的被动对象,而BSs的传输信号以瞬时的CSI为根据。 通过这种方式,可以对可实现的加权总比率进行封闭式表达,从而能够评估系统性能的主要参数的影响。为了获得更多的洞察,一个没有直线(LES)的变量,从而最大限度地超超重总和精确度值的系统(RIS)的被动性能和精确性压值值的值值值值值值值值值值值值值值值值值, 也通过CMRIS的精确性价值的精确性价值的精确值 显示显示的精确值 。