Reconfigurable intelligent surfaces (RIS) can be crucial in next-generation communication systems. However, designing the {RIS} phases according to the instantaneous channel state information (CSI) can be challenging in practice due to the short coherent time of the channel. In this regard, we propose a novel algorithm based on the channel statistics of massive multiple input multiple output systems rather than the instantaneous {CSI}. The beamforming at the base station (BS), power allocation of the users, and phase shifts at the RIS elements are optimized to maximize the minimum signal-to-interference and noise ratio (SINR), guaranteeing fair operation among various users. In particular, we design the RIS phases by leveraging the asymptotic deterministic equivalent of the minimum {SINR} that depends only on the channel statistics. This significantly reduces the computational complexity and the amount of controlling data between the {BS} and {RIS} for updating the phases. This setup is also useful for electromagnetic fields (EMF)-aware systems with constraints on the maximum user's exposure to EMF. The numerical results show that the proposed algorithms achieve more than $100 \%$ gain in terms of minimum SINR, compared to a system with random RIS phase shifts, when $40$ RIS elements, $20$ antennas at the BS and $10$ users, are considered.

翻译：可重构智能表面（RIS）在下一代通信系统中可能发挥关键作用。然而，由于信道相干时间较短，在实际中根据瞬时信道状态信息（CSI）设计RIS相位面临挑战。为此，我们提出一种基于大规模多输入多输出系统信道统计特性而非瞬时CSI的新型算法。基站（BS）的波束成形、用户的功率分配以及RIS单元的相位偏移被联合优化，以最大化最小信干噪比（SINR），从而保证各用户间的公平性。具体而言，我们利用仅依赖于信道统计特性的最小SINR渐近确定性等效来设计RIS相位。这显著降低了计算复杂度以及BS与RIS之间用于更新相位的控制数据量。该方案对具有用户最大电磁场（EMF）暴露约束的EMF感知系统同样适用。数值结果表明，在考虑40个RIS单元、BS配置20根天线和10个用户的场景下，与采用随机RIS相位的系统相比，所提算法在最小SINR方面实现了超过100%的增益。