有限反馈RIS辅助系统的无信道估计波束成形
Channel-Estimation-Free Beamforming for RIS-Assisted Systems with Limited Feedback
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中文总结 AI 辅助
针对RIS辅助系统，提出仅用有限RSS反馈的无信道估计波束成形算法，含单用户及多用户场景，仿真显示其性能接近全CSI交替优化，可保障用户公平性。
中文摘要 AI 辅助
本文研究RIS辅助无线链路中仅利用有限接收信号强度（RSS）反馈最大化接收功率的问题，避免显式估计高维级联信道。我们针对被动和主动波束成形提出随机与确定性算法：确定性方法中，每个RIS单元仅需三次固定相位的RSS测量即可恢复相位，随后采用树结构量化；我们在级联瑞利衰落下证明了固定波束成形单用户RIS扫描的非渐近接收功率保证，并将该界扩展至有限分辨率RIS移相器。对瑞利信道与时变相关信道的仿真显示，所提方法性能接近全信道状态信息（CSI）交替优化。我们将无信道估计框架扩展至多用户RIS辅助传输，提出适用于RIS相位调整与发射波束成形的统一单比特共识方法：该机制中所有用户仅通过本地信干噪比（SINR）比较对每个共享扰动投票，使更新兼顾期望信号提升与对其他用户的干扰，加权共识可基于用户优先级保障公平性。
英文摘要
In this article, we consider received-power maximization in RIS-assisted wireless links using only limited received signal strength (RSS) feedback, avoiding explicit estimation of the high-dimensional cascaded channel. We propose stochastic and deterministic algorithms for passive and active beamforming. In the deterministic method, each RIS element requires only three fixed-phase RSS measurements to recover the phase, followed by tree-structured quantization. We prove a non-asymptotic received-power guarantee for the fixed-beamformer single-user RIS sweep under cascaded Rayleigh fading and extend the bound to finite-resolution RIS phase shifters. Simulations over Rayleigh and temporally correlated channels show that the proposed methods approach full-CSI alternating optimization. We extend the channel-estimation-free framework to multi-user RIS-assisted transmission by proposing a unified single-bit consensus method for both RIS phase adaptation and transmit beamforming. In this mechanism, all users vote on each shared perturbation using only local SINR comparisons, allowing the update to account for both desired-signal improvement and interference generated to other users. The weighted consensus allows for fairness among users based on their priority.
