发表机构
RWTH Aachen University（亚琛工业大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文针对K用户上行链路系统，提出大规模分区式RIS波束成形方案，通过渐近分析推导平均SINR闭式近似，证明等分区近似和速率最优，贪心搜索可进一步优化，仿真验证了理论的准确性与实用性。
AI 中文摘要
将可重构智能表面（RIS）与接收天线阵列相结合，是一种颇具前景的低复杂度多用户上行链路接收架构，但针对用户数超过2的场景，其性能分析仍是一个未解决的问题：迫零（ZF）信号与干扰加噪声比（SINR）不再存在显式、低维的闭式表达式，且其分布因设计需求而难以解析处理。本文针对K用户、K天线的上行链路系统解决了这一问题，该系统中包含一个大规模L单元RIS，被划分为K个用户专用子表面，位于基站的ZF接收前端。通过对子表面规模无界增长的渐近分析，我们证明了ZF SINR所依赖的正交投影矩阵收敛到与目标用户信道对齐的秩1矩阵。我们利用该收敛性推导了仅依赖确定性信道参数的平均用户SINR的闭式渐近近似。将该表达式作为易处理的设计目标，我们证明了无论用户间路径损耗是否不对称，等分区在主导阶近似达到和速率最优。我们还开发了一种低复杂度的贪心成对转移搜索，可在主导阶最优的基础上进一步优化分区。对不同系统规模和RIS规模的蒙特卡洛仿真证实，当RIS规模相对于用户数足够大时，闭式SINR能紧密跟踪精确仿真速率；贪心搜索相比等分区也能产生一致的、虽幅度不大但稳定的和速率增益，验证了该理论既是准确的性能预测工具，也是实用的设计工具。
英文摘要
Combining a reconfigurable intelligent surface (RIS) with a receive antenna array is a promising low-complexity architecture for multi-user uplink reception, but its performance analysis for more than two users has remained an open problem: the zero-forcing (ZF) signal-to-interference-plus-noise ratio (SINR) no longer admits an explicit, low-dimensional closed-form expression, and its distribution is analytically intractable for design purposes. This paper addresses this gap for a K-user, K-antenna uplink system in which a large-scale, L-element RIS, partitioned into K user-dedicated sub-surfaces, precedes ZF reception at the base station. Through an asymptotic analysis in which the sub-surface sizes grow without bound, we show that the orthogonal projector underlying the ZF SINR converges to a rank-one matrix aligned with the desired user's channel. We use this convergence to derive a closed-form asymptotic approximation for the average per-user SINR that depends only on deterministic channel parameters. Treating this expression as a tractable design objective, we prove that equal partitioning is approximately sum-rate-optimal at leading order regardless of path-loss asymmetry across users. We also develop a low-complexity greedy pairwise-transfer search that refines the partition beyond this leading-order optimum. Monte Carlo simulations across a range of system and RIS sizes confirm that the closed-form SINR tracks the exact simulated rate closely once the RIS is large relative to the number of users. The greedy search also yields consistent, if modest, sum-rate gains over equal partitioning, validating the theory as both an accurate performance predictor and a practical design tool.
