适应性通道估计半被动IRS与优化传感器部署的适应性通道估计
Zhiyu Han1, Hanning Wang2, Yafeng Wang1
1The Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China.
Sensors (Basel, Switzerland)
|November 13, 2025
概括
精确的通道状态信息 (CSI) 对智能反射表面 (IRS) 至关重要. 本研究介绍了一种新的压缩传感算法和半被动IRS的传感器部署,提高CSI采集准确性并减少估计开销.
科学领域:
- 无线通信无线通信
- 信号处理 信号处理
- 超材料是指一种超材料.
背景情况:
- 智能反射面 (IRS) 为被动光束成形提供了显著的潜力.
- 准确的通道状态信息 (CSI) 获取对于最佳的IRS性能至关重要.
- 由于其信号处理的局限性,被动IRS设备在获得精确的CSI方面存在挑战.
研究的目的:
- 为半被动IRS开发一个改进的道估计算法.
- 为了提高IRS系统中CSI获取的准确性.
- 为了最大限度地减少与通道估计相关的开销.
主要方法:
- 对于半被动的IRS,建议使用压缩感应通道估计算法,不需要先前了解通道路径号码.
- 粒子集群优化 (PSO) 用于确定半被动IRS中的活跃传感器的最佳部署方案.
- 进行数值模拟以验证拟议的方法.
主要成果:
- 拟议的压缩传感算法可以提高通道估计的准确性.
- 基于PSO的传感器部署方案有效优化了主动传感器的放置.
- 观察到正常化平均平方误差 (NMSE) 的减少,表明估计精度提高.
- 对于有效的通道估计,需要更少的试点符号,从而减少开销.
结论:
- 开发的方法显著提高了半被动IRS的CSI获取.
- 拟议的方法为改善无线通信系统的IRS性能提供了一个实际的解决方案.
- 这项工作有助于减少基于IRS的系统中的计算和飞行员开销.
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