在RIS辅助的毫米波系统中用于通道估计的自适应过
Shuying Shao1, Tiejun Lv1, Pingmu Huang2
1School of Information and Communication Engineering, Beijing University of Posts and Telecommunications (BUPT), Beijing 100876, China.
Sensors (Basel, Switzerland)
|January 25, 2025
概括
新的自适应算法改善了对具有可重新配置智能表面 (RIS) 的毫米波 (mmWave) 大规模MIMO系统的通道估计. 这些方法提高了准确性和速度,克服了RIS信号处理的局限性,以实现更好的无线通信.
科学领域:
- 无线通信无线通信
- 信号处理 信号处理
- 信息理论 信息理论
背景情况:
- 与可重新配置的智能表面 (RIS) 集成的毫米波 (mmWave) 大规模MIMO系统承诺增强无线通信.
- 在这些系统中,由于RIS信号处理的局限性,通道估计 (CE) 面临挑战.
- 现有的CE方法很难满足先进无线网络的需求.
研究的目的:
- 为毫米波巨型MIMO-RIS系统提出适应性通道估计框架.
- 开发新的算法,提高CE准确性和融合速度.
- 为了减少这些先进系统中通道估计的计算复杂性.
主要方法:
- 开发了两个自适应算法:Log-Sum规范最小平均平方 (Log-Sum NLMS) 和混合规范最小平均平方-规范最小平均第四 (混合NLMS-NLMF).
- 利用毫米波频道的稀疏性来改善估计.
- 在Log-Sum NLMS中包含了对Log-Sum NLMS进行更快的融合的逻辑总和惩罚,以及在混合NLMS-NLMF中用于各种SNR条件的混合错误函数.
主要成果:
- 拟议的Log-Sum NLMS和混合NLMS-NLMF算法在道估计准确度方面取得了显著的改进.
- 与NLMS,SEFWLMS和SHAFA等现有方法相比,这两种算法都表现出更快的融合速度.
- 新的算法显示了较低的计算复杂性.
结论:
- 拟议的自适应通道估计框架有效地解决了毫米波大规模MIMO-RIS系统中的CE挑战.
- 逻辑总和NLMS和混合NLMS-NLMF在准确性和融合速度方面提供了卓越的性能.
- 这些算法代表了未来无线通信技术的重大进步.
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