电讯技术2024，Vol.64Issue(4)：520-527,8.DOI:10.20079/j.issn.1001-893x.221102004
分布式机器学习在RIS辅助的无线信道估计中的应用
Distributed Machine Learning for Channel Estimation in RIS-assisted Wireless Channel
摘要
Abstract
Wireless channel estimation is the key and prerequisite for deploying reconfigurable intelligent surface(RIS)-assisted communication system.However,the difficulty of channel estimation and the huge pilot overhead in the downlink transmission environment are major challenges for RIS-assisted communication.In order to solve above problems,a regional intersection switching scheme based on distributed machine learning(DML)technique is proposed.Firstly,a multi-user shared downlink channel estimation network is proposed,which is trained by DML technique in collaboration with users and base stations.Then,a hierarchical neural network structure is built to classify and extract features of user regional channels.Finally,the feature region model fusion is used to solve the problem of users at the intersection position of adjacent channels.The simulation results show that the DML model scheme based on regional intersection can reduce the channel training pilot overhead and maximize the accurate performance of channel estimation.关键词
可重构智能超表面(RIS)/信道估计/分布式机器学习(DML)Key words
reconfigurable intelligent surface(RIS)/channel estimation/distributed machine learning(DML)分类
信息技术与安全科学引用本文复制引用
陈静,邓炳光,冀涵颖..分布式机器学习在RIS辅助的无线信道估计中的应用[J].电讯技术,2024,64(4):520-527,8.基金项目
国家自然科学基金资助项目(61901075) （61901075）
