通信学报2023,Vol.44Issue(10):112-123,12.DOI:10.11959/j.issn.1000-436x.2023188
无蜂窝大规模MIMO网络下基于联邦学习的用户接入策略及能耗优化
Federated learning-based user access strategy and energy consumption optimization in cell-free massive MIMO network
摘要
关键词
无蜂窝大规模MIMO/用户接入/智能感知/AP选择/能耗优化Key words
cell-free massive MIMO/user access/intelligent sensing/AP selection/energy consumption optimization分类
信息技术与安全科学引用本文复制引用
姚媛媛,刘忆秋,黄赛,潘春雨,李学华,袁昕..无蜂窝大规模MIMO网络下基于联邦学习的用户接入策略及能耗优化[J].通信学报,2023,44(10):112-123,12.基金项目
国家自然科学基金资助项目(No.62301059) (No.62301059)
北京市属高等学校优秀青年人才培育计划基金资助项目(No.BPHR202203228) (No.BPHR202203228)
泛网无线通信教育部重点实验室(BUPT)基金资助项目(No.KFKT-2020105) (BUPT)
北京市自然科学基金-海淀联合基金资助项目(No.L212026,No.L222004) The National Natural Science Foundation of China(No.62301059),The Project of Cultivation for Young Top-Motch Talents of Beijing Municipal Institutions(No.BPHR202203228),The Key Laboratory of Universal Wireless Communi-cations(BUPT),Ministry of Education(No.KFKT-2020105),Beijing Natural Science Foundation-Haidian Original Innovation Joint Fund(No.L212026,No.L222004) (No.L212026,No.L222004)