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

作　　者：姚媛媛 刘忆秋 黄赛 潘春雨 李学华[1,2] 袁昕 YAO Yuanyuan;LIU Yiqiu;HUANG Sai;PAN Chunyu;LI Xuehua;YUAN Xin(Key Laboratory of Information and Communication Systems,Ministry of Information Industry,Beijing Information Science and Technology University,Beijing 100101,China;Key Laboratory of Modern Measurement&Control Technology,Ministry of Education,Beijing Information Science and Technology University Beijing 100101,China;Key Laboratory of Universal Wireless Communications,Ministry of Education,Beijing University of Posts and Telecommunications,Beijing 100876,China;School of Electrical and Data Engineering,University of Technology Sydney,Sydney NSW 2007,Australia)

机构地区：[1]北京信息科技大学信息与通信系统信息产业部重点实验室,北京100101 [2]北京信息科技大学现代测控技术教育部重点实验室,北京100101 [3]北京邮电大学泛网无线通信教育部重点实验室,北京100876 [4]悉尼科技大学电气与数据工程学院,悉尼NSW 2007

出　　处：《通信学报》2023年第10期112-123,共12页Journal on Communications

基　　金：国家自然科学基金资助项目(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);泛网无线通信教育部重点实验室(BUPT)基金资助项目(No.KFKT-2020105);北京市自然科学基金-海淀联合基金资助项目(No.L212026,No.L222004)。

摘　　要：针对无蜂窝大规模多输入多输出(CF-mMIMO)网络中用户如何选择接入点的问题,提出了一种基于信道排序的较差用户优先接入策略。首先,用户进行信道感知后对其信道质量和稳定性进行评估和排序,用户按照信道状态信息的顺序依次选择合适的接入点;其次,考虑到用户的能耗与数据安全等问题,采用联邦学习框架以增强用户的数据隐私安全,并提出一种基于能耗优化的交替优化变量算法,对多维变量进行优化,使系统总能耗最小化。仿真结果表明,相较于传统的大规模MIMO中用户为中心的接入策略,所提接入策略可使用户平均上行可达速率提升20%,信道较差用户的上行速率可提升2倍;在能耗优化方面,优化后的总能耗可降低50%以上。To solve the problem that how users choose access points in cell-free massive multiple-input multiple-output(CF-mMIMO)network,a prioritized access strategy for poorer users based on channel coefficient ranking was proposed.First,users were evaluated and ranked for their channel quality and stability after channel sensing,and suitable access points were selected in sequence according to the order of the channel state information.Second,considering issues such as users'energy consumption and data security,a federal learning framework was used to enhance user's data privacy and security.Meanwhile,an alternating optimization variables algorithm based on energy consumption optimization was proposed to optimize the multi-dimensional variables,for the purpose of minimizing the total energy consumption of the system.Simulation results show that compared with the traditional user-centric in massive MIMO,the proposed access strategy can improve the average uplink reachable rate of users by 20%,and the uplink rate of users with poor channels can be double improved;in terms of energy consumption optimization,the total energy consumption can be reduced by much more than 50%after optimization.

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 

分 类 号：TN929.5[电子电信—通信与信息系统]