Localizing base stations with measured data:a concatenated image-based deep learning approach

作     者：Yang CHEN Ziyuan LIU Feng JIANG Hong SHEN Wei XU Mengyu LI Ritao CHENG 

作者机构：National Mobile Communications Research LaboratorySoutheast University China Mobile Group Design Institute Co.Ltd. 

出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))

年 卷 期：2025年第68卷第2期

页      面：385-386页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 12[管理学] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0810[工学-信息与通信工程] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 080203[工学-机械设计及理论] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 081001[工学-通信与信息系统] 0835[工学-软件工程] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by joint research and development project with the Wireless Network Department of China Mobile Design Institute,which is entitled “Research on New Wireless Networking and Antenna Technology”(Grant No. R23101PE) National Natural Science Foundation of China (Grant No. 61871108) 

摘      要：Localization has become an indispensable function of modern cellular communication systems [1]. In a cloud radio access network(C-RAN), the remote radio head(RRH) is the actual signal transmitter, whose location can assist in wireless network layout optimization and wireless resource management. The measurement of the RRH location can only be done manually on-site due to the lack of global positioning systems(GPS) at the RRH side, which is thus not a cost-effective solution for the widely used C-RAN with a large number of RRH units.