Robust Fingerprint Localization Based on Massive MIMO Systems  

作　　者：Xiaojun Wang Yijie Ren Weiguang Sun Xiaoshu Chen 

机构地区：[1]National Mobile Communications Research Laboratory,Southeast University,Nanjing 210000,China [2]Purple Mountain Laboratories,Nanjing 210000,China [3]Frontiers Science Center for Mobile Information Communication and Security,Southeast University,Nanjing 210000,China

出　　处：《China Communications》2022年第11期148-159,共12页中国通信（英文版）

基　　金：supported by Jiangsu Province Key Research and Development Program(BE2018704);Technical Innovation Project of The Ministry of Public Security(20170001);Fundamental Research Funds for the Central Universities(2242022k30001);National Science Foundation of China(CN)(Grant No.61871111).

摘　　要：Location-based services have become an important part of the daily life.Fingerprint localization has been put forward to overcome the shortcomings of the traditional positioning algorithms in indoor scenario and rich scattering environment.In this paper,a single-site multiple-input multiple-output(MIMO)orthogonal frequency division multiplexing(OFDM)system is modeled,from which an angle delay channel power matrix(ADCPM)is extracted.Considering the changing environment,auto encoders are used to generate new fingerprints based on ADCPM fingerprints to improve the robustness of the fingerprints.When the scattering environment has changed beyond a certain extent,the robustness will not be able to make up for the positioning error.Under this circumstance,an updating of the fingerprint database is imperative.A new fingerprint database updating algorithm which combines a new clustering method and an updating rule based on probability is proposed.Simulation results show the desirable performance of the proposed methods.

关 键 词：massive multiple-input multiple-output fingerprint extraction ROBUSTNESS database updating 

分 类 号：TN929.5[电子电信—通信与信息系统]