To estimate the channel correlation matrix (CCM) in areas where channel information cannot be collected in advance, this paper proposes a way to spatially extrapolate CCM based on the calibration of the surface roughness parameters of scatterers in the propagation scene. We calibrate the roughness parameters of scene scatters based on CCM data in some specific areas. From these calibrated roughness parameters, we are able to generate a good prediction of the CCM for any other area in the scene by performing ray tracing. Simulation results show that the channel extrapolation method proposed in this paper can effectively realize the extrapolation of the CCM between different areas in frequency domain, or even from one domain to another.
{"title":"Channel Correlation Matrix Extrapolation Based on Roughness Calibration of Scatterers","authors":"Heling Zhang, Xiujun Zhang, Xiaofeng Zhong, Shidong Zhou","doi":"arxiv-2409.10900","DOIUrl":"https://doi.org/arxiv-2409.10900","url":null,"abstract":"To estimate the channel correlation matrix (CCM) in areas where channel\u0000information cannot be collected in advance, this paper proposes a way to\u0000spatially extrapolate CCM based on the calibration of the surface roughness\u0000parameters of scatterers in the propagation scene. We calibrate the roughness\u0000parameters of scene scatters based on CCM data in some specific areas. From\u0000these calibrated roughness parameters, we are able to generate a good\u0000prediction of the CCM for any other area in the scene by performing ray\u0000tracing. Simulation results show that the channel extrapolation method proposed\u0000in this paper can effectively realize the extrapolation of the CCM between\u0000different areas in frequency domain, or even from one domain to another.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142251319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We recently introduced the "Virtual VNA" concept which estimates the $N times N$ scattering matrix characterizing an arbitrarily complex linear system with $N$ monomodal ports by inputting and outputting waves only via $N_mathrm{A}