{"title":"聚类无线电传播MIMO信道模型的柯西功率方位角谱","authors":"Xin Li, T. Ekman","doi":"10.1109/VETECF.2010.5594337","DOIUrl":null,"url":null,"abstract":"This paper presents a state-space based simulation model for multiple-input and multiple-output (MIMO) channels with spatio-temporal channel correlations due to clustered radio propagation. The scattering clusters are modeled as two-dimensional Cauchy (TDCA) clusters. This renders the joint probability density function (PDF) of angle of arrival (AOA) and angle of departure (AOD) that can be approximated as the product of two Cauchy angular power distributions. Thus, the spatio-temporal correlation can be approximated as the product of an autoregressive order one (AR1) model and the corresponding spatial antenna correlation. A state-space model is employed to the temporal dynamics of the MIMO channels. The contribution of the cluster to each antenna is a state in this model. A correlated innovation process adjusts the correlation between antennas. This renders the appropriate spatio-temporal channel correlation in the simulated channels.","PeriodicalId":417714,"journal":{"name":"2010 IEEE 72nd Vehicular Technology Conference - Fall","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Cauchy Power Azimuth Spectrum for Clustered Radio Propagation MIMO Channel Model\",\"authors\":\"Xin Li, T. Ekman\",\"doi\":\"10.1109/VETECF.2010.5594337\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a state-space based simulation model for multiple-input and multiple-output (MIMO) channels with spatio-temporal channel correlations due to clustered radio propagation. The scattering clusters are modeled as two-dimensional Cauchy (TDCA) clusters. This renders the joint probability density function (PDF) of angle of arrival (AOA) and angle of departure (AOD) that can be approximated as the product of two Cauchy angular power distributions. Thus, the spatio-temporal correlation can be approximated as the product of an autoregressive order one (AR1) model and the corresponding spatial antenna correlation. A state-space model is employed to the temporal dynamics of the MIMO channels. The contribution of the cluster to each antenna is a state in this model. A correlated innovation process adjusts the correlation between antennas. This renders the appropriate spatio-temporal channel correlation in the simulated channels.\",\"PeriodicalId\":417714,\"journal\":{\"name\":\"2010 IEEE 72nd Vehicular Technology Conference - Fall\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE 72nd Vehicular Technology Conference - Fall\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VETECF.2010.5594337\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE 72nd Vehicular Technology Conference - Fall","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VETECF.2010.5594337","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cauchy Power Azimuth Spectrum for Clustered Radio Propagation MIMO Channel Model
This paper presents a state-space based simulation model for multiple-input and multiple-output (MIMO) channels with spatio-temporal channel correlations due to clustered radio propagation. The scattering clusters are modeled as two-dimensional Cauchy (TDCA) clusters. This renders the joint probability density function (PDF) of angle of arrival (AOA) and angle of departure (AOD) that can be approximated as the product of two Cauchy angular power distributions. Thus, the spatio-temporal correlation can be approximated as the product of an autoregressive order one (AR1) model and the corresponding spatial antenna correlation. A state-space model is employed to the temporal dynamics of the MIMO channels. The contribution of the cluster to each antenna is a state in this model. A correlated innovation process adjusts the correlation between antennas. This renders the appropriate spatio-temporal channel correlation in the simulated channels.