{"title":"5G基于几何的随机信道模型:扩展大规模MIMO的关键特征","authors":"À. Martínez, P. Eggers, E. Carvalho","doi":"10.1109/PIMRC.2016.7794648","DOIUrl":null,"url":null,"abstract":"This paper introduces three key features in geometry-based stochastic channel models in order to include massive MIMO channels. Those key features consists of multiuser (MU) consistency, non-stationarities across the base station array and inclusion of spherical wave modelling. To ensure MU consistency, we introduce the concept of “user aura”, which is a circle around the user with radius defined according to the stationarity interval. The overlap between auras determines the share of common clusters among users. To model non-stationarities across a massive array, sub-arrays are defined for which clusters are independently generated. At last, we describe a procedure to incorporate spherical wave modelling, where a cluster focal point is defined to account for distance between user and cluster.","PeriodicalId":137845,"journal":{"name":"2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":"{\"title\":\"Geometry-based stochastic channel models for 5G: Extending key features for massive MIMO\",\"authors\":\"À. Martínez, P. Eggers, E. Carvalho\",\"doi\":\"10.1109/PIMRC.2016.7794648\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces three key features in geometry-based stochastic channel models in order to include massive MIMO channels. Those key features consists of multiuser (MU) consistency, non-stationarities across the base station array and inclusion of spherical wave modelling. To ensure MU consistency, we introduce the concept of “user aura”, which is a circle around the user with radius defined according to the stationarity interval. The overlap between auras determines the share of common clusters among users. To model non-stationarities across a massive array, sub-arrays are defined for which clusters are independently generated. At last, we describe a procedure to incorporate spherical wave modelling, where a cluster focal point is defined to account for distance between user and cluster.\",\"PeriodicalId\":137845,\"journal\":{\"name\":\"2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"23\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PIMRC.2016.7794648\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PIMRC.2016.7794648","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Geometry-based stochastic channel models for 5G: Extending key features for massive MIMO
This paper introduces three key features in geometry-based stochastic channel models in order to include massive MIMO channels. Those key features consists of multiuser (MU) consistency, non-stationarities across the base station array and inclusion of spherical wave modelling. To ensure MU consistency, we introduce the concept of “user aura”, which is a circle around the user with radius defined according to the stationarity interval. The overlap between auras determines the share of common clusters among users. To model non-stationarities across a massive array, sub-arrays are defined for which clusters are independently generated. At last, we describe a procedure to incorporate spherical wave modelling, where a cluster focal point is defined to account for distance between user and cluster.