标题:A Novel 2D Non-Stationary Wideband Massive MIMO Channel Model
作者:Lopez, Carlos L.; Wang, Cheng-Xiang; Feng, Rui
通讯作者:Lopez, CL
作者机构:[Lopez, Carlos L.; Wang, Cheng-Xiang] Heriot Watt Univ, Inst Sensors Signals & Syst, Edinburgh EH14 4AS, Midlothian, Scotland.; [Feng, Rui] Shandong 更多
会议名称:21st IEEE International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD)
会议日期:OCT 23-25, 2016
来源:2016 IEEE 21ST INTERNATIONAL WORKSHOP ON COMPUTER AIDED MODELLING AND DESIGN OF COMMUNICATION LINKS AND NETWORKS (CAMAD)
出版年:2016
页码:207-212
关键词:Massive MIMO channel model; parabolic wavefront; non-stationarity;; spatial lognormal process; cluster shadowing
摘要:In this paper, a novel two-dimensional (2D) non-stationary wideband geometry-based stochastic model (GBSM) for massive multiple-input multiple-output (MIMO) communication systems is proposed. Key characteristics of massive MIMO channels such as near field effects and cluster evolution along the array are addressed in this model. Near field effects are modeled by a second-order approximation to spherical wavefronts, i.e., parabolic wavefronts, leading to linear drifts of the angles of multipath components (MPCs) and non-stationarity along the array. Cluster evolution along the array involving cluster (dis) appearance and smooth average power variations is considered. Cluster (dis) appearance is modeled by a two-state Markov process and smooth average power variations are modeled by a spatial lognormal process. Statistical properties of the channel model such as time autocorrelation function (ACF), spatial cross-correlation function (CCF), and cluster average power and Rician factor variations over the array are derived. Finally, simulation results are presented and analyzed, demonstrating that parabolic wavefronts and cluster soft evolution are good candidates to model important massive MIMO channel characteristics.
收录类别:CPCI-S
WOS核心被引频次:3
资源类型:会议论文
TOP