3‐D Massive MIMO Channel Model for High‐Speed Railway Wireless Communication. Issue 8 (7th August 2020)

• Record Type: Journal Article
• Authors: Liao, Chengjian; Xu, Kui; Xie, Wei; Xia, Xiaochen
• Is Part Of: Radio science. Volume 55:Issue 8(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-08-07
• Subjects: Radio meteorology -- Periodicals; Radio wave propagation -- Periodicals; 621.38405
• DOI: 10.1029/2020RS007070
• Languages: English
• ISSNs: 0048-6604

Abstract

Abstract: In the fifth generation (5G) wireless communication, high‐speed railway (HSR) communication is one of the most challenging scenarios. By adopting massive multi‐input multioutput (mMIMO) technology in HSR communication, the design of the underlying communication system becomes more challenging. Some new channel characteristics must be studied, such as nonstationarity in space, time, and frequency domains. In this paper, two models are established for the two states of HSR. When the HSR stops, a three‐dimensional (3‐D) stationary channel model based on the single‐ring distribution of the scatterers is established. When the HSR moves, a 3‐D nonstationary geometric random channel model (GRCM) based on the cylinder distribution of the scatterers by introducing the birth and death process of the propagation path and time‐varying characteristics of the channel parameters is established. Moreover, a time evolution algorithm for time‐varying channel parameters is proposed, and a modularization study of key parameter update algorithms is conducted. Finally, based on the proposed 3‐D nonstationary geometric random channel model, important time‐varying channel statistical characteristics, such as time autocorrelation function (ACF), spatial cross‐correlation function (CCF), Doppler power spectral density (DPSD), and stationary interval are studied. Simulation results indicate that the properties of the proposed channel models, verified by simulation results, can match well with those of the theoretical model. Key Points: A 3‐D nonstationary geometric random channel model (GRCM) based on the cylinder distribution of the scatterers is established A time evolution algorithm for time‐varying channel parameters is proposed Important time‐varying channel statistical characteristics, such as ACF, CCF, DPSD, and stationary interval, are studied