3‐D Massive MIMO Channel Model for High‐Speed Railway Wireless Communication

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.

A survey on advanced transmission technologies for high bandwidth and good signal quality for high-speed railways

“…Recently, besides these modified schemes, researchers are taking interest in massive MIMO systems [53], [54] that use a very high number of antennas at transmitter and receiver to provide high bandwidth and high spectrum efficiency, especially for HSR communications because of large size of the train. Keeping this advanced system, many methods are adopted such as a two-antenna configuration [22], [55], 3-D based massive MIMO [56], and massive MIMO based adaptive multi-stream beamforming scheme [57]. Basic working principle of RoF technology as shown in Figure 2.…”

Performance analysis of massive multiple input multiple output for high speed railway

“…These scenarios can be approximately categorised into six scenarios of train passes from like open space, viaduct, hilly terrain, cutting, tunnels and stations. Moreover, wireless signal propagation can be categorised into five categories that is, inter train, train to infrastructure, infrastructure to infrastructure, intra train, inside the train station, and [16]. Table 1 shows various HSR channel models.…”

“…The Ray tracing channel model is deterministic channel model and operates in mmWave frequency band. It can provide accurate characterization of a propagation channel at a train speed of around 300 km/h [16], [17]. One Ray is transmitted which measures information like delay, angle information and amplitude which is tracked and at receiver summation of all such rays gives information of channel for modelling.…”

Millimeter Wave Spatial Statistical Channel Model for High-altitude Military UAV Battlefield Situation Awareness

“…From the point of view of UAV control, omnidirectional antennas have better communication performance during movement, while directional antennas perform poorly during movement (Khawaja et al, 2019), so the use of MIMO antenna arrays can better meet the needs of battlefield situation awareness. MIMO antenna arrays can improve channel reliability and channel capacity (Liao et al, 2020), and multiple antennas in a MIMO system can be utilized in different ways effectively. The most common of these are spatial multiplexing (SM) and beamforming (BF) (Sun et al, 2014).…”