High-Speed Train Wireless Communication Channel Modeling In Different Scenarios

The fifth generation(5G)mobile communication technology will be commercialized by 2020 in China.With high mobility becoming one of the major performance indicators of 5G,high speed train(HST)wireless communication scenario and vehicle to vehicle communication scenario will be taken as the typical networks.38,000 kilometers will be brought into service by 2025,and the sustained speed of Renaissance EMU can easily exceed 350 km/h.The increasing number of people who takes the HSTs demands the explosive growth of data traffic and reliable high-capacity communication systems.In order to satisfy the needs of high-quality communication services,HST wireless communication systems have to conquer numerous challenges,such as diverse scenarios,fast handover,and large Doppler spreads,besides many problems inherited from traditional trains such as high penetration losses,limited visibility in tunnels,and the severe electromagnetic environment.The aforementioned challenges should be considered in the design of HST communication system.Accurate and efficient channel models considering both large scale and small scale fading characteristics are crucial for the design,performance evaluation,and parameter optimization of HST wireless communication systems.The large scale fading characteristics are beneficial to the overall design,while the small scale fading features count for the design of the receiver and the selection of modulation mode.However,the characteristics of the underlying HST channels have not yet been sufficiently investigated.In this paper,the analysis of different HST scenarios has been provided based on stochastic channel model and deterministic tunnel channel model.HSTs will encounter complex scenarios in the travel.Different geographical environments will have the significant impact on propagation properties of wireless signal.The small scale fading characteristics of rural area,viaduct scenario and cutting scenario,such as temporal autocorrelation function(ACF),cross-correlation function(CCF),and power spectrum density(PSD)are analyzed based on the geometry-based stochastic model(GBSM).The impacts of different scenario-specific parameters on the channel statistical properties can also be easily observed via simulation results.As the unique architectural structure of HST tunnel,signals will encounter with rich effect scatterers.Multiple reflections,diffractions will be the dominant propagation mechanisms,which make some existing HST channel models cannot be directly applied to tunnel scenarios.In this paper,based on the proposed ray tracing tunnel channel model,we investigate the impact of different parameters on large-scale channel statistical characteristics,such as carrier frequency,tunnel shape,tunnel dimension,antenna polarization and the distance between the transmitter(Tx)and receiver(Rx).