Measurement-Based Channel Characterization in 5G High-Speed-Train Scenarios

With the rapid development of communication, especially the fifth-generation (5G) technology, the railway communication system has evolved towards intelligence. In this paper, a 5G passive channel measurement scheme was proposed and a corresponding platform was successfully built up. The measurement platform was applied to collect the 5G downlink signals based on the in-service communication network in high-speed-train (HST) scenarios. The channel impulse responses (CIRs) were extracted from the received channel state information reference signals (CSI-RSs) and the key channel characteristics were analyzed. Both the large-scale and small-scale parameters including pathloss, shadow fading, ricean K-factor, and root mean square (RMS) delay spread were analyzed and modeled. The empirical pathloss and estimated shadow fading were close to the proposed model. The cumulative distribution functions (CDFs) of K-factor and RMS delay spread fitted the desired distribution. The empirical channel characteristics in 5G HST scenarios will be useful for future 5G railway communication simulation and performance evaluation.