Li Tian

In this paper, a recently conducted measurement campaign for unmanned-aerial-vehicle (UAV) channels is introduced. The downlink signals of an in-service long-time-evolution (LTE) network which is deployed in a suburban scenario were acquired. Five horizontal and five vertical flight routes were considered. The channel impulse responses (CIRs) are extracted from the received data by exploiting the cell specific signals (CRSs). Based on the CIRs, the parameters of multipath components (MPCs) are estimated by using a high-resolution algorithm derived according to the space-alternating generalized expectation-maximization (SAGE) principle. Based on the SAGE results, channel characteristics including the path loss, shadow fading, fast fading, delay spread and Doppler frequency spread are thoroughly investigated for different heights and horizontal distances, which constitute a stochastic model.

In the future railway services, wireless communication is the fundamental part and millimeter wave (mmWave) is foreseen to be a key enabler towards the smart railway. An accurate understanding of the propagation environment can assist designing both systems and railway infrastructures for better communication services. In this paper, the influence of typical objects to the mmWave propagation channel are analyzed for “Train-to-infrastructure” and “Intra-wagon” railway scenarios with various configurations. Propagation measurements are conducted in the mmWave band for the 12 most common railway materials. The corresponding electromagnetic parameters are obtained and a 3D ray tracing (RT) simulator is calibrated. The mean absolute error of the simulated S21 parameter is -53.5 dB, indicating that the calibrated RT can be used to generate the close-to-real mmWave channel for railway scenarios. Statistically consistent scenarios and deployments are generated, which enables drawing unbiased numerical results based on intensive RT simulations. The influence of typical objects and corresponding material compositions are then compared and significant objects are determined for each scenario. The results of this work not only imply how the propagation environment impacts on the propagation channel, but also makes suggestions to efficiently reconstruct railway environment models for an accurate RT based channel model. Moreover, the understanding of the influence of the environment at object and material levels will in turn guide the construction of railway infrastructure for better railway services.