Mobility Model-Based Non-Stationary Mobile-to-Mobile Channel Modeling

Authors:
Publisher website
Google Scholar
Abstract
Non-stationary mobile-to-mobile (M2M) channel modeling has gained strong momentum as it is vital for developing M2M communications technology. Traditional geometry-based channel models (GSCMs) for M2M communications usually assume fixed velocity and moving direction, which differs from the realistic M2M scenarios and also makes it difficult to incorporate non-stationarity of channel into the regular-shaped GSCMs. In this paper, a mobility model-based method is proposed to incorporate non-stationarity into M2M channel modeling by introducing dynamic velocities and trajectories. A revised Gauss-Markov mobility model is first presented together with the cluster-based two-ring M2M reference model. The mobility model uses tuning parameters to adjust the degree of mobility randomness and covers different M2M mobility trajectories. Then, a closed-form time-variant time-frequency correlation function and the Doppler power spectrum are derived from the model. Based on the numerical analysis, it is found that for a regular-shaped GSCM with a fixed M2M scattering environment, the motion does not introduce non-stationarity, however, the dynamic motion (i.e., the changes of velocity and moving direction) leads to non-stationarity, which is reflected by the time-variant time correlation function and Doppler spectrum. Different propagation modes, cluster number, and intra-cluster nonisotropic scattering also have major impacts on channel non-stationarity. Moreover, the randomness of the mobility model is found to significantly increase the degree of channel non-stationarity. These conclusions are useful for M2M non-stationary channel simulation and communication system evaluation.
Funding Information
  • National Natural Science Foundation of China (61771037, 61501020, 61725101)
  • Natural Science Foundation of Beijing Municipality (4182047, L172020)
  • National key research and development program (2016YFB1200102-04, 2016YFE0200900)
  • State Key Laboratory of Rail Traffic Control and Safety (RCS2018ZT014)
  • Fundamental Research Funds for the Central Universities (2018JBM301)
  • Teaching Reform Project (134496522, 134493522)

This publication has 41 references indexed in Scilit: