This chapter works on developing a novel three-dimensional (3D) non-stationary irregular-shaped geometry-based stochastic model (IS-GBSM) for beyond 5G and 6G vehicle-to-vehicle (V2V) mmWave massive multiple-input multiple-output (MIMO) channels. The proposed IS-GBSM utilizes distinguishable dynamic clusters and static clusters to explore the impact of vehicular traffic density (VTD) on channel statistics. Specifically, the developed method generates dynamic/static correlated clusters by an improved K-Means clustering algorithm. Then, by employing a birth-death process based on correlated groups, the consistency in birth and death between dynamic/static correlated clusters during time-array evolution is modeled. Finally, extensive simulations are carried out and demonstrate that space-time-frequency non-stationarity has been accurately captured, and the influence of VTDs on channel statistics has been successfully explored.
Millimeter-Wave Massive MIMO Vehicular Channel Modeling
Wireless Networks
2022-05-03
32 pages
Article/Chapter (Book)
Electronic Resource
English
Geometry-based , Stochastic , Channel model , mmWave , Massive multiple-input multiple-output , Vehicle-to-vehicle , Vehicular traffic density , Space-time-frequency correlation Engineering , Communications Engineering, Networks , Computer Communication Networks , Transportation Technology and Traffic Engineering , Automotive Engineering
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