Modeling of Intelligent Reflecting Surface Based 3-D Non-Stationary Massive MIMO Channel for Vehicle-to-Vehicle Communications

Massive multiple-input multiple-output (MIMO) and intelligent reflecting surface (IRS) technologies have become a research focus for non-stationary vehicle-to-vehicle (V2V) wireless communications due to their capability to control radio propagation environment. In this paper, a non-stationary irregular geometry-based stochastic model (I-GBSM) for V2V massive MIMO systems using three-dimensional uniform linear arrays and discrete IRS at millimetre wave operating frequency is proposed. A new approach for determining IRS elements phase-shift using the Doppler effect and channel impulse response is introduced to mitigate channel non-stationarity and enhance propagation conditions. Unlike traditional models, it considers practical spherical wavefronts instead of plane wavefronts. The proposed model categorizes clusters into moving and static clusters to examine traffic density and its effects on channel characteristics in V2V environments. It employs a novel birth-death process to ensure consistency in cluster evolution. The non-stationary stochastic channel characteristics are comprehensively analyzed through simulations, including space–time–frequency correlation functions, Doppler power spectral density, path loss, delay spread, root mean square error of the correlation function, and achievable rate across different operating frequencies, demonstrating notable performance improvements. The proposed I-GBSM is also validated by a good agreement with results from existing models and measurements under reduced scenarios.