A Novel 3D Non-Stationary Wideband GBSM for AIRS-Assisted Massive MIMO V2V Communication in Viaduct Scenarios

Massive multiple-input multiple-output (MIMO) vehicle-to-vehicle (V2V) communication faces more challenges in viaduct scenarios due to the obstructive effects of ramps and sound barriers compared to normal urban roads. To improve the communication quality, aerial intelligent reflecting surface (AIRS) can be flexibly deployed in this scenario to assist V2V communication. This paper presents a novel three dimensional (3D) non-stationary wideband geometry-based stochastic model (GBSM) designed for enhancing MIMO V2V communication systems utilizing AIRS in viaduct scenarios. Leveraging this frame-work, the paper derives closed-form expressions for the channel impulse responses (CIR) under spherical wavefront assumption. Furthermore, correlation functions and channel capacities are analytically obtained and several viable phase-shift schemes are tailored for the AIRS units. Simulation results show that the proposed model can accurately capture the characteristics of the AIRS-assisted MIMO V2V channel in viaduct scenarios, and the proposed phase-shift methods can effectively improve the channel statistical characteristics and increase the system capacity.