Novel AoD Estimation Algorithms for WSSUS and Non-WSSUS V2V Channel Modeling

In this paper, we propose efficient computational solutions for estimating the statistical properties of wide-sense stationary un-correlative scattering (WSSUS) and non-WSSUS multiple-input multiple-output (MIMO) vehicle-to-vehicle (V2V) channel models. Specifically, in the WSSUS channel models, we first estimate the angle of departure (AoD) for the non-line of sight (NLoS) propagation components. In this manner, the complex channel impulse response (CIR), which are widely used in the existing literature to characterize the wireless channel physical properties, can be estimated on the basis of the estimated AoD and defined model parameters. Conversely, in the non-WSSUS channel models, by estimating the AoD in the initial stage, the real-time complex CIR of the V2V channel model can be estimated on the basis of the estimated AoD and the moving time/velocities/directions of the mobile transmitter (MT) and mobile receiver (MR). In the estimation process of the aforementioned cases, we introduce different solutions to convert the CIRs from the complex domain to the real-value domain, thereby optimizing the computational efficiency for investigating channel characteristics as compared to existing methods. Numerical results of the WSSUS and non-WSSUS MIMO V2V channel characteristics, such as the spatial-temporal (ST) cross-correlation functions (CCFs) and auto-correlation functions (ACFs), are estimated on the basis of the estimated complex CIRs. These results are in agreements with theoretical ones, indicating that the proposed algorithms are practical for estimating the WSSUS and non-WSSUS MIMO V2V channel characteristics.