Kalman-Filter-Based Tracking of Millimeter-Wave Channel Parameters for V2X Applications

The spectrum of millimeter waves, when properly exploited, represents an important asset for achieving the high data rates and low latencies required by applications in vehicular communications. However, vehicle scenarios are characterized by high mobility, which results in frequent misalignment of beams. Therefore, in these types of scenarios, beam tracking algorithms are important because they can keep the beams aligned with a low training overhead. Kalman filters are strong candidates for the implementation of such algorithms, because they ensure high channel tracking performance over a wide range of signal-to-noise-ratios (SNR) and are easy to implement. This work evaluates the performance of channel tracking methods based on Kalman filters for high mobility. Our numerical results show that the proposed Kalman filter-based channel tracking method has high performance at low SNR regimes compared to least square-based methods, and improve the robustness when using planar instead of linear arrays. Moreover, the proposed channel tracking method is shown to perform well in multipath fading scenarios, while achieving high performance in the presence of strong line-of-sight components.