Beam Tracking Based on unscented Kalman Filter Theory in Millimeter Wave Communication Systems for IoT

The beam coverage directivity of mmWave communication brings great challenges to the application research of high-speed Internet of things (IoT) terminal devices, such as unmanned vehicles and unmanned aerial vehicles (UAV). Most of the existing millimeter wave beam tracking algorithms aim at AOA / AOD (Angles of Arrival / Angles of Departure) for continuous tracking estimation. However, the estimation error will increase rapidly with the increase of AOA / AOD change speed. Inspired by Auxiliary Beam Pair (ABP) algorithm, a robust two-stage beam tracking algorithm is proposed in this paper. First, AOA/AOD is estimated by the Unscented Kalman filter (UKF) algorithm, and then the AOA/AOD is modified by the improved ABP algorithm. The simulation results show that when AOA / AOD changes at a speed greater than 0.25 degrees per time slot, the proposed two-step beam tracking algorithm significantly reduces the estimation error and effectively increases the robustness of the same type of algorithm.