Active Beam Tracking Under Stochastic Mobility

In mmWave communications, higher data rate long-range transmission is achieved by using highly directional beams with access to larger bandwidth. An inherent challenge is tracking channel state information (CSI) necessary for mmWave transmission under systems with unpredictable mobility. We propose a novel method of active and sequential beam tracking at mmWave frequencies and above. We focus on the dynamic scenario of UAV to UAV communications where the problem is equivalent to tracking an optimal beamforming vector along the line-of-sight path. In this setting, the resulting receiver beam ideally points in the direction of the angle of arrival with sufficiently high resolution. Existing solutions account for predictable movements or small random movements using known filtering strategies but resort to re-estimation protocols when tracking fails due to unpredictable movements. We propose an algorithm for actively and sequentially selecting beamforming vectors based on a Bayesian posterior with a prediction step to account for the mobility. Numerically, we analyze the normalized beamforming gain achieved by our proposed algorithm and demonstrate significant improvements over existing strategies.