LAUSR

In order to guarantee the reliability of millimeter-wave communication under user mobility, fast beam tracking is essential to adapt the beamforming vectors in time-varying beamspace channels. To find the best beam alignment, traditional exhaustive search scans all possible beam directions, thus introducing up to seconds of delay for wireless networks to accommodate mobile clients. In this letter, we propose a data-driven beam tracking approach to find the beamforming/combining vectors that achieve the target quality of service based on a series of equivalent dynamic linearization data models with a time-varying pseudo-gradient parameter estimation procedure. Unlike the model-based approach, which requires the prior knowledge about the channel and user mobility in beamforming design, the proposed data-driven approach depends only on the real-time measurement data. Numerical analyses show that the proposed data-driven beam tracking algorithm can achieve reliable tracking performance with much shorter alignment time compared to traditional schemes.