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In this paper, we study low-complexity algorithms for beam and channeltracking for millimeter-wave (mmWave) communications. In particular, the leastmean squares (LMS) and bidirectional LMS (BiLMS) algorithms are derived for amobile mmWave transmission scenario, where channel measurement is a nonlinearfunction of the unknown angle-of-arrival (AoA) and angle-of-departure (AoD).Numerical results confirm that LMS is superior to widely used Extended KalmanFilter (EKF) algorithm in tracking the mmWave beam, when the initialization ofAoA/AoD and channel gains is imperfect (i.e., performed using noisy channelestimates). Moreover, BiLMS exhibits a very good mean square error (MSE)performance as compared to both LMS and EKF, which makes it a promising channeltracking algorithm for a mobile mmWave transmission scenario. We also show thatLMS and BiLMS algorithms are more robust against the impairments due to thenon-optimal antenna array size as compared to EKF, and show relatively fasterconvergence characteristic along with increasing signal-to-noise ratio (SNR).

Low-Complexity Adaptive Beam and Channel Tracking for Mobile mmWave Communications