Abstract-In this paper, we study low-complexity algorithms for beam and channel tracking for millimeter-wave (mmWave) communications. In particular, the least mean squares (LMS) and bidirectional LMS (BiLMS) algorithms are derived for a mobile mmWave transmission scenario, where channel measurement is a nonlinear function of the unknown angle-of-arrival (AoA) and angle-of-departure (AoD). Numerical results confirm that LMS is superior to widely used Extended Kalman Filter (EKF) algorithm in tracking the mmWave beam, when the initialization of AoA/AoD and channel gains is imperfect (i.e., performed using noisy channel estimates). Moreover, BiLMS exhibits a very good mean square error (MSE) performance as compared to both LMS and EKF, which makes it a promising channel tracking algorithm for a mobile mmWave transmission scenario. We also show that LMS and BiLMS algorithms are more robust against the impairments due to the non-optimal antenna array size as compared to EKF, and show relatively faster convergence characteristic along with increasing signal-to-noise ratio (SNR). Index Terms-5G, bidirectional LMS (BiLMS), extended kalman filter (EKF), least mean squares (LMS), mean-square error (MSE), millimeter-wave (mmWave) communications.
Ref. REF shows that Least Mean Square (LMS) performs better than EKF.
Low-Complexity Adaptive Beam and Channel Tracking for Mobile mmWave Communications
2018 52nd Asilomar Conference on Signals, Systems, and Computers
2018 52nd Asilomar Conference on Signals, Systems, and Computers
Computer Science Mathematics