Abstract
Millimetres wave (mm-wave) is an attractive option for high data rate applications in the 5G wireless communication systems that require proper beamforming and channel tracking. In this paper, we study, analyse and compare the performance of two closely related stochastic gradient descent-based approaches, namely the least mean square (LMS) algorithm, and the normalized least mean square (NLMS) algorithm, for tracking the transmit array beam in addition to the channel status. These adaptive filters usually result in a trade-off between convergence and accuracy. We found that the quality of the tracking results, measured in mean squared error (MSE) sense, are heavily dependent on the present step-the size of the gradient descent.
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