UKF-Based Channel Tracking Method for IRS-aided mmWave MISO Systems

In this paper, we propose an unscented Kalman filtering (UKF)-based method to track the channel parameters of the intelligent reflecting surface (IRS) aided millimeter wave (mmWave) multi-input single-output (MISO) systems. To minimize the mean squared error (MSE) of the tracking parameters, the beamforming vector of the base station (BS) and the reflecting vector of the IRS are designed iteratively, considering the transmit power constraint of the BS and the unit module constraint of the IRS. The resulting sub-problems can be transformed into quadratic constraint quadratic problems (QCQPs), which are solved by the semidefinite relaxation (SDR) method and Gaussian randomization. Simulation results demonstrate that the proposed method outperforms existing benchmark methods.