Beam Alignment for High-Speed UAV via Angle Prediction and Adaptive Beam Coverage

In unmanned aerial vehicle (UAV) communications, continuing beamforming along with the movement of the UAV to mitigate the severe path loss is indispensable, which is called beam tracking. The conventional beam tracking studies focus on tracking the angle resulting from the movement of a target and obtaining the maximum beamforming gain with a narrow beam through phased array-based beamforming. However, the high mobility and perturbation of UAV impose a challenge on aligning narrow beams between the base node and the UAV node in the aerial network. In particular, the spatial angular velocity is significantly high in the field of view (FoV) of antenna array. In this article, we propose a scheme that predicts the spatial angle of the moving object in the next time unit
¹
and design a wide beam pattern based on the predicted value to reduce the beam misalignment issue. The proposed scheme can establish a robust communication link with the reduced packet loss, by mitigating the variations resulting from angle transition during a time unit, prediction errors, and the angle process noise. Especially, Gaussian process regression (GPR)-based spatial angle prediction method can predict spatial angle for the next time unit, with lower overhead than conventional methods. Considering the fact that UAVs typically travel at speeds from
$\boldsymbol{40}$
to
$\boldsymbol{160}$
[km/hr], we verify the simulation results in high-speed scenario such as from
$\boldsymbol{170}$
to
$\boldsymbol{200}$
[km/hr]. The simulation results show that the proposed scheme reduces the alignment error while maintaining sufficient signal-to-noise ratio (SNR) condition required for vehicular communication.