  Jittering effects significantly degrade the performance of UAV
millimeter-wave (mmWave) communications. To investigate the impacts of UAV
jitter on mmWave communications, we firstly model UAV mmWave channel based on
the geometric relationship between element antennas of the uniform planar
arrays (UPAs). Then, we extract the relationship between (I) UAV attitude
angles & position coordinates and (II) angle of arrival (AoA) & angle of
departure (AoD) of mmWave channel, and we also derive the distribution of
AoA/AoD at UAV side from the random fluctuations of UAV attitude angles, i.e.,
UAV jitter. In beam training design, with the relationship between attitude
angles and AoA/AoD, we propose to generate a rough estimate of AoA and AoD from
UAV navigation information. Finally, with the rough AoA/AoD estimate, we
develop a compressed sensing (CS) based beam training scheme with constrained
sensing range as the fine AoA/AoD estimation. Particularly, we construct a
partially random sensing matrix to narrow down the sensing range of CS-based
beam training. Numerical results show that our proposed UAV beam training
scheme assisted by navigation information can achieve better accuracy with
reduced training length in AoA/AoD estimation and is thus more suitable for UAV
mmWave communications under jittering effects.
