Quadrotor unmanned aerial vehicles (UAVs) have emerged as ubiquitous and agile robots and data carriers within the framework of the future Internet of Things (IoT) and mobile wireless networks. Yet, the insufficient onboard battery necessitates the optimization of energy consumption for both the UAV and IoT devices while ensuring that communication requirements are met. This paper therefore proposes a more accurate and mathematically tractable model for characterizing a UAV’s energy consumption concerning desired trajectories. This nonlinear model takes into account the UAV’s dynamics, brushless direct current (BLDC) motor dynamics, and aerodynamics. To optimize the communication time between IoT devices and the UAV, IoT devices are clustered using a modified GAK-means algorithm, with dynamically optimized communication coverage radii. Subsequently, a fly–circle–communicate (FCC) trajectory design algorithm is introduced and derived to conserve energy and save mission time. Under the FCC approach, the UAV sequentially visits the cluster centers and performs circular flight and communication. Transitions between cluster centers are smoothed via 3D Dubins curves, which provide physically achievable trajectories. Comprehensive numerical studies indicate that the proposed trajectory planning method reduces overall communication time and preserves UAV battery energy compared to other benchmark schemes.

Donor-like defects are activated and acceptor-like defects are passivated when commercial AlGaN/GaN HEMTs are irradiated with 10-keV X-rays or 1.8-MeV protons at low fluence. Displacement-damage-induced creation of acceptor-like defects is observed at higher proton fluences. The dehydrogenation of FeGa-H and ON-H substitutional impurities and generation of N-vacancy-related defects most likely account for the modest degradation of these devices at high proton fluences. Low-frequency noise measurements identify FeGa defects as prominent generation-recombination centers in these devices. These results enable recalibration of the Dutta-Horn model of low-frequency noise and increased insight into the defect identities and energy distributions in AlGaN/GaN HEMTs.

Temperature-dependent threshold voltage (VTH) hysteresis and gate leakage current are characterized in commercial AlGaN/GaN HEMTs. Significant peaks in VTH hysteresis are observed at 220 ± 10 K. Gate leakage current increases with increasing temperature for as-processed devices and devices irradiated with 1.8-MeV protons at OFF-state bias, due to Mott hopping. In contrast, gate leakage current for devices irradiated or stressed at ON bias increases strongly with decreasing temperature below 200 K. The increased gate leakage at low temperature and large negative bias in ON-bias stressed and/or irradiated devices is attributed primarily to trap-assisted tunneling through oxygen impurities (ON) in AlGaN. Dehydrogenation of ON–H impurity centers during stress and/or ON-bias irradiation evidently plays a key role in enhanced cryogenic gate leakage at large negative bias in these devices.