Abstract: In wireless sensor networks, unmanned aerial vehicles (UAVs) regularly cruise around the sensor-covered area to collect the data sensed by the sensors. Due to the broadcast nature of wireless channels, information is more likely to be eavesdropped by illegal nodes on the ground, which makes the security of wireless com-munication challenging. Through UAV trajectory planning and sensor power control, the security of wireless communication can be guaranteed in the physical layer. However, in the existing researches on UAV-assisted wireless communication trajectory planning, the minimum communication time required by sensors is not considered to ensure the quality of service. To solve this problem, the minimum communication time con-straint is added. By jointly optimizing the trajectory of UAV, the transmission power of sensors and the scheduling order of UAV serving sensors, the problem of maximizing the average secrecy rate is proposed. The non-convexity of this problem is also proved. In order to solve the proposed non-convex problem, the original problem is decomposed into three sub-problems, and a fast convergent iterative algorithm TPA is proposed, which uses block coordinate descending, continuous convex optimization and iterative rounding method. The experimental results show that TPA improves the average secrecy rate by 15.7% on average in comparison to the baseline scheme without trajectory optimization, and by 159.8% on average in comparison to the baseline scheme without power control. In comparison to the baseline scheme without the minimum communication time constraint, TPA improves the task completion rate on average by 44.6% and 27.1%, when the UAV flight period is greater than 70s under two different task distribution situations.

Key words: wireless sensor network, unmanned aerial vehicle, wireless communication, amount of data, secrecy rate