Completion time minimization for multi-antenna UAV-enabled data collection in uncorrelated Rician fading

In 5G, the unmanned aerial vehicle (UAV) is regarded as an essential way to support energy-saving, reliable, and low-cost data collection in wireless sensor networks. However, UAV-based data collection inevitably suffers from more significant data collection delays due to the UAV movement time in large application scenarios. In this paper, we consider a UAV-enabled wireless sensor network under the uncorrelated Rician fading channel, where a multi-antenna UAV is dispatched to collect data from ground sensor nodes (SNs). The objective is to minimize the mission completion time, including UAV flight and data collection time, by jointly optimizing UAV trajectory, UAV-SN transmission scheduling, and trajectory-based time allocation under the constraints of UAV speed, outage probability, data size, and transmission power. To solve this nonconvex problem, we decompose it into two subproblems: 1) trajectory optimization and 2) UAV-SN transmission scheduling and trajectory-based time allocation optimization. In the trajectory optimization, we first rewrite the outage probability constraint into the communication distance constraint and propose a Spiral-based method to find the shortest trajectory covering all SNs. Then, we propose a scheduling initialization algorithm and employ alternating optimization to solve the UAV-SN transmission scheduling and trajectory-based time allocation optimization. Finally, numerical results show that the proposed algorithm outperforms the benchmark and typical algorithms in terms of the mission completion time through a large number of experiments.