@article{Li2025, 
author = {Guangshun Li and Tielin Wang and Junhua Wu and Zhiyun Guan},
title = {Co-Design Enhanced Power Scheme and Trajectory Optimization of UAV-Enabled Data Collection from WSNs},
year = {2025},
journal = {Tsinghua Science and Technology},
volume = {30},
number = {6},
pages = {2343-2365},
keywords = {data collection, energy management, trajectory optimization, Unmanned Aerial Vehicle (UAV)-enabled Wireless Sensor Networks (WSNs)},
url = {https://www.sciopen.com/article/10.26599/TST.2024.9010094},
doi = {10.26599/TST.2024.9010094},
abstract = {Due to their versatility and ease of movement, Unmanned Aerial Vehicles (UAVs) have become crucial tools in data collection for Wireless Sensor Networks (WSNs). While numerous UAV-based solutions exist, the focus often needs to be on optimizing flight trajectories and managing energy use, sometimes neglecting key factors affecting channel quality. In this article, we introduce a collaborative design framework designed to alleviate channel quality degradation caused by UAV flight distance in three-dimensional spaces. Our approach jointly optimizes UAV power schemes, positions, and flight trajectories. Firstly, we start by introducing a novel enhancing power model developed explicitly for rotary-wing UAVs gathering data, utilizing an alternating optimization method to achieve locally optimal solutions. Next, we frame an optimization problem aimed at maximizing the total average collection rate while achieving approximate optimal position relationships among UAVs. Additionally, we propose a new trajectory optimization model based on the Steiner Minimal Tree (SMT) concept, which is called the Circumcircle Steiner Minimal Tree Problem with Neighborhood (CSMTPN). Finally, we confirm our theoretical insights and numerical outcomes through extensive simulations demonstrating our framework’s effectiveness.}
}