This paper investigates the joint optimization of trajectory, user scheduling, and time-slot duration in unmanned aerial vehicle (UAV)-assisted wireless communication systems under minimum expected spectral efficiency (SE) constraints. Unlike most existing studies that approximate the expected SE by substituting the random channel gain with its mean value, thereby evaluating the SE at the average channel realization and overestimating the true expected SE due to Jensen's inequality, we approximate the expected SE by numerically integrating the SE over the channel distributions. Specifically, instead of relying on average-channel-based approximations, we develop a conservative yet tractable quadrature-based approximation by discretizing the associated cumulative distribution functions. The resulting finite-sum representation explicitly accounts for the probabilistic LoS structure and channel fading effects, while remaining tractable for optimization. Leveraging this lower bound, we formulate a mission completion time minimization problem subject to minimum expected-SE requirements for all ground nodes. The resulting problem is a mixed-integer nonconvex optimization, which is tackled via a penalty-based block coordinate descent framework. The proposed algorithm alternately optimizes the scheduling decisions and the UAV trajectory along with adaptive time-slot durations, and maintains feasibility with respect to the original expected-SE constraints by leveraging successive convex approximation and quadratic transform techniques. Simulation results demonstrate that the proposed method strictly satisfies the minimum expected-SE constraints and achieves a significantly shorter mission completion time than conventional average-channel-based approaches, which are shown to yield infeasible or overly conservative solutions.
Efficient Trajectory Design and Communication Scheduling for Dual-UAV Jamming-Aided Secure Communication Networks
School of Electronic Information, Wuhan University（武汉大学电子信息学院）；Chair of Information Theory and Data Analytics, RWTH Aachen University（亚琛工业大学信息理论与数据分析讲席）
Cluster-Based Multi-Agent Task Scheduling for Space-Air-Ground Integrated Networks
School of Information and Communication Engineering, University of Electronic Science and Technology of China（电子科技大学信息与通信工程学院）；College of Computing and Data Science, Nanyang Technological University（南洋理工大学计算与数据科学学院）
Personalized Federated Learning by Energy-Efficient UAV Communications
Department of Computer Science, North Carolina State University（计算机科学系，北卡罗来纳州立大学）；Department of Electrical and Computer Engineering, University of Massachusetts（电气与计算机工程系，马萨诸塞大学）
UAV Trajectory Optimization via Improved Noisy Deep Q-Network
Dept. of Computer Science（计算机科学系）；Wenzhou-Kean University（温州市凯恩大学）；School of Electrical and Computer Engineering（电气与计算机工程学院）；University of Tehran（伊朗塔里班大学）；School of Computer Science and Info. Eng.（计算机科学与信息工程学院）；Qilu Institute of Technology（青岛理工学院）
