Joint Sensing-Communication Beam Scheduling for Low-Altitude UAV Data Delivery
Keywords:
Integrated Sensing and Communication, Unmanned Aerial Vehicles, Beam Scheduling, Trajectory Optimization, Spatial MultiplexingAbstract
The integration of unmanned aerial vehicles into next-generation wireless networks has catalyzed the development of aerial platforms capable of performing simultaneous data delivery and environmental perception. This paper investigates the complex problem of joint sensing-communication beam scheduling for low-altitude unmanned aerial vehicle data delivery systems. In conventional paradigms, radar sensing and wireless communication operate in orthogonal frequency bands or time slots, leading to suboptimal resource utilization. We propose a unified framework that leverages integrated sensing and communication principles to dynamically schedule transmit beams, thereby maximizing communication throughput while strictly satisfying radar sensing accuracy requirements. By modeling the dual-functional aerial system, we mathematically formulate a non-convex optimization problem that jointly optimizes the spatial beamforming vectors, power allocation, and time scheduling. To address the inherent mathematical intractability, an alternating optimization algorithm is developed, decoupling the problem into tractable subproblems that can be solved iteratively. Extensive theoretical analysis and simulation evaluations are provided to demonstrate the efficacy of the proposed joint scheduling mechanism. The results confirm that the proposed algorithm significantly outperforms traditional orthogonal scheduling schemes in terms of overall spectral efficiency and target detection probability. This research provides a foundational step toward the deployment of highly autonomous, intelligent low-altitude aerial networks for prospective wireless architectures.
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Copyright (c) 2026 Nora P. Russell, Anthony Morris, Gabriel A. Zhang
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