Joint Optimization for Dual UAV Swarm Collaborative Beamforming in Long-Range Communications
作者：王瑜 时间：2026年10月01日 13:19 点击数：
语言：English
发表会议：2026 International Conference on Communication Networks and Machine Learning (CNML)
发表日期：2026年2月1日
摘要：
Long-range wireless communication typically requires high transmit power or costly satellite links, which limits coverage in remote or obstructed areas. Uncrewed aerial vehicle (UAV) swarms provide a flexible and low-cost solution by forming virtual antenna arrays, where collaborative beamforming (CB) enables high directional gain with lightweight, low-power hardware. However, long-range CB introduces significant formation delays and propulsion energy consumption due to UAV mobility and array reconfiguration, creating a fundamental trade-off between communication latency and energy efficiency. To address this issue, this paper investigates a three-hop UAV-assisted relay network, in which two UAV swarms forward data between a ground server and multiple ground users. The total service time is minimized by jointly optimizing excitation currents, 3D UAV positions, formation times, and service sequences under propulsion energy constraints. The resulting mixed-integer non-convex problem is efficiently solved using a block coordinate descent (BCD) algorithm embedded with successive convex approximation (SCA). Simulation results verify rapid convergence and demonstrate that the proposed design significantly reduces latency and energy consumption compared with benchmark schemes in long-range communication scenarios.
原文链接
