Distributed Real-Time Optimization for UAV-Based MIMO Communication System With Dynamic Cooperative Performance Adaptation

This paper proposes a real-time dynamic optimization algorithm and controller design for a multi-node UAV-based distributed communication system, leveraging the phase and energy characteristics of radio waves. The algorithm employs a distributed framework and an online optimization strategy to adaptively adjust the positions of communication nodes in dynamic environments. It is a task-driven method and aimed at maximizing system communication capacity while significantly reducing UAV movement distance. Unlike traditional optimization methods with fixed performance functions, this approach incorporates time-varying performance functions for dynamic adaptation, while ensuring the convergence and optimality. Simulation results demonstrate that the proposed algorithm maintains global optimal performance under dynamic scenarios and offers robust computational adaptability, providing both theoretical and practical support for optimizing dynamic UAV communication networks.