Robust Cooperative Communication Optimization for Multi-UAV-Aided Vehicular Networks
Songge Zhang, Jianshan Zhou, Daxin Tian, Zhengguo Sheng, Xuting Duan, Victor C. M. Leung
Abstract
Aerial-ground cooperative vehicular networks are envisioned as a novel paradigm in B5G/6G visions. In this letter, the challenge of optimizing the global energy-efficiency (EE) of multi-UAV-aided vehicular networks in the presence of uncertain air-to-ground (A2G) channels is addressed. Specifically, we propose a maximin paradigm to characterize the system, which aims to maximize its global EE meanwhile satisfying Quality-of-Service (QoS)-oriented data rate requirements in the worst-case situation. We theoretically derive a closed-form optimal solution for an embedded minimization subproblem under a parametric channel uncertainty set and thus develop a computationally tractable robust counterpart, which leads to a robust EE optimization design. Simulation results show that the proposed method significantly outperforms conventional EE schemes in terms of achieving higher global system performance and better robustness under random uncertain environments.