论文标题
基于无人机的无线网络的不确定性下的分布式合作：贝叶斯联盟游戏
Distributed Cooperation Under Uncertainty in Drone-Based Wireless Networks: A Bayesian Coalitional Game
论文作者
论文摘要
我们在基于无人机的无线网络中研究资源共享问题。我们考虑在不确定性下的分布式控制设置（即无法获得完整信息）。尤其是，在没有有关不同系统特征的先验知识的情况下，例如其他无人机可用功率的数量，无人机在汇总其光谱和能源资源的同时为用户提供了合作。我们将上述问题作为贝叶斯合作游戏，在该游戏中，代理商（无人机）参与了联盟形成过程，其目标是最大程度地提高网络的总体传输速度。无人机使用一种新型技术更新他们的信念，该技术将最大似然估计与Kullback-Leibler Divergence结合在一起。我们提出了一种反复联盟形成的决策策略，该策略会融合到稳定的联盟结构。我们通过理论分析和模拟分析了所提出的方法的性能。
We study the resource sharing problem in a drone-based wireless network. We consider a distributed control setting under uncertainty (i.e. unavailability of full information). In particular, the drones cooperate in serving the users while pooling their spectrum and energy resources in the absence of prior knowledge about different system characteristics such as the amount of available power at the other drones. We cast the aforementioned problem as a Bayesian cooperative game in which the agents (drones) engage in a coalition formation process, where the goal is to maximize the overall transmission rate of the network. The drones update their beliefs using a novel technique that combines the maximum likelihood estimation with Kullback-Leibler divergence. We propose a decision-making strategy for repeated coalition formation that converges to a stable coalition structure. We analyze the performance of the proposed approach by both theoretical analysis and simulations.
