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Toward Fair Maximization of Energy Efficiency in Multiple UAS-Aided Networks: A Game-Theoretic Methodology

机译:争取在多个UAS辅助网络中实现能源效率的公平最大化:一种博弈论方法

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摘要

Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.
机译:电子,传感器和通信领域的最新技术进步加速了无人机系统(UAS)辅助应用程序的广泛部署。然而,由多个UAS和地面站组成的网络(称为UAS辅助通信网络)尚未受到足够的研究关注。在本文中,我们解决了阻碍此类网络的一项基本研究挑战,即如何在包含自适应调制地面节点的网络中合理地最大化能量效率(每能量吞吐量)。对于UAS固有的移动性模式,我们演示了自适应调制如何受到影响。此外,我们将最大化公平能源效率的问题公式化为在多个地面节点之间进行的潜在博弈,并证明了其稳定性,最优性和收敛性。基于公式化的潜在博弈,提出了一种在公平约束下最大化能效的数据收集方法。此外,我们分析了我们提出的博弈论数据收集方法的无政府状态价格。广泛的仿真显示了我们的建议在不同环境下的有效性。

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