论文标题
基于通信的应用程序中无人机的节能技术
Energy-Efficient Techniques for UAVs in Communication-based Applications
论文作者
论文摘要
在尖端技术的最前沿，无人驾驶飞机（UAV）具有无与伦比的开拓性应用潜力。特别是在认知无线电（CR）领域，这是新的5G电信技术实施的关键方面。无人机和CR之间的集成巩固了无人机的功能，这是CR支持的非常有前途的The Internet Internet（IoT）技术的核心。与地面无线网络相比，高度动态的网络拓扑，弱网络拓扑，可靠的路线（LOS）通信链接以及轨道或飞行路径是无人机通信的特征。然而，该系统的实施受到了一些严重的挑战，例如能源效率，电池功率限制，频谱交换，传播渠道建模，路由协议，安全策略和延迟挫折。在本文中，我们考虑了无人机在各种CR应用中面临的能源稀缺的影响。我们还分析了能源稀缺对基于通信的应用的影响，并提出了电池限制的一般问题。最后，我们对研究人员在通信领域和电池领域提出的最新解决方案进行了概述和比较，并根据最新的状态考虑可能的未来方向，例如新颖的图形信号处理（GSP）和机器学习（ML）。
Unmanned Aerial Vehicles (UAVs), which are at the forefront of cutting-edge technology, have unmatched potential for pioneering applications in a wide range of disciplines. In particular, in the field of cognitive radio (CR), which is a key aspect in the implementation of the new 5G telecommunication technology. The integration between the drone and CR consolidates the drone's capabilities at the heart of the remarkably promising Internet-of-Things (IoT) technology supported by CR. The highly dynamic network topologies, weakly networked communication links, reliable line-of-sight (LOS) communication links, and orbital or flight paths are characteristic features of UAV communication compared to terrestrial wireless networks. Nevertheless, the implementation of this system is constrained by several severe challenges, such as energy efficiency, battery power limitation, spectrum handover, propagation channel modeling, routing protocols, security policy, and delay setbacks. In this paper, we consider the impact of energy scarcity faced by the UAV in various CR applications. We also analyze the impact of energy scarcity on communication-based applications and present the general problem of battery limitation. Finally, we give an overview and comparison between recent solutions proposed by researchers both in the field of communication and based on batteries and consider possible future directions according to the state of the art, such as novel Graph Signal Processing (GSP) and machine learning (ML).
