Cache-aided UAV-assisted relaying networks: Performance analysis and system optimization

IF 1.8 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Zhe Wang, Chun Yang, Binyu Xie
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引用次数: 0

Abstract

The utilization of distributed multi-agent unmanned aerial vehicles (UAVs) for computing tasks in remote areas has gained significant traction in recent years due to their adaptability and capability to access hard-to-reach regions that are inaccessible to ground-based methods. However, establishing wireless communication between UAVs and ground-based data sources in remote areas presents considerable challenges, particularly when UAVs are in motion. To tackle this challenge, this article investigates a cache-aided relaying system in the presence of UAVs, wherein a ground-based decode-and-forward relay equipped with cache space is deployed to facilitate wireless communication between UAVs and a central data source. Within the scope of this system, we first analyze the probability of transmission outage, providing an analytical expression for performance evaluation. We commence with the case of a single stationary UAV, subsequently expanding to multiple stationary UAVs, and ultimately incorporating multiple dynamic UAVs. Subsequently, we enhance the system performance by minimizing the outage probability through efficient power resource allocation among users. By means of mathematical modeling and simulations, this research examines the influence of various factors, including the cache size at the relay and the working mode of the UAV, on the system performance. Finally, simulations are conducted to validate the proposed analysis.

缓存辅助无人机中继网络:性能分析与系统优化
近年来,利用分布式多代理无人飞行器(UAVs)在偏远地区执行计算任务的做法受到了广泛关注,这是因为 UAVs 具有适应性强的特点,能够进入地面方法难以到达的区域。然而,在偏远地区建立无人机与地面数据源之间的无线通信面临着相当大的挑战,尤其是当无人机处于运动状态时。为了应对这一挑战,本文研究了无人机存在时的缓存辅助中继系统,即部署一个配备缓存空间的地面解码转发中继器,以促进无人机与中央数据源之间的无线通信。在该系统范围内,我们首先分析了传输中断的概率,为性能评估提供了一个分析表达式。我们从单个固定无人机的情况开始,随后扩展到多个固定无人机,并最终纳入多个动态无人机。随后,我们通过在用户之间有效分配电力资源,最大限度地降低中断概率,从而提高系统性能。通过数学建模和模拟,本研究探讨了各种因素对系统性能的影响,包括中继站的缓存大小和无人机的工作模式。最后,通过模拟验证了所提出的分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Computational Intelligence
Computational Intelligence 工程技术-计算机:人工智能
CiteScore
6.90
自引率
3.60%
发文量
65
审稿时长
>12 weeks
期刊介绍: This leading international journal promotes and stimulates research in the field of artificial intelligence (AI). Covering a wide range of issues - from the tools and languages of AI to its philosophical implications - Computational Intelligence provides a vigorous forum for the publication of both experimental and theoretical research, as well as surveys and impact studies. The journal is designed to meet the needs of a wide range of AI workers in academic and industrial research.
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