{"title":"Cache-aided UAV-assisted relaying networks: Performance analysis and system optimization","authors":"Zhe Wang, Chun Yang, Binyu Xie","doi":"10.1111/coin.12610","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":55228,"journal":{"name":"Computational Intelligence","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Intelligence","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/coin.12610","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
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.
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.