首页 | 本学科首页   官方微博 | 高级检索  
     


Machine Learning and Deep Learning powered satellite communications: Enabling technologies,applications, open challenges,and future research directions
Authors:Arindam Bhattacharyya  Shvetha M Nambiar  Ritwik Ojha  Amogh Gyaneshwar  Utkarsh Chadha  Kathiravan Srinivasan
Affiliation:1. School of Electronics Engineering, Vellore Institute of Technology, Vellore, India;2. School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India;3. Faculty of Applied Sciences and Engineering, University of Toronto, Toronto, Ontario, Canada
Abstract:The recent wave of creating an interconnected world through satellites has renewed interest in satellite communications. Private and government-funded space agencies are making advancements in the creation of satellite constellations, and the introduction of 5G has brought a new focus to a fully connected world. Satellites are the proposed solutions for establishing high throughput and low latency links to remote, hard-to-reach areas. This has caused the injection of many satellites in Earth's orbit, which has caused many discrepancies. There is a need to establish highly adaptive and flexible satellite systems to overcome this. Machine Learning (ML) and Deep Learning (DL) have gained much popularity when it comes to communication systems. This review extensively provides insight into ML and DL's utilization in satellite communications. This review covers how satellite communication subsystems and other satellite system applications can be implemented through Artificial Intelligence (AI) and the ongoing open challenges and future directions.
Keywords:Deep Learning  Indoor Positioning and Indoor Navigation  Machine Learning  Network Intrusion Detection System  satellite communications  satellite IoT
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号