Machine Learning and Deep Learning powered satellite communications: Enabling technologies, applications, open challenges, and future research directions

Author:

Bhattacharyya Arindam1ORCID,Nambiar Shvetha M.1,Ojha Ritwik1,Gyaneshwar Amogh2,Chadha Utkarsh3ORCID,Srinivasan Kathiravan2ORCID

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

SummaryThe 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.

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Media Technology

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