CubeSat Communications: Recent Advances and Future Challenges

Given the increasing number of space-related applications, research in the emerging space industry is becoming more and more attractive. One compelling area of current space research is the design of miniaturized satellites, known as CubeSats, which are enticing because of their numerous application...

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Bibliographic Details
Published in:IEEE Communications surveys and tutorials 2020-01, Vol.22 (3), p.1839-1862
Main Authors: Saeed, Nasir, Elzanaty, Ahmed, Almorad, Heba, Dahrouj, Hayssam, Al-Naffouri, Tareq Y., Alouini, Mohamed-Slim
Format: Article
Language:English
Subjects:
communications
connectivity
CubeSat
CubeSats
cyber-physical systems
Earth
Industries
Internet
Internet of Things
Machine learning
Remote sensing
Resource allocation
Satellite constellations
Small satellites
Space exploration
Space research
Space vehicles
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Summary:Given the increasing number of space-related applications, research in the emerging space industry is becoming more and more attractive. One compelling area of current space research is the design of miniaturized satellites, known as CubeSats, which are enticing because of their numerous applications and low design-and-deployment cost. The new paradigm of connected space through CubeSats makes possible a wide range of applications, such as Earth remote sensing, space exploration, and rural connectivity. CubeSats further provide a complementary connectivity solution to the pervasive Internet of Things (IoT) networks, leading to a globally connected cyber-physical system. This paper presents a holistic overview of various aspects of CubeSat missions and provides a thorough review of the topic from both academic and industrial perspectives. We further present recent advances in the area of CubeSat communications, with an emphasis on constellation-and-coverage issues, channel modeling, modulation and coding, and networking. Finally, we identify several future research directions for CubeSat communications, including Internet of space things, low-power long-range networks, and machine learning for CubeSat resource allocation.
ISSN:1553-877X
1553-877X
2373-745X
DOI:10.1109/COMST.2020.2990499