CubeSat Communications: Recent Advances and Future Challenges

TL;DR

This paper reviews recent advances in CubeSat communication technologies, discussing constellation coverage, channel modeling, and networking, while highlighting future challenges like IoT integration, low-power networks, and machine learning applications.

Contribution

It provides a comprehensive overview of current CubeSat communication research and identifies key future research directions in the field.

Findings

Advances in constellation and coverage strategies for CubeSat networks

Development of new channel models and modulation techniques

Identification of future challenges including IoT integration and machine learning

Abstract

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.