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On Use of LEO-GEO Hybrid Model for Optimized Data Traffic Performance

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Abstract

As the world is moving towards the Internet of Things (IoT), more data rate is required with wider coverage and small delay. While the 5G supports the needed increased data rate, it suffers from a decreased coverage per tower. In contrast, the low population areas such as deserts, oceans, forests, and mountains contain most of the world's transportation such as highways, ships, and planes as well as large areas of agricultural lands that are all not supported by 5G. Consequently, LEO satellite constellations have been introduced to cover the earth's surface with a high-speed data rate. Each LEO satellite constellation requires 4000 + satellites and at least one ground base station (BS) for control, tracking, telemetry, and remote sensing functions. However, to support the needed downlink high-speed data rate demand, the LEO satellite constellation must add many BSs to increase the uplink data rate. As a result, the GEO communication satellites face great competitors in their market. This paper introduces the hybrid LEO-GEO satellite communication system to change this competition into cooperation that benefits both systems. In the hybrid LEO-GEO satellite communication system, this paper proposes maximizing the downlink utilization of both LEO and GEO satellites by the traffic-aware Artificial Expectation Detection (AED) technique. In such a technique, the trending multicast data choose the GEO link while the unicast data and control data choose the LEO link to maximize the downlink utilization efficiency. Our results show that using AED is power efficient and delay efficient while increasing the data rate by (100)x to (100k)x or decreasing the needed number of LEO BSs.

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Acknowledgements

We would like to thank Prof. Dr. Abdel Halem A. Zekry for helping us brainstorm the idea of this research. May Allah bless his soul in heaven.

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Authors and Affiliations

  1. Electronics and Communications Engineering Department, Faculty of Engineering, Ain Shams University, Cairo, Egypt

    Hany Ali & Mohamed Abouelatta

  2. Communications Engineering Department, Faculty of Navigation Science and Space Technology, Beni-Suef University, Beni-Suef, Egypt

    Khaled Y. Youssef

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  1. Hany Ali
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Contributions

H.A. presented the paper idea, wrote the paper sections, built the MATLAB model, and discussed the findings. M.A. and K.Y. reviewed the paper idea and sections, supervised the model, and proofread the manuscript. All authors read and approved the final manuscript.

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Correspondence to Hany Ali.

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Ali, H., Abouelatta, M. & Youssef, K.Y. On Use of LEO-GEO Hybrid Model for Optimized Data Traffic Performance. Wireless Pers Commun 138, 641–657 (2024). https://doi.org/10.1007/s11277-024-11527-z

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