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    This study introduces a low-complexity compressive sensing multiple access (CSMA) system for satellite Internet of Things (IoT) communications. The novel approach significantly reduces computational complexity and improves bit error rate performance, making it ideal for satellite IoT networks.

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    Area of Science:

    • Wireless Communication Systems
    • Signal Processing
    • Internet of Things (IoT)

    Background:

    • Satellite IoT communications face challenges with complexity and efficiency.
    • Sparse Code Multiple Access (SCMA) is a promising technique but can be computationally intensive.
    • Existing methods like MPA and Log-MPA struggle with high computational loads in sparse environments.

    Purpose of the Study:

    • To propose a low-complexity CSMA communication system for satellite IoT.
    • To replace traditional SCMA encoding and decoding algorithms with more efficient methods.
    • To enhance performance in terms of bit error rate and computational complexity.

    Main Methods:

    • Developed a CSMA system using non-orthogonal sparse codebooks.
    • Implemented a measurement matrix at the transmitter, replacing linear SCMA encoding.
    • Utilized the smoothed L0 (SL0) algorithm at the receiver, leveraging user sparsity.

    Main Results:

    • Achieved 4.5 Gb/s in a W-band wireless system over 6m and 12m.
    • SL0 algorithm demonstrated superior bit error rate (BER) performance compared to MPA and Log-MPA.
    • Achieved significant computational complexity reduction rates (CCRR) of up to 85.7% (vs. MPA) and 72.8% (vs. Log-MPA).

    Conclusions:

    • The proposed CSMA system offers a low-complexity, high-performance solution for satellite IoT.
    • The SL0 algorithm provides a computationally efficient alternative for decoding in sparse user scenarios.
    • The scheme shows substantial potential for practical deployment in satellite IoT communication.