Publications Conference paper · Satellite IoT · 2026

Fast Analytical Tuning of Repetition-Based MAC for IoT in Sparse LEO Constellations

Benoit Coeugnet, André-Luc Beylot, Vincent Deslandes, and Juan A. Fraire

IEEE International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM), 2026

Abstract

The growing demand for IoT deployments beyond cellular coverage is driving adoption of low-data-rate direct-to-satellite (DtS-IoT) communication, with sparse Low Earth Orbit (LEO) constellations emerging as a cost-effective way to achieve global coverage. In such systems, downlink bandwidth may be too limited to acknowledge every uplink packet, making non-slotted ALOHA with blind retransmissions the dominant MAC paradigm, and turning the choice of repetition count and spacing into a critical design decision. Existing analytical treatments either rely on idealized visibility formulas or require time-consuming event-driven simulation, neither of which is well-suited to per-device, per-location deployment tuning. We propose an analytical model, grounded in renewal theory and discrete-time Markov chains, that uses empirical visibility distributions derived from real Two-Line Element (TLE) sets to compute the full reception-probability distribution under both blind (BlindTx) and beacon-assisted (SatDetect) MAC schemes. For a given deployment, the model returns optimal retransmission parameters in seconds, versus minutes for event-driven simulation. Validated against the FLoRaSat simulator (RMSE <3%), which is itself calibrated to Kinéis on-field measurements, the model shows that SatDetect achieves almost 4× better energy efficiency than BlindTx at low latitudes while meeting a 95% reception target.

Cite

BibTeX

@inproceedings{coeugnet2026mswim,
  author    = {Coeugnet, Benoit and Beylot, Andr{\'e}-Luc and Deslandes, Vincent and Fraire, Juan A.},
  title     = {Fast Analytical Tuning of Repetition-Based {MAC} for {IoT} in Sparse {LEO} Constellations},
  booktitle = {IEEE International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM)},
  year      = {2026}
}

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