Enhancing LR-FHSS Scalability Through Advanced Sequence Design and Demodulator Allocation
Diego Maldonado, Megumi Kaneko, Juan A. Fraire, Alexandre Guitton, Oana Iova, Herve Rivano
TL;DR
This paper tackles LR-FHSS scalability for Direct-to-Satellite IoT by jointly optimizing FHS design and demodulator allocation. It introduces Wide-Gap FHS concepts and Li-Fan-based sequence constructions, alongside two demodulator strategies—Early-Decode and Early-Drop—to maximize gateway processing capacity. Through extensive simulations, Li-Fan FHS families consistently outperform driver-based sequences under high-load conditions, especially when paired with the proposed allocation strategies, achieving substantial gains in decoded payload throughput. The findings indicate that combining Wide-Gap FHS with adaptive demodulator strategies can significantly enhance LR-FHSS scalability, enabling robust operation in networks with potentially hundreds of thousands of nodes.
Abstract
The accelerating growth of the Internet of Things (IoT) and its integration with Low-Earth Orbit (LEO) satellites demand efficient, reliable, and scalable communication protocols. Among these, the Long-Range Frequency Hopping Spread Spectrum (LR-FHSS) modulation, tailored for LEO satellite IoT communications, sparks keen interest. This work presents a joint approach to enhancing the scalability of LR-FHSS, addressing the demand for massive connectivity. We deepen into Frequency Hopping Sequence (FHS) mechanisms within LR-FHSS, spotlighting the potential of leveraging Wide-Gap sequences. Concurrently, we introduce two novel demodulator allocation strategies, namely, ``Early-Decode" and ``Early-Drop," to optimize the utilization of LoRa-specific gateway decoding resources. Our research further validates these findings with extensive simulations, offering a comprehensive look into the future potential of LR-FHSS scalability in IoT settings.