Enhancing LR-FHSS Scalability Through Advanced Sequence Design and Demodulator Allocation
David Maldonado, Megumi Kaneko, Juan A. Fraire, Alexandre Guitton, Oana Iova, Hervé Rivano · IEEE Transactions on Green Communications and Networking · 2025
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 validates these findings through extensive simulations, providing a detailed analysis of the scalability potential of LR-FHSS in IoT environments. The results demonstrate that the proposed strategies can boost decoding capacity by up to 50% in certain configurations.