Probabilistic Allocation of Payload Code Rate and Header Copies in LR-FHSS Networks

TL;DR

This paper proposes a probabilistic strategy for optimizing code rate and header replica allocation in LR-FHSS networks, leading to improved performance over standard data rates by leveraging a device-level probabilistic approach.

Contribution

It introduces a novel probabilistic allocation strategy for LR-FHSS that outperforms standard data rates in terms of goodput and energy efficiency.

Findings

The proposed strategy consistently outperforms DR8 and DR9.

Optimal distribution rarely includes DR9, favoring DR8.

Significant improvements in goodput and energy efficiency observed.

Abstract

We evaluate the performance of the LoRaWAN Long-Range Frequency Hopping Spread Spectrum (LR-FHSS) technique using a device-level probabilistic strategy for code rate and header replica allocation. Specifically, we investigate the effects of different header replica and code rate allocations at each end-device, guided by a probability distribution provided by the network server. As a benchmark, we compare the proposed strategy with the standardized LR-FHSS data rates DR8 and DR9. Our numerical results demonstrate that the proposed strategy consistently outperforms the DR8 and DR9 standard data rates across all considered scenarios. Notably, our findings reveal that the optimal distribution rarely includes data rate DR9, while data rate DR8 significantly contributes to the goodput and energy efficiency optimizations.