Fragment-Level Macro-Diversity Reception in LoRaWAN Networks with LR-FHSS

TL;DR

This paper introduces a macro-diversity reception strategy for LR-FHSS in LoRaWAN, enabling multiple gateways to collaboratively receive and combine fragments, significantly enhancing network capacity and reliability.

Contribution

It proposes a novel fragment-level macro-diversity approach for LR-FHSS, supported by a stochastic geometry model and analytical expressions for success probability.

Findings

Significant capacity gains over single-gateway reception.

Analytical model accurately predicts success probabilities.

Enhanced scalability and robustness in LPWAN deployments.

Abstract

The rapid expansion of Internet of Things (IoT) deployments demands wireless protocols that combine high scalability with robust performance. Long Range-Frequency Hopping Spread Spectrum (LR-FHSS) extends LoRaWAN by increasing capacity and resilience through frequency hopping and redundancy. However, current deployments require packet reconstruction at a single gateway, limiting the benefits of LR-FHSS. This paper proposes a macro-diversity reception strategy where multiple gateways collectively receive and combine payload fragments. We develop a stochastic geometry-based analytical model that captures the impact of header repetition, payload fragmentation, and coding redundancy. Closed-form expressions quantify success probabilities under interference, and numerical evaluations demonstrate significant capacity gains over nearest-gateway reception. These results highlight the potential of fragment-level macro-diversity to improve scalability and reliability in future LPWAN deployments.