Physical-Layer Analysis of LoRa Robustness in the Presence of Narrowband Interference

TL;DR

This paper analyzes how narrowband interference affects LoRa's physical-layer performance, revealing that common modeling approaches overestimate errors and providing insights into interference mechanisms and thresholds for reliable demodulation.

Contribution

It offers a detailed physical-layer analysis of narrowband interference on LoRa, highlighting the limitations of AWGN approximation and proposing a model for maximum interference levels.

Findings

Modeling narrowband interference as AWGN overestimates SER.

Distinct impairment effects of AWGN and narrowband interferers identified.

A two-segment function for maximum INR ensuring correct demodulation is proposed.

Abstract

With the rapid development of Internet of Things (IoT) technologies, the sub-GHz unlicensed spectrum is increasingly being shared by protocols such as Long Range (LoRa), Sigfox, and Long-Range Frequency-Hopping Spread Spectrum (LR-FHSS). These protocols must coexist within the same frequency bands, leading to mutual interference. This paper investigates the physical-layer impact of two types of narrowband signals (BPSK and GMSK) on LoRa demodulation. We employ symbol-level Monte Carlo simulations to analyse how the interference-to-noise ratio (INR) affects the symbol error rate (SER) at a given signal-to-noise ratio (SNR) and noise floor, and then compare the results with those for additive white Gaussian noise (AWGN) of equal power. We demonstrate that modelling narrowband interference as additive white Gaussian noise (AWGN) systematically overestimates the SER of Chirp Spread Spectrum (CSS) demodulation. We also clarify the distinct impairment levels induced by AWGN and two types of narrowband interferers, and provide physical insight into the underlying mechanisms. Finally, we fit a two-segment function for the maximum INR that ensures correct demodulation across SNRs, with one segment for low SNR and the other for high SNR.