An Analysis of Uplink Success Probability in Multi-Cell Lora Networks Under Different Channel Models

TL;DR

This paper analyzes the success probability of multi-cell LoRa networks under different channel models using stochastic geometry, providing insights into network reliability and performance metrics.

Contribution

It offers a novel stochastic geometry-based analysis of success probability in multi-cell LoRa networks across Rayleigh and Rician channels.

Findings

Success probability varies with channel conditions and network parameters.

Numerical simulations confirm the accuracy of the theoretical analysis.

The analysis aids in evaluating throughput, SNR, and SIR in LoRa networks.

Abstract

The development of the low power wide area network (LPWAN) for the internet of things (IoTs) is expected to grow widely, allowing remote monitoring of smart devices from a distance of up to several kilometers. This paper studies the performance and success probability of multi-cell LoRa networks. Using tools of stochastic geometry, the paper analyzes the important metric namely success probability in both Rayleigh and Rician channel models. The obtained analysis helps investigate and evaluate other quality criteria in the multi-cell LoRa network such as throughput, SNR and SIR requirements. Moreover, we provide numerical simulation results to corroborate the theoretical analysis and to verify how our analysis can characterize the given reliability target.