FAST-LoRa: An Efficient Simulation Framework for Evaluating LoRaWAN Networks and Transmission Parameter Strategies

TL;DR

FAST-LoRa is a new simulation framework that provides fast, accurate, and computationally efficient evaluation of LoRaWAN network performance and parameter strategies, especially suited for stable, uplink-focused scenarios.

Contribution

It introduces an analytical, lightweight simulation tool that significantly reduces computation time while maintaining accuracy compared to traditional detailed simulators.

Findings

Achieves similar accuracy to established simulators in estimating network metrics.

Reduces simulation time by up to three orders of magnitude.

Maintains low error margins in complex interference scenarios.

Abstract

The Internet of Things (IoT) has transformed many industries, and LoRaWAN (Long Range Wide Area Network), built on LoRa (Long Range) technology, has become a crucial solution for enabling scalable, low-cost, and energy-efficient communication in wide-area networks. Simulation tools are essential for optimizing the transmission parameters and, therefore, the energy efficiency and performance of LoRaWAN networks. While existing simulation frameworks accurately replicate real-world scenarios by including multiple layers of communication protocols, they often imply significant computational overhead and simulation times. To address this issue, this paper introduces FAST-LoRa, a novel simulation framework designed to enable fast and efficient evaluation of LoRaWAN networks and selection of transmission parameters. FAST-LoRa streamlines computation by relying on analytical models without complex packet-level simulations and implementing gateway reception using efficient matrix operations. Rather than aiming to replace discrete-event simulators, FAST-LoRa is intended as a lightweight and accurate approximation tool for evaluating transmission parameter strategies in scenarios with stable traffic patterns and uplink-focused communications. In our evaluation, we compare FAST-LoRa with a well-established simulator using multiple network configurations with varying numbers of end devices and gateways. The results show that FAST-LoRa achieves similar accuracy in estimating key network metrics, even in complex scenarios with interference and multi-gateway reception, with a Mean Absolute Error (MAE) of 0.940 $\times 10^{-2}$ for the Packet Delivery Ratio (PDR) and 0.040 bits/mJ for Energy Efficiency (EE), while significantly reducing computational time by up to three orders of magnitude.