Resilience Analysis in Off-Grid LoRa Mesh Networks: Evaluation of Meshtastic Profiles in Long-Range Propagation Scenarios
Provides quantitative design criteria for selecting LoRa mesh configurations in smart city emergency communications, though the results are specific to the 915 MHz band and Meshtastic firmware.
This work characterizes all eight Meshtastic modem presets at three power levels in the 915 MHz band, finding that 'Long Slow' presets achieve up to 180 dB path attenuation before failure, a 60-70 dB advantage over fastest profiles, and defines three operational regimes for off-grid mesh network design.
The integration of LoRa technologies with mesh topologies represents a robust alternative for off-grid communications in emergency scenarios within smart cities. Meshtastic firmware implements a decentralised mesh network over LoRa where each node acts simultaneously as end device and router, enabling communication via Bluetooth-connected mobile devices without reliance on conventional infrastructure. Within the Colombian context (915 MHz ISM band), this work establishes design and planning criteria through a controlled guided-link methodology that isolates the LoRa physical layer from propagation effects, enabling deterministic characterisation of all eight Meshtastic modem presets at three transmission power levels (42 datasets). The results reveal a performance partitioning governed primarily by Spreading Factor (SF): "Short" presets (SF7-SF8) fail at 110-120 dB of path attenuation, "Medium" presets (SF9-SF10) sustain links up to 135-150 dB, and "Long" presets (SF11-SF12) maximise coverage, with "Long Slow" reaching 180 dB before failure - a 60-70 dB advantage over the fastest profiles. The SNR analysis confirms sub-noise-floor demodulation down to -18 dB for SF12, with abrupt link failure occurring within 2-4 dB of the theoretical limit. Based on these thresholds, three operational regimes are defined (high-density IoT, balanced urban mesh, and maximum-range emergency), providing network designers with quantitative criteria to select the appropriate configuration and node density for smart city deployments.