OpenLoRa: Validating LoRa Implementations through an Extensible and Open-sourced Framework

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Manan Mishra, Daniel Koch, Muhammad Osama Shahid, and Bhuvana Krishnaswamy, University of Wisconsin-Madison; Krishna Chintalapudi, Microsoft Research; Suman Banerjee, University of Wisconsin-Madison


LoRa is one of the most widely used LPWAN communication techniques operating in the unlicensed sub-GHz ISM bands. Its long range however also results in increased interference from other LoRa and non-LoRa networks, undermining network throughput due to packet collisions. This has motivated extensive research in the area of collision resolution techniques for concurrent LoRa transmissions and continues to be a topic of interest. In this paper, we verify the implementation and efficacy of four of the most recent works on LoRa packet collisions, in addition to standard LoRa. We implement OpenLoRa, an open-source, unified platform to evaluate these works and is extensible for future researchers to compare against existing works. We implement each of the four techniques in Python as well as separate the demodulator and decoder to provide benchmarks for future demodulators that can be plugged into the framework for fair and easy comparison against existing works. Our evaluation indicates that existing contention resolution techniques fall short in their throughput performance, especially due to poor packet detection in low and ultra-low SNR regimes.

NSDI '23 Open Access Sponsored by
King Abdullah University of Science and Technology (KAUST)

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@inproceedings {285200,
author = {Manan Mishra and Daniel Koch and Muhammad Osama Shahid and Bhuvana Krishnaswamy and Krishna Chintalapudi and Suman Banerjee},
title = {{OpenLoRa}: Validating {LoRa} Implementations through an Extensible and Open-sourced Framework},
booktitle = {20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 23)},
year = {2023},
isbn = {978-1-939133-33-5},
address = {Boston, MA},
pages = {1165--1183},
url = {},
publisher = {USENIX Association},
month = apr
Mishra Paper (Prepublication) PDF

Presentation Video