Understanding the limits of LoRaWAN
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Abstract (arXiv)
The quick proliferation of LPWAN networks, being LoRaWAN one of the most adopted, raised the interest of the industry, network operators and facilitated the development of novel services based on large scale and simple network structures. LoRaWAN brings the desired ubiquitous connectivity to enable most of the outdoor IoT applications and its growth and quick adoption are real proofs of that. Yet the technology has some limitations that need to be understood in order to avoid over-use of the technology. In this article we aim to provide an impartial overview of what are the limitations of such technology, and in a comprehensive manner bring use case examples to show where the limits are.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Jul 2016.
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Citing papers per year: 2021: 2; 2022: 4; 2023: 2; 2024: 0; 2025: 3.
11 papers.
- 2021Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challengescited by 114
- 2022BottleFit: Learning Compressed Representations in Deep Neural Networks for Effective and Efficient Split Computingcited by 28
- 2022SC2 Benchmark: Supervised Compression for Split Computingcited by 14
- 2022MIX-MAB: Reinforcement Learning-based Resource Allocation Algorithm for LoRaWANcited by 3
- 2021Machine Learning Framework for Sensing and Modeling Interference in IoT Frequency Bandscited by 1
- 2023An Interpretable Determinantal Choice Model for Subset Selectioncited by 1
- 2025acoupi: An Open-Source Python Framework for Deploying Bioacoustic AI Models on Edge Devicescited by 1
- 2022A Practical AoI Scheduler in IoT Networks with Relayscited by 0
- 2023Data-driven classification of low-power communication signals by an unauthenticated user using a software-defined radiocited by 0
- 2025OrbitChain: Orchestrating In-orbit Real-time Analytics of Earth Observation Datacited by 0
- 2025Online Learning Based Efficient Resource Allocation for LoRaWAN Networkcited by 0
- 2025Online Learning Based Efficient Resource Allocation for LoRaWAN Network31 Aug 2025
- 2025OrbitChain: Orchestrating In-orbit Real-time Analytics of Earth Observation Data18 Aug 2025
- 2025acoupi: An Open-Source Python Framework for Deploying Bioacoustic AI Models on Edge Devices29 Jan 2025
- 2023Data-driven classification of low-power communication signals by an unauthenticated user using a software-defined radio8 Sep 2023
- 2023An Interpretable Determinantal Choice Model for Subset Selection22 Feb 2023
- 2022MIX-MAB: Reinforcement Learning-based Resource Allocation Algorithm for LoRaWAN7 Jun 2022
- 2022SC2 Benchmark: Supervised Compression for Split Computing16 Mar 2022
- 2022A Practical AoI Scheduler in IoT Networks with Relays8 Mar 2022
- 2022BottleFit: Learning Compressed Representations in Deep Neural Networks for Effective and Efficient Split Computing7 Jan 2022
- 2021Machine Learning Framework for Sensing and Modeling Interference in IoT Frequency Bands10 Jun 2021
- 2021Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges8 Mar 2021