# A Survey on LoRa Networking: Research Problems, Current Solutions and Open Issues

arXiv: https://arxiv.org/abs/1908.10195 · HTML: https://mlsanity.com/paper/1908.10195/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Aug 2019.

## Built on by (most cited first, 14 of 14)

- [MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of Experts](https://mlsanity.com/paper/2404.15159/) (2024)
- [IndexTTS2: A Breakthrough in Emotionally Expressive and Duration-Controlled Auto-Regressive Zero-Shot Text-to-Speech](https://mlsanity.com/paper/2506.21619/) (2025)
- [Comprehensive RF Dataset Collection and Release: A Deep Learning-Based Device Fingerprinting Use Case](https://mlsanity.com/paper/2201.02213/) (2022)
- [RF Challenge: The Data-Driven Radio Frequency Signal Separation Challenge](https://mlsanity.com/paper/2409.08839/) (2024)
- [DEEP-IoT: Downlink-Enhanced Efficient-Power Internet of Things](https://mlsanity.com/paper/2403.00321/) (2024)
- [An Interpretable Determinantal Choice Model for Subset Selection](https://mlsanity.com/paper/2302.11477/) (2023)
- [LoRaWAN-enabled Smart Campus: The Dataset and a People Counter Use Case](https://mlsanity.com/paper/2304.13366/) (2023)
- [LoRa Communication for Agriculture 4.0: Opportunities, Challenges, and Future Directions](https://mlsanity.com/paper/2409.11200/) (2024)
- [A Lightweight Transmission Parameter Selection Scheme Using Reinforcement Learning for LoRaWAN](https://mlsanity.com/paper/2208.01824/) (2022)
- [SignCRF: Scalable Channel-agnostic Data-driven Radio Authentication System](https://mlsanity.com/paper/2303.12811/) (2023)
- [Intelligent Communication Planning for Constrained Environmental IoT Sensing with Reinforcement Learning](https://mlsanity.com/paper/2308.10124/) (2023)
- [Multiagent Reinforcement Learning with an Attention Mechanism for Improving Energy Efficiency in LoRa Networks](https://mlsanity.com/paper/2309.08965/) (2023)
- [Online Learning Based Efficient Resource Allocation for LoRaWAN Network](https://mlsanity.com/paper/2509.10493/) (2025)
- [State Space Models Meet Remote Sensing: A Survey](https://mlsanity.com/paper/2606.25329/) (2026)

## Abstract (arXiv)

Wireless networks have been widely deployed for many Internet-of-Things (IoT) applications, like smart cities and precision agriculture. Low Power Wide Area Networking (LPWAN) is an emerging IoT networking paradigm to meet three key requirements of IoT applications, i.e., low cost, large scale deployment and high energy efficiency. Among all available LPWAN technologies, LoRa networking has attracted much attention from both academia and industry, since it specifies an open standard and allows us to build autonomous LPWAN networks without any third-party infrastructure. Many LoRa networks have been developed recently, e.g., managing solar plants in Carson City, Nevada, USA and power monitoring in Lyon and Grenoble, France. However, there are still many research challenges to develop practical LoRa networks, e.g., link coordination, resource allocation, reliable transmissions and security. This article provides a comprehensive survey on LoRa networks, including the technical challenges of deploying LoRa networks and recent solutions. Based on our detailed analysis of current solutions, some open issues of LoRa networking are discussed. The goal of this survey paper is to inspire more works on improving the performance of LoRa networks and enabling more practical deployments.