Applying reinforcement learning in slotted LoRaWAN: From concept to implementation

IF 4.3 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Computer Communications Pub Date : 2025-08-19 DOI:10.1016/j.comcom.2025.108297

Dimitrios Zorbas, Sultan Kasenov, Kamila Salimzhanova, Dias Gaziz, Timur Ismailov, Batyrkhan Baimukhanov

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引用次数: 0

Abstract

As Low Power Wide Area Networks (LPWANs) are increasingly adopted for Internet of Things (IoT) applications, they face significant challenges related to interference and scalability, which can lead to high collision rates and reduced network throughput. This paper presents a novel approach to enhancing the performance of LoRaWAN, one of the dominant LPWAN protocols, by leveraging Reinforcement Learning (RL). The proposed solution introduces a synchronization framework designed to operate under LoRaWAN principles, coupled with a low-cost, on-device RL mechanism that autonomously mitigates collisions. Through extensive simulations and real-world experiments, the effectiveness of the RL approach is demonstrated, showing an over 30% improvement in terms of packet delivery ratio (PDR) compared to traditional multiple access methods such as Pure-Aloha, Slotted-Aloha, and Carrier Sense Multiple Access (CSMA). Additionally, open-source implementations for both simulation and experimental validation are provided, ensuring reproducibility and facilitating further research in this domain.

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在开槽LoRaWAN中应用强化学习：从概念到实现

随着低功耗广域网（lpwan）越来越多地用于物联网（IoT）应用，它们面临着与干扰和可扩展性相关的重大挑战，这可能导致高碰撞率和网络吞吐量降低。本文提出了一种利用强化学习（RL）来提高LoRaWAN （LPWAN的主要协议之一）性能的新方法。提出的解决方案引入了一个同步框架，设计在LoRaWAN原则下运行，再加上一个低成本的设备上RL机制，可以自主减轻碰撞。通过大量的模拟和真实世界的实验，RL方法的有效性得到了证明，与传统的多址方法（如Pure-Aloha、slotte - aloha和Carrier Sense multiple access (CSMA)）相比，RL方法在分组传输率（PDR）方面提高了30%以上。此外，提供了仿真和实验验证的开源实现，确保了可重复性并促进了该领域的进一步研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computer Communications 工程技术-电信学

CiteScore

14.10

自引率

5.00%

发文量

397

审稿时长

66 days

期刊介绍： Computer and Communications networks are key infrastructures of the information society with high socio-economic value as they contribute to the correct operations of many critical services (from healthcare to finance and transportation). Internet is the core of today''s computer-communication infrastructures. This has transformed the Internet, from a robust network for data transfer between computers, to a global, content-rich, communication and information system where contents are increasingly generated by the users, and distributed according to human social relations. Next-generation network technologies, architectures and protocols are therefore required to overcome the limitations of the legacy Internet and add new capabilities and services. The future Internet should be ubiquitous, secure, resilient, and closer to human communication paradigms. Computer Communications is a peer-reviewed international journal that publishes high-quality scientific articles (both theory and practice) and survey papers covering all aspects of future computer communication networks (on all layers, except the physical layer), with a special attention to the evolution of the Internet architecture, protocols, services, and applications.