Recent Advances in LoRa: A Comprehensive Survey

Author:

Sun Zehua1ORCID,Yang Huanqi1ORCID,Liu Kai1ORCID,Yin Zhimeng1ORCID,Li Zhenjiang1ORCID,Xu Weitao1ORCID

Affiliation:

1. City University of Hong Kong Shenzhen Research Institute, City University of Hong Kong, China

Abstract

The vast demand for diverse applications raises new networking challenges, which have encouraged the development of a new paradigm of Internet of Things (IoT), e.g., LoRa. LoRa is a proprietary spread spectrum modulation technique that provides a solution for long-range and ultra-low power-consumption transmission. Due to promising prospects of LoRa, significant effort has been made on this compelling technology since its emergence. In this article, we provide a comprehensive survey of LoRa from a systematic perspective: LoRa analysis, communication, security, and its enabled applications. First, we summarize works focusing on analyzing the performance of LoRa networks. Then, we review studies enhancing the performance of LoRa networks in communication. Afterward, we analyze the security vulnerabilities and countermeasures. Finally, we survey the various LoRa-enabled applications. We also present comparisons of existing methods, together with insightful observations and inspiring future research directions.

Funder

NSFC

Shenzhen Research Institute, City University of Hong Kong

Research Grants Council of the Hong Kong Special Administrative Region, China

Shenzhen Science and Technology Funding Fundamental Research Program

NSF of Shandong Province

International and Regional Science and Technology Cooperation Program

Chow Sang Sang Group Research Fund sponsored by Chow Sang Sang Holdings International Limited

CityU MFPRC

CityU SIRG

CityU APRC

CityU ARG

CityU SRG-Fd

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications

Reference190 articles.

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3. Cedric Adjih, Emmanuel Baccelli, Eric Fleury, Gaetan Harter, Nathalie Mitton, Thomas Noel, Roger Pissard-Gibollet, Frederic Saint-Marcel, Guillaume Schreiner, Julien Vandaele, et al. 2015. FIT IoT-LAB: A large scale open experimental IoT testbed. In IEEE 2nd World Forum on Internet of Things (WF-IoT). IEEE, 459–464.

4. Amani Al-Shawabka, Philip Pietraski, Sudhir B. Pattar, Francesco Restuccia, and Tommaso Melodia. 2021. DeepLoRa: Fingerprinting LoRa devices at scale through deep learning and data augmentation. In 22nd International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing. 251–260.

5. Joint Allocation Strategies of Power and Spreading Factors With Imperfect Orthogonality in LoRa Networks

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