Back to Search
Start Over
Integrating LoRa Collision Decoding and MAC Protocols for Enabling IoT Massive Connectivity
- Source :
- IEEE Internet of Things Magazine, IEEE Internet of Things Magazine, 2022
- Publication Year :
- 2022
- Publisher :
- HAL CCSD, 2022.
-
Abstract
- International audience; One major goal of Beyond 5G and 6G networks is to provide connectivity for a massive number of Internet-of-Things (IoT) devices. Towards that goal, Long Range (LoRa) is a promising physical layer technology which features low data-rates and large communication ranges, while requiring only low power. However, as the number of devices increases, more and more collisions occur, hence severely degrading LoRa system performances. To cope with this critical drawback, several LoRa collision decoding algorithms and MAC protocols have been proposed. The purpose of this article is to present how collision decoding algorithms interact with MAC layer protocols, and to discuss the potential of such integrated approaches. To do so, we first classify the collision decoding algorithms according to their principles and distinctive features, and compare some reference algorithms in a single simulation setup, using a Software Defined Radio (SDR) hardware. Then, we analyze how each class of MAC protocols can benefit from each category of collision decoding algorithms. Finally, we discuss longterm perspectives and open issues in this active research area.
- Subjects :
- IoT
[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]
2022 DRAFT
[INFO.INFO-NI] Computer Science [cs]/Networking and Internet Architecture [cs.NI]
MAC protocols
Interferences
Packet Collisions
General Earth and Planetary Sciences
Massive Connectivity
Beyond 5G May 4
LoRa
General Environmental Science
Subjects
Details
- Language :
- English
- ISSN :
- 25763180 and 25763199
- Database :
- OpenAIRE
- Journal :
- IEEE Internet of Things Magazine, IEEE Internet of Things Magazine, 2022
- Accession number :
- edsair.doi.dedup.....62674dbd6dee85221e0e4ab020594256