X-MAC : Achieving High Scalability via Imperfect-Orthogonality Aware Scheduling in LPWAN

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

3 Scopus Citations
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Author(s)

  • Zhuqing Xu
  • Junzhou Luo
  • Shuai Wang
  • Ciyuan Chen
  • Jingkai Lin
  • Runqun Xiong
  • Tian He

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publication2022 IEEE 30th International Conference on Network Protocols (ICNP 2022)
PublisherIEEE
ISBN (Electronic)978-1-6654-8234-9
Publication statusPublished - 2022

Publication series

NameProceedings - International Conference on Network Protocols, ICNP
Volume2022-October
ISSN (Print)1092-1648

Conference

Title30th IEEE International Conference on Network Protocols, ICNP 2022
PlaceUnited States
CityLexington
Period30 October - 2 November 2022

Abstract

As an emerging Low-Power Wide Area Networks (LPWAN) technology, LoRa is dedicated to providing long-range connections for pervasive Internet-of-Things devices. As LoRa operates in the unlicensed spectrum, transmissions from multiple LoRa end-devices inevitably collide into each other, leading to packet losses and increased transmission delay. Targeting at collisions caused by interferences under the same spreading factor (SF) settings, researchers introduce multiple lines of techniques. Despite their efforts, these techniques commonly neglect the potential collisions caused by interferences under different SF settings, which are resulted by the imperfect orthogonality. Given the disparate transmission power configurations and diverse deployed locations, the collisions under different SFs commonly exist in practical networks, and significantly limit the LoRa reliability. In this paper, we present X-MAC, the first scheduler that is aware of imperfect orthogonality. Technically, X-MAC detects the collisions under different SFs via tracking historical transmissions, and further performs dynamic channel scheduling to avoid collisions caused by interferences both under the same and different SFs. Extensive evaluations on testbed devices show that, compared with the state-of-the-art methods, X-MAC boosts the network scalability (number of concurrent end-devices) by 2.41× with packet reception rate (PRR) requirement of > 95%.

Bibliographic Note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

Citation Format(s)

X-MAC: Achieving High Scalability via Imperfect-Orthogonality Aware Scheduling in LPWAN. / Xu, Zhuqing; Luo, Junzhou; Yin, Zhimeng et al.
2022 IEEE 30th International Conference on Network Protocols (ICNP 2022). IEEE, 2022. (Proceedings - International Conference on Network Protocols, ICNP; Vol. 2022-October).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review