Edge-Cloud Collaborative Interference Mitigation with Fuzzy Detection Recovery for LPWANs

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

1 Scopus Citations
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Author(s)

  • Peiyuan Qin
  • Qi Jing
  • Shuai Wang
  • Xiaolei Zhou

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings of the 2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD)
EditorsWeiming Shen, Jean-Paul Barthès, Junzhou Luo, Gang Chen, Jinghui Zhang, Haibin Zhu, Kunkun Peng
PublisherIEEE
Pages792-797
ISBN (Electronic)9781665405270, 978-1-6654-0526-3
ISBN (Print)978-1-6654-0763-2
Publication statusPublished - 2022

Publication series

NameIEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD

Conference

Title2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD 2022)
LocationBlossom Tao Hotel (Hangzhou International Expo Center)
PlaceChina
CityHangzhou
Period4 - 6 May 2022

Abstract

Recent researches have mitigated interference by utilizing cloud assistance or cloud-edge collaboration for Low-Power Wide-Area Networks. However, the issue of long interference recovery time prevents these methods from being well utilized in practical scenarios. In this paper, we propose a novel method, called FDR, for Edge-Cloud collaborative interference mitigation with Fuzzy Detection Recovery, which recovers errors in real-time. Our design (i) utilizes gateways and cloud servers and (ii) reduces data transmissions with fuzzy detection codes for real-time error recovery. In our design, each gateway detects and reports the fuzzy positions of errors to the cloud. Then the cloud restores packets with fuzzy detection results. FDR takes the advantage of both the computational ability of the cloud and the error detection benefit of each gateway. We design and implement FDR with commodity devices including LoRa SX1280 and the USRP-B210 platform. Experimental results show that FDR reduces recovery time by 78.53% compared with the state-of-art, and recovers interfered data packets accurately when the packet damage rate reaches 45.72%.

Research Area(s)

  • Fuzzy Detection, Low-Power Wide-Area Networks (LP-WANs), Signal Real-Time Recovery

Citation Format(s)

Edge-Cloud Collaborative Interference Mitigation with Fuzzy Detection Recovery for LPWANs. / Qin, Peiyuan; Mei, Luoyu; Jing, Qi et al.
Proceedings of the 2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD). ed. / Weiming Shen; Jean-Paul Barthès; Junzhou Luo; Gang Chen; Jinghui Zhang; Haibin Zhu; Kunkun Peng. IEEE, 2022. p. 792-797 (IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD).

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