Poster abstract: Energy efficient LPWAN decoding via joint sparse approximation

Jun Liu; Weitao Xu; Wen Hu

doi:10.1145/3274783.3275165

Poster abstract: Energy efficient LPWAN decoding via joint sparse approximation

Jun Liu, Weitao Xu, Wen Hu

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

2 Citations (Scopus)

Abstract

We propose a sparse approximation based joint-decoding system for LPWAN (LoRa) PHY-layer frame decoding. Recent research has shown that joint-decoding raw radio ADC samples in the Cloud offloaded from LPWAN gateways can decode weak radio signals by combining coherent frames. However, this approach requires high network bandwidth usage to collect a large amount of ADC samples from each gateway, which results in network congestion and high financial cost due to Internet data usage between the gateway and the Cloud server. In order to reduce the bandwidth usage of this data offloading operation, we propose a LPWAN packet acquisition mechanism based on joint sparse approximation.

Original language	English
Title of host publication	SenSys 2018 - Proceedings of the 16th Conference on Embedded Networked Sensor Systems
Publisher	Association for Computing Machinery
Pages	325-326
ISBN (Electronic)	9781450359528
DOIs	https://doi.org/10.1145/3274783.3275165
Publication status	Published - Nov 2018
Externally published	Yes
Event	16th ACM Conference on Embedded Networked Sensor Systems (SENSYS 2018) - Southern University of Science and Technology & Shenzhen Sea World Culture and Arts Center, Shenzhen, China Duration: 4 Nov 2018 → 7 Nov 2018 http://sensys.acm.org/2018/

Publication series

Name	SenSys - Proceedings of the 16th Conference on Embedded Networked Sensor Systems

Conference

Conference	16th ACM Conference on Embedded Networked Sensor Systems (SENSYS 2018)
Abbreviated title	SENSYS 2018)
Place	China
City	Shenzhen
Period	4/11/18 → 7/11/18
Internet address	http://sensys.acm.org/2018/

Research Keywords

Joint sparse approximation
LoRa
LPWAN

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10.1145/3274783.3275165

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Liu, J., Xu, W., & Hu, W. (2018). Poster abstract: Energy efficient LPWAN decoding via joint sparse approximation. In SenSys 2018 - Proceedings of the 16th Conference on Embedded Networked Sensor Systems (pp. 325-326). (SenSys - Proceedings of the 16th Conference on Embedded Networked Sensor Systems). Association for Computing Machinery. https://doi.org/10.1145/3274783.3275165

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title = "Poster abstract: Energy efficient LPWAN decoding via joint sparse approximation",

abstract = "We propose a sparse approximation based joint-decoding system for LPWAN (LoRa) PHY-layer frame decoding. Recent research has shown that joint-decoding raw radio ADC samples in the Cloud offloaded from LPWAN gateways can decode weak radio signals by combining coherent frames. However, this approach requires high network bandwidth usage to collect a large amount of ADC samples from each gateway, which results in network congestion and high financial cost due to Internet data usage between the gateway and the Cloud server. In order to reduce the bandwidth usage of this data offloading operation, we propose a LPWAN packet acquisition mechanism based on joint sparse approximation.",

keywords = "Joint sparse approximation, LoRa, LPWAN",

author = "Jun Liu and Weitao Xu and Wen Hu",

year = "2018",

month = nov,

doi = "10.1145/3274783.3275165",

language = "English",

series = "SenSys - Proceedings of the 16th Conference on Embedded Networked Sensor Systems",

publisher = "Association for Computing Machinery",

pages = "325--326",

booktitle = "SenSys 2018 - Proceedings of the 16th Conference on Embedded Networked Sensor Systems",

address = "United States",

note = "16th ACM Conference on Embedded Networked Sensor Systems (SENSYS 2018), SENSYS 2018) ; Conference date: 04-11-2018 Through 07-11-2018",

url = "http://sensys.acm.org/2018/",

}

Liu, J, Xu, W & Hu, W 2018, Poster abstract: Energy efficient LPWAN decoding via joint sparse approximation. in SenSys 2018 - Proceedings of the 16th Conference on Embedded Networked Sensor Systems. SenSys - Proceedings of the 16th Conference on Embedded Networked Sensor Systems, Association for Computing Machinery, pp. 325-326, 16th ACM Conference on Embedded Networked Sensor Systems (SENSYS 2018), Shenzhen, China, 4/11/18. https://doi.org/10.1145/3274783.3275165

Poster abstract: Energy efficient LPWAN decoding via joint sparse approximation. / Liu, Jun; Xu, Weitao; Hu, Wen.
SenSys 2018 - Proceedings of the 16th Conference on Embedded Networked Sensor Systems. Association for Computing Machinery, 2018. p. 325-326 (SenSys - Proceedings of the 16th Conference on Embedded Networked Sensor Systems).

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

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T1 - Poster abstract

T2 - 16th ACM Conference on Embedded Networked Sensor Systems (SENSYS 2018)

AU - Liu, Jun

AU - Xu, Weitao

AU - Hu, Wen

PY - 2018/11

Y1 - 2018/11

N2 - We propose a sparse approximation based joint-decoding system for LPWAN (LoRa) PHY-layer frame decoding. Recent research has shown that joint-decoding raw radio ADC samples in the Cloud offloaded from LPWAN gateways can decode weak radio signals by combining coherent frames. However, this approach requires high network bandwidth usage to collect a large amount of ADC samples from each gateway, which results in network congestion and high financial cost due to Internet data usage between the gateway and the Cloud server. In order to reduce the bandwidth usage of this data offloading operation, we propose a LPWAN packet acquisition mechanism based on joint sparse approximation.

AB - We propose a sparse approximation based joint-decoding system for LPWAN (LoRa) PHY-layer frame decoding. Recent research has shown that joint-decoding raw radio ADC samples in the Cloud offloaded from LPWAN gateways can decode weak radio signals by combining coherent frames. However, this approach requires high network bandwidth usage to collect a large amount of ADC samples from each gateway, which results in network congestion and high financial cost due to Internet data usage between the gateway and the Cloud server. In order to reduce the bandwidth usage of this data offloading operation, we propose a LPWAN packet acquisition mechanism based on joint sparse approximation.

KW - Joint sparse approximation

KW - LoRa

KW - LPWAN

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DO - 10.1145/3274783.3275165

M3 - RGC 32 - Refereed conference paper (with host publication)

AN - SCOPUS:85061755470

T3 - SenSys - Proceedings of the 16th Conference on Embedded Networked Sensor Systems

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BT - SenSys 2018 - Proceedings of the 16th Conference on Embedded Networked Sensor Systems

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Y2 - 4 November 2018 through 7 November 2018

ER -

Liu J, Xu W, Hu W. Poster abstract: Energy efficient LPWAN decoding via joint sparse approximation. In SenSys 2018 - Proceedings of the 16th Conference on Embedded Networked Sensor Systems. Association for Computing Machinery. 2018. p. 325-326. (SenSys - Proceedings of the 16th Conference on Embedded Networked Sensor Systems). Epub 2018 Nov 4. doi: 10.1145/3274783.3275165

Poster abstract: Energy efficient LPWAN decoding via joint sparse approximation

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