Sparse Signal Aloha: A Compressive Sensing-Based Method for Uncoordinated Multiple Access

Liantao Wu; Peng Sun; Ming Xiao; Yuhen Hu; Zhi Wang

doi:10.1109/LCOMM.2017.2666809

Sparse Signal Aloha: A Compressive Sensing-Based Method for Uncoordinated Multiple Access

Liantao Wu, Peng Sun, Ming Xiao, Yuhen Hu, Zhi Wang

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

We investigate the problem of sparse signal medium access control in the wireless sensor networks. The proposed sparse signal Aloha (SSA) transmits sampled compressive data to the fusion center using Aloha random access protocol. In order to maximize the overall data transmission rate in the presence of packet collision, redundant data are randomly subsampled at individual sensor nodes according to an optimal subsampling rate before transmission. Data loss due to random subsampling and collision in the wireless channel are compensated using compressive sensing recovery method at the fusion center. Simulation results verify the theoretical analysis and show the significant improvement of SSA compared with existing CS-based random access method.

Original language	English
Article number	7849200
Pages (from-to)	1301-1304
Number of pages	4
Journal	IEEE Communications Letters
Volume	21
Issue number	6
DOIs	https://doi.org/10.1109/LCOMM.2017.2666809
State	Published - Jun 2017
Externally published	Yes

Keywords

Aloha
Sparse signal transmission
compressive sensing
optimal subsampling rate
wireless sensor networks

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10.1109/LCOMM.2017.2666809

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title = "Sparse Signal Aloha: A Compressive Sensing-Based Method for Uncoordinated Multiple Access",

abstract = "We investigate the problem of sparse signal medium access control in the wireless sensor networks. The proposed sparse signal Aloha (SSA) transmits sampled compressive data to the fusion center using Aloha random access protocol. In order to maximize the overall data transmission rate in the presence of packet collision, redundant data are randomly subsampled at individual sensor nodes according to an optimal subsampling rate before transmission. Data loss due to random subsampling and collision in the wireless channel are compensated using compressive sensing recovery method at the fusion center. Simulation results verify the theoretical analysis and show the significant improvement of SSA compared with existing CS-based random access method.",

keywords = "Aloha, Sparse signal transmission, compressive sensing, optimal subsampling rate, wireless sensor networks",

author = "Liantao Wu and Peng Sun and Ming Xiao and Yuhen Hu and Zhi Wang",

note = "Publisher Copyright: {\textcopyright} 1997-2012 IEEE.",

year = "2017",

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doi = "10.1109/LCOMM.2017.2666809",

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T2 - A Compressive Sensing-Based Method for Uncoordinated Multiple Access

AU - Wu, Liantao

AU - Sun, Peng

AU - Xiao, Ming

AU - Hu, Yuhen

AU - Wang, Zhi

PY - 2017/6

Y1 - 2017/6

N2 - We investigate the problem of sparse signal medium access control in the wireless sensor networks. The proposed sparse signal Aloha (SSA) transmits sampled compressive data to the fusion center using Aloha random access protocol. In order to maximize the overall data transmission rate in the presence of packet collision, redundant data are randomly subsampled at individual sensor nodes according to an optimal subsampling rate before transmission. Data loss due to random subsampling and collision in the wireless channel are compensated using compressive sensing recovery method at the fusion center. Simulation results verify the theoretical analysis and show the significant improvement of SSA compared with existing CS-based random access method.

AB - We investigate the problem of sparse signal medium access control in the wireless sensor networks. The proposed sparse signal Aloha (SSA) transmits sampled compressive data to the fusion center using Aloha random access protocol. In order to maximize the overall data transmission rate in the presence of packet collision, redundant data are randomly subsampled at individual sensor nodes according to an optimal subsampling rate before transmission. Data loss due to random subsampling and collision in the wireless channel are compensated using compressive sensing recovery method at the fusion center. Simulation results verify the theoretical analysis and show the significant improvement of SSA compared with existing CS-based random access method.

KW - Aloha

KW - Sparse signal transmission

KW - compressive sensing

KW - optimal subsampling rate

KW - wireless sensor networks

UR - https://www.scopus.com/pages/publications/85020901976

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DO - 10.1109/LCOMM.2017.2666809

M3 - 文章

AN - SCOPUS:85020901976

SN - 1089-7798

VL - 21

SP - 1301

EP - 1304

JO - IEEE Communications Letters

JF - IEEE Communications Letters

IS - 6

M1 - 7849200

ER -

Sparse Signal Aloha: A Compressive Sensing-Based Method for Uncoordinated Multiple Access

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Keywords

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