Sequential Compressive Sensing in Wireless Sensor Networks

Jinping Hao; Filippo Tosato; Robert J Piechocki

Sequential Compressive Sensing in Wireless Sensor Networks

Jinping Hao, Filippo Tosato, Robert J Piechocki

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

6 Citations (Scopus)

Abstract

Compressive sensing (CS) is a new signal acquisition framework, which allows for a signal recovery from far fewer samples than what is required by traditional sampling methods. In this paper we propose new strategies for adaptively adjusting the number of CS samples in wireless sensor networks (WSNs). Additionally, in the signal reconstruction procedure we apply homotopy algorithm to update the reconstructed signals. The reduction of CS samples and the homotopy update reduce the computational complexity and save processing time and energy for both the fusion centre and wireless sensors. The proposed techniques are investigated numerically in various WSN scenarios.

Original language	English
Title of host publication	Vehicular Technology Conference (VTC Spring), 2012 IEEE 75th
Publication status	Published - 2012

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@inproceedings{d3b22b0f255d4709b26affb2aa96a65c,

title = "Sequential Compressive Sensing in Wireless Sensor Networks",

abstract = "Compressive sensing (CS) is a new signal acquisition framework, which allows for a signal recovery from far fewer samples than what is required by traditional sampling methods. In this paper we propose new strategies for adaptively adjusting the number of CS samples in wireless sensor networks (WSNs). Additionally, in the signal reconstruction procedure we apply homotopy algorithm to update the reconstructed signals. The reduction of CS samples and the homotopy update reduce the computational complexity and save processing time and energy for both the fusion centre and wireless sensors. The proposed techniques are investigated numerically in various WSN scenarios.",

author = "Jinping Hao and Filippo Tosato and Piechocki, {Robert J}",

year = "2012",

language = "English",

booktitle = "Vehicular Technology Conference (VTC Spring), 2012 IEEE 75th",

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TY - GEN

T1 - Sequential Compressive Sensing in Wireless Sensor Networks

AU - Hao, Jinping

AU - Tosato, Filippo

AU - Piechocki, Robert J

PY - 2012

Y1 - 2012

N2 - Compressive sensing (CS) is a new signal acquisition framework, which allows for a signal recovery from far fewer samples than what is required by traditional sampling methods. In this paper we propose new strategies for adaptively adjusting the number of CS samples in wireless sensor networks (WSNs). Additionally, in the signal reconstruction procedure we apply homotopy algorithm to update the reconstructed signals. The reduction of CS samples and the homotopy update reduce the computational complexity and save processing time and energy for both the fusion centre and wireless sensors. The proposed techniques are investigated numerically in various WSN scenarios.

AB - Compressive sensing (CS) is a new signal acquisition framework, which allows for a signal recovery from far fewer samples than what is required by traditional sampling methods. In this paper we propose new strategies for adaptively adjusting the number of CS samples in wireless sensor networks (WSNs). Additionally, in the signal reconstruction procedure we apply homotopy algorithm to update the reconstructed signals. The reduction of CS samples and the homotopy update reduce the computational complexity and save processing time and energy for both the fusion centre and wireless sensors. The proposed techniques are investigated numerically in various WSN scenarios.

M3 - Conference Contribution (Conference Proceeding)

BT - Vehicular Technology Conference (VTC Spring), 2012 IEEE 75th

ER -