Design and Detection of Multilinear Chirp Signals for Underwater Acoustic Sensor Networks

In Underwater Acoustic Sensor Networks (UW-ASNs), some key problems have attracted more and more attention, including power consumption, performance of multiple access, and complexity of node. Motivated by finding reduced power consumption and improved performance of multiple access in UW-ASNs, a mu...

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Main Authors: En Cheng, Shengli Chen, Fei Yuan
Format: Article
Language:English
Published: SAGE Publishing 2015-11-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1155/2015/371579
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spelling doaj-554fa53b52e64b21b87b96021a01f9c02020-11-25T03:34:12ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772015-11-011110.1155/2015/371579371579Design and Detection of Multilinear Chirp Signals for Underwater Acoustic Sensor NetworksEn ChengShengli ChenFei YuanIn Underwater Acoustic Sensor Networks (UW-ASNs), some key problems have attracted more and more attention, including power consumption, performance of multiple access, and complexity of node. Motivated by finding reduced power consumption and improved performance of multiple access in UW-ASNs, a multilinear chirp-Code Division Multiple Access (MLC-CDMA) scheme is proposed. The differences between single slope chirp signal and multilinear chirp signal are analyzed in the paper. At the receiving end, a new detection technique called mixing-change rate along with fractional Fourier transform (MCR-FrFT) is proposed to detect the multirate chirp (MRC) signal and reduce complexity of node. There are two steps to realize the detection technique MCR-FrFT. By using the MCR-FrFT, the computation of detection can be decreased to 50% compared with direct FrFT. The simulation results indicate that, using the MCR-FrFT technique, the different users' signal can be separated and detected rapidly.https://doi.org/10.1155/2015/371579
collection DOAJ
language English
format Article
sources DOAJ
author En Cheng
Shengli Chen
Fei Yuan
spellingShingle En Cheng
Shengli Chen
Fei Yuan
Design and Detection of Multilinear Chirp Signals for Underwater Acoustic Sensor Networks
International Journal of Distributed Sensor Networks
author_facet En Cheng
Shengli Chen
Fei Yuan
author_sort En Cheng
title Design and Detection of Multilinear Chirp Signals for Underwater Acoustic Sensor Networks
title_short Design and Detection of Multilinear Chirp Signals for Underwater Acoustic Sensor Networks
title_full Design and Detection of Multilinear Chirp Signals for Underwater Acoustic Sensor Networks
title_fullStr Design and Detection of Multilinear Chirp Signals for Underwater Acoustic Sensor Networks
title_full_unstemmed Design and Detection of Multilinear Chirp Signals for Underwater Acoustic Sensor Networks
title_sort design and detection of multilinear chirp signals for underwater acoustic sensor networks
publisher SAGE Publishing
series International Journal of Distributed Sensor Networks
issn 1550-1477
publishDate 2015-11-01
description In Underwater Acoustic Sensor Networks (UW-ASNs), some key problems have attracted more and more attention, including power consumption, performance of multiple access, and complexity of node. Motivated by finding reduced power consumption and improved performance of multiple access in UW-ASNs, a multilinear chirp-Code Division Multiple Access (MLC-CDMA) scheme is proposed. The differences between single slope chirp signal and multilinear chirp signal are analyzed in the paper. At the receiving end, a new detection technique called mixing-change rate along with fractional Fourier transform (MCR-FrFT) is proposed to detect the multirate chirp (MRC) signal and reduce complexity of node. There are two steps to realize the detection technique MCR-FrFT. By using the MCR-FrFT, the computation of detection can be decreased to 50% compared with direct FrFT. The simulation results indicate that, using the MCR-FrFT technique, the different users' signal can be separated and detected rapidly.
url https://doi.org/10.1155/2015/371579
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