Convex optimization–based multi-user detection in underwater acoustic sensor networks

Multi-carrier code-division multiple access is an important technical means for high-performance underwater acoustic sensor networks. Nevertheless, severe multiple access interference is a huge challenge. As the core technology, multi-user detection is used to eliminate multiple access interference....
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Autor*in:	Jianping Wang [verfasserIn] Shujing Zhang [verfasserIn] Wei Chen [verfasserIn] Dechuan Kong [verfasserIn] Zhou Yu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Übergeordnetes Werk:	In: International Journal of Distributed Sensor Networks - SAGE Publishing, 2011, 14(2018)
Übergeordnetes Werk:	volume:14 ; year:2018

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1177/1550147718757665

Katalog-ID:	DOAJ041459342

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allfieldsSound	10.1177/1550147718757665 doi (DE-627)DOAJ041459342 (DE-599)DOAJ90adab8e49a54fb0ae90c73c5210075a DE-627 ger DE-627 rakwb eng QA75.5-76.95 Jianping Wang verfasserin aut Convex optimization–based multi-user detection in underwater acoustic sensor networks 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Multi-carrier code-division multiple access is an important technical means for high-performance underwater acoustic sensor networks. Nevertheless, severe multiple access interference is a huge challenge. As the core technology, multi-user detection is used to eliminate multiple access interference. The traditional optimal detection algorithms (e.g. maximum likelihood) have very high computational complexity, and the performances of suboptimal detection methods (i.e. zero forcing, minimum mean square error, etc.) are poor. Therefore, taking into account the characteristics of underwater acoustic sensor networks, it is of great significance to design multi-user detection algorithms for achieving a tradeoff between the detection performance and the computational complexity in multi-carrier code-division multiple access systems. In this article, we design a transmitter model of underwater multi-carrier code-division multiple access system and then implement a multi-user detection algorithm based on convex optimization, which is named convex optimization–based algorithm. Next, we conduct the detection performance and computational complexity comparisons of maximum likelihood, zero forcing, minimum mean square error, and convex optimization–based algorithm. The results show that the performance of convex optimization–based algorithm is close to that of maximum likelihood, and the complexity is close to that of zero forcing. Therefore, a tradeoff between the computational complexity and the detection performance is realized in convex optimization–based algorithm. It means that convex optimization–based algorithm is suitable for the multi-user detection in multi-carrier code-division multiple access systems of underwater acoustic sensor networks. Electronic computers. Computer science Shujing Zhang verfasserin aut Wei Chen verfasserin aut Dechuan Kong verfasserin aut Zhou Yu verfasserin aut In International Journal of Distributed Sensor Networks SAGE Publishing, 2011 14(2018) (DE-627)490718124 (DE-600)2192922-1 15501477 nnns volume:14 year:2018 https://doi.org/10.1177/1550147718757665 kostenfrei https://doaj.org/article/90adab8e49a54fb0ae90c73c5210075a kostenfrei https://doi.org/10.1177/1550147718757665 kostenfrei https://doaj.org/toc/1550-1477 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2119 GBV_ILN_2706 GBV_ILN_2707 GBV_ILN_2890 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2018
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author	Jianping Wang
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topic_title	QA75.5-76.95 Convex optimization–based multi-user detection in underwater acoustic sensor networks
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title	Convex optimization–based multi-user detection in underwater acoustic sensor networks
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title_full	Convex optimization–based multi-user detection in underwater acoustic sensor networks
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title_sort	convex optimization–based multi-user detection in underwater acoustic sensor networks
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title_auth	Convex optimization–based multi-user detection in underwater acoustic sensor networks
abstract	Multi-carrier code-division multiple access is an important technical means for high-performance underwater acoustic sensor networks. Nevertheless, severe multiple access interference is a huge challenge. As the core technology, multi-user detection is used to eliminate multiple access interference. The traditional optimal detection algorithms (e.g. maximum likelihood) have very high computational complexity, and the performances of suboptimal detection methods (i.e. zero forcing, minimum mean square error, etc.) are poor. Therefore, taking into account the characteristics of underwater acoustic sensor networks, it is of great significance to design multi-user detection algorithms for achieving a tradeoff between the detection performance and the computational complexity in multi-carrier code-division multiple access systems. In this article, we design a transmitter model of underwater multi-carrier code-division multiple access system and then implement a multi-user detection algorithm based on convex optimization, which is named convex optimization–based algorithm. Next, we conduct the detection performance and computational complexity comparisons of maximum likelihood, zero forcing, minimum mean square error, and convex optimization–based algorithm. The results show that the performance of convex optimization–based algorithm is close to that of maximum likelihood, and the complexity is close to that of zero forcing. Therefore, a tradeoff between the computational complexity and the detection performance is realized in convex optimization–based algorithm. It means that convex optimization–based algorithm is suitable for the multi-user detection in multi-carrier code-division multiple access systems of underwater acoustic sensor networks.
abstractGer	Multi-carrier code-division multiple access is an important technical means for high-performance underwater acoustic sensor networks. Nevertheless, severe multiple access interference is a huge challenge. As the core technology, multi-user detection is used to eliminate multiple access interference. The traditional optimal detection algorithms (e.g. maximum likelihood) have very high computational complexity, and the performances of suboptimal detection methods (i.e. zero forcing, minimum mean square error, etc.) are poor. Therefore, taking into account the characteristics of underwater acoustic sensor networks, it is of great significance to design multi-user detection algorithms for achieving a tradeoff between the detection performance and the computational complexity in multi-carrier code-division multiple access systems. In this article, we design a transmitter model of underwater multi-carrier code-division multiple access system and then implement a multi-user detection algorithm based on convex optimization, which is named convex optimization–based algorithm. Next, we conduct the detection performance and computational complexity comparisons of maximum likelihood, zero forcing, minimum mean square error, and convex optimization–based algorithm. The results show that the performance of convex optimization–based algorithm is close to that of maximum likelihood, and the complexity is close to that of zero forcing. Therefore, a tradeoff between the computational complexity and the detection performance is realized in convex optimization–based algorithm. It means that convex optimization–based algorithm is suitable for the multi-user detection in multi-carrier code-division multiple access systems of underwater acoustic sensor networks.
abstract_unstemmed	Multi-carrier code-division multiple access is an important technical means for high-performance underwater acoustic sensor networks. Nevertheless, severe multiple access interference is a huge challenge. As the core technology, multi-user detection is used to eliminate multiple access interference. The traditional optimal detection algorithms (e.g. maximum likelihood) have very high computational complexity, and the performances of suboptimal detection methods (i.e. zero forcing, minimum mean square error, etc.) are poor. Therefore, taking into account the characteristics of underwater acoustic sensor networks, it is of great significance to design multi-user detection algorithms for achieving a tradeoff between the detection performance and the computational complexity in multi-carrier code-division multiple access systems. In this article, we design a transmitter model of underwater multi-carrier code-division multiple access system and then implement a multi-user detection algorithm based on convex optimization, which is named convex optimization–based algorithm. Next, we conduct the detection performance and computational complexity comparisons of maximum likelihood, zero forcing, minimum mean square error, and convex optimization–based algorithm. The results show that the performance of convex optimization–based algorithm is close to that of maximum likelihood, and the complexity is close to that of zero forcing. Therefore, a tradeoff between the computational complexity and the detection performance is realized in convex optimization–based algorithm. It means that convex optimization–based algorithm is suitable for the multi-user detection in multi-carrier code-division multiple access systems of underwater acoustic sensor networks.
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title_short	Convex optimization–based multi-user detection in underwater acoustic sensor networks
url	https://doi.org/10.1177/1550147718757665 https://doaj.org/article/90adab8e49a54fb0ae90c73c5210075a https://doaj.org/toc/1550-1477
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up_date	2024-07-03T20:21:50.906Z
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