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neural network-based receiver for interference cancellation in multi-user environment for DS/CDMA systems

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Date Issued:
2003
Summary:
The objective of this work is to apply and investigate the performance of a neural network-based receiver for interference cancellation in multiuser direct sequence code division multiple access (DSCDMA) wireless networks. This research investigates a Receiver model which uses Neural Network receiver in combination with a conventional receiver system to provide an efficient mechanism for the Interference Suppression in DS/CDMA systems. The Conventional receiver is used for the time during which the neural network receiver is being trained. Once the NN receiver is trained the conventional receiver system is deactivated. It is demonstrated that this receiver when used along with an efficient Neural network model can outperform MMSE receiver or DFFLE receiver with significant advantages, such as improved bit-error ratio (BER) performance, adaptive operation, single-user detection in DS/CDMA environment and a near far resistant system.
Title: A neural network-based receiver for interference cancellation in multi-user environment for DS/CDMA systems.
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Name(s): Shukla, Kunal Hemang.
Florida Atlantic University, Degree grantor
Pandya, Abhijit S., Thesis advisor
College of Engineering and Computer Science
Department of Computer and Electrical Engineering and Computer Science
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Issuance: monographic
Date Issued: 2003
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 106 p.
Language(s): English
Summary: The objective of this work is to apply and investigate the performance of a neural network-based receiver for interference cancellation in multiuser direct sequence code division multiple access (DSCDMA) wireless networks. This research investigates a Receiver model which uses Neural Network receiver in combination with a conventional receiver system to provide an efficient mechanism for the Interference Suppression in DS/CDMA systems. The Conventional receiver is used for the time during which the neural network receiver is being trained. Once the NN receiver is trained the conventional receiver system is deactivated. It is demonstrated that this receiver when used along with an efficient Neural network model can outperform MMSE receiver or DFFLE receiver with significant advantages, such as improved bit-error ratio (BER) performance, adaptive operation, single-user detection in DS/CDMA environment and a near far resistant system.
Identifier: 9780496179121 (isbn), 12975 (digitool), FADT12975 (IID), fau:9843 (fedora)
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): College of Engineering and Computer Science
Thesis (M.S.)--Florida Atlantic University, 2003.
Subject(s): Neural networks (Computer science)
Wireless communication systems
Code division multiple access
Held by: Florida Atlantic University Libraries
Persistent Link to This Record: http://purl.flvc.org/fcla/dt/12975
Sublocation: Digital Library
Use and Reproduction: Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.