Cognitive radio: Cyclostationarity-based classification approach for analog TV and wireless microphone signals

In cognitive radio system, different primary signals have different protection requirements and operating parameters. So, classification of primary signals at secondary user receiver is needed to achieve these requirements of protection and support scalability. Scalability means changing operating p...

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Main Authors: V., Jeoti, A.M., Mossa
Format: Conference or Workshop Item
Published: 2009
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Online Access:http://eprints.utp.edu.my/363/1/paper.pdf
http://www.scopus.com/inward/record.url?eid=2-s2.0-70449090690&partnerID=40&md5=eaada311832d989eb6071e93adaddcb8
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Institution: Universiti Teknologi Petronas
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spelling my.utp.eprints.3632017-01-19T08:25:58Z Cognitive radio: Cyclostationarity-based classification approach for analog TV and wireless microphone signals V., Jeoti A.M., Mossa TK Electrical engineering. Electronics Nuclear engineering In cognitive radio system, different primary signals have different protection requirements and operating parameters. So, classification of primary signals at secondary user receiver is needed to achieve these requirements of protection and support scalability. Scalability means changing operating parameters according to the current conditions which one of them is the primary signal that occupies the spectrum band. In this paper, we propose an approach to classify the primary signal either TV-PAL signal or wireless microphone signal using cyclostationary features in the context of IEEE 802.22 Wireless Regional Area Network (WRAN). The performance of the proposed approach is evaluated by probability of correct classification. This knowledge of identifying the primary signals can be applied for bandwidth scalability to use fractions of TV channel when it is occupied by wireless microphone signal. The results show that the proposed approach performs well in low signal-to-noise ratio (LSNR) and it is expected to increase the overall spectrum utilization of WRAN cognitive radio as well. © 2009 IEEE. 2009 Conference or Workshop Item NonPeerReviewed application/pdf http://eprints.utp.edu.my/363/1/paper.pdf http://www.scopus.com/inward/record.url?eid=2-s2.0-70449090690&partnerID=40&md5=eaada311832d989eb6071e93adaddcb8 V., Jeoti and A.M., Mossa (2009) Cognitive radio: Cyclostationarity-based classification approach for analog TV and wireless microphone signals. In: 2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009, 25 July 2009 through 26 July 2009, Kuala Lumpur. http://eprints.utp.edu.my/363/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
V., Jeoti
A.M., Mossa
Cognitive radio: Cyclostationarity-based classification approach for analog TV and wireless microphone signals
description In cognitive radio system, different primary signals have different protection requirements and operating parameters. So, classification of primary signals at secondary user receiver is needed to achieve these requirements of protection and support scalability. Scalability means changing operating parameters according to the current conditions which one of them is the primary signal that occupies the spectrum band. In this paper, we propose an approach to classify the primary signal either TV-PAL signal or wireless microphone signal using cyclostationary features in the context of IEEE 802.22 Wireless Regional Area Network (WRAN). The performance of the proposed approach is evaluated by probability of correct classification. This knowledge of identifying the primary signals can be applied for bandwidth scalability to use fractions of TV channel when it is occupied by wireless microphone signal. The results show that the proposed approach performs well in low signal-to-noise ratio (LSNR) and it is expected to increase the overall spectrum utilization of WRAN cognitive radio as well. © 2009 IEEE.
format Conference or Workshop Item
author V., Jeoti
A.M., Mossa
author_facet V., Jeoti
A.M., Mossa
author_sort V., Jeoti
title Cognitive radio: Cyclostationarity-based classification approach for analog TV and wireless microphone signals
title_short Cognitive radio: Cyclostationarity-based classification approach for analog TV and wireless microphone signals
title_full Cognitive radio: Cyclostationarity-based classification approach for analog TV and wireless microphone signals
title_fullStr Cognitive radio: Cyclostationarity-based classification approach for analog TV and wireless microphone signals
title_full_unstemmed Cognitive radio: Cyclostationarity-based classification approach for analog TV and wireless microphone signals
title_sort cognitive radio: cyclostationarity-based classification approach for analog tv and wireless microphone signals
publishDate 2009
url http://eprints.utp.edu.my/363/1/paper.pdf
http://www.scopus.com/inward/record.url?eid=2-s2.0-70449090690&partnerID=40&md5=eaada311832d989eb6071e93adaddcb8
http://eprints.utp.edu.my/363/
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