Optimizing distributed cooperative sensing performance using swarm intelligence

Cognitive radio (CR) technology offers attractive solution to overcome spectrum scarcity problem and improve spectrum utilization. Opportunistic spectrum access concept adopted by a CR network allows unlicensed or cognitive users (CUs) to access a frequency band that is not in use by the licensed or...

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Main Authors: Mohd, Alias, Sarijari, M. Adib, Fisal, N., Latiff, N. M. A., A. Rashid, Rozeha, Ariffin, S. H. S., Yusof, S. K. S., S. Baguda, Yacub
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Published: 2011
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Online Access:http://eprints.utm.my/id/eprint/46101/
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spelling my.utm.461012017-07-05T08:48:47Z http://eprints.utm.my/id/eprint/46101/ Optimizing distributed cooperative sensing performance using swarm intelligence Mohd, Alias Sarijari, M. Adib Fisal, N. Latiff, N. M. A. A. Rashid, Rozeha Ariffin, S. H. S. Yusof, S. K. S. S. Baguda, Yacub TK Electrical engineering. Electronics Nuclear engineering Cognitive radio (CR) technology offers attractive solution to overcome spectrum scarcity problem and improve spectrum utilization. Opportunistic spectrum access concept adopted by a CR network allows unlicensed or cognitive users (CUs) to access a frequency band that is not in use by the licensed or primary users (PUs). In enabling such spectrum-aware communication protocol, spectrum sensing becomes the fundamental requirement to exploit the unused spectrum and effectively protect the quality of service (QoS) of PUs. An increase in sensing time results in a higher detection probability (Pd) and lower false alarm probability (Pf), which leads to better protection of the primary users from harmful interference in addition to improved utilization of the available unused spectrum. However, this will reduce the amount of time for data transmission and hence, affects the achievable throughput of CUs. In this paper, this sensing-throughput trade off is addressed in terms of distributed approach of cooperative channel sensing. In order to find the optimal sensing time that maximizes the throughput of an OSA based CR network, the decision fusion scheme of OR rule are subjected to particle swarm optimization (PSO). The results show that a lower sensing time is achieved under PSO based cooperative sensing. The maximum achievable normalized throughput also increases with the increase of sensing terminals under optimal fusion scheme compared to normal fusion technique. 2011 Conference or Workshop Item PeerReviewed Mohd, Alias and Sarijari, M. Adib and Fisal, N. and Latiff, N. M. A. and A. Rashid, Rozeha and Ariffin, S. H. S. and Yusof, S. K. S. and S. Baguda, Yacub (2011) Optimizing distributed cooperative sensing performance using swarm intelligence. In: The International Conference On Informatics Engineering & Information Science (Icieis 2011). http://apps.webofknowledge.com.ezproxy.utm.my/Search.do?product=WOS&SID=Q1X85YxXCtZZKDY62ie&search_mode=GeneralSearch&prID=9ed76318-6524-4fdb-9067-628ed939e8f0
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Mohd, Alias
Sarijari, M. Adib
Fisal, N.
Latiff, N. M. A.
A. Rashid, Rozeha
Ariffin, S. H. S.
Yusof, S. K. S.
S. Baguda, Yacub
Optimizing distributed cooperative sensing performance using swarm intelligence
description Cognitive radio (CR) technology offers attractive solution to overcome spectrum scarcity problem and improve spectrum utilization. Opportunistic spectrum access concept adopted by a CR network allows unlicensed or cognitive users (CUs) to access a frequency band that is not in use by the licensed or primary users (PUs). In enabling such spectrum-aware communication protocol, spectrum sensing becomes the fundamental requirement to exploit the unused spectrum and effectively protect the quality of service (QoS) of PUs. An increase in sensing time results in a higher detection probability (Pd) and lower false alarm probability (Pf), which leads to better protection of the primary users from harmful interference in addition to improved utilization of the available unused spectrum. However, this will reduce the amount of time for data transmission and hence, affects the achievable throughput of CUs. In this paper, this sensing-throughput trade off is addressed in terms of distributed approach of cooperative channel sensing. In order to find the optimal sensing time that maximizes the throughput of an OSA based CR network, the decision fusion scheme of OR rule are subjected to particle swarm optimization (PSO). The results show that a lower sensing time is achieved under PSO based cooperative sensing. The maximum achievable normalized throughput also increases with the increase of sensing terminals under optimal fusion scheme compared to normal fusion technique.
format Conference or Workshop Item
author Mohd, Alias
Sarijari, M. Adib
Fisal, N.
Latiff, N. M. A.
A. Rashid, Rozeha
Ariffin, S. H. S.
Yusof, S. K. S.
S. Baguda, Yacub
author_facet Mohd, Alias
Sarijari, M. Adib
Fisal, N.
Latiff, N. M. A.
A. Rashid, Rozeha
Ariffin, S. H. S.
Yusof, S. K. S.
S. Baguda, Yacub
author_sort Mohd, Alias
title Optimizing distributed cooperative sensing performance using swarm intelligence
title_short Optimizing distributed cooperative sensing performance using swarm intelligence
title_full Optimizing distributed cooperative sensing performance using swarm intelligence
title_fullStr Optimizing distributed cooperative sensing performance using swarm intelligence
title_full_unstemmed Optimizing distributed cooperative sensing performance using swarm intelligence
title_sort optimizing distributed cooperative sensing performance using swarm intelligence
publishDate 2011
url http://eprints.utm.my/id/eprint/46101/
http://apps.webofknowledge.com.ezproxy.utm.my/Search.do?product=WOS&SID=Q1X85YxXCtZZKDY62ie&search_mode=GeneralSearch&prID=9ed76318-6524-4fdb-9067-628ed939e8f0
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score 13.211869