Dynamic characterized genetic algorithm for adaptive beam forming in WCDMA system
In this paper, a modified Genetic Algorithm named as Dynamic Characterized Genetic Algorithm (DCGA) is proposed. The new DCGA is then integrated into adaptive beam forming technique to reduce the power usage of adaptive antenna at WCDMA base station (Node B) for serving instantaneous mobile needs. A...
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my.uniten.dspace-297422023-12-28T16:08:40Z Dynamic characterized genetic algorithm for adaptive beam forming in WCDMA system Kiong T.S. Ismail M. Hassan A. 15128307800 7401908770 57226304105 Adaptive beam forming Dynamic characterized genetic algorithm WCDMA Adaptive systems Computer simulation Genetic algorithms Wireless telecommunication systems Adaptive antenna Adaptive beam forming Convergence rate WCDMA Code division multiple access In this paper, a modified Genetic Algorithm named as Dynamic Characterized Genetic Algorithm (DCGA) is proposed. The new DCGA is then integrated into adaptive beam forming technique to reduce the power usage of adaptive antenna at WCDMA base station (Node B) for serving instantaneous mobile needs. As contradict to conventional GA, DCGA is able to adapt itself in chromosome representation and number of crossover points in order to reduce unnecessary searching space and thus, increase convergence rate efficiently. Power usage at Node B is used as fitness function to compare the performance of DCGA and GA. Simulation result has shown that DCGA converges faster and is superior in adaptive beam forming in the aspect of power usage at Node B as compared to conventional GA. � 2005 IEEE. Final 2023-12-28T08:08:40Z 2023-12-28T08:08:40Z 2005 Conference paper 10.1109/ICON.2005.1635472 2-s2.0-33847286403 https://www.scopus.com/inward/record.uri?eid=2-s2.0-33847286403&doi=10.1109%2fICON.2005.1635472&partnerID=40&md5=d6c7b5c3f809c6f94409e8a06c42e573 https://irepository.uniten.edu.my/handle/123456789/29742 1 1635472 219 224 Scopus |
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Adaptive beam forming Dynamic characterized genetic algorithm WCDMA Adaptive systems Computer simulation Genetic algorithms Wireless telecommunication systems Adaptive antenna Adaptive beam forming Convergence rate WCDMA Code division multiple access |
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Adaptive beam forming Dynamic characterized genetic algorithm WCDMA Adaptive systems Computer simulation Genetic algorithms Wireless telecommunication systems Adaptive antenna Adaptive beam forming Convergence rate WCDMA Code division multiple access Kiong T.S. Ismail M. Hassan A. Dynamic characterized genetic algorithm for adaptive beam forming in WCDMA system |
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In this paper, a modified Genetic Algorithm named as Dynamic Characterized Genetic Algorithm (DCGA) is proposed. The new DCGA is then integrated into adaptive beam forming technique to reduce the power usage of adaptive antenna at WCDMA base station (Node B) for serving instantaneous mobile needs. As contradict to conventional GA, DCGA is able to adapt itself in chromosome representation and number of crossover points in order to reduce unnecessary searching space and thus, increase convergence rate efficiently. Power usage at Node B is used as fitness function to compare the performance of DCGA and GA. Simulation result has shown that DCGA converges faster and is superior in adaptive beam forming in the aspect of power usage at Node B as compared to conventional GA. � 2005 IEEE. |
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15128307800 |
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15128307800 Kiong T.S. Ismail M. Hassan A. |
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Conference paper |
author |
Kiong T.S. Ismail M. Hassan A. |
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Kiong T.S. |
title |
Dynamic characterized genetic algorithm for adaptive beam forming in WCDMA system |
title_short |
Dynamic characterized genetic algorithm for adaptive beam forming in WCDMA system |
title_full |
Dynamic characterized genetic algorithm for adaptive beam forming in WCDMA system |
title_fullStr |
Dynamic characterized genetic algorithm for adaptive beam forming in WCDMA system |
title_full_unstemmed |
Dynamic characterized genetic algorithm for adaptive beam forming in WCDMA system |
title_sort |
dynamic characterized genetic algorithm for adaptive beam forming in wcdma system |
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2023 |
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1806426307239608320 |