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Hybrid artificial intelligent algorithm for call admission control in WCDMA mobile network

In wideband code division multiple access (WCDMA) mobile network, total transmission power of Node B depends on diverse factors such as accommodation of new service request, termination of active user equipment (UE) and movement of UE. This makes power prediction a complicated task. In this paper, s...

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Main Authors: Tee, Y.K., Tiong, S.K., Johnny, K.S.P., Yeoh, E.C.
Format: Conference Paper
Language:en_US
Published: 2017
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spelling my.uniten.dspace-58472018-01-08T04:20:35Z Hybrid artificial intelligent algorithm for call admission control in WCDMA mobile network Tee, Y.K. Tiong, S.K. Johnny, K.S.P. Yeoh, E.C. In wideband code division multiple access (WCDMA) mobile network, total transmission power of Node B depends on diverse factors such as accommodation of new service request, termination of active user equipment (UE) and movement of UE. This makes power prediction a complicated task. In this paper, support vector regression (SVR) has been implemented successfully to forecast next interval power consumption at Node B with different type of antenna system. The predicted output is used by WCDMA mobile network to make decision on new service request admission. Genetic algorithm is then applied to form beams with minimum power to cover all UEs in a macro cell. The proposed algorithm, support vector regression assists genetic algorithm (SVRaGA) was tested in a dynamic WCDMA mobile network simulator. Simulation results have shown SVR can predict next cycle power usage at Node B with excellent accuracy and improve the quality of service (QoS) by minimizing dropped calls in the system. © 2008 IEEE. 2017-12-08T07:26:41Z 2017-12-08T07:26:41Z 2008 Conference Paper 10.1109/NCTT.2008.4814303 en_US Proceedings of IEEE 2008 6th National Conference on Telecommunication Technologies and IEEE 2008 2nd Malaysia Conference on Photonics, NCTT-MCP 2008
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language en_US
description In wideband code division multiple access (WCDMA) mobile network, total transmission power of Node B depends on diverse factors such as accommodation of new service request, termination of active user equipment (UE) and movement of UE. This makes power prediction a complicated task. In this paper, support vector regression (SVR) has been implemented successfully to forecast next interval power consumption at Node B with different type of antenna system. The predicted output is used by WCDMA mobile network to make decision on new service request admission. Genetic algorithm is then applied to form beams with minimum power to cover all UEs in a macro cell. The proposed algorithm, support vector regression assists genetic algorithm (SVRaGA) was tested in a dynamic WCDMA mobile network simulator. Simulation results have shown SVR can predict next cycle power usage at Node B with excellent accuracy and improve the quality of service (QoS) by minimizing dropped calls in the system. © 2008 IEEE.
format Conference Paper
author Tee, Y.K.
Tiong, S.K.
Johnny, K.S.P.
Yeoh, E.C.
spellingShingle Tee, Y.K.
Tiong, S.K.
Johnny, K.S.P.
Yeoh, E.C.
Hybrid artificial intelligent algorithm for call admission control in WCDMA mobile network
author_facet Tee, Y.K.
Tiong, S.K.
Johnny, K.S.P.
Yeoh, E.C.
author_sort Tee, Y.K.
title Hybrid artificial intelligent algorithm for call admission control in WCDMA mobile network
title_short Hybrid artificial intelligent algorithm for call admission control in WCDMA mobile network
title_full Hybrid artificial intelligent algorithm for call admission control in WCDMA mobile network
title_fullStr Hybrid artificial intelligent algorithm for call admission control in WCDMA mobile network
title_full_unstemmed Hybrid artificial intelligent algorithm for call admission control in WCDMA mobile network
title_sort hybrid artificial intelligent algorithm for call admission control in wcdma mobile network
publishDate 2017
_version_ 1644493789716283392
score 13.211869

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