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An Enhanced Genetic Algorithm to Optimize Network Parameters for Soft Handover in Universal Mobile Telecommunications Systems.

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Title: An Enhanced Genetic Algorithm to Optimize Network Parameters for Soft Handover in Universal Mobile Telecommunications Systems.
Authors: Tayyeba Minhas, Xu Ning, Satish Anamalamudi
Source: International Journal of Simulation: Systems, Science & Technology; 2016, Vol. 17 Issue 44, p32.1-32.8, 8p
Subject Terms: GENETIC algorithms, UNIVERSAL Mobile Telecommunications System, RADIO access networks
Abstract: In the Radio Access Networks guaranteed service levels and performance management are crucial factors because of limited licensed spectrum support of cognitive Mesh mobility and multimedia services. One way to enhance the performance of Radio Access Networks is by selecting appropriate network parameters and parameter optimization. Optimum network parameters can be selected by minimizing its corresponding predefined cost function with respect to key performance indicators and best proposed optimization algorithm. In our approach, enhanced Search and Optimization based Genetic Algorithm is used to optimize UMTS Soft Handover (SHO) Overhead network parameters with proposed (Window Add, Window Drop) to increase capacity and control downlink transmission power through minimizing its cost function with selection, crossover and mutation operations. Enhanced UMTS System Level Simulator with JGAP(Java Genetic Algorithm Package) and Bonn-motion mobility scenario tool is used to optimize network parameters with respect to its proposed cost function (KPI's) and compared with other existing intelligent optimization Algorithms(Ant colony optimization, Bee Colony Optimization, Particle Swarm Optimization(PSO). Simulation results shows that the performance of UMTS long term Evolution with modified GA is almost same as Bee colony optimization and outperforms when compared with PSO and Ant colony optimization. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Simulation: Systems, Science & Technology is the property of UK Simulation Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: An Enhanced Genetic Algorithm to Optimize Network Parameters for Soft Handover in Universal Mobile Telecommunications Systems.
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  Data: <searchLink fieldCode="AR" term="%22Tayyeba+Minhas%22">Tayyeba Minhas</searchLink><br /><searchLink fieldCode="AR" term="%22Xu+Ning%22">Xu Ning</searchLink><br /><searchLink fieldCode="AR" term="%22Satish+Anamalamudi%22">Satish Anamalamudi</searchLink>
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  Data: International Journal of Simulation: Systems, Science & Technology; 2016, Vol. 17 Issue 44, p32.1-32.8, 8p
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  Data: <searchLink fieldCode="DE" term="%22GENETIC+algorithms%22">GENETIC algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22UNIVERSAL+Mobile+Telecommunications+System%22">UNIVERSAL Mobile Telecommunications System</searchLink><br /><searchLink fieldCode="DE" term="%22RADIO+access+networks%22">RADIO access networks</searchLink>
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  Label: Abstract
  Group: Ab
  Data: In the Radio Access Networks guaranteed service levels and performance management are crucial factors because of limited licensed spectrum support of cognitive Mesh mobility and multimedia services. One way to enhance the performance of Radio Access Networks is by selecting appropriate network parameters and parameter optimization. Optimum network parameters can be selected by minimizing its corresponding predefined cost function with respect to key performance indicators and best proposed optimization algorithm. In our approach, enhanced Search and Optimization based Genetic Algorithm is used to optimize UMTS Soft Handover (SHO) Overhead network parameters with proposed (Window Add, Window Drop) to increase capacity and control downlink transmission power through minimizing its cost function with selection, crossover and mutation operations. Enhanced UMTS System Level Simulator with JGAP(Java Genetic Algorithm Package) and Bonn-motion mobility scenario tool is used to optimize network parameters with respect to its proposed cost function (KPI's) and compared with other existing intelligent optimization Algorithms(Ant colony optimization, Bee Colony Optimization, Particle Swarm Optimization(PSO). Simulation results shows that the performance of UMTS long term Evolution with modified GA is almost same as Bee colony optimization and outperforms when compared with PSO and Ant colony optimization. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Simulation: Systems, Science & Technology is the property of UK Simulation Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.5013/IJSSST.a.17.44.32
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        Text: English
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        StartPage: 32.1
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      – SubjectFull: GENETIC algorithms
        Type: general
      – SubjectFull: UNIVERSAL Mobile Telecommunications System
        Type: general
      – SubjectFull: RADIO access networks
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            NameFull: Tayyeba Minhas
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            NameFull: Xu Ning
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            NameFull: Satish Anamalamudi
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              Text: 2016
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