A novel user classification method for femtocell network by using affinity propagation algorithm and artificial neural network

Afaz Uddin Ahmed, Mohammad Tariqul Islam, Mahamod Ismail, Salehin Kibria, Haslina Arshad

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

An artificial neural network (ANN) and affinity propagation (AP) algorithm based user categorization technique is presented. The proposed algorithm is designed for closed access femtocell network. ANN is used for user classification process and AP algorithm is used to optimize the ANN training process. AP selects the best possible training samples for faster ANN training cycle.The users are distinguished by using the difference of received signal strength in a multielement femtocell device. A previously developed directive microstrip antenna is used to configure the femtocell device. Simulation results show that, for a particular house pattern, the categorization technique without AP algorithm takes 5 indoor users and 10 outdoor users to attain an error-free operation. While integrating AP algorithm with ANN, the system takes 60% less training samples reducing the training time up to 50%. This procedure makes the femtocell more effective for closed access operation.

Original languageEnglish
Article number253787
JournalScientific World Journal
Volume2014
DOIs
Publication statusPublished - 2014

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Femtocell
artificial neural network
Neural networks
Directive antennas
Equipment and Supplies
Microstrip antennas
antenna
method
simulation

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Environmental Science(all)
  • Medicine(all)

Cite this

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abstract = "An artificial neural network (ANN) and affinity propagation (AP) algorithm based user categorization technique is presented. The proposed algorithm is designed for closed access femtocell network. ANN is used for user classification process and AP algorithm is used to optimize the ANN training process. AP selects the best possible training samples for faster ANN training cycle.The users are distinguished by using the difference of received signal strength in a multielement femtocell device. A previously developed directive microstrip antenna is used to configure the femtocell device. Simulation results show that, for a particular house pattern, the categorization technique without AP algorithm takes 5 indoor users and 10 outdoor users to attain an error-free operation. While integrating AP algorithm with ANN, the system takes 60{\%} less training samples reducing the training time up to 50{\%}. This procedure makes the femtocell more effective for closed access operation.",
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AU - Islam, Mohammad Tariqul

AU - Ismail, Mahamod

AU - Kibria, Salehin

AU - Arshad, Haslina

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