A Novel User Classification Method for Femtocell Network by Using Affinity Propagation Algorithm and Artificial Neural Network
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 proce...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/253787 |
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| author | Afaz Uddin Ahmed Mohammad Tariqul Islam Mahamod Ismail Salehin Kibria Haslina Arshad |
| author_facet | Afaz Uddin Ahmed Mohammad Tariqul Islam Mahamod Ismail Salehin Kibria Haslina Arshad |
| author_sort | Afaz Uddin Ahmed |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-287d1514a3504297b9371840ea2e5cf7 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-287d1514a3504297b9371840ea2e5cf72025-02-03T01:25:59ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/253787253787A Novel User Classification Method for Femtocell Network by Using Affinity Propagation Algorithm and Artificial Neural NetworkAfaz Uddin Ahmed0Mohammad Tariqul Islam1Mahamod Ismail2Salehin Kibria3Haslina Arshad4Space Science Centre (ANGKASA), Universiti Kebangsaan Malaysia (UKM), 43600 Bangi, Selangor, MalaysiaDepartment of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia (UKM), 43600 Bangi, Selangor, MalaysiaDepartment of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia (UKM), 43600 Bangi, Selangor, MalaysiaSpace Science Centre (ANGKASA), Universiti Kebangsaan Malaysia (UKM), 43600 Bangi, Selangor, MalaysiaCentre of Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), 43600 Bangi, Selangor, MalaysiaAn 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.http://dx.doi.org/10.1155/2014/253787 |
| spellingShingle | Afaz Uddin Ahmed Mohammad Tariqul Islam Mahamod Ismail Salehin Kibria Haslina Arshad A Novel User Classification Method for Femtocell Network by Using Affinity Propagation Algorithm and Artificial Neural Network The Scientific World Journal |
| title | A Novel User Classification Method for Femtocell Network by Using Affinity Propagation Algorithm and Artificial Neural Network |
| title_full | A Novel User Classification Method for Femtocell Network by Using Affinity Propagation Algorithm and Artificial Neural Network |
| title_fullStr | A Novel User Classification Method for Femtocell Network by Using Affinity Propagation Algorithm and Artificial Neural Network |
| title_full_unstemmed | A Novel User Classification Method for Femtocell Network by Using Affinity Propagation Algorithm and Artificial Neural Network |
| title_short | A Novel User Classification Method for Femtocell Network by Using Affinity Propagation Algorithm and Artificial Neural Network |
| title_sort | novel user classification method for femtocell network by using affinity propagation algorithm and artificial neural network |
| url | http://dx.doi.org/10.1155/2014/253787 |
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