Joint Power Control, Base Station Assignment, and Channel Assignment in Cognitive Femtocell Networks
Cognitive radio and femtocells are recent technology breakthroughs that aim to achieve throughput improvement by means of spectrum management and interference mitigation, respectively. However, these technologies are limited by the former's susceptibility to interference and the latter&#...
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Series: | EURASIP Journal on Wireless Communications and Networking |
Online Access: | http://dx.doi.org/10.1155/2010/285714 |
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doaj-4aa8322ef41747bbbff53366cfb298332020-11-25T00:29:20ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14721687-14992010-01-01201010.1155/2010/285714Joint Power Control, Base Station Assignment, and Channel Assignment in Cognitive Femtocell NetworksJohn Paul M. TorregozaRentsen EnkhbatWon-Joo HwangCognitive radio and femtocells are recent technology breakthroughs that aim to achieve throughput improvement by means of spectrum management and interference mitigation, respectively. However, these technologies are limited by the former's susceptibility to interference and the latter's dependence on bandwidth availability. In this paper, we overcome these limitations by integrating cognitive radio and femtocell technology and exploring its feasibility and throughput improvement. To realize this, we propose an integrated architecture and formulate a multiobjective optimization problem with mixed integer variables for the joint power control, base station assignment, and channel assignment scheme. In order to find a pareto optimal solution, a weighted sum approach was used. Based on numerical results, the optimization framework is found to be both stable and converging. Simulation studies further show that the proposed architecture and optimization framework improve the aggregate throughput as the client population rises, hence confirming the successful and beneficial integration of these technologies. http://dx.doi.org/10.1155/2010/285714 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
John Paul M. Torregoza Rentsen Enkhbat Won-Joo Hwang |
spellingShingle |
John Paul M. Torregoza Rentsen Enkhbat Won-Joo Hwang Joint Power Control, Base Station Assignment, and Channel Assignment in Cognitive Femtocell Networks EURASIP Journal on Wireless Communications and Networking |
author_facet |
John Paul M. Torregoza Rentsen Enkhbat Won-Joo Hwang |
author_sort |
John Paul M. Torregoza |
title |
Joint Power Control, Base Station Assignment, and Channel Assignment in Cognitive Femtocell Networks |
title_short |
Joint Power Control, Base Station Assignment, and Channel Assignment in Cognitive Femtocell Networks |
title_full |
Joint Power Control, Base Station Assignment, and Channel Assignment in Cognitive Femtocell Networks |
title_fullStr |
Joint Power Control, Base Station Assignment, and Channel Assignment in Cognitive Femtocell Networks |
title_full_unstemmed |
Joint Power Control, Base Station Assignment, and Channel Assignment in Cognitive Femtocell Networks |
title_sort |
joint power control, base station assignment, and channel assignment in cognitive femtocell networks |
publisher |
SpringerOpen |
series |
EURASIP Journal on Wireless Communications and Networking |
issn |
1687-1472 1687-1499 |
publishDate |
2010-01-01 |
description |
Cognitive radio and femtocells are recent technology breakthroughs that aim to achieve throughput improvement by means of spectrum management and interference mitigation, respectively. However, these technologies are limited by the former's susceptibility to interference and the latter's dependence on bandwidth availability. In this paper, we overcome these limitations by integrating cognitive radio and femtocell technology and exploring its feasibility and throughput improvement. To realize this, we propose an integrated architecture and formulate a multiobjective optimization problem with mixed integer variables for the joint power control, base station assignment, and channel assignment scheme. In order to find a pareto optimal solution, a weighted sum approach was used. Based on numerical results, the optimization framework is found to be both stable and converging. Simulation studies further show that the proposed architecture and optimization framework improve the aggregate throughput as the client population rises, hence confirming the successful and beneficial integration of these technologies. |
url |
http://dx.doi.org/10.1155/2010/285714 |
work_keys_str_mv |
AT johnpaulmtorregoza jointpowercontrolbasestationassignmentandchannelassignmentincognitivefemtocellnetworks AT rentsenenkhbat jointpowercontrolbasestationassignmentandchannelassignmentincognitivefemtocellnetworks AT wonjoohwang jointpowercontrolbasestationassignmentandchannelassignmentincognitivefemtocellnetworks |
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