Adaptive cost-based handover decision algorithm for user equipment battery-life aware load balancing in LTE network

The demand for higher data rate and lower cost is making the use of Long Term Evolution (LTE network) more popular in recent years. In this paper, we deal with an adaptive cost-based handover decision algorithm for user equipment battery-life aware load balancing in LTE. The algorithm has a simple c...

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Main Authors: Nathaniel, Salawu, Syed Ariffin, Sharifah Hafizah, Khan, Adnan Shahid
Format: Article
Published: Praise Worthy Prize 2016
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Online Access:http://eprints.utm.my/id/eprint/71316/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019286717&doi=10.15866%2firecos.v11i11.10671&partnerID=40&md5=d4803b59ca6902f4abaad8f24780087a
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spelling my.utm.713162017-11-16T09:37:03Z http://eprints.utm.my/id/eprint/71316/ Adaptive cost-based handover decision algorithm for user equipment battery-life aware load balancing in LTE network Nathaniel, Salawu Syed Ariffin, Sharifah Hafizah Khan, Adnan Shahid TK Electrical engineering. Electronics Nuclear engineering The demand for higher data rate and lower cost is making the use of Long Term Evolution (LTE network) more popular in recent years. In this paper, we deal with an adaptive cost-based handover decision algorithm for user equipment battery-life aware load balancing in LTE. The algorithm has a simple cost function decision engine to reduce computational complexity and network overhead while load balancing and optimizing the battery life of the user’s equipment. The cost function comprises of load and power related parameters which are cell load, uplink transmission power as well as Reference signal received power (RSRP). A weight factor (bounded between zero and one) for each cost function parameter has an initial (constant) or adaptive (dynamic) value depending on the user equipment battery’s state of charge. Whenever the algorithm is run, a cell with dominant cost value is chosen to serve as the new target cell so as to avoid load imbalance of the network. The parameters for performance testing are handover and new call blocking rate, the number of handovers and load distribution index. The proposed algorithm is compared with two related works. Results obtained show that the proposed algorithm has better performance over the other two schemes compared. In particular, over 90% is achieved in terms of load distribution index which is higher than that of the two other schemes compared. Praise Worthy Prize 2016 Article PeerReviewed Nathaniel, Salawu and Syed Ariffin, Sharifah Hafizah and Khan, Adnan Shahid (2016) Adaptive cost-based handover decision algorithm for user equipment battery-life aware load balancing in LTE network. International Review on Computers and Software, 11 (11). pp. 979-988. ISSN 1828-6003 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019286717&doi=10.15866%2firecos.v11i11.10671&partnerID=40&md5=d4803b59ca6902f4abaad8f24780087a
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Nathaniel, Salawu
Syed Ariffin, Sharifah Hafizah
Khan, Adnan Shahid
Adaptive cost-based handover decision algorithm for user equipment battery-life aware load balancing in LTE network
description The demand for higher data rate and lower cost is making the use of Long Term Evolution (LTE network) more popular in recent years. In this paper, we deal with an adaptive cost-based handover decision algorithm for user equipment battery-life aware load balancing in LTE. The algorithm has a simple cost function decision engine to reduce computational complexity and network overhead while load balancing and optimizing the battery life of the user’s equipment. The cost function comprises of load and power related parameters which are cell load, uplink transmission power as well as Reference signal received power (RSRP). A weight factor (bounded between zero and one) for each cost function parameter has an initial (constant) or adaptive (dynamic) value depending on the user equipment battery’s state of charge. Whenever the algorithm is run, a cell with dominant cost value is chosen to serve as the new target cell so as to avoid load imbalance of the network. The parameters for performance testing are handover and new call blocking rate, the number of handovers and load distribution index. The proposed algorithm is compared with two related works. Results obtained show that the proposed algorithm has better performance over the other two schemes compared. In particular, over 90% is achieved in terms of load distribution index which is higher than that of the two other schemes compared.
format Article
author Nathaniel, Salawu
Syed Ariffin, Sharifah Hafizah
Khan, Adnan Shahid
author_facet Nathaniel, Salawu
Syed Ariffin, Sharifah Hafizah
Khan, Adnan Shahid
author_sort Nathaniel, Salawu
title Adaptive cost-based handover decision algorithm for user equipment battery-life aware load balancing in LTE network
title_short Adaptive cost-based handover decision algorithm for user equipment battery-life aware load balancing in LTE network
title_full Adaptive cost-based handover decision algorithm for user equipment battery-life aware load balancing in LTE network
title_fullStr Adaptive cost-based handover decision algorithm for user equipment battery-life aware load balancing in LTE network
title_full_unstemmed Adaptive cost-based handover decision algorithm for user equipment battery-life aware load balancing in LTE network
title_sort adaptive cost-based handover decision algorithm for user equipment battery-life aware load balancing in lte network
publisher Praise Worthy Prize
publishDate 2016
url http://eprints.utm.my/id/eprint/71316/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019286717&doi=10.15866%2firecos.v11i11.10671&partnerID=40&md5=d4803b59ca6902f4abaad8f24780087a
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score 13.160551