Mobility prediction in long term evolution (LTE) femtocell network

The Long Term Evolution (LTE) femtocell has promised to improve indoor coverage and enhance data rate capacity. Due to the special characteristic of the femtocell, it introduces several challenges in terms of mobility and interference management. This chapter focuses on mobility prediction in a wire...

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Main Authors: Amirrudin, N. A., Ariffin, S. H. S., Abd Malik, N. N. N., Ghazali, N. E.
Format: Book Section
Published: IGI Global 2014
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Online Access:http://eprints.utm.my/id/eprint/74708/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84960540310&doi=10.4018%2f978-1-4666-5170-8.ch005&partnerID=40&md5=3617ef5596d71b9b6530bbeafadc85b3
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spelling my.utm.747082017-11-26T05:51:32Z http://eprints.utm.my/id/eprint/74708/ Mobility prediction in long term evolution (LTE) femtocell network Amirrudin, N. A. Ariffin, S. H. S. Abd Malik, N. N. N. Ghazali, N. E. TK Electrical engineering. Electronics Nuclear engineering The Long Term Evolution (LTE) femtocell has promised to improve indoor coverage and enhance data rate capacity. Due to the special characteristic of the femtocell, it introduces several challenges in terms of mobility and interference management. This chapter focuses on mobility prediction in a wireless network in order to enhance handover performance. The mobility prediction technique via Markov Chains and a user's mobility history is proposed as a technique to predict user movement in the deployment of the LTE femtocell. Simulations have been developed to evaluate the relationship between prediction accuracy and the amount of non-random data, as well as the relationship between the prediction accuracy and the duration of the simulation. The result shows that the prediction is more accurate if the user moves in regular mode, which is directly proportional to the amount of non-random data. Moreover, the prediction accuracy is maintained at 0.7 when the number of weeks is larger than 50. IGI Global 2014 Book Section PeerReviewed Amirrudin, N. A. and Ariffin, S. H. S. and Abd Malik, N. N. N. and Ghazali, N. E. (2014) Mobility prediction in long term evolution (LTE) femtocell network. In: Handbook of Research on Progressive Trends in Wireless Communications and Networking. IGI Global, pp. 99-121. ISBN 978-146665171-5 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84960540310&doi=10.4018%2f978-1-4666-5170-8.ch005&partnerID=40&md5=3617ef5596d71b9b6530bbeafadc85b3
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
Amirrudin, N. A.
Ariffin, S. H. S.
Abd Malik, N. N. N.
Ghazali, N. E.
Mobility prediction in long term evolution (LTE) femtocell network
description The Long Term Evolution (LTE) femtocell has promised to improve indoor coverage and enhance data rate capacity. Due to the special characteristic of the femtocell, it introduces several challenges in terms of mobility and interference management. This chapter focuses on mobility prediction in a wireless network in order to enhance handover performance. The mobility prediction technique via Markov Chains and a user's mobility history is proposed as a technique to predict user movement in the deployment of the LTE femtocell. Simulations have been developed to evaluate the relationship between prediction accuracy and the amount of non-random data, as well as the relationship between the prediction accuracy and the duration of the simulation. The result shows that the prediction is more accurate if the user moves in regular mode, which is directly proportional to the amount of non-random data. Moreover, the prediction accuracy is maintained at 0.7 when the number of weeks is larger than 50.
format Book Section
author Amirrudin, N. A.
Ariffin, S. H. S.
Abd Malik, N. N. N.
Ghazali, N. E.
author_facet Amirrudin, N. A.
Ariffin, S. H. S.
Abd Malik, N. N. N.
Ghazali, N. E.
author_sort Amirrudin, N. A.
title Mobility prediction in long term evolution (LTE) femtocell network
title_short Mobility prediction in long term evolution (LTE) femtocell network
title_full Mobility prediction in long term evolution (LTE) femtocell network
title_fullStr Mobility prediction in long term evolution (LTE) femtocell network
title_full_unstemmed Mobility prediction in long term evolution (LTE) femtocell network
title_sort mobility prediction in long term evolution (lte) femtocell network
publisher IGI Global
publishDate 2014
url http://eprints.utm.my/id/eprint/74708/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84960540310&doi=10.4018%2f978-1-4666-5170-8.ch005&partnerID=40&md5=3617ef5596d71b9b6530bbeafadc85b3
_version_ 1643656916359970816
score 13.214268