The Enhanced User History-Based Prediction In 5G

SAFA E., ABDALLA and SHARIFAH, H. SYED ARIFFIN (2016) The Enhanced User History-Based Prediction In 5G. In: Fourth International Conference on Advances in Computing, Communication and Information Technology CCIT- 2016, 17 - 18 March, 2016, Birmingham City University, Birmingham, UNITED KINGDOM.

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Abstract

Achieving seamless, mobile access is a major challenge in the next generation networks due to the huge traffic growth for mobile multimedia applications such as VoIP where the end-to-end delay is considerably big. By predicting where the users are moving, the resource allocation can perform prior to the actual handover, thus can reduce delays in resource allocation and finally can reduce the handover latency. This paper is aims to achieve an accurate user history-based by adding Temporal Prediction scheme for similar routes to eliminate the scanning overhead and unnecessary handoffs incurred in next generation networks. This is achieved by considering multiple characteristics of mobile users, and captures short-term and periodic behavior of mobile users to provide accurate next-cell predictions. The result shows 17% improvement in the accuracy compared to essential schemes.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: handover, Long Term Evolution, Femtocells,Mobility Prediction, scanning.
Depositing User: Mr. John Steve
Date Deposited: 25 Mar 2019 12:11
Last Modified: 25 Mar 2019 12:11
URI: http://publications.theired.org/id/eprint/895

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