Analysis Of User Throughput Based Predictive Mobility Load Balancing Using Logarithmic Regression Of Reference Signal Received Quality In Long Term Evolution Radio Access Network

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Published Feb 1, 2018
DOI https://doi.org/10.20895/infotel.v10i1.350

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Achmad Rizal Danisya
Institut Teknologi Telkom Purwokerto
Rendy Munadi
Universitas Telkom
Sofia Naning Hertiana
Universitas Telkom

Abstract

The improvement of Long Term Evolution (LTE) radio access network services is affecting the increased value of traffic load in its network, which is causing traffic unbalance between cells in LTE Radio Access Network (RAN). Users will be served with ineffective resource block allocation which will make the total of gained throughput are not optimal. A method is required to move network load from overloaded cells to underloaded cells in order to balance the resource block allocation optimally. By using NS-3.26 simulation, User Throughput Based (UTB) predictive Mobility Load Balancing (MLB) method is tested with RandomWalkMobilityModel for each user. This method produces an improvement of 2,29 % in average of total throughput of 63,33 % successful optimization.

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How to Cite
[1]
A. R. Danisya, R. Munadi, and S. N. Hertiana, “Analysis Of User Throughput Based Predictive Mobility Load Balancing Using Logarithmic Regression Of Reference Signal Received Quality In Long Term Evolution Radio Access Network”, INFOTEL, vol. 10, no. 1, pp. 1-6, Feb. 2018.
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Vol 10 No 1 (2018): February 2018
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Articles
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