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Location Prediction with Markov Model using Long Term Evolution Datasets
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 176 - Number 14 |
| Year of Publication: 2020 |
| Authors: S. S. Daodu, Akinola E. |
10.5120/ijca2020920054
|
S. S. Daodu, Akinola E. . Location Prediction with Markov Model using Long Term Evolution Datasets. International Journal of Computer Applications. 176, 14 ( Apr 2020), 12-16. DOI=10.5120/ijca2020920054
Abstract
Location prediction is fast becoming a wide field for research and has received great attention from diverse fields. Markov model are of various types but the memoryless property of the Markov model makes it easily applicable in location prediction. Network dataset chosen for the analysis and evaluation of the proposed system is a 4G LTE dataset with channel and context metrics. This dataset is an LTE network known as Beyond Throughput: a 4G LTE Dataset with Channel and Context Metrics dataset developed by Raca et al., (2018). It is a 4G trace dataset which is composed of client-side cellular key performance indicators (KPIs) with 135 traces. This paper focuses on using Markov model to efficiently and successfully predict a user location using the long term evolution network datasets.
References
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