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Machine learning based handover management for improved QoE in LTE | IEEE Conference Publication | IEEE Xplore

Machine learning based handover management for improved QoE in LTE


Abstract:

This paper presents a machine learning based handover management scheme for LTE to improve the Quality of Experience (QoE) of the user in the presence of obstacles. We sh...Show More

Abstract:

This paper presents a machine learning based handover management scheme for LTE to improve the Quality of Experience (QoE) of the user in the presence of obstacles. We show that, in this scenario, a state-of-the-art handover algorithm is unable to select the appropriate target cell for handover, since it always selects the target cell with the strongest signal without taking into account the perceived QoE of the user after the handover. In contrast, our scheme learns from past experience how the QoE of the user is affected when the handover was done to a certain eNB. Our performance evaluation shows that the proposed scheme substantially improves the number of completed downloads and the average download time compared to state-of-the-art. Furthermore, its performance is close to an optimal approach in the coverage region affected by an obstacle.
Date of Conference: 25-29 April 2016
Date Added to IEEE Xplore: 04 July 2016
Electronic ISBN:978-1-5090-0223-8
Electronic ISSN: 2374-9709
Conference Location: Istanbul, Turkey

References

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