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Authors: Souhir Feki 1 ; Faouzi Zarai 1 and Aymen Belghith 2

Affiliations: 1 NTS'COM Research Unit and National School of Electronics and Telecommunications of Sfax, Tunisia ; 2 Saudi Electronic University (SEU), Saudi Arabia

ISBN: 978-989-758-261-5

ISSN: 2184-2825

Keyword(s): LTE-Advanced, scheduling algorithm, Q-learning, QoS, Fairness.

Related Ontology Subjects/Areas/Topics: Mobile Software and Services ; Radio Resource Management ; Telecommunications ; Wireless Information Networks and Systems

Abstract: Long Term Evolution Advanced (LTE-A) is a mobile communication standard used for transmitting data in cellular networks. It inherits all principal technologies of LTE such as flexible bandwidth, Orthogonal Frequency Division Multiplexing Access (OFDMA) and provides new functionalities to enhance the performance and capacity. For some time, LTE-A must co-exist with the 2G and 3G cellular networks, so resource management, potential interference, interworking necessities, etc. are an important issues. The Radio Resource Management (RRM) main function is to ensure the efficient use of available radio resources, making use of the available adaptation techniques, and to serve users depending on their Quality of Service (QoS) parameters. In this paper, we propose a novel dynamic Q-learning based Scheduling Algorithm (QLSA) for downlink transmission in LTE and LTE-A cellular network based on the Q-learning algorithm and adaptable to variations in channel conditions. The main objective of the proposed algorithm is to make a good trade-off between fairness and throughput and to provide Quality of Service (QoS) guarantee to Guaranteed Bit Rate (GBR) services. Performances of QLSA are compared with existing scheduling algorithms and simulation results show that the proposed QLSA provides the best trade-off fairness/throughput. (More)

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Paper citation in several formats:
Feki, S.; Zarai, F. and Belghith, A. (2017). A Q-learning-based Scheduler Technique for LTE and LTE-Advanced Network.In Proceedings of the 14th International Joint Conference on e-Business and Telecommunications - Volume 5: WINSYS, (ICETE 2017) ISBN 978-989-758-261-5, ISSN 2184-2825, pages 27-35. DOI: 10.5220/0006425200270035

@conference{winsys17,
author={Souhir Feki. and Faouzi Zarai. and Aymen Belghith.},
title={A Q-learning-based Scheduler Technique for LTE and LTE-Advanced Network},
booktitle={Proceedings of the 14th International Joint Conference on e-Business and Telecommunications - Volume 5: WINSYS, (ICETE 2017)},
year={2017},
pages={27-35},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006425200270035},
isbn={978-989-758-261-5},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on e-Business and Telecommunications - Volume 5: WINSYS, (ICETE 2017)
TI - A Q-learning-based Scheduler Technique for LTE and LTE-Advanced Network
SN - 978-989-758-261-5
AU - Feki, S.
AU - Zarai, F.
AU - Belghith, A.
PY - 2017
SP - 27
EP - 35
DO - 10.5220/0006425200270035

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