Journal of ICT Research and Applications ITB Bandung Vol. 15 No. 1 2021
Cell Selection Mechanism Based on Q-learning Environment in Femtocell LTE-A Networks
Dublin Core
Title
Journal of ICT Research and Applications ITB Bandung Vol. 15 No. 1 2021
Cell Selection Mechanism Based on Q-learning Environment in Femtocell LTE-A Networks
Cell Selection Mechanism Based on Q-learning Environment in Femtocell LTE-A Networks
Subject
cell selection; femtocell; handover learning; LTE-A; Q-learning.
Description
Abstract. Universal mobile networks require enhanced capability and appropriate quality of service (QoS) and experience (QoE). To achieve this, Long Term Evolution (LTE) system operators have intensively deployed femtocells (HeNBs) along with macrocells (eNBs) to offer user equipment (UE) with optimal capacity coverage and best quality of service. To achieve the requirement of QoS in the handover stage among macrocells and femtocells we need a seamless cell selection mechanism. Cell selection requirements are considered a difficult task in femtocell-based networks and effective cell selection procedures are essential to reduce the ping-pong phenomenon and to minimize needless handovers. In this
study, we propose a seamless cell selection scheme for macrocell-femtocell LTE systems, based on the Q-learning environment. A novel cell selection mechanism is proposed for high-density femtocell network topologies to evaluate the target base station in the handover stage. We used the LTE-Sim simulator to implement
and evaluate the cell selection procedures. The simulation results were encouraging: a decrease in the control signaling rate and packet loss ratio were observed and at the same time the system throughput was increased.
study, we propose a seamless cell selection scheme for macrocell-femtocell LTE systems, based on the Q-learning environment. A novel cell selection mechanism is proposed for high-density femtocell network topologies to evaluate the target base station in the handover stage. We used the LTE-Sim simulator to implement
and evaluate the cell selection procedures. The simulation results were encouraging: a decrease in the control signaling rate and packet loss ratio were observed and at the same time the system throughput was increased.
Creator
Ammar Bathich, Saiful Izwan Suliman, Hj. Mohd Asri Hj. Mansor, Sinan Ghassan Abid Ali & Raed Abdulla
Source
DOI: 10.5614/itbj.ict.res.appl.2021.15.1.4
Publisher
IRCS-ITB
Date
07 Mei 2021
Contributor
Sri Wahyuni
Rights
ISSN: 2337-5787
Format
PDF
Language
English
Type
Text
Coverage
Journal of ICT Research and Applications ITB Bandung Vol. 15 No. 1 2021
Files
Collection
Citation
Ammar Bathich, Saiful Izwan Suliman, Hj. Mohd Asri Hj. Mansor, Sinan Ghassan Abid Ali & Raed Abdulla, “Journal of ICT Research and Applications ITB Bandung Vol. 15 No. 1 2021
Cell Selection Mechanism Based on Q-learning Environment in Femtocell LTE-A Networks,” Repository Horizon University Indonesia, accessed April 3, 2025, https://repository.horizon.ac.id/items/show/3410.
Cell Selection Mechanism Based on Q-learning Environment in Femtocell LTE-A Networks,” Repository Horizon University Indonesia, accessed April 3, 2025, https://repository.horizon.ac.id/items/show/3410.