Image of Cell Selection Mechanism Based on Q-learning Environment in Femtocell LTE-A Networks

Artikel Jurnal

Cell Selection Mechanism Based on Q-learning Environment in Femtocell LTE-A Networks




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.


Ketersediaan

JICTRA4a-004JICTRA V15N1 June 2021Perpustakaan FT UPI YAITersedia
JICTRA4b-004JICTRA V15N1 June 2021Perpustakaan FT UPI YAITersedia
JICTRA4c-004JICTRA V15N1 June 2021Perpustakaan FT UPI YAITersedia

Informasi Detil

Judul Seri
Journal of ICT Research and Application
No. Panggil
JICTRA V15N1 June 2021
Penerbit ITB Journal Publisher : Bandung.,
Deskripsi Fisik
hlm : 56-70
Bahasa
English
ISBN/ISSN
2337-5787
Klasifikasi
JICTRA
Tipe Isi
-
Tipe Media
-
Tipe Pembawa
-
Edisi
Volume 15 Nomor 1 June 2021
Subyek
Info Detil Spesifik
-
Pernyataan Tanggungjawab

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