Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Adnane El Hanjri
Hassan 1st University Settat
Computer Science & IT Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Features detection based blind handover using kullback leibler distance for 5G HetNets systems Adnane El Hanjri; Aawatif Hayar; Abdelkrim Haqiq
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 9, No 2: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1144.795 KB) | DOI: 10.11591/ijai.v9.i2.pp193-202

Abstract

The Fifth Generation of Mobile Networks (5G) is changing the cellular network infrastructure paradigm, and Small Cells are a key piece of this shift. But the high number of Small Cells and their low coverage involve more Handovers to provide continuous connectivity, and the selection, quickly and at low energy cost, of the appropriate one in the vicinity of thousands is also a key problem. In this paper, we propose a new method, to have an efficient, blind and rapid handover just by analysing Received Signal probability density function instead of demodulating and analysing Received Signal itself as in classical handover. The proposed method exploits KL Distance, Akaike Information Criterion (AIC) and Akaike weights, in order to decide blindly the best handover and the best Base Station (BS) for each user
Co-Authors Aawatif Hayar Abdelkrim Haqiq