Frequency Plan Optimization Based on Genetic Algorithms for Cellular Networks

Cellular networks are constantly evolving to ensure a better Quality of Service (QoS) and quality of coverage ever more important. The radio cellular systems are based on frequency allocation. In this context, frequency allocation principle consists in choosing an optimal frequency plan to meet traf...

Full description

Bibliographic Details
Main Author: Hicham Megnafi
Format: Article
Language:English
Published: Croatian Communications and Information Society (CCIS) 2020-09-01
Series:Journal of Communications Software and Systems
Subjects:
Online Access:https://jcomss.fesb.unist.hr/index.php/jcomss/article/view/1012
id doaj-254c1fdb52f9416684bf15613bef429d
record_format Article
spelling doaj-254c1fdb52f9416684bf15613bef429d2020-11-25T03:41:48ZengCroatian Communications and Information Society (CCIS)Journal of Communications Software and Systems1845-64211846-60792020-09-01163217223Frequency Plan Optimization Based on Genetic Algorithms for Cellular NetworksHicham MegnafiCellular networks are constantly evolving to ensure a better Quality of Service (QoS) and quality of coverage ever more important. The radio cellular systems are based on frequency allocation. In this context, frequency allocation principle consists in choosing an optimal frequency plan to meet traffic demand constraints and communication quality while minimizing the radio interferences. This paper proposes an optimal frequency allocation approach based on genetic algorithms to minimize co-channel and adjacent channel interference. The validation of this new approach is confirmed by the results of the work we have done in the GSM network. In fact, we used the file obtained by the OMC-R, which defines the adjacent cells of each cell and the frequencies allocated to the considered area. The results obtained clearly show the effectiveness and robustness of the approach used.https://jcomss.fesb.unist.hr/index.php/jcomss/article/view/1012cellular networksradio optimizationfrequency allocationradio interferencegenetic algorithmsdrive test
collection DOAJ
language English
format Article
sources DOAJ
author Hicham Megnafi
spellingShingle Hicham Megnafi
Frequency Plan Optimization Based on Genetic Algorithms for Cellular Networks
Journal of Communications Software and Systems
cellular networks
radio optimization
frequency allocation
radio interference
genetic algorithms
drive test
author_facet Hicham Megnafi
author_sort Hicham Megnafi
title Frequency Plan Optimization Based on Genetic Algorithms for Cellular Networks
title_short Frequency Plan Optimization Based on Genetic Algorithms for Cellular Networks
title_full Frequency Plan Optimization Based on Genetic Algorithms for Cellular Networks
title_fullStr Frequency Plan Optimization Based on Genetic Algorithms for Cellular Networks
title_full_unstemmed Frequency Plan Optimization Based on Genetic Algorithms for Cellular Networks
title_sort frequency plan optimization based on genetic algorithms for cellular networks
publisher Croatian Communications and Information Society (CCIS)
series Journal of Communications Software and Systems
issn 1845-6421
1846-6079
publishDate 2020-09-01
description Cellular networks are constantly evolving to ensure a better Quality of Service (QoS) and quality of coverage ever more important. The radio cellular systems are based on frequency allocation. In this context, frequency allocation principle consists in choosing an optimal frequency plan to meet traffic demand constraints and communication quality while minimizing the radio interferences. This paper proposes an optimal frequency allocation approach based on genetic algorithms to minimize co-channel and adjacent channel interference. The validation of this new approach is confirmed by the results of the work we have done in the GSM network. In fact, we used the file obtained by the OMC-R, which defines the adjacent cells of each cell and the frequencies allocated to the considered area. The results obtained clearly show the effectiveness and robustness of the approach used.
topic cellular networks
radio optimization
frequency allocation
radio interference
genetic algorithms
drive test
url https://jcomss.fesb.unist.hr/index.php/jcomss/article/view/1012
work_keys_str_mv AT hichammegnafi frequencyplanoptimizationbasedongeneticalgorithmsforcellularnetworks
_version_ 1724528165693423616