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...
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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 |
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1724528165693423616 |