Differential Evolution in Wireless Communications: A Review

<p class="0abstract">Differential Evolution (DE) is an evolutionary computational method inspired by the biological processes of evolution and mutation. DE has been applied in numerous scientific fields. The paper presents a literature review of DE and its application in wireless com...

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Main Authors: Hilary I Okagbue, Muminu O Adamu, Timothy A Anake
Format: Article
Language:English
Published: International Association of Online Engineering (IAOE) 2019-07-01
Series:International Journal of Online and Biomedical Engineering
Subjects:
Online Access:https://online-journals.org/index.php/i-joe/article/view/10651
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spelling doaj-83a8518b62b24f5887eb969f81b6ef542021-09-02T08:30:34ZengInternational Association of Online Engineering (IAOE)International Journal of Online and Biomedical Engineering2626-84932019-07-011511295210.3991/ijoe.v15i11.106514593Differential Evolution in Wireless Communications: A ReviewHilary I OkagbueMuminu O AdamuTimothy A Anake<p class="0abstract">Differential Evolution (DE) is an evolutionary computational method inspired by the biological processes of evolution and mutation. DE has been applied in numerous scientific fields. The paper presents a literature review of DE and its application in wireless communication. The detailed history, characteristics, strengths, variants and weaknesses of DE were presented. Seven broad areas were identified as different domains of application of DE in wireless communications. It was observed that coverage area maximisation and energy consumption minimisation are the two major areas where DE is applied. Others areas are quality of service, updating mechanism where candidate positions learn from a large diversified search region, security and related field applications. Problems in wireless communications are often modelled as multiobjective optimisation which can easily be tackled by the use of DE or hybrid of DE with other algorithms. Different research areas can be explored and DE will continue to be utilized in this context.</p>https://online-journals.org/index.php/i-joe/article/view/10651Differential evolutionmultiobjective optimizationevolutionary computationenergy utilizationlocalizationcoveragewireless networks.
collection DOAJ
language English
format Article
sources DOAJ
author Hilary I Okagbue
Muminu O Adamu
Timothy A Anake
spellingShingle Hilary I Okagbue
Muminu O Adamu
Timothy A Anake
Differential Evolution in Wireless Communications: A Review
International Journal of Online and Biomedical Engineering
Differential evolution
multiobjective optimization
evolutionary computation
energy utilization
localization
coverage
wireless networks.
author_facet Hilary I Okagbue
Muminu O Adamu
Timothy A Anake
author_sort Hilary I Okagbue
title Differential Evolution in Wireless Communications: A Review
title_short Differential Evolution in Wireless Communications: A Review
title_full Differential Evolution in Wireless Communications: A Review
title_fullStr Differential Evolution in Wireless Communications: A Review
title_full_unstemmed Differential Evolution in Wireless Communications: A Review
title_sort differential evolution in wireless communications: a review
publisher International Association of Online Engineering (IAOE)
series International Journal of Online and Biomedical Engineering
issn 2626-8493
publishDate 2019-07-01
description <p class="0abstract">Differential Evolution (DE) is an evolutionary computational method inspired by the biological processes of evolution and mutation. DE has been applied in numerous scientific fields. The paper presents a literature review of DE and its application in wireless communication. The detailed history, characteristics, strengths, variants and weaknesses of DE were presented. Seven broad areas were identified as different domains of application of DE in wireless communications. It was observed that coverage area maximisation and energy consumption minimisation are the two major areas where DE is applied. Others areas are quality of service, updating mechanism where candidate positions learn from a large diversified search region, security and related field applications. Problems in wireless communications are often modelled as multiobjective optimisation which can easily be tackled by the use of DE or hybrid of DE with other algorithms. Different research areas can be explored and DE will continue to be utilized in this context.</p>
topic Differential evolution
multiobjective optimization
evolutionary computation
energy utilization
localization
coverage
wireless networks.
url https://online-journals.org/index.php/i-joe/article/view/10651
work_keys_str_mv AT hilaryiokagbue differentialevolutioninwirelesscommunicationsareview
AT muminuoadamu differentialevolutioninwirelesscommunicationsareview
AT timothyaanake differentialevolutioninwirelesscommunicationsareview
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