Application of Computational Intelligence Algorithms in Radio Propagation: A Systematic Review and Metadata Analysis

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dc.contributor.authorQuadri, Ramon
dc.contributor.authorNasir, Faruk
dc.contributor.authorKayode, Adewole
dc.contributor.authorAbubakar, Abdulkarim
dc.contributor.authorLukman, Olawoyin
dc.contributor.authorAbdulkarim, Oloyede
dc.contributor.authorHaruna, Chiroma
dc.contributor.authorAliyu, Usman
dc.contributor.authorCarlos, Calafate
dc.date.accessioned2023-06-07T09:18:32Z
dc.date.available2023-06-07T09:18:32Z
dc.date.issued2021-01-21
dc.description.abstractThe importance of wireless path loss prediction and interference minimization studies in various environments cannot be over- emphasized. In fact, numerous researchers have done massive work on scrutinizing the effectiveness of existing path loss models for channel modeling. The difficulties experienced by the researchers determining or having the detailed information about the propagating environment prompted for the use of computational intelligence (CI) methods in the prediction of path loss. This paper presents a comprehensive and systematic literature review on the application of nature-inspired computational approaches in radio propagation analysis. In particular, we cover artificial neural networks (ANNs), fuzzy inference systems (FISs), swarm intelligence (SI), and other computational techniques. The main research trends and a general overview of the different research areas, open research issues, and future research directions are also presented in this paper. This review paper will serve as reference material for researchers in the field of channel modeling or radio propagation and in particular for research in path loss prediction.en_US
dc.identifier.urihttps://uilspace.unilorin.edu.ng/handle/20.500.12484/11005
dc.language.isoenen_US
dc.publisherMobile Information Systemsen_US
dc.subjectFuzzy Logic, Artificial Neural Network, Swam Interferenceen_US
dc.titleApplication of Computational Intelligence Algorithms in Radio Propagation: A Systematic Review and Metadata Analysisen_US
dc.typeArticleen_US

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