Please use this identifier to cite or link to this item: https://repository.rsif-paset.org/xmlui/handle/123456789/361
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dc.contributor.authorBalogoun, Marianne Alfredine Omonlola-
dc.contributor.authorHoundji, Vinasétan Ratheil-
dc.contributor.authorDossou, Michel-
dc.contributor.authorHonfoga, Anne-Carole-
dc.date.accessioned2024-02-22T13:44:56Z-
dc.date.available2024-02-22T13:44:56Z-
dc.date.issued2023-09-15-
dc.identifier.urihttps://repository.rsif-paset.org/xmlui/handle/123456789/361-
dc.descriptionConference proceeding full text: https://doi.org/10.1007/978-981-99-3236-8_27en_US
dc.description.abstractThe problem of predicting radio coverage is a fundamental step in the wireless networks design process and is nowadays very helpful in reducing drive tests for monitoring. Among the continuous flow of research in this area, a scientific contributions map becomes relevant to guide future researches correctly. This paper provides a bibliometric analysis and future research avenues to predict radio coverage. A structural insight is obtained on conceptual clarification, collaborations, top sources, authors, affiliations, most cited documents, and most cited countries. A total of 3134 documents have been analyzed: 49% are journal papers and 51% are proceedings papers. 60% of them are published during the last seven years. The majority of recent relevant works on the topic are focused on wireless communication systems, specifically 5G. The USA, China, and India are leading the way in research in this field. IEEE access, IEEE transactions on antennas, and propagation are the leading journals.en_US
dc.publisherSpringer Linken_US
dc.subjectWireless networks\, Radio coverage prediction, Bibliometric studyen_US
dc.titleRadio Coverage Prediction in Wireless Networks: A Bibliometric Studyen_US
dc.typePresentationen_US
Appears in Collections:ICTs including Big Data and Artificial Intelligence

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