Addressing the real world problem of managing wireless communication systems using explainable ai-based models through correlation analysis

• Autores: Panduro Ramirez, Jeidy Gisell, Surya, S., Gupta, Sumeet, Mehbodniya, Abolfazl, Rao Kapula, Prabhakara, Alam, Tanweer, Kaliyaperumal, Karthikeyan
• Formato: artículo
• Fecha de Publicación: 2022
• Institución: Universidad Tecnológica del Perú
• Repositorio: UTP-Institucional
• Lenguaje: español
• OAI Identifier: oai:repositorio.utp.edu.pe:20.500.12867/5809
• Enlace del recurso: https://hdl.handle.net/20.500.12867/5809; http://doi.org/10.1155/2022/3390075
• Nivel de acceso: acceso abierto
• Materia: Wireless communication; Artificial intelligence; https://purl.org/pe-repo/ocde/ford#2.02.00

In a general parlance, wireless communication tends to be investigated based on the available methods that support enhancing the optimized data link, especially the software-based methods. AI is mainly used to create and design efficient communication network systems and variable node locations. The major factors impacting wireless communications in the current context are enhanced channel frequency, efficiency of using the bandwidth, and modulation type. The software-defined ratio enables collecting the information and analyzing the overall signal-related components and processing them in real-time situations. This will support in detecting unnecessary information and identifying latency at each stage of communication. The study is intended to measure the influence of critical factors in enhancing the overall management of wireless communication systems through the application of AI technologies. The researchers used the questionnaire method in order to collect the data from the respondents and enable them to analyze the data using the SPSS data package.