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    Intelligent determination of signals in beyond 5G wireless communication systems
    (Karabük Üniversitesi, Lisansüstü Eğitim Enstitüsü, 2025) Alao, Oluwaponmile David; Almohamad, Tarik Adnan
    Wireless communications systems have recorded significant developments since the beginning of the twenty-first century. With the recent development of the 5G wireless communication system, crucial challenges such as security issues, reliability, increased efficiency, cost-effectiveness, and a few more are tackled by researchers and designers of the wireless telecommunication industry in both academia and industry. With 5G and beyond representing the next generation of wireless systems for implementation globally, several challenges still have to be addressed due to the rapid growth and increased demand for high data rates, QoS, and mobility. To meet these challenges to the next-generation wireless communication system that range from QoS enhancement of the wireless schemes, reduction in implementation complexity, and the provision of accurate channel state estimation, a potential platform that provides viable solutions is the automatic determination techniques of signal parameters. These automatic recognition schemes, which include automatic modulation recognition (AMR) techniques and SNR estimation approaches, are able to provide increased reliability, improved spectrum utilization efficiency, and higher security to modern wireless communication systems. This study uses a feature-based approach to examine the intelligent determination of signals in next-generation wireless communication systems. A robust deep-learning signal classifier will be developed for this task.