Intelligent Channel Estimation and Sensing in Next-Generation Wireless Networks
Date of Award
8-1-2024
Degree Name
Ph.D. in Electrical and Computer Engineering
Department
Department of Electrical and Computer Engineering
Advisor/Chair
Bradley Ratliff
Abstract
Internet of things (IoT), an all pervasive technology, is expected to reach 41 billions by 2027. Such a revolutionary technology is utilized in plethora of applications such as health, and agriculture. IoT offers numerous advantages in terms of computing, and intelligence. Such a growth of IoT devices lead to the proliferation of wireless technologies to cater to the growing demands of users. Such proliferation of wireless technologies pose multiple challenges such as higher interference, limited spectrum resources, compatibility issues between different standards, and higher power consumption. The existing approaches as well as their limitations are surveyed in addition to including end-to-end deep learning based frameworks to alleviate the challenges described above. The proposed framework is validated, and evaluated on open-source and real-time data respectively.
Keywords
IoT, deep-learning, wireless technologies
Rights Statement
Copyright © 2024, author.
Recommended Citation
Kumar, Venkataramani, "Intelligent Channel Estimation and Sensing in Next-Generation Wireless Networks" (2024). Graduate Theses and Dissertations. 7415.
https://ecommons.udayton.edu/graduate_theses/7415
