International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 3 May-June 2024 Submit your research before last 3 days of June to publish your research paper in the issue of May-June.

5G Channel Estimation using Deep Learning

Author(s) Deepanjali S, Bhoomika A J, Chandana T Y, K Ashrith Reddy
Country India
Abstract The abstract focuses on the integration of 5G channel estimation and the vulnerability of deep learning models, specifically in the context of OFDM signals, while employing a student-teacher model architecture. Channel estimation is a crucial aspect of 5G communication systems, ensuring reliable data transmission in dynamic wireless environments. Simultaneously, the advent of deep learning introduces susceptibility to adversarial attacks, where malicious inputs can deceive the model's predictions. This paper explores the intricate relationship between 5G channel estimation and deep learning vulnerabilities, emphasising the application of a student-teacher model to enhance system robustness. By delving into the nuances of OFDM signals, the study aims to provide a comprehensive understanding of how these elements intertwine, offering insights into potential security enhancements for next-generation wireless communication systems.
Keywords 5G channel estimation,deep learning,OFMD,adversarial attacks,malicious inputs.
Field Engineering
Published In Volume 6, Issue 3, May-June 2024
Published On 2024-05-09
Cite This 5G Channel Estimation using Deep Learning - Deepanjali S, Bhoomika A J, Chandana T Y, K Ashrith Reddy - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.11040
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