Hybrid AI Framework for Real-Time Signal Denoising and Error Correction in 5G/6G Wireless Communication Systems

Purushotham Endla, Rajkumar Mandal, R. Purushothaman, Nimmagadda Padmaja, Tandra Nagarjuna, Syed Zahidur Rashid

2025

Abstract

In 5G and future 6G networks, it is important to guarantee strong and reliable signal transmission in the presence of noise, interference, and data degradation. A new trainable hybrid AI framework with deep learning, denoising diffusion models, and attention-based autoencoders is suggested to conduct the real-time noise removal and error correction in the dynamic wireless channels. Unlike its predecessors, which are either simulation-oriented, hardware-based, or application-specific, our technique is validated on the real-time communication testbeds and learns multi-level AI layers to combat the physical corruption, semantic discrepancy, and packet-level mistakes. Combining positional accuracy and adaptive signal enhancement, this design does not only decrease the bit error rate (BER) and signal-to-noise ratio (SNR) which, but it also makes the wireless communication reliable for various channel scenarios. Experimental results show significant improvements over existing models, indicating that the proposed method is highly promising for URLLC in future networks.

Paper Citation

in Harvard Style

Endla P., Mandal R., Purushothaman R., Padmaja N., Nagarjuna T. and Rashid S. (2025). Hybrid AI Framework for Real-Time Signal Denoising and Error Correction in 5G/6G Wireless Communication Systems. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 1: ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 500-507. DOI: 10.5220/0013868200004919

in Bibtex Style

@conference{icrdicct`2525,
author={Purushotham Endla and Rajkumar Mandal and R. Purushothaman and Nimmagadda Padmaja and Tandra Nagarjuna and Syed Rashid},
title={Hybrid AI Framework for Real-Time Signal Denoising and Error Correction in 5G/6G Wireless Communication Systems},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 1: ICRDICCT`25},
year={2025},
pages={500-507},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013868200004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 1: ICRDICCT`25
TI - Hybrid AI Framework for Real-Time Signal Denoising and Error Correction in 5G/6G Wireless Communication Systems
SN - 978-989-758-777-1
AU - Endla P.
AU - Mandal R.
AU - Purushothaman R.
AU - Padmaja N.
AU - Nagarjuna T.
AU - Rashid S.
PY - 2025
SP - 500
EP - 507
DO - 10.5220/0013868200004919
PB - SciTePress