Deep learning-aided 6G wireless networks: A comprehensive survey of revolutionary PHY architectures

B Ozpoyraz, AT Dogukan, Y Gevez… - IEEE Open Journal …, 2022 - ieeexplore.ieee.org
Deep learning (DL) has proven its unprecedented success in diverse fields such as
computer vision, natural language processing, and speech recognition by its strong …

Deep channel prediction: A DNN framework for receiver design in time-varying fading channels

SR Mattu, LN Theagarajan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In time-varying fading channels, channel coefficients are estimated using pilot symbols that
are transmitted every coherence interval. For channels with high Doppler spread, the rapid …

An improved deep learning-based end-to-end autoencoder for UAV-to-ground free space optical communication

Q Zhang, G Chen, B Liu, X Zhi, S Zhan, J Zhang… - Optics …, 2023 - Elsevier
In this paper, an improved deep learning-based end-to-end autoencoder is proposed for
unmanned aerial vehicle (UAV) to ground free space optical communication to mitigate …

A model‐driven robust deep learning wireless transceiver

S Duan, J Xiang, X Yu - IET Communications, 2021 - Wiley Online Library
Recently, deep learning (DL) has been successfully applied in computer vision and natural
language processing. The communication physical layer based on deep learning has …

Deep Learning Neural Receiver for Organic Communication Channels

A Roopnarine, S Rocke - 2023 IEEE Latin-American …, 2023 - ieeexplore.ieee.org
Organic communication channels (OCCs) are any hydrocarbon-based media used to
communicate data. OCCs have gained attention as an alternative to short-range RF …

Error correcting codes using neural networks

A Fuentes Contreras - 2021 - oa.upm.es
Durante las últimas décadas, se han producido grandes mejoras en el proceso de
entrenamiento de redes de neuronas; atrayendo más atención y financiación a los …

[PDF][PDF] Neural Network Equalizer and Decoder for Linear Block Codes in ISI Channels

Z Joleini, A Jamshidi - researchgate.net
This paper delves into the design and evaluation of neural decoders, efficient neural
network-based algorithms for decoding linear block codes like the Hamming code. The …