Semantic communications for future internet: Fundamentals, applications, and challenges

W Yang, H Du, ZQ Liew, WYB Lim… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
With the increasing demand for intelligent services, the sixth-generation (6G) wireless
networks will shift from a traditional architecture that focuses solely on a high transmission …

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 source-channel coding for sentence semantic transmission with HARQ

P Jiang, CK Wen, S Jin, GY Li - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Recently, semantic communication has been brought to the forefront because deep learning
(DL)-based methods, such as Transformer, have achieved great success in semantic …

Big data analytics deep learning techniques and applications: A survey

HA Selmy, HK Mohamed, W Medhat - Information Systems, 2023 - Elsevier
Deep learning (DL), as one of the most active machine learning research fields, has
achieved great success in numerous scientific and technological disciplines, including …

End-to-end learning for OFDM: From neural receivers to pilotless communication

FA Aoudia, J Hoydis - IEEE Transactions on Wireless …, 2021 - ieeexplore.ieee.org
The benefits of end-to-end learning has been demonstrated over AWGN channels but has
not yet been quantified over realistic wireless channel models. This work aims to fill this gap …

Online meta-learning for hybrid model-based deep receivers

T Raviv, S Park, O Simeone, YC Eldar… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Recent years have witnessed growing interest in the application of deep neural networks
(DNNs) for receiver design, which can potentially be applied in complex environments …

Distributed intelligence in wireless networks

X Liu, J Yu, Y Liu, Y Gao, T Mahmoodi… - IEEE Open Journal …, 2023 - ieeexplore.ieee.org
The cloud-based solutions are becoming inefficient due to considerably large time delays,
high power consumption, and security and privacy concerns caused by billions of connected …

AI Empowered Wireless Communications: From Bits to Semantics

Z Qin, L Liang, Z Wang, S Jin, X Tao… - Proceedings of the …, 2024 - ieeexplore.ieee.org
Artificial intelligence (AI) and machine learning (ML) have shown tremendous potential in
reshaping the landscape of wireless communications and are, therefore, widely expected to …

Learn to adapt to new environments from past experience and few pilot blocks

O Wang, J Gao, GY Li - IEEE Transactions on Cognitive …, 2022 - ieeexplore.ieee.org
In recent years, deep learning has been widely applied in communications and achieved
remarkable performance improvement. Most of the existing works are based on data-driven …

Deep learning in physical layer communications: Evolution and prospects in 5G and 6G networks

C Mao, Z Mu, Q Liang, I Schizas, C Pan - IET Communications, 2023 - Wiley Online Library
With the rapid development of the communication industry in the fifth generation and the
advance towards the intelligent society of the sixth generation wireless networks, traditional …