Deep learning-driven wireless communication for edge-cloud computing: opportunities and challenges

H Wu, X Li, Y Deng - Journal of Cloud Computing, 2020 - Springer
Future wireless communications are becoming increasingly complex with different radio
access technologies, transmission backhauls, and network slices, and they play an …

Deep learning for wireless communications: An emerging interdisciplinary paradigm

L Dai, R Jiao, F Adachi, HV Poor… - IEEE Wireless …, 2020 - ieeexplore.ieee.org
Wireless communications are envisioned to bring about dramatic changes in the future, with
a variety of emerging applications, such as virtual reality, Internet of Things, and so on …

Deep learning for wireless physical layer: Opportunities and challenges

T Wang, CK Wen, H Wang, F Gao… - China …, 2017 - ieeexplore.ieee.org
Machine learning (ML) has been widely applied to the upper layers of wireless
communication systems for various purposes, such as deployment of cognitive radio and …

Wireless network intelligence at the edge

J Park, S Samarakoon, M Bennis… - Proceedings of the …, 2019 - ieeexplore.ieee.org
Fueled by the availability of more data and computing power, recent breakthroughs in cloud-
based machine learning (ML) have transformed every aspect of our lives from face …

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 …

Toward an intelligent edge: Wireless communication meets machine learning

G Zhu, D Liu, Y Du, C You, J Zhang… - IEEE communications …, 2020 - ieeexplore.ieee.org
The recent revival of AI is revolutionizing almost every branch of science and technology.
Given the ubiquitous smart mobile gadgets and IoT devices, it is expected that a majority of …

Deep learning for intelligent wireless networks: A comprehensive survey

Q Mao, F Hu, Q Hao - IEEE Communications Surveys & …, 2018 - ieeexplore.ieee.org
As a promising machine learning tool to handle the accurate pattern recognition from
complex raw data, deep learning (DL) is becoming a powerful method to add intelligence to …

[HTML][HTML] Toward intelligent wireless communications: Deep learning-based physical layer technologies

S Liu, T Wang, S Wang - Digital Communications and Networks, 2021 - Elsevier
Advanced technologies are required in future mobile wireless networks to support services
with highly diverse requirements in terms of high data rate and reliability, low latency, and …

Mobile edge computing

B Liang, VWS Wong, R Schober… - Key technologies for …, 2017 - books.google.com
The ongoing development of the fifth generation (5G) wireless technologies is taking place
in a unique landscape of recent advancement in information processing, marked by the …

Edge computing in IoT: A 6G perspective

M Ishtiaq, N Saeed, MA Khan - arXiv preprint arXiv:2111.08943, 2021 - arxiv.org
Edge computing is one of the key driving forces to enable Beyond 5G (B5G) and 6G
networks. Due to the unprecedented increase in traffic volumes and computation demands …