Towards 6G wireless communication networks: Vision, enabling technologies, and new paradigm shifts
The fifth generation (5G) wireless communication networks are being deployed worldwide
from 2020 and more capabilities are in the process of being standardized, such as mass …
from 2020 and more capabilities are in the process of being standardized, such as mass …
A tutorial on ultrareliable and low-latency communications in 6G: Integrating domain knowledge into deep learning
As one of the key communication scenarios in the fifth-generation and also the sixth-
generation (6G) mobile communication networks, ultrareliable and low-latency …
generation (6G) mobile communication networks, ultrareliable and low-latency …
Edge artificial intelligence for 6G: Vision, enabling technologies, and applications
KB Letaief, Y Shi, J Lu, J Lu - IEEE Journal on Selected Areas …, 2021 - ieeexplore.ieee.org
The thriving of artificial intelligence (AI) applications is driving the further evolution of
wireless networks. It has been envisioned that 6G will be transformative and will …
wireless networks. It has been envisioned that 6G will be transformative and will …
Semantic communication systems for speech transmission
Semantic communications could improve the transmission efficiency significantly by
exploring the semantic information. In this paper, we make an effort to recover the …
exploring the semantic information. In this paper, we make an effort to recover the …
Multi-agent reinforcement learning based resource management in MEC-and UAV-assisted vehicular networks
In this paper, we investigate multi-dimensional resource management for unmanned aerial
vehicles (UAVs) assisted vehicular networks. To efficiently provide on-demand resource …
vehicles (UAVs) assisted vehicular networks. To efficiently provide on-demand resource …
Model-based deep learning
Signal processing, communications, and control have traditionally relied on classical
statistical modeling techniques. Such model-based methods utilize mathematical …
statistical modeling techniques. Such model-based methods utilize mathematical …
Joint secure offloading and resource allocation for vehicular edge computing network: A multi-agent deep reinforcement learning approach
The mobile edge computing (MEC) technology can simultaneously provide high-speed
computing services for multiple vehicular users (VUs) in vehicular edge computing (VEC) …
computing services for multiple vehicular users (VUs) in vehicular edge computing (VEC) …
Graph neural networks for scalable radio resource management: Architecture design and theoretical analysis
Deep learning has recently emerged as a disruptive technology to solve challenging radio
resource management problems in wireless networks. However, the neural network …
resource management problems in wireless networks. However, the neural network …
An efficient specific emitter identification method based on complex-valued neural networks and network compression
Specific emitter identification (SEI) is a promising technology to discriminate the individual
emitter and enhance the security of various wireless communication systems. SEI is …
emitter and enhance the security of various wireless communication systems. SEI is …
Survey on artificial intelligence (AI) techniques for vehicular ad-hoc networks (VANETs)
A Mchergui, T Moulahi, S Zeadally - Vehicular Communications, 2022 - Elsevier
Advances in communications, smart transportation systems, and computer systems have
recently opened up vast possibilities of intelligent solutions for traffic safety, convenience …
recently opened up vast possibilities of intelligent solutions for traffic safety, convenience …