Artificial intelligence for 5g wireless systems: Opportunities, challenges, and future research direction
The advent of the wireless communications systems augurs new cutting-edge technologies,
including self-driving vehicles, unmanned aerial systems, autonomous robots, the Internet-of …
including self-driving vehicles, unmanned aerial systems, autonomous robots, the Internet-of …
A deep reinforcement learning framework for spectrum management in dynamic spectrum access
Dynamic spectrum access (DSA) has the great potential to alleviate spectrum shortage and
promote network capacity. However, two fundamental technical issues have to be …
promote network capacity. However, two fundamental technical issues have to be …
Dynamic spectrum access for internet-of-things based on federated deep reinforcement learning
The explosive growth of Internet-of-Things (IoT) applications such as smart cities and
Industry 4.0 have led to drastic increase in demand for wireless bandwidth, hence motivating …
Industry 4.0 have led to drastic increase in demand for wireless bandwidth, hence motivating …
Evolution toward intelligent communications: Impact of deep learning applications on the future of 6G technology
The sixth generation (6G) represents the next evolution in wireless communication
technology and is currently under research and development. It is expected to deliver faster …
technology and is currently under research and development. It is expected to deliver faster …
Deep reinforcement learning paradigm for dense wireless networks in smart cities
Wireless local area networks (WLANs) are widely deployed for Internet-centric data
applications. Due to their extensive norm in our day-to-day wireless-enabled life, WLANs are …
applications. Due to their extensive norm in our day-to-day wireless-enabled life, WLANs are …
A deep-tree-model-based radio resource distribution for 5G networks
MS Hossain, G Muhammad - IEEE Wireless Communications, 2020 - ieeexplore.ieee.org
Deep learning is a branch of machine learning that learns the high-level abstraction of data
in a layered structure. Since its invention, it has been successfully applied in many image …
in a layered structure. Since its invention, it has been successfully applied in many image …
ORACLE: Optimized radio classification through convolutional neural networks
K Sankhe, M Belgiovine, F Zhou… - … -IEEE Conference on …, 2019 - ieeexplore.ieee.org
This paper describes the architecture and performance of ORACLE, an approach for
detecting a unique radio from a large pool of bit-similar devices (same hardware, protocol …
detecting a unique radio from a large pool of bit-similar devices (same hardware, protocol …
AI-enabled future wireless networks: Challenges, opportunities, and open issues
M Elsayed, M Erol-Kantarci - IEEE Vehicular Technology …, 2019 - ieeexplore.ieee.org
An expected plethora of demanding services and use cases mandates a revolutionary shift
in the way future wireless network resources are managed. Indeed, when application …
in the way future wireless network resources are managed. Indeed, when application …
DeepRx: Fully convolutional deep learning receiver
Deep learning has solved many problems that are out of reach of heuristic algorithms. It has
also been successfully applied in wireless communications, even though the current radio …
also been successfully applied in wireless communications, even though the current radio …
[PDF][PDF] Thirty years of machine learning: The road to pareto-optimal next-generation wireless networks
Next-generation wireless networks (NGWN) have a substantial potential in terms of
supporting a broad range of complex compelling applications both in military and civilian …
supporting a broad range of complex compelling applications both in military and civilian …