Deep reinforcement learning for intelligent internet of vehicles: An energy-efficient computational offloading scheme
The emerging vehicular services call for updated communication and computing platforms.
Fog computing, whose infrastructure is deployed in close proximity to terminals, extends the …
Fog computing, whose infrastructure is deployed in close proximity to terminals, extends the …
On the integration of enabling wireless technologies and sensor fusion for next-generation connected and autonomous vehicles
The automotive industry is transitioning towards intelligent, connected, and autonomous
vehicles to avoid traffic congestion, conflicts, and collisions with increased driver safety …
vehicles to avoid traffic congestion, conflicts, and collisions with increased driver safety …
Deep learning-inspired message passing algorithm for efficient resource allocation in cognitive radio networks
M Liu, T Song, J Hu, J Yang… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Energy efficiency (EE) and spectrum efficiency (SE) have received significant attentions on
optimizing the network performance in cognitive radio networks. In this paper, an EE+ SE …
optimizing the network performance in cognitive radio networks. In this paper, an EE+ SE …
Machine learning meets communication networks: Current trends and future challenges
The growing network density and unprecedented increase in network traffic, caused by the
massively expanding number of connected devices and online services, require intelligent …
massively expanding number of connected devices and online services, require intelligent …
A deep-learning-based radio resource assignment technique for 5G ultra dense networks
Recently, deep learning has emerged as a state-of-the-art machine learning technique with
promising potential to drive significant breakthroughs in a wide range of research areas. The …
promising potential to drive significant breakthroughs in a wide range of research areas. The …
DRL-R: Deep reinforcement learning approach for intelligent routing in software-defined data-center networks
Data-center networks (DCN) possess multiple new features: coexistence of elephant
flow/mice flow/coflow, and coexistence of multiple network resources (bandwidth, cache and …
flow/mice flow/coflow, and coexistence of multiple network resources (bandwidth, cache and …
HCP: Heterogeneous computing platform for federated learning based collaborative content caching towards 6G networks
ZM Fadlullah, N Kato - IEEE Transactions on Emerging Topics …, 2020 - ieeexplore.ieee.org
A heterogeneous computing architecture is essential to facilitate intelligent network traffic
control for a joint computation, communication, and collaborative caching optimization in 6G …
control for a joint computation, communication, and collaborative caching optimization in 6G …
Deep learning-based cooperative automatic modulation classification method for MIMO systems
Automatic modulation classification (AMC) is one of the most essential algorithms to identify
the modulation types for the non-cooperative communication systems. Recently, it has been …
the modulation types for the non-cooperative communication systems. Recently, it has been …
Fine-grained vehicle classification with channel max pooling modified CNNs
Convolutional neural networks (CNNs) have recently shown excellent performance on the
task of fine-grained vehicle classification, where the motivation is to identify the fine-grained …
task of fine-grained vehicle classification, where the motivation is to identify the fine-grained …
Internet of intelligence: A survey on the enabling technologies, applications, and challenges
The Internet of Intelligence is conceived as an emerging networking paradigm, which will
make intelligence as easy to obtain as information. This paper provides an overview of the …
make intelligence as easy to obtain as information. This paper provides an overview of the …