Quantum machine learning for 6G communication networks: State-of-the-art and vision for the future
The upcoming fifth generation (5G) of wireless networks is expected to lay a foundation of
intelligent networks with the provision of some isolated artificial intelligence (AI) operations …
intelligent networks with the provision of some isolated artificial intelligence (AI) operations …
Deep learning in mobile and wireless networking: A survey
The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …
services pose unprecedented demands on mobile and wireless networking infrastructure …
Deep joint source-channel coding for wireless image transmission
E Bourtsoulatze, DB Kurka… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
We propose a joint source and channel coding (JSCC) technique for wireless image
transmission that does not rely on explicit codes for either compression or error correction; …
transmission that does not rely on explicit codes for either compression or error correction; …
Grant-free non-orthogonal multiple access for IoT: A survey
MB Shahab, R Abbas… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
Massive machine-type communications (mMTC) is one of the main three focus areas in the
5th generation (5G) of wireless communications technologies to enable connectivity of a …
5th generation (5G) of wireless communications technologies to enable connectivity of a …
ColO-RAN: Developing machine learning-based xApps for open RAN closed-loop control on programmable experimental platforms
Cellular networks are undergoing a radical transformation toward disaggregated, fully
virtualized, and programmable architectures with increasingly heterogeneous devices and …
virtualized, and programmable architectures with increasingly heterogeneous devices and …
An introduction to deep learning for the physical layer
We present and discuss several novel applications of deep learning for the physical layer.
By interpreting a communications system as an autoencoder, we develop a fundamental …
By interpreting a communications system as an autoencoder, we develop a fundamental …
Deep learning based communication over the air
End-to-end learning of communications systems is a fascinating novel concept that has so
far only been validated by simulations for block-based transmissions. It allows learning of …
far only been validated by simulations for block-based transmissions. It allows learning of …
Neural network detection of data sequences in communication systems
N Farsad, A Goldsmith - IEEE Transactions on Signal …, 2018 - ieeexplore.ieee.org
We consider detection based on deep learning, and show it is possible to train detectors that
perform well without any knowledge of the underlying channel models. Moreover, when the …
perform well without any knowledge of the underlying channel models. Moreover, when the …
A deep learning framework for optimization of MISO downlink beamforming
Beamforming is an effective means to improve the quality of the received signals in multiuser
multiple-input-single-output (MISO) systems. Traditionally, finding the optimal beamforming …
multiple-input-single-output (MISO) systems. Traditionally, finding the optimal beamforming …
Machine learning in the air
Thanks to the recent advances in processing speed, data acquisition and storage, machine
learning (ML) is penetrating every facet of our lives, and transforming research in many …
learning (ML) is penetrating every facet of our lives, and transforming research in many …