WGAN-based Autoencoder Training Over-the-air
The practical realization of end-to-end training of communication systems is fundamentally
limited by its accessibility of the channel gradient. To overcome this major burden, the idea …
limited by its accessibility of the channel gradient. To overcome this major burden, the idea …
Channel agnostic end-to-end learning based communication systems with conditional GAN
In this article, we use deep neural networks (DNNs) to develop an end-to-end wireless
communication system, in which DNNs are employed for all signal-related functionalities …
communication system, in which DNNs are employed for all signal-related functionalities …
A communication channel density estimating generative adversarial network
A Smith, J Downey - 2019 IEEE Cognitive Communications for …, 2019 - ieeexplore.ieee.org
Autoencoder-based communication systems use neural network channel models to
backwardly propagate message reconstruction error gradients across an approximation of …
backwardly propagate message reconstruction error gradients across an approximation of …
Channel-Agnostic Training of Transmitter and Receiver for Wireless Communications
Wireless communications systems are traditionally designed by independently optimising
signal processing functions based on a mathematical model. Deep learning-enabled …
signal processing functions based on a mathematical model. Deep learning-enabled …
Deep learning-based end-to-end wireless communication systems with conditional GANs as unknown channels
In this article, we develop an end-to-end wireless communication system using deep neural
networks (DNNs), where DNNs are employed to perform several key functions, including …
networks (DNNs), where DNNs are employed to perform several key functions, including …
Channel estimation enhancement with generative adversarial networks
Improving the accuracy of channel estimation is a significant topic in the context of wireless
communications. For training-based channel estimations, increasing the length of a training …
communications. For training-based channel estimations, increasing the length of a training …
Approximating the void: Learning stochastic channel models from observation with variational generative adversarial networks
Channel modeling is a critical topic when considering accurately designing or evaluating the
performance of a communications system. Most prior work in designing or learning new …
performance of a communications system. Most prior work in designing or learning new …
End-to-end learning of communication system without known channel
H Jiang, L Dai - ICC 2021-IEEE International Conference on …, 2021 - ieeexplore.ieee.org
Leveraging powerful deep learning techniques, the end-to-end (E2E) learning of
communication system is able to outperform the classical communication system …
communication system is able to outperform the classical communication system …
Deep reinforcement learning autoencoder with noisy feedback
End-to-end learning of communication systems enables joint optimization of transmitter and
receiver, implemented as deep neural network (NN)-based autoencoders, over any type of …
receiver, implemented as deep neural network (NN)-based autoencoders, over any type of …
Learning end-to-end channel coding with diffusion models
It is a known problem that deep-learning-based end-to-end (E2E) channel coding systems
depend on a known and differentiable channel model, due to the learning process and …
depend on a known and differentiable channel model, due to the learning process and …