DDPG-E2E: A Novel Policy Gradient Approach for End-to-End Communication Systems
The End-to-end (E2E) learning-based approach has great potential to reshape the existing
communication systems by replacing the transceivers with deep neural networks. To this …
communication systems by replacing the transceivers with deep neural networks. To this …
Autoencoder based robust transceivers for fading channels using deep neural networks
SR Mattu, TL Narasimhan… - 2020 IEEE 91st …, 2020 - ieeexplore.ieee.org
In this paper, we design transceivers for fading channels using autoencoders and deep
neural networks (DNN). Specifically, we consider the problem of finding (n, k) block codes …
neural networks (DNN). Specifically, we consider the problem of finding (n, k) block codes …
Signal restoration and prediction for end-to-end learning of practical wireless communication system
Z Chen - 2022 IEEE 19th International Conference on Mobile …, 2022 - ieeexplore.ieee.org
Autoencoders (AEs) have been proposed to learn the physical layer of wireless
communication systems in an end-to-end fashion. However, it is challenging to jointly train …
communication systems in an end-to-end fashion. However, it is challenging to jointly train …
AI-Native Communications
The emergence of artificial intelligence (AI)-based methods evolving from 5G to 6G is
accelerating. Therefore, to optimize the communication system in the 6G era, it is essential to …
accelerating. Therefore, to optimize the communication system in the 6G era, it is essential to …
End-to-end learning for fiber-optic communication systems
In this chapter, we review the application of end-to-end learning in optical communication
systems. First, we briefly discuss the motivation and idea behind end-to-end learning using …
systems. First, we briefly discuss the motivation and idea behind end-to-end learning using …
Deep Reinforcement Learning For Secure Communication
Y Yang, M Shikh-Bahaei - 2022 IEEE 96th Vehicular …, 2022 - ieeexplore.ieee.org
In physical layer security, one interest of the community is the development of practical
approaches to achieve reliable and secure communication, such as model-free approaches …
approaches to achieve reliable and secure communication, such as model-free approaches …
Neural Network-Based Fixed-Complexity Precoder Selection for Multiple Antenna Systems
J Kim, HS Lim - IEEE Access, 2022 - ieeexplore.ieee.org
In this paper, we propose a neural network-based precoder selection method for multiple
antenna systems that are equipped with maximum likelihood detectors. We train a fully …
antenna systems that are equipped with maximum likelihood detectors. We train a fully …
Early results on deep unfolded conjugate gradient‐based large‐scale MIMO detection
M Ahmed Ouameur, D Massicotte - IET communications, 2021 - Wiley Online Library
Deep learning (DL) is attracting considerable attention in the design of communication
systems. This paper derives a deep unfolded conjugate gradient (CG) architecture for large …
systems. This paper derives a deep unfolded conjugate gradient (CG) architecture for large …
Symbol-based over-the-air digital predistortion using reinforcement learning
We propose an over-the-air digital predistortion optimization algorithm using reinforcement
learning. Based on a symbol-based criterion, the algorithm minimizes the errors between …
learning. Based on a symbol-based criterion, the algorithm minimizes the errors between …
Signal detection for full-duplex cognitive underwater acoustic communications with SIC using model-driven deep learning network
This paper aims to handle the model-driven deep learning network based signal detection
for full-duplex cognitive underwater acoustic communications (FDCUACs) with self …
for full-duplex cognitive underwater acoustic communications (FDCUACs) with self …