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 …
Meta-ViterbiNet: Online meta-learned Viterbi equalization for non-stationary channels
Deep neural networks (DNNs) based digital receivers can potentially operate in complex
environments. How-ever, the dynamic nature of communication channels implies that in …
environments. How-ever, the dynamic nature of communication channels implies that in …
Knowledge distillation-aided end-to-end learning for linear precoding in multiuser MIMO downlink systems with finite-rate feedback
K Kong, WJ Song, M Min - IEEE Transactions on Vehicular …, 2021 - ieeexplore.ieee.org
We propose a deep learning-based channel estimation, quantization, feedback, and
precoding method for downlink multiuser multiple-input and multiple-output systems. In the …
precoding method for downlink multiuser multiple-input and multiple-output systems. In the …
Deep learning-driven MIMO: Data encoding and processing mechanism
Z Song, J Ma - Physical Communication, 2023 - Elsevier
Abstract Large-scale Multiple-Input Multiple Output (MIMO) is the key technology of 5G
communication. However, dealing with physical channels is a complex process. Machine …
communication. However, dealing with physical channels is a complex process. Machine …
Massive data generation for deep learning-aided wireless systems using meta learning and generative adversarial network
As an entirely-new paradigm to design the communication systems, deep learning (DL), an
approach that the machine learns the desired wireless function, has received much attention …
approach that the machine learns the desired wireless function, has received much attention …
MIMO channel estimation using score-based generative models
Channel estimation is a critical task in multiple-input multiple-output (MIMO) digital
communications that substantially affects end-to-end system performance. In this work, we …
communications that substantially affects end-to-end system performance. In this work, we …
Deep learning for wireless communications: An emerging interdisciplinary paradigm
Wireless communications are envisioned to bring about dramatic changes in the future, with
a variety of emerging applications, such as virtual reality, Internet of Things, and so on …
a variety of emerging applications, such as virtual reality, Internet of Things, and so on …
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 …
Massive MIMO channel prediction via meta-learning and deep denoising: Is a small dataset enough?
Accurate channel knowledge is critical in massive multiple-input multiple-output (MIMO),
which motivates the use of channel prediction. Machine learning techniques for channel …
which motivates the use of channel prediction. Machine learning techniques for channel …
Deep learning for fading channel prediction
W Jiang, HD Schotten - IEEE Open Journal of the …, 2020 - ieeexplore.ieee.org
Channel state information (CSI), which enables wireless systems to adapt their transmission
parameters to instantaneous channel conditions and consequently achieve great …
parameters to instantaneous channel conditions and consequently achieve great …