Role of deep learning in wireless communications
Traditional communication system design has always been based on the paradigm of first
establishing a mathematical model of the communication channel, then designing and …
establishing a mathematical model of the communication channel, then designing and …
Toward an intelligent edge: Wireless communication meets machine learning
The recent revival of AI is revolutionizing almost every branch of science and technology.
Given the ubiquitous smart mobile gadgets and IoT devices, it is expected that a majority of …
Given the ubiquitous smart mobile gadgets and IoT devices, it is expected that a majority of …
[图书][B] Machine learning and wireless communications
How can machine learning help the design of future communication networks-and how can
future networks meet the demands of emerging machine learning applications? Discover the …
future networks meet the demands of emerging machine learning applications? Discover the …
Backpropagating through the air: Deep learning at physical layer without channel models
Recent developments in applying deep learning techniques to train end-to-end
communication systems have shown great promise in improving the overall performance of …
communication systems have shown great promise in improving the overall performance of …
Learn to communicate with neural calibration: Scalability and generalization
The conventional design of wireless communication systems typically relies on established
mathematical models that capture the characteristics of different communication modules …
mathematical models that capture the characteristics of different communication modules …
Learning to communicate with autoencoders: Rethinking wireless systems with deep learning
ME Morocho-Cayamcela, JN Njoku… - … in Information and …, 2020 - ieeexplore.ieee.org
The design and implementation of conventional communication systems are based on
strong probabilistic models and assumptions. These fixed and conventional communication …
strong probabilistic models and assumptions. These fixed and conventional communication …
Model-aided wireless artificial intelligence: Embedding expert knowledge in deep neural networks for wireless system optimization
Deep learning based on artificial neural networks (ANNs) is a powerful machine-learning
method that, in recent years, has been successfully used to realize tasks such as image …
method that, in recent years, has been successfully used to realize tasks such as image …
5G MIMO data for machine learning: Application to beam-selection using deep learning
The increasing complexity of configuring cellular networks suggests that machine learning
(ML) can effectively improve 5G technologies. Deep learning has proven successful in ML …
(ML) can effectively improve 5G technologies. Deep learning has proven successful in ML …
Two applications of deep learning in the physical layer of communication systems
E Björnson, P Giselsson - arXiv preprint arXiv:2001.03350, 2020 - arxiv.org
Deep learning has proved itself to be a powerful tool to develop data-driven signal
processing algorithms for challenging engineering problems. By learning the key features …
processing algorithms for challenging engineering problems. By learning the key features …
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 …