Generative-adversarial-network-based wireless channel modeling: Challenges and opportunities
In modern wireless communication systems, wireless channel modeling has always been a
fundamental task in system design and performance optimization. Traditional channel …
fundamental task in system design and performance optimization. Traditional channel …
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 …
ChannelGAN: Deep learning-based channel modeling and generating
H Xiao, W Tian, W Liu, J Shen - IEEE Wireless …, 2022 - ieeexplore.ieee.org
The increasing complexity on channel modeling and the cost on collecting plenty of high-
quality wireless channel data have become the main bottlenecks of developing deep …
quality wireless channel data have become the main bottlenecks of developing deep …
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 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 …
Wideband channel estimation with a generative adversarial network
E Balevi, JG Andrews - IEEE Transactions on Wireless …, 2021 - ieeexplore.ieee.org
Communication at high carrier frequencies such as millimeter wave (mmWave) and
terahertz (THz) requires channel estimation for very large bandwidths at low SNR. Hence …
terahertz (THz) requires channel estimation for very large bandwidths at low SNR. Hence …
Artificial intelligence enabled radio propagation for communications—Part II: Scenario identification and channel modeling
This two-part paper investigates the application of artificial intelligence (AI) and, in particular,
machine learning (ML) to the study of wireless propagation channels. In Part I of this article …
machine learning (ML) to the study of wireless propagation channels. In Part I of this article …
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 …
Artificial intelligence enabled radio propagation for communications—Part I: Channel characterization and antenna-channel optimization
To provide higher data rates, as well as better coverage, cost efficiency, security,
adaptability, and scalability, the 5G and beyond 5G networks are developed with various …
adaptability, and scalability, the 5G and beyond 5G networks are developed with various …
Generative AI for physical layer communications: A survey
The recent evolution of generative artificial intelligence (GAI) leads to the emergence of
groundbreaking applications such as ChatGPT, which not only enhances the efficiency of …
groundbreaking applications such as ChatGPT, which not only enhances the efficiency of …