W Kim, Y Ahn, J Kim, B Shim - Journal of Communications and …, 2023 - ieeexplore.ieee.org
Deep learning (DL), a branch of artificial intelligence (AI) techniques, has shown great promise in various disciplines such as image classification and segmentation, speech …
Q Bai, J Wang, Y Zhang, J Song - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
The research about deep learning application for physical layer has been received much attention in recent years. In this paper, we propose a Deep Learning (DL) based channel …
In this paper, online deep learning (DL)-based channel estimation algorithm for doubly selective fading channels is proposed by employing the deep neural network (DNN). With …
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 …
H Ye, GY Li, BH Juang - IEEE Wireless Communications …, 2017 - ieeexplore.ieee.org
This letter presents our initial results in deep learning for channel estimation and signal detection in orthogonal frequency-division multiplexing (OFDM) systems. In this letter, we …
Y Liao, Y Hua, X Dai, H Yao… - ICC 2019-2019 IEEE …, 2019 - ieeexplore.ieee.org
Aiming at the problem that the downlink channel estimation performance is limited due to the fast time-varying and non-stationary characteristics in the high-speed mobile scenarios, we …
In this letter we apply deep learning tools to conduct channel estimation for an orthogonal frequency division multiplexing (OFDM) system based on downlink pilots. To be specific, a …
IEEE 802.11 p standard is specially developed to define vehicular communications requirements and support cooperative intelligent transport systems. In such environment …
Deep learning has demonstrated the important roles in improving the system performance and reducing computational complexity for 5G-and-beyond networks. In this paper, we …