@inproceedings{b4430ff7bb06470eb739a232c3815a86,
title = "Deep Learning Enhanced Channel Estimation for the Internet of Vehicles OFDM Systems",
abstract = "The deep learning enhanced channel estimation is presented for the OFDM communication in the Internet of Vehicles (10V). Using the image enhancement and denoising, the channel responses at unknown positions are predicted under a specified Signal-to-Noise Ratio (SNR). Simulation experiments were conducted in predefined urban road scenes.Experimental results show that this method shows significant improvement compared to traditional methods in the minimum mean square error (MMSE) of channel estimation, with an average decrease of 0.03 in a series of experiments with different SNRs.",
keywords = "Deep Learning, IoV, OFDM",
author = "Zheng Liu and Xiaomin Pan",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 2024 IEEE International Conference on Computational Electromagnetics, ICCEM 2024 ; Conference date: 15-04-2024 Through 17-04-2024",
year = "2024",
doi = "10.1109/ICCEM60619.2024.10558915",
language = "English",
series = "2024 IEEE International Conference on Computational Electromagnetics, ICCEM 2024 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2024 IEEE International Conference on Computational Electromagnetics, ICCEM 2024 - Proceedings",
address = "United States",
}