@inproceedings{9af70dff59a74a6586fa624800640531,
title = "A DFT-based channel estimation algorithm with noise elimination for burst OFDM systems",
abstract = "Accurate channel estimation can greatly improve the performance of burst OFDM system by compensating channel fading. Channel estimation based on discrete Fourier transform (DFT) is suitable for burst OFDM systems due to its low complexity and short convergence time. Traditional DFT-based channel estimation algorithm does not consider the noise influence within the length of cyclic prefix, which greatly decreases its performance. A DFT-based channel estimation algorithm with noise elimination (DCEA/NE) is proposed to estimate the instantaneous signal-to-noise ratio (SNR) using the training sequence in the burst OFDM system, and based on this, eliminate the noise influence. Simulation results show that the proposed algorithm outperforms the traditional DFT-based channel estimation algorithm.",
keywords = "Burst OFDM, DFT-based channel estimation, Multipath channel, Noise elimination, SNR estimation",
author = "Yupeng Zhang and Kai Liu",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 6th International Conference on Information Science and Control Engineering, ICISCE 2019 ; Conference date: 20-12-2019 Through 22-12-2019",
year = "2019",
month = dec,
doi = "10.1109/ICISCE48695.2019.00015",
language = "英语",
series = "Proceedings - 2019 6th International Conference on Information Science and Control Engineering, ICISCE 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "28--31",
editor = "Shaozi Li and Yun Cheng and Ying Dai and Jianwei Ma",
booktitle = "Proceedings - 2019 6th International Conference on Information Science and Control Engineering, ICISCE 2019",
address = "美国",
}