A scheme of combining DFO and channel estimation scheme for mobile OFDM systems

Abstract To reduce the impact of residual Doppler frequency offset (RDFO), a joint DFO estimation and CE scheme is proposed for the OFDM systems under the high‐speed mobile environment. In the paper, the expression of interference power caused by the RDFO is first derived, and the effect of RDFO on time‐varying characteristic of channel is analysed. Then, a joint DFO and channel estimation scheme is presented. Specifically, a high‐precision DFO estimator based on the convolutional neural network with anti‐noise is firstly designed. Due to its ability to use fewer samples to adapt well to the new environments, the meta learning is adopted to estimate the time‐varying channel. Moreover, to improve the practicality of the algorithm, the non‐ideal values rather than ideal values are used as the training targets in the two neural networks. Additionally, the proposed method is only based on the received signal and does not require any pilots or training sequences, which has higher transmission efficiency compared to the existing algorithms. The research results indicate that the proposed method has good estimation performance and good practicality, and it is suitable for high‐speed mobile scenarios.

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Publication Details

Journal
IET Communications
Published
2024-10-14
DOI
https://doi.org/10.1049/cmu2.12851
Primary Topic
Advanced Wireless Communication Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

A scheme of combining DFO and channel estimation scheme for mobile OFDM systems

Ao Chang, Bo Hu, Yongqi Shao, Lihua Yang
IET Communications
Advanced Wireless Communication Techniques
article

A scheme of combining DFO and channel estimation scheme for mobile OFDM systems

Ao Chang, Bo Hu, Yongqi Shao, Lihua Yang
article en

Abstract

Abstract To reduce the impact of residual Doppler frequency offset (RDFO), a joint DFO estimation and CE scheme is proposed for the OFDM systems under the high‐speed mobile environment. In the paper, the expression of interference power caused by the RDFO is first derived, and the effect of RDFO on time‐varying characteristic of channel is analysed. Then, a joint DFO and channel estimation scheme is presented. Specifically, a high‐precision DFO estimator based on the convolutional neural network with anti‐noise is firstly designed. Due to its ability to use fewer samples to adapt well to the new environments, the meta learning is adopted to estimate the time‐varying channel. Moreover, to improve the practicality of the algorithm, the non‐ideal values rather than ideal values are used as the training targets in the two neural networks. Additionally, the proposed method is only based on the received signal and does not require any pilots or training sequences, which has higher transmission efficiency compared to the existing algorithms. The research results indicate that the proposed method has good estimation performance and good practicality, and it is suitable for high‐speed mobile scenarios.

IET CommunicationsVol. 18(19)
Nanjing University of Posts and Telecommunications (CN)
National Science Foundation, National Natural Science Foundation of China, Government of Jiangsu Province
Openalex Percentile: Top 84%
Advanced Wireless Communication Techniques
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