Joint channel and Doppler frequency shift estimation in OFDM systems under impulse noise.
Saved in:
| Title: | Joint channel and Doppler frequency shift estimation in OFDM systems under impulse noise. |
|---|---|
| Authors: | Hong, Shunli1,2 (AUTHOR) hsl@zjvtit.edu.cn, Li, Youming1 (AUTHOR) liyouming@nbu.edu.cn, Li, Liang2 (AUTHOR) Liangli@zjvtit.edu.cn, Wu, Yonghong3 (AUTHOR) wuyh7426@126.com |
| Source: | EURASIP Journal on Wireless Communications & Networking. 2/14/2026, Vol. 2026 Issue 1, p1-24. 24p. |
| Subjects: | Orthogonal frequency division multiplexing, Channel estimation, Noise, Signal processing, Doppler effect, Mean square algorithms |
| Abstract: | In this paper, a blind channel and Doppler frequency shift (DFS) estimation method based on cyclostationarity is proposed for orthogonal frequency division multiplexing (OFDM) transmission under impulse noise environment. The proposed method begins with a compressing transform (CT) applied to the received signal to mitigate the adverse effects of impulse noise on estimation performance. Through analysis, it is found that the energy distributions of the cyclic correlation functions of the OFDM signal and Gaussian white noise (AWGN) before and after CT remain unchanged. Furthermore, it is shown that the energy of the cyclic correlation function of the impulse noise after CT only exists at zero cyclic frequency and delay variables. Based on these properties, we simplify the cyclic spectral functions and construct Toeplitz matrices by carefully selecting cycle frequency and delay variables. This selection is guided by the distinct energy distributions of the cyclic correlation functions corresponding to the OFDM signal, impulse noise, and AWGN, respectively. Thus, a matrix equation based on cyclic spectral functions is further constructed. Based on these analyses, DFS and channel estimation values are derived by solving this equation. The simulation results show that the proposed method has lower mean square errors (MSE). [ABSTRACT FROM AUTHOR] |
| Copyright of EURASIP Journal on Wireless Communications & Networking is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
| Abstract: | In this paper, a blind channel and Doppler frequency shift (DFS) estimation method based on cyclostationarity is proposed for orthogonal frequency division multiplexing (OFDM) transmission under impulse noise environment. The proposed method begins with a compressing transform (CT) applied to the received signal to mitigate the adverse effects of impulse noise on estimation performance. Through analysis, it is found that the energy distributions of the cyclic correlation functions of the OFDM signal and Gaussian white noise (AWGN) before and after CT remain unchanged. Furthermore, it is shown that the energy of the cyclic correlation function of the impulse noise after CT only exists at zero cyclic frequency and delay variables. Based on these properties, we simplify the cyclic spectral functions and construct Toeplitz matrices by carefully selecting cycle frequency and delay variables. This selection is guided by the distinct energy distributions of the cyclic correlation functions corresponding to the OFDM signal, impulse noise, and AWGN, respectively. Thus, a matrix equation based on cyclic spectral functions is further constructed. Based on these analyses, DFS and channel estimation values are derived by solving this equation. The simulation results show that the proposed method has lower mean square errors (MSE). [ABSTRACT FROM AUTHOR] |
|---|---|
| ISSN: | 16871472 |
| DOI: | 10.1186/s13638-026-02585-x |
