Progressive iterative channel estimation in 
fast time-varying OFDM systems

doi:10.1016/S1005-8885(14)60309-5

Acta Metallurgica Sinica(English letters) ›› 2014, Vol. 21 ›› Issue (4): 8-14.doi: 10.1016/S1005-8885(14)60309-5

Progressive iterative channel estimation in fast time-varying OFDM systems

杨睿哲¹,叶斯洋¹,²,张延华²,²,孙艳华¹,²,Richard Yu²,³

1. College of Electronics Information and Control Engineering, Beijing University of Technology, Beijing 100124, China 2. Department of Systems and Computer Engineering, Carleton University, Ottawa, ON Canada

收稿日期:2013-12-10 修回日期:2014-05-09 出版日期:2014-08-31 发布日期:2014-08-30
通讯作者: 杨睿哲 E-mail:xiangshe124@139.com
基金资助:
基于多模型的信道混合估计理论及方法;格约减理论在MIMO系统中的应用;绿色无线通信网络的基础理论和方法研究

Progressive iterative channel estimation in fast time-varying OFDM systems

1. College of Electronics Information and Control Engineering, Beijing University of Technology, Beijing 100124, China 2. Department of Systems and Computer Engineering, Carleton University, Ottawa, ON Canada

Received:2013-12-10 Revised:2014-05-09 Online:2014-08-31 Published:2014-08-30
Contact: Rui-Zhe Yang E-mail:xiangshe124@139.com

摘要/Abstract

摘要： Considering the joint channel estimation and data detection in time-varying orthogonal frequency division multiplexing (OFDM) and addressing transmission performance degradation induced by the severe inter-carrier interference (ICI) at very high speed, a new progressive iterative channel estimation scheme is proposed. To alleviate the error propagation of the inaccurate data due to ICI, the measurement subcarriers in the Kalman filter is designed to be extended from pilots subcarriers to all the subcarriers progressively through the iterations. Furthermore, in iteration process, the interference of the non-pilot data to the measurement subcarriers is considered to be part of noise in the modified Kalman filter, which improves the estimation accuracy. Simulation indicates that the proposed scheme improves the performance in fast time-varying situation.

关键词: time-varying OFDM, channel estimation, ICI, progressive, Kalman

Abstract: Considering the joint channel estimation and data detection in time-varying orthogonal frequency division multiplexing (OFDM) and addressing transmission performance degradation induced by the severe inter-carrier interference (ICI) at very high speed, a new progressive iterative channel estimation scheme is proposed. To alleviate the error propagation of the inaccurate data due to ICI, the measurement subcarriers in the Kalman filter is designed to be extended from pilots subcarriers to all the subcarriers progressively through the iterations. Furthermore, in iteration process, the interference of the non-pilot data to the measurement subcarriers is considered to be part of noise in the modified Kalman filter, which improves the estimation accuracy. Simulation indicates that the proposed scheme improves the performance in fast time-varying situation.

Key words: time-varying OFDM, channel estimation, ICI, progressive, Kalman

参考文献

1. Cimini L J. Analysis and simulation of a digital mobile channel using orthogonal frequency division multiplexing. IEEE Transactions on Communications, 1985, 33(7): 665-675

2. Tang Z, Cannizzaro R C, Leus G, et al. Pilot-assisted time varying channel estimation for OFDM systems. IEEE Transactions on Signal Processing, 2007, 55(5): 2226-2238

3. Tomasin S, Gorokhov A, Yang H, et al. Iterative interference cancellation and channel estimation for mobile OFDM. IEEE Transactions on Wireless Communications, 2005, 4(1): 238-245

4. Zhang Q, Wu M, Guo Q,et al. Optimized generalized complex exponential basis expansion in the OFDM system. Journal of Xidian University, 2012,39(3): 131-135 (in Chinese)

5. Guo Q, Wu M, Zhang Q, et al. Channel estimation for OFDM systems over time-varying and sparse dispersive channels. Proceedings of the 75th Vehicular Technology Conference (VTC-Spring’12), May 6-9, 2012, Yokohama, Japan. Piscataway, NJ, USA: IEEE, 2012:5p

6. Kim H, Tugnait J K. Turbo equalization for doubly-selective fading channels using nonlinear kalman filtering and basis expansion models. IEEE Transactions on Wireless Communications, 2010, 9(6): 2076-2087

7. Movahedian A, McGuire M. Estimation of fast fading channels for turbo receivers with high order modulation. IEEE Transactions on Vehicular Technology,2013,62(2): 667-678

8. Zhao M, Shi Z, Reed M C. Iterative turbo channel estimation for OFDM systems over rapid dispersive fading channel. IEEE Transactions on Communications, 2008, 7(7): 1-11

9. Hijazi H, Ros L. Polynomial estimation of time-varying multi-path gains with intercarrier interference mitigation in OFDM systems. IEEE Transactions on Vehicular Technology, 2009, 58(1): 140-151

10. Hijazi H, Ros L. Joint data QR-detection and Kalman estimation for OFDM time-varying Rayleigh channel complex gains. IEEE Transactions on Communications, 2010, 58(1): 170-178

11. Molisch A F, Toeltsch M, Vermani S. Iterative methods for cancellation of intercarrier interference in OFDM systems. IEEE Transactions on Vehicular Technology, 2007, 56(4): 2158-2167

12. Li F, Xu Z, Zhu S. Variational-inference-based data detection for OFDM systems with imperfect channel estimation. IEEE Transactions on Vehicular Technology, 2013, 62(3): 1394-1399

13. Wang H W, Lin D W,Sang T H. OFDM signal detection in doubly selective channels with blockwise whitening of residual intercarrier interference and noise. IEEE Journal on Selected Areas in Communications, 2012, 30(4): 684-694

14. GSM 05.05 vers 4.6.0. European digital cellular telecommunication system (Phase 2); Radio transmission and reception. Sophia Antipolis, France: European Telecommunications Standards Institute,1994

15. 15 Hijazi H, Ros L. Analytical analysis of Bayesian Cramer-Rao bound for dynamical Rayleigh channel complex gains estimation in OFDM system. IEEE Transactions on Signal Processing, 2009, 57(5): 1889-1900

Progressive iterative channel estimation in fast time-varying OFDM systems

Progressive iterative channel estimation in fast time-varying OFDM systems

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 0

编辑推荐

Metrics

本文评价