Adaptive Channel Estimator Design for OFDM-Based Wireless Communication Systems

1. Adaptive Channel Estimator Design for OFDM-Based Wireless Communication Systems Reporter : Yen-Ming Huang Date : 2012 . 11 . 22

2. Outline • Motivation • Introduction • Interpolation Criterion in Frequency Domain • Interpolation Criterion in Time Domain • Adaptive Channel Estimator Design • Conclusions • Reference

3. Motivation • The goal is to develop an adaptive channel estimator in light of practical concerns according to wireless channel characteristics. Wireless Channel TX RX • Multipath Propagation Delay • Doppler Shift

4. Introduction

5. Outline • Motivation • Introduction • Interpolation Criterion in Frequency Domain • Linear Interpolation Criterion • DFT-Based Interpolation with Virtual Subcarriers • Time Domain Threshold Selection • Edge Effect Mitigation • Interpolation Criterion in Time Domain • Adaptive Channel Estimator Design • Conclusions • Reference

6. Linear Interpolation Criterion Based on the estimated CIR within CP length SNR High SNR Edge Effect Complexity Increasing

7. Linear Interpolation Criterion

8. DFT-Based Interpolation with Virtual Subcarriers In practical, the temperature and the bandwidth are known to receiver. Therefore, we may have the information of noise in advance. Noise Power λ

9. Time Domain Threshold Selection Method 1 The real and the imaginary part of noise follow Gaussian probability distribution. Method 2 Rayleigh probability derived from complex Gaussian variables is exploited. Although the larger value of threshold can achieve more complete noise reduction, the taps with slight channel energy will be removed possibly.

10. Edge Effect Mitigation Repetition[18] Linear Fashion[21]

11. Outline • Motivation • Introduction • Interpolation Criterion in Frequency Domain • Interpolation Criterion in Time Domain • Analysis of Time Varying Channel • Approaches to CFO Estimation • Linear Interpolation Criterion • Adaptive Channel Estimator Design • Conclusions • Reference

12. Analysis of Time Varying Channel

13. Approaches to CFO Estimation There are two main causes of distortion associated with the carrier frequency. One is the non-coherent up and down frequency conversion accompanied with an unavoidable difference due to physically inherent nature of the transceiver oscillators. The other is caused by Doppler shift due to the transceiver mobility. CP-Based Estimator [26]: Pilot-Based Estimator[27]: LOS-Based Estimator [28]:

14. Linear Interpolation Criterion Most of the maximum Doppler offset can be compensated with the proper schemes in the Rician fading channel. Broadly speaking, the LOS component usually emerges on the first arrival propagation path, and the Rician factor enlarges its weight diminishing the affection of scattered components.

15. Outline • Motivation • Introduction • Interpolation Criterion in Frequency Domain • Interpolation Criterion in Time Domain • Adaptive Channel Estimator Design • Moving Average • DFT-Based Transition • Strategies for Large Delay Spread Channel • Conclusions • Reference

16. Moving Average Owing to the performance of linear interpolation highly depends on pilots, noise reduction on them makes an improvement as expected. Although more MAWs mitigate the effect of noise evidently, it means the requirement of constant in several time-slots must to be satisfied.

17. Moving Average

18. DFT-Based Transition When the rise of velocity such that the technique of Moving Average is unsuitable to use especially at high SNR, DFT-based transition is an alternative way. By inherent time domain processing, the goal of noise reduction on pilots can be achieved.

19. DFT-Based Transition

20. Strategies for Large Delay Spread Channel In order to make the frequency domain interpolation more robust to such large delay spread scenario, the time domain interpolation may be performed prior to the frequency domain interpolation.

21. Channel Information Acquirement

22. Adaptive Channel Estimator Design

23. Outline • Motivation • Introduction • Interpolation Criterion in Frequency Domain • Interpolation Criterion in Time Domain • Adaptive Channel Estimator Design • Conclusions • Reference

24. Conclusions • In order to accomplish the intention desired, the first and the second term of Taylor expansion are used as a criterion of linearity. • Compared with many proposed methods of time domain processing based on the information of channel delay length, the proper threshold selection according to the known noise power is more rational. • In this study, inspired from the statistical characteristics of Gaussian noise, two schemes of threshold selection have been proposed. • By the reasonable assumptions of time-varying channel and the techniques of CFO compensation, the effect of Doppler shift due to mobility can be mitigated evidently in the Rician fading channel. Accordingly, the feasibility of time domain linear interpolation can be firmly confirmed.

25. Conclusions • To enlarge the usability of linear interpolation, two techniques of Moving Average and DFT-based transition for noise reduction on pilots have been proposed. • There are benefits to adaptability for a low power mobile terminal due to the restricted quantity of available processing power. • Given the practical positions taken for the study and the status of the field as completely introduced above, the goal to provide an adaptive channel estimator design based on channel understanding is achieved.

26. Reference [13] J. J. van de Beek, 0. Edfors, M. Sandell. S. K. Wilson and P. 0. Borjesson, “On channel estimation in OFDM systems,” Proc. IEEE Vehicular Technology Conf. vol. 2, Jul. 1995, pp. 815-819. [18] X. Hou, Z. Zhang, and H. Kayama, “Low-Complexity Enhanced DFT-based Channel Estimation for OFDM Systems with Virtual Subcarriers,” in Proc. IEEE PIMRC’07, Sep. 2007. [21] Szu-Lin Su, Yung-Chuan Lin, Chieh-Chih Hsu, and Gene C. H. Chuang, “A DFT-based Channel Estimation Scheme for IEEE 802.16e OFDMA Systems,”International Conference on Advanced Communication Technology, (ICACT10), IEEE Press, 2010, pp.775-779.  [26] J. van de Beek, M. Sandell, and P. Börjesson, “ML estimation of timing and frequency offset in OFDM systems,” IEEE Trans. Signal Processing, vol. 45, no. 7, pp. 1800–1805, Jul. 1997.  [27] F. Classen and H. Meyr, “Frequency synchronization algorithms for OFDM systems suitable for communication over frequency selective fading channels,” in Proc. IEEE VTC’94, Stockholm, Sweden, Jun. 1994, pp. 1655–1659. [28] L. Yang, G. Ren, and Z. Qiu, “A novel Doppler frequency offset estimation method for DVB-T system in HST environment,” IEEE Trans. Broadcasting, vol. 58, no. 1, pp. 139–143, Mar. 2012. [30] F. Foroughi, J. Lofgren, and O. Edfors, "Channel estimation for a mobile terminal in a multi-standard environment (LTE and DVB-H)," in Signal Processing and Communication Systems, 2009. ICSPCS 2009. 3rd International Conference, pp. 1-9, 2009.  [31] F. Foroughi, F. Sharifabad, and O. Edfors, “Low complexity channel estimation for LTE in fast fading environments for implementation on Multi-Standard platforms,” in proc. IEEE Vehicular Tech. Conf., Ottawa, September 2010.

27. Thanks for your attention.