A Non-Pilot Aided Iterative Carrier Frequency Offset Estimator Using Optimal Filtering for an Interleaved OFDMA Uplink System
In an uplink transmission of a coded orthogonal frequency division multiple access (C-OFDMA) system, channel estimation, time and frequency synchronization has to be addressed. For this purpose a control data, i.e. a known training sequence called “preamble” and pilot sub-carriers are used. As an alternative to the classic scheme and in order to maximize the data rate, we propose a non-pilot aided estimator based on an iterative architecture that does not require pilot sub-carriers. Our approach combines 1/ the so-called minimum mean square error successive detector to estimate the signal sent by each user 2/ a recursive method estimating the CFOs. Various algorithms such as the extended Kalman filter, the sigma-point Kalman filters and the extended H ∞ filter are tested and their performances are compared in terms of convergence speed and estimation accuracy. When considering an interleaved OFDMA uplink system over a Rayleigh fading channel, simulation results clearly show the efficiency of the proposed algorithm in terms of CFO estimation and bit error rate performances.
KeywordsOFDMA Extended Kalman filter Sigma-point Kalman filter Extended H∞ filter Carrier frequency offset
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- 1.IEEE Standard (2006) Part 16: Air Interface for Fixed and Mobile Broadband Wireless Access System; Amendment 2: Physical and Medium Access Control Layers for Combined Fixed and Mobile Operation in Licensed Bands, IEEE Std 802.16e-2005. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1603394&userType=inst.
- 2.3GPP Standard (2009) Technical Specification Group Radio Access Network; Evolved Universal Terrestrial Radio Access (E-UTRA); Physical layer procedures (Release 8), 3GPP TS 36.213 V8.8.0. http://www.etsi.org/deliver/etsi_ts/136300_136399/136304/08.08.00_60/ts_136304v080800p.pdf.
- 5.Zhao, P., Kuang, L., & Lu, J. (2006). Carrier frequency offset estimation using extended Kalman filter in uplink OFDMA systems. ICC ’06, June 2006, vol. 6, pp. 2870–2874.Google Scholar
- 6.Dai X. (2007) Carrier frequency offset estimation and correction for OFDMA uplink. IET Communication 1(2): 261–273Google Scholar
- 10.Cao, Z. Tureli, U., Yao, Y., & Honan, P. (2004). Frequency synchronization for generalized OFDMA uplink. Globecom ’04, Dec. 2004 , pp. 1071–1075.Google Scholar
- 11.Hou, S. W., & Ko, C. C. (2008). Intercarrier interference suppression for OFDMA uplink in time and frequency selective Rayleigh fading channels. VTC ’08, May 2008, pp. 1438–1442.Google Scholar
- 12.Pun, M. O., Shang-Ho, T., & Jay Kuo, C. C. (2004). An EM-based joint maximum likelihood estimation of carrier frequency offset and channel for uplink OFDMA systems. VTC ’04, Sept. 2004, vol. 1, pp. 598–602.Google Scholar
- 13.Pun, M. O., Shang-Ho, T., & Jay Kuo, C. C. (2004). Joint maximum likelihood estimation of carrier frequency offset and channel for uplink OFDMA systems. Globecom ’04, Nov. 2004, vol. 6, pp. 3748–3752.Google Scholar
- 14.Xiaoyu, F., Minn, H., & Cantrell, C. (2006). Two novel iterative joint frequency-offset and channel estimation methods for OFDMA uplink. GLOBECOM ’06, Nov.–Dec. 2006, vol. 3, pp. 1–6.Google Scholar
- 16.Movahedian, M., Yi Ma, M., & Tafazolli, R. (2008). An MUI resilient approach for blind CFO estimation in OFDMA uplink. PIMRC ’08, Sept. 2008, pp. 1–5.Google Scholar
- 18.Van der Merwe, R. (2004). Sigma-point Kalman filters for probabilistic inference in dynamic state-space models, PhD thesis, OGI School of Science and Engineering, Oregon Health and Science University, Portland, 2004, pp. 35–37, 50–71.Google Scholar
- 19.Poveda, H., Ferré, G., Grivel, E., & Ramos, P. (2009). A blind iterative carrier frequency offset estimator based on a Kalman approach for an interleaved OFDMA uplink system. EUSIPCO ’09, Aug. 2009, pp. 378–382.Google Scholar
- 21.Haykin S. (1996) Adaptative filter theory. Prentice Hall, Englewood, pp 328–333Google Scholar
- 23.Hassibi, B., Sayed, A. H., & Kailath, T. (1999). Indefinite-quadratic estimation and control, a unified approach to H 2 and H ∞ theories. Philadelphia: Society for Industrial and Applied Mathematics (SIAM).Google Scholar