Superimposed training-based joint CFO and channel estimation for CP-OFDM modulated two-way relay networks

  • Authors:

  • Gongpu Wang;Feifei Gao;Xin Zhang;Chintha Tellambura

  • Affiliations:

  • Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada;School of Engineering and Science, Jacobs University, Bremen, Germany;School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China;Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

  • Venue:
  • EURASIP Journal on Wireless Communications and Networking - Special issue on physical-layer network coding for wireless cooperative networks
  • Year:
  • 2010

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Abstract

Joint carrier frequency offset (CFO) and channel estimation is considered for two-way relay networks (TWRNs). Existing estimators provide only the convolved channel parameters and the mixed CFO values. In contrast, estimators using a superimposed training strategy are developed for the individual frequency and channel parameters. Depending on the number of pilots, three different estimators are developed. An iterative estimator with low complexity is also developed to further improve the estimation accuracy. The Cramér-Rao Bounds (CRBs) are derived. The simulations show that the iterative estimator converges rapidly, and the resultant estimation mean square error (MSE) approaches the CRB. For the special case of small CFO between the two source terminals, the MSE achieves the CRB at high SNRs, and the iterative algorithm is not necessary. However, for the general case, the gap between the MSE and the CRB indicates that there is room for further improvement of the estimation accuracy.