Low-Complexity Iterative Channel Estimation for Turbo Receivers

This letter discusses a receiver-side channel estimation algorithm well-suited to turbo equalizers for multiple-input multiple-output (MIMO) systems. The proposed technique is a Kalman-based channel estimator that runs on parallel single-input single-output (SISO) channels. Soft-decision-feedback interference cancellation is utilized to reduce the MIMO channel estimation problem into multiple SISO channel estimation problems. Unlike existing methods, however, the inherent correlation that exists among the output samples of the successive interference canceller is suppressed via careful puncturing of observation samples. The quality of soft decisions and channel estimates are also continuously monitored and incorporated in the Kalman filter update process.

[1]  Alexander M. Haimovich,et al.  Decision directed iterative channel estimation for MIMO systems , 2003, IEEE International Conference on Communications, 2003. ICC '03..

[2]  Andrew C. Singer,et al.  Soft input channel estimation for turbo equalization , 2004, IEEE Transactions on Signal Processing.

[3]  Joachim Hagenauer,et al.  A Viterbi algorithm with soft-decision outputs and its applications , 1989, IEEE Global Telecommunications Conference, 1989, and Exhibition. 'Communications Technology for the 1990s and Beyond.

[4]  Giuseppe Caire,et al.  Successive interference cancellation with SISO decoding and EM channel estimation , 2001, IEEE Journal on Selected Areas in Communications.

[5]  Daejung Yoon,et al.  Soft-Decision-Driven Channel Estimation for Pipelined Turbo Receivers , 2011, IEEE Transactions on Communications.

[6]  Ran-Hong Yan,et al.  Iterative channel estimation using soft decision feedback , 1998, IEEE GLOBECOM 1998 (Cat. NO. 98CH36250).

[7]  Jie Gao,et al.  Decision-directed estimation of MIMO time-varying Rayleigh fading channels , 2005, IEEE Transactions on Wireless Communications.

[8]  J. Woods,et al.  Probability and Random Processes with Applications to Signal Processing , 2001 .

[9]  Mohammad Ali Khalighi,et al.  Semi-Blind Channel Estimation Using the EM Algorithm in Iterative MIMO APP Detectors , 2006, IEEE Transactions on Wireless Communications.

[10]  S. Kay.  Fundamentals of statistical signal processing: estimation theory , 1993 .

[11]  Andrew C. Singer,et al.  Turbo equalization with an unknown channel , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[12]  J. Wehinger,et al.  Iterative joint detection, decoding, and channel estimation for dual antenna arrays in frequency selective fading , 2002, The 5th International Symposium on Wireless Personal Multimedia Communications.

[13]  Luc Vandendorpe,et al.  Comparison of EM-Based Algorithms for MIMO Channel Estimation , 2007, IEEE Transactions on Communications.

[14]  John M. Cioffi,et al.  Iterative soft interference cancellation for multiple antenna systems , 2000, 2000 IEEE Wireless Communications and Networking Conference. Conference Record (Cat. No.00TH8540).

[15]  Andrew C. Singer,et al.  Minimum mean squared error equalization using a priori information , 2002, IEEE Trans. Signal Process..

[16]  Daejung Yoon,et al.  Soft-Decision-Directed MIMO Channel Estimation Geared to Pipelined Turbo Receiver Architecture , 2010, 2010 IEEE International Conference on Communications.

[17]  Michael Tüchler,et al.  Performance of soft iterative channel estimation in turbo equalization , 2002, 2002 IEEE International Conference on Communications. Conference Proceedings. ICC 2002 (Cat. No.02CH37333).

[18]  James A. Ritcey,et al.  16-QAM BICM-ID in fading channels with imperfect channel state information , 2003, IEEE Trans. Wirel. Commun..