Coding-Assisted Blind MIMO Separation and Decoding

Despite the widespread use of forward-error correcting (FEC) coding, most multiple-input-multiple-output (MIMO) blind channel-estimation techniques ignore its presence and instead make the simplifying assumption that the transmitted symbols are uncoded. However, FEC induces code structure in the transmitted sequence that can be exploited to improve blind MIMO channel estimates. In this paper, we exploit the iterative channel estimation based on a posteriori information for blind MIMO separation and decoding. Experiments show improvements that are achievable by exploiting the existence of coding structures and that our technique can approach the performance of a Bahl-Cocke-Jelinek-Raviv (BCJR) equalizer with perfect channel-state information in a reasonable signal-to-noise ratio (SNR) range. In addition, by splitting the FEC codeword over multiple blocks, the impact in performance of a bad-conditioned channel matrix can be kept at a reasonable level.

[1]  Ghassan Kawas Kaleh,et al.  Joint parameter estimation and symbol detection for linear or nonlinear unknown channels , 1994, IEEE Trans. Commun..

[2]  Todd K. Moon,et al.  A Generalized BCJR Algorithm and Its Use in Iterative Blind Channel Identification , 2007, IEEE Signal Processing Letters.

[3]  Babak Hassibi,et al.  On joint detection and decoding of linear block codes on Gaussian vector channels , 2006, IEEE Transactions on Signal Processing.

[4]  T. Moon,et al.  A generalized LDPC decoder for blind turbo equalization , 2005, IEEE Transactions on Signal Processing.

[5]  Tareq Y. Al-Naffouri,et al.  Exploiting error-control coding and cyclic-prefix in channel estimation for coded OFDM systems , 2003, IEEE Communications Letters.

[6]  Sylvie Perreau,et al.  Reduced computation blind equalization for FIR channel input Markov models , 1995, Proceedings IEEE International Conference on Communications ICC '95.

[7]  Gerhard Bauch,et al.  Optimization of symbol mappings for bit-interleaved coded Modulation with iterative decoding , 2003, IEEE Communications Letters.

[8]  Stephan ten Brink,et al.  Achieving near-capacity on a multiple-antenna channel , 2003, IEEE Trans. Commun..

[9]  John R. Barry,et al.  Exploiting error-control coding in blind channel estimation , 2001, GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270).

[10]  A. Glavieux,et al.  Near Shannon limit error-correcting coding and decoding: Turbo-codes. 1 , 1993, Proceedings of ICC '93 - IEEE International Conference on Communications.

[11]  Joaquín Míguez,et al.  Maximum Likelihood Turbo Iterative Channel Estimation for Space-Time Coded Systems and Its Application to Radio Transmission in Subway Tunnels , 2004, EURASIP J. Adv. Signal Process..

[12]  Gene H. Golub,et al.  Matrix computations (3rd ed.) , 1996 .

[13]  John S. Thompson,et al.  Extending a Fixed-Complexity Sphere Decoder to Obtain Likelihood Information for Turbo-MIMO Systems , 2008, IEEE Transactions on Vehicular Technology.

[14]  J.D. Villasenor,et al.  Blind turbo decoding and equalization , 1999, 1999 IEEE 49th Vehicular Technology Conference (Cat. No.99CH36363).

[15]  Hyung-Myung Kim,et al.  Reduced Complexity Sliding Window BCJR Decoding Algorithms for Turbo Codes , 1999, IMACC.

[16]  Babak Hassibi,et al.  Bounds on the performance of sphere decoding of linear block codes , 2005, IEEE Information Theory Workshop, 2005..

[17]  Joachim Speidel,et al.  A comparative study of iterative channel estimators for mobile OFDM systems , 2003, IEEE Trans. Wirel. Commun..

[18]  Robert H. Halstead,et al.  Matrix Computations , 2011, Encyclopedia of Parallel Computing.

[19]  Chrysostomos L. Nikias,et al.  An ML/MMSE estimation approach to blind equalization , 1994, Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing.

[20]  Ching-Yung Chen,et al.  Blind Equalization and System Identification , 2006 .

[21]  John D. Villasenor,et al.  Combined turbo detection and decoding for unknown ISI channels , 2003, IEEE Trans. Commun..

[22]  Xiaodong Wang,et al.  Efficient maximum-likelihood decoding of spherical lattice space-time codes , 2006, 2006 IEEE International Conference on Communications.

[23]  Riccardo Raheli,et al.  Per-Survivor Processing: a general approach to MLSE in uncertain environments , 1995, IEEE Trans. Commun..

[24]  E. Oja,et al.  Independent Component Analysis , 2013 .

[25]  M. Tsatsanis,et al.  Stochastic maximum likelihood methods for semi-blind channel equalization , 1997, Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136).

[26]  J. Treichler,et al.  A new approach to multipath correction of constant modulus signals , 1983 .

[27]  Charles Elkan,et al.  Expectation Maximization Algorithm , 2010, Encyclopedia of Machine Learning.

[28]  Javier Garcia-Frías,et al.  Serially-Concatenated LDGM Codes for MIMO Channels , 2007, IEEE Transactions on Wireless Communications.

[29]  Ruifeng Zhang,et al.  Blind OFDM channel estimation through linear precoding: a subspace approach , 2002, Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002..

[30]  Xu Zhao,et al.  A feasible Blind Equalization scheme in large constellation MIMO systems , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[31]  Bahram Honary,et al.  Improved blind turbo detector , 2000, VTC2000-Spring. 2000 IEEE 51st Vehicular Technology Conference Proceedings (Cat. No.00CH37026).

[32]  Xia Liu,et al.  SVD-Based Blind Channel Estimation for a MIMO OFDM System Employing a Simple Block Pre-coding Scheme , 2007, EUROCON 2007 - The International Conference on "Computer as a Tool".

[33]  Georgios B. Giannakis,et al.  Subspace-based (semi-) blind channel estimation for block precoded space-time OFDM , 2002, IEEE Trans. Signal Process..

[34]  Hui Liu Signal Processing Applications in CDMA Communications , 2000 .

[35]  D. Godard,et al.  Self-Recovering Equalization and Carrier Tracking in Two-Dimensional Data Communication Systems , 1980, IEEE Trans. Commun..

[36]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[37]  Michael Davies,et al.  ICA with the EM Algorithm in the Low Noise Case , 2006 .

[38]  Gerhard Fettweis,et al.  Channel state information based LLR clipping in list MIMO detection , 2008, 2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications.

[39]  I. Jolliffe Principal Component Analysis , 2002 .

[40]  New York Dover,et al.  ON THE CONVERGENCE PROPERTIES OF THE EM ALGORITHM , 1983 .

[41]  Jean-Francois Cardoso,et al.  Approximate likelihood for noisy mixtures , 1999 .

[42]  Tricia J. Willink,et al.  Iterative tree search detection for MIMO wireless systems , 2005, IEEE Transactions on Communications.

[43]  Andrew C. Singer,et al.  Turbo equalization: principles and new results , 2002, IEEE Trans. Commun..

[44]  John Cocke,et al.  Optimal decoding of linear codes for minimizing symbol error rate (Corresp.) , 1974, IEEE Trans. Inf. Theory.

[45]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[46]  John R. Barry,et al.  Blind iterative channel identification and equalization , 2001, ICC 2001. IEEE International Conference on Communications. Conference Record (Cat. No.01CH37240).

[47]  Hoang Nguyen,et al.  Blind and semi-blind equalization of CPM signals with the EMV algorithm , 2003, IEEE Trans. Signal Process..

[48]  Visa Koivunen,et al.  Autocorrelation properties of channel encoded sequences-applicability to blind equalization , 2000, IEEE Trans. Signal Process..

[49]  A. Edelman Eigenvalues and condition numbers of random matrices , 1988 .