Scheduling of the Activations in Iterative Detection, Decoding, and Channel Estimation for MIMO-OFDM

An iterative receiver for a multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) system is considered to jointly decode the transmitted bits and estimate the channel state. The receiver consists of the a posteriori probability (APP) algorithm, the repeat-accumulate (RA) decoder, and the least-squares (LS) channel estimator. An obvious problem, with more than two blocks in an iterative receiver, is to find the optimal activation schedule of the different blocks. This paper proposes to use extrinsic information transfer (EXIT) charts to characterize the behavior of the receiver blocks and find out the optimal activation schedule for them. A semi-analytical expression of the EXIT function is derived for the decision directed LS channel estimator. An algorithm is proposed to generate the EXIT function of the APP algorithm as a function of channel estimate mutual information (MI). Surface fitting is used to get closed form expressions for the EXIT functions of the APP algorithm and the RA decoder. Trellis search based algorithms are shown to find the convergence with the lowest possible complexity using the EXIT charts. With the proposed concept, the activation scheduling can be adapted to prevailing channel circumstances and unnecessary iterations will be avoided.

[1]  Xiaodong Wang,et al.  EXIT chart analysis of turbo multiuser detection , 2005, IEEE Trans. Wirel. Commun..

[2]  Jürgen Lindner,et al.  An improved block equalization scheme for uncertain channel estimation , 2007, IEEE Transactions on Wireless Communications.

[3]  P. Alexander,et al.  Iterative decoding and channel estimation , 2000, 2000 IEEE International Symposium on Information Theory (Cat. No.00CH37060).

[4]  Sailes K. Sengijpta Fundamentals of Statistical Signal Processing: Estimation Theory , 1995 .

[5]  Paul D. Alexander,et al.  Iterative detection in code-division multiple-access with error control coding , 1998, Eur. Trans. Telecommun..

[6]  Stephan ten Brink,et al.  Design of repeat-accumulate codes for iterative detection and decoding , 2003, IEEE Trans. Signal Process..

[7]  Alex J. Grant,et al.  Convergence analysis and optimal scheduling for multiple concatenated codes , 2005, IEEE Transactions on Information Theory.

[8]  K. Pedersen,et al.  A stochastic multiple-input-multiple-output radio channel model for evaluation of space-time coding algorithms , 2000, Vehicular Technology Conference Fall 2000. IEEE VTS Fall VTC2000. 52nd Vehicular Technology Conference (Cat. No.00CH37152).

[9]  Markku J. Juntti,et al.  Avoiding Matrix Inversion in DD SAGE Channel Estimation in MIMO-OFDM with M-QAM , 2009, 2009 IEEE 70th Vehicular Technology Conference Fall.

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

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

[12]  P. D. Alexander,et al.  Iterative channel and information sequence estimation in CDMA , 2000, 2000 IEEE Sixth International Symposium on Spread Spectrum Techniques and Applications. ISSTA 2000. Proceedings (Cat. No.00TH8536).

[13]  R. Otnes,et al.  Soft iterative channel estimation for turbo equalization: comparison of channel estimation algorithms , 2002, The 8th International Conference on Communication Systems, 2002. ICCS 2002..

[14]  Richard E. Blahut,et al.  Convergence Analysis and BER Performance of Finite-Length Turbo Codes , 2007, IEEE Transactions on Communications.

[15]  Michael Tüchler Convergence prediction for iterative decoding of threefold concatenated systems , 2002, GLOBECOM.

[16]  Markku J. Juntti,et al.  On the Activation Ordering of Detector, Decoder, and Channel Estimator in Iterative Receiver for MIMO-OFDM , 2010, 2010 IEEE International Conference on Communications.

[17]  Mark C. Reed,et al.  Adaptive Optimization of an Iterative Multiuser Detector for Turbo-Coded CDMA , 2008, IEEE Transactions on Wireless Communications.

[18]  Michael Tüchler,et al.  EXIT CHART ANALYSIS APPLIED TO ADAPTIVE TURBO EQUALIZATION , 2002 .

[19]  Andrej Stefanov,et al.  Turbo-coded modulation for systems with transmit and receive antenna diversity over block fading channels: system model, decoding approaches, and practical considerations , 2001, IEEE J. Sel. Areas Commun..

[20]  Werner G. Teich,et al.  Joint Iterative Equalization, Demapping, and Decoding with a Soft Interference Canceler , 2003 .

[21]  Markku J. Juntti,et al.  Iterative Joint Detection, Decoding, and Channel Estimation in Turbo-Coded MIMO-OFDM , 2009, IEEE Transactions on Vehicular Technology.

[22]  Hesham El Gamal,et al.  Analyzing the turbo decoder using the Gaussian approximation , 2001, IEEE Trans. Inf. Theory.

[23]  Paul D. Alexander,et al.  Iterative multi-user detection and channel estimation for CDMA with non-binary modulation , 2001, GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270).

[24]  Mark C. Reed,et al.  EXIT Chart Analysis of an Iterative Receiver with Channel Estimation , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[25]  David Gesbert,et al.  From theory to practice: an overview of MIMO space-time coded wireless systems , 2003, IEEE J. Sel. Areas Commun..

[26]  Helmut Bölcskei,et al.  An overview of MIMO communications - a key to gigabit wireless , 2004, Proceedings of the IEEE.

[27]  Stephan ten Brink,et al.  Convergence behavior of iteratively decoded parallel concatenated codes , 2001, IEEE Trans. Commun..

[28]  Preben E. Mogensen,et al.  A stochastic MIMO radio channel model with experimental validation , 2002, IEEE J. Sel. Areas Commun..

[29]  Michael Tüchler,et al.  Iterative channel estimation for turbo equalization of time-varying frequency-selective channels , 2004, IEEE Transactions on Wireless Communications.

[30]  Dariush Divsalar,et al.  Iterative turbo decoder analysis based on density evolution , 2001, IEEE J. Sel. Areas Commun..