Tree-Search Multiple-Symbol Differential Decoding for Unitary Space-Time Modulation

Differential space-time modulation (DSTM) using unitary-matrix signal constellations is an attractive solution for transmission over multiple-input multiple-output (MIMO) fading channels without requiring channel state information (CSI) at the receiver. To avoid a high error floor for DSTM in relatively fast MIMO fading channels, multiple-symbol differential detection (MSDD) has to be applied at the receiver. MSDD jointly processes blocks of several received matrix-symbols, and power efficiency improves as the blocksize increases. But since the search space of MSDD grows exponentially with the blocksize and also with the number of transmit antennas and the data rate, the complexity of MSDD quickly becomes prohibitive. In this paper, we investigate the application of tree-search algorithms to overcome the complexity limitation of MSDD. We devise a nested MSDD structure consisting of an outer and a number of inner tree-search decoders, which renders MSDD feasible for wide ranges of system parameters. Decoder designs tailored for diagonal and orthogonal DSTM codes are given, and a more power-efficient variant of MSDD, so-called subset MSDD, is proposed. Furthermore, we derive a tight symbol-error rate approximation for MSDD, which lends itself to efficient numerical evaluation. Numerical and simulation results for different DSTM constellations and fading channel scenarios show that the new tree-search MSDD achieves a significantly better performance-complexity tradeoff than benchmark decoders.

[1]  Lutz H.-J. Lampe,et al.  Noncoherent receivers for differential space-time modulation , 2002, IEEE Trans. Commun..

[2]  Bertrand M. Hochwald,et al.  Differential unitary space-time modulation , 2000, IEEE Trans. Commun..

[3]  Siavash M. Alamouti,et al.  A simple transmit diversity technique for wireless communications , 1998, IEEE J. Sel. Areas Commun..

[4]  Fumihito Sasamori,et al.  Multiple-symbol differential detection for space-time block codes with diversity reception , 2006, IEEE Wireless Communications and Networking Conference, 2006. WCNC 2006..

[5]  Thomas L. Marzetta,et al.  Systematic design of unitary space-time constellations , 2000, IEEE Trans. Inf. Theory.

[6]  Dariush Divsalar,et al.  Multiple-symbol differential detection of MPSK , 1990, IEEE Trans. Commun..

[7]  P. Ho,et al.  Error performance of multiple symbol differential detection of PSK signals transmitted over correlated Rayleigh fading channels , 1991, ICC 91 International Conference on Communications Conference Record.

[8]  M. O. Damen,et al.  A unified framework for tree search decoding: rediscovering the sequential decoder , 2005, SPAWC 2005.

[9]  Giorgio Matteo Vitetta,et al.  Further results on differential space-time modulations , 2003, IEEE Trans. Commun..

[10]  Brian L. Hughes,et al.  Differential space-time modulation , 1999, WCNC. 1999 IEEE Wireless Communications and Networking Conference (Cat. No.99TH8466).

[11]  Vijay K. Bhargava,et al.  Reduced complexity multiple symbol differential detection of space-time block code , 2002, 2002 IEEE Wireless Communications and Networking Conference Record. WCNC 2002 (Cat. No.02TH8609).

[12]  Lutz H.-J. Lampe,et al.  Multiple-symbol differential sphere decoding , 2005, IEEE Transactions on Communications.

[13]  Paul K. M. Ho,et al.  The performance of Fano-multiple symbol differential detection , 2005, IEEE International Conference on Communications, 2005. ICC 2005. 2005.

[14]  Wai Ho Mow,et al.  Multiple-antenna differential lattice decoding , 2005, IEEE Journal on Selected Areas in Communications.

[15]  P. Schniter,et al.  Multiple-Symbol Detection of Differential Unitary Space-Time Modulation in Fast-Fading Channels with Known Correlation , 2004 .

[16]  Babak Hassibi,et al.  Cayley differential unitary space - Time codes , 2002, IEEE Trans. Inf. Theory.

[17]  Matthias Brehler,et al.  Asymptotic error probability analysis of quadratic receivers in Rayleigh-fading channels with applications to a unified analysis of coherent and noncoherent space-Time receivers , 2001, IEEE Trans. Inf. Theory.

[18]  Giuseppe Caire,et al.  On maximum-likelihood detection and the search for the closest lattice point , 2003, IEEE Trans. Inf. Theory.

[19]  R. Clarke A statistical theory of mobile-radio reception , 1968 .

[20]  Giuseppe Caire,et al.  Computing error probabilities over fading channels: A unified approach , 1998, Eur. Trans. Telecommun..

[21]  Chintha Tellambura,et al.  Multiple-symbol differential unitary space-time demodulation with reduced-complexity , 2005, IEEE International Conference on Communications, 2005. ICC 2005. 2005.

[22]  Desmond P. Taylor,et al.  Maximum likelihood decoding of uncoded and coded PSK signal sequences transmitted over Rayleigh flat-fading channels , 1995, IEEE Trans. Commun..

[23]  Michael P. Fitz,et al.  A new view of performance analysis of transmit diversity schemes in correlated Rayleigh fading , 2002, IEEE Trans. Inf. Theory.

[24]  Chong-Yung Chi,et al.  Extended Differential Unitary Space-Time Modulation: A Non-Coherent Scheme with Error Penalty Less Than 3DB , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[25]  Brian L. Hughes,et al.  Optimal space-time constellations from groups , 2003, IEEE Trans. Inf. Theory.

[26]  Zhan Guo,et al.  Reduced complexity Schnorr-Euchner decoding algorithms for MIMO systems , 2004, IEEE Communications Letters.

[27]  Kenneth L. Clarkson,et al.  Fast multiple-antenna differential decoding , 2001, IEEE Trans. Commun..

[28]  Hamid Jafarkhani,et al.  A differential detection scheme for transmit diversity , 2000, IEEE Journal on Selected Areas in Communications.

[29]  Rolf Johannesson,et al.  Fundamentals of Convolutional Coding , 1999 .

[30]  Alexander Vardy,et al.  Closest point search in lattices , 2002, IEEE Trans. Inf. Theory.