Design of adaptive multi-branch SIC receivers for MIMO spatial multiplexing systems

In this paper we propose an adaptive successive interference cancellation (SIC) strategy for multiple-input multiple-output (MIMO) spatial multiplexing systems based on multiple interference cancellation branches. The proposed detection structure employs SICs on several parallel branches which are equipped with different ordering patterns so that each branch produces a vector of estimate symbols by exploiting a certain ordering pattern. The novel detector, therefore, achieves higher detection diversity by selecting the branch which yields the estimates with best performance according to the selection rule. We consider two selection rules for the proposed detector, namely, maximum likelihood (ML), minimum mean square error (MMSE) criteria. An efficient adaptive receiver is developed to update the filter weight vectors and estimate the channel using the recursive least squares (RLS) algorithm. The simulation results reveal that our scheme successfully mitigates the error propagation and approaches the performance of the optimal ML detector, while requiring a significantly lower complexity than the ML and sphere decoder detectors.

[1]  Ebrahim Karami,et al.  Tracking Performance of Least Squares MIMO Channel Estimation Algorithm , 2007, IEEE Transactions on Communications.

[2]  John M. Cioffi,et al.  On the relation between V-BLAST and the GDFE , 2001, IEEE Communications Letters.

[3]  Babak Hassibi,et al.  On the sphere-decoding algorithm I. Expected complexity , 2005, IEEE Transactions on Signal Processing.

[4]  Sergio Verdu,et al.  Multiuser Detection , 1998 .

[5]  Ali H. Sayed,et al.  The finite-length multi-input multi-output MMSE-DFE , 2000, IEEE Trans. Signal Process..

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

[7]  Alexandra Duel-Hallen,et al.  Equalizers for Multiple Input/Multiple Output Channels and PAM Systems with Cyclostationary Input Sequences , 1992, IEEE J. Sel. Areas Commun..

[8]  Reinaldo A. Valenzuela,et al.  Detection algorithm and initial laboratory results using V-BLAST space-time communication architecture , 1999 .

[9]  A. Robert Calderbank,et al.  Space-Time block codes from orthogonal designs , 1999, IEEE Trans. Inf. Theory.

[10]  Gerard J. Foschini,et al.  Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas , 1996, Bell Labs Technical Journal.

[11]  M. J. Gans,et al.  On Limits of Wireless Communications in a Fading Environment when Using Multiple Antennas , 1998, Wirel. Pers. Commun..

[12]  Reinaldo A. Valenzuela,et al.  V-BLAST: an architecture for realizing very high data rates over the rich-scattering wireless channel , 1998, 1998 URSI International Symposium on Signals, Systems, and Electronics. Conference Proceedings (Cat. No.98EX167).

[13]  Emanuele Viterbo,et al.  A universal lattice code decoder for fading channels , 1999, IEEE Trans. Inf. Theory.

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

[15]  Emre Telatar,et al.  Capacity of Multi-antenna Gaussian Channels , 1999, Eur. Trans. Telecommun..

[16]  Behnaam Aazhang,et al.  Multistage detection in asynchronous code-division multiple-access communications , 1990, IEEE Trans. Commun..