Joint equalization and interference suppression for high data rate wireless systems

Enhanced Data Rates for Global Evolution (EDGE) is currently being standardized as an evolution of GSM in Europe and IS-136 in the United States as an air interface for high speed data services for third generation mobile systems. We study space-time processing for EDGE to provide interference suppression. We consider the use of two receive antennas and propose a joint equalization and diversity receiver. This receiver uses front-end filters on each diversity branch to perform minimum mean-square error (MMSE) cochannel interference suppression, while leaving the intersymbol interference to be mitigated by the subsequent equalizer. The equalizer is a delayed decision feedback sequence estimator (DDFSE), consisting of a reduced-state Viterbi processor and a feedback filter. The equalizer provides soft output to the channel decoder after deinterleaving. We describe a novel weight generation algorithm and present simulation results on the link performance of EDGE with interference suppression. These results show a significant improvement in the signal-to-interference ratio (SIR) performance due to both diversity (against fading) and interference suppression. At a 10% block error rate, the proposed receiver provides a 20 dB improvement in SIR for both the typical urban and hilly terrain profiles.

[1]  J.B. Huber,et al.  Reduced-state soft-output trellis-equalization incorporating soft feedback , 1996, Proceedings of GLOBECOM'96. 1996 IEEE Global Telecommunications Conference.

[2]  Sirikiat Lek Ariyavisitakul,et al.  Reduced-Complexity Equalization Techniques for Broadband Wireless Channels , 1997, IEEE J. Sel. Areas Commun..

[3]  Alexandra Duel-Hallen,et al.  Delayed decision-feedback sequence estimation , 1989, IEEE Trans. Commun..

[4]  J. Skold,et al.  Radio interface performance of EDGE, a proposal for enhanced data rates in existing digital cellular systems , 1998, VTC '98. 48th IEEE Vehicular Technology Conference. Pathway to Global Wireless Revolution (Cat. No.98CH36151).

[5]  Yoichi Sato,et al.  Optimum soft-output detection for channels with intersymbol interference , 1995, IEEE Trans. Inf. Theory.

[6]  Shahid U. H. Qureshi,et al.  Reduced-state sequence estimation with set partitioning and decision feedback , 1988, IEEE Trans. Commun..

[7]  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.

[8]  Inkyu Lee,et al.  Optimum space-time processors with dispersive interference-unified analysis and required filter span , 1999, 1999 IEEE International Conference on Communications (Cat. No. 99CH36311).

[9]  J. H. Winters Signal acquisition and tracking with adaptive arrays in the digital mobile radio system IS-54 with flat fading , 1993 .

[10]  Randy L. Haupt,et al.  Introduction to Adaptive Arrays , 1980 .

[11]  Ye Li,et al.  Joint coding and decision feedback equalization for broadband wireless channels , 1998, VTC '98. 48th IEEE Vehicular Technology Conference. Pathway to Global Wireless Revolution (Cat. No.98CH36151).

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

[13]  Achilleas Anastasopoulos,et al.  Soft-decisions per-survivor processing for mobile fading channels , 1997, 1997 IEEE 47th Vehicular Technology Conference. Technology in Motion.

[14]  L. Lee Real-Time Minimal-Bit-Error Probability Decoding of Convolutional Codes , 1974, IEEE Trans. Commun..

[15]  Jiunn-Tsair Chen,et al.  A two-stage hybrid approach for CCI/ISI reduction with space-time processing , 1997, IEEE Communications Letters.