Application-specific Instruction Set Processor Implementation of List Sphere Detector

Multiple-input multiple-output (MIMO) technology enables higher transmission capacity without additional frequency spectrum and is becoming a part of many wireless system standards. Sphere detection has been introduced in MIMO systems to achieve maximum likelihood (ML) or near-ML estimation with reduced complexity. This paper presents an application-specific instruction set processor (ASIP) implementation of if-best list sphere detector (LSD) using the transport triggered architecture (TTA). The implementation is based on using memory and heap data structure for symbol vector sorting. The design space is explored by presenting several variations of the implementation and comparing them with each other in terms of latency and hardware complexity. An early proposal for a parallelized architecture with a detection throughput of approximately 5.3 Mbps is presented.

[1]  Markku J. Juntti,et al.  Suboptimal soft-output MAP detector with lattice reduction , 2006, IEEE Signal Processing Letters.

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

[3]  D. Garrett,et al.  A 28.8 Mb/s 4 /spl times/ 4 MIMO 3G CDMA receiver for frequency selective channels , 2005, IEEE Journal of Solid-State Circuits.

[4]  Jarmo Takala,et al.  Memory-Based List Updating for List Sphere Decoders , 2007, 2007 IEEE Workshop on Signal Processing Systems.

[5]  J.R. Cavallaro,et al.  Complexity Analysis of MMSE Detector Architectures for MIMO OFDM Systems , 2005, Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005..

[6]  Takeshi Onizawa,et al.  A new signal detection scheme combining ZF and K-best algorithms for OFDM/SDM , 2004, 2004 IEEE 15th International Symposium on Personal, Indoor and Mobile Radio Communications (IEEE Cat. No.04TH8754).

[7]  Dirk Wübben,et al.  Near-maximum-likelihood detection of MIMO systems using MMSE-based lattice reduction , 2004, 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577).

[8]  B. Hochwald,et al.  Silicon complexity for maximum likelihood MIMO detection using spherical decoding , 2004, IEEE Journal of Solid-State Circuits.

[9]  Gregory W. Wornell,et al.  Lattice-reduction-aided detectors for MIMO communication systems , 2002, Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE.

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

[11]  J.R. Fonollosa,et al.  Efficient implementation of sphere demodulation , 2003, 2003 4th IEEE Workshop on Signal Processing Advances in Wireless Communications - SPAWC 2003 (IEEE Cat. No.03EX689).

[12]  Henk Corporaal Microprocessor architectures - from VLIW to TTA , 1997 .

[13]  Jee Woong Kang,et al.  Simplified ML detection scheme for MIMO systems , 2004, 2004 IEEE 59th Vehicular Technology Conference. VTC 2004-Spring (IEEE Cat. No.04CH37514).

[14]  U. Fincke,et al.  Improved methods for calculating vectors of short length in a lattice , 1985 .

[15]  Markku J. Juntti,et al.  Application-Specific Instruction Set Processor Implementation of List Sphere Detector , 2007, 2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers.

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

[17]  Henk Corporaal Design of transport triggered architectures , 1994, Proceedings of 4th Great Lakes Symposium on VLSI.

[18]  Franz Hlawatsch,et al.  Efficient detection algorithms for MIMO channels: a geometrical approach to approximate ML detection , 2003, IEEE Trans. Signal Process..

[19]  Joseph R. Cavallaro,et al.  Comparison of Two Novel List Sphere Detector Algorithms for MIMO-OFDM Systems , 2006, 2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications.

[20]  Mohamed Oussama Damen,et al.  Lattice code decoder for space-time codes , 2000, IEEE Communications Letters.

[21]  A. Burg,et al.  VLSI implementation of MIMO detection using the sphere decoding algorithm , 2005, IEEE Journal of Solid-State Circuits.

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

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

[24]  John B. Anderson,et al.  Sequential Coding Algorithms: A Survey and Cost Analysis , 1984, IEEE Trans. Commun..

[25]  Helmut Bölcskei,et al.  Space-Time Wireless Systems: From Array Processing to MIMO Communications , 2008 .

[26]  Zhan Guo,et al.  Algorithm and implementation of the K-best sphere decoding for MIMO detection , 2006, IEEE Journal on Selected Areas in Communications.

[27]  Wai Ho Mow,et al.  A VLSI architecture of a K-best lattice decoding algorithm for MIMO channels , 2002, 2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353).

[28]  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).

[29]  D. Garrett,et al.  19.2 Mbit/s 4 × 4 BLAST/MIMO detector with soft ML outputs , 2003 .

[30]  John B. Anderson,et al.  Instrumentable tree encoding of information sources (Corresp.) , 1971, IEEE Trans. Inf. Theory.

[31]  Graeme Woodward,et al.  A highly-parallel VLSI architecture for a list sphere detector , 2004, 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577).

[32]  Andreas Peter Burg,et al.  K-best MIMO detection VLSI architectures achieving up to 424 Mbps , 2006, 2006 IEEE International Symposium on Circuits and Systems.

[33]  Christian Schlegel,et al.  Trellis and turbo coding , 2004 .

[34]  John B. Anderson,et al.  Source and Channel Coding: An Algorithmic Approach , 1991 .

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

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

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

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

[39]  Markku J. Juntti,et al.  Implementation of a K-best based MIMO-OFDM detector algorithm , 2007, 2007 15th European Signal Processing Conference.

[40]  Babak Hassibi,et al.  On the sphere-decoding algorithm II. Generalizations, second-order statistics, and applications to communications , 2005, IEEE Transactions on Signal Processing.

[41]  Henk Corporaal A different approach to high performance computing , 1997, Proceedings Fourth International Conference on High-Performance Computing.