Improving the Reliability of the K-Best algorithm for MIMO detection with ordering

It is well known that the order of the channel matrix columns has significant impact on a MIMO detector's performance in terms of the computational complexity, memory requirement, and/or the detection error rate. In our previous work, novel ordering schemes have been proposed to reduce the computational complexities and/or memory requirements of various maximum likelihood (ML) MIMO detectors. In this paper, we incorporate our ordering schemes with the K-Best detector, which is a near-ML detector and is particularly suitable for hardware implementation. Our simulation results show that our ordering schemes greatly improve the reliability of the K-Best detector. Given a fixed detection error rate, our ordering schemes either result in SNR gains or enable the usage of even smaller K, thereby leading to small area and power consumption and higher throughput for their hardware implementations.

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

[2]  Zhongding Lei,et al.  A low complexity near ML V-BLAST algorithm , 2005, VTC-2005-Fall. 2005 IEEE 62nd Vehicular Technology Conference, 2005..

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

[4]  K. Kammeyer,et al.  Efficient algorithm for decoding layered space-time codes , 2001 .

[5]  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).

[6]  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).

[7]  Jing Wang,et al.  A computationally efficient exact ML sphere decoder , 2004, IEEE Global Telecommunications Conference, 2004. GLOBECOM '04..

[8]  Ian J. Wassell,et al.  A new ordering for efficient sphere decoding , 2005, IEEE International Conference on Communications, 2005. ICC 2005. 2005.

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

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

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

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

[14]  Zhiyuan Yan,et al.  Memory-Constrained Tree Search Detection and New Ordering Schemes , 2009, IEEE Journal of Selected Topics in Signal Processing.

[15]  Zhiyuan Yan,et al.  Memory-constrained ML-optimal tree search detection , 2008, 2008 42nd Annual Conference on Information Sciences and Systems.