ABSTRACT
Tree search detection algorithms can provide Maximum-Likelihood detection over Gaussian MIMO channels with lower complexity than the exhaustive search. Furthermore, the performance of MIMO detectors is highly influenced by the channel matrix condition number. In this paper, the impact of the 2-norm condition number in data detection is exploited in order to decrease the complexity of already proposed algorithms. A suboptimal tree search method called K-Best is combined with a channel matrix condition number estimator and a threshold selection method. This approach leads to a variable-breadth K-Best detector with predictable average performance and suitable for hardware implementation. The results show that the proposed scheme has lower complexity, i.e. it is less power consuming, than a fixed K-Best detector of similar performance.
- H. Artes, D. Seethaler, and F. Hlawatsch. Efficient detection algorithms for MIMO channels: A geometrical approach to approximate ML detection. IEEE Trans. on Signal Processing, 51(11):2808--2820, November 2003. Google ScholarDigital Library
- L. G. Barbero and J. S. Thompson. Fixing the complexity of the sphere decoder for MIMO detection. IEEE Trans. on Wireless Communications, 7(6):2131--2142, June 2008. Google ScholarDigital Library
- A. K. Cline, C. B. Moler, G. W. Stewart, and J. H. Wilkinson. An estimate for the condition number of a matrix. SIAM Journal on Numerical Analysis, 16(2):368--375, April 1979.Google ScholarCross Ref
- A. Edelman. Eigenvalues and Condition Numbers of Random Matrices. Ph.d. thesis, Massachusetts Institute of Technology, Cambridge (MA), 1989.Google Scholar
- G. Golub and C. V. Loan. Matrix Computations. The Johns Hopkins University Press, Baltimore, 1996. Google ScholarDigital Library
- Z. Guo and P. Nilsson. Algorithm and implementation of the K-Best Sphere Decoding for MIMO Detection. IEEE Journal on Selected Areas in Communications, 24(3):491--503, March 2006. Google ScholarDigital Library
- B. Hassibi and H. Vikalo. On Sphere Decoding algorithm. Part I, the expected complexity. IEEE Trans. on Signal Processing, 54(5):2806--2818, August 2005. Google ScholarDigital Library
- J. Janhunen, O. Silvén, and M. Juntti. Programmable processor implementations of K-best list sphere detector for MIMO receiver. Signal Processing, 90(1):313--323, January 2010. Google ScholarDigital Library
- E. G. Larsson. MIMO detection methods: How they work. IEEE Signal Processing Magazine, 26(3):91--95, May 2009.Google ScholarCross Ref
- J. Maurer, G. Matz, and D. Seethaler. Low-complexity and full-diversity MIMO detection based on condition number thresholding. In ICASSP'07, Honolulu, Hawaii, USA, April 2007.Google ScholarCross Ref
- A. J. Paulraj, D. A. Gore, R. U. Nabar, and H. Bölcskei. An overview of MIMO communications - a key to gigabit wireless. Proceedings of the IEEE, 92(2):198--218, 2004.Google ScholarCross Ref
- S. Roger, A. Gonzalez, V. Almenar, and A. M. Vidal. Combined K-Best Sphere Decoder based on the channel matrix condition number. In ISCCSP'08, St. Julians, Malta, March 2008.Google ScholarCross Ref
- C. Studer, A. Burg, and H. Bölcksei. Soft-output sphere decoding: Algorithms and VLSI implementation. IEEE Journal on Selected Areas in Communications, 26(2):290--300, February 2008. Google ScholarDigital Library
- M. Wenk, M. Zellweger, A. Burg, N. Felber, and W. Fichtner. K-best MIMO detection VLSI architectures achieving up to 424 Mbps. In ISCAS'06, Island of Kos, Greece, May 2006.Google ScholarCross Ref
Index Terms
- Variable-breadth K-best detector for MIMO systems
Recommendations
Adaptive multiple stage K-best successive interference cancellation algorithm for MIMO detection
In this article, we propose an adaptive multiple stage K-best successive interference cancellation (AMS-KSIC) algorithm for symbol vector detection in multiple-input multiple-output systems. The proposed algorithm employs multiple successive ...
MIMO Detector for LTE/LTE-A Uplink Receiver
We propose a carefully selected receiver structure, detector and detector implementation architecture for multiple-input multiple-output (MIMO) uplink base station receiver for fourth generation (4G) wireless cellular systems. First, we compare ...
Reconfigurable K-best algorithm for MIMO detection systems
ICICS'09: Proceedings of the 7th international conference on Information, communications and signal processingThe maximum likelihood (ML) detection is the optimal detection method for multiple-input multiple-output (MIMO) communication systems. The normal K-best Sphere Decoding Algorithm (SDA) can guarantee a fixed throughput, but it induces a large bit error ...
Comments