Browse > Article

Lattice Reduction Aided MIMO Detection using Seysen's Algorithm  

An, Hong-Sun (인하대학교 정보통신대학원 이동통신연구실)
Mohaisen, Manar (인하대학교 정보통신대학원 이동통신연구실)
Chang, Kyung-Hi (인하대학교 정보통신대학원 이동통신연구실)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.34, no.6C, 2009 , pp. 642-648 More about this Journal
Abstract
In this paper, we use SA (Seysen's Algorithm) instead of LLL (Lenstra-Lenstra-Lovasz) to perform LRA (Lattice Reduction-Aided) detection. By using SA, the complexity of lattice reduction is reduced and the detection performance is improved Although the performance is improved using SA, there still exists a gap in the performance between SA-LRA and ML detection. To reduce the performance difference, we apply list of candidates scheme to SA-LRA. The list of candidates scheme finds a list of candidates. Then, the candidate with the smallest squared Euclidean distance is considered as the estimate of the transmitted signal. Simulation results show that the SA-LRA detection learn to quasi-ML performance. Moreover, the efficiency of the SA is shown to highly improve the channel matrix conditionality.
Keywords
MIMO Detection; Lattice Reduction; LRA Detection; LLL Algorithm; Seysen's Algorithm; List of Candidates;
Citations & Related Records
연도 인용수 순위
  • Reference
1 D. Wubben, R. Bohnke, V. Kuhn, and K. D.Kammeyer, 'MMSE-Based Lattice Reduc- tionfor Near-ML Detection of MIMO Systems,' in Proc. ITG Workshop on Smart Antennas, March 2004
2 M. Seysen, 'Simultaneous Reduction of A Lattice Basis and Its Reciprocal Basis,' Combinatorica, vol.13, pp.363-376, 1993   DOI
3 J. Niu and I-Tai Lu, 'A New Lattice Reduction Based Receiver for MIMO Systems,' in Proc.of 41st CISS, March 2007
4 E. Agrell, T. Eriksson, A. Vardy, K. Zeger,'Closest point search in lattice,' IEEE Trans.on Information Theory, vol.48, No.8, pp.2201-2214, August 2002   DOI   ScienceOn
5 C. Windpassinger, L. H.-J. Lampe, R. F. H.Fischer, 'From Lattice-Reduction-Aided DetectionTowards Maximum-Likelihood Detection in MIMO Systems,' in Proc. Int. Conf. Wireless Opt. Commun., July 2003
6 S. Haykin and M. Moher, Modern Wireless Communications. Pearson Prentice Hall, NewJersey, 2005
7 H. Yao and G. W. Wornell, 'Lattice Reduction Aided Detectors for MIMO Com- munication Systems,' in IEEE Proc. Globecom, November 2002
8 C. Windpassinger and R. F. H. Fischer, 'Low Complexity Near-Maximum-Likelihood Detectionand Pre-coding for MIMO Systems using Lattice Reduction,' in IEEE Proc. ITW, March 2003
9 D. Wubben, R. Bohnke, V. Kuhn, and K. D.Kammeyer, 'MMSE Extension of V-BLAST based on Sorted QR Decomposition,' in IEEE Proc. VTC-Fall, October 2003
10 A. K. Lenstra, H. W. Lenstra, and L. Lovasz,'Factoring Polynomials with RationalCoefficients,' Math. Ann, vol.261, pp.515-534,1982   DOI
11 K. Su, Efficient Maximum Likelihood Detectionfor Communication over Multiple Input MultipleOutput Channels. Doctoral Dissertation,University of Cambridge, 2005
12 B. A. Lamacchia, Basis Reduction Algorithmsand Subset Sum Problems. Master Thesis, MIT, 1991
13 T. D. Nguyen, T. Fujino, and X. N. Tran, 'AnImproved Quantization Scheme for Lattice-Reduction Aided MIMO Detection,' in IEEE Proc. ISCIT, October 2007