Partition-Based Hybrid MIMO Decoding Schemes with Combined Depth- and Breath-First Search

Abstract:

In this paper, we propose a novel maximum likelihood (ML) decoding scheme based on the combination of depth- and breadth-first search methods on a partitioned tree for multiple input multiple output systems. The proposed scheme first partitions the searching tree into several stages, each of which is then searched by a depth- or breadth-first search method, possibly exploiting the advantages of both the depth- and breadth-first search methods in an organized way. Numerical results indicate that, when the depth- and breadth-first search algorithms are adopted appropriately, the proposed scheme exhibits substantially lower computational complexity than conventional ML decoders while maintaining the ML bit error performance.

• Periodical: Applied Mechanics and Materials (Volumes 284-287)
• Pages: 2652-2656
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.284-287.2652
• Online since: January 2013
• Authors: Jong In Park, Young Po Lee, Seok Ho Yoon
• Keywords: Hybrid Decoding, Maximum Likelihood Detection, Multiple Input Multiple Output (MIMO), Tree Partitioning

References

[1] K. Higuchi; H. Kawai; N. Maeda; H. Taoka and M. Sawahashi: IEEE J. Sel. Areas Commun. Vol. 24 (2006), pp.1141-1153.

DOI: 10.1109/jsac.2005.864026

[2] B. Hochwald and S.T. Brink: IEEE Tr. Commun. Vol. 51 (2003), pp.389-399.

[3] J. Jaldén and B. Ottersten: IEEE Tr. Signal Process. Vol. 53 (2005), pp.1474-1484.

[4] H.G. Kang; I. Song; J. Oh; J. Lee and S. Yoon: IEEE Tr. Vehic. Techn. Vol. 57 (2008).

[5] G.H. Golub and C.F.V. Loan: Matrix Computations (Johns Hopkins University Press, United States 1996).

[6] A.D. Murugan; H.E. Gamal; M.O. Damen and G. Caire: IEEE Tr. Inform. Theory Vol. 52 (2006), pp.933-953.

DOI: 10.1109/tit.2005.864418