Low-Complexity Soft-MIMO Detection Algorithm Based on Ordered Parallel Tree-Search Using Efficient Node Insertion 


Vol. 37,  No. 10, pp. 841-849, Oct.  2012


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  Abstract

This paper proposes an low-complexity soft-output multiple-input multiple-output (soft-MIMO) detection algorithm for achieving soft-output maximum-likelihood (soft-ML) performance under max-log approximation. The proposed algorithm is based on a parallel tree-search (PTS) applying a channel ordering by a sorted-QR decomposition (SQRD)　with altered sort order. The empty-set problem that can occur in calculation of log-likelihood ratio (LLR) for each bit is solved by inserting additional nodes at each search level. Since only the closest node is inserted among nodes with opposite bit value to a selected node, the proposed node insertion scheme is very efficient in the perspective of computational complexity. The computational complexity of the proposed algorithm is approximately 37?74% of that of existing algorithms, and from simulation results for a 4×4 system, the proposed algorithm shows a performance degradation of less than 0.1dB.

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  Cite this article

[IEEE Style]

K. Kim, J. Park, J. Kim, "Low-Complexity Soft-MIMO Detection Algorithm Based on Ordered Parallel Tree-Search Using Efficient Node Insertion," The Journal of Korean Institute of Communications and Information Sciences, vol. 37, no. 10, pp. 841-849, 2012. DOI: .

[ACM Style]

Kilhwan Kim, Jangyong Park, and Jaeseok Kim. 2012. Low-Complexity Soft-MIMO Detection Algorithm Based on Ordered Parallel Tree-Search Using Efficient Node Insertion. The Journal of Korean Institute of Communications and Information Sciences, 37, 10, (2012), 841-849. DOI: .

[KICS Style]

Kilhwan Kim, Jangyong Park, Jaeseok Kim, "Low-Complexity Soft-MIMO Detection Algorithm Based on Ordered Parallel Tree-Search Using Efficient Node Insertion," The Journal of Korean Institute of Communications and Information Sciences, vol. 37, no. 10, pp. 841-849, 10. 2012.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880