An Adaptive K-best Algorithm Based on Path Metric Comparison for MIMO Systems 


Vol. 32,  No. 11, pp. 1197-1205, Nov.  2007


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  Abstract

An adaptive K-best detection scheme is proposed for MIMO systems. The proposed scheme changes the number of survivor paths, K based on the degree of the reliability of Zero-Forcing (ZF) estimates at each K-best step. The critical drawback of the fixed K-best detection is that the correct path’s metric may be temporarily larger than K minimum paths metrics due to imperfect interference cancellation by the incorrect ZF estimates. Based on the observation that there are insignificant differences among path metrics (ML distances) when the ZF estimates are incorrect, we use the ratio of the minimum ML distance to the second minimum as a reliability indicator for the ZF estimates. So, we adaptively select the value of K according to the ML distance ratio. It is shown that the proposed scheme achieves the significant improvement over the conventional fixed K-best scheme. The proposed scheme effectively achieves the performance of large K-best system while maintaining the overall average computation complexity much smaller than that of large K system.

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  Cite this article

[IEEE Style]

B. Kim and K. Choi, "An Adaptive K-best Algorithm Based on Path Metric Comparison for MIMO Systems," The Journal of Korean Institute of Communications and Information Sciences, vol. 32, no. 11, pp. 1197-1205, 2007. DOI: .

[ACM Style]

Bong-seok Kim and Kwonhue Choi. 2007. An Adaptive K-best Algorithm Based on Path Metric Comparison for MIMO Systems. The Journal of Korean Institute of Communications and Information Sciences, 32, 11, (2007), 1197-1205. DOI: .

[KICS Style]

Bong-seok Kim and Kwonhue Choi, "An Adaptive K-best Algorithm Based on Path Metric Comparison for MIMO Systems," The Journal of Korean Institute of Communications and Information Sciences, vol. 32, no. 11, pp. 1197-1205, 11. 2007.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880