Adaptive K-best Sphere Decoding Algorithm Using the Characteristics of Path Metric 


Vol. 34,  No. 11, pp. 862-869, Nov.  2009


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  Abstract

We propose a new adaptive K-best Sphere Decoding (SD) algorithm for Multiple Input Multiple Output (MIMO) systems where the number of survivor paths, K is changed based on the characteristics of path metrics which contain the instantaneous channel condition. In order to overcome a major drawback of Maximum Likelihood Detection (MLD) which exponentially increases the computational complexity with the number of transmit antennas, the conventional adaptive K-best SD algorithms which achieve near to MLD performance have been proposed. However, they still have redundant computation complexity since they only employ the channel fading gain as a channel condition indicator without instantaneous Signal to Noise Ratio (SNR) information. In order to complement this drawback, the proposed algorithm use the characteristics of path metrics as a simple channel indicator. It is found that the ratio of the minimum path metric to the other path metrics reflects SNR information as well as channel fading gain. By adaptively changing K based on this ratio, the proposed algorithm more effectively reduce the computation complexity compared to the conventional K-best algorithms which achieve same performance.

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  Cite this article

[IEEE Style]

B. Kim and K. Choi, "Adaptive K-best Sphere Decoding Algorithm Using the Characteristics of Path Metric," The Journal of Korean Institute of Communications and Information Sciences, vol. 34, no. 11, pp. 862-869, 2009. DOI: .

[ACM Style]

Bong-seok Kim and Kwonhue Choi. 2009. Adaptive K-best Sphere Decoding Algorithm Using the Characteristics of Path Metric. The Journal of Korean Institute of Communications and Information Sciences, 34, 11, (2009), 862-869. DOI: .

[KICS Style]

Bong-seok Kim and Kwonhue Choi, "Adaptive K-best Sphere Decoding Algorithm Using the Characteristics of Path Metric," The Journal of Korean Institute of Communications and Information Sciences, vol. 34, no. 11, pp. 862-869, 11. 2009.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880