Complex-Channel Blind Equalization using Euclidean Distance Algorithms with a Self-generated Symbol Set and Kernel Size Modification 


Vol. 36,  No. 1, pp. 35-40, Jan.  2011


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  Abstract

The complex-valued blind algorithm based on a set of randomly generated symbols and Euclidean distance can take advantage of information theoretic learning and cope with the channel phase rotation problems. On the algorithm, in this paper, the effect of kernel size has been studied and a kernel-modified version of the algorithm that rearranges the forces between the information potentials by kernel-modification has been proposed. In simulation results for 16 QAM and complex-channel models, the proposed algorithm show significantly enhanced performance of symbol-point concentration and no phase rotation problems caused by the complex channel models.

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  Cite this article

[IEEE Style]

N. Kim, "Complex-Channel Blind Equalization using Euclidean Distance Algorithms with a Self-generated Symbol Set and Kernel Size Modification," The Journal of Korean Institute of Communications and Information Sciences, vol. 36, no. 1, pp. 35-40, 2011. DOI: .

[ACM Style]

Namyong Kim. 2011. Complex-Channel Blind Equalization using Euclidean Distance Algorithms with a Self-generated Symbol Set and Kernel Size Modification. The Journal of Korean Institute of Communications and Information Sciences, 36, 1, (2011), 35-40. DOI: .

[KICS Style]

Namyong Kim, "Complex-Channel Blind Equalization using Euclidean Distance Algorithms with a Self-generated Symbol Set and Kernel Size Modification," The Journal of Korean Institute of Communications and Information Sciences, vol. 36, no. 1, pp. 35-40, 1. 2011.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880