Multi-User Detection using Support Vector Machines 


Vol. 34,  No. 12, pp. 1177-1183, Dec.  2009


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  Abstract

In this paper, support vector machines (SVM) are applied to multi-user detector (MUD) for direct sequence (DS)-CDMA system. This work shows an analytical performance of SVM based multi-user detector with some of kernel functions, such as linear, sigmoid, and Gaussian. The basic idea in SVM based training is to select the proper number of support vectors by maximizing the margin between two different classes. In simulation studies, the performance of SVM based MUD with different kernel functions is compared in terms of the number of selected support vectors, their corresponding decision boundary, and finally the bit error rate. It was found that controlling parameter  , in SVM training have an effect, in some degree, to SVM based MUD with both sigmoid and Gaussian kernel. It is shown that SVM based MUD with Gaussian kernels outperforms those with other kernels.

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  Cite this article

[IEEE Style]

J. Lee, J. Lee, J. Hwang, K. Chung, "Multi-User Detection using Support Vector Machines," The Journal of Korean Institute of Communications and Information Sciences, vol. 34, no. 12, pp. 1177-1183, 2009. DOI: .

[ACM Style]

Jung-Sik Lee, Jae-Wan Lee, Jae-Jeong Hwang, and Kyung-Taek Chung. 2009. Multi-User Detection using Support Vector Machines. The Journal of Korean Institute of Communications and Information Sciences, 34, 12, (2009), 1177-1183. DOI: .

[KICS Style]

Jung-Sik Lee, Jae-Wan Lee, Jae-Jeong Hwang, Kyung-Taek Chung, "Multi-User Detection using Support Vector Machines," The Journal of Korean Institute of Communications and Information Sciences, vol. 34, no. 12, pp. 1177-1183, 12. 2009.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880