Performance of the Recursive Systematic Convolutional Code with Turbo-Equalization Method for PMR Channel 


Vol. 34,  No. 1, pp. 15-20, Jan.  2009


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  Abstract

For perpendicular magnetic recording (PMR) channels, noise-predictive maximum likelihood (NPML) detection method has been used. But, it is hard to expect improving the performance when the bit density is increased. Hence, we exploit the coding methods which has good performance. In this paper, we show the performance of the recursive systematic convolutional (RSC) codes with turbo-equalization method with different channel bit densities. The noise model is 80% jitter noise and 20% AWGN.

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  Cite this article

[IEEE Style]

D. Park and J. Lee, "Performance of the Recursive Systematic Convolutional Code with Turbo-Equalization Method for PMR Channel," The Journal of Korean Institute of Communications and Information Sciences, vol. 34, no. 1, pp. 15-20, 2009. DOI: .

[ACM Style]

Donghyuk Park and Jaejin Lee. 2009. Performance of the Recursive Systematic Convolutional Code with Turbo-Equalization Method for PMR Channel. The Journal of Korean Institute of Communications and Information Sciences, 34, 1, (2009), 15-20. DOI: .

[KICS Style]

Donghyuk Park and Jaejin Lee, "Performance of the Recursive Systematic Convolutional Code with Turbo-Equalization Method for PMR Channel," The Journal of Korean Institute of Communications and Information Sciences, vol. 34, no. 1, pp. 15-20, 1. 2009.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880