Parameter Estimation of RSC Turbo Codes with Full Search 


Vol. 45,  No. 3, pp. 537-545, Mar.  2020
10.7840/kics.2020.45.3.537


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  Abstract

A full search scheme for the blind RSC parameter estimation of a turbo encoder is proposed and its performance is explored by simulations over the AWGN channels. The constraint length of RSC encoder dictates the search space and, hence, the complexity of the full search scheme. Most commercial standards have turbo encoders with RSC sub-encoders with relatively short constraint length in comparison to non-systematic convolutional codes and the full search is a practical solution. It is shown that the search space can be further reduced using some properties of legitimate RSC encoders. Our simulation results for 3GPP UMTS scenario showed that the proposed full search scheme has about 2.5dB SNR gain over the wide range of SNR values when operating over AWGN channel, in comparison to the best scheme reported in the literature previously. In terms of the detection error rate, the previous scheme resulted in 65% at the channel SNR of 0dB, while the proposed scheme results in 0.6%. The corresponding complexity of our scheme was about 70% when compared to that of the previous scheme.

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  Cite this article

[IEEE Style]

S. Ko, J. Kim, S. Kim, B. Choi, "Parameter Estimation of RSC Turbo Codes with Full Search," The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 3, pp. 537-545, 2020. DOI: 10.7840/kics.2020.45.3.537.

[ACM Style]

Seon-Jae Ko, Jae-Yun Kim, Seon-Kyo Kim, and Byoung-Jo Choi. 2020. Parameter Estimation of RSC Turbo Codes with Full Search. The Journal of Korean Institute of Communications and Information Sciences, 45, 3, (2020), 537-545. DOI: 10.7840/kics.2020.45.3.537.

[KICS Style]

Seon-Jae Ko, Jae-Yun Kim, Seon-Kyo Kim, Byoung-Jo Choi, "Parameter Estimation of RSC Turbo Codes with Full Search," The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 3, pp. 537-545, 3. 2020. (https://doi.org/10.7840/kics.2020.45.3.537)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880