An Interleaver Estimation Algorithm for Turbo-code Based on Conformity of Parity-Check Equation

Tao, Jinghe; Diao, Ming; Chen, Zengmao

doi:10.1109/apcap.2018.8538311

Cited by 1 publication

(1 citation statement)

References 12 publications

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“…Therefore, RSC code is an important component of turbo code. RSC code parameter identification is the premise of interleaver identification and an important part of Turbo code parameter identification [2][3][4][5] .…”

Section: Introductionmentioning

confidence: 99%

Blind recognition of RSC based on binary artificial bee colony algorithm

WANG¹,

Zhang²,

Wang³

et al. 2023

Second International Conference on Electronic Information Engineering and Computer Communication (EIECC 2022)

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In order to overcome the shortcomings of poor fault tolerance and complicated computation in blind identification of recursive systematic convolutional (RSC) codes, a blind identification method based on binary artificial bee colony algorithm is proposed. Firstly, according to the structure of RSC encoder, the product vector of output bit matrix and the coded polynomial vector is obtained. Then, the artificial bee colony algorithm for continuous decision variables is modified to be suitable for binary optimization problems, and the sum of the elements of the product vector is used as the fitness function of the binary artificial bee colony algorithm to optimize the coefficient vector of coded polynomial. Finally, the termination conditions of the algorithm are set according to the fitness value and the number of iterations. Furthermore, the termination condition of the algorithm is improved according to the characteristics of the coding polynomial. Thus, the RSC coded polynomial can be identified while the computation is reduced. The experimental results show that the algorithm can recognize RSC coded polynomials effectively, and the correct rate of recognition is over 98% for coded polynomials with different coding constraints when the bit error rate reaches 0.05.

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Section: Introductionmentioning

confidence: 99%