一种基于遗传算法的RSC码盲识别方法

doi:10.7527/S1000-6893.2017.321246

Abstract

Abstract:

To address the problems of poor performance and heavy computation in blind identification of Recursive Systematic Convolutional (RSC) code, a new algorithm for blind identification of RSC polynomial parameters is proposed based on the genetic algorithm. Considering the special structure of RSC code, the identification model is constructed based on the genetic algorithm. The weight of the result vector is used as fitness function, and the theoretical value of the average code weight is derived at different Bit Error Rates, as the results. The optimal threshold is then obtained. The performance of the proposed algorithm is good, and the maximum amount of calculation is only proportional to the initial population size, genetic generations, and paths of outputs. The simulation results show that the theoretical derivation of the code weight is in good agreement with the simulation results, and the recognition rate of the RSC code is close to 0.9 at different number of registers when the Bit Error Rate is up to 0.06.

Key words: Recursive Systematic Convolutional (RSC) code, genetic algorithm, fitness function, optimal threshold, blind identification

CLC Number:

ZHANG Limin, WU Zhaojun, ZHONG Zhaogen. Blind identification of RSC code based on genetic algorithm[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2017, 38(11): 321246-321246.

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Blind identification of RSC code based on genetic algorithm

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