关键词: RSC码, 双曲正切符合度, 变步长, 梯度上升法, 识别

Abstract: In order to solve the defects which are poor error tolerance and large amount of calculation in current algorithms in recognition of the RSC encoder, a fast iterative recognition algorithm which has excellent performance was proposed. Firstly, according to the linear constraint relation between RSC symbols, the concept of hyperbolic tangent conformation was defined; this can measure the possibility of the linear relationship between the symbols under a certain polynomial parameter. Secondly, the total hyperbolic tangent coincidence value of the intercepted symbol was used as a cost function, and then the probability value of the polynomial parameters were regarded as the cost function independent variable and the problem of RSC code identification was transformed into the maximum value of the multivariate function. Finally, the variable step gradient method was used to solve the maximum value of the cost function in the continuous probability space at the finite iteration. The proposed algorithm has a fast and stable convergence speed. In addition to the strong adaptive ability of low SNR, the computational complexity increases squarely with the number of encoder registers and the number of symbols. The simulation experiment showed that the proposed algorithm could achieve the convergence of the parameters at most fifth iterations, while have strong ability to suit to the low SNR. Even the SNR is 0dB, the correct identification rate of RSC code can reach more than 90%. Compared with the existing algorithm, the proposed algorithm improved the adaptive capacity of low SNR by nearly 3dB, at the same time,the time consuming is greatly reduced.

Key words: recursive systematic convolutional (RSC) codes, hyperbolic tangent conformation, variable step size, gradient ascent method, recognition