Blind Recognition of Turbo Product Codes in Soft Decision Situations

In this paper a method of blind recognition of the coding parameters for binary turbo product codes is proposed. The only knowledge is that the stream is encoded using binary product codes, while the coding parameters are unknown. The recognition processing includes two major procedures: code word length estimation and generator polynomial reconstruction. A hard decision method has been proposed in a previous literature. In this paper we propose the recognition approach in soft decisions situations with Binary-Phase-Shift-Key (BPSK) modulations and Additive-White-Gaussian-Noise (AWGN) channels. The code word length is estimated by maximizing the root information dispersion entropy function (RIDEF) for two dimension of the bit stream. And then we search for the code roots to reconstruct the primitive and generator polynomials. By utilizing the soft output of the channel, the recognition performance is improved and simulations show the efficiency of the proposed algorithm.