This letter presents an RS-SPC concatenated code blindrecognition algorithm based on the single-error correction. The algorithm corrects the least reliable bit of the single parity check (SPC) codewords based on the parity check characteristics, thereby increasing correct Reed-Solomon (RS) codewords and laying the foundation for improving the recognition probability. In addition, this algorithm combines threshold judgement with the matrix recording method, thereby eliminating unnecessary iterative operations under the condition that accurate recognition is possible. At the same time, it employs probability theory as a theoretical basis to quantify the degree of dispersion of the data through sample variance. The experimental results demonstrate that the recognition probability of this algorithm is superior to that of all other algorithms. When the codeword error rate (CER) is 0.5, RS(15,9)-SPC(4,3) still has a recognition probability of 20%. For RS(255,239)-SPC(8,7), the gain of the proposed algorithm exceeds 1.3dB compared to the upper bound of the recognition probability.

This paper proposes a full-blind recognition method that aims to recognize coding parameters from a noisy bitstream of limited BCH and RS codes intercepted in a non-cooperative communication system under harsh channel environments. This paper optimizes the codeword reliability calculation by fully utilizing channel soft information, based on which the single-bit error codewords can be effectively selected from the codeword stream with a high probability. Subsequently, the channel soft information-based single-error correction (CSI-SEC) algorithm is proposed for correcting single-bit error codewords. The blind recognition algorithm, based on the Galois domain Fourier transform (GFFT) with a dual decision-making mechanism, is applied to these corrected codewords and reliable codewords to extract the encoding parameters. Finally, the method’s superiority is demonstrated through comprehensive simulation experiments. Compared to other blind recognition methods based on error correction, the proposed method exhibits enhanced recognition performance, with a cumulative computational complexity of only 39.8% of that of the other methods. Compared to other algorithms for blind recognition of limited intercepted bitstream, the proposed method achieves at least a 3 dB improvement in recognition performance.