2017/07/14 by Hossein Mani, Mani, Hossein, Saied Hemati +1
Computer Science · #Cellular Automata and Applications #Coding theory and cryptography #Error Correcting Code Techniques #FOS: Computer and information sciences #Information Theory (cs.IT)
paper · pdf · doi:10.48550/arxiv.1707.04390
openalex publication_date 2017/07/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper proposes the Symbolic-Stochastic Chase Decoding Algorithm (S-SCA) for the Reed-Solomon (RS) and BCH codes. By efficient usage of void space between constellation points for q-ary modulations and using soft information at the input of the decoder, the S-SCA is capable of outperforming conventional Symbolic-Chase algorithm (S-CA) with less computational cost. Since the S-SCA starts with the randomized generation of likely test-vectors, it reduces the complexity to polynomial order and also it does not need to find the least reliable symbols to generate test-vectors. Our simulation results show that by increasing the number of test-vectors, the performance of the algorithm can approach the ML bound. The S-SCA(1K) provides near 2 dB gain in comparison with S-CA(1K) for (31, 25) RS code using 32-QAM. Furthermore, the algorithm provides near 3 dB further gain with 1K iteration compared with S-CA(65K) when (255, 239) RS code is used in an AWGN channel. For the Rayleigh fading channel and the same code, the algorithm provides more that 5 dB gain. Also for (63, 57) BCH codes and 8-PSK modulation the proposed algorithm provides 3dB gain with less complexity. This decoder is Soft-Input Soft-Output (SISO) decoder and is highly attractive in low power applications. Finally, the Symbolic-Search Bitwise-Transmission Stochastic Chase Algorithm (SSBT-SCA) was introduced for RS codes over BPSK transmission that is capable of generating symbolic test-vectors that reduce complexity and mitigate burst errors.