A new adaptive two-stage maximum-likelihood decoding algorithm for linear block codes

• Published in: 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577) Vol. 2; pp. 656 - 660 Vol.2
• Main Authors: Xianren Wu, Sadjadpour, H.R., Zhi Tian
• Format: Conference Proceeding
• Language: English
• Published: Piscataway, New Jersey IEEE 2004
• Subjects: Applied sciences; Block codes; Coding, codes; Computational complexity; Conferences; Degradation; Error analysis; Exact sciences and technology; Information, signal and communications theory; Iterative decoding; Maximum likelihood decoding; Maximum likelihood estimation; Signal and communications theory; Statistics; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Testing; Turbo codes; Performance evaluation; Block code; Second order; Multistage method; Optimal algorithm; Turbo code; Computational complexity; Block error rate; Maximum likelihood decoding; Degradation; Linear code; Algorithm performance; Simulation; Optimal solution; Algorithm complexity
• ISBN: 0780385330; 9780780385337
• DOI: 10.1109/ICC.2004.1312583

This work presents a maximum-likelihood (ML) decoding algorithm for linear block codes. In this algorithm, the optimal performance is achieved at low computational complexity through a two-stage processing. At the first stage, a minimum sufficient set S that includes the optimal solution is estimated. With the minimum sufficient set, the decoding complexity can be greatly reduced without performance degradation. At the second stage, ordered processing is performed within the estimated minimum sufficient set S to obtain the optimal solution. During the ordered processing, S is adoptively updated to minimize the computational complexity, and an effective stopping criterion is used to decide whether the optimal solution is found. Ordered processing not only helps to find the optimal solution quickly, but also enables simplified sub-optimal solutions with bounded block error rates. The proposed algorithm is also extended to decode block turbo codes. Finally, simulation results are given to show that this algorithm achieves optimal performance with a low average computational complexity.