상세정보
학술지
Fast Soft Decision Decoding Algorithm for Linear Block Codes Using Permuted Generator Matrices
- 저자
- 최창열, 정제창
- 발행일
- 202112
- 출처
- IEEE Communications Letters, v.25 no.12, pp.3775-3779
- ISSN
- 1089-7798
- 출판사
- IEEE
- 협약과제
- 20HH2900, 셀룰러 기반 산업 자동화 시스템 구축을 위한 5G 성능 한계 극복 저지연, 고신뢰, 초연결 통합 핵심기술 개발, 신재승
- 초록
- The Gaussian elimination algorithm is an essential part of the ordered statistics-based decoding (OSD); the algorithm is required to be executed at least once for a typical OSD algorithm, with its computational complexity serving as the lower bound of the total computational complexity. When the signal-to-noise ratio (SNR) is relatively low, the computational complexity of the Gaussian elimination algorithm can be ignored as the decoding process is relatively complex. However, with an increase in the SNR, this cannot be ignored. In this letter, we propose a fast soft decision decoding algorithm using templates that are precalculated and permuted generator matrices, enabling us to decode a received vector without having to perform the OSD algorithm. In particular, if the Hamming distance between the received vector and the candidate codeword generated by one of the templates is less than a certain threshold, we can terminate the decoding process without executing the typical OSD algorithm. This aids in reducing the computational complexity in high SNR regimes without compromising the decoding performance.
- KSP 제안 키워드
- Computational complexity, Gaussian Elimination, Hamming Distance, Linear Block Codes, Lower bound, Ordered Statistics, Signal noise ratio(SNR), Signal-to-Noise, decoding algorithm, decoding performance, elimination algorithm