Self-Adaptive Termination Check of Min-Sum Algorithm for LDPC Decoders Using the First Two Minima
- Authors
- Cho, Keol; Chung, Ki-Seok
- Issue Date
- Apr-2017
- Publisher
- 한국인터넷정보학회
- Keywords
- Low-density parity-check codes; LDPC decoder; min-sum algorithm; adaptive min-sum decoding; error correction codes
- Citation
- KSII Transactions on Internet and Information Systems, v.11, no.4, pp 1987 - 2001
- Pages
- 15
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- KSII Transactions on Internet and Information Systems
- Volume
- 11
- Number
- 4
- Start Page
- 1987
- End Page
- 2001
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/20462
- DOI
- 10.3837/tiis.2017.04.009
- ISSN
- 1976-7277
1976-7277
- Abstract
- Low-density parity-check (LDPC) codes have attracted a great attention because of their excellent error correction capability with reasonably low decoding complexity. Among decoding algorithms for LDPC codes, the min-sum (MS) algorithm and its modified versions have been widely adopted due to their high efficiency in hardware implementation. In this paper, a self-adaptive MS algorithm using the difference of the first two minima is proposed for faster decoding speed and lower power consumption. Finding the first two minima is an important operation when MS-based LDPC decoders are implemented in hardware, and the found minima are often compressed using the difference of the two values to reduce interconnection complexity and memory usage. It is found that, when these difference values are bounded, decoding is not successfully terminated. Thus, the proposed method dynamically decides whether the termination-checking step will be carried out based on the difference in the two found minima. The simulation results show that the decoding speed is improved by 7%, and the power consumption is reduced by 16.34% by skipping unnecessary steps in the unsuccessful iteration without any loss in error correction performance. In addition, the synthesis results show that the hardware overhead for the proposed method is negligible.
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