Return
Improved Free-of-CPP ADMM-Based Iterative Decoding Algorithm of Binary LDPC Codes
DOI:10.1109/LSP.2024.3511336.png)
Abstract
En 中文
Iterative decoding algorithms based on the alternating direction method of multipliers (ADMM) decoding of low density parity check (LDPC) codes has emerged as an alternating decoding method and bringed a boom of research on drawing upon mathematical optimization to LDPC decoding. Improving error-correcting performance is a key issue to enhance the superiority of ADMM decoding. In this letter, we investigate an efficient ADMM-based iterative decoder for binary LDPC codes. First, we build an mathematical programming equivalence of the maximum likelihood (ML) decoding problem by transforming parity-check constraints to multiple equivalent linear constraints and eliminating check-polytope projection (CPP). Then, an iterative algorithm based on ADMM technique is developed to solve this free-of-CPP (FCPP) equivalence and each ADMM update can be computed efficiently. Moreover, the proposed ADMM-FCPP decoding algorithm is analyzed to display a linear complexity to the length of the LDPC code at each iteration. Finally, simulation results demonstrate the superiority of the proposed decoder in error-correcting performance compared with the state-of-the-art ADMM-based decoders.
Keywords:
Maximum likelihood decoding
Iterative decoding
Convex functions
Vectors
Signal processing algorithms
Optimization
Complexity theory
Simulation
Programming profession
Low-density parity-check (LDPC) codes
alternating direction method of multipliers (ADMM)
check- polytope projection (CPP)
mathematical programming
mathematical programming
Journal
IF:
9.6
Papers:
1.1W
Citations:
1.7W

