An Efficient ADMM-Based Penalized Decoding Algorithm for Binary LDPC Code

LDPC decoding algorithm based on the alternating direction method of multipliers (ADMM) technique has increased much attentions because of its outstanding decoding performance. To enhancing performance advantages of ADMM decoding in practical application, a main challenge is to design an efficient penalty function and then customize an accelerating decoding algorithm. To address this issue, in this paper we propose an improved penalized decoding problem based on a segmented penalty function (SPF), and then develop an efficient ADMM algorithm via optimizing variable updating to solve this SPF-based decoding model. Experimental simulations demonstrate that the proposed algorithm effectively reduces the number of iterations while achieving better error-correction performance, when compared to the state-of-the-art ADMM-based decoding algorithms.