Simplified variable-scaled min sum LDPC decoder for irregular LDPC codes

Abstract

Min-Sum decoding is widely used for decoding LDPC codes in many modern digital video broadcasting decoding due to its relative low complexity and robustness against quantization error. However, the suboptimal performance of the Min-Sum affects the integrated performance of wireless receivers. In this paper, we present the idea of adapting the scaling factor of the Min-Sum decoder with iterations through a simple approximation. For the ease of implementation the scaling factor can be changed in a staircase fashion. The stair step is designed to optimize the decoder performance and the required storage for its different values. The variable scaling factor proposed algorithm produces a nontrivial improvement of the performance of the Min-Sum decoding as verified by simulation results.

Generalized simplified variable-scaled min sum LDPC decoder for irregular LDPC codes

“…Maximum number of iterations is set to 40 iterations. [7]), GSVS-min-sum with (α 0 = 0.75 and S = 9) (optimized by DE with Nelder-Mead method) and 2D correction min-sum; where the output of the check nodes with degree 4,5,6 and 7 is multiplied by 0.94, 0.92, 0.88 and 0.86 respectively, and the output of the variable nodes with degree 1,2,3 and 8 is multiplied by 1.00, 1.00, 0.91 and 0.83 respectively [5]. Results in Fig.5 show that:…”

“…It is simpler than both variable scaling factor [6] and 2D correction Min-Sum [5] in implementing and designing. Simulation results show that SVS-min-sum has lower Bit Error Rate (BER) than constant scaling factor for many LDPC codes [7]. SVS-min-sum algorithm starts the scaling factor sequence with a constant value equals 0.5.…”

Error Estimation at the Information Reconciliation Stage of Quantum Key Distribution

“…Then, Bob tries to find a key k A , which is closest to k B such that H k A (mod 2) = s A . For that purpose he may use different approximate iterative algorithms of syndrome decoding such as sum-product [17], min-sum [18], scaled min-sum [19], and others. Finally, after the decoding parties can use -almost universal 2 ( -AU 2 ) hash functions to check whether k A and k A are equal up to small error probability [15].…”

Optimized quantization and scaling of layered LDPC scaled min-sum decoder

“…GSVS-min-sum is a modified version of our previously developed SVS-min-sum decoding [11], where in the GSVS-min-sum the scaling factor increases exponentially with iterations, starting by an initial scaling factor α 0 and ends at unity. As opposed to starting the scaling factor sequence by 0.5 in the SVS-min-sum [11].…”

“…GSVS-min-sum is a modified version of our previously developed SVS-min-sum decoding [11], where in the GSVS-min-sum the scaling factor increases exponentially with iterations, starting by an initial scaling factor α 0 and ends at unity. As opposed to starting the scaling factor sequence by 0.5 in the SVS-min-sum [11]. In [10], we applied the GSVS-min-sum on flooding implementation of LDPC decoder with floating point simulation to test its improved error rate and converging performance.…”