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SiPS ... design and implementation - IEEE Workshop on Signal Processing Systems

A Channel-Adaptive Early Termination strategy for LDPC decoders

Yu-Hsin Chen, Yi‐Ju Chen, Xin-Yu Shih, An-Yeu Andy Wu

Published Oct 1, 2009• 13 citations
Publisher

Abstract

In this paper, we propose a new Channel-Adaptive Early Termination (CAET) strategy to early stop Low-Density Parity-Check (LDPC) decoders. Our method checks the sign-changing rate of the log-likelihood ratios, and is able to perform the early termination under all SNR ranges with simple methodology. The average decoding latency can be decreased from the preset number of 8 to 6.73 iterations with negligible performance degradation. In addition, we create the BER Performance Loss Ratio (BPLR) index to evaluate the performance loss of different ET criteria. Compared to the hard-decision-aided criterion, our CAET strategy reduces the decoding iterations effectively and improves the BPLR by 76.6%.

DOI
10.1109/sips.2009.5336256

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In this paper, we propose a new Channel-Adaptive Early Termination (CAET) strategy to early stop Low-Density Parity-Check (LDPC) decoders. Our method checks the sign-changing rate of the log-likelihood ratios, and is able to perform the early termination under all SNR ranges with simple methodology. The average decoding latency can be decreased from the preset number of 8 to 6.73 iterations with negligible performance degradation. In addition, we create the BER Performance Loss Ratio (BPLR) index to evaluate the performance loss of different ET criteria. Compared to the hard-decision-aided criterion, our CAET strategy reduces the decoding iterations effectively and improves the BPLR by 76.6%.
By tracking the changing rate of hard decisions during every two consecutive iterations of the alternating direction method of multipliers (ADMM) penalized decoding, an efficient early termination (ET) criterion is proposed to improve the convergence rate of ADMM penalized decoder for low-density parity-check (LDPC) codes. Compared to the existing ET criterion for ADMM penalized decoding, the proposed method can reduce the average number of iterations significantly at low signal-to-noise ratios with negligible performance degradation.
Energy consumption is a major issue for LDPC decoding. To save LDPC iterative process energy, early terminations are commonly used. Traditional parity check equation is used but has a growing complexity as the block size increases. This requires a large overhead in term of area. This paper proposes an ultra-low complexity early termination (ET) scheme with a small loss of bit error rate performance based on the layer stopping (LS) criterion. The proposed ET scheme is performed by checking the number of convergent layers stopped by the LS criterion with a preset threshold. Compared with other ET schemes, the proposed ET scheme has a negligible hardware overhead and an acceptable bit error rate performance.
Low-density parity-check (LDPC) codes are one of the most popular linear block codes have ever been used in the communication system.The standard two-phase message passing decoding (TPMPD) algorithm and the layered message-passing decoding (LMPD) algorithm are widely used in LDPC decoder.However, the convergence speed of LMPD algorithm is much faster than that of TPMPD algorithm, particularly in the condition of high signal noise ratio (SNR).In this paper, we propose an early termination criterion for quasi-cyclic low-density parity-check (QC-LDPC) codes based on LMPD algorithm with fast convergence speed.The strategy is to dynamically reprocesses the uncorrected related layers while skipping the corrected ones.Simulations show that 3% reduction in terms of iteration numbers can be achieved with no performance loss compared to the traditional termination strategies, such as hard decision aided (HDA) strategy and parity check equations (PCE) strategy.Furthermore, the optimized early termination strategy achieves low complexity in hardware implementation.
As a critical communication technology, low-density parity-check (LDPC) codes are widely concerned with the Internet of things (IoT). To increase the convergence rate of the alternating direction method of multiplier (ADMM)-penalized decoder for LDPC codes, a novel early termination (ET) method is presented by computing the average sum of the hard decision (ASHD) during each ADMM iteration. In terms of the flooding scheduling and layered scheduling ADMM-penalized decoders, the simulation results show that the proposed ET method can significantly reduce the average number of iterations at low signal-to-noise ratios (SNRs) with negligible decoding performance loss.