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International Conference on Computer Science and Network Technology (ICCSNT)

An efficient early stopping analog decoder for LDPC codes

Yuan Gao, Yujie Lin, Bowen Zeng, Zhe Zhao, Hao Ran Zheng

Published Dec 1, 2015• 1 citation
Publisher

Abstract

The analog implementation of error control decoders is a competitive methodology compared with the digital implementation in power efficiency and throughput. In order to detect uncorrectable frames and early stop the iterative decoding of low-density parity check (LDPC) analog decoders, a probability stopping block using probabilities of satisfied checks is proposed. Simulation results show that the proposed criterion can greatly reduce the average number of iterations at low SNR, and has better tradeoff between complexity and performance than other stopping criteria using extrinsic information.

DOI
10.1109/iccsnt.2015.7490926

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The analog implementation of error control decoders is a competitive methodology compared with the digital implementation in power efficiency and throughput. In order to detect uncorrectable frames and early stop the iterative decoding of low-density parity check (LDPC) analog decoders, a probability stopping block using probabilities of satisfied checks is proposed. Simulation results show that the proposed criterion can greatly reduce the average number of iterations at low SNR, and has better tradeoff between complexity and performance than other stopping criteria using extrinsic information.
Low density parity check (LDPC) codes are amongst the most powerful codes known today. They are decoded iteratively by a message-passing algorithm. For this, an inherent stopping criterion exists for decodable blocks based on parity checks. For undecodable blocks, typically, a fixed number of iterations are carried out before the decoding procedure is terminated, which is a waste of energy and time. We present a stopping criterion which detects undecodable blocks in an early stage of the decoding process. The novel stopping criterion works for floating and fixed point implementations. It greatly reduces the average number of required iterations without any loss in communication performance.
An early stopping criterion for low-density parity-check decoding is proposed to reduce the number of decoding iterations. The proposed early stopping criterion is based on the average weighted reliability measure of the hard output of decoder to detect undecodable blocks in an early stage of the decoding process. Simulation results show that the proposed algorithm can achieve about 0.2–0.4 dB coding gain improvement on average while reducing up to about 50%–85% iteration for decoding at low to medium Eb/N0, compared with the existing method.
Nonbiliary low-density parity-check (LDPC) codes can lead to excellent error performance while the codewords are of short or moderate length. However, the high decoding complexity of nonbiliary LDPC codes inevitably depreciates their practical values. The computational bottleneck arises from the check node processing in the iterative message passing (MP) algorithms which terminate when either all parity checks are satisfied or the maximum iteration number is reached. We have observed that for undecodable blocks, the MP algorithms always run up to the maximum iteration limit and therefore cannot generate the correct codeword. Thus, it would be better to terminate the algorithms early so as to save the unnecessary computational time and reduce the extra power consumption when undecodable blocks are experienced. In this paper, we propose a new T-tolerance stopping criterion for LDPC decoders by exploiting the fact that the total a posteriori probability (APP) should increase as the iteration number grows. Simulation results demonstrate that our proposed new T-tolerance criterion can greatly reduce the average iteration number (complexity) while restricting the decoding performance degradation within 0.1 dB in low bit-energy-to-noise ratio scenarios.
Nonbinary low-density parity-check (LDPC) codes over finite fields GF(q) have a better performance than those of the binary low-density parity-check codes, at short and medium block lengths, but the decoder of GF(q)-LDPC has more complexity. In this paper, a new stopping criterion is proposed. Based on the changes of the variance of variable node¿s extrinsic information, the criterion can predict a decoding failure and decide whether the iteration of the decoder should be stopped. The simulation results show that the stopping criterion can greatly reduces the average number of required iterations of GF(q)-LDPC decoder with negligible performance loss.
An efficient early stopping criterion based on the evolution of the number of reliable variable nodes (NRVN) is proposed for low density parity check (LDPC) codes in this paper. This criterion can significantly reduce the average number of iterations (ANI) at low to middle signal to noise ratios (SNRs) with minimal performance degradation. Furthermore, a hybrid decoding method is presented to reduce the decoding complexity of LDPC codes by combining the proposed stopping criterion and forced convergence (FC) decoding algorithm. Compared with the classic belief propagation (BP) decoding, significant computation complexity reduction can be achieved with small computation overhead.
A weighted belief propagation decoding algorithm for low-density parity-check decoding is proposed to accelerate the convergence of decoding and reduce the number of decoding iterations. We propose an early stopping criterion which is based on the average weighted reliability measure of the hard output of decoder to detect undecodable blocks in an early stage of the decoding process. In addition, an adaptive weighted iteration scheme is proposed to increase the convergence speed of belief propagation (BP) decoding and therefore improve the error performance. The evolution of the adaptive weighting factor with the number of decoding iterations is based on the relative entropy between two consecutive ”a posteriori” probabilities distribution at decoder output. Simulation results show that the proposed algorithm can achieve about 0.2-0.4 dB coding gain improvement on average while reducing up to about 50%-85% iterations for decoding at low to medium E(subscript b)/ N(subscript 0) , compared with the conventional BP based algorithms.