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International SoC Design Conference

Efficient Forced Convergence algorithm for low power LDPC decoders

Byung Jun Choi, Myung Hoon Sunwoo

Published Nov 1, 2013• 8 citations
Publisher

Abstract

This paper proposes an efficient Forced Convergence (FC) algorithm to reduce the computational complexity of LDPC decoders. To reduce the computational complexity, the proposed algorithm uses only one threshold value and two conditions of variable nodes (VNs) while the existing FC algorithm uses two threshold values and two conditions. The simulation results show that the proposed algorithm achieves the bit error rate (BER) performance close to the typical Min-Sum algorithm. however, it can significantly reduce the computational complexity compared to the existing FC algorithm.

DOI
10.1109/isocc.2013.6864054

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This paper proposes an efficient Forced Convergence (FC) algorithm to reduce the computational complexity of LDPC decoders. To reduce the computational complexity, the proposed algorithm uses only one threshold value and two conditions of variable nodes (VNs) while the existing FC algorithm uses two threshold values and two conditions. The simulation results show that the proposed algorithm achieves the bit error rate (BER) performance close to the typical Min-Sum algorithm. however, it can significantly reduce the computational complexity compared to the existing FC algorithm.
This paper proposes a simplified forced-convergence (SFC) algorithm to reduce the computational complexity for low-density parity-check (LDPC) decoding. To reduce the computational complexity, the proposed algorithm uses the modified check node (CN) operation that does not use a condition for deactivating CNs. Therefore, the proposed SFC algorithm uses only one threshold value while the existing forced-convergence (FC) algorithm uses two threshold values. The simulation results show that SFC achieves a bit error rate (BER) performance close to min-sum (MS) algorithm. SFC can reduce the computational complexity of check node by approximately 22.21% compared to FC.
An improvement of the forced-convergence decoding algorithm is discussed. Iterative decoding schemes such as the sum-product (SP) decoding bring out excellent performance of low-density parity check (LDPC) codes. The forced-convergence (FC) decoding is also an iterative decoding algorithm obtained by modifying the SP decoding. The FC decoding succeeds to reduce the decoding complexity of the SP decoding, but the error correcting performance is severely degraded by the modification. The performance degradation of the FC decoding is expected to be mitigated if the convergence criterion used in the algorithm is appropriately modified. This paper discusses several types of modifications of the convergence criteria. Computer simulation shows that the proposed modifications improve the performance of the FC decoding algorithm.
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 modified message propagation algorithm is proposed for a low-complexity decoder of low-density parity-check (LDPC) codes, which controls the information propagated from variable and check nodes.The proposed threshold-based node deactivation for variable nodes and zero-forcing scheme for check nodes remarkably reduce decoding complexity required for similar error performance. In the proposed scheme, different thresholds, which are determined from the base matrix of the LDPC codes, are applied for each type of variable node. In addition, thresholds for deactivating variable nodes are increased while the decoding process is operated for a reduction in decoding complexity without early error floor, which is a drawback of the conventional threshold-based deactivation scheme. Simulation results show that the proposed scheme enables normalized min-sum decoders to decode successfully with less complexity than the conventional threshold-based deactivating scheme.
In this paper, we propose a scheme to reduce the computation complexity of min-sum (MS) algorithm for decoding of nonbinary low-density parity-check (LDPC) codes over GF(q). Previously, MS algorithm reduced the decoding complexity by lowering the size of the configuration set for each variable node through a sorting. In the proposed scheme, we modify the MS algorithm by minimizing the size of the configuration set for each variable node through a filtering. In the filtering, the reduction of the set size can be controlled by a preset threshold. This way we can reduce the complexity more efficiently. Simulation results show, compared to the previous EMS algorithm, the complexity of proposed scheme is reduced with a negligible degradation in the code performance.
The fast decoding of low-density parity-check (LDPC) is crucial for its future applications. In this paper, we propose to use Early Termination (ET) and Force Convergence (FC) techniques to accelerate the decoding of two new local/global two-phases decoding algorithms to reduce the Globally Coupled (GC) LDPC codes. Specifically, ET is applied in the local decoding phase of two- phases decoding of GC-LDPC codes to skip the local decoding which is highly likely to fail and avoid the unnecessary iterations. FC is applied in global decoding phase where converged variable nodes are identified and removed from Tanner graph and the decoding can be speed up shrinking parity check matrices. Two variants are proposed for the ET operation in local decoding phase. ET-1 merely stops iteration if it meets the stopping criterion while in ET-1, the iteration number saved in local decoding is added up in global decoding to improve the decoding performance. The simulation results show that the ET-1-FC scheme can save up to 42% decoding time complexity in the low SNR region while keeping the error rate performance nearly unchanged, the ET-2-FC can improve the error rate performance by 0.18dB at bit error rate 0.001 or 0.23dB at frame error rate 0.1. In the waterfalling region of BER/FER curves, both schemes can save about 25% decoding time complexity.