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Telfor Journal

Reduced-complexity offset min-sum check node unit for layered 5G LDPC decoder

Vladimir L. Petrović, Mezeni El

Published Jan 1, 2021• 0 citations
Publisher

Abstract

This paper presents a novel approach for the reduced-complexity Min-Sum (MS) decoding of low density parity check (LDPC) codes in the partially parallel layered decoder architecture, which contains a large number of serial check node processors. Reduced complexity is obtained by using the variant of the single-minimum Offset Min-Sum (smOMS) algorithm that approximates a second minimum with the addition of the variable weight parameter to the minimum value. Although the reduced-complexity MS algorithms primarily reduce hardware resources in fully parallel implementations, the results showed that a considerable reduction can be obtained if serial check node processors are used. The paper also proposes a better subminimum estimation for irregular codes from 5G new radio (5G NR). The method uses smaller subminimum estimation weights in check nodes with a higher degree and higher weights in check nodes with a smaller degree, which leads to the significant improvement in the SNR performance. Additionally, it is shown that SNR performance can be further improved by applying offset before minimum calculation, which differs from conventional Min-Sum approaches.

DOI
10.5937/telfor2101007p

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This paper presents a novel approach for the reduced-complexity Min-Sum (MS) decoding of low density parity check (LDPC) codes in the partially parallel layered decoder architecture, which contains a large number of serial check node processors. Reduced complexity is obtained by using the variant of the single-minimum Offset Min-Sum (smOMS) algorithm that approximates a second minimum with the addition of the variable weight parameter to the minimum value. Although the reduced-complexity MS algorithms primarily reduce hardware resources in fully parallel implementations, the results showed that a considerable reduction can be obtained if serial check node processors are used. The paper also proposes a better subminimum estimation for irregular codes from 5G new radio (5G NR). The method uses smaller subminimum estimation weights in check nodes with a higher degree and higher weights in check nodes with a smaller degree, which leads to the significant improvement in the SNR performance. Additionally, it is shown that SNR performance can be further improved by applying offset before minimum calculation, which differs from conventional Min-Sum approaches.
This paper presents a novel approach for the reduced-complexity Min-Sum (MS) decoding of low density parity check (LDPC) codes in the partially parallel layered decoder architecture, which contains large number of serial check node processors. Reduced complexity is obtained by using the variant of the single-minimum Offset Min-Sum (smOMS) algorithm that approximates a second minimum with the addition of the variable weight parameter to the minimum value. Although the reduced-complexity MS algorithms primarily reduce hardware resources in fully parallel implementations, the results showed that a considerable reduction can be obtained if serial check node processors are used. Additionally, the paper proposes a better subminimum estimation for irregular codes from 5G new radio (5G NR). The method uses smaller subminimum estimation weights in check nodes with higher degree and higher weights in check nodes with smaller degree, which lead to the significant improvement in the SNR performance.
The development of the Fifth Generation (5G) New Radio (NR) provides several significant advantages when compared to the fourth generation (4G) Long Term Evolution (LTE) in mobile communications. Due to the outstanding characteristics of Low-Density Parity-Check (LDPC) codes such as high decoding performance, high throughput, low complexity, they have been accepted as the standard codes for the 5G NR. In this paper, we propose two LDPC decoding algorithms: Hybrid Offset Min-Sum (HOMS) and Variable Offset Min-Sum (VOMS), which are aimed at improving the error correction performance. The main idea of the HOMS/VOMS algorithm is to apply modified factors to both variable-nodes and check-nodes updated processing in order to compensate the extrinsic messages overestimation of the MS-based algorithms and increase the protection ability for degree-1 variable-nodes. The simulation results show that at the Bit-Error-Rate (BER) of 10-5, the proposed HOMS/VOMS algorithm achieves the decoding gain up to 0.2 dB compared to the Offset Min-Sum (OMS) algorithm, with a slight increase in decoding complexity.
This paper presents an Enhanced Offset Min-Sum (EOMS) decoder for Low-Density Parity-Check (LDPC) codes used in the 5th generation (5G) mobile communications. It is observed that a significant part of Variable Nodes (VNs) in the 5G LDPC codes are with degree-1 and are very sensitive to be erroneous, leading to the fact that the decoding performance is generally reduced. In the EOMS decoding, the core check nodes (CN) and extension CNs are processed with different update rules. A new CN -update criterion is also proposed by making use of the third minimum value. As a result, the offset factors are adaptively selected and the error probability of degree-1 VNs is significantly reduced. Simulation results show that the proposed EOMS decoder offers a much better error-correction performance than the state-of-the-art benchmarks for several 5G LDPC codes with a negligible complexity overhead.
Low-density parity-check (LDPC) codes have attracted tremendous attention for their excellent error-correction performance and inherent fitness for high-parallelism implementation. With great complexity reduction and friendly for hardware implementation, the min-sum (MS) decoding algorithm for LDPC codes gains widespread applications in practical. In the MS decoding algorithm, finding the first two minima among input variable-to-check messages is the most complex part. To further reduce the complexity of the MS decoding algorithm, an efficient single-minimum (single-min) based layered MS decoding for quasi-cyclic LDPC (QC-LDPC) codes is proposed in this paper. It is found that statistically the difference between the first minimum and second minimum increases as the decoding becomes more convergent. Accordingly, in the proposed single-min scheme, the second minimum is approximately derived based on the first minimum and an index indicating the convergence degree. Besides, some other metrics that are easily obtained are used to refine the second minimum. Simulation results show that the proposed method can significantly improve the error-correction performance and lower the average number of iterations, compared with the state-of-the-art single-min based MS decoding algorithms.
One of the most important units of Low-Density Parity-Check (LDPC) decoders is the Check-Node Unit.Its main task is to find the first two minimum values among incoming variable-to-check messages and return check-tovariable messages.This block significantly affects the decoding performance, as well as the hardware implementation complexity.In this paper, we first propose a modification to the check-node update rule by introducing two optimal offset factors applied to the check-to-variable messages.Then, we present the Check-Node Unit hardware architecture which performs the proposed algorithm.The main objective of this work aims to improve further the decoding performance for 5 th Generation (5G) LDPC codes.The simulation results show that the proposed algorithm achieves essential improvements in terms of error correction performance.More precisely, the error-floor does not appear within Bit-Error-Rate (BER) of 10 -8 , while the decoding gain increases up to 0.21 dB compared to the baseline Normalized Min-Sum, as well as several state-ofthe-art LDPC-based Min-Sum decoders.
This paper presents a pipelined layered quasi-cyclic low-density parity-check (QC-LDPC) decoder architecture targeting low-complexity, high-throughput, and efficient use of hardware resources compliant with the specifications of 5G new radio (NR) wireless communication standard. First, a combined min-sum (CMS) decoding algorithm, which is a combination of the offset min-sum and the original min-sum algorithm, is proposed. Then, a low-complexity and high-throughput pipelined layered QC-LDPC decoder architecture for enhanced mobile broadband specifications in 5G NR wireless standards based on CMS algorithm with pipeline layered scheduling is presented. Enhanced versions of check node-based processor architectures are proposed to improve the complexity of the LDPC decoders. An efficient minimum-finder for the check node unit architecture that reduces the hardware required for the computation of the first two minima is introduced. Moreover, a low complexity a posteriori information update unit architecture, which only requires one adder array for their operations, is presented. The proposed architecture shows significant improvements in terms of area and throughput compared to other QC-LDPC decoder architectures available in the literature.