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European Signal Processing Conference (EUSIPCO)

A novel hardware-friendly self-adjustable offset min-sum algorithm for ISDB-S2 LDPC decoder

Wen Ji, Makoto Hamaminato, Hiroshi Nakayama, Satoshi Goto

Published Aug 1, 2010• 2 citations
OpenAlex

Abstract

In this paper, a novel self-adjustable offset min-sum LDPC decoding algorithm is proposed for ISDB-S2 (Integrated Services Digital Broadcasting via Satellite — Second Generation) application. We present for the first time a uniform approximation of the check node operation through mathematical induction on Jacobian logarithm. The approximation theoretically shows that the offset value is mainly dependent on the difference between the two most unreliable inputs from the bit nodes and the algorithm proposed can adjust the offset value according to the inputs during the iterative decoding procedure. Simulation results for all 11 code rates of ISDB-S2 demonstrate that the proposed method can achieve an average of 0.15dB gain under the same Bit Error Rate (BER) performance, compared to the Min-sum based algorithms, and consumes only 1.21% computation complexity compared to BP-based algorithms in the best case.

Related papers

Self-adjustable offset min-sum algorithm for ISDB-S2 LDPC decoder

Wen Ji, Makoto Hamaminato, Hiroshi Nakayama +1 more

In this paper, a novel self-adjustable offset min-sum LDPC decoding algorithm is proposed for ISDB-S2 application. We present for the first time a uniform approximation of the check node operation through mathematical induction on Jacobian logarithm and theoretically shows that the offset value is mainly dependent on the difference of the two most unreliable inputs from the bit nodes, which makes the offset value adjustable during the iterative decoding procedure. Simulation results for all 11 code rates of ISDB-S2 demonstrate that the proposed method can achieve an average of 0.15dB gain compared to the Min-sum based algorithms, and consumes only 1.21% computation complexity compared to BP-based algorithms in the best case.

IEICE Electronics Express•Jan 1, 2010•5 citations

A modified Offset Min-Sum decoding algorithm for LDPC codes

Meng Xu, Jianhui Wu, Meng Zhang

In this paper a modified Offset Min-Sum decoding algorithm for Low-Density Parity Check Codes is presented. In this modified algorithm, the offset factor in the original Offset Min-Sum algorithm is adjusted iteratively with the assistance of the check-node computation outputs of the Normalized Min-Sum algorithm. As a result, the offset factor in our modified algorithm can be calculated adaptively and more efficiently according to the previous decoding procedure, which can minimize the decoding degradation compared with the Belief Propagation decoding algorithm. The simulation results show that, compared with the original Offset Min-Sum decoding algorithm, our modified algorithm can achieve noticeable performance improvement with minor extra hardware complexity. For example, when BER is 10−5, our algorithm can achieve 0.1dB and 0.2dB decoding gain over Offset Min-Sum algorithm for regular and irregular LDPC codes respectively.

•Jul 1, 2010•29 citations

Genetic Algorithm-Optimized Adaptive Offset Min-Sum LDPC Decoder for 5G- NR Base Graph 2 Codes

Anwer Sabah Ahmed, Yousif Jawad Kadhim Nukhailawi, Heyam A. Marzog +1 more

Abstract This paper proposes a resource-efficient Adaptive Offset Min-Sum (A-OMS) LDPC decoder for 5G-NR Base Graph 2 (BG2) codes. A Genetic Algorithm (GA) is employed to optimize the offset factor within the check-node update, addressing the difficulty of selecting a globally optimal offset for the irregular BG2 structure. The GA operates as a meta-heuristic optimizer that minimizes the bit-error rate (BER) over a wide range of signal-to-noise ratios (SNRs). Simulation results show that the proposed GA-optimized A-OMS decoder achieves performance within 0.2–0.4 dB of belief-propagation decoding, while providing coding gains of 0.3–0.6 dB and up to a 4.6× BER reduction compared with conventional fixed-offset OMS. These improvements are obtained with approximately 35% of the computational complexity of BP decoding. The proposed approach offers a practical balance between performance and implementation efficiency for next-generation 5G-NR receivers.

•Jan 28, 2026•1 citation

Modified min-sum decoding algorithm for LDPC codes based on classified correction

Zhong Zhou, Yunzhou Li, Xiang Chen +2 more

In this paper, a modified min-sum decoding algorithm based on classified correction is proposed for low density parity check (LDPC) codes. Different from the single correction in the normalized belief propagation (BP)-based and offset BP-based algorithms [4], the proposed algorithm utilizes two corrections for both minimum and sub-minimum magnitudes of input messages in check nodes. These two correction factors can be obtained by analyzing the offset of updated messages in check nodes between the BP and the min-sum algorithms associated with check node degree. Simulation results show that the proposed algorithm can achieve performance very close to that of the BP algorithm. Furthermore, the FPGA implementation of this algorithm can reach a throughput of 200 Mbps at BER=10-6with lower complexity and fewer resources than the BP algorithm.

International Conference on Communications and Networking in China (ChinaCom)•Aug 1, 2008•9 citations

Alternative Approximation of Check Node Algorithm for DVB-S2 LDPC Decoder

O. Eljamaly Toumaz, P. Sweeney

In this paper, a new approximation of the check node rule algorithm is proposed for updating the check nodes messages in LDPC decoding. The new technique evaluates the check node min-sum magnitude algorithm using the Taylor series and results in reduced computational complexity and hardware implementation. The architecture of a check node processing unit, implementing the new alternative approximation of the check node, is also presented. The proposed method can achieve the same BER performance with a reduction of ~20% hardware complexity in the LDPE decoder. The simulation results obtained shows that the packet error rate performance of 10-7, which is the DVB-S2 requirement for MPEG packets transmitted, can be achieved with this new method.

International Conference on Systems and Networks Communications•Aug 1, 2007•5 citations

Further Improvements in Decoding Performance for 5G LDPC Codes Based on Modified Check-Node Unit

Bich Ngoc Tran-Thi, Truong Nguyen, Trang Hoang

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.

Radioengineering•May 11, 2023•1 citation
In this paper, a novel self-adjustable offset min-sum LDPC decoding algorithm is proposed for ISDB-S2 (Integrated Services Digital Broadcasting via Satellite — Second Generation) application. We present for the first time a uniform approximation of the check node operation through mathematical induction on Jacobian logarithm. The approximation theoretically shows that the offset value is mainly dependent on the difference between the two most unreliable inputs from the bit nodes and the algorithm proposed can adjust the offset value according to the inputs during the iterative decoding procedure. Simulation results for all 11 code rates of ISDB-S2 demonstrate that the proposed method can achieve an average of 0.15dB gain under the same Bit Error Rate (BER) performance, compared to the Min-sum based algorithms, and consumes only 1.21% computation complexity compared to BP-based algorithms in the best case.
In this paper, a novel self-adjustable offset min-sum LDPC decoding algorithm is proposed for ISDB-S2 application. We present for the first time a uniform approximation of the check node operation through mathematical induction on Jacobian logarithm and theoretically shows that the offset value is mainly dependent on the difference of the two most unreliable inputs from the bit nodes, which makes the offset value adjustable during the iterative decoding procedure. Simulation results for all 11 code rates of ISDB-S2 demonstrate that the proposed method can achieve an average of 0.15dB gain compared to the Min-sum based algorithms, and consumes only 1.21% computation complexity compared to BP-based algorithms in the best case.
In this paper a modified Offset Min-Sum decoding algorithm for Low-Density Parity Check Codes is presented. In this modified algorithm, the offset factor in the original Offset Min-Sum algorithm is adjusted iteratively with the assistance of the check-node computation outputs of the Normalized Min-Sum algorithm. As a result, the offset factor in our modified algorithm can be calculated adaptively and more efficiently according to the previous decoding procedure, which can minimize the decoding degradation compared with the Belief Propagation decoding algorithm. The simulation results show that, compared with the original Offset Min-Sum decoding algorithm, our modified algorithm can achieve noticeable performance improvement with minor extra hardware complexity. For example, when BER is 10−5, our algorithm can achieve 0.1dB and 0.2dB decoding gain over Offset Min-Sum algorithm for regular and irregular LDPC codes respectively.
Abstract This paper proposes a resource-efficient Adaptive Offset Min-Sum (A-OMS) LDPC decoder for 5G-NR Base Graph 2 (BG2) codes. A Genetic Algorithm (GA) is employed to optimize the offset factor within the check-node update, addressing the difficulty of selecting a globally optimal offset for the irregular BG2 structure. The GA operates as a meta-heuristic optimizer that minimizes the bit-error rate (BER) over a wide range of signal-to-noise ratios (SNRs). Simulation results show that the proposed GA-optimized A-OMS decoder achieves performance within 0.2–0.4 dB of belief-propagation decoding, while providing coding gains of 0.3–0.6 dB and up to a 4.6× BER reduction compared with conventional fixed-offset OMS. These improvements are obtained with approximately 35% of the computational complexity of BP decoding. The proposed approach offers a practical balance between performance and implementation efficiency for next-generation 5G-NR receivers.
In this paper, a modified min-sum decoding algorithm based on classified correction is proposed for low density parity check (LDPC) codes. Different from the single correction in the normalized belief propagation (BP)-based and offset BP-based algorithms [4], the proposed algorithm utilizes two corrections for both minimum and sub-minimum magnitudes of input messages in check nodes. These two correction factors can be obtained by analyzing the offset of updated messages in check nodes between the BP and the min-sum algorithms associated with check node degree. Simulation results show that the proposed algorithm can achieve performance very close to that of the BP algorithm. Furthermore, the FPGA implementation of this algorithm can reach a throughput of 200 Mbps at BER=10-6with lower complexity and fewer resources than the BP algorithm.
In this paper, a new approximation of the check node rule algorithm is proposed for updating the check nodes messages in LDPC decoding. The new technique evaluates the check node min-sum magnitude algorithm using the Taylor series and results in reduced computational complexity and hardware implementation. The architecture of a check node processing unit, implementing the new alternative approximation of the check node, is also presented. The proposed method can achieve the same BER performance with a reduction of ~20% hardware complexity in the LDPE decoder. The simulation results obtained shows that the packet error rate performance of 10-7, which is the DVB-S2 requirement for MPEG packets transmitted, can be achieved with this new method.
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.