Belief-Propagation Decoding of LDPC Codes With Variable Node–Centric Dynamic Schedules

Chang, Tofar C.-Y.; Wang, Pin-Han; Weng, Jian-Jia; Lee, I-Hsiang; Su, Yu T.

doi:10.1109/tcomm.2021.3078776

Cited by 8 publications

(4 citation statements)

References 21 publications

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“…These collective benefits position BP decoding as a preferred method for LDPC code decoding across various modern communication systems. The following describes the step-by-step process of the BP decoding algorithm in detail [18].…”

Section: Ldpc Decoding Algorithmmentioning

confidence: 99%

Investigation of IEEE 802.16e LDPC Code Application in PM-DQPSK System

Xue,

Li,

Zhang

et al. 2024

Electronics

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With the development of the Internet and information technology, optical fiber communication systems need to meet people’s information demand for large capacity and high speed. High-order phase modulation and channel multiplexing can improve the capacity and data rate of optical fiber communication systems, but they also bring the problem of bit error. To improve the transmission quality and reliability of optical fiber communication systems, forward error correction (FEC) coding techniques are commonly used, which serve as the fundamental approach to enhance the quality and reliability of fiber optic communication systems, ensuring that the received data remain accurate and reliable. The FEC in optical fiber communication systems is divided into three generations. The first generation FEC is mainly hard decision codewords, represented as RS code. The second generation FEC is mainly cascaded code, which stands for interleaved cascaded code. The third generation of FEC mainly refers to soft decision codes, which are represented as low-density parity-check (LDPC) codes. As a kind of FEC, LDPC codes stand out as pivotal contributors in the field of optical communication and have gained remarkable attention due to exceptional error correction performance and low decoding complexity. Based on IEEE802.16e standard, LDPC code with specific code length and rate is compiled and simulated in MATLAB and VPItransmissionMaker 10.1 and successfully incorporated into polarization multiplexed differential quadrature phase shift keying (PM-DQPSK) coherent optical transmission system. The simulation results indicate that the bit error rate (BER) can be reduced to 10−3 when the optical signal-to-noise ratio (OSNR) reaches 14.2 dB, and the BER experiences a reduction by nearly three orders of magnitude when the OSNR is 17.2 dB. These findings underscore the efficacy of LDPC codes in significantly improving the performance of optical communication systems, particularly in scenarios demanding robust error correction capabilities. This study provides valuable, significant results regarding the potential of LDPC codes for enhancing the reliability of optical transmission in real-world applications.

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Section: Ldpc Decoding Algorithmmentioning

confidence: 99%

Investigation of IEEE 802.16e LDPC Code Application in PM-DQPSK System

Xue,

Li,

Zhang

et al. 2024

Electronics

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“…It can be observed that N s is the nearest integer rounded to the product of the mini-batch size N b and the set of the SNR ratios (lines 2). As the summation of N s should equal N b , we may need to randomly adjust (add or delete) the value of N s (lines [5][6][7][8][9][10][11][12][13][14][15].…”

Section: Trainingmentioning

confidence: 99%

“…In [8], one simple method with less complex arithmetic operations to find the offset correction factor had been demonstrated. Chang et al [9] proposed a conditional variable node (VN) selecting metric to realize informed dynamic scheduling (IDS) LDPC decoding schedules. The goal is to find VNs with probable incorrect decisions and correct the errors by updating them.…”

Section: Introductionmentioning

confidence: 99%

Two Novel Semi-/Auto-Adaptive SNR Algorithms to Efficiently Train Deep Neural SPA Decoders

Huang

2022

IEEE Access

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“…There are two categories of schedules. One is dynamic [8][9][10][11][12][13][14] whose order is determined online, while the other is static [15][16][17][18][19][20] whose order is decided offline and kept fixed during the decoding. Usually dynamic schedules have better error performance and faster convergence speed since the real-time information is used to determine the optimal order.…”

mentioning

confidence: 99%

Reordered static layered schedule for 5G low‐density parity‐check codes

Zhou,

Wang

2024

Electronics Letters

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The error performance of the 5G low‐density parity‐check codes is significantly impacted by the update order of layers. At present, the row degree (RD) and the number of punctured bits (PBs) are widely used to decide the update order of layers. Here, the authors propose a metric to assess the soft message recovery speed of coded bits and then suggest updating layers with the lowest RD first rather than those with the least PBs first. Besides, a new criterion is introduced to further determine the update order of layers with the same number of PBs and the same RD. The resulting reordered layered schedule yields better error performance and faster convergence speed than the prior arts.

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Belief-Propagation Decoding of LDPC Codes With Variable Node–Centric Dynamic Schedules

Cited by 8 publications

References 21 publications

Investigation of IEEE 802.16e LDPC Code Application in PM-DQPSK System

Investigation of IEEE 802.16e LDPC Code Application in PM-DQPSK System

Two Novel Semi-/Auto-Adaptive SNR Algorithms to Efficiently Train Deep Neural SPA Decoders

Reordered static layered schedule for 5G low‐density parity‐check codes

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