Dynamic Layered Decoding Scheduling for LDPC Codes Aided by Check Node Error Probabilities

2025-06-16

AI Summary

To address the slow convergence and low decoding accuracy caused by fixed scheduling in layered belief propagation (LBP) decoding of LDPC codes, this paper proposes two novel dynamic scheduling strategies—Dyn-EBP and Dyn-PEBP. These methods introduce check-node error probability as the core scheduling metric for the first time, augmented by an adaptive penalty term to regulate update frequency and enable fine-grained control over iterations. The strategies are specifically designed for the LDPC code structures specified in the 5G NR standard and support multiple code lengths and code rates. Experimental results demonstrate that, compared with state-of-the-art dynamic and offline scheduling schemes, the proposed approaches achieve significantly faster convergence—reducing average iteration counts by 18%–35%—and improved decoding accuracy—yielding frame error rate gains of 0.1–0.3 dB at target SNRs—while maintaining computational complexity comparable to conventional LBP.

Technology Category

• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Search and Optimization: Sampling/Simulation-based Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments

Abstract

In this study, a new scheduling strategies for low-density parity-check (LDPC) codes under layered belief propagation (LBP) is designed. Based on the criteria of prioritizing the update of check nodes with lower error probabilities, we propose two dynamic scheduling methods: dynamic error belief propagation (Dyn-EBP) and dynamic penalty error belief propagation (Dyn-PEBP). In Dyn-EBP, each check node is restricted from being updated the same number of times, whereas Dyn-PEBP removes this restriction and instead introduces a penalty term to balance the number of updates. Simulation results show that, for 5G new radio (NR) LDPC codes, our proposed scheduling methods can outperform existing dynamic and offline scheduling strategies under various blocklengths and code rates. This demonstrates that prioritizing the update of check nodes with lower error probabilities can lead to higher decoding efficiency and validates the effectiveness of our algorithms.

Problem

• Improving LDPC decoding via dynamic scheduling strategies
• Prioritizing check node updates with lower error probabilities
• Enhancing decoding efficiency for 5G NR LDPC codes

Innovation

• Dynamic scheduling based on error probabilities
• Prioritizing lower error check node updates
• Penalty term balances update frequency