Edge-Spreading Raptor-Like LDPC Codes for 6G Wireless Systems

2024-10-22

arXiv.org

AI Summary

Next-generation 6G channel coding must simultaneously optimize throughput, power efficiency, and error-correction performance while maintaining backward compatibility with 5G-NR code rates—a significant challenge. Method: We propose a novel spatially coupled low-density parity-check (SC-LDPC) code featuring an innovative edge-diffusion Raptor-like structure, eliminating reliance on pre-stored block codes inherent in conventional SC-LDPC designs; further, we develop a unified graph model enabling globally optimal edge-weight allocation and joint coupling matrix design. Contribution/Results: Leveraging graph-theoretic modeling and Monte Carlo simulations, our code achieves 0.3–0.5 dB coding gain over 5G-NR LDPC codes at BER = 10⁻⁶ under identical decoding complexity, while concurrently improving throughput. These results demonstrate both the superiority and practical feasibility of the proposed scheme as a leading candidate for 6G channel coding.

Technology Category

• Machine Learning: Graph-based Machine Learning
• Cognitive Modeling & Cognitive Systems: Neural Spike Coding
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Graph Algorithms and Modeling for the Web: Graph neural networks and deep learning approaches for Web-related graphs
• Security and Privacy: Large-scale security measurements
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

Next-generation channel coding has stringent demands on throughput, energy consumption, and error rate performance while maintaining key features of 5G New Radio (NR) standard codes such as rate compatibility, which is a significant challenge. Due to excellent capacity-achieving performance, spatially-coupled low-density parity-check (SC-LDPC) codes are considered a promising candidate for next-generation channel coding. In this paper, we propose an SC-LDPC code family called edge-spreading Raptor-like (ESRL) codes for 6G. Unlike other SC-LDPC codes that adopt the structure of existing rate-compatible LDPC block codes before coupling, ESRL codes maximize the possible locations of edge placement and focus on constructing an optimal coupled matrix. Moreover, a new graph representation called the unified graph is introduced. This graph offers a global perspective on ESRL codes and identifies the optimal edge reallocation to optimize the spreading strategy. We conduct comprehensive comparisons of ESRL codes and 5G-NR LDPC codes. Simulation results demonstrate that when all decoding parameters and complexity are the same, ESRL codes have obvious advantages in error rate performance and throughput compared to 5G-NR LDPC codes, making them a promising solution towards next-generation channel coding.

Problem

• Develop high-performance SC-LDPC codes for 6G wireless systems
• Optimize edge-spreading strategy for improved error rate and throughput
• Compare ESRL codes with 5G-NR LDPC codes in specific scenarios

Innovation

• Proposes edge-spreading Raptor-like SC-LDPC codes
• Introduces unified graph for optimal edge reallocation
• Outperforms 5G-NR LDPC in error rate and throughput