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arXiv · 2501.14102

5G LDPC Linear Transformer for Channel Decoding

Mario Hernandez·Fernando Pinero
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Abstract

This work introduces a novel, fully differentiable linear-time complexity transformer decoder and a transformer decoder to correct 5G New Radio (NR) LDPC. We propose a scalable approach to decode linear block codes with $O(n)$ complexity rather than $O(n^2)$ for regular transformers. The architectures' performances are compared to Belief Propagation (BP), the production-level decoding algorithm used for 5G New Radio (NR) LDPC codes. We achieve bit error rate performance that matches a regular Transformer decoder and surpases one iteration BP, also achieving competitive time performance against BP, even for larger block codes. We utilize Sionna, Nvidia's 5G & 6G physical layer research software, for reproducible results.

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BibTeXRIS

Mario Hernandez, Fernando Pinero. 2025-01-23. 5G LDPC Linear Transformer for Channel Decoding. https://arxiv.org/abs/2501.14102

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