Toward Terabits-per-second Communications: Low-Complexity Parallel Decoding of $G_N$-Coset Codes

TL;DR

This paper presents a low-complexity, high-throughput parallel decoding framework for $G_N$-coset codes, utilizing simplified SC decoders with integrated error detection and LLR generation optimized by genetic algorithms, achieving significant area efficiency.

Contribution

It introduces a parallel decoding scheme using SC decoders with integrated error detection and LLR generation, optimized via genetic algorithms for high area efficiency.

Findings

Achieves 533 Gbps/mm^2 area efficiency in 7nm technology.

Reduces complexity compared to soft-output decoders.

Maintains high throughput with simplified binary interconnections.

Abstract

Recently, a parallel decoding framework of $G_N$-coset codes was proposed. High throughput is achieved by decoding the independent component polar codes in parallel. Various algorithms can be employed to decode these component codes, enabling a flexible throughput-performance tradeoff. In this work, we adopt SC as the component decoders to achieve the highest-throughput end of the tradeoff. The benefits over soft-output component decoders are reduced complexity and simpler (binary) interconnections among component decoders. To reduce performance degradation, we integrate an error detector and a log-likelihood ratio (LLR) generator into each component decoder. The LLR generator, specifically the damping factors therein, is designed by a genetic algorithm. This low-complexity design can achieve an area efficiency of $533Gbps/mm^2$ under 7nm technology.