Node-Based Soft-Output Fast Successive Cancellation List Decoding of Polar Codes

TL;DR

This paper introduces the SO-FSCL decoding algorithm for polar codes, significantly reducing latency and complexity while maintaining soft-output performance, and enabling flexible hard or soft output options.

Contribution

It proposes a node-based fast decoding extension to SO-SCL, addressing soft output extraction and hardware efficiency, with substantial latency and complexity improvements.

Findings

Reduces decoding time steps by 81.8%

Decreases the number of additions by 41.3%

Maintains near-identical soft-output performance as SO-SCL

Abstract

The soft-output successive cancellation list (SO-SCL) decoder provides a methodology for estimating the a-posteriori probability log-likelihood ratios by only leveraging the conventional SCL decoder of polar codes. However, the sequential decoding nature of SCL introduces high decoding latency to SO-SCL. In this paper, we incorporate node-based fast decoding into the SO-SCL framework. After addressing the challenge of soft output extraction in special node decoding, we proposed the soft-output fast SCL (SO-FSCL) decoding algorithm, along with its log-domain implementation and hardware-friendly version. The proposed SO-FSCL decoder can be regarded as an add-on extension to FSCL decoder, enabling us to autonomously choose whether to output only hard decisions like FSCL or to provide additional soft outputs. Latency and complexity analyses demonstrate that SO-FSCL can significantly reduce, for example, decoding time steps by 81.8\% (with unlimited resources), the number of additions by 41.3\%, and the number of comparisons by 46.4\%. Meanwhile, simulation results indicate that SO-FSCL delivers almost the same soft-output performance as SO-SCL, outperforming other soft-output polar decoders, especially in scenarios involving iterative decoding.