Simplified Successive Cancellation List Decoding of PAC Codes

TL;DR

This paper introduces a simplified successive cancellation list (SSCL) decoding algorithm for PAC codes, reducing latency while maintaining performance, thus enhancing the practicality of PAC codes in communication systems.

Contribution

It proposes a novel SSCL decoding method for PAC codes that decreases decoding latency by processing special nodes at intermediate stages.

Findings

PAC codes with SSCL decoding have similar performance to traditional SCL decoding.

The SSCL algorithm significantly reduces decoding latency.

Simulation results confirm the effectiveness of the proposed method.

Abstract

Polar codes are the first class of structured channel codes that achieve the symmetric capacity of binary channels with efficient encoding and decoding. In 2019, Arikan proposed a new polar coding scheme referred to as polarization-adjusted convolutional (PAC)} codes. In contrast to polar codes, PAC codes precode the information word using a convolutional code prior to polar encoding. This results in material coding gain over polar code under Fano sequential decoding as well as successive cancellation list (SCL) decoding. Given the advantages of SCL decoding over Fano decoding in certain scenarios such as low-SNR regime or where a constraint on the worst case decoding latency exists, in this paper, we focus on SCL decoding and present a simplified SCL (SSCL) decoding algorithm for PAC codes. SSCL decoding of PAC codes reduces the decoding latency by identifying special nodes in the decoding tree and processing them at the intermediate stages of the graph. Our simulation results show that the performance of PAC codes under SSCL decoding is almost similar to the SCL decoding while having lower decoding latency.