On Reducing Decoding Complexity of Successive-Cancellation List Flip Decoding of Polar Codes

2026-05-08

AI Summary

This work addresses the high computational complexity of the successive cancellation list flip (SCLF) decoding algorithm for polar codes by proposing a partitioned SCLF (PSCLF) decoder. The proposed approach employs a specially designed partitioned polar code structure, integrates a dynamic flipping metric with a multi-flip strategy, and incorporates early termination and skip-based restart mechanisms. These innovations collectively reduce decoding complexity substantially while maintaining or even improving error-correction performance. Experimental results demonstrate that, under identical parameters, PSCLF achieves up to a 0.1 dB gain over SCLF and reduces decoding complexity by as much as 77%. Furthermore, at a frame error rate (FER) of ≤ 4×10⁻³, the average execution time of PSCLF is comparable to that of standard successive cancellation list (SCL) decoding.

Abstract

The recently proposed SCLF decoding algorithm for polar codes improves the error-correcting performance of state-of-the-art SCL decoding. However, it comes at the cost of a higher complexity. In this paper, partitioned polar codes tailored for the proposed PSCLF decoding algorithm are used to reduce the complexity of SCLF. Indeed, compared to SCLF, PSCLF allows early termination and is able to restart by skipping part of the decoding tree traversed sequentially. In order to maximize the coding gain, design of partitions tailored to PSCLF is proposed. In this extended paper, dynamic flip metric is used, as well as the possibility to flip multiple times during SCL. An analysis on the impact of this strategy on the early-termination or the CRC collisions encountered in PSCLF is carried out. Error-correction performance of multiple code rates and multiple partition strategies are shown. With the baseline algorithm SCL with $L=2$, degradation of $0.05$ dB is shown with respect to SCL-64, using $ω=3$ flip per trial with $T_{max}=300$ trials. Numerical results show that the proposed PSCLF algorithm has an error-correction performance gain of up to 0.1 dB with respect to SCLF with same decoding parameters. This work is also compared with existing techniques to reduce the complexity of the SCLF decoding algorithm. The proposed algorithm reduces the complexity up to 77 % at the frame-error rate of $0.01$ with respect to SCLF and is able to reduce more the decoding complexity of SCLF embedding as well a restart mechanism. The average execution time of PSCLF matches the latency of SCL at $\text{FER}=4\cdot10^{-3}$ and lower.

Problem

• polar codes
• decoding complexity
• successive-cancellation list flip decoding
• SCLF

Innovation

• Polar codes
• SCLF decoding
• partitioned decoding
• complexity reduction
• early termination