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

TL;DR

This paper introduces a partitioned polar code decoding method called PSCLF that reduces the complexity of the SCLF decoding algorithm while maintaining or improving error correction performance.

Contribution

The paper proposes a novel partitioned decoding approach for SCLF that enables early termination, multiple flips, and tailored partitions to significantly reduce decoding complexity.

Findings

PSCLF reduces decoding complexity by up to 77% at FER of 0.01.

PSCLF achieves up to 0.1 dB error correction gain over SCLF with same parameters.

The average execution time of PSCLF matches or is lower than SCL at certain FER levels.

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 $\omega=3$ 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.