Low-Complexity PSCL Decoding of Polar Codes

TL;DR

This paper introduces a low-complexity PSCL decoding algorithm for polar codes that reduces latency and computational complexity by using a double-threshold strategy based on reliability metrics, improving efficiency especially at higher SNRs.

Contribution

The paper proposes a novel double-threshold strategy for PSCL decoding that lowers complexity and latency in polar-like codes, with defined reliability metrics at each decoding tree level.

Findings

Reduced sorting and computational complexity at higher SNRs

Effective pruning of unreliable paths improves decoding efficiency

Significant complexity decrease demonstrated through simulations

Abstract

Successive cancellation list (SCL) decoding enables polar codes and their generalizations to deliver satisfactory performance in finite-length scenarios but it comes with high latency and complexity. To reduce latency, a partitioned SCL (PSCL) decoding algorithm, implemented over a PSCL decoding tree, can be utilized. In this work, we aim to lower down the complexity of the PSCL decoding, resulting in an efficient decoding algorithm with low latency and complexity for polar-like codes. To achieve this, we define two metrics at each level of the PSCL decoding tree. One is for evaluating the reliability of a path and the other is for estimating the probability of the correct path being included in a list of paths. Then, we propose a double-threshold strategy in the PSCL decoding process where unreliable valid paths are pruned based on the first metric, and then a list of surviving paths is selected based on the second metric. Simulation results demonstrate that when polar/CRC-polar/PAC codes are decoded using the proposed low-complexity PSCL decoder, both the sorting complexity and the computational complexity are reduced and significantly decrease as the signal-to-noise ratio (SNR) increases.