Low Complexity Successive Cancellation Decoding of Polar Codes based on Pruning Strategy in Deletion Error Channels

TL;DR

This paper introduces a low complexity successive cancellation decoding method for polar codes in deletion error channels, utilizing a novel pruning strategy that reduces computational complexity by optimizing scenario calculations.

Contribution

It presents a new pruning strategy for SC decoding of polar codes in deletion channels, significantly reducing the number of scenarios to compute during decoding.

Findings

Reduced scenario calculations from (d+1)(d+2)/2 to d+1

Designed pruning thresholds based on scenario weight distributions

Achieved lower decoding complexity in deletion error channels

Abstract

A novel SC decoding method of polar codes is proposed in $d$-deletion channels, where a new pruning strategy is designed to reduce decoding complexity. Considering the difference of the scenario weight distributions, pruning thresholds for each node are designed separately according to a uniform constraint on the pruning error probability, which further reduce the number of scenarios that need to be calculated during the decoding procedure. In addition, by exploiting the properties of the joint weight distribution, a simplified calculation method of thresholds is proposed. Using this simplified calculation method, the number of scenarios that required to be calculated is reduced from $(d+1)(d+2)/2$ to $d+1$.