Sequential Automorphism Ensemble Decoding with Early Stopping

TL;DR

This paper introduces a low-complexity sequential automorphism ensemble decoding method with early stopping, significantly reducing decoding complexity while maintaining low error rates.

Contribution

It proposes a novel sequential activation and early stopping scheme for automorphism ensemble decoding that minimizes complexity under error constraints.

Findings

Decoding complexity reduced by at least 6 times, up to 22 times.

Negligible impact on block-error rate below 10^{-3}.

Effective early termination thresholds improve efficiency.

Abstract

In this paper, a low-complexity approach for the automorphism ensemble decoder (AED) using successive cancellation (SC) as constituent decoders is proposed. The approach sequentially activates sub-decoders and terminates the decoding process based on pre-optimized parameters, derived from the strong correlation observed between the decoding outcome and the SC path metric. An algorithm is proposed to find a list of early termination thresholds that minimize average decoding complexity subject to a block-error rate (BLER) constraint. For various code parameters and a BLER below $10^{-3}$, simulation results show that average decoding complexity is reduced by a factor of at least $6 \times$, and up to $22 \times$, compared to the original AED complexity, with a negligible degradation in BLER.