Finite-Length Scaling of SC-LDPC Codes With a Limited Number of Decoding Iterations

TL;DR

This paper introduces finite-length scaling laws for spatially-coupled LDPC codes under limited-iteration BP decoding, enabling accurate FER prediction with a balance of complexity and precision.

Contribution

It develops four new scaling laws for predicting FER performance of SC-LDPC codes with limited decoding iterations, including a novel model for sliding window decoding.

Findings

Scaling laws accurately predict FER performance.

A balance between accuracy and computational complexity is achieved.

The Ornstein-Uhlenbeck process effectively models decoding dynamics.

Abstract

We propose four finite-length scaling laws to predict the frame error rate (FER) performance of spatially-coupled low-density parity-check codes under full belief propagation (BP) decoding with a limit on the number of decoding iterations and a scaling law for sliding window decoding, also with limited iterations. The laws for full BP decoding provide a choice between accuracy and computational complexity; a good balance between them is achieved by the law that models the number of decoded bits after a certain number of BP iterations by a time-integrated Ornstein-Uhlenbeck process. This framework is developed further to model sliding window decoding as a race between the integrated Ornstein-Uhlenbeck process and an absorbing barrier that corresponds to the left boundary of the sliding window. The proposed scaling laws yield accurate FER predictions.