Chase-like Decoding: Test Pattern Design and Performance Analysis

TL;DR

This paper evaluates and improves Chase-like decoding algorithms for algebraic codes by analyzing test pattern sets and proposing a new design that enhances decoding performance for high-rate BCH codes.

Contribution

It introduces a new algorithm for designing test pattern sets that outperform standard sets by up to 0.2 dB for high-rate BCH codes.

Findings

Test pattern sets with specific structures are effectively evaluated using order statistics.

Arbitrary test pattern sets' performance can be assessed via space coverage probabilities and Monte Carlo simulations.

The proposed test pattern design improves decoding performance by up to 0.2 dB for high-rate BCH codes.

Abstract

Chase-like decoding algorithms are a popular choice for soft-input decoding of algebraic codes. In this paper, we evaluate the performance of different test pattern sets using three methods. For test pattern sets with a certain structure such as Chase-II test patterns and patterns up to a maximum logistic weight, we use a method that relies on order statistics. The performance of arbitrary sets of test patterns is evaluated by calculating covered space probabilities and via direct Monte Carlo simulation. Based on the idea of covering as many likely error patterns as possible, we propose an algorithm for the design of test pattern sets which perform up to 0.2$\,$dB better for high-rate BCH codes than commonly used test pattern sets.