Chase-like Decoding: Test Pattern Design and Performance Analysis
For researchers working on soft-input decoding of algebraic codes, this work provides an improved test pattern design method with modest performance gains.
The paper evaluates test pattern sets for Chase-like decoding of algebraic codes and proposes a new design algorithm that achieves up to 0.2 dB gain for high-rate BCH codes over commonly used test patterns.
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 performs up to 0.2\,dB better for high-rate BCH codes than commonly used test patterns.