The Asymmetric Hamming Bidistance and Distributions over Binary Asymmetric Channels
2026-04-09 • Information Theory
Information Theory
AI summaryⓘ
The authors study a communication model where the chance of flipping a 0 to a 1 differs from flipping a 1 to a 0, called the binary asymmetric channel. They introduce a new way to measure differences between codewords, called asymmetric Hamming bidistance, that looks at errors in both directions separately. This new measure helps to better analyze and bound decoding error probabilities, especially when older methods give similar results for different codes. The authors also calculate these new distributions for various special code families to show how their approach works.
binary asymmetric channelmaximum-likelihood decodingasymmetric Hamming bidistanceerror probabilityweight distributionprojective codesstrongly regular graphsassociation schemesbalanced incomplete block designsnonlinear codes
Authors
Shukai Wang, Cuiling Fan, Chunming Tang, Zhengchun Zhou
Abstract
The binary asymmetric channel is a model for practical communication systems where the error probabilities for symbol transitions $0\rightarrow 1$ and $1\rightarrow0$ differ substantially. In this paper, we introduce the notion of asymmetric Hamming bidistance (AHB) and its two-dimensional distribution, which separately captures directional discrepancies between codewords. This finer characterization enables a more discriminative analysis of decoding the error probabilities for maximum-likelihood decoding (MLD), particularly when conventional measures, such as weight distributions and existing discrepancy-based bounds, fail to distinguish code performance. Building on this concept, we derive a new upper bound on the average error probability for binary codes under MLD and show that, in general, it is incomparable with the two existing bounds derived by Cotardo and Ravagnani (IEEE Trans. Inf. Theory, 68 (5), 2022). To demonstrate its applicability, we compute the complete AHB distributions for several families of codes, including two-weight and three-weight projective codes (with the zero codeword removed) via strongly regular graphs and 3-class association schemes, as well as nonlinear codes constructed from symmetric balanced incomplete block designs (SBIBDs).