Practical Short-Length Coding Schemes for Binary Distributed Hypothesis Testing

TL;DR

This paper develops practical short-length binary coding schemes for distributed hypothesis testing, providing analytical error expressions and demonstrating their effectiveness through numerical validation.

Contribution

It introduces practical short-length binary coding schemes for DHT using linear block codes and derives exact analytical error probabilities.

Findings

Analytical expressions match numerical results

Proposed schemes outperform baseline methods

Effective for practical DHT implementations

Abstract

This paper investigates practical coding schemes for Distributed Hypothesis Testing (DHT). While the literature has extensively analyzed the information-theoretic performance of DHT and established bounds on Type-II error exponents through quantize and quantize-binning achievability schemes, the practical implementation of DHT coding schemes has not yet been investigated. Therefore, this paper introduces practical implementations of quantizers and quantize-binning schemes for DHT, leveraging short-length binary linear block codes. Furthermore, it provides exact analytical expressions for Type-I and Type-II error probabilities associated with each proposed coding scheme. Numerical results show the accuracy of the proposed analytical error probability expressions, and enable to compare the performance of the proposed schemes.