  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.
