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.

翻译：本文研究了分布式假设检验（DHT）的实用编码方案。尽管现有文献已广泛分析了DHT的信息论性能，并通过量化与量化-分箱可实现方案建立了II类错误指数的界，但DHT编码方案的实际实现尚未得到探究。因此，本文引入基于短长度二元线性分组码的量化器与量化-分箱方案的实用实现方法。此外，针对每种提出的编码方案，本文给出了I类与II类错误概率的精确解析表达式。数值结果验证了所提错误概率解析表达式的准确性，并使得能够对比各方案性能。