English

Improved Random-Binning Exponent for Distributed Hypothesis Testing

Information Theory 2025-08-26 v2 math.IT

Abstract

Consider the problem of distributed binary hypothesis testing with two terminals, where the decision is made at one of them (the "receiver"). We study the exponent of the error probability of the second type. Previously, an achievable exponent was derived by Shimokawa, Han, and Amari using a "quantization and binning" scheme. We propose a simple modification on the receiver's decision rule in this scheme to attain a better exponent.

Keywords

Cite

@article{arxiv.2306.14499,
  title  = {Improved Random-Binning Exponent for Distributed Hypothesis Testing},
  author = {Yuval Kochman and Ligong Wang},
  journal= {arXiv preprint arXiv:2306.14499},
  year   = {2025}
}

Comments

Updated version to appear in IEEE Transactions on Information Theory