A new approach to distributed hypothesis testing

Abstract : A distributed hypothesis testing problem is considered, where the goal is to declare the distribution of two random variables, based on their observations. Defining two error events, the error exponent of Type II is studied under a fixed constraint over the error of type I. A novel approach is presented, based on random binning. The benefits of this approach are demonstrated through an example, compared to a more traditional approach, as well as to a different binned decoding method. These performance gains are then generalized to a large set of probability distributions.
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Contributor : Pablo Piantanida <>
Submitted on : Monday, January 16, 2017 - 5:14:03 PM
Last modification on : Thursday, April 5, 2018 - 12:30:05 PM



Gil Katz, Pablo Piantanida, Merouane Debbah. A new approach to distributed hypothesis testing. 50th Asilomar Conference on Signals, Systems and Computers, Oct 2016, San Francisco, United States. ⟨10.1109/acssc.2016.7869599 ⟩. ⟨hal-01436813⟩



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