An Achievable Rate Region for Hypothesis Testing and User Identification with Multiple Sources

Yachongka, Vamoua; Chou, Rémi A.; Yagi, Hideki

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https://hdl.handle.net/2142/130274 Copy

Description

Title

An Achievable Rate Region for Hypothesis Testing and User Identification with Multiple Sources

Author(s)

• Yachongka, Vamoua
• Chou, Rémi A.
• Yagi, Hideki

Issue Date

2025-09-17

Keyword(s)

• Biometric identification systems
• Hypothesis testing
• Identification rate
• Error exponent

Abstract

This paper studies a biometric identification system model with two distinct biometric sources, extending beyond the existing model that assumes all biometric sequences are drawn from a common source. We consider a scenario involving two user groups, where the biometric sequences in each group are generated from separate sources and stored in two corresponding databases. To identify an unknown user, the decoder first performs hypothesis testing to determine which database the observed sequence is correlated with, followed by user identification. The main contribution of this work is the derivation of an achievable rate region for the optimal trade-off between identification rates and error exponent of the type-II error probability under negligible type-I error probability, called the capacity region. When testing against independence, the capacity region is obtained and coincides with previous results in several special cases.

Publisher

Allerton Conference on Communication, Control, and Computing

Series/Report Name or Number

2025 61st Allerton Conference on Communication, Control, and Computing Proceedings

ISSN

2836-4503

Type of Resource

Text

Genre of Resource

Conference Paper/Presentation

Language

eng

Handle URL

https://hdl.handle.net/2142/130274&&

Copyright and License Information

Copyright 2025 owned by the authors.

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