A Sequential Problem in Decentralized Detection with Communication

TL;DR

This paper investigates a sequential decentralized detection problem involving two observers with noisy measurements, analyzing optimal stopping policies under different communication scenarios and extending to multiple sensors.

Contribution

It introduces a parametric framework for optimal policies in sequential decentralized detection with communication constraints and extends it to multiple sensors.

Findings

Optimal policies characterized for both scenarios.

Methodology for finding these policies is provided.

Extensions to larger communication alphabets and multiple sensors.

Abstract

A sequential problem in decentralized detection is considered. Two observers can make repeated noisy observations of a binary hypothesis on the state of the environment. At any time, observer 1 can stop and send a final binary message to observer 2 or it may continue to take more measurements. Every time observer 1 postpones its final message to observer 2, it incurs a penalty. Observer 2's operation under two different scenarios is explored. In the first scenario, observer 2 waits to receive the final message from observer 1 and then starts taking measurements of its own. It is then faced with a stopping problem on whether to stop and declare a decision on the hypothesis or to continue taking measurements. In the second scenario, observer 2 starts taking measurements from the beginning. It is then faced with a different stopping problem. At any time, observer 2 can decide whether to stop and declare a decision on the hypothesis or to continue to take more measurements and wait for observer 1 to send its final message. Parametric characterization of optimal policies for the two observers are obtained under both scenarios. A sequential methodology for finding the optimal policies is presented. The parametric characterizations are then extended to problem with increased communication alphabet for the final message from observer 1 to observer 2; and to the case of multiple peripheral sensors that each send a single final message to a coordinating sensor who makes the final decision on the hypothesis.