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Abstract:
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The sequential hypothesis testing problem is studied in sensor networks, where a set of sensor receive independent observations and send summary messages to the fusion center, which makes a final decision. In the scenario where the sensors have full access to their past observations, the first of asymptotically optimal sequential tests in the literature is developed, and the proposed test has same asymptotic performance as the optimal centralized test that has access to all the sensor observations. Next, in the scenario where the sensors do not have full access to their past observations, a simple but asymptotically optimal sequential tests is developed, in which sensor message functions are what we call tandem quantizer, where each sensor only uses two different sensor quantizers with at most one switch between these two quantizers.
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