Asymptotic results for detection in power constrained wireless sensor networks

This work studies a binary decentralized detection problem in which a set of parallel sensors provides partial information about the state of nature to a fusion center. Sensors have access to conditionally independent and identically distributed observations, given the state of nature, and transmit their data over a noisy channel. Upon reception of the information, the fusion center attempts to accurately reconstruct the state of nature. We extend existing asymptotic results about large sensor networks to the case where the sensors are subject to a joint power constraint and the communication channel from each sensor to the fusion center is corrupted by additive noise. Large deviation theory is used to show that having identical sensors, i.e., each sensor using the same transmission scheme, is asymptotically optimal.