Clustered Decentralized Binary Detection: An Information-Theoretic Approach

Provided by: Institute of Electrical & Electronic Engineers
Topic: Mobility
Format: PDF
This paper presents an information-theoretic approach to decentralized binary detection in sensor networks. In particular, the authors consider a Bayesian approach for the minimization of the probability of decision error. Two scenarios are considered: a scenario where clusters are identical (uniform clustering) and a scenario where clusters are different (non-uniform clustering). The performance analysis obtained with a classical "Communication-theoretic" approach is extended to the "Information-theoretic" realm using the concept of mutual information. They then propose a simplified Binary Symmetric Channel (BSC) model to analyze the clustered schemes, and they show that it allows to accurately predict their realistic performance.

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