Bayesian Design of Decentralized Hypothesis Testing Under Communication Constraints
2014 (English)In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014, IEEE Signal Processing Society, 2014, -7628 p.Conference paper (Refereed)
We consider a distributed detection system under communication constraints, where several peripheral nodes observe a common phenomenon and send their observations to a fusion center via error-free but rate-constrained channels. Using the minimum expected error probability as a design criterion, we propose a cyclic procedure for the design of the peripheral nodes using the person-by-person methodology. It is shown that a fine-grained binning idea together with a method for updating the conditional probabilities of the joint index space at the fusion center, decrease the complexity of the algorithm and make it tractable. Also, unlike previous methods which use dissimilarity measures (e.g., the Bhattacharyya distance), a-prior hypothesis probabilities are allowed to contribute to the design in the proposed method. The performance of the proposed method is comparedto a method due to Longo et al.’s and it is shown that the new method can significantly outperform the previous one at a comparable complexity.
Place, publisher, year, edition, pages
IEEE Signal Processing Society, 2014. -7628 p.
Decentralized detection, Bayesian criterion, parallel network, person-by-person optimization
IdentifiersURN: urn:nbn:se:kth:diva-143804DOI: 10.1109/ICASSP.2014.6855083ISI: 000343655307132ScopusID: 2-s2.0-84905245189OAI: oai:DiVA.org:kth-143804DiVA: diva2:708762
IEEE Int. Conf. Acoustics, Speech, Signal Process (ICASSP'14)4-9 May 2014,Florence, Italy
QC 201412032014-03-282014-03-282015-01-21Bibliographically approved