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Bayesian Design of Decentralized Hypothesis Testing Under Communication Constraints
KTH, School of Electrical Engineering (EES), Signal Processing.ORCID iD: 0000-0003-1569-3527
KTH, School of Electrical Engineering (EES), Signal Processing.ORCID iD: 0000-0001-6630-243X
2014 (English)In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014, IEEE Signal Processing Society, 2014, -7628 p.Conference paper, Published paper (Refereed)
Abstract [en]

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.
Keyword [en]
Decentralized detection, Bayesian criterion, parallel network, person-by-person optimization
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-143804DOI: 10.1109/ICASSP.2014.6855083ISI: 000343655307132Scopus ID: 2-s2.0-84905245189OAI: oai:DiVA.org:kth-143804DiVA: diva2:708762
Conference
IEEE Int. Conf. Acoustics, Speech, Signal Process (ICASSP'14)4-9 May 2014,Florence, Italy
Note

QC 20141203

Available from: 2014-03-28 Created: 2014-03-28 Last updated: 2016-11-02Bibliographically approved
In thesis
1. Decentralized Hypothesis Testing in Sensor Networks
Open this publication in new window or tab >>Decentralized Hypothesis Testing in Sensor Networks
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Wireless sensor networks (WSNs) play an important role in the future ofInternet of Things IoT systems, in which an entire physical infrastructurewill be coupled with communication and information technologies. Smartgrids, smart homes, and intelligent transportation systems are examples ofinfrastructure that will be connected with sensors for intelligent monitoringand management. Thus, sensing, information gathering, and efficientprocessing at the sensors are essential.

An important problem in wireless sensor networks is that of decentralizeddetection. In a decentralized detection network, spatially separatedsensors make observations on the same phenomenon and send informationabout the state of the phenomenon towards a central processor. The centralprocessor (or the fusion center, FC) makes a decision about the state of thephenomenon, base on the aggregate received messages from the sensors. Inthe context of decentralized detection, the object is often to make the bestdecision at the FC. Since this decision is made based on the received messagesfrom the sensors, it is of interest to optimally design decision rules atthe remote sensors.

This dissertation deals mainly with the problem of designing decisionrules at the remote sensors and at the FC, while the network is subjectto some limitation on the communication between nodes (sensors and theFC). The contributions of this dissertation can be divided into three (overlapping)parts. First, we consider the case where the network is subjectto communication rate constraint on the links connecting different nodes.Concretely, we propose an algorithm for the design of decision rules at thesensors and the FC in an arbitrary network in a person-by-person (PBP)methodology. We first introduce a network of two sensors, labeled as therestricted model. We then prove that the design of sensors’ decision rules,in the PBP methodology, is in an arbitrary network equivalent to designingthe sensors’ decision rules in the corresponding restricted model. We alsopropose an efficient algorithm for the design of the sensors’ decision rules inthe restricted model.

Second, we consider the case where remote sensors share a commonmultiple access channel (MAC) to send their messages towards the FC, andwhere the MAC channel is subject to a sum rate constraint. In this situation,ithe sensors compete for communication rate to send their messages. Wefind sufficient conditions under which allocating equal rate to the sensors,so called rate balancing, is an optimal strategy. We study the structure ofthe optimal rate allocation in terms of the Chernoff information and theBhattacharyya distance.

Third, we consider a decentralized detection network where not onlyare the links between nodes subject to some communication constraints,but the sensors are also subject to some energy constraints. In particular,we study the network under the assumption that the sensors are energyharvesting devices that acquire all the energy they need to transmit theirmessages from their surrounding environment. We formulate a decentralizeddetection problem with system costs due to the random behavior of theenergy available at the sensors in terms of the Bhattacharyya distance.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2016. 50 p.
Series
TRITA-EE, ISSN 1653-5146
National Category
Signal Processing
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-195173 (URN)978-91-7729-185-5 (ISBN)
Public defence
2016-11-30, F3, Lindstedtsvagen, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20161103

Available from: 2016-11-03 Created: 2016-11-02 Last updated: 2016-11-16Bibliographically approved

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