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Tarighati, A., Gross, J. & Jaldén, J. (2017). Decentralized Hypothesis Testing in Energy Harvesting Wireless Sensor Networks. IEEE Transactions on Signal Processing, 65(18), 4862-4873
Open this publication in new window or tab >>Decentralized Hypothesis Testing in Energy Harvesting Wireless Sensor Networks
2017 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 65, no 18, p. 4862-4873Article in journal (Refereed) Published
Abstract [en]

We consider the problem of decentralized hypothesis testing in a network of energy harvesting sensors, where sensors make noisy observations of a phenomenon and send quantized information about the phenomenon towards a fusion center. The fusion center makes a decision about the present hypothesis using the aggregate received data during a time interval. We explicitly consider a scenario under which the messages are sent through parallel access channels towards the fusion center. To avoid limited lifetime issues, we assume each sensor is capable of harvesting all the energy it needs for the communication from the environment. Each sensor has an energy buffer (battery) to save its harvested energy for use in other time intervals. Our key contribution is to formulate the problem of decentralized detection in a sensor network with energy harvesting devices. Our analysis is based on a queuing-theoretic model for the battery and we propose a sensor decision design method by considering long term energy management at the sensors. We show how the performance of the system changes for different battery capacities. We then numerically show how our findings can be used in the design of sensor networks with energy harvesting sensors.

Place, publisher, year, edition, pages
IEEE, 2017
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-208654 (URN)10.1109/TSP.2017.2716909 (DOI)000405705900013 ()2-s2.0-85023178804 (Scopus ID)
Note

QC 20170706

Available from: 2017-06-10 Created: 2017-06-10 Last updated: 2024-03-18Bibliographically approved
Tarighati, A., Gross, J. & Jaldén, J. (2016). Decentralized Detection in Energy Harvesting Wireless Sensor Networks. In: 2016 24TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO): . Paper presented at 24th European Signal Processing Conference (EUSIPCO), AUG 28-SEP 02, 2016, Budapest, HUNGARY (pp. 567-571). IEEE conference proceedings
Open this publication in new window or tab >>Decentralized Detection in Energy Harvesting Wireless Sensor Networks
2016 (English)In: 2016 24TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), IEEE conference proceedings, 2016, p. 567-571Conference paper, Published paper (Refereed)
Abstract [en]

We consider a decentralized hypothesis testing problem in which several peripheral energy harvesting sensors are arranged in parallel. Each sensor makes a noisy observation of a time varying phenomenon, and sends a message about the present hypothesis towards a fusion center at each time instance t. The fusion center, using the aggregate of the received messages during the time instance t, makes a decision about the state of the present hypothesis. We assume that each sensor is an energy harvesting device and is capable of harvesting all the energy it needs to communicate from its environment. Our contribution is to formulate and analyze the decentralized detection problem when the energy harvesting sensors are allowed to form a long term energy usage policy. Our analysis is based on a queuing-theoretic model for the battery. Then, by using numerical simulations, we show how the resulting performance differs from the energy-unconstrained case.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2016
Series
European Signal Processing Conference, ISSN 2076-1465
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-201278 (URN)10.1109/EUSIPCO.2016.7760312 (DOI)000391891900111 ()2-s2.0-85005959803 (Scopus ID)978-0-9928-6265-7 (ISBN)
Conference
24th European Signal Processing Conference (EUSIPCO), AUG 28-SEP 02, 2016, Budapest, HUNGARY
Note

QC 20170215

Available from: 2017-02-15 Created: 2017-02-15 Last updated: 2022-06-27Bibliographically approved
Tarighati, A., Gross, J. & Jalden, J. (2016). Distributed detection in energy harvesting wireless sensor networks. In: European Signal Process. Conf. (EUSIPCO), Aug. 2016: . Paper presented at European Signal Process. Conf. (EUSIPCO). August 29-Sept. 2, 2016. Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Distributed detection in energy harvesting wireless sensor networks
2016 (English)In: European Signal Process. Conf. (EUSIPCO), Aug. 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016Conference paper, Published paper (Refereed)
Abstract [en]

We consider a decentralized hypothesis testing problem in which several peripheral energy harvesting sensors arearranged in parallel. Each sensor makes a noisy observation of a time varying phenomenon, and sends a message about the present hypothesis towards a fusion center at each time instance t. The fusion center, using the aggregate of the received messages during the time instance t, makes a decision about the state of the present hypothesis. We assume that each sensor is an energy harvesting device and is capable of harvesting all the energy it needs to communicate from its environment. Our contribution is to formulate and analyze the decentralized detection problem when the energy harvesting sensors are allowed to form a long term energy usage policy. Our analysis is based on a queuing-theoretic model for the battery. Then, by using numerical simulations, we show how the resulting performance differs from the energy-unconstrained case.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-189862 (URN)
External cooperation:
Conference
European Signal Process. Conf. (EUSIPCO). August 29-Sept. 2, 2016
Note

QC 20160907

Available from: 2016-07-20 Created: 2016-07-20 Last updated: 2024-03-18Bibliographically approved
Tarighati, A. & Jalden, J. (2016). Optimality of Rate Balancing in Wireless Sensor Networks. IEEE Transactions on Signal Processing, 64(14)
Open this publication in new window or tab >>Optimality of Rate Balancing in Wireless Sensor Networks
2016 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 64, no 14Article in journal (Refereed) Published
Abstract [en]

We consider the problem of distributed binary hypothesis testing in a parallel network topology where sensors independently observe some phenomenon and send a finite rate summary of their observations to a fusion center for the final decision. We explicitly consider a scenario under which (integer) rate messages are sent over an error free multiple access channel, modeled by a sum rate constraint at the fusion center. This problem was previously studied by Chamberland and Veeravalli, who provided sufficient conditions for the optimality of one bit sensor messages. Their result is however crucially dependent on the feasibility of having as many one bit sensors as the (integer) sum rate constraint of the multiple access channel, an assumption that can often not be satisfied in practice. This prompts us to consider the case of an a-priori limited number of sensors and we provide sufficient condition under which having no two sensors with rate difference more than one bit, so called rate balancing, is an optimal strategy with respect to the Bhattacharyya distance between the hypotheses at the input to the fusion center. We further discuss explicit observation models under which these sufficient conditions are satisfied.

Place, publisher, year, edition, pages
IEEE Signal Processing Society, 2016
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-184672 (URN)10.1109/TSP.2016.2551691 (DOI)000377370500014 ()2-s2.0-84974633341 (Scopus ID)
Note

QC 20160414

Available from: 2016-04-02 Created: 2016-04-02 Last updated: 2022-06-23Bibliographically approved
Tarighati, A. & Jalden, J. (2015). Bayesian Design of Tandem Networks for Distributed Detection With Multi-bit Sensor Decisions. IEEE Transactions on Signal Processing, 63(7), 1821-1831
Open this publication in new window or tab >>Bayesian Design of Tandem Networks for Distributed Detection With Multi-bit Sensor Decisions
2015 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 63, no 7, p. 1821-1831Article in journal (Refereed) Published
Abstract [en]

We consider the problem of decentralized hypothesis testing under communication constraints in a topology where several peripheral nodes are arranged in tandem. Each node receives an observation and transmits a message to its successor, and the last node then decides which hypothesis is true. We assume that the observations at different nodes are, conditioned on the true hypothesis, independent and the channel between any two successive nodes is considered error-free but rate-constrained. We propose a cyclic numerical design algorithm for the design of nodes using a person-by-person methodology with the minimum expected error probability as a design criterion, where the number of communicated messages is not necessarily equal to the number of hypotheses. The number of peripheral nodes in the proposed method is in principle arbitrary and the information rate constraints are satisfied by quantizing the input of each node. The performance of the proposed method for different information rate constraints, in a binary hypothesis test, is compared to the optimum rate-one solution due to Swaszek and a method proposed by Cover, and it is shown numerically that increasing the channel rate can significantly enhance the performance of the tandem network. Simulation results for $M$-ary hypothesis tests also show that by increasing the channel rates the performance of the tandem network significantly improves.

Place, publisher, year, edition, pages
IEEE Signal Processing Society, 2015
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Signal Processing
Identifiers
urn:nbn:se:kth:diva-159597 (URN)10.1109/TSP.2015.2401535 (DOI)000350880900016 ()2-s2.0-84924674518 (Scopus ID)
Note

QC 201502010

Available from: 2015-02-05 Created: 2015-02-05 Last updated: 2022-06-23Bibliographically approved
Tarighati, A. & Jaldén, J. (2015). Rate Allocation for Decentralized Detection in Wireless Sensor Networks. In: 16th IEEE International Workshop on Signal Processing Advances in Wireless Communications, Stockholm, June 28 - July 1, 2015: . Paper presented at IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), June 28 -July 1 2015, Stockholm, Sweden (pp. 341-345). IEEE conference proceedings
Open this publication in new window or tab >>Rate Allocation for Decentralized Detection in Wireless Sensor Networks
2015 (English)In: 16th IEEE International Workshop on Signal Processing Advances in Wireless Communications, Stockholm, June 28 - July 1, 2015, IEEE conference proceedings, 2015, p. 341-345Conference paper, Published paper (Refereed)
Abstract [en]

We consider the problem of decentralized detection where peripheral nodes make noisy observations of a phenomenon and send quantized information about the phenomenon towards a fusion center over a sum-rate constrained multiple access channel. The fusion center then makes a decision about the state of the phenomenon based on the aggregate received data. Using the Chernoff information as a performance metric, Chamberland and Veeravalli previously studied the structure of optimal rate allocation strategies for this scenario under the assumption of an unlimited number of sensors. Our key contribution is to extend these result to the case where there is a constraint on the maximum number of active sensors. In particular, we find sufficient conditions under which the uniform rate allocation is an optimal strategy, and then numerically verify that these conditions are satisfied for some relevant sensor design rules under a Gaussian observation model.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2015
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-165257 (URN)10.1109/SPAWC.2015.7227056 (DOI)000380547100069 ()2-s2.0-84953389066 (Scopus ID)
External cooperation:
Conference
IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), June 28 -July 1 2015, Stockholm, Sweden
Note

QC 20150904

Available from: 2015-04-24 Created: 2015-04-24 Last updated: 2022-06-23Bibliographically approved
Tarighati, A. & Jalden, J. (2014). A General Method for the Design of Tree Networks Under Communication Constraints. In: Information Fusion (FUSION), 2014 17th International Conference on: . Paper presented at 17th Int. Conf. Information Fusion,7-10 July 2014, Salamanca, Spain. IEEE conference proceedings
Open this publication in new window or tab >>A General Method for the Design of Tree Networks Under Communication Constraints
2014 (English)In: Information Fusion (FUSION), 2014 17th International Conference on, IEEE conference proceedings, 2014, , p. 7p. -7Conference paper, Published paper (Refereed)
Abstract [en]

We consider a distributed detection system with communication constraints, where several nodes are arranged in an arbitrary tree topology, under the assumption of conditionally independent observations. We propose a cyclic design procedure using the minimum expected error probability as a design criterion while adopting a person-by-person methodology. We design each node jointly together with the fusion center, while other nodes are kept fixed, and show that the design of each node using the person-by-person methodology is analogous to the design of a network with two nodes, a network which we refer to as the restricted model. We further show how the parameters in the restricted model for the design of a node in the tree network can be found in a computationally efficient manner. The proposed numerical methodology can be applied for the design of nodes arranged in arbitrary tree topologies with arbitrary channel rates for the links between nodes and for a general M-ary hypothesis testing problem.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2014. p. 7
Keywords
Decentralized detection, Bayesian criterion, tree topology, person-by-person optimization
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-145647 (URN)000363896100324 ()2-s2.0-84910665324 (Scopus ID)978-849012355-3 (ISBN)
Conference
17th Int. Conf. Information Fusion,7-10 July 2014, Salamanca, Spain
Note

QC 20141208

QC 20151214

Available from: 2014-05-23 Created: 2014-05-23 Last updated: 2022-06-23Bibliographically approved
Tarighati, A. & Jalden, J. (2014). Bayesian Design of Decentralized Hypothesis Testing Under Communication Constraints. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014: . Paper presented at IEEE Int. Conf. Acoustics, Speech, Signal Process (ICASSP'14)4-9 May 2014,Florence, Italy. IEEE Signal Processing Society
Open this publication in new window or tab >>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, p. -7628Conference 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
Keywords
Decentralized detection, Bayesian criterion, parallel network, person-by-person optimization
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-143804 (URN)10.1109/ICASSP.2014.6855083 (DOI)000343655307132 ()2-s2.0-84905245189 (Scopus ID)
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: 2022-06-23Bibliographically approved
Tarighati, A., Farhadi, H. & Lahouti, F. (2010). Performance Analysis of Noisy Message-Passing Decoding of Low-Density Parity-Check Codes. In: 6th International Symposium on Turbo Codes & Iterative Informayion Processing: . Paper presented at 6th International Symposium on Turbo Codes & Iterative Informayion Processing, Brest, France, September 6-10, 2010.
Open this publication in new window or tab >>Performance Analysis of Noisy Message-Passing Decoding of Low-Density Parity-Check Codes
2010 (English)In: 6th International Symposium on Turbo Codes & Iterative Informayion Processing, 2010Conference paper, Published paper (Refereed)
Abstract [en]

A noisy message-passing decoding scheme isconsidered for low-density parity-check (LDPC) codes overadditive white Gaussian noise (AWGN) channels. The internaldecoder noise is motivated by the quantization noise in digitalimplementations or the intrinsic noise of analog LDPC decoders.We modelled the decoder noise as AWGN on the exchangedmessages in the iterative LDPC decoder. This is shown to renderthe message densities in the noisy LDPC decoder inconsistent.We then invoke Gaussian approximation and formulate a twodimensionaldensity evolution analysis for the noisy LDPCdecoder. This allows for not only tracking the mean, but also thevariance of the message densities, and hence, quantifying thethreshold of the LDPC code. According to the results, a decodernoise of unit variance, increases the threshold for a regular (3,6) code by 1.672dB.

National Category
Communication Systems Telecommunications
Identifiers
urn:nbn:se:kth:diva-44528 (URN)
Conference
6th International Symposium on Turbo Codes & Iterative Informayion Processing, Brest, France, September 6-10, 2010
Note

QC 20111111

Available from: 2011-10-24 Created: 2011-10-24 Last updated: 2024-03-18Bibliographically approved
Kazemi, K., Ghadimi, S., Lyaghat, A., Tarighati, A., Golshaeyan, N., Abrishami-Moghaddam, H., . . . Wallois, F. (2009). Automatic Fontanel Extraction from Newborns' CT Images Using Variational Level set. In: Jiang, X, Petkov, N (Ed.), COMPUTER ANALYSIS OF IMAGES AND PATTERNS, PROCEEDINGS: . Paper presented at 13th International Conference on Computer Analysis of Images and Patterns. Munster, GERMANY. SEP 02-04, 2009 (pp. 639-646). Springer Berlin/Heidelberg
Open this publication in new window or tab >>Automatic Fontanel Extraction from Newborns' CT Images Using Variational Level set
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2009 (English)In: COMPUTER ANALYSIS OF IMAGES AND PATTERNS, PROCEEDINGS / [ed] Jiang, X, Petkov, N, Springer Berlin/Heidelberg, 2009, p. 639-646Conference paper, Published paper (Refereed)
Abstract [en]

A realistic head model is needed for source localization methods used for the study of epilepsy in neonates applying Electroencephalographic (EEG) measurements from the scalp. The earliest models consider the head as a series of concentric spheres, each layer corresponding to a different tissue whose conductivity is assumed to be homogeneous. The results of the source reconstruction depend highly on the electric conductivities of the tissues forming the head.The most used model is constituted of three layers (scalp, skull, and intracranial). Most of the major bones of the neonates’ skull are ossified at birth but can slightly move relative to each other. This is due to the sutures, fibrous membranes that at this stage of development connect the already ossified flat bones of the neurocranium. These weak parts of the neurocranium are called fontanels. Thus it is important to enter the exact geometry of fontaneles and flat bone in a source reconstruction because they show pronounced in conductivity. Computer Tomography (CT) imaging provides an excellent tool for non-invasive investigation of the skull which expresses itself in high contrast to all other tissues while the fontanels only can be identified as absence of bone, gaps in the skull formed by flat bone. Therefore, the aim of this paper is to extract the fontanels from CT images applying a variational level set method. We applied the proposed method to CT-images of five different subjects. The automatically extracted fontanels show good agreement with the manually extracted ones.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2009
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 5702
Keywords
newborns, fontanel, source reconstruction, level set, segmentation.
National Category
Medical Image Processing
Identifiers
urn:nbn:se:kth:diva-91215 (URN)10.1007/978-3-642-03767-2_78 (DOI)000273458100078 ()2-s2.0-70349330895 (Scopus ID)978-3-642-03766-5 (ISBN)
Conference
13th International Conference on Computer Analysis of Images and Patterns. Munster, GERMANY. SEP 02-04, 2009
Note

QC 20120312

Available from: 2012-03-09 Created: 2012-03-09 Last updated: 2022-06-24Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-1569-3527

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