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Large Deviations Performance of Consensus plus Innovations distributed detection With Non-Gaussian Observations

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2012年第11期60卷 5987-6002页

作者： Bajovic, Dragana Jakovetic, Dusan Moura, Jose M. F. Xavier, Joao Sinopoli, Bruno Univ Tecn Lisboa IST ISR Lisbon Portugal Carnegie Mellon Univ Dept Elect & Comp Engn Pittsburgh PA 15213 USA

We establish the large deviations asymptotic performance (error exponent) of consensus+innovations distributed detection over random networks with generic (non-Gaussian) sensor observations. At each time instant, sensors 1) combine theirs with the decision variables of their neighbors (consensus) and 2) assimilate their new observations (innovations). This paper shows for general non-Gaussian distributions that consensus+innovations distributed detection exhibits a phase transition behavior with respect to the network degree of connectivity. Above a threshold, distributed is as good as centralized, with the same optimal asymptotic detection performance, but, below the threshold, distributed detection is suboptimal with respect to centralized detection. We determine this threshold and quantify the performance loss below threshold. Finally, we show the dependence of the threshold and of the performance on the distribution of the observations: the asymptotic performance of distributed detectors over the same random network with different observations' distributions, for example, Gaussian, Laplace, or quantized, may be different, even though the asymptotic performance of the corresponding centralized detectors is the same.

关键词： Chernoff information consensus plus innovations distributed detection information flow large deviations non-Gaussian distributions performance analysis random network

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detection of Bad Data in Phasor Measurement Units Using distributed Approach

Detection of Bad Data in Phasor Measurement Units Using Dist...

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Conference on Innovations in Power and Advanced Computing Technologies (i-PACT)

作者： Thomas, Polly Skariah, Emil Ninan Varghese, Sheena Thomas Saintgits Coll Engn Dept Elect & Elect Engn Kottayam Kerala India

ISBN: (纸本)9781509056828

The chances for presence of bad data in Phasor measurement units are increasing due to complicated power system. Thus the voltage magnitude and phase angle obtained from PMU is no longer accurate. Hence it is important to detect the presence of bad data and identify the PMU which contains the error. In order to implement bad data detection and identification, state estimation is carried out to obtain the true state variables using weighted least square method. In this paper a distributed approach is chosen for identification of bad data. The system network is divided into different areas and the technique is applied to each area separately. The area and the meter which contains error is identified through this method. The system works in MATLAB platform.

关键词： power system state estimation Phasor measurement units distributed detection

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distributed LARGEST EIGENVALUE detection

DISTRIBUTED LARGEST EIGENVALUE DETECTION

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IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Ainomae, Ahti Trump, Tonu Bengtsson, Mats KTH Royal Inst Technol Stockholm Sweden Tallinn Univ Technol Tallinn Estonia

ISBN: (纸本)9781509041176

Cognitive radio (CR) systems need to detect the presence of a primary user (PU) signal by continuously sensing the spectrum area of interest. Radiowave propagation effects like fading and shadowing often complicate sensing of spectrum holes because the PU signal can be weak in a particular area. Cooperative spectrum sensing is seen as a prospective solution to enhance the detection of PU signals. In this paper we study distributed spectrum sensing, based on the largest eigenvalue of adaptively estimated correlation matrices (CMs) of received signals. The PU signal is assumed to be temporally correlated. In this paper an Combine and Adapt (CTA) least mean square (LMS) diffusion based mean vector estimation scheme is proposed. No fusion center (FC) for estimation or detection is used. We analyse the resulting detection performance and verify the theoretical findings through simulations.

关键词： Cognitive radio distributed estimation diffusion LMS distributed detection Spectrum Sensing

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Minimizing Misclassification for Cooperative Spectrum Sensing Using M-Ary Hypothesis Testing

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2019年第8期68卷 8210-8215页

作者： Ma, Yuan Quan, Zhi Li, Dong Zhang, Bojun Shenzhen Univ Coll Informat Engn Shenzhen 518060 Peoples R China Macau Univ Sci & Technol Fac Informat Technol Macau 999078 Peoples R China SAICT Shenzhen 518033 Peoples R China

In traditional spectrum sensing, binary hypothesis testing has been used to detect whether a frequency band is being occupied by the primary user or not. In this correspondence paper, we investigate M-ary hypothesis testing for spectrum sensing to further identify the signal type of the primary user. Linear cooperation among spatially distributed cognitive radios is applied to combine the observation statistics and make a final decision. The problem of data fusion is formulated as minimizing the total probability of misclassification subject to the constraint on the probability of successful classification. To deal with the non-convex problem formulated, we develop two solutions in this paper. In the first solution, we transform the problem into an unconstrained one, and adopt a zooming-based search algorithm to iteratively update multiple continuous variables until convergence. This solution requires searching all possible combinations of variables. To reduce the computation complexity and achieve closed-form analytical expressions, in the second solution, we decompose the original problem into multiple subproblems, each with the objective of minimizing an individual probability of misclassification. These subproblems can lead to closed-form expressions, and the weights are chosen as the best ones that correspond to the minimum total probability of misclassification. The proposed solutions are examined numerically, and the results show that the decomposition-based solution can achieve performance comparable to the zooming-based one but with much less complexity.

关键词： M-ary hypothesis testing nonconvex optimization signal classification distributed detection and cognitive communication networks

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2019年第8期67卷 2066-2079页

作者： Zhang, Shan Theagarajan, Lakshmi Narasimhan Choi, Sora Varshney, Pramod K. Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA Indian Inst Technol Palakkad Dept Elect Engn Kozhippara 678557 India Aptiv PLC Kokomo IN 46902 USA

In this paper, we propose a regular vine copula based methodology for the fusion of correlated decisions. Regular vine copula is an extremely flexible and powerful graphical model to characterize complex dependence among multiple modalities. It can express a multivariate copula by using a cascade of bivariate copulas, the so-called pair copulas. Assuming that local detectors are single threshold binary quantizers and taking complex dependence among sensor decisions into account, we design an optimal fusion rule using a regular vine copula under the Neyman-Pearson framework. In order to reduce the computational complexity resulting from the complex dependence, we propose an efficient and computationally light regular vine copula based optimal fusion algorithm. Numerical experiments are conducted to demonstrate the effectiveness of our approach.

关键词： distributed detection dependence modeling regular vine copula sensor fusion decision fusion

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A New Framework for distributed detection With Conditionally Dependent Observations

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2012年第3期60卷 1409-1419页

作者： Chen, Hao Chen, Biao Varshney, Pramod K. Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA

distributed detection with conditionally dependent observations is known to be a challenging problem in decentralized inference. This paper attempts to make progress on this problem by proposing a new framework for distributed detection that builds on a hierarchical conditional independence model. Through the introduction of a hidden variable that induces conditional independence among the sensor observations, the proposed model unifies distributed detection with dependent or independent observations. This new framework allows us to identify several classes of distributed detection problems with dependent observations whose optimal decision rules resemble the ones for the independent case. The new framework induces a decoupling effect on the forms of the optimal local decision rules for these problems, much in the same way as the conditionally independent case. This is in sharp contrast to the general dependent case where the coupling of the forms of local sensor decision rules often renders the problem intractable. Such decoupling enables the use of, for example, the person-by-person optimization approach to find optimal local decision rules. Two classical examples in distributed detection with dependent observations are reexamined under this new framework: detection of a deterministic signal in dependent noises and detection of a random signal in independent noises.

关键词： Dependent observations distributed detection likelihood quantizer

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Nonparametric distributed Sequential detection via Universal Source Coding

Nonparametric Distributed Sequential Detection via Universal...

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Information Theory and Applications (ITA) Workshop

作者： Sreedharan, Jithin K. Sharma, Vinod Indian Inst Sci Dept Elect Commun Engn Bangalore 560012 Karnataka India

ISBN: (纸本)9781467346481

We consider nonparametric or universal sequential hypothesis testing when the distribution under the null hypothesis is fully known but the alternate hypothesis corresponds to some other unknown distribution. These algorithms are primarily motivated from spectrum sensing in Cognitive Radios and intruder detection in wireless sensor networks. We use easily implementable universal lossless source codes to propose simple algorithms for such a setup. The algorithms are first proposed for discrete alphabet. Their performance and asymptotic properties are studied theoretically. Later these are extended to continuous alphabets. Their performance with two well known universal source codes, Lempel-Ziv code and KT-estimator with Arithmetic Encoder are compared. These algorithms are also compared with the tests using various other nonparametric estimators. Finally a decentralized version utilizing spatial diversity is also proposed and analysed.

关键词： Sequential Hypothesis Testing Universal Testing Universal Source Codes distributed detection

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On the Effectiveness of Multiple Antennas in distributed detection over Fading MACs

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2012年第5期11卷 1744-1752页

作者： Banavar, Mahesh K. Smith, Anthony D. Tepedelenlioglu, Cihan Spanias, Andreas Arizona State Univ Fulton Sch Engn SenSIP Ctr Sch Elect Comp & Energy Engn Tempe AZ 85287 USA L 3 Commun Salt Lake City UT USA

A distributed detection problem over fading Gaussian multiple-access channels is considered. Sensors observe a phenomenon and transmit their observations to a fusion center using the amplify and forward scheme. The fusion center has multiple antennas with different channel models considered between the sensors and the fusion center, and different cases of channel state information are assumed at the sensors. The performance is evaluated in terms of the error exponent for each of these cases, where the effect of multiple antennas at the fusion center is studied. When there is channel information at the sensors, the gain in error exponent due to having multiple antennas at the fusion center is shown to be limited to a factor of 8/pi for Rayleigh fading channels between the sensors and the fusion center, and independent of the number of antennas at the fusion center. Simple practical schemes and numerical methods using semidefinite relaxation techniques are presented that utilize the limited possible gains available. Simulations are used to establish the accuracy of the results.

关键词： distributed detection fading channels error exponent wireless sensor network performance bounds

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A REVIEW OF SENSING AND distributed detection ALGORITHMS FOR COGNITIVE RADIO SYSTEMS

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INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS 2012年第1期5卷 177-190页

作者： Viswanathan, Ramanarayanan Ahsant, Babak Southern Illinois Univ Dept Elect & Comp Engn Carbondale IL 62901 USA

Optimized spectrum sensing using distributed detection techniques for secondary user spectrum access is becoming important in Cognitive Radio (CR) systems, which have been proposed to utilize the available frequency spectrum more efficiently. For achieving best performance and ensuring minimal acceptable interference to spectrum owners, it is important to accurately sense and detect the presence or absence of primary licensed users. For this purpose, the solutions learned within the framework of distributed detection in wireless sensor networks have been considered. In this paper, we review sensing algorithms and approaches of distributed detection and their relevance to CR systems.

关键词： Wireless Sensor Networks Sensing Techniques distributed detection Cognitive Radio

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Disconnection-aware Attack detection in Networked Control Systems ⁎

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IFAC-PapersOnLine 2020年第2期53卷 3515-3520页

作者： Hampei Sasahara Takayuki Ishizaki Jun-ichi Imura Henrik Sandberg KTH Royal Institute of Technology Stockholm SE-100 44 Sweden Tokyo Institute of Technology Tokyo 1528552 Japan

This study deals with security issues in dynamical networked control systems. The goal is to establish a unified framework of the attack detection stage, which includes the four processes of monitoring the system state, making a decision based on the monitored signal, disconnecting the corrupted subsystem, and operating the remaining system during restoration. This paper, in particular, considers a disconnection-aware attack detector design problem. Traditionally, observer-based attack detectors are designed based on the system model with a fixed network topology and cannot cope with a change of the topology caused by disconnection. The disconnection-aware design problem is mathematically formulated and a solution is proposed in this paper. A numerical example demonstrates the effectiveness of the proposed detector through an inverter-based voltage control system in a benchmark model.

关键词： detection algorithms distributed detection large-scale systems networks on-line security analysis system security

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