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43rd Annual Conference on Information Sciences and Systems

作者： Lin, Ying Li, Mingyan SUNY Coll New Paltz Dept Elect & Comp Engn New Paltz NY 12561 USA Boeing Phantom Works Seattle WA USA

ISBN: (纸本)9781424427338

We consider in this paper a single-channel wireless sensor network (WSN) where communication among sensor nodes are subject to jamming by an attacker. In particular, we address the detection of a jamming event, and investigate the optimal network defense strategy to mitigate jamming effects. A multiple-monitor distributed detection structure is considered. The optimal detection scheme is developed under the Bayesian criterion, with the goal of minimizing the error probability of detection at a fusion center. For the optimal network defense strategy, we formulate and solve the design problem using a constrained maximization problem by jointly considering Quality-of-Service and resource constraints of WSNs such as communication throughput, energy, and delay.

关键词： distributed detection jamming attacks network security

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distributed detection of Generalized Gaussian Sparse Signals with One-Bit Measurements (Poster) 22

Distributed Detection of Generalized Gaussian Sparse Signals...

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22nd International Conference on Information Fusion (FUSION)

作者： Wang, Xueqian Li, Gang Quan, Chen Varshney, Pramod K. Tsinghua Univ Elect Engn Beijing Peoples R China Syracuse Univ Elect Engn & Comp Sci Syracuse NY USA

ISBN: (纸本)9780996452786

In this paper, distributed detection of sparse stochastic signals with one-bit measurements is studied. We assume that both the noise and the dominant elements in sparse signals follow the generalized Gaussian (GG) distribution. Due to constrained bandwidth/energy in sensor networks, the local sensors send binary measurements instead of analog data to the fusion center. First, we propose the locally most powerful test (LMPT) detector based on one-bit measurements for distributed detection of sparse signals. Then, we analytically derive near-optimal one-bit quantizers at the local sensor nodes using the log-concave approximation of the efficacy. Simulation results corroborate our theoretical analysis and show that, the proposed one-bit LMPT detector with analytically obtained one-bit quantizers provides detection performance which is comparable to that with numerically obtained optimal quantizers in the GG case.

关键词： Generalized Gaussian distribution distributed detection Sparse signals Locally most powerful tests One-bit Quantizers Sensor networks

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distributed detection in a Wireless Sensor Network Using Hybrid MAC

Distributed Detection in a Wireless Sensor Network Using Hyb...

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77th IEEE Vehicular Technology Conference (VTC)

作者： Liu, Ju-Chieh Chou, Po-Heng Chung, Char-Dir Natl Taiwan Univ Grad Inst Commun Engn Taipei 10617 Taiwan

ISBN: (纸本)9781467363372

In this paper, distributed detection is investigated in a wireless sensor network (WSN) using the hybrid multiple-access channel (MAC) which is a composite of orthogonal and nonorthogonal MACs. Specifically, a simple ideal sensing (IS) fusion rule is proposed, and the corresponding detection error probability upper bound and approximate system outage probability are analytically derived. Performance results show that the IS fusion rule provides nearly minimum detection error probability under high sensor observation signal-to-noise power ratios, and offers a diversity gain in system outage probability which is equal to the number of orthogonal channels. Moreover, the hybrid MAC WSN with IS fusion rule is shown to provide more performance choices than orthogonal and nonorthogonal MAC WSNs with IS fusion rule in terms of detection error probability and system outage probability.

关键词： distributed detection detection error probability multiple-access channel system outage probability wireless sensor network

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OPTIMUM distributed detection OF WEAK SIGNALS IN DEPENDENT SENSORS

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IEEE TRANSACTIONS ON INFORMATION THEORY 1992年第3期38卷 1066-1079页

作者： BLUM, RS KASSAM, SA UNIV PENN DEPT ELECT ENGNMOORE SCH ELECT ENGNPHILADELPHIAPA 19104

Locally optimum (LO) distributed detection is considered for observations that are dependent from sensor to sensor. LO detection has been extensively studied for classical detection scenarios but general results for LO distributed detection, specifically for dependent sensor observations, have been lacking. The necessary conditions are presented for the LO distributed sensor detector designs and fusion rule for an N sensor parallel distributed detection system with dependent sensor observations, and specific solutions are obtained for a random signal in additive noise detection problem with two sensors. These solutions indicate that the LO sensor detector nonlinearities, in general, contain a term proportional to f'/f, where f is the noise probability density function (pdf). The importance of this term varies with the additive noise pdf and the false alarm probability. For some non-Gaussian pdfs, the new term is significant and causes the LO sensor detector nonlinearities to be nonsymmetric even for symmetric pdfs. LO solutions are presented for finite sample sizes and the LO solutions are discussed in the asymptotic case. These results are extended to yield the form of the solutions for the N sensor LO random signal distributed detection problem, that yields expected generalizations of the two sensor results.

关键词： LOCALLY OPTIMUM distributed detection DECENTRALIZED detection DEPENDENT OBSERVATIONS RANDOM SIGNAL detection

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Near-Optimal distributed detection in Balanced Binary Relay Trees

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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2017年第4期4卷 826-837页

作者： Zhang, Zhenliang Chong, Edwin K. P. Pezeshki, Ali Moran, Bill Howard, Stephen D. Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen 518055 Peoples R China Colorado State Univ Dept Elect & Comp Engn Ft Collins CO 80523 USA RMIT Univ Melbourne Vic 3000 Australia Def Sci & Technol Grp Edinburgh SA 5111 Australia

We study the distributed detection problem in a balanced binary relay tree, where the leaves of the tree are sensors generating binary messages. The root of the tree is a fusion center that makes an overall decision. Every other node in the tree is a relay node that fuses binary messages from its two child nodes into a new binary message and sends it to the parent node at the next level. We assume that the relay nodes at the same level use identical fusion rule. The goal is to find a string of fusion rules used at all the levels in the tree that maximizes the reduction in the total error probability between the leaf nodes and the fusion center. We formulate this problem as a deterministic dynamic program and express the optimal strategy in terms of Bellman's equation. Moreover, we use the notion of string-submodularity to show that the reduction in the total error probability is a string-submodular function. Consequentially, we show that the greedy strategy, which only maximizes the level-wise reduction in the total error probability, performs at least within a factor (1-1/e) of the optimal strategy in terms of reduction in the total error probability, even if the nodes and links in the trees are subject to random failures.

关键词： Bayesian social learning distributed detection greedy strategy submodular function

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distributed detection of information flows in chaff

Distributed detection of information flows in chaff

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IEEE International Symposium on Information Theory

作者： He, Ting Tong, Lang Cornell Univ Sch Elect & Comp Engn Ithaca NY 14853 USA

ISBN: (纸本)9781424413973

distributed detection of information flows is considered. The detector detects the presence of information flows by collecting timing information from nodes of interest through channels of finite capacity. The information flows are assumed to be perturbed up to a bounded delay and interleaved with chaff. Joint compression and detection schemes are proposed to achieve reliable detection with inaccurate measurements. detection performance is analytically evaluated by robustness against chaff as functions of the capacity constraints in the data collection. The proposed detectors are proved to be optimal for their corresponding quantizers. A comparison of their performance gives guidelines on quantizer design.

关键词： information flow detection robust detection algorithms quantizer design distributed detection

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distributed detection in Cognitive Radio Networks

Distributed Detection in Cognitive Radio Networks

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作者： AHTI AINOMAE KTH Royal Institute of Technology

学位级别：博士

One of the problems with the modern radio communication is the lack of available radio frequencies. Recent studies have shown that, while the available licensed radio spectrum becomes more occupied, the assigned spectrum is significantly underuti- lized. To alleviate the situation, cognitive radio (CR) technology has been proposed to provide an opportunistic access to the licensed spectrum areas. Secondary CR systems need to cyclically detect the presence of a primary user by continuously sensing the spectrum area of interest. Radiowave propagation effects like fading and shadowing often complicate sensing of spectrum holes. When spectrum sensing is performed in a cooperative manner, then the resulting sensing performance can be improved and stabilized. In this thesis, two fully distributed and adaptive cooperative Primary User (PU) detection solutions for CR networks are studied. In the first part of this thesis we study a distributed energy detection scheme without using any fusion center. Due to reduced communication such a topology is more energy efficient. We propose the usage of distributed, diffusion least mean square (LMS) type of power estimation algorithms with different network topolo- gies. We analyze the resulting energy detection performance by using a common framework and verify the theoretical findings through simulations. In the second part of this thesis we propose a fully distributed detection scheme, based on the largest eigenvalue of adaptively estimated correlation matrices, assum- ing that the primary user signal is temporally correlated. Different forms of diffusion LMS algorithms are used for estimating and averaging the correlation matrices over the CR network. The resulting detection performance is analyzed using a common framework. In order to obtain analytic results on the detection performance, the adaptive correlation matrix estimates are approximated by a Wishart distribution. The theoretical findings are verified through simulations.

关键词： Cognitive Radio distributed estimation distributed detection Diffusion LMS Diffusion Networks Adaptive Networks Spectrum Sensing Energy detection Random Matrix Largest Eigenvalue detection

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distributed detection with Unreliable Reporting Channels: Quantize or Not Quantize? 57

Distributed Detection with Unreliable Reporting Channels: Qu...

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57th Annual Conference on Information Sciences and Systems, CISS 2023

作者： Cao, Lei Viswanathan, Ramanarayanan University of Mississippi Dept. of Electrical and Computer Engineering OxfordMS38677 United States

ISBN: (纸本)9781665451819

It is known that reporting the raw data observed at sensors to the fusion center completely and without any channel distortion always performs better than reporting the quantized data. However, when channel noise exists as it is always in practice, we show whether it is optimal to send the unquantized raw data or quantized data is a very interesting question that requires more research efforts. We compare these two schemes under the constraints of using the same transmission power and the bandwidth where analog modulation is assumed per channel use. The detection performance with one sensor and two sensors is presented in terms of the Bayes error. The performance of using asymptotically many sensors is compared with the Chernoff information. What presented in the paper could open up a new perspective in the design of the optimal distributed detection systems. © 2023 IEEE.

关键词： centralized or decentralized distributed detection quantize or not quantize

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Robustness of the Counting Rule for distributed detection in Wireless Sensor Networks

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IEEE SIGNAL PROCESSING LETTERS 2018年第8期25卷 1191-1195页

作者： Goel, Abhinav Patel, Adarsh Nagananda, Kyatsandra G. Varshney, Pramod K. Peoples Educ Soc Univ Dept Elect & Commun Engn Bangalore 560085 Karnataka India Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA Univ Calif Irvine Dept Elect Engn & Comp Sci Irvine CA 92697 USA

We consider the problem of energy-efficient distributed detection to infer the presence of a target in a wireless sensor network and analyze its robustness to modeling uncertainties. The sensors make noisy observations of the target's signal power, which follows the isotropic power-attenuation model. Binary local decisions of the sensors are transmitted to a fusion center, where a global inference regarding the target's presence is made, based on the counting rule. We consider uncertain knowledge of: I) the signal decay exponent of the wireless medium;2) the power attenuation constant;and 3) the distance between the target and the sensors. For a given degree of uncertainty, we show that there exists a limit on the target's signal power below which the distributed detector fails to achieve the desired performance regardless of the number of sensors deployed. Simulation results are presented to determine the level of sensitivity of the detector to uncertainty in these parameters. The results throw light on the limits of robustness for distributed detection, akin to "SNR walls" for classical detection.

关键词： Counting rule distributed detection energy efficiency robust sensing sensitivity

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Evolution of distributed detection performance over balanced binary relay tree networks with bit errors

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NONLINEAR DYNAMICS 2022年第4期107卷 3903-3917页

作者： Tian, Yu-Ping Zhu, Wenbo Hangzhou Dianzi Univ Sch Automat Hangzhou 310018 Peoples R China Southeast Univ Sch Automat Nanjing 210096 Peoples R China

Target detection based on wireless sensor networks can be considered as a distributed binary hypothesis testing problem. In this paper, the evolution of detection error probability with the increase in the network scale is studied for the balanced binary relay tree network with channel noise. Firstly, the iterative expressions of false-alarm probability and missed-detection probability depending on the number of tree network layers are given. Then, the iterative process of two types of error probabilities in the network space is described as a discrete nonlinear switched dynamic system, and the dynamic properties of two types of error probabilities are analyzed in a plane rectangular coordinate system. A globally attractive invariant set of the state of the dynamic system, which is not related to the channel noise, is derived. The switching mode of the system and the total error probability in the invariant set are further analyzed, and a necessary and sufficient convergence condition of the total error probability is provided. Based on this condition, the following detection properties of the network are revealed: (1) as long as the channel bit error probability is not zero, the total error probability does not tend to zero as the network size grows to infinity;(2) when the channel bit error probability is greater than 2-root 3/2, the total error probability will continue to increase with the increase in the network size.

关键词： distributed detection distributed hypothesis testing Nonlinear switched system Invariant set Channel noise

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