检索结果-内蒙古大学图书馆

distributed detection of Binary Decisions with Collisions in a Large, Random Network

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2015年第6期63卷 1477-1489页

作者： Whipps, Gene T. Ertin, Emre Moses, Randolph L. US Army Res Lab Adelphi MD 20783 USA Ohio State Univ Dept Elect & Comp Engn Columbus OH 43210 USA

We consider the problem of distributed detection in a large network of sensors. A random number of sensor nodes are randomly deployed. Sensor nodes perform local detection tests and communicate detections over a multiple-access channel to a fusion center. The fusion center can recognize both successful communications and communication collisions in the channel. We derive decision rules for both perfect communications and a delay-constrained communications protocol, and show that each are functions of count statistics only. We derive analytical expressions that characterize the performance of the system in terms of detection performance. We analyze performance with respect to sensor density and with respect to communications delay. Simulation examples validate theoretical predictions with numerical results. We show that the detection performance improves with network density despite increasing communication collisions. In addition, we show that detection performance using the protocol model, with imperfect communications, rapidly converges to the perfect communications case as the number of communication slots increase.

关键词： Binary sensors distributed detection local vote point process random access random sensor network

来源：评论

学校读者我要写书评

暂无评论

distributed detection Over Gaussian Multiple Access Channels With Constant Modulus Signaling

引用

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2011年第6期59卷 2875-2886页

作者： Tepedelenlioglu, Cihan Dasarathan, Sivaraman Arizona State Univ Sch Elect Comp & Energy Engn Tempe AZ 85287 USA

A distributed detection scheme where the sensors transmit with constant modulus signals over a Gaussian multiple access channel is considered. The deflection coefficient of the proposed scheme is shown to depend on the characteristic function of the sensing noise and the error exponent for the system is derived using large deviation theory. Optimization of the deflection coefficient and error exponent are considered with respect to a transmission phase parameter for a variety of sensing noise distributions including impulsive ones. The proposed scheme is also favorably compared with existing amplify-and-forward and detect-and-forward schemes. The effect of fading is shown to be detrimental to the detection performance through a reduction in the deflection coefficient depending on the fading statistics. Simulations corroborate that the deflection coefficient and error exponent can be effectively used to optimize the error probability for a wide variety of sensing noise distributions.

关键词： Constant modulus deflection coefficient distributed detection error exponent multiple access channel

来源：评论

学校读者我要写书评

暂无评论

distributed detection in Sensor Networks Over Fading Channels With Multiple Antennas at the Fusion Centre

引用

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2014年第3期62卷 671-683页

作者： Nevat, Ido Peters, Gareth W. Collings, Iain B. Inst Infocomm Res Singapore 138632 Singapore UCL Dept Stat Sci London England CSIRO Math & Informat Sci Sydney NSW Australia CSIRO Wireless & Networking Tech Lab Sydney NSW Australia

We develop new and optimal algorithms for distributed detection in sensor networks over fading channels with multiple receive antennas at the Fusion Centre (FC). Sensors observe a hidden physical phenomenon over fading channels and transmit their observations using the amplify-and-forward scheme over fading channels to the FC which is equipped with multiple antennas. We derive the optimal decision rules and the associated probabilities of detection and false alarm for three scenarios of Channel State Information (CSI) availability. For the most difficult case of unknown CSI, we develop two new algorithms to derive the optimal decision rule. The first is based on a Gaussian approximation method where we quantify the approximation error and its rate of convergence (to a true Normal distribution) via a multivariate version of the Berry-Esseen bound. The second is based on a multivariate Saddle-point (Laplace) approximation which is obtained via a non-convex optimisation problem which is solved efficiently via Bayesian Expectation-Maximisation method. We show under which system configuration which algorithm is suitable and should be used. For cases where the distribution of the optimal decision rule can not be derived exactly, we develop a Laguerre series expansion to approximate the resulting distribution. The performance of the proposed algorithms is evaluated via analytic bounds and numerical simulations. We show that the detection performance of the proposed algorithms is significantly superior to a local vote decision fusion based algorithms.

关键词： Bayesian expectation maximization Berry-Esseen theorem distributed detection fading channels Laguerre polynomial Laplace method likelihood ratio test multiaccess communication sensor networks

来源：评论

学校读者我要写书评

暂无评论

distributed detection of Gauss-Markov signals using diffusion Kalman filtering

引用

SIGNAL PROCESSING 2018年 153卷 368-378页

作者： Pang, Feifei Dogancay, Kutluyil Zhang, Qunfei Northwestern Polytech Univ Sch Marine Sci & Technol Xian 710072 Shaanxi Peoples R China Univ South Australia Sch Engn Mawson Lakes SA 5095 Australia Univ South Australia Sch Informat Technol & Math Sci Inst Telecommun Res Mawson Lakes SA 5095 Australia

This paper addresses the problem of distributed detection of Gauss-Markov signals in adaptive networks, where nodes make individual decisions by exchanging information with their neighbours and no fusion centre is used. Relying on the connection between the log-likelihood ratio (LLR) and the innovations process, a distributed detection algorithm for Gauss-Markov signals is proposed based on diffusion Kalman filtering. To perform hypothesis testing, a LLR is constructed using the innovations estimated by the diffusion Kalman filter. The detection performance of the new algorithm is analysed by deriving approximate expressions for the probability of false alarm and detection. The mean and mean-square value of the test statistic, and the probability of detection and receiver operating characteristics of the algorithm are demonstrated by way of Monte Carlo simulations, where a good agreement between theoretical and simulation results is observed. Simulations also confirm the improved detection performance of the proposed algorithm over non-cooperative detection and show that the performance of the algorithm converges to that of the centralized scheme. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Gauss-Markov signals Adaptive networks distributed detection Diffusion scheme Kalman filter

来源：评论

学校读者我要写书评

暂无评论

distributed detection in Mobile Access Wireless Sensor Networks under Byzantine Attacks

引用

IEEE TRANSACTIONS ON PARALLEL AND distributed SYSTEMS 2014年第4期25卷 950-959页

作者： Abdelhakim, Mai Lightfoot, Leonard E. Ren, Jian Li, Tongtong Michigan State Univ Dept Elect & Comp Engn E Lansing MI 48824 USA Air Force Res Lab Dayton OH 45433 USA

This paper explores reliable data fusion in mobile access wireless sensor networks under Byzantine attacks. We consider the q-out-of-m rule, which is popular in distributed detection and can achieve a good tradeoff between the miss detection probability and the false alarm rate. However, a major limitation with it is that the optimal scheme parameters can only be obtained through exhaustive search, making it infeasible for large networks. In this paper, first, by exploiting the linear relationship between the scheme parameters and the network size, we propose simple but effective sub-optimal linear approaches. Second, for better flexibility and scalability, we derive a near-optimal closed-form solution based on the central limit theorem. Third, subjecting to a miss detection constraint, we prove that the false alarm rate of q-out-of-m diminishes exponentially as the network size increases, even if the percentage of malicious nodes remains fixed. Finally, we propose an effective malicious node detection scheme for adaptive data fusion under time-varying attacks;the proposed scheme is analyzed using the entropy-based trust model, and shown to be optimal from the information theory point of view. Simulation examples are provided to illustrate the performance of proposed approaches under both static and dynamic attacks.

关键词： Security in wireless sensor networks Byzantine attacks distributed detection

来源：评论

学校读者我要写书评

暂无评论

distributed detection for diversity reception of fading signals in noise

引用

IEEE TRANSACTIONS ON INFORMATION THEORY 1999年第1期45卷 158-164页

作者： Blum, RS Lehigh Univ Dept Comp Sci & Elect Engn Bethlehem PA 18015 USA

A multiple-antenna diversity scheme is investigated for digital communications. Antenna observations are immediately quantized and sent to a fusion center. At the fusion center, the quantized observations are combined to form a final, decision on which symbol was transmitted. The optimum reception scheme is described for the case where frequency-shift keying is employed and where slow Rayleigh fading and Gaussian additive noise are present. Two cases are studied. In the first case, an accurate estimate of the signal-to-noise ratio is available at each receiver. In the second case, estimates are not available. Results indicate that two- or three-bit quantizations may be most appropriate. Further, if binary decisions are made at each antenna, performance may not improve if an estimate of the signal-to-noise ratio is available at each antenna or if two antennas are used instead of one.

关键词： decentralized detection distributed detection noncoherent BFSK quantized diversity reception

来源：评论

学校读者我要写书评

暂无评论

distributed detection of Sparse Stochastic Signals With 1-Bit Data in Tree-Structured Sensor Networks

引用

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2020年 68卷 2963-2976页

作者： Li, Chengxi Li, Gang Varshney, Pramod K. Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA

In this paper, we consider the problem of detection of sparse stochastic signals based on 1-bit data with tree-structured sensor networks (TSNs). In the literature, distributed detection of sparse signals with parallel sensor networks (PSNs) has previously been studied, and detectors using the locally most powerful test (LMPT) strategies with analog data and 1-bit data have been proposed, respectively. However, parallel topology does not always reflect the practical scenario, such as in the case where some nodes are outside the communication range of the fusion center (FC). In this paper, we design a new detector for TSNs with extremely limited resources and let each local sensor node send 1-bit data to its immediate successor. For the proposed detector, we devise 1-bit quantizers at the local sensor nodes and the decision fusion rule with the 1-bit data collected at the FC, based on quantization of likelihood ratios and the LMPT strategy. We also present the procedure to obtain the near optimal quantization thresholds numerically for nodes at different levels by characterizing the detection performance in terms of the Fisher Information. In particular, in two-level two-degree (2L-2D) TSNs, compared with the analog LMPT detector with Q nodes that transmit analog data hierarchically, the proposed 1-bit LMPT detector asymptotically needs 1.74Q nodes to compensate for the performance loss induced by local quantization. Simulation results validate our theoretical analysis.

关键词： Detectors Quantization (signal) distributed databases Bandwidth Network topology Data models Testing distributed detection locally most powerful tests sparse signals tree-structured sensor networks 1-bit quantization

来源：评论

学校读者我要写书评

暂无评论

distributed detection via Gaussian Running Consensus: Large Deviations Asymptotic Analysis

引用

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2011年第9期59卷 4381-4396页

作者： Bajovic, Dragana Jakovetic, Dusan Xavier, Joao Sinopoli, Bruno Moura, Jose M. F. Univ Tecn Lisbon Inst Super Tecn IST Inst Syst & Robot ISR P-1049001 Lisbon Portugal Carnegie Mellon Univ Dept Elect & Comp Engn Pittsburgh PA 15213 USA

We study, by large deviations analysis, the asymptotic performance of Gaussian running consensus distributed detection over random networks;in other words, we determine the exponential decay rate of the detection error probability. With running consensus, at each time step, each sensor averages its decision variable with the neighbors' decision variables and accounts on-the-fly for its new observation. We show that: 1) when the rate of network information flow (the speed of averaging) is above a threshold, then Gaussian running consensus is asymptotically equivalent to the optimal centralized detector, i.e., the exponential decay rate of the error probability for running consensus equals the Chernoff information;and 2) when the rate of information flow is below a threshold, running consensus achieves only a fraction of the Chernoff information rate. We quantify this achievable rate as a function of the network rate of information flow. Simulation examples demonstrate our theoretical findings on the behavior of running consensus detection over random networks.

关键词： Chernoff information distributed detection information flow large deviations random network running consensus

来源：评论

学校读者我要写书评

暂无评论

distributed detection With Censoring Sensors Under Physical Layer Secrecy

引用

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2009年第5期57卷 1976-1986页

作者： Marano, Stefano Matta, Vincenzo Willett, Peter K. Univ Salerno DIIIE I-84084 Fisciano SA Italy Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

We consider distributed binary detection problems in which the remote sensors of a network implement a censoring strategy to fulfill energy constraints, and the network works under the attack of an eavesdropper. The attacker wants to discover the state of the nature scrutinized by the system, but the network implements appropriate countermeasures to make this task hopeless. The goal is to achieve perfect secrecy at the physical layer, making the data available at the eavesdropper useless for its detection task. Adopting as performance metric certain Ali-Silvey distances, we characterize the detection performance of the system under physical layer secrecy. Two communication scenarios are addressed: parallel access channels and a multiple access channel. In both cases the optimal operative points from the network perspective are found. The most economic operative solution is shown to lie in the asymptote of low energy regime. How the perfect secrecy requirement impacts on the achievable performances, with respect to the absence of countermeasures, is also investigated.

关键词： Attack countermeasure censoring nodes distributed detection physical-layer security

来源：评论

学校读者我要写书评

暂无评论

distributed detection With Empirically Observed Statistics

引用

IEEE TRANSACTIONS ON INFORMATION THEORY 2020年第7期66卷 4349-4367页

作者： He, Haiyun Zhou, Lin Tan, Vincent Y. F. Natl Univ Singapore Dept Elect & Comp Engn Singapore 119077 Singapore Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48109 USA Natl Univ Singapore Dept Math Singapore 119077 Singapore

Consider a distributed detection problem in which the underlying distributions of the observations are unknown;instead of these distributions, noisy versions of empirically observed statistics are available to the fusion center. These empirically observed statistics, together with source (test) sequences, are transmitted through different channels to the fusion center. The fusion center decides which distribution the source sequence is sampled from based on these data. For the binary case, we derive the optimal type-II error exponent given that the type-I error decays exponentially fast. The type-II error exponent is maximized over the proportions of channels for both source and training sequences. We conclude that as the ratio of the lengths of training to test sequences alpha tends to infinity, using only one channel is optimal. By calculating the derived exponents numerically, we conjecture that the same is true when alpha is finite under certain conditions. We relate our results to the classical distributed detection problem studied by Tsitsiklis, in which the underlying distributions are known. Finally, our results are extended to the case of m-ary distributed detection with a rejection option.

关键词： Training Bayes methods Noise measurement Indexes Testing Task analysis Compressors distributed detection error exponents training samples hypothesis testing

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：