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

作者： Xu, Zhenhua Huang, Jianguo Zhang, Qunfei Northwestern Polytech Univ Coll Marine Engn Xian 710072 Peoples R China

ISBN: (纸本)9781479903566

In this paper, we consider the problem of power constrained partially coherent distributed detection over fading multiaccess channel. The deflection coefficient maximization (DCM) is used to optimize the performance of detectors. Two cases of the channel gain information are considered separately at the fusion center, one case with perfect channel gain (the corresponding method is referred to as PC-DCM, with PC being the abbreviation for "partially coherent"), the other case with statistical information of channel gain (the corresponding method is referred to as PC-DCM-CS, with CS being the abbreviation for "channel statistics"). We derive the closed-form solutions to the considered problems. Monte-Carlo simulations are carried out to verify the performance of the proposed methods. Simulation results show that the proposed new methods could significantly improve the detection performance of the fusion system at low signal-to-noise ratio (SNR).

关键词： distributed detection partially coherent deflection coefficient maximization power constraint multiaccess channel

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distributed Combining Techniques for distributed detection in Fading Wireless Sensor Networks 2

Distributed Combining Techniques for Distributed Detection i...

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2nd IEEE Middle East and North Africa COMMunications Conference (IEEE MENACOMM)

作者： Aldalahmeh, Sami Al-Jazzar, Saleh O. McLernon, Des Zaidi, Syed Ali Raza Cardenas, Marco Al Zaytoonah Univ Jordan Fac Engn & Technol Amman Jordan Univ Leeds Sch Elect & Elect Engn Leeds W Yorkshire England Autonomous Univ San Luis Potosi Fac Sci Mexico City DF Mexico

ISBN: (纸本)9781728136875

We investigate distributed combining techniques for distributed detection in wireless sensor networks (WSNs) over Rayleigh fading multiple access channel (MAC). The MAC also suffers from with path loss and additive noise. The WSN is modelled as a Poisson point process (PPP). Two distributed transmit combining techniques are proposed to mitigate fading;distributed equal gain transmit combining (ddEGTC) and distributed maximum ratio transmit combining (dMRTC). The performance of the previous methods is analysed using stochastic geometry tools, where the mean and variance of the detector's test statistic are found thus enabling the fitting of the received signal distribution by a log-normal distribution. Surprisingly, simulation results show a that ddEGTC outperforms dMRTC.

关键词： Wireless sensor networks distributed detection multiple access channel distributed transmit combining stochastic geometry

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Adaptive retransmission with balanced load for fault-tolerant distributed detection in wireless sensor networks

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JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 2007年第4期23卷 1141-1154页

作者： Pai, Hung-Ta Sung, Jing-Tian Han, Yunghsiang S. Natl Taiwan Univ Grad Inst Commun Engn Sanhsia 237 Taiwan Natl Taiwan Univ Sci Technol Dept Elect Engn Taipei 106 Taiwan

A fault-tolerant classification system in wireless sensor networks combining distributed detection with error-correcting codes has recently been proposed. Associated with a decision pattern, each sensor makes a local decision based on its detection result and a set of decision thresholds. The detection result must then be transmitted to a fusion center to make a final decision. The probability of misclassification when adopting this approach is high when the transmission channel is highly noisy. This work first describes an adaptive retransmission algorithm to reduce the misclassification probability. The fusion center calculates the reliability of each local decision received while making the final decision. If the final decision is not reliable, then the fusion center asks the sensor that has sent the received local decision with the lowest reliability to retransmit its decision. However, when some sensors have unrecognized faults, the fusion center tends to query the sensor with the same decision pattern as the faulty sensor to retransmit its decision. This tendency causes unbalanced network load. This work further presents a novel adaptive retransmission algorithm with balanced load to combat this problem. Each sensor carries all sets of decision thresholds. A sensor is randomly selected when the decision based on a set of thresholds must be retransmitted. The selected sensor then makes its new decision according to the threshold set and its detection result. The random selection means the load is balanced. Simulation results show that the misclassification probability can be effectively decreased through the retransmission with a balanced load.

关键词： wireless sensor networks retransmission fault-tolerant balanced load distributed detection

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Hard Decision Based distributed detection in Multi-Sensor System over Noise Correlated Sensing Channels 50

Hard Decision Based Distributed Detection in Multi-Sensor Sy...

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50th Annual Conference on Information Science and Systems (CISS)

作者： Kasasbeh, Hadi Cao, Lei Viswanathan, Ramanarayanan Univ Mississippi Dept Elect Engn University MS 38677 USA

ISBN: (纸本)9781467394574

In spite of the spectrum sensing importance, small part of the literature deals with the case of dependency between sensors' observations. In this paper, Bayes criterion for minimizing the probability of error (P-e) is used to find the distributed decision rule at each sensor in a binary hypothesis multi-sensor system, while considering the correlation over the sensing channels. This paper proposes a new, simple, yet efficient algorithm to find the local decision rules to achieve the objective of minimizing the Pe. Upon receiving the signal, each sensor sends a local hard decision to the fusion center (FC). The FC then generates a global decision using the K-out-of-N majority rule. The derived problem formulation and the proposed algorithm can be used with any joint probability density functions and with any odd number of sensors. The proposed framework also accounts for the path attenuation effect on the global decision. The results show the effectiveness and validity of the proposed framework in practical sensor systems.

关键词： distributed detection Correlated Sensing Spectrum Sensing Hard Decision

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Anonymous Heterogeneous distributed detection: Optimal Decision Rules, Error Exponents, and the Price of Anonymity

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IEEE TRANSACTIONS ON INFORMATION THEORY 2019年第11期65卷 7390-7406页

作者： Chen, Wei-Ning Wang, I-Hsiang Natl Taiwan Univ Grad Inst Commun Engn Taipei 10617 Taiwan Natl Taiwan Univ Dept Elect Engn Taipei 10617 Taiwan

We explore the fundamental limits of heterogeneous distributed detection in an anonymous sensor network with n sensors and a single fusion center. The fusion center collects the single observation from each of the n sensors to detect a binary parameter. The sensors are clustered into multiple groups, and different groups follow different distributions under a given hypothesis. The key challenge for the fusion center is the anonymity of sensors-although it knows the exact number of sensors and the distribution of observations in each group, it does not know which group each sensor belongs to. It is hence natural to consider it as a composite hypothesis testing problem. First, we propose an optimal test called mixture likelihood ratio test, which is a randomized threshold test based on the ratio of the uniform mixture of all the possible distributions under one hypothesis to that under the other hypothesis. Optimality is shown by first arguing that there exists an optimal test that is symmetric, that is, it does not depend on the order of observations across the sensors, and then proving that the mixture likelihood ratio test is optimal among all symmetric tests. Second, we focus on the Neyman-Pearson setting and characterize the error exponent of the worst-case type-II error probability as n tends to infinity, assuming the number of sensors in each group is proportional to n. Finally, we generalize our result to find the collection of all achievable type-I and type-II error exponents, showing that the boundary of the region can be obtained by solving an optimization problem. Our results elucidate the price of anonymity in heterogeneous distributed detection, and can be extended to M-ary hypothesis testing with heterogeneous observations generated according to hidden latent variables.

关键词： distributed detection anonymity error exponent large deviation

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Sequential distributed detection via Level-Triggered Sampling in Underwater Wireless Sensor Networks

Sequential Distributed Detection via Level-Triggered Samplin...

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Oceans Aberdeen Conference

作者： Hu, Li Wang, Shilian Zhang, Eryang Natl Univ Def Technol Coll Elect Sci & Engn Changsha Hunan Peoples R China

ISBN: (纸本)9781509052783

In implementations of distributed detection based on underwater wireless sensor networks (UWSN), a few technique challenges are faced. Among them is the strict limited communication ability of local sensors due to constrained bandwidth as well as energy, and the severe synchronization error among sensors which makes data fusion in the fusion center (FC) difficult. To solve the above problems to some extent, a sequential distributed detection (SDD) scheme based on level-triggered sampling (LTS) mechanism is proposed. In the LTS-SDD scheme, sequential test method is applied in both sensors and the FC, then the distributed detection system works with asynchronous sampling among sensors and low-speed communication between sensors and the FC. Though potential, the proposed scheme faced some unaddressed challenges when used in practical underwater distributed detection system, which are also discussed in the paper. To validate the suggested scheme, distributed detection of weak single frequency signal via UWSN is studied under some assumptions. Corresponding simulation results show that the LTS-SDD scheme works well and its error performance as well as average decision delay performance is superior to sequential detection (SD) scheme with single sensor.

关键词： underwater wireless sensor networks level-triggered sampling sequential test SPRT distributed detection

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An Energy Allocation Method of Nodes in Energy Harvesting distributed detection System 4

An Energy Allocation Method of Nodes in Energy Harvesting Di...

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4th International Conference on Integrated Circuits and Microsystems (ICICM)

作者： Liu Fei Liu Xiangyang Qi Zhengwei Natl Univ Def Technol Coll Informat & Commun Xian 710106 Shanxi Peoples R China

ISBN: (纸本)9781728151328

In the distributed detection system with energy harvesting, the uncertainty of node energy makes the optimal allocation of sensing and communication energy a challenge. This paper analyzed the influence of sensing uncertainty and communication uncertainty on detection system performance. The joint optimization of single slot node energy between sensing and communication was carried out by Monte Carlo simulation. The energy allocation method of nodes with the highest detection probability received by fusion center was determined, which laid a foundation for the establishment of node energy management strategy.

关键词： energy harvesting distributed detection energy allocation

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Research on a distributed detection system model and its application in engineering 11

Research on a distributed detection system model and its app...

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IEEE 11th Conference on Industrial Electronics and Applications (ICIEA)

作者： Xia Wenyue Yuan Haiwen Beijing Univ Aeronaut & Astronaut Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China

ISBN: (纸本)9781467386449

To analyze the distributed detection systems in complicated application environments theoretically and overcome the disadvantages, where a high-general and abstract model is lacking for the analysis, guidance and visualized description, a distributed network architecture model from the design point of view of the top level of the system was proposed. We define and analyze our model based on the theory of network calculus. Quantitative description formulas are derived, and the performance analysis method of distributed detection systems based on our distributed network architecture models is established. As validated by the real project, our method is effective and efficient in modeling and analyzing complicated distributed detection systems, which also has been shown general, abstract, guidable for quickly realize of the system.

关键词： distributed detection Network architecture Network calculus Analysis model UHVDC Corona current

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A NOVEL FRAMEWORK FOR distributed detection WITH DEPENDENT OBSERVATIONS

A NOVEL FRAMEWORK FOR DISTRIBUTED DETECTION WITH DEPENDENT O...

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2010 IEEE International Conference on Acoustics, Speech, and Signal Processing

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

ISBN: (纸本)9781424442966

In this paper, we present a unifying framework for distributed detection with dependent or independent observations. This novel framework utilizes an expanded hierarchical model by introducing a hidden variable. Facilitated by this new framework, we identify several classes of distributed detection problems with conditionally dependent observations whose optimal sensor signaling structure resembles that of the independent case. These classes of problems exhibit a decoupling effect on the form of the optimal local decision rules, much in the same way as the conditionally independent case using both the Bayesian and the Neyman-Pearson criteria.

关键词： distributed detection Dependent Observation Hierarchical Independence Model Quantization

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On Optimal Fusion Architecture For a Two-Sensor Tandem distributed detection System

On Optimal Fusion Architecture For a Two-Sensor Tandem Distr...

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IEEE Global Conference on Signal and Information Processing (GlobalSIP)

作者： Akofor, Earnest Chen, Biao Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA

ISBN: (纸本)9781479902484

The paper revisits the classical problem of determining the optimal communication direction in a two-sensor fusion system. For the problem of signal detection in additive Gaussian noises, the paper attempts to reconcile the difference in existing literature about which sensor ought to serve as the fusion center for optimal detection performance. While there has been no general conclusion as to which direction is preferred for general detection problems, we establish that for the aforementioned Gaussian problem, having the better sensor, i.e., the sensor with higher signal to noise power ratio, serving as the fusion center is preferred for better detection performance. This is true for the cases of both deterministic signal detection and the Gaussian random signal detection.

关键词： distributed detection communication direction dependent observations Bayesian decision

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