Distributed Estimation in Wireless Sensor Networks With an Interference Canceling Fusion Center

2016 ◽  
Vol 15 (3) ◽  
pp. 2205-2214 ◽  
Author(s):  
Antonios Argyriou ◽  
Ozgu Alay
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Distributed Estimation ◽  
Wireless Sensor ◽  
Fusion Center

scholarly journals Repeated Game for Distributed Estimation in Autonomous Clustered Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-8
Author(s):  
Guiyun Liu ◽  
Yonggui Liu ◽  
Jing Yao ◽  
Hongbin Chen ◽  
Dong Tang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Repeated Games ◽  
Repeated Game ◽  
Distributed Estimation ◽  
Wireless Sensor ◽  
Fusion Center ◽  
Equilibrium Strategies ◽  
Finitely Repeated Games ◽  
Nash Equilibrium Strategies

A commonly encountered problem in wireless sensor networks (WSNs) applications is to reconstruct the state of nature, that is, distributed estimation of a parameter of interest through WSNs’ observations. However, the distributed estimation in autonomous clustered WSNs faces a vital problem of sensors’ selfishness. Each sensor autonomously decides whether or not to transmit its observations to the fusion center (FC) and not be controlled by the fusion center (FC) any more. Thus, to encourage cooperation within selfish sensors, infinitely and finitely repeated games are firstly modeled to depict sensors’ behaviors. Then, the existences of Nash equilibriums for infinitely and finitely repeated games are discussed. Finally, simulation results show that the proposed Nash equilibrium strategies are effective.

Robust Decentralized and Distributed Estimation of a Correlated Parameter Vector in MIMO-OFDM Wireless Sensor Networks

2021 ◽  
pp. 1-1
Author(s):  
Kunwar Pritiraj Rajput ◽  
Mohammad Faisal Ahmed ◽  
Naveen K. D. Venkategowda ◽  
Aditya K. Jagannatham ◽  
Govind Sharma ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Distributed Estimation ◽  
Wireless Sensor ◽  
Parameter Vector ◽  
Mimo Ofdm

scholarly journals Pseudo-Random Encryption for Security Data Transmission in Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2452 ◽  
Author(s):  
Liang Liu ◽  
Wen Chen ◽  
Tao Li ◽  
Yuling Liu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Fusion ◽  
Data Transmission ◽  
Multiple Scales ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Fusion Center ◽  
Inverse Mapping ◽  
The Matrix

The security of wireless sensor networks (WSN) has become a great challenge due to the transmission of sensor data through an open and wireless network with limited resources. In the paper, we discussed a lightweight security scheme to protect the confidentiality of data transmission between sensors and an ally fusion center (AFC) over insecure links. For the typical security problem of WSN’s binary hypothesis testing of a target’s state, sensors were divided into flipping and non-flipping groups according to the outputs of a pseudo-random function which was held by sensors and the AFC. Then in order to prevent an enemy fusion center (EFC) from eavesdropping, the binary outputs from the flipping group were intentionally flipped to hinder the EFC’s data fusion. Accordingly, the AFC performed inverse flipping to recover the flipped data before data fusion. We extended the scheme to a more common scenario with multiple scales of sensor quantification and candidate states. The underlying idea was that the sensor measurements were randomly mapped to other quantification scales using a mapping matrix, which ensured that as long as the EFC was not aware of the matrix, it could not distract any useful information from the captured data, while the AFC could appropriately perform data fusion based on the inverse mapping of the sensor outputs.

scholarly journals Distributed parameter estimation in wireless sensor networks in the presence of fading channels and unknown noise variance

2018 ◽  
Vol 14 (9) ◽  
pp. 155014771880330
Author(s):  
Shoujun Liu ◽  
Kezhong Liu ◽  
Jie Ma ◽  
Wei Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Fading Channels ◽  
Expectation Maximization ◽  
Multiple Access ◽  
Expectation Maximization Algorithm ◽  
Wireless Sensor ◽  
Fusion Center ◽  
Noise Variance ◽  
Access Scheme

Parameter estimation is one of the most important research areas in wireless sensor networks. In this study, we consider the problem of estimating a deterministic parameter over fading channels with unknown noise variance. Owing to the bandwidth constraints in wireless sensor networks, sensor observations are quantized and subsequently transmitted to the fusion center. Two types of communication channels are considered, namely, parallel-access channels and multiple-access channels. Based on the knowledge of channel statistics, the power of the received signals at the fusion center can be described by the mode of the exponential mixture distribution. The expectation maximization algorithm is used to determine maximum likelihood solutions for this mixture model. A new estimator based on the expectation maximization algorithm is subsequently proposed. Simulation results show that this estimator exhibits superior performance compared to the method of moments estimator in both parallel- and multiple-access schemes. In addition, we determine that the parallel-access scheme outperforms the multiple-access scheme when the noise variance is small and it loses its superiority when the noise variance is large.

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