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.

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.

Sign in / Sign up

Export Citation Format

Share Document