Effect of Signal Propagation Model Calibration on Localization Performance Limits for Wireless Sensor Networks

2021 ◽  
pp. 1-1
Author(s):  
Bingpeng Zhou ◽  
Hing Cheung So ◽  
Shahid Mumtaz
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Model Calibration ◽  
Signal Propagation ◽  
Propagation Model ◽  
Wireless Sensor ◽  
Performance Limits ◽  
Localization Performance ◽  
Signal Propagation Model

The Hybrid HMM for RSS-Based Localization in Wireless Sensor Networks

2013 ◽  
Vol 347-350 ◽  
pp. 796-802 ◽  
Author(s):  
Yan Hong Zang ◽  
Jin Song Wang ◽  
Lin Ling ◽  
Pei Zhong Lu
Keyword(s):  
Wireless Sensor Networks ◽  
Hidden Markov ◽  
Signal Strength ◽  
Threshold Value ◽  
Signal Propagation ◽  
Propagation Model ◽  
Wireless Sensor ◽  
Node Localization ◽  
Localization Accuracy ◽  
Signal Propagation Model

We proposea method of RSS-base localization in WSN (Wireless Sensor Network), called Hybrid HMM, to improve the stabilityof node localization basedon RSS(Received Signal Strength).This model utilizesHMM(Hidden Markov Model) to takeinto account the time factor when receiving the RSS sequence, andconverts the action of ranging into an operationof classification.For the received RSS used for localization,our Hybrid HMMwill compare it withthe preset RSS threshold value, and put the result into one of two categories for subsequent processing: If the received value is higher than the threshold value, the distance value will be drawn from the signal propagation model. If lower, the information will be obtained from a trained HMM. Experimental results show that the Hybrid HMM method can greatly improve the localization accuracy.

Signal Propagation and Analysis in Wireless Underground Sensor Networks

2019 ◽  
Vol 41 ◽  
pp. 60-78
Author(s):  
Adamu Murtala Zungeru ◽  
Joseph Chuma ◽  
Mmoloki Mangwala ◽  
Boyce Sigweni ◽  
Oduetse Matsebe
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Magnetic Induction ◽  
Signal To Noise Ratio ◽  
Path Loss ◽  
Signal Propagation ◽  
Pulse Power ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Nonlinear Program

The most challenging issue in the design of wireless sensor networks for the application of localization in the underground environment, mostly for miner’s location, is the sensor nodes’ energy consumption, efficiency and communication. Underground Wireless Sensor Networks are active and promising area of application of Wireless Sensor Networks (WSNs), whereby sensor nodes perform sensing duties in the underground environment. Most of the communication techniques used in the underground environment experience a high path loss and hence, hinders the range needed for transmission. However, the available option to increase information transmission is to increase the transmission power which needs large size of apparatus which is also limited in the underground. To solve the mentioned problems, this paper proposed a Magnetic Induction based Pulse Power. Analytical results of the Magnetic Induction based Pulse Power with an ordinary magnetic induction communication technique show an improvement in Signal-to-Noise Ratio (SNR) and path loss with variation in distance between nodes and frequency of operation. This paper further formulates a nonlinear program to determine the optimal data (events) extraction in a grid based WUSNs.

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