DocumentCode
1776103
Title
Received signal strength index estimation using Kalman Filter for fuzzy based transmission power control in wireless sensor networks
Author
Venugopal, Vinaya ; Ramakrishnan, Shankar
Author_Institution
Dept. of Instrum. Eng., Anna Univ., Chennai, India
fYear
2014
fDate
10-11 July 2014
Firstpage
81
Lastpage
86
Abstract
Received Signal Strength estimation plays a vital role for Transmission Power Control in Wireless Sensor Networks (WSN). The received signal from the wireless channel is attenuated by a lot of noises such as interference noise, additive white Gaussian noise and measurement noise. To obtained a noise free and accurate data RSSI estimation is very important. Here Fading Channel model is used to represent the real scenario of Wireless Channel for RSSI estimation for various noisy environment conditions such as high noise environment, medium noise environment and low noise environment. RSSI obtained for Kalman Filter (KF) estimation is very accurate, since it performs filtering along with estimation. This estimated RSSI plays a crucial role for deciding the next transmission power required for Fuzzy logic based Transmission Power Control (TPC). Thereby increasing the life time of WSN.
Keywords
AWGN; Kalman filters; RSSI; fuzzy logic; power control; telecommunication power management; wireless channels; wireless sensor networks; Kalman filter; WSN; additive white Gaussian noise; data RSSI estimation; fading channel model; fuzzy based transmission power control; interference noise; measurement noise; received signal strength index estimation; wireless channel; wireless sensor networks; Estimation; Kalman filters; Mathematical model; Noise; Noise measurement; Pragmatics; Wireless sensor networks; Kalman Filter; RSSI estimation; Transmission Power Control; Wireless Sensor Networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Control, Instrumentation, Communication and Computational Technologies (ICCICCT), 2014 International Conference on
Conference_Location
Kanyakumari
Print_ISBN
978-1-4799-4191-9
Type
conf
DOI
10.1109/ICCICCT.2014.6992934
Filename
6992934
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