Qin, F;
Dai, X;
Mitchell, JE;
(2013)
Effective-SNR estimation for wireless sensor network using Kalman filter.
AD HOC NETWORKS
, 11
(3)
944 - 958.
10.1016/j.adhoc.2012.11.002.
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Abstract
In many Wireless Sensor Network (WSN) applications, the availability of a simple yet accurate estimation of the RF channel quality is vital. However, due to measurement noise and fading effects, it is usually estimated through probe or learning based methods, which result in high energy consumption or high overheads. We propose to make use of information redundancy among indicators provided by the IEEE 802.15.4 system to improve the estimation of the link quality. A Kalman filter based solution is used due to its ability to give an accurate estimate of the un-measurable states of a dynamic system subject to observation noise. In this paper we present an empirical study showing that an improved indicator, termed Effective-SNR, can be produced by combining Signal to Noise Ratio (SNR) and Link Quality Indicator (LQI) with minimal additional overhead. The estimation accuracy is further improved through the use of Kalman filtering techniques. Finally, experimental results demonstrate that the proposed algorithm can be implemented on resource constraints devices typical in WSNs.
Type: | Article |
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Title: | Effective-SNR estimation for wireless sensor network using Kalman filter |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1016/j.adhoc.2012.11.002 |
Publisher version: | http://dx.doi.org/10.1016/j.adhoc.2012.11.002 |
Language: | English |
Additional information: | This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
Keywords: | Sensor networks, SNR, Link quality, Estimation, Kalman filter |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
URI: | https://discovery.ucl.ac.uk/id/eprint/1396349 |
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