Effective-SNR Estimation for Wireless Sensor Network Using Kalman Filter

Dai, Xuewu, Qin, Fei and Mitchell, John (2013) Effective-SNR Estimation for Wireless Sensor Network Using Kalman Filter. Ad Hoc Networks, 11 (3). pp. 944-958. ISSN 1570-8705

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Official URL: http://dx.doi.org/10.1016/j.adhoc.2012.11.002

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.

Item Type: Article
Uncontrolled Keywords: sensor networks, SNR, link quality, estimation, Kalman filter
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Physics and Electrical Engineering
Related URLs:
Depositing User: Daniel Dai
Date Deposited: 04 Jul 2014 14:27
Last Modified: 10 Feb 2016 04:45
URI: http://nrl.northumbria.ac.uk/id/eprint/16844

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