CCI-based link quality estimation mechanism for wireless sensor networks under non-perceived packet loss

• Published in: Journal of China universities of posts and telecommunications Vol. 20; no. 1; pp. 1 - 10
• Main Authors: SHU, Jian, TAO, Juan, LIU, Lin-lan, CHEN, Ye-bin, ZANG, Chao
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.02.2013
• Subjects: CCI; Fluctuation; Kalman filter; Least squares method; link quality estimation; Links; Mathematical models; non-perceived packet loss; Packets (communication); Raw; Remote sensors; SNR; Wireless networks; wireless sensor network; 丢包率; 无线传感器网络; 机制; 相关模型; 自觉; 质量估计; 链路; CCI; SNR; Kalman filter; wireless sensor network; non-perceived packet loss; link quality estimation
• ISSN: 1005-8885
• DOI: 10.1016/S1005-8885(13)60001-1

This paper proposes a chip correlation indicator （CCI）-based link quality estimation mechanism for wireless sensor networks under non-perceived packet loss. On the basis of analyzing all related factors, it can be concluded that signal-to-noise rate （SNR） is the main factor causing the non-perceived packet loss. In this paper, the relationship model between CCI and non-perceived packet loss rate （NPLR） is established from related models such as SNR versus packet success rate （PSR）, CCI versus SNR and CCI-NPLR. Due to the large fluctuating range of the raw CCI, Kalman filter is introduced to do de-noising of the raw CCI. The cubic model and the least squares method are employed to fit the relationship between CCI and SNR. In the experiments, many groups of comparison have been conducted and the results show that the proposed mechanism can achieve more accurate measurement of the non-perceived packet loss than existing approaches. Moreover, it has the advantage of decreasing extra energy consumption caused by sending large number of probe packets.