中国邮电高校学报(英文) ›› 2013, Vol. 20 ›› Issue (1): 1-10.doi: 10.1016/S1005-8885(13)60001-1

• Networks •    下一篇

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

舒坚1,陶娟1,刘林岚2,谌业滨1,藏超1   

  1. 1. 南昌航空大学软件学院
    2. 南昌航空大学信息工程学院
  • 收稿日期:2012-08-05 修回日期:2012-09-19 出版日期:2013-02-28 发布日期:2013-02-28
  • 通讯作者: 舒坚 E-mail:shujian@jxjt.gov.cn
  • 基金资助:

    This work was supported by the National Natural Science Foundation of China (61262020), Aeronautical Science Foundation of China (2010ZC56008), Nanchang Hangkong University Postgraduate Innovation Foundation (YC2011030).

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

  1. 1. Internet of Things Technology Institute School of Software, Nanchang Hangkong University, Nanchang 330063, China 2. Internet of Things Technology Institute School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China
  • Received:2012-08-05 Revised:2012-09-19 Online:2013-02-28 Published:2013-02-28
  • Contact: Jian SHU E-mail:shujian@jxjt.gov.cn
  • Supported by:

    This work was supported by the National Natural Science Foundation of China (61262020), Aeronautical Science Foundation of China (2010ZC56008), Nanchang Hangkong University Postgraduate Innovation Foundation (YC2011030).

摘要:

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.

关键词:

wireless sensor network, link quality estimation, non-perceived packet loss, CCI, SNR, Kalman filter

Abstract:

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.

Key words:

wireless sensor network, link quality estimation, non-perceived packet loss, CCI, SNR, Kalman filter