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Performance Evaluation of Cross Correlation Based Node Estimation Technique

Received: 19 July 2015     Accepted: 30 July 2015     Published: 11 August 2015
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Abstract

Estimating the number of operating nodes is an important factor in wireless communication network (WCN) in which the nodes are deployed in different forms to cover small or large areas of interest for a wide range of personal, scientific and commercial applications. It is important to estimate the number of operating nodes at any point in time for proper network operation and maintenance. Proper operation of a network depends on the total number of nodes present at a particular moment. Counting the number is very important in useful data collection, node localization and network maintenance. Also network performance depends on the area node ratio i.e. the number of operating nodes per unit area. So, node estimation is a vital requirement in wireless sensor network. At present, different estimation techniques exist but they are only effective for communication friendly networks. In underwater wireless sensor network node estimation faces a great difficulty due to underwater propagation characteristics such as high propagation delay, high absorption and dispersion. In such environment the number of nodes may vary frequently due to ad-hoc nature, power failure of nodes or environmental disaster. A statistical signal processing approach of node estimation is proposed in this paper and the performance of the proposed method is evaluated by comparing the results with other techniques. The nodes are considered as acoustic signal sources and their number is obtained through the cross correlation of the acoustic signals received at two sensors in the network. The mean of the cross correlation function is related with the number of nodes and is used as the estimation parameter in the process. Theoretical and simulation results are provided which show effectiveness of the signal processing approach instead of protocols in node estimation process

Published in Communications (Volume 3, Issue 5)
DOI 10.11648/j.com.20150305.12
Page(s) 86-92
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

Wireless Communication Network (WCN), Cross Correlation Function (CCF), Estimation Parameter, Mean of Cross Correlation Function, Node Estimation, Underwater Acoustic Sensor Networks (UASN)

References
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[5] J. Myung,W. Lee and J. Srivastava, “Adaptive binary splitting for efficient RFID tag anti-collision,” IEEE Communications Letters, vol. 10 (3), pp.144–146, Mar. 2006.
[6] J. Myung and W. Lee, et al., “Adaptive binary splitting for efficient RFID tag anti-collision,” IEEE Communications Letters 10(3): 144-146.2006.
[7] J. Myung and L. Wonjun, et al., “Tag-Splitting: Adaptive Collision Arbitration Protocols for RFID Tag Identification,” IEEE Transactions on Parallel and Distributed Systems 18: 763-775.2007.
[8] M.A. Bonuccelli, F. Lonetti and F. Martelli, “Perfect tag identification protocol in RFID networks,”http://arxiv.org/PS_cache/arxiv/pdf/0805/0805.1877v1.pdf, May 13, 2008.
[9] C. Budianu, S. Ben-David and L. Tong, “Estimation of the number of operating sensors in large-scale sensor network with mobile access,” IEEE Transactions on Signal Processing, vol. 54, no. 5, pp. 1703–1715, May 2006. doi: 10.1109/TSP.2006.871973.
[10] C. Budianu and L. Tong, “Estimation of the number of the operating sensors in a sensor network,” presented at 2003 Asilomar Conf. Signals, Systems, Computers, Monterey, California.
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[13] M. S. A. Howlader and M. R. Frater, et al., “Estimation in underwater sensor network taking into account capture,” IEEE OCEANS '07, Aberdeen, Scotland.2007.
[14] L. Liu, S. Zhou and C. Jun-Hong, “Prospects and problems of wireless communication for underwater sensor networks,” Wireless Communication Mobile Computer 2008, Published online in Wiley InterScience. DOI= http://doi.wiley.com/10.1002/wcm.654.
[15] J.H. Cui, J. Kong, M. Gerla and S. Zhou, “Challenges: Building scalable mobile underwater wireless sensor networks for aquatic applications,” IEEE Network, Special Issue on Wireless Sensor Networking, pp. 12-18, 2006.
[16] I. F. Akyildiz, D. Pompili and T. Melodia, “Underwater acoustic sensor networks: Research challenges, Ad Hoc Networks,” pp. 257–279, 2005.
[17] P. Roux, K. Sabra, W. Kuperman and A. Roux, “Ambient noise cross correlation in free space: theoretical approach,” J. Acoustic Soc. Am., 117, 79–84, 2005.
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Cite This Article
  • APA Style

    Abu Sadat Md. Sayem, Md. Shamim Anower. (2015). Performance Evaluation of Cross Correlation Based Node Estimation Technique. Communications, 3(5), 86-92. https://doi.org/10.11648/j.com.20150305.12

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    ACS Style

    Abu Sadat Md. Sayem; Md. Shamim Anower. Performance Evaluation of Cross Correlation Based Node Estimation Technique. Communications. 2015, 3(5), 86-92. doi: 10.11648/j.com.20150305.12

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    AMA Style

    Abu Sadat Md. Sayem, Md. Shamim Anower. Performance Evaluation of Cross Correlation Based Node Estimation Technique. Communications. 2015;3(5):86-92. doi: 10.11648/j.com.20150305.12

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  • @article{10.11648/j.com.20150305.12,
      author = {Abu Sadat Md. Sayem and Md. Shamim Anower},
      title = {Performance Evaluation of Cross Correlation Based Node Estimation Technique},
      journal = {Communications},
      volume = {3},
      number = {5},
      pages = {86-92},
      doi = {10.11648/j.com.20150305.12},
      url = {https://doi.org/10.11648/j.com.20150305.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.com.20150305.12},
      abstract = {Estimating the number of operating nodes is an important factor in wireless communication network (WCN) in which the nodes are deployed in different forms to cover small or large areas of interest for a wide range of personal, scientific and commercial applications. It is important to estimate the number of operating nodes at any point in time for proper network operation and maintenance. Proper operation of a network depends on the total number of nodes present at a particular moment. Counting the number is very important in useful data collection, node localization and network maintenance. Also network performance depends on the area node ratio i.e. the number of operating nodes per unit area. So, node estimation is a vital requirement in wireless sensor network. At present, different estimation techniques exist but they are only effective for communication friendly networks. In underwater wireless sensor network node estimation faces a great difficulty due to underwater propagation characteristics such as high propagation delay, high absorption and dispersion. In such environment the number of nodes may vary frequently due to ad-hoc nature, power failure of nodes or environmental disaster. A statistical signal processing approach of node estimation is proposed in this paper and the performance of the proposed method is evaluated by comparing the results with other techniques. The nodes are considered as acoustic signal sources and their number is obtained through the cross correlation of the acoustic signals received at two sensors in the network. The mean of the cross correlation function is related with the number of nodes and is used as the estimation parameter in the process. Theoretical and simulation results are provided which show effectiveness of the signal processing approach instead of protocols in node estimation process},
     year = {2015}
    }
    

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    T1  - Performance Evaluation of Cross Correlation Based Node Estimation Technique
    AU  - Abu Sadat Md. Sayem
    AU  - Md. Shamim Anower
    Y1  - 2015/08/11
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    DO  - 10.11648/j.com.20150305.12
    T2  - Communications
    JF  - Communications
    JO  - Communications
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    EP  - 92
    PB  - Science Publishing Group
    SN  - 2328-5923
    UR  - https://doi.org/10.11648/j.com.20150305.12
    AB  - Estimating the number of operating nodes is an important factor in wireless communication network (WCN) in which the nodes are deployed in different forms to cover small or large areas of interest for a wide range of personal, scientific and commercial applications. It is important to estimate the number of operating nodes at any point in time for proper network operation and maintenance. Proper operation of a network depends on the total number of nodes present at a particular moment. Counting the number is very important in useful data collection, node localization and network maintenance. Also network performance depends on the area node ratio i.e. the number of operating nodes per unit area. So, node estimation is a vital requirement in wireless sensor network. At present, different estimation techniques exist but they are only effective for communication friendly networks. In underwater wireless sensor network node estimation faces a great difficulty due to underwater propagation characteristics such as high propagation delay, high absorption and dispersion. In such environment the number of nodes may vary frequently due to ad-hoc nature, power failure of nodes or environmental disaster. A statistical signal processing approach of node estimation is proposed in this paper and the performance of the proposed method is evaluated by comparing the results with other techniques. The nodes are considered as acoustic signal sources and their number is obtained through the cross correlation of the acoustic signals received at two sensors in the network. The mean of the cross correlation function is related with the number of nodes and is used as the estimation parameter in the process. Theoretical and simulation results are provided which show effectiveness of the signal processing approach instead of protocols in node estimation process
    VL  - 3
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Author Information
  • Department of Electrical & Electronic Engineering, Rajshahi University of Engineering & Technology, Rajshahi, Bangladesh

  • Department of Electrical & Electronic Engineering, Rajshahi University of Engineering & Technology, Rajshahi, Bangladesh

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