Performance Evaluation of Cross Correlation Based Node Estimation Technique
Communications
Volume 3, Issue 5, September 2015, Pages: 86-92
Received: Jul. 19, 2015; Accepted: Jul. 30, 2015; Published: Aug. 11, 2015
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Authors
Abu Sadat Md. Sayem, Department of Electrical & Electronic Engineering, Rajshahi University of Engineering & Technology, Rajshahi, Bangladesh
Md. Shamim Anower, Department of Electrical & Electronic Engineering, Rajshahi University of Engineering & Technology, Rajshahi, Bangladesh
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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
Keywords
Wireless Communication Network (WCN), Cross Correlation Function (CCF), Estimation Parameter, Mean of Cross Correlation Function, Node Estimation, Underwater Acoustic Sensor Networks (UASN)
To cite this article
Abu Sadat Md. Sayem, Md. Shamim Anower, Performance Evaluation of Cross Correlation Based Node Estimation Technique, Communications. Vol. 3, No. 5, 2015, pp. 86-92. doi: 10.11648/j.com.20150305.12
References
[1]
M. Kodialam and T. Nandagopal, “Fast and reliable estimation schemes in RFID systems,” 12th annual international conference on Mobile computing and networking (MobiCom'06), Los Angeles, CA, USA, ACM.2006.
[2]
M.A. Bonuccelli and F. Lonetti, et al., “Tree Slotted Aloha: a New Protocol for Tag Identification in RFID Networks,” Proceedings of the 2006 International Symposium on World of Wireless, Mobile and Multimedia Networks, IEEE Computer Society.2006.
[3]
M. A.-I. Center, Draft protocol specification for a 900 MHz class 0 radio frequency identification tag, http://www.epcglobalinc.org, Feb. 2003.
[4]
C. Law and K. Lee, et al., “Efficient memory less protocol for tag identification (extended abstract),”Proceedings of the 4th international workshop on Discrete algorithms and methods for mobile computing and communications”, Boston, Massachusetts, USA, ACM: 75-84.2000.
[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.
[11]
C. Budianu and L. Tong, “Good-Turing estimation of the number of operating sensors: a large deviations analysis,” Int. Conf. Acoustics, Speech, Signal Processing (ICASSP), Montreal, QC, Canada, May 2004, vol. 2, pp. 1029–1032. doi: 10.1109/ICASSP.2004.1326436.
[12]
M. S. A. Howlader M. R. Frater, et el.,“Estimating the Number and Distribution of the Neighbors in an Underwater Communication Network,” Second International Conference on Sensor Technologies and Applications (SENSORCOMM'08).2008.
[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.
[18]
R. Snieder, “Extracting the Green’s function of attenuating heterogeneous acoustic media from uncorrelated waves,” J. Acoustic Soc. Am., Vol. 121, No. 5, 2637-2643, May 2007.
[19]
O.A. Godin, “Recovering the Acoustic Green’s function from ambient noise cross correlation in an inhomogeneous moving medium,” Physical Review Letters, The American Physical Society, 97, 054301(2006).
[20]
K.G. Sabra, P. Roux and W.A. Kuperman, “Emergence rate of the time-domain Green’s function from the ambient noise cross - correlation function,” J. Acoustic Soc. Am., Vol. 118, No. 6, 3524–3531, December 2005.
[21]
M. S. Anower, M. A. Motin, A. S. M. Sayem, and S. A. H. Chowdhury, “A node estimation technique in underwater wireless sensor network,” In Proceedings of International Conference on Informatics, Electronics & Vision (ICIEV), 17–18 May, 2013, pp. 1–6. doi: 10.1109/ICIEV.2013.6572582.
[22]
H.Vogt, “Efficient object identification with passive RFID tags”, Lecture Notes in Computer Science 2414.2002.
[23]
W. Feller, “An Introduction to Probability Theory and its Applications,” John Wiley, 1968.
[24]
M. S. Anower, S. A. H. Chowdhury, Jishan-E-Giti, A. S. M. Sayem and M.I. Haque “Underwater network size estimation using cross - correlation: selection of estimation parameter,” Proceedings of the 9th International Forum on Strategic Technology (IFOST-2014), 21-23 October-2014 in Cox’s Bazar, Bangladesh. DOI:10.1109/IFOST.2014.6991097.
[25]
M. S. Anower, “Estimation using cross - correlation in a communications network,” Ph.D. dissertation, SEIT, University of New South Wales at Australian Defense Force Academy, Canberra, 2011.
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