CFP last date
22 April 2024
Call for Paper
May Edition
IJCA solicits high quality original research papers for the upcoming May edition of the journal. The last date of research paper submission is 22 April 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Energy Detection for MIMO Decision Fusion in Underwater Sensor Network: Critical Review

by Shweta, Vibhav Kumar Sachan, Syed Akhtar Imam
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 140 - Number 3
Year of Publication: 2016
Authors: Shweta, Vibhav Kumar Sachan, Syed Akhtar Imam
10.5120/ijca2016909263

Shweta, Vibhav Kumar Sachan, Syed Akhtar Imam . Energy Detection for MIMO Decision Fusion in Underwater Sensor Network: Critical Review. International Journal of Computer Applications. 140, 3 ( April 2016), 33-38. DOI=10.5120/ijca2016909263

@article{ 10.5120/ijca2016909263,
author = { Shweta, Vibhav Kumar Sachan, Syed Akhtar Imam },
title = { Energy Detection for MIMO Decision Fusion in Underwater Sensor Network: Critical Review },
journal = { International Journal of Computer Applications },
issue_date = { April 2016 },
volume = { 140 },
number = { 3 },
month = { April },
year = { 2016 },
issn = { 0975-8887 },
pages = { 33-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume140/number3/24576-2016909263/ },
doi = { 10.5120/ijca2016909263 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:41:48.751738+05:30
%A Shweta
%A Vibhav Kumar Sachan
%A Syed Akhtar Imam
%T Energy Detection for MIMO Decision Fusion in Underwater Sensor Network: Critical Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 140
%N 3
%P 33-38
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Underwater sensor network has different applications ranging from environmental monitoring, data collection to survey mission and coastal surveillance. In this paper several fundamental aspects of underwater acoustic communication are discussed in detail. Different architecture and channel model are also been discussed. This paper also covers the latest techniques which are used in order to increase the data rate in underwater acoustic communication. The performance of the energy detector which is considered for binary hypothesis decision fusion has been reviewed and analyzed on different parameters of the investigation. This paper is based on a MIMO model for underwater acoustic network using Neymen-Pearson/ Bayesian hypothesis testing. Previous investigation and the conclusion will be useful for possible future research direction.

References
  1. Ms. Akanksha V. Patil, Mrs. Sapana G. Buwa, Mr. Vijay U. Patil, “Underwater sensor network” IJSER.org, 2012.
  2. G. Hattab, M. El-Tarhuni, M. Al-Ali, T. Joudeh, N. Qaddoumi, “An underwater wireless sensor network with realistic radio frequency path loss model”, International Journal of Distributed Sensor Networks, vol 9, 2013.
  3. L. Lanbo, Z. Shengli, and C. Jun-Hong, “Prospects and problems of wireless communication for underwater sensor networks”, Wireless Communication and Mobile Computing., vol. 8, no. 8, pp. 977–994, Oct. 2008.
  4. F. Akyildiz, D. Pompili, and T. Melodia, “Underwater acoustic sensor networks: Research challenges,” Ad Hoc Network., vol. 3, no. 3, pp. 257–279, Mar. 2005.
  5. P. A. van Walree and R. Otnes, “Ultrawideband underwater acoustic communication channels,” IEEE J. Ocean. Eng., vol. 38, no. 4, pp. 678–688, Oct. 2013.
  6. P. Qarabaqi and M. Stojanovic, “Statistical characterization and computationally efficient modeling of a class of underwater acoustic communication channels,” IEEE J. Ocean. Eng., vol. 38, no. 4, pp. 701–717, Oct. 2013.
  7. B. Li, S. Zhou, M. Stojanovic, L. Freitag, and P. Willett, “Multicarrier communication over underwater acoustic channels with non-uniform Doppler shifts,” IEEE J. Ocean. Eng., vol. 33, no. 2, pp. 198–209, Apr. 2008.
  8. P. A. van Walree and G. Leus, “Robust underwater telemetry with adaptive turbo multiband equalization,” IEEE J. Ocean. Eng., vol. 34, no. 4, pp. 645–655, Oct. 2009.
  9. B. Li et al., “MIMO-OFDM for high-rate underwater acoustic communications,” IEEE J. Ocean. Eng., vol. 34, no. 4, pp. 634–644, Oct. 2009.
  10. Z. Wang, S. Zhou, G. B. Giannakis, C. R. Berger, and J. Huang, “Frequency-domain oversampling for zero-padded OFDM in underwater acoustic communications,” IEEE J. Ocean. Eng., vol. 37, no. 1, pp. 14–24, Jan. 2012.
  11. G. Zhang and H. Dong, “Experimental assessment of a multicarrier underwater acoustic communication system,” Appl. Acoust., vol. 72, no. 12, pp. 953–961, Dec. 2011.
  12. G. Zhang and H. Dong, “Spatial diversity in multichannel processing for underwater acoustic communications,” Ocean. Eng., vol. 38, nos. 14–15, pp. 1611–1623, Oct. 2011.
  13. S. Roy, T. Duman, L. Ghazikhanian, V. McDonald, J. Proakis, and J. Zeidler, “Enhanced underwater acoustic communication performance using space-time coding and processing,” in Proc. IEEE OCEANS Conf, vol. 1, Nov. 2004.
  14. M. L. Nordenvaad and T. Oberg, “Iterative reception for acoustic underwater MIMO communications,” in Proc. IEEE OCEANS Conf.,Sep. 2006,
  15. D. B. Kilfoyle, J. C. Preisig, and A. B. Baggeroer, “Spatial modulation experiments in the underwater acoustic channel,” IEEE J. Ocean. Eng.,vol. 30, no. 2, pp. 406–415, Apr. 2005.
  16. E. M. Sozer, M. Stojanovic, and J. G. Proakis, “Underwater acoustic networks,” IEEE J. Ocean. Eng., vol. 25, no. 1, pp. 72–83, Jan. 2000.
  17. M. K. Park and V. Rodoplu, “UWAN-MAC: An energy-efficient MAC protocol for underwater acoustic wireless sensor networks,” IEEE J. Ocean. Eng., vol. 32, no. 3, pp. 710–720, Jul. 2007.
  18. X. Guo, M. R. Frater, and M. J. Ryan, “Design of a propagation delay tolerant MAC protocol for underwater acoustic sensor networks,” IEEE J. Ocean. Eng., vol. 34, no. 2, pp. 170–180, Apr. 2009.
  19. W.-H. Liao and C.-C. Huang, “SF-MAC: A spatially fair MAC protocol for underwater acoustic sensor networks,” IEEE Sensors J., vol. 12,no. 6, pp. 1686–1694, Jun. 2012.
  20. M. Zorzi, P. casari and A.F. Harris, “An energy-efficient routing schemes for underwater acoustic networks,” IEEE J.sel. commmun., vol. 26, no. 9, pp. 1754–1766, Dec. 2008.
  21. J. M. Jordet, M. Stojanovic, and M. Zorzi, “On joint frequency and power allocation in a cross-layer protocol for underwater acoustic networks,” IEEE J. Ocean. Eng., vol. 35, no. 4, pp. 936–947, Oct. 2010.
  22. R. Niu, M. Moore, D. Klamer, “Decision Fusion in a Wireless Sensor Network with a Large Number of Sensors,” Electrical Engineering and Computer Science, paper 82, 2004.
  23. B. Chen, L. Tong, and P. K. Varshney, “Channel-aware distributed detection in wireless sensor networks,” IEEE Signal Process. Mag., vol. 23, no. 4, pp. 16–26, Jul. 2006.
  24. B. Chen, R. Jiang, T. Kasetkasem, and P. K. Varshney, “Channel aware decision fusion in wireless sensor networks,” IEEE Trans. Signal Process, vol. 52, no. 12, pp. 3454–3458, Dec. 2004.
  25. J. Park, E. Kim, and K. Kim, “Large signal robustness of the Chair–Varshney fusion rule under generalized-Gaussian noises,”IEEE Sensors J., vol. 10, no. 9, pp. 1438–1439, Sep. 2010.
  26. Lei and R. Schober, “Coherent max-log decision fusion in wireless sensor networks,” IEEE Trans. Commun., vol. 58, no. 5, pp. 1327–1332, May 2010.
  27. D. Ciuonzo, G. Romano, and P. Salvo Rossi, “Channel-aware decision fusion in distributed MIMO wireless sensor networks: Decode-and-fuse vs. decode-then-fuse,” IEEE Trans. Wireless Commun., vol. 11, no. 8, pp. 2976–2985, Aug. 2012.
  28. D. Ciuonzo, G. Romano, and P. Salvo Rossi, “Performance analysis and design of maximum ratio combining in channel-aware MIMO decision fusion,” IEEE Trans. Wireless Commun., vol. 12, no. 9, pp. 4716 4728, Sep. 2013.
  29. D. Ciuonzo, G. Romano, and P. Salvo Rossi, “Optimality of received energy in decision fusion over Rayleigh fading diversity MAC with non-identical sensors,” IEEE Trans. Signal Process, vol. 61, no. 1, pp. 22–27, Jan. 2013.
  30. P. S. Rossi, D.Ciuonzo, T.Ekman, and H. Dong, “Energy Detection for MIMO Decision Fusion in Underwater Sensor Networks” IEEE SENSORS JOURNAL, VOL. 15, NO. 3 MARCH 2015.
  31. S. M. Kay, Fundamental of Statistical Signal processing: Detection Theory, vol. 2. Englewood Cliffs, NJ, USA: Prentice-Hall, 1998.
  32. F. Li, J. S. Evans, and S. Dey, “Decision fusion over non-coherent fading multi-access channels,” IEEE Trans. Signal Process, vol. 59, no. 9, pp. 4367–4380, Sep. 2011.
  33. D. Ciuonzo, G. Romano, and P. Salvo Rossi, “Optimality of received energy in decision fusion over Rayleigh fading diversity MAC with non-identical sensors,” IEEE Trans. Signal Process, vol. 61, no. 1, pp. 22–27,Jan. 2013.
Index Terms

Computer Science
Information Sciences

Keywords

Decision Fusion Energy detection Multiple-input Multiple-output (MIMO) underwater sensor networks

Powered by PhDFocusTM