Table of Contents
ISRN Sensor Networks
Volume 2014, Article ID 389451, 9 pages
http://dx.doi.org/10.1155/2014/389451
Research Article

Capacity of Data Collection in Wireless Sensor Networks Based on Mutual Information and MMSE Estimation

Graduate School of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan

Received 4 December 2013; Accepted 30 December 2013; Published 17 February 2014

Academic Editors: T.-S. Chen, J. Li, and Y. Yu

Copyright © 2014 Ajib Setyo Arifin and Tomoaki Ohtsuki. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. C. Wang, C. Jiang, Y. Liu, X. Li, and S. Tang, “Aggregation capacity of wireless sensor networks: extended network case,” IEEE Transactions on Computers, no. 99, pp. 1–10, 2012. View at Google Scholar
  2. S. Chen, M. Huang, S. Tang, and Y. Wang, “Capacity of data collection in arbitrary wireless sensor networks,” IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 1, pp. 52–60, 2012. View at Publisher · View at Google Scholar · View at Scopus
  3. P. Santi, “On the data gathering capacity and latency in wireless sensor networks,” IEEE Journal on Selected Areas in Communications, vol. 28, no. 7, pp. 1211–1221, 2010. View at Publisher · View at Google Scholar · View at Scopus
  4. D. Marco, E. J. Duarte-Melo, M. Liu, and D. L. Neuhoff, “On the many-to-one transport capacity of a dense wireless sensor network and the compressibility of its data,” Lecture Notes in Computer Science, vol. 2634, pp. 1–16, 2003. View at Google Scholar · View at Scopus
  5. E. J. Duarte-Melo and M. Liu, “Data-gathering wireless sensor networks: organization and capacity,” Computer Networks, vol. 43, no. 4, pp. 519–537, 2003. View at Publisher · View at Google Scholar · View at Scopus
  6. H. El Gamal, “On the scaling laws of dense wireless sensor networks: the data gathering channel,” IEEE Transactions on Information Theory, vol. 51, no. 3, pp. 1229–1234, 2005. View at Publisher · View at Google Scholar · View at Scopus
  7. K. Zheng and R. Barton, “Toward optimal data aggregation in random wireless sensor networks,” in Proceedings of the 26th IEEE International Conference on Computer Communications (IEEE INFOCOM '07), pp. 249–257, May 2007. View at Publisher · View at Google Scholar · View at Scopus
  8. B. Liu, D. Towsley, and A. Swami, “Data gathering capacity of large scale multihop wireless networks,” in Proceedings of the 5th IEEE International Conference on Mobile Ad-Hoc and Sensor Systems (MASS '08), pp. 124–132, October 2008. View at Publisher · View at Google Scholar · View at Scopus
  9. S. Chen, Y. Wang, X.-Y. Li, and X. Shi, “Capacity of data collection in randomly-deployed wireless sensor networks,” Wireless Networks, vol. 17, no. 2, pp. 305–318, 2011. View at Publisher · View at Google Scholar · View at Scopus
  10. H. Zheng, S. Xiao, X. Wang, X. Tian, and M. Guizani, “Capacity and delay analysis for data gathering with compressive sensing in wireless sensor networks,” IEEE Transactions on Wireless Communications, vol. 12, no. 2, pp. 917–927, 2013. View at Google Scholar
  11. P. Gupta and P. R. Kumar, “The capacity of wireless networks,” IEEE Transactions on Information Theory, vol. 46, no. 2, pp. 388–404, 2000. View at Publisher · View at Google Scholar · View at Scopus
  12. S. Marano, V. Matta, and P. Willett, “Distributed estimation in large wireless sensor networks via a locally optimum approach,” IEEE Transactions on Signal Processing, vol. 56, no. 2, pp. 748–756, 2008. View at Publisher · View at Google Scholar · View at Scopus
  13. A. Ribeiro and G. B. Giannakis, “Bandwidth-constrained distributed estimation for wireless sensor networks—part I: gaussian case,” IEEE Transactions on Signal Processing, vol. 54, no. 3, pp. 1131–1143, 2006. View at Publisher · View at Google Scholar · View at Scopus
  14. A. Ribeiro and G. B. Giannakis, “Bandwidth-constrained distributed estimation for wireless sensor networks—part II: unknown probability density function,” IEEE Transactions on Signal Processing, vol. 54, no. 7, pp. 2784–2796, 2006. View at Publisher · View at Google Scholar · View at Scopus
  15. Z.-Q. Luo, “Universal decentralized estimation in a bandwidth constrained sensor network,” IEEE Transactions on Information Theory, vol. 51, no. 6, pp. 2210–2219, 2005. View at Publisher · View at Google Scholar · View at Scopus
  16. J.-J. Xiao and Z.-Q. Luo, “Decentralized estimation in an inhomogeneous sensing environment,” IEEE Transactions on Information Theory, vol. 51, no. 10, pp. 3564–3575, 2005. View at Publisher · View at Google Scholar · View at Scopus
  17. K. Liu, H. E. Gamal, and A. M. Sayeed, “On optimal parametric field estimation in sensor networks,” in Proceedings of the IEEE/SP 13th Workshop on Statistical Signal Processing, pp. 1170–1175, July 2005. View at Scopus
  18. G. Mergen and L. Tong, “Type based estimation over multiaccess channels,” IEEE Transactions on Signal Processing, vol. 54, no. 2, pp. 613–626, 2006. View at Publisher · View at Google Scholar · View at Scopus
  19. M. K. Banavar, C. Tepedelenlioǧlu, and A. Spanias, “Estimation over fading channels with limited feedback using distributed sensing,” IEEE Transactions on Signal Processing, vol. 58, no. 1, pp. 414–425, 2010. View at Publisher · View at Google Scholar · View at Scopus
  20. H. Şenol and C. Tepedelenlioǧlu, “Performance of distributed estimation over unknown parallel fading channels,” IEEE Transactions on Signal Processing, vol. 56, no. 12, pp. 6057–6068, 2008. View at Publisher · View at Google Scholar · View at Scopus
  21. T. J. Goblick, “Theoretical limitations on the transmission of data from analog sources,” IEEE Transactions on Information Theory, vol. 11, no. 4, pp. 558–567, 1965. View at Publisher · View at Google Scholar
  22. M. Gasfpar, B. Rimoldi, and M. Vetterli, “To code, or not to code: lossy source-channel communication revisited,” IEEE Transactions on Information Theory, vol. 49, no. 5, pp. 1147–1158, 2003. View at Publisher · View at Google Scholar · View at Scopus
  23. M. Gastpar, “Uncoded transmission is exactly optimal for a simple Gaussian “sensor” network,” IEEE Transactions on Information Theory, vol. 54, no. 11, pp. 5247–5251, 2008. View at Publisher · View at Google Scholar · View at Scopus
  24. J.-J. Xiao, S. Cui, Z.-Q. Luo, and A. J. Goldsmith, “Linear coherent decentralized estimation,” IEEE Transactions on Signal Processing, vol. 56, no. 2, pp. 757–770, 2008. View at Publisher · View at Google Scholar · View at Scopus
  25. S. Cui, J.-J. Xiao, A. J. Goldsmith, Z.-Q. Luo, and H. V. Poor, “Estimation diversity and energy efficiency in distributed sensing,” IEEE Transactions on Signal Processing, vol. 55, no. 9, pp. 4683–4695, 2007. View at Publisher · View at Google Scholar · View at Scopus
  26. D. Guo, S. Shamai, and S. Verdú, “Mutual information and minimum mean-square error in Gaussian channels,” IEEE Transactions on Information Theory, vol. 51, no. 4, pp. 1261–1282, 2005. View at Publisher · View at Google Scholar · View at Scopus
  27. J. M. Steele, The Cauchy-Schwarz Master Class, Cambridge University Press, Cambridge, Mass, USA, 2004.
  28. S. Byod and L. Vandenberghe, Convex Optimization, Cambridge University Press, Cambridge, Mass, USA, 2003.