Statistical Modeling of Local Area Fading Channels Based on Triply Stochastic Filtered Marked Poisson Point Processes
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33122
Statistical Modeling of Local Area Fading Channels Based on Triply Stochastic Filtered Marked Poisson Point Processes

Authors: Jihad S. Daba, J. P. Dubois

Abstract:

Fading noise degrades the performance of cellular communication, most notably in femto- and pico-cells in 3G and 4G systems. When the wireless channel consists of a small number of scattering paths, the statistics of fading noise is not analytically tractable and poses a serious challenge to developing closed canonical forms that can be analysed and used in the design of efficient and optimal receivers. In this context, noise is multiplicative and is referred to as stochastically local fading. In many analytical investigation of multiplicative noise, the exponential or Gamma statistics are invoked. More recent advances by the author of this paper utilized a Poisson modulated-weighted generalized Laguerre polynomials with controlling parameters and uncorrelated noise assumptions. In this paper, we investigate the statistics of multidiversity stochastically local area fading channel when the channel consists of randomly distributed Rayleigh and Rician scattering centers with a coherent Nakagami-distributed line of sight component and an underlying doubly stochastic Poisson process driven by a lognormal intensity. These combined statistics form a unifying triply stochastic filtered marked Poisson point process model.

Keywords: Cellular communication, femto- and pico-cells, stochastically local area fading channel, triply stochastic filtered marked Poisson point process.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1110109

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1351

References:


[1] R. Prasad and L. Munoz, WLANs and WPANs Towards 4G Wireless, Artech House, MA, 2003.
[2] L. C. Godara, “Applications of Antenna Arrays to Mobile Communications, Part I: Performance, Improvement, Feasibility, and System Considerations,” Proceedings of the IEEE, vol. 85, no. 7, pp. 1031-1060, July 1997.
[3] J. H. Winters, “Smart Antennas for Wireless Systems,” IEEE Personal Communications, vol. 1, pp. 23-27, Feb. 1998.
[4] T. S. Rappaport, Wireless Communications: Principles and Practice, Prentice Hall Inc., Upper Saddle River, NJ, 2nd edition, 2002.
[5] W. R. Braun and U. Dersh, “A Physical Mobile Radio Channel,” IEEE Transactions on Vehicular Technology, vol. 40, no. 2, pp. 472-482, May 1991.
[6] S. O. Rice, “Statistical Properties of a Sine Wave Plus Random Noise,” Bell System Technical Journal, vol. 27, no. 1, pp. 109-157, Jan. 1948.
[7] J. Daba and P. Jreije, “Advanced Stochastic Models for Partially Developed Speckle,” International Journal of Electrical and Electronics Engineering, Vol. 3, No. 3, pp. 183-187, 2009.
[8] J. Daba and M. R. Bell, “Segmentation of Speckled Images Using a Likelihood Random Field Model,” Optical Engineering, vol. 47, no. 1, pp. 017005-1 to 017005-20, January 2008.
[9] J. Daba and M. R. Bell, “Object Discrimination and Orientation- Determination in Speckled Images,” Optical Engineering, vol. 33, no. 4, pp. 1287-1302, April 1994.
[10] J. Daba and O. Abdul-Latif, “Detection of Ultrasonic Images in the Presence of a Random Number of Scatterers: A Statistical Learning Approach,” Transactions on Engineering, Computing, and Technology, ISSN 1305-5313, vol. 7, pp. 326-329, 2005.
[11] J. Daba and O. Abdul-Latif, “SVM-Based Detection of SAR Images in Partially Developed Speckle Noise,” Transactions on Engineering, Computing, and Technology, ISSN 1305-5313, vol. 7, pp. 321-325, 2005.
[12] J. Daba, “Improved Segmentation of Speckled Images Using an Arithmetic-to-Geometric Mean Ratio Kernel”, International Journal of Computer, Information, and Systems Science, and Engineering, vol. 1, no. 4, pp.218-221, 2007.
[13] J. Daba, “Segmentation of Speckled Ultrasound Images Based on a Statistical Model,” Proceedings of the 16th International EURASIP Conference BIOSIGNAL 2002, vol. 16, Brno, Czech Republic, June 2002.
[14] J. Daba and M. R. Bell, “Object Discrimination and Orientation- Determination in Synthetic Aperture Radar Images,” IEEE International Geoscience and Remote Sensing Symposium, NASA, Houston, TX, USA, May 23-29, 1992.
[15] D. Snyder and M. Miller, Random Point Processes in Time and Space, NY: Springer-Verlag, 2002.
[16] J. Daba and M. R. Bell, “Synthetic-Aperture-Radar Surface Reflectivity Estimation Using a Marked Point-Process Speckle Model,” Optical Engineering, vol. 42, no. 1, pp.211-227, January 2003.
[17] J. Daba, “Estimation of the SNR for Wireless Systems in a Local Fading Environment with Multi-Element Antennas,” EURASIP - 13th European Signal Processing Conference, Turkey, Sept. 2005.
[18] J. Daba, “Estimation Algorithms for Quantitative Tissue Characterization in Ultrasound Images Using Doubly Stochastic Translated Point Processes”, Proceedings of the IEE Medical Signal and Information Processing Conference – MEDSIP 2004, Malta, Sept. 2004.
[19] J. Daba, “Traffic Estimation in Wireless Networks Using Filtered Doubly Stochastic Point Processes”, IEEE Conference on Electrical, Electronic, and Computer Engineering, Cairo, Egypt, September 2004.
[20] J. Daba and M. R. Bell, “Estimation of the Surface Reflectivity of SAR Images Based on a Marked Poisson Point Process Model,” IEEE International Symposium on Signals, Systems, and Electronics, San Francisco, USA, October 25, 1995.
[21] F. Oberhettinger, Tables of Bessel Transforms, Berlin, Germany: Springer, 1972.
[22] J. Daba and M. R. Bell, “Statistics of the Scattering Cross Section of a Small Number of Random Scatterers,” IEEE Transactions on Antennas and Propagation, vol. 43, no. 8, pp. 773-783, August 1995.
[23] A. Abdi, S. Nader-Esfahani, J. Daba and M. R. Bell, “Comments on Statistics of the Scattering Cross Section of a Small Number of Random Scatterers,” IEEE Transactions on Antennas and Propagation, vol. 48, no. 5, pp. 844-845, May 2000.
[24] O. Abdul-Latif and J. Daba, “Performance of a UWB System in a Partially Developed Fading Channel with CCI,” 5th IEEE GCC Communication and Signal Processing Conference, Kuwait, March 2009.
[25] J. Daba and P. Jreije, “Advanced Stochastic Models for Partially Developed Speckle,” 5th International Conference on Computer, Electrical, and Systems Science, and Engineering (CESSE 2008), organized by the World Congress on Science, Engineering, and Technology, Vienna, Austria, August 2008.
[26] J. Daba, “Poisson Modulated Stochastic Model for Partially Developed Multi-Look Speckle,” American Conference on Applied Mathematics, Harvard University, Cambridge, MA, USA, March 2008.
[27] J. Daba, “Scattering Statistics of Doppler Faded Acoustic Signals Using Speckle Noise Models,” IEEE International Conference on Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory, Lviv, Ukraine, Sept. 2003.
[28] J. Daba and M. R. Bell, “Object Discrimination and Orientation- Determination in Synthetic Aperture Radar Images,” West Lafayette, IN, Purdue University, School of Electrical Engineering Technical Report, July 1994.
[29] J. Daba and M R. Bell, “Statistics of the Scattering Cross Section of a Collection of Constant Amplitude Scatterers with Random Phase,” West Lafayette, IN, Purdue University, School of Electrical Engineering Technical Report, TR-EE 94-25, July 1994.
[30] J. Daba, Detection and Estimation in Speckled Images Based on Marked Point Process Speckle Noise Models, Ph.D Dissertation, Purdue University, West Lafayette, IN, USA, August 1994. Published by University Microfilms International, Ann Arbor, Michigan, USA.
[31] J. Daba, “Burstiness Reduction of Uniform Activity Video Sources Using a Doubly Stochastic AR Model,” International Journal of Computer, Information, and Systems Science, and Engineering, ISSN 1307-2331, vol. 1, no. 4, pp.226-230, 2007.
[32] J. Daba, “Statistical Multiplexing of Non Uniform Activity Video Sources Using ARMA Models,” International Journal of Computer, Information, and Systems Science, and Engineering, ISSN 1307-2331, vol. 1, no. 4, pp.231-237, 2007.
[33] R. M. Cramblitt and M. R. Bell, "Marked Regularity Models," IEEE Transactions on Ultrasonics, Ferromagnetics, and Frequency Control. Vol. 46, No. 1, January 1999, pp. 24 – 34.
[34] J. W. Goodman, “Some effects of target-induced scintillation on optical radar performance,” Proeedings of the IEEE, Vol. 53, Issue 11, Nov. 1965, pp.1688 – 1700.