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Co-channel Interference Modeling and Analysis in a Poisson Field of Interferers in Wireless Communications

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Classical, Semi-classical and Quantum Noise

Abstract

This chapter considers interference in a wireless communication network, caused by users that share the same propagation medium. Under the assumption that the interfering users are spatially Poisson distributed, and under a power-law propagation loss function, it has been shown in the past that the interference instantaneous amplitude at the receiver is α-stable distributed. Past work has not considered the second-order statistics of the interference, and has relied on the assumption that interference samples are independent. In this chapter, analytic expressions for the interference second-order statistics are provided, and it is shown that depending on the properties of the users’ holding times, the interference can be long-range dependent.

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Notes

  1. 1.

    λ may be function of time and locations of the unit area/volume, which forms a non-homogeneous Poisson point process. A non-homogeneous Poisson process can be mapped to a homogeneous one through transformations, cf. [5,  7]. In this paper, we only consider the homogeneous case, i.e., λ is a constant.

References

  1. Wegman EJ, Schwartz SC, Thomas JB (eds) (1989) Topics in non-Gaussian signal processing. Springer, New York

    MATH  Google Scholar 

  2. Middleton D (1977) Statistical-physical models of electromagnetic interference. IEEE Trans Electromagn C EMC-19(3):106–127

    Article  Google Scholar 

  3. Furutsu K, Ishida T (1961) On the theory of amplitude distribution of impulsive random noise. J Appl Phys 32(7):1206–1221

    Article  MathSciNet  Google Scholar 

  4. Giordano A, Haber F (1972) Modeling of atmosphere noise. Radio Sci 7(11):1011–1023

    Article  Google Scholar 

  5. Sousa ES (1992) Performance of a spread spectrum packet radio network link in a Poisson field of interferers. IEEE Trans Inf Theory 38(6):1743–1754

    Article  Google Scholar 

  6. Nikias CL, Shao M (1995) Signal processing with alpha-stable distributions and applications. Wiley, New York

    Google Scholar 

  7. Ilow J, Hatzinakos D (1998) Analytic alpha-stable noise modeling in a Poisson field of interferers or scatters. IEEE Trans Signal Process 46(6):1601–1611

    Article  Google Scholar 

  8. Blackard KL, Rappaport TS, Bostian CW (1993) Measurements and models of radio frequency impulsive noise for indoor wireless communications. IEEE J Sel Areas Comm 11(7):991–1001

    Article  Google Scholar 

  9. Blankenship TK, Krizman DM, Rappaport TS (1997) Measurements and simulation of radio frequency impulsive noise in hospitals and clinics. In: Proceedings of the 47th IEEE vehicular technology conference, Phoenix, AZ, May 1997, vol. 3, pp 1942–1946

    Google Scholar 

  10. Kogon SM, Manolakis DG (1996) Signal modeling with self-similar α-stable processes: the fractional levy stable motion model. IEEE Trans Signal Process 44:1006–1010

    Article  Google Scholar 

  11. Parsons JD (1996) The mobile radio propagation channel. Wiley, New York

    Google Scholar 

  12. Kassam SA (1987) Signal detection in non-Gaussian noise. Springer, New York

    Google Scholar 

  13. Poor HV, Thomas JB (1993) Signal detection in dependent non-Gaussian noise. In: Poor HV, Thomas JB (eds) Advances in statistical signal processing, vol. 2, JAI Press, Greenwich, CT

    Google Scholar 

  14. McDonald KF, Blum RS (2000) A statistical and physical mechanisms-based interference and noise model for array observations. IEEE Trans Signal Process 48(7):2044–2056

    Article  Google Scholar 

  15. Middleton D (1995) Threshold detection in correlated non-Gaussian noise fields. IEEE Trans Inf Theory 41(4):976–1000

    Article  MathSciNet  Google Scholar 

  16. Yang X, Petropulu AP (2002) Interference modeling in radio communication networks. In: Proakis J (ed) Trends in wireless indoor networks, Wiley encyclopedia of telecommunications, Wiley, New York

    Google Scholar 

  17. Navaie K, Valaee S, Sharafat AR, Sousa ES (2006) IEEE Trans Wireless Commun 5(2): 384–393

    Article  Google Scholar 

  18. Chong C-C, Pinto PC, Win MZ, Watanabe F, Inamura H (2008) Method and system for wireless design subject to interference contraints. US Patent Application US2008/0188253

    Google Scholar 

  19. Maras AM (1988) Locally optimum detection in moving average non-Gaussian noise. IEEE Trans Commun 36(8):907–912

    Article  Google Scholar 

  20. Maras AM (1994) Locally optimum Bayes detection in ergotic Markov noise. IEEE Trans Inf Theory 40(1):41–55

    Article  MathSciNet  Google Scholar 

  21. Samorodnitsky G, Taqqu MS (1994) Stable non-Gaussian random processes: stochastic models with infinite variance, Chapman and Hall, New York

    MATH  Google Scholar 

  22. Petropulu AP, Pesquet J-C, Yang X (2000) Power-law shot noise and relationship to long-memory processes. IEEE Trans Signal Process 48(7):1883–1892

    Article  MathSciNet  Google Scholar 

  23. Beran J (1994) Statistics for long-memory processes, Chapman & Hall, New York

    MATH  Google Scholar 

  24. Yang X, Petropulu AP (2001) The extended alternating fractal renewal process for modeling traffic in high-speed communication networks. IEEE Trans Signal Process 49(7):1349–1363

    Article  Google Scholar 

  25. Yang X, Petropulu AP (2003) Co-channel interference modeling and analysis in a Poisson field of interferers in wireless communications. IEEE Trans Signal Process 51(1):64–76

    Article  MathSciNet  Google Scholar 

  26. Kunz T, Barry T, Zhou X et al (2000) WAP traffic: description and comparison to WWW traffic. In: Proceedings of the 3rd ACM international workshop on modeling, analysis and simulation of wireless and mobile systems, Boston, USA, August 2000.

    Google Scholar 

  27. Willinger W, Taqqu MS, Sherman R, Wilson DV (1997) Self-similarity through high-variability: statistical analysis of Ethernet LAN traffic at the source level. IEEE/ACM Trans Network 5(1):71–86

    Article  Google Scholar 

  28. Arnold BC (1983) Pareto distributions, International Co. Publishing House, Maryland

    MATH  Google Scholar 

  29. Yang X, Poor HV, Petropulu AP (2004) Memoryless discrete-time signal detection in long-range dependent noise. IEEE Trans Signal Process 52(6):1607–1619

    Article  MathSciNet  Google Scholar 

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Author information

Authors and Affiliations

  1. Marvell Semiconductor Inc., 5488 Marvell Lane, Santa Clara, CA, 94087, USA

    Xueshi Yang

  2. ECE Department, Rutgers The State University of New Jersey, Piscataway, NJ, 08854, USA

    Athina P. Petropulu

Authors
  1. Xueshi Yang
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  2. Athina P. Petropulu
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Correspondence to Xueshi Yang .

Editor information

Editors and Affiliations

  1. Hunter College & Graduate Center, City University of New York, Park Ave. 695, New York, 10021, New York, USA

    Leon Cohen

  2. Dept. Electrical Engineering, Princeton University, Olden Street, Princeton, 08544, New Jersey, USA

    H. Vincent Poor

  3. Mechanical & Aerospace, Engineering Dept., Princeton University, Olden Street, Princeton, 08544, New Jersey, USA

    Marlan O. Scully

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Yang, X., Petropulu, A.P. (2012). Co-channel Interference Modeling and Analysis in a Poisson Field of Interferers in Wireless Communications. In: Cohen, L., Poor, H., Scully, M. (eds) Classical, Semi-classical and Quantum Noise. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-6624-7_19

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  • DOI: https://doi.org/10.1007/978-1-4419-6624-7_19

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4419-6623-0

  • Online ISBN: 978-1-4419-6624-7

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