Statistics of co-channel interference in a field of Poisson and Poisson-Poisson clustered interferers

  • Authors:

  • Kapil Gulati;Brian L. Evans;Jeffrey G. Andrews;Keith R. Tinsley

  • Affiliations:

  • Department of Electrical and Computer Engineering, The University of Texas at Austin, TX;Department of Electrical and Computer Engineering, The University of Texas at Austin, TX;Department of Electrical and Computer Engineering, The University of Texas at Austin, TX;Intel Corporation, Santa Clara, CA

  • Venue:
  • IEEE Transactions on Signal Processing
  • Year:
  • 2010

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Abstract

With increasing spatial reuse of radio spectrum, co-channel interference is becoming a dominant noise source and may severely degrade the communication performance of wireless transceivers. In this paper, we consider the problem of statistical-physical modeling of co-channel interference from an annular field of Poisson or Poisson-Poisson cluster distributed interferers. Poisson and Poisson-Poisson cluster processes are commonly used to model interferer distributions in large wireless networks without and with interferer clustering, respectively. Further, by considering the interferers distributed over a parametric annular region, we derive interference statistics for finite-and infinite- area interference region with and without a guard zone around the receiver. Statistical modeling of interference is a useful tool to analyze outage probabilities in wireless networks and design interference-aware transceivers. Our contributions include: 1) developing a unified framework for deriving interference models for various wireless network environments; 2) demonstrating the applicability of the symmetric alpha stable and Gaussian mixture (with Middleton Class A as a particular form) distributions in modeling co-channel interference; and 3) deriving analytical conditions on the system model parameters for which these distributions accurately model the statistical properties of the interference. Applications include co-channel interference modeling for various wireless networks, including wireless ad hoc, cellular, local area, and femtocell networks.