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Modeling Heterogeneous Network Interference Using Poisson Point Processes

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Heath, Robert W., Kountouris, Marios, Bai, Tianyang·2013·IEEE Transactions on Signal Processing

Abstract

Cellular systems are becoming more heterogeneous with the introduction of low power nodes including femtocells, relays, and distributed antennas. Unfortunately, the resulting interference environment is also becoming more complicated, making evaluation of different communication strategies challenging in both analysis and simulation. Leveraging recent applications of stochastic geometry to analyze cellular systems, this paper proposes to analyze downlink performance in a fixed-size cell, which is inscribed within a weighted Voronoi cell in a Poisson field of interferers. A nearest out-of-cell interferer, out-of-cell interferers outside a guard region, and cross-tier interferers are included in the interference calculations. Bounding the interference power as a function of distance from the cell center, the total interference is characterized through its Laplace transform. An equivalent marked process is proposed for the out-of-cell interference under additional assumptions. To facilitate simplified calculations, the interference distribution is approximated using the Gamma distribution with second order moment matching. The Gamma approximation simplifies calculation of the success probability and average rate, incorporates small-scale and large-scale fading, and works with co-tier and cross-tier interference. Simulations show that the proposed model provides a flexible way to characterize outage probability and rate as a function of the distance to the cell edge.

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Metadata

Authors
Heath, R. W., Kountouris, M., & Bai, T.
Venue
IEEE Transactions on Signal Processing
Published
2013-08
Volume
61
Issue
16
Pages
4114-4126
ISSN
  • 1053-587X (ISSN-L)
  • 1941-0476
OpenAlex
W2081450055
Cited by
423
References
0
FWCI
36.15
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Modeling Heterogeneous Network Interference Using Poisson Point Processes. https://app.cochat.ai/papers/10.1109/tsp.2013.2262679
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Heath, R. W., Kountouris, M., & Bai, T. (2013). Modeling Heterogeneous Network Interference Using Poisson Point Processes. IEEE Transactions on Signal Processing. https://doi.org/10.1109/tsp.2013.2262679

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