Stochastic-Geometry Based Characterization of Aggregate Interference in TVWS Cognitive Radio Networks

Madhukar Mohanrao Deshmukh; S. M. Zafaruddin; Albena Mihovska; Ramjee Prasad

doi:10.1109/JSYST.2019.2904584

Stochastic-Geometry Based Characterization of Aggregate Interference in TVWS Cognitive Radio Networks

Madhukar Mohanrao Deshmukh
, S. M. Zafaruddin
, Albena Mihovska
, Ramjee Prasad

Bar-Ilan University - The Alexander Kofkin Faculty of Engineering

Birla Institute of Technology and Science Pilani
Aarhus University

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

In this paper, we characterize the worst-case interference for a finite-area TV white space heterogeneous network using the tools of stochastic geometry. We derive closed-form expressions on the probability distribution function (PDF) and an average value of the aggregate interference for various values of path loss exponent under Rayleigh fading channel. The proposed characterization of the interference is simple and can be used in improving the spectrum access techniques. Using the derived PDF, we demonstrate the performance gain in the spectrum detection of an eigenvalue-based detector for cognitive radio networks.

Original language	English
Article number	8678398
Pages (from-to)	2728-2731
Number of pages	4
Journal	IEEE Systems Journal
Volume	13
Issue number	3
DOIs	https://doi.org/10.1109/JSYST.2019.2904584
State	Published - Sep 2019

Bibliographical note

Publisher Copyright:
© 2007-2012 IEEE.

Keywords

Aggregate interference
cognitive radio (CR)
stochastic geometry
television white space (TVWS)

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10.1109/JSYST.2019.2904584

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title = "Stochastic-Geometry Based Characterization of Aggregate Interference in TVWS Cognitive Radio Networks",

abstract = "In this paper, we characterize the worst-case interference for a finite-area TV white space heterogeneous network using the tools of stochastic geometry. We derive closed-form expressions on the probability distribution function (PDF) and an average value of the aggregate interference for various values of path loss exponent under Rayleigh fading channel. The proposed characterization of the interference is simple and can be used in improving the spectrum access techniques. Using the derived PDF, we demonstrate the performance gain in the spectrum detection of an eigenvalue-based detector for cognitive radio networks.",

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AU - Prasad, Ramjee

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Stochastic-Geometry Based Characterization of Aggregate Interference in TVWS Cognitive Radio Networks

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