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

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

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


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 languageEnglish
Article number8678398
Pages (from-to)2728-2731
Number of pages4
JournalIEEE Systems Journal
Issue number3
StatePublished - Sep 2019

Bibliographical note

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© 2007-2012 IEEE.


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


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