Copula-Based Cooperative Sensing of OFDM Signals in Cognitive Radios

Akhil Singh, Sai Praneeth Chokkarapu, Sachin Chaudhari, Pramod K. Varshney

Research output: Chapter in Book/Entry/PoemConference contribution

1 Scopus citations

Abstract

This paper proposes the use of copula theory for cooperative spectrum sensing (CSS) of orthogonal frequency-division multiplexing (OFDM) based primary user (PU). A distributed detection model is assumed where secondary users (SUs) employ autocorrelation detectors (ADs) for the detection of a PU. In the presence of a PU, it is assumed that the observations across different SUs and subsequently the decision statistics are dependent. For the fusion of these dependent statistics, different copulas such as t-copula, Gaussian, Clayton and Gumbel are employed. In the presence of dependence among decision statistics, significant improvement in detection performance is observed while using copula theory instead of the traditional assumption of independence. Simulation results are presented to show the superiority of copula-based spectrum sensing.

Original languageEnglish (US)
Title of host publication2020 International Conference on COMmunication Systems and NETworkS, COMSNETS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages446-451
Number of pages6
ISBN (Electronic)9781728131870
DOIs
StatePublished - Jan 2020
Event2020 International Conference on COMmunication Systems and NETworkS, COMSNETS 2020 - Bengaluru, India
Duration: Jan 7 2020Jan 11 2020

Publication series

Name2020 International Conference on COMmunication Systems and NETworkS, COMSNETS 2020

Conference

Conference2020 International Conference on COMmunication Systems and NETworkS, COMSNETS 2020
Country/TerritoryIndia
CityBengaluru
Period1/7/201/11/20

Keywords

  • Autocorrelation detector
  • cognitive radio
  • cooperative spectrum sensing
  • copula
  • dependence

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Signal Processing

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