Fixed and dynamic threshold selection criteria in energy detection for cognitive radio communication systems

Alok Kumar, Prabhat Thakur, Shweta Pandit, G. Singh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Citations (Scopus)

Abstract

Spectrum sensing is a key step in cognitive radio communication systems. The probability of detection and probability of false-alarm are two crucial performance parameters in spectrum sensing. In this paper, we have presented the effect of selection of fixed and dynamic threshold scheme of energy detection technique on various spectrum sensing performance parameters such as probability of detection, probability of false-alarm, and probability of error, considering the constant noise variance in the channel. In addition to this, we have also computed the minimum value of time-bandwidth product when the noise variance is constant or variable in the channel.

Original languageEnglish
Title of host publication2017 10th International Conference on Contemporary Computing, IC3 2017
EditorsSrinivas Alum, Ananth Kalyanararnan, Bora Ucar, Kishor Kothapalli, Mahantesh Halappanavar, Kamesh Madduri, Madhu Govindaraju, Yinglong Xia, Sushil Prasad, Martina Barnas, Ashish Sureka, Pankesh Patel, Vikas Saxena, Sanjay Goel
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781538630778
DOIs
Publication statusPublished - 2 Jul 2017
Externally publishedYes
Event10th International Conference on Contemporary Computing, IC3 2017 - Noida, India
Duration: 10 Aug 201712 Aug 2017

Publication series

Name2017 10th International Conference on Contemporary Computing, IC3 2017
Volume2018-January

Conference

Conference10th International Conference on Contemporary Computing, IC3 2017
Country/TerritoryIndia
CityNoida
Period10/08/1712/08/17

Keywords

  • CFAR
  • Cognitive radio
  • SNR wall
  • energy detection
  • fixed and dynamic threshold

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Health Informatics
  • Computer Networks and Communications
  • Computer Science Applications

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