Distributed autocorrelation-based sequential detection of OFDM signals in cognitive radios

Sachin Chaudhari, Visa Koivunen, H. Vincent Poor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

26 Scopus citations

Abstract

This paper addresses the problem of collaborative spectrum sensing using sequential detection (SD) in cognitive radios. The goal of sequential processing is to reduce the delay and amount of data needed in identifying underutilized spectrum. Each secondary user (SU) employs a simple and computationally efficient autocorrelation-based detector for Orthogonal Frequency Division Multiplexing (OFDM) signals of the primary user (PU). The decision statistics from individual detectors are combined in a fusion center that may be a separate node or one of the secondary users. The statistical properties of the decision statistics are established. The performance of the scheme is studied by theory and simulations. A comparison of the SD scheme with the Neyman-Pearson Fixed Sample Size (FSS) test for the same false alarm and missed detection probabilities is also carried out.

Original languageEnglish (US)
Title of host publicationProceedings of the 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications, CrownCom 2008
DOIs
StatePublished - 2008
Event3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications, CrownCom 2008 - Singapore, Singapore
Duration: May 15 2008May 17 2008

Publication series

NameProceedings of the 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications, CrownCom 2008

Other

Other3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications, CrownCom 2008
Country/TerritorySingapore
CitySingapore
Period5/15/085/17/08

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Human-Computer Interaction
  • Communication

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