Robust Cooperative Spectrum Sensing for MIMO Cognitive Radio Networks under CSI Uncertainty

Adarsh Patel, Hukma Ram, Aditya K. Jagannatham, Pramod Kumar Varshney

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

This paper considers the problem of cooperative spectrum sensing in multiuser multiple-input multiple-output (MIMO) cognitive radio networks considering the presence of uncertainty in the channel state information (CSI) of the secondary user channels available at the fusion center. Several schemes are proposed that employ cooperative decision rules based on local sensor decisions transmitted to the fusion center by the cooperating nodes over an orthogonal multiple access channel (MAC). First, fusion rules are derived under perfect CSI at the fusion center for both antipodal and non-antipodal signaling. Then, a robust detector, termed the uncertainty statistics-based likelihood ratio test (US-LRT), which optimally combines the decisions of different secondary users, is obtained for scenarios with CSI uncertainty. A generalized likelihood ratio test (GLRT) based robust detector is also derived for this scenario. Closed form expressions are obtained to characterize the probabilities of false alarm (<formula><tex>$P_{FA}$</tex></formula>) and detection (<formula><tex>$P_{D}$</tex></formula>) at the fusion center. Simulation results are presented to compare the performance of the proposed schemes with that of the conventional uncertainty agnostic detectors and also to corroborate the analytical expressions developed.

Original languageEnglish (US)
JournalIEEE Transactions on Signal Processing
DOIs
StateAccepted/In press - Oct 1 2017

Keywords

  • Cognitive radio
  • Cognitive radio networks
  • cooperative spectrum sensing
  • Detectors
  • generalized likelihood ratio test (GLRT)
  • likelihood ratio test (LRT)
  • MIMO
  • multiple-input multiple-output (MIMO)
  • Receiving antennas
  • Uncertainty
  • Wireless sensor networks

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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