Complex random matrices and multiple-antenna spectrum sensing

T. Ratnarajah*, C. Zhong, A. Kortun, M. Sellathurai, C. B. Papadias

*Corresponding author for this work

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

Abstract / Description of output

In this paper, we study the eigenvalue-based spectrum sensing techniques for multiple-antenna cognitive radio networks. First, we study the extreme eigenvalue distributions of a complex Wishart matrix and then, in contrast to the asymptotic analysis reported in the literature, we derive the exact distribution of the test statistics of (i) maximum eigenvalue detector (MED) (ii) maximum-minimum eigenvalue (MME) detector and (iii) energy with minimum eigenvalue (EME) detector for finite number of samples (n) and finite number of antennas (m). These distributions are represented by complex hypergeometric functions of matrix argument, which can be expressed in terms of complex zonal polynomials. We also describe the method to compute these complex hypergeometric functions. Based on these exact distribution of the test statistics we find the exact decision thresholds as a function of the desired probability of false-alarms for MED, MME and EME. Simulation results show superior performance compared to the decision thresholds obtained from asymptotic (i.e, n,m → ∞) distributions.

Original languageEnglish
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Pages3848-3851
Number of pages4
DOIs
Publication statusPublished - 18 Aug 2011
Event36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Prague, United Kingdom
Duration: 22 May 201127 May 2011

Conference

Conference36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011
Country/TerritoryUnited Kingdom
CityPrague
Period22/05/1127/05/11

Keywords / Materials (for Non-textual outputs)

  • Cognitive radio
  • multiple-antenna spectrum sensing
  • Wishart matrix

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