On the eigenvalue-based spectrum sensing and secondary user throughput

Ayse Kortun, Tharmalingam Ratnarajah, Mathini Sellathurai, Ying Chang Liang, Yonghong Zeng

Research output: Contribution to journalArticle

34 Citations (Scopus)

Abstract

In this paper, we study the tradeoff between sensing time and achievable throughput of the secondary user that employs robust eigenvalue-based spectrum sensing techniques in the presence of noise uncertainty. First, we study exact distributions of the test statistics for two types of robust eigenvalue-based sensing techniques, namely, the blind generalized likelihood ratio test (B-GLRT) detection and energy with minimum eigenvalue (EME) detection. The developed threshold setting is more accurate than benchmark methods in achieving a target constant false alarm rate (CFAR). Second, prior to the throughput analysis, the necessary asymptotic detection and false alarm probabilities under noise uncertainty are formulated for eigenvalue-based detectors such as maximum eigenvalue detection (MED) and maximum-minimum eigenvalue (MME) detection. Finally, the throughput is maximized using eigenvalue-based spectrum sensing techniques which are B-GLRT, EME, MME, and MED detectors. The results are compared with the commonly used energy detector (ED). An improved achievable throughput is obtained under low-signal-to-noise-ratio (SNR) regime by incorporating the robust eigenvalue-based techniques, which are insusceptible to noise uncertainty.

Original languageEnglish
Article number6601644
Pages (from-to)1480-1486
Number of pages7
JournalIEEE Transactions on Vehicular Technology
Volume63
Issue number3
DOIs
Publication statusPublished - 1 Jan 2014

Keywords

  • Cognitive radio (CR)
  • eigenvalue-based detection
  • sensing-throughput tradeoff
  • spectrum sensing

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Aerospace Engineering
  • Automotive Engineering
  • Computer Networks and Communications
  • Applied Mathematics

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