Non-coherent power decomposition-based energy detection for cooperative spectrum sensing in cognitive radio networks

Bingxuan Zhao, Shigeru Shimamoto

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

As the fundamental component of dynamic spectrum access, implementing spectrum sensing is one of the most important goals in cognitive radio networks due to its key functions of protecting licensed primary users from harmful interference and identifying spectrum holes for the improvement of spectrum utilization. However, its performance is generally compromised by the interference from adjacent primary channels. To cope with such interference and improve detection performance, this paper proposes a non-coherent power decomposition-based energy detection method for cooperative spectrum sensing. Due to its use of power decomposition, interference cancellation can be applied in energy detection. The proposed power decomposition does not require any prior knowledge of the primary signals. The power detection with its interference cancellation can be implemented indirectly by solving a non-homogeneous linear equation set with a coefficient matrix that involves only the distances between primary transmitters and cognitive secondary users (SUs). The optimal number of SUs for sensing a single channel and the number of channels that can be sensed simultaneously are also derived. The simulation results show that the proposed method is able to cope with the expected interference variation and achieve higher probability of detection and lower probability of false alarm than the conventional method in both hard combining and soft combining scenarios.

Original languageEnglish
Pages (from-to)234-242
Number of pages9
JournalIEICE Transactions on Communications
VolumeE-95-B
Issue number1
DOIs
Publication statusPublished - 2012 Jan

Keywords

  • Cooperative spectrum sensing
  • Energy detection
  • Hypothesis testing
  • Interference cancellation
  • Power decomposition

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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