A Blind OFDM Detection and Identification Method Based on Cyclostationarity for Cognitive Radio Application

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概要

• 論文の詳細を見る

• The key issue in cognitive radio is to design a reliable spectrum sensing method that is able to detect the signal in the target channel as well as to recognize its type. In this paper, focusing on classifying different orthogonal frequency-division multiplexing (OFDM) signals, we propose a two-step detection and identification approach based on the analysis of the cyclic autocorrelation function. The key parameters to separate different OFDM signals are the subcarrier spacing and symbol duration. A symmetric peak detection method is adopted in the first step, while a pulse detection method is used to determine the symbol duration. Simulations validate the proposed method.

• （社）電子情報通信学会の論文
• 2009-06-01

著者

• Sohn Sung

  INHA-WiTLAB, INHA University

• Sohn Sung

  Inha-witlab Inha University

• HAN Ning

  INHA-WiTLAB, Inha University

• KIM Ja

  INHA-WiTLAB, Inha University

• Kim Ja

  Inha-witlab Inha University

• Han Ning

  Inha-witlab Inha University

関連論文

• Cooperative Network Management in Cognitive Radio Network Assisted Satellite
• A Blind OFDM Detection and Identification Method Based on Cyclostationarity for Cognitive Radio Application
• PAPR Reduction Using Hybrid Schemes for Satellite Communication System(Transmission Technology)

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