For Full-Text PDF, please login, if you are a member of IEICE,|
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
A Blind OFDM Detection and Identification Method Based on Cyclostationarity for Cognitive Radio Application
Ning HAN Sung Hwan SOHN Jae Moung KIM
IEICE TRANSACTIONS on Communications
Publication Date: 2009/06/01
Online ISSN: 1745-1345
Print ISSN: 0916-8516
Type of Manuscript: LETTER
Category: Fundamental Theories for Communications
cognitive radio, spectrum sensing, OFDM, cyclic autocorrelation, signal detection and identification,
Full Text: PDF>>
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.