Auto-Correlation based Spectrum Sensing at Low SNR for Cognitive Radio
نویسندگان
چکیده
A challenging problem in Cognitive radio is that the secondary users in cognitive radios must be able to detect primary users under low signal-to-noise ratio (SNR) and dispersive channel. Spectrum sensing based on auto-correlation of the received signal samples being more prone to correlate under dispersive condition, has been investigated. Simplified theoretical expressions for probability of false alarm and probability of detection of the auto-correlation based algorithm are derived in the presence of multi-path fading channel. Spectrum of an unknown primary signal has been obtained through auto-regressive parametric signal modeling. By the proposed auto-correlation technique the detection probability near unity can be achieved at finite input samples and at a very low SNR for OFDM DVB-T signal and a wireless FM microphone signal in VHF band. It is found that dimension of auto-correlation matrix and signal
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