Title: A novel primary user detection using OFDM internal structures on Raspberry Pi
Authors: Mobin Alizadeh; Javad Kazemitabar
Addresses: Babol Noshirvani University of Technology, Babol, Iran ' Babol Noshirvani University of Technology, Babol, Iran
Abstract: Using autocorrelation-based techniques for detecting (Orthogonal Frequency Division Multiplexing) OFDM signals in cognitive radio systems is well studied. Correlating the cyclic prefix with its replica provides a means to distinguish an OFDM signal from noise as shown in previous research. A subtle yet crucial shortcoming of this autocorrelation-based method is that it may mistake a sinusoidal for an OFDM signal. All for that to happen is for the sinusoid to have the proper period; the algorithm would then find a repeating pattern and declare OFDM signal detection. In this paper, we modify the conventional autocorrelation-based method to avoid generating false-alarms in the presence of sinusoidal signals. We test our algorithm on a custom-built Raspberry Pi.
Keywords: cognitive radio; primary user detection; OFDM; spectrum sensing; Raspberry Pi.
DOI: 10.1504/IJWMC.2022.127602
International Journal of Wireless and Mobile Computing, 2022 Vol.23 No.3/4, pp.329 - 337
Received: 12 Jan 2022
Received in revised form: 17 May 2022
Accepted: 02 Jul 2022
Published online: 12 Dec 2022 *