Performance Analysis of Three Spectrum Sensing Detection Techniques with Ambient Backscatter Communication in Cognitive Radio Networks

Abstract: In wireless communications, the Ambient Backscatter Communication (AmBC) technique is a promising approach, detecting user presence accurately at low power levels. At low power or a low Signal-to-Noise Ratio (SNR), there is no dedicated power for the users. Instead, they can transmit information by reflecting the ambient Radio Frequency (RF) signals in the spectrum. Therefore, it is essential to detect user presence in the spectrum for the transmission of data without loss or without collision at a specific time. In this paper, the authors proposed a novel Spectrum Sensing (SS) detection technique in the Cognitive Radio (CR) spectrum, by developing the AmBC. Novel Matched Filter Detection with Inverse covariance (MFDI), Cyclostationary Feature Detection with Inverse covariance (CFDI) and Hybrid Filter Detection with Inverse covariance (HFDI) approaches are used with AmBC to detect the presence of users at low power levels. The performance of the three detection techniques is measured using the parameters of Probability of Detection (PD), Probability of False Alarms (Pfa), Probability of Missed Detection (Pmd), sensing time and throughput at low power or low SNR. The results show that there is a significant improvement via the HFDI technique for all the parameters.

Author(s): Shayla Islam, Anil Kumar Budati, Mohammad Kamrul Hasan, Saoucene Mahfoudh and Syed Bilal Hussian Shah

Date Published: 29 December 2022

Depositing User: Basiratu Kolawole

DOI: https://doi.org/10.32604/cmes.2023.027595

Keywords: Ambient backscatter communication, cognitive radio, MFDI, CFDI & HFDI

Page(s): 813-825

Place of publication: Malaysia

Publication title: Computer Modeling in Engineering and Sciences

Publisher: Tech Science Press

Subject(s): Electrical and Computer Engineering