Title: MDI-SS: matched filter detection with inverse covariance matrix-based spectrum sensing in cognitive radio

Authors: Budati Anil Kumar; P. Trinatha Rao

Addresses: Department of ECE, Vignana Bharathi Institute of Technology, Hyderabad-501301, India ' Department of ECE, GITAM University, Hyderabad-502329, India

Abstract: Spectrum sensing has been a major issue while dealing with cognitive radio (CR) networks. Predominantly the situation arises where noise is falsely interpreted as primary user signal called as probability of false alarm (Pfa). The user presence is estimated based on the parameters Pfa, probability of detection (PD) and receiver operating characteristics (ROC). Matched filter detection (MFD) and Neyman Pearson (NP) observer approaches are existing methods used to identify the Pfa. MFD measured ROC with different algorithms and suggests NP observer to improve the PD and minimise the Pfa. This paper proposes a novel method of matched filter detection with inverse covariance matrix-based spectrum sensing (MDI-SS). The ROC is measured, compared between MDI-SS and MFD. Next by comparing NP observer and MDI-SS, the affected samples of Pfa are identified, tabulated for different SNR levels. Finally, comparative analysis has been proposed between MDI-SS with NP observer for PD and Pfa.

Keywords: cognitive radio networks; matched filter detection; MFD; Neyman Pearson observer; generalised log likelihood ratio test; GLRT; probability of false alarm; probability of detection; receiver operating characteristics; ROC; spectrum sensing; 5G mobile communications; additive white noise; AWGN.

DOI: 10.1504/IJITST.2017.10012599

International Journal of Internet Technology and Secured Transactions, 2017 Vol.7 No.4, pp.353 - 363

Received: 04 Apr 2017
Accepted: 25 May 2017

Published online: 04 May 2018 *

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