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 (P_fa). The user presence is estimated based on the parameters P_fa, probability of detection (P_D) and receiver operating characteristics (ROC). Matched filter detection (MFD) and Neyman Pearson (NP) observer approaches are existing methods used to identify the P_fa. MFD measured ROC with different algorithms and suggests NP observer to improve the P_D and minimise the P_fa. 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 P_fa are identified, tabulated for different SNR levels. Finally, comparative analysis has been proposed between MDI-SS with NP observer for P_D and P_fa.

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.2017.091524

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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