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Keywords
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Spectrum sensing, Expert algorithm, Spreading sequences length estimation, MC-CDMA, Algebraic properties, Hypothesis test
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Abstract
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The Spectrum sensing is an essential function in the various types of fifth-generation (5G) networks and beyond,
which can address some of the fundamental challenges for 5G, including spectral efficiency and the reliable
connectivity of internet of things (IoT) devices. In this article, we aim to present a real-time and expert spectrum
sensing algorithm for 5G cellular networks. The novel method exploits the cyclostationary nature of the spread
spectrum signal without any prior knowledge of its structure. In the proposed algorithm, the multi-carrier code
division multiple access (MC-CDMA) technique will be utilized by the users. The multidimensional spectrum
sensing method introduces a novel correlation measurement based on the algebraic characteristics of pseudonoise (PN) sequences. The existence of periodic peaks in the new correlation function presents new modelling
of the emergence of the spread-spectrum signal. Our basis for this is to use the cyclostatic property of the pseudonoise code and obtain the distance between the two main peaks in the received signal correlation. According to
the simulation results, the proposed algorithm exhibits excellent performance in signal detection and exact
estimation of PN code length in low SNRs and multipath fading environments
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