Estimation of Primary Channel Activity Statistics in Cognitive Radio Based on Imperfect Spectrum Sensing

Toma, Ogeen H ORCID: 0000-0002-3969-0470, Lopez-Benitez, Miguel ORCID: 0000-0003-0526-6687, Patel, Dhaval K and Umebayashi, Kenta (2020) Estimation of Primary Channel Activity Statistics in Cognitive Radio Based on Imperfect Spectrum Sensing. IEEE TRANSACTIONS ON COMMUNICATIONS, 68 (4). pp. 2016-2031.

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Official URL: http://dx.doi.org/10.1109/tcomm.2020.2965944

Abstract

Primary channel statistics have recently gained increasing attention due to its remarkable role in the performance improvement of Dynamic Spectrum Access (DSA)/Cognitive Radio (CR) systems. These statistics can be calculated from the outcomes of spectrum sensing, which is the well-known method used to identify the available instantaneous opportunities in the spectrum. Computing statistical information from spectrum sensing, however, may sometimes be unreliable due to the fact that spectrum sensing is imperfect in the real world and errors are likely to occur in the sensing decisions. In this context, this work provides a detailed analysis of a broad range of primary channel statistics under Imperfect Spectrum Sensing (ISS) and finds a set of closed-form expressions for the calculated statistics under ISS as a function of the original primary channel statistics, probability of error, and the employed sensing period. In addition, the obtained mathematical expressions are employed to find and propose novel estimators for the primary channel statistics, which outperform the existing estimators in the literature and can provide accurate estimations of the original statistics even under high probability of error of spectrum sensing. The correctness of the obtained analytical expressions and the accuracy of the proposed estimators are corroborated with both simulation and experimental results.

Item Type:	Article
Uncontrolled Keywords:	Sensors, Channel estimation, Estimation, Signal to noise ratio, Probability, Analytical models, Wireless communication, Cognitive radio, dynamic spectrum access, primary activity statistics, spectrum sensing
Depositing User:	Symplectic Admin
Date Deposited:	23 Jan 2020 09:35
Last Modified:	15 Mar 2024 06:09
DOI:	10.1109/TCOMM.2020.2965944
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3071603