Performance Analysis of Various Eigenvalue-Based Spectrum Sensing Algorithms for Different Types of Primary User Signals
Spectrum sensing plays a very essential role in the implementation of cognitive radio networks. Eigenvalue-based spectrum sensing algorithms have been comprehensively discussed in the literature, for detection of primary user signal in the case of uncerta
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Abstract Spectrum sensing plays a very essential role in the implementation of cognitive radio networks. Eigenvalue-based spectrum sensing algorithms have been comprehensively discussed in the literature, for detection of primary user signal in the case of uncertain noise. For detection of signals, the test statistics of these algorithms depend on the eigenvalues of the covariance matrix of the received signal. Eigenvalues generally capture the correlation among the signal samples. In this context, we have examined the sensing performance of various eigenvalue-based spectrum sensing techniques for different types of primary user signals having different levels of correlation. In results, it has been noticed that the sensing performance of the algorithms relies on the type of primary user signal transmitted.
Keywords Cognitive radio Spectrum sensing Energy detection Eigenvalue-based detection Random matrix theory
1 Introduction The accelerated growth in the wireless services and their applications has induced the requirement of more and more spectrum, which is a scarce resource. The prevailing spectrum allocation policy allots spectrum to some users (also known as licensed users) for exclusive access. However, it has been revealed in a survey conducted under the supervision of the Federal Communications Commission (FCC) [1] that the part of the spectrum, which is assigned to the licensed users, remains unexploited maximum of the time. This underutilization of the radio
P. Verma (&) B. Singh Department of Electronics and Communication Engineering, National Institute of Technology Kurukshetra, Kurukshetra, India e-mail: [email protected] B. Singh e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2018 A. Kalam et al. (eds.), Advances in Electronics, Communication and Computing, Lecture Notes in Electrical Engineering 443, https://doi.org/10.1007/978-981-10-4765-7_41
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spectrum motivated researchers to search for some technology that can handle this issue and use the radio spectrum effectively. Cognitive radio (CR) is a recent archetype, which attempts to solve this issue of spectrum underutilization through opportunistic spectrum access [2, 3]. Under this technology, secondary users (SUs) or unlicensed users can transmit in a frequency band of licensed users (or primary users (PUs)) provided the band is not being used. CR has the ability to alter its transmission specifications like modulation scheme, transmit power, operating frequency, and other parameters, as per the environment in its vicinity. To enable this technology, spectrum sensing plays a very imperative role. SUs identify the vacant spectrum with the help of different spectrum sensing algorithms. If the PU is found absent, then the band can be used by SUs, otherwise sensing is done again to identify other vacant bands. There are numerous spectrum sensing techniques debated in the literature, each having its own advantages and disadvantages [4, 5]. Among all the sensing algorithms, energy detect
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