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In this paper, we study the performance of sequential detectors (SDs) in cooperative cognitive radio networks. In the fixed sample size (FSS) detectors, the generalized likelihood ratio (GLR) test, obtained through substituting the maximum likelihood (ML) estimates of the unknown parameters in the likelihood functions, is a current alternative when deriving the uniformly most powerful (UMP) test is...
Recently several time-domain approaches relying on the generalized likelihood ratio test (GLRT) paradigm have been proposed for multiple antenna spectrum sensing in cognitive radios. These approaches are suitable for flat-fading channels in white noise with equal noise variances across antennas; knowledge of the noise variance is not required, unlike the energy detector. In this paper we investigate...
In this paper, we address the problem of cooperatively detecting a primary user with unknown transmit power among multiple cognitive radio (CR) users with their location information available at the CR base station. A generalized likelihood ratio test (GLRT) is developed at the CR base station to first estimate the transmit power of the primary user and then detect the primary user signal. The maximum...
We propose a computationally efficient spectrum sensing solution for an Orthogonal Frequency Division Multiplexing (OFDM) signal in a frequency selective fading channel with Additive White Gaussian Noise (AWGN). Our assumption is that the data symbols, channel coefficients and the noise variance are all unknown. The nature of the problem leads us to find an invariant detector, the optimum one is Uniformly...
One of the key problems in cognitive radio (CR) is the detection of primary activity in order to determine which parts of the spectrum are available for opportunistic access. In this work, we present a new multiantenna detector which fully exploits the spatial and temporal structure of the signals. In particular, we derive the generalized likelihood ratio test (GLRT) for the problem of detecting a...
This paper deals with the local spectrum sensing problem in non-Gaussian noise. It is of great importance to reliably detect the presence of licensed users in cognitive radio. This task highly depends on the noise distribution, thus it is important to characterize the noise behavior as best as possible. Although Gaussian assumption for noise is of interest due to many reasons, it sometimes fails to...
One of the key problems in cognitive radio (CR) is the detection of primary activity in order to determine which parts of the spectrum are available for opportunistic access. This detection task is challenging, since the wireless environment often results in very low SNR conditions. Moreover, calibration errors and imperfect analog components at the CR spectral monitor result in uncertainties in the...
In this paper, we consider the problem of detecting a primary user in a cognitive radio network by employing multiple antennas at the cognitive receiver. In vehicular applications, cognitive radios typically transit regions with differing densities of primary users. Therefore, speed of detection is key, and so, detection based on a small number of samples is particularly advantageous for vehicular...
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