Journal ArticleDOI
Multiple antenna spectrum sensing in cognitive radios
TLDR
The simulation results provide the available traded-off in using multiple antenna techniques for spectrum sensing and illustrates the robustness of the proposed GLR detectors compared to the traditional energy detector when there is some uncertainty in the given noise variance.Abstract:
In this paper, we consider the problem of spectrum sensing by using multiple antenna in cognitive radios when the noise and the primary user signal are assumed as independent complex zero-mean Gaussian random signals. The optimal multiple antenna spectrum sensing detector needs to know the channel gains, noise variance, and primary user signal variance. In practice some or all of these parameters may be unknown, so we derive the generalized likelihood ratio (GLR) detectors under these circumstances. The proposed GLR detector, in which all the parameters are unknown, is a blind and invariant detector with a low computational complexity. We also analytically compute the missed detection and false alarm probabilities for the proposed GLR detectors. The simulation results provide the available traded-off in using multiple antenna techniques for spectrum sensing and illustrates the robustness of the proposed GLR detectors compared to the traditional energy detector when there is some uncertainty in the given noise variance.read more
Citations
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Journal ArticleDOI
Lowering the SNR Wall for Energy Detection Using Cross-Correlation
TL;DR: The SNR wall for cross-correlation is mathematically quantify, showing that it linearly scales with the amount of noise correlation, which results in higher sensitivity, which is significantly better than that for autocorrelation.
Journal ArticleDOI
Distribution of the Ratio of the Largest Eigenvalue to the Trace of Complex Wishart Matrices
TL;DR: It is shown that the exact decision threshold based B-GLRT detector gives superior performance over the asymptotic decision threshold schemes proposed in the literature, which leads to efficient spectrum usage in cognitive radio.
Journal ArticleDOI
An Eigenvalue-Moment-Ratio Approach to Blind Spectrum Sensing for Cognitive Radio Under Sample-Starving Environment
TL;DR: The EMR detector is developed from the RMT perspective and utilizes all the signal eigenvalues for detection, it can be superior to state-of-the-art detection algorithms, particularly for relatively small samples.
Journal ArticleDOI
Polarity-Coincidence-Array Based Spectrum Sensing for Multiple Antenna Cognitive Radios in the Presence of Non-Gaussian Noise
TL;DR: The use of a non-parametric and easily implementable detection device, namely the polarity-coincidence-array (PCA) detector, is proposed for the detection of weak primary signals with a cognitive radio equipped with multiple antennas and its performance is evaluated in the presence of heavy-tailed noise.
Journal ArticleDOI
On the Performance of Covariance Based Spectrum Sensing for Cognitive Radio
TL;DR: The distribution of the test-statistic for the covariance based detection is studied in order to obtain the mathematical expressions of false alarm probability (Pf) and detection probability (pd) and the formulation of decision threshold λ for any Pf is presented.
References
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Cognitive radio: brain-empowered wireless communications
TL;DR: Following the discussion of interference temperature as a new metric for the quantification and management of interference, the paper addresses three fundamental cognitive tasks: radio-scene analysis, channel-state estimation and predictive modeling, and the emergent behavior of cognitive radio.
Proceedings Article
Wireless communications
TL;DR: This book aims to provide a chronology of key events and individuals involved in the development of microelectronics technology over the past 50 years and some of the individuals involved have been identified and named.
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Detection of signals by information theoretic criteria
Mati Wax,Thomas Kailath +1 more
TL;DR: Simulation results that illustrate the performance of the new method for the detection of the number of signals received by a sensor array are presented.
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