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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Proceedings ArticleDOI
Asymptotic analysis of eigenvalue-based blind Spectrum Sensing techniques
TL;DR: It is shown that noise correlation significantly degrades the performance of ST and JD detectors in practical scenarios, and the SLE detector is the best for a range of scenarios, followed by JD, SCN, ST.
Journal ArticleDOI
Improving Detection Delay in Cognitive Radios Using Secondary-User Receiver Statistics
TL;DR: This paper constructs a decision statistic for SM based on the SU's receiver error count, and evaluates the detection probability of SM in the presence of interference from the PU signal, and derives closed-form formulas for channel utilization and detection delay using two Markov chain models.
Journal ArticleDOI
Distributed Largest Eigenvalue-Based Spectrum Sensing Using Diffusion LMS
TL;DR: This paper proposes a distributed detection scheme for cognitive radio (CR) networks, based on the largest eigenvalues (LEs) of adaptively estimated correlation matrices (CMs), assuming that the primary user signal is temporally correlated.
Proceedings ArticleDOI
Sigmoid function detector in the Presence of heavy-tailed noise for multiple antenna cognitive radio networks
Mohammad Yavari Manesh,Ali Olfat +1 more
TL;DR: It is shown through simulations that the sigmoid detector outperforms well known detectors such as SL-PCA (soft-limited polarity coincidence array) with soft limiting function, PCA (polarity coincidencearray) and the energy detection (ED) scheme in the presence of heavy-tailed GGN.
Journal ArticleDOI
Optimized Error Probability for Weighted Collaborative Spectrum Sensing in Time- and Energy-Limited Cognitive Radio Networks
TL;DR: A collaborative energy-harvesting cognitive radio network is considered such that the transmitter of the secondary user (SU) is allowed to harvest signal energy of the primary user (PU) when the presence of the PU is detected.
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.
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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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