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Keywords
(16)
Chromium
Cognitive Radio
Cognitive Radio Network
Correlation Coefficient
Gaussian Approximation
Mathematical Model
nonconvex optimization
Receiver Operator Characteristic
Sensor Network
Signal To Noise Ratio
Spectrum Sensing
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Likelihood Ratio Test
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Optimization of Linear Cooperative Spectrum Sensing for Cognitive Radio Networks
Optimization of Linear Cooperative Spectrum Sensing for Cognitive Radio Networks,10.1109/JSTSP.2010.2055537,IEEE Journal of Selected Topics in Signal
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Optimization of Linear Cooperative Spectrum Sensing for Cognitive Radio Networks
(
Citations: 3
)
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Giorgio Taricco
Spectrum sensing
is the key to coordinate the secondary users in a
cognitive radio network
by limiting the prob ability of interference with the primary users. Linear cooperative
spectrum sensing
consists of comparing the linear combination of the secondary users' recordings against a given threshold in order to assess the presence of the
primary user
signal. Simplicity is traded off for a slight suboptimality with respect to the like lihoodratio test. Tuning the performance of linear cooperative radio sensing is complicated by the fact that optimization of the linear combining vector is required. This is accomplished by solving a
nonconvex optimization
problem, which is the main focus of this work. The global optimum is found by an explicit algorithm based on the solution of a polynomial equation in one scalar variable. Numerical results are reported for validation purposes and to analyze the effects of the system parameters on the complementary receiver operating characteristic. It is shown that the optimum probability of missed detection for a system with constant local signaltonoise ratios (SNRs) and constant channel gain correlation coefficients can be expressed in closed form by a simple expression. Simulation results are also included to validate the accuracy of the Gaussian approximation. These results illustrate how large the number of sampling intervals must be in order that the
Gaussian approximation
holds.
Journal:
IEEE Journal of Selected Topics in Signal Processing  IEEE J SEL TOP SIGNAL PROCESS
, vol. 5, no. 1, pp. 7786, 2011
DOI:
10.1109/JSTSP.2010.2055537
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Citation Context
(1)
...Among them, linear cooperative spectrum sensing (LCSS) [11], [
12
] has the merit of simplifying the hypothesis testing problem so much that it can be implemented in devices of limited complexity, such as those present in sensor networks...
Giorgio Taricco
.
On the Accuracy of the Gaussian Approximation With Linear Cooperative ...
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, 2005
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Citations
(3)
On the Accuracy of the Gaussian Approximation With Linear Cooperative Spectrum Sensing Over Rician Fading Channels
(
Citations: 2
)
Giorgio Taricco
Journal:
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