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20102017
most citedMultiple Antenna Cyclostationary Spectrum Sensing Based on the Cyclic Correlation Significance Test

64 citations · 134 across the 5 of their papers we have counts for

collaborators

6 papers

cs.NI2017★ 4 cited

Channel Access Method Classification For Cognitive Radio Applications

Mihir Laghate, Paulo Urriza, Danijela Cabric

Motivated by improved detection and prediction of temporal holes, we propose a two stage algorithm to classify the channel access method used by a primary network. The first stage…

stat.ML2013★ 12 cited

Optimal Discriminant Functions Based On Sampled Distribution Distance for Modulation Classification

Paulo Urriza, Eric Rebeiz, Danijela Cabric

In this letter, we derive the optimal discriminant functions for modulation classification based on the sampled distribution distance. The proposed method classifies various candid…

cs.PF2012★ 64 cited

Multiple Antenna Cyclostationary Spectrum Sensing Based on the Cyclic Correlation Significance Test

Paulo Urriza, Eric Rebeiz, Danijela Cabric

In this paper, we propose and analyze a spectrum sensing method based on cyclostationarity specifically targeted for receivers with multiple antennas. This detection method is used…

cs.PF2012★ 4 cited

Eigenvalue-based Cyclostationary Spectrum Sensing Using Multiple Antennas

Paulo Urriza, Eric Rebeiz, Danijela Cabric

In this paper, we propose a signal-selective spectrum sensing method for cognitive radio networks and specifically targeted for receivers with multiple-antenna capability. This met…

cs.IT2010★ 50 cited

Computationally Efficient Modulation Level Classification Based on Probability Distribution Distance Functions

Paulo Urriza, Eric Rebeiz, Przemysław Pawełczak +1

We present a novel modulation level classification (MLC) method based on probability distribution distance functions. The proposed method uses modified Kuiper and Kolmogorov-Smirno…

cs.PF2010

Weighted Centroid Algorithm for Estimating Primary User Location: Theoretical Analysis and Distributed Implementation

Jun Wang, Paulo Urriza, Yuxing Han +1

Information about primary transmitter location is crucial in enabling several key capabilities in cognitive radio networks, including improved spatio-temporal sensing, intelligent…