This work addresses the problem of determining whether two multivariate random time series have the same power spectral density

(PSD), which has applications, for instance, in physical-layer security and cognitive radio. Remarkably, existing detectors for this

problem do not usually provide any kind of optimality. Thus, we study here the existence under the Gaussian assumption of optimal

invariant detectors for this problem, proving that the uniformly most powerful invariant test (UMPIT) does not exist. Thus, focusing on

close hypotheses, we show that the locally most powerful invariant test (LMPIT) only exists for univariate time series. In the multivariate

case, we prove that the LMPIT does not exist. However, this proof suggests two LMPIT-inspired detectors, one of which outperforms

previously proposed approaches, as computer simulations show.

%B IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
%C Calgary, Canada
%G eng
%0 Journal Article
%J IEEE Trans. Signal Processing
%D 2018
%T Testing equality of multiple power spectral density matrices
%A David Ramírez
%A Daniel Romero
%A Javier Vía
%A R. López-Valcarce
%A Ignacio Santamaría
%K cognitive radio
%K winter
%B IEEE Trans. Signal Processing
%V 66
%P 6268-6280
%8 12/2018
%G eng
%N 23
%R 10.1109/TSP.2018.2875884
%0 Journal Article
%J IEEE Transactions on Signal Processing
%D 2017
%T Learning Power Spectrum Maps from Quantized Power Measurements
%A Daniel Romero
%A Seung-Jun Kim
%A Georgios Giannakis
%A R. López-Valcarce
%K cognitive radio
%K compass
%K compressed sensing
%K spectrum sensing
%K winter
%K wsn
%X Using power measurements collected by a network of low-cost sensors, power spectral density (PSD) maps are con-

structed to capture the distribution of RF power across space and frequency. Linearly compressed and quantized power measure-

ments enable wideband sensing at affordable implementation complexity using a small number of bits. Strengths of data- and model-

driven approaches are combined to develop estimators capable of incorporating multiple forms of spectral and propagation prior

information while fitting the rapid variations of shadow fading across space. To this end, novel nonparametric and semiparametric

formulations are investigated. It is shown that the desired PSD maps can be obtained using support vector machine-type solvers.

In addition to batch approaches, an online algorithm attuned to real-time operation is developed. Numerical tests assess the performance of the novel algorithms.

%B IEEE Transactions on Signal Processing
%V 65
%P 2547-2560
%8 05/2017
%G eng
%N 10
%R 10.1109/TSP.2017.2666775
%0 Journal Article
%J IEEE Transactions on Signal Processing
%D 2016
%T Multiantenna GLR detection of rank-one signals with known power spectral shape under spatially uncorrelated noise
%A Josep Sala
%A Gonzalo Vázquez-Vilar
%A R. López-Valcarce
%A Saeid Sedighi
%A Abbas Taherpour
%K cognitive radio
%K compass
%X We establish the generalized likelihood ratio (GLR) test for a Gaussian signal of known power spectral shape and unknown rank-one spatial signature in additive white Gaussian noise with an unknown diagonal spatial correlation matrix. This is motivated by spectrum sensing problems in dynamic spectrum access (DSA), in which the temporal correlation of the primary signal can be assumed known up to a scaling, and where the noise is due to an uncalibrated receive array. For spatially independent identically distributed (i.i.d.) noise, the corresponding GLR test reduces to a scalar optimization problem, whereas the GLR detector in the general non-i.i.d. case yields a more involved expression, which can be computed via alternating optimization methods. Low signal-to-noise ratio (SNR) approximations to the detectors are given, together with an asymptotic analysis showing the influence on detection performance of the signal power spectrum and SNR distribution across antennas. Under spatial rank-P conditions, we show that the rank-one GLR detectors are consistent with a statistical criterion that maximizes the output energy of a beamformer operating on filtered data. Simulation results support our theoretical findings in that exploiting prior knowledge on the signal power spectrum can result in significant performance improvement.

%B IEEE Transactions on Signal Processing %V 64 %P 6269-6283 %8 12/2016 %G eng %N 23 %& 6269 %R 10.1109/TSP.2016.2601290 %0 Thesis %D 2015 %T Estimation, Detection, and Learning for Dynamic Spectrum Access %A Daniel Romero %K cognitive radio %K compass %K dynacs %K wsn %I University of Vigo %C Vigo, Spain %V Ph.D. %8 05/2015 %G eng %9 Ph.D. Thesis %0 Conference Paper %B IEEE Int. Conference on Acoustics, Speech and Signal Processing (ICASSP) %D 2015 %T Spectrum Cartography using quantized observations %A Daniel Romero %A Seung-Jun Kim %A R. López-Valcarce %A Georgios Giannakis %K cognitive radio %K compass %K compressed sensing %K spectrum sensing %XThis work proposes a spectrum cartography algorithm used for learning the power spectrum distribution over a wide frequency band across a given geographic area. Motivated by low-complexity sensing hardware and stringent communication constraints, compressed and quantized measurements are considered. Setting out from a nonparametric regression framework, it is shown that a sensible approach leads to a support vector machine formulation. The simulated tests verify that accurate spectrum maps can be constructed using a simple sensing architecture with significant savings in the feedback.

%B IEEE Int. Conference on Acoustics, Speech and Signal Processing (ICASSP)
%I IEEE
%C Brisbane, Australia
%8 04/2015
%G eng
%0 Journal Article
%J IEEE Communications Letters
%D 2014
%T Active Interference Cancellation for OFDM Spectrum Sculpting: Linear Processing is Optimal
%A Schmidt, J.F.
%A Daniel Romero
%A R. López-Valcarce
%K cognitive radio
%K compass
%K dynacs
%K spectrum shaping
%X Active interference cancellation (AIC) is a multicarrier spectrum sculpting technique which reduces the power of undesired out-of-band emissions by adequately modulating a subset of reserved cancellation subcarriers. In most schemes online complexity is a concern, and thus cancellation subcarriers have traditionally been constrained to linear combinations of the data subcarriers. Recent AIC designs truly minimizing out-of-band emission shift complexity to the offline design stage, motivating the consideration of more general mappings to improve performance. We show that there is no loss in optimality incurred by constraining these mappings to the set of linear functions.

%B IEEE Communications Letters %V 18 %P 1543-1546 %8 09/2014 %G eng %N 9 %& 1543 %R 10.1109/LCOMM.2014.2338316 %0 Conference Paper %B IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) %D 2014 %T Antenna competition to boost Active Interference Cancellation in cognitive MIMO-OFDM %A Schmidt, J.F. %A R. López-Valcarce %K cognitive radio %K dynacs %K spectrum shaping %X Active Interference Cancellation (AIC) techniques for OFDM spectrum sculpting have gained interest over the last years, and several extensions to the MIMO case have been recently proposed. However, these designs do not fully exploit the spatial diversity provided by the multiple transmit antennas, as canceler allocation is fixed. This paper proposes a more general mechanism for the allocation of the cancellation subcarriers across antennas in order to better exploit spatial diversity. In particular, we present a novel AIC design for cognitive MIMOOFDM systems, in which transmit antennas compete against each other for a fixed number of cancellation subcarriers. We show that this more general allocation approach results in significant performance improvements with respect to previous designs. %B IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) %C A Coruña, Spain %G eng %R 10.1109/SAM.2014.6882392 %0 Conference Paper %B IEEE Global Communications Conference %D 2014 %T Circular Sparse Rulers Based On Co-prime Sampling For Compressive Power Spectrum Estimation %A Nuria González-Prelcic %A M. E. Domíngez-Jiménez %K cognitive radio %K compass %K compressed sensing %B IEEE Global Communications Conference %I IEEE %C Austin, TX %8 12/2014 %G eng %R 10.1109/GLOCOM.2014.7037272 %0 Thesis %D 2014 %T Cognitive and Signal Processing Techniques for Improved Spectrum Exploitation in Wireless Communications %A Alberto Rico-Alvariño %K cognitive radio %K satcom %I Universidade de Vigo %C Vigo %G eng %0 Conference Paper %B IEEE Sensor Array Multichannel Signal Process. Workshop (SAM) %D 2014 %T Cooperative compressive power spectrum estimation %A Dyonisius D Ariananda %A Daniel Romero %A Geert Leus %K cognitive radio %K wsn %B IEEE Sensor Array Multichannel Signal Process. Workshop (SAM) %G eng %0 Conference Paper %B IEEE Int. Workshop on Signal Processing Advances in Wireless Communications (SPAWC) %D 2014 %T Nearly-Optimal Compression Matrices for Signal Power Estimation %A Daniel Romero %A R. López-Valcarce %K cognitive radio %K dynacs %B IEEE Int. Workshop on Signal Processing Advances in Wireless Communications (SPAWC) %C Toronto, Canada %G eng %R 10.1109/SPAWC.2014.6941849 %0 Conference Paper %B IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) %D 2014 %T OFDM spectrum sculpting with active interference cancellation: Keeping spectral spurs at bay %A Schmidt, J.F. %A R. López-Valcarce %K cognitive radio %K dynacs %K spectrum shaping %B IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) %I IEEE %C Florence, Italy %P 1-5 %8 05/2014 %G eng %R 10.1109/ICASSP.2014.6855169 %0 Conference Paper %B IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) %D 2014 %T Power spectrum blind sampling using optimal multicoset sampling patterns in the MSE sense %A Bamrung TauSiesakul %A Nuria González-Prelcic %K cognitive radio %K dynacs %B IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) %G eng %R 10.1109/ICASSP.2014.6853758 %0 Journal Article %J IEEE Trans. on Vehicular Technology %D 2014 %T Spectrum Sensing for Wireless Microphone Signals using Multiple Antennas %A Daniel Romero %A R. López-Valcarce %K cognitive radio %K dynacs %X Spectrum sensors for cognitive radio are expected to deploy multiple antennas in order to overcome the noise uncertainty problem and minimize the effects of small-scale fading. Despite the requirement that these sensors must detect wireless microphone (WM) signals, works in the literature have focused either on general purpose multiantenna detectors, or single antenna WM detectors. We exploit the spatial structure and particular properties of WM waveforms to derive four multiantenna detectors for WM signals with different performance/ complexity tradeoffs. These detectors are based on the generalized likelihood ratio test, which is derived under several signal models exploiting either the fact that the bandwidth of a WM signal never exceeds 200 kHz, the property that these signals have a constant magnitude, or both. The proposed detectors do not require synchronization with the WM signal and are robust to the noise uncertainty problem as well as to small-scale fading. Using the simulation guidelines from the IEEE 802.22 standard, the novel multiantenna WM detectors are shown to outperform previous schemes, thus demonstrating the advantages of exploiting spatial correlation along with WM signal structure. %B IEEE Trans. on Vehicular Technology %V 63 %P 4395-4407 %8 11/2014 %G eng %N 9 %& 4395 %R 10.1109/TVT.2014.2316513 %0 Journal Article %J IEEE Journal on Emerging and Selected Topics in Circuits and Systems %D 2013 %T Choose Your Subcarriers Wisely: Active Interference Cancellation for Cognitive OFDM %A Schmidt, J.F. %A Costas-Sanz, S. %A R. López-Valcarce %K cognitive radio %K dynacs %K spectrum shaping %B IEEE Journal on Emerging and Selected Topics in Circuits and Systems %V 3 %P 615-625 %8 12/2013 %G eng %N 4 %& 615 %R 10.1109/JETCAS.2013.2280808 %0 Conference Paper %B European Signal Processing Conf. (EUSIPCO), Marrakech (Morocco) %D 2013 %T A Class of Circular Sparse Rulers for Compressive Power Spectrum Estimation %A M. Elena Domínguez-Jiménez %A Nuria González-Prelcic %K cognitive radio %K dynacs %B European Signal Processing Conf. (EUSIPCO), Marrakech (Morocco) %8 09/2013 %G eng %0 Journal Article %J Sensors %D 2013 %T A Cognitive Mobile BTS Solution with Software-Defined Radioelectric Sensing %A J. Muñoz %A J. Vales-Alonso %A F. Quiñoy-García %A Costas-Sanz, S. %A M. Pillado %A F.J. González-Castaño %A M. García-Sanchez %A R. López-Valcarce %A C. López-Bravo %K cognitive radio %K dynacs %K mobile communications %K SDR %K vehicular communications %X

Private communications inside large vehicles such as ships may be effectively provided using standard cellular systems. In this paper we propose a new solution based on software-defined radio with electromagnetic sensing support. Software-defined radio allows low-cost developments and, potentially, added-value services not available in commercial cellular networks. The platform of reference, OpenBTS, only supports single-channel cells. Our proposal, however, has the ability of changing BTS channel frequency without disrupting ongoing communications. This ability should be mandatory in vehicular environments, where neighbouring cell configurations may change rapidly, so a moving cell must be reconfigured in real-time to avoid interferences. Full details about frequency occupancy sensing and the channel reselection procedure are provided in this paper. Moreover, a procedure for fast terminal detection is proposed. This may be decisive in emergency situations, e.g., if someone falls overboard. Different tests confirm the feasibility of our proposal and its compatibility with commercial GSM terminals.

%B Sensors %V 13 %P 2051-2075 %8 02/2013 %G eng %N 2 %& 2051 %R 10.3390/s130202051 %0 Conference Paper %B IEEE Int. Workshop Comput. Advances Multi-Sensor Adaptive Process (CAMSAP) %D 2013 %T Compressive Angular and Frequency Periodogram Reconstruction for Multiband Signals %A Ariananda, D. D. %A Daniel Romero %A Geert Leus %K cognitive radio %K dynacs %B IEEE Int. Workshop Comput. Advances Multi-Sensor Adaptive Process (CAMSAP) %C San Martin %G eng %R 10.1109/CAMSAP.2013.6714102 %0 Conference Paper %B Inform. Theory Appl. Workshop %D 2013 %T Compressive Covariance Sampling %A Daniel Romero %A Geert Leus %K cognitive radio %K dynacs %B Inform. Theory Appl. Workshop %P 1-8 %8 Feb. %G eng %R 10.1109/ITA.2013.6502949 %0 Conference Paper %B Int. Conf. Acoust., Speech, Signal Process. (ICASSP) %D 2013 %T Compressive wideband spectrum sensing with spectral prior information %A Daniel Romero %A R. López-Valcarce %A Geert Leus %K cognitive radio %K dynacs %K spectrum sensing %XWideband spectrum sensing provides a means to determine

the occupancy of channels spanning a broad range of frequencies.

Practical limitations impose that the acquisition should

be accomplished at a low rate, much below the Nyquist lower

bound. Dramatic rate reductions can be obtained by the observation

that only a few parameters need to be estimated in

typical spectrum sensing applications. This paper discusses

the joint estimation of the power of a number of channels,

whose power spectral density (PSD) is known up to a scale

factor, using compressive measurements. First, relying on

a Gaussian assumption, an efficient approximate maximum

likelihood (ML) technique is presented. Next, a least-squares

estimator is applied for the general non-Gaussian case.

%B Int. Conf. Acoust., Speech, Signal Process. (ICASSP)
%G eng
%R 10.1109/ICASSP.2013.6638505
%0 Conference Paper
%B European Signal Processing Conf. (EUSIPCO), Marrakech (Morocco)
%D 2013
%T Low Complexity Primary User Protection for Cognitive OFDM
%A Schmidt, J.F.
%A R. López-Valcarce
%K cognitive radio
%K dynacs
%K spectrum shaping
%B European Signal Processing Conf. (EUSIPCO), Marrakech (Morocco)
%8 09/2013
%G eng
%0 Conference Paper
%B Asilomar Conference on Signals, Systems and Computers
%D 2013
%T Power Spectrum Blind Sampling Using Minimum Mean Square Error and Weighted Least Squares
%A Bamrung TauSiesakul
%A Nuria González-Prelcic
%K cognitive radio
%K dynacs
%B Asilomar Conference on Signals, Systems and Computers
%8 11/2013
%G eng
%R 10.1109/ACSSC.2013.6810249
%0 Conference Paper
%B IEEE 14th Int. Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Darmstadt (Germany)
%D 2013
%T Spectrum Sensing in Time-Varying Channels Using Multiple Antennas
%A Daniel Romero
%A R. López-Valcarce
%K cognitive radio
%K dynacs
%K spectrum sensing
%B IEEE 14th Int. Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Darmstadt (Germany)
%8 06/2013
%G eng
%R 10.1109/SPAWC.2013.6612027
%0 Journal Article
%J IEEE Trans. Signal Process.
%D 2013
%T Wideband Spectrum Sensing From Compressed Measurements Using Spectral Prior Information
%A Daniel Romero
%A Geert Leus
%K cognitive radio
%K compressed sensing
%K dynacs
%K spectrum sensing
%B IEEE Trans. Signal Process.
%V 61
%P 6232-6246
%G eng
%R 10.1109/TSP.2013.2283473
%0 Conference Paper
%B IEEE Statistical Signal Processing Workshop (SSP 2012)
%D 2012
%T Detection of Gaussian signals in unknown time-varying channels
%A Daniel Romero
%A Javier Vía
%A R. López-Valcarce
%A Ignacio Santamaría
%K cognitive radio
%K dynacs
%K spectrum sensing
%X Detecting the presence of a white Gaussian signal distorted by a noisy time-varying channel is addressed by means of three different detectors. First, the generalized likelihood ratio test (GLRT) is found for the case where the channel has no temporal structure, resulting in the well-known Bartlett’s test. Then it is shown that, under the transformation group given by scaling factors, a locally most powerful invariant test (LMPIT) does not exist. Two alternative approaches are explored in the low signal-to-noise ratio (SNR) regime: the first assigns a prior probability density function (pdf) to the channel (hence modeled as random), whereas the second assumes an underlying basis expansion model (BEM) for the (now deterministic) channel and obtains the maximum likelihood (ML) estimates of the parameters relevant for the detection problem. The performance of these detectors is evaluated via Monte Carlo simulation.

%B IEEE Statistical Signal Processing Workshop (SSP 2012)
%I IEEE
%C Ann Arbor, MI
%8 08/2012
%G eng
%R 10.1109/SSP.2012.6319858
%0 Conference Paper
%B 3rd Int. Workshop on Cognitive Information Processing (CIP 2012)
%D 2012
%T Detection of unknown constant magnitude signals in time-varying channels
%A Daniel Romero
%A R. López-Valcarce
%K cognitive radio
%K dynacs
%K spectrum sensing
%X Spectrum sensing constitutes a key ingredient in many cognitive radio paradigms in order to detect and protect primary transmissions. Most sensing schemes in the literature assume a time-invariant channel. However, when operating in low Signal-to-Noise Ratio (SNR) conditions, observation times are necessarily long and may become larger than the coherence time of the channel. In this paper the problem of detecting an unknown constant-magnitude waveform in frequency-flat time-varying channels with noise background of unknown variance is considered. The channel is modeled using a basis expansion model (BEM) with random coefficients. Adopting a generalized likelihood ratio (GLR) approach in order to deal with nuisance parameters, a non-convex optimization problem results. We discuss different possibilities to circumvent this problem, including several low complexity approximations to the GLR test as well as an efficient fixed-point iterative method to obtain the true GLR statistic. The approximations exhibit a performance ceiling in terms of probability of detection as the SNR increases, whereas the true GLR test does not. Thus, the proposed fixed-point iteration constitutes the preferred choice in applications requiring a high probability of detection.

%B 3rd Int. Workshop on Cognitive Information Processing (CIP 2012) %C Baiona, Spain %8 05/2012 %G eng %R 10.1109/CIP.2012.6232933 %0 Conference Paper %B IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP 2012) %D 2012 %T Generalized matched filter detector for fast fading channels %A Daniel Romero %A R. López-Valcarce %A Geert Leus %K cognitive radio %K dynacs %K spectrum sensing %XWe consider the problem of detecting a known signal with constant magnitude immersed in noise of unknown variance,

when the propagation channel is frequency-flat and randomly

time-varying within the observation window. A Basis Expansion

Model with random coefficients is used for the channel, and a Generalized Likelihood Ratio approach is adopted in order to cope with deterministic nuisance parameters. The resulting scheme can be seen as a generalization of the well-known

Matched Filter detector, to which it reduces for timeinvariant

channels. Closed-form analytical expressions are provided for the distribution of the test statistic under both hypotheses, which allow to assess the detection performance.

%B IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP 2012)
%I IEEE
%C Kyoto, Japan
%8 07/2012
%G eng
%R 10.1109/ICASSP.2012.6288587
%0 Journal Article
%J IEEE Trans. on Signal Processing
%D 2012
%T Multiantenna GLR detection of rank-one signals with known power spectrum in white noise with unknown spatial correlation
%A Josep Sala
%A Gonzalo Vázquez-Vilar
%A R. López-Valcarce
%K cognitive radio
%K dynacs
%X Multiple-antenna detection of a Gaussian signal with spatial rank one in temporally white Gaussian noise with arbitrary and unknown spatial covariance is considered. This is motivated by spectrum sensing problems in the context of Dynamic Spectrum Access in which several secondary networks coexist but do not cooperate, creating a background of spatially correlated broadband interference. When the temporal correlation of the signal of interest is assumed known up to a scale factor, the corresponding Generalized Likelihood Ratio Test is shown to yield a scalar optimization problem. Closed-form expressions of the test are obtained for the general signal spectrum case in the low signal-to-noise ratio (SNR) regime, as well as for signals with binary-valued power spectrum in arbitrary SNR. The two resulting detectors turn out to be equivalent. An asymptotic approximation to the test distribution for the low-SNR regime is derived, closely matching empirical results from spectrum sensing simulation experiments.

%B IEEE Trans. on Signal Processing
%V 60
%P 3065 - 3078
%8 06/2012
%G eng
%N 6
%R 10.1109/TSP.2012.2189767
%0 Conference Paper
%B Asilomar Conference on Signals, Systems, and Computers
%D 2012
%T Optimum Training for CSI Acquisition in Cognitive Radio Channels
%A Alberto Rico-Alvariño
%A C. Mosquera
%K adaptive signal processing
%K cognitive radio
%K dynacs
%B Asilomar Conference on Signals, Systems, and Computers
%C Pacific Grove, CA
%G eng
%R 10.1109/ACSSC.2012.6488973
%0 Journal Article
%J IEEE Transactions on Wireless Communications
%D 2012
%T Overlay Cognitive Transmission in a Multicarrier Broadcast Network with Dominant Line of Sight Reception
%A Alberto Rico-Alvariño
%A C. Mosquera
%A Fernando Pérez-González
%K cognitive radio
%K dynacs
%K satcom
%B IEEE Transactions on Wireless Communications
%G eng
%R 10.1109/TWC.2012.092112.120257
%0 Conference Paper
%B 3rd International Workshop on Cognitive Information Processing (CIP)
%D 2012
%T Overlay cognitive transmission in OFDM point to point systems exploiting primary feedback
%A Alberto Rico-Alvariño
%A C. Mosquera
%K cognitive radio
%K dynacs
%X A secondary user that tries to reuse the spectrum allocated to a primary user can exploit the knowledge of the primary message to perform this task. In particular, the overlay cognitive radio paradigm postulates the use of a fraction of the available power at the secondary transmitter to convey the primary message, so the spectral efficiency of the primary system is increased, and, therefore, some transmission resources (time slots or frequency bands) can be released to the secondary transmission while the primary user rate is kept constant. The fraction of released resources can be incremented if some channel state information is available at the secondary transmitter. In this paper, we present a scenario where the secondary transmitter maximizes the primary link quality (measured in terms of Effective SNR), and obtains its channel state information by exploiting the primary user SNR-based feedback.

%B 3rd International Workshop on Cognitive Information Processing (CIP) %C Baiona, Galicia, Spain %8 05/2012 %G eng %R 10.1109/CIP.2012.6232932 %0 Conference Proceedings %B IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN 2012) %D 2012 %T Overlay Spectrum Reuse in a Broadcast Network: Covering the Whole Grayscale of Spaces %A Alberto Rico-Alvariño %A C. Mosquera %K cognitive radio %K dynacs %B IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN 2012) %C Bellevue, WA %G eng %R 10.1109/DYSPAN.2012.6478172 %0 Conference Paper %B The 13th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2012) %D 2012 %T Overlay Spectrum Reuse in a Multicarrier Broadcast Network: Coverage Analysis %A Alberto Rico-Alvariño %A C. Mosquera %A Fernando Pérez-González %K cognitive radio %K dynacs %XA secondary cognitive user overlaying its message in a broadcast multicarrier network is studied. The secondary user exploits the primary message knowledge to convey its own information while preserving the primary user coverage area, determined by a bound on the BER, and taking into account the degradation due to the insertion of an echo in a dominant line of sight environment. The results are compared with those obtained when the coverage area is defined in capacity terms, and regardless of the degradation caused by the secondary replica of the primary message.

%B The 13th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2012) %C Cesme, Turkey %G eng %R 10.1109/SPAWC.2012.6292889 %0 Conference Paper %B The 13th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2012) %D 2012 %T Overlay Spectrum Reuse in a Multicarrier Broadcast Network: Single Receiver Analysis %A Alberto Rico-Alvariño %A C. Mosquera %A Fernando Pérez-González %K cognitive radio %K dynacs %XThe overlay cognitive radio paradigm presents a framework where a secondary user exploits the knowledge of the primary user's message to improve spectrum utilization. A multicarrier broadcast network is one of the scenarios where this knowledge is possible: the secondary user could join a single frequency network and, therefore, gain access to the primary message. However, if the primary signal is received with a strong line of sight component, its relaying from the secondary transmitter does not suffice to ensure the primary user quality of service. In this paper we study the scenario where a secondary transmitter maximizes its own transmission rate, keeping the quality of a primary receiver over a given threshold. The analytical results, based on bit error rate bounds, are verified by means of software simulations and hardware tests.

%B The 13th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2012) %C Cesme, Turkey %G eng %R 10.1109/SPAWC.2012.6292890 %0 Conference Paper %B International Conference on Cognitive Radio and Advanced Spectrum Management %D 2011 %T On the Co-existence of Primary and Secondary Transmitters in a Broadcast Network %A Alberto Rico-Alvariño %A C. Mosquera %A Fernando Pérez-González %K Broadcast %K cognitive radio %K Overlay %K Single Frequency Network %B International Conference on Cognitive Radio and Advanced Spectrum Management %C Barcelona, Catalonia, Spain %G eng %0 Conference Paper %B IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP 2011) %D 2011 %T Detection diversity of multiantenna spectrum sensors %A Gonzalo Vázquez-Vilar %A R. López-Valcarce %A Ashish Pandharipande %K cognitive radio %K detection diversity %K spectrum sensing %XIn the context of spectrum sensing, we investigate the performance of detectors equipped with M antennas (co-located or distributed) under Rayleigh fading, in terms of detection diversity. Rather than the high-SNR concept of diversity order common in the communications literature, we adopt the notion recently advocated by Daher and Adve in the radar community: the slope of the average probability of detection (\bar{P}_D) vs. SNR curve at \bar{P}_D = 0.5. This definition is well suited to spectrum sensing, which invariably deals with low SNR levels. It is shown that the diversity order grows as M for an optimal centralized detector having access to all observations, whereas for the two distributed schemes considered (the multiantenna energy detector and the OR detector) it grows no faster than √M.

%B IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP 2011)
%I IEEE
%C Prague, Czech Republic
%P 2936-2939
%8 05/2011
%G eng
%0 Journal Article
%J IEEE Trans. on Signal Processing
%D 2011
%T Detection of Rank-P Signals in Cognitive Radio Networks With Uncalibrated Multiple Antennas
%A David Ramírez
%A Gonzalo Vázquez-Vilar
%A R. López-Valcarce
%A Javier Vía
%A Ignacio Santamaría
%K cognitive radio
%K dynacs
%K spectrum sensing
%X Spectrum sensing is a key component of the Cognitive Radio paradigm. Typically, primary signals have to be detected with uncalibrated receivers at signal-to-noise ratios (SNRs) well below decodability levels. Multiantenna detectors exploit spatial independence of receiver thermal noise to boost detection performance and robustness. We study the problem

of detecting a Gaussian signal with rank-P unknown spatial

covariance matrix in spatially uncorrelated Gaussian noise with

unknown covariance using multiple antennas. The generalized

likelihood ratio test (GLRT) is derived for two scenarios. In the

first one, the noises at all antennas are assumed to have the same (unknown) variance, whereas in the second, a generic diagonal noise covariance matrix is allowed in order to accommodate calibration uncertainties in the different antenna frontends. In the latter case, the GLRT statistic must be obtained numerically, for which an efficient method is presented. Furthermore, for asymptotically low SNR, it is shown that the GLRT does admit a closed form, and the resulting detector performs well in practice. Extensions are presented in order to account for unknown temporal correlation in both signal and noise, as well as frequency-selective channels.

%B IEEE Trans. on Signal Processing
%V 59
%P 3764-3774
%8 08/2012
%G eng
%N 8
%R 10.1109/TSP.2011.2146779
%0 Conference Paper
%B IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
%D 2011
%T Distributed spectrum sensing with multiantenna sensors under calibration errors
%A Daniel Romero
%A R. López-Valcarce
%K ad hoc detectors
%K antenna arrays
%K calibration
%K calibration errors
%K cognitive radio
%K energy detector
%K generalized likelihood ratio
%K log normal distribution
%K lognormal shadowing
%K multiantenna sensors
%K Ricean fading
%K spectrum sensing
%K wireless medium
%X Spectrum sensing design for Cognitive Radio systems is challenged by the nature of the wireless medium, which makes the detection requirements difficult to achieve by standalone sensors. To combat shadowing and fading, distributed strategies are usually proposed. However, most distributed approaches are based on the energy detector, which is not robust to noise uncertainty. This phenomenon can be overcome by multi-antenna sensors exploiting spatial independence of the noise process. We combine both ideas to develop distributed detectors for multiantenna sensors. Fusion rules are provided for sensors based on the Generalized Likelihood Ratio as well as for ad hoc detectors derived from geometric considerations. Simulation results are provided comparing the performance of the different strategies under lognormal shadowing and Ricean fading.

%B IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC) %P 441 -445 %8 june %G eng %R 10.1109/SPAWC.2011.5990448 %0 Thesis %D 2011 %T Interference and Network Management in Cognitive Communication Systems %A Gonzalo Vázquez-Vilar %K cognitive radio %K spectrum sensing %I University of Vigo %C Vigo, Spain %V Ph.D. %8 06/2011 %G eng %9 Ph.D. thesis %0 Conference Paper %B IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC) %D 2011 %T Multiantenna detection of constant-envelope signals in noise of unknown variance %A Daniel Romero %A R. López-Valcarce %K cognitive radio %K multiantenna detection %K spectrum sensing %XDetection of unknown signals with constant modulus (CM) using multiple antennas in additive white Gaussian noise of unknown variance is considered. The channels from the source to each antenna are assumed frequency-flat and unknown. This problem is of interest for spectrum sensing in cognitive radio systems in which primary signals are known to have the CM property. Examples include analog frequency modulated signals such as those transmitted by wireless microphones in the TV bands and Gaussian Minimum Shift Keying modulated signals as in the GSM cellular standard. The proposed detector, derived from a Generalized Likelihood Ratio (GLR) approach, exploits both the CM property and the spatial independence of noise, outperforming the GLR test for Gaussian signals as shown by simulation.

%B IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC) %P 446 -450 %8 june %G eng %R 10.1109/SPAWC.2011.5990449 %0 Conference Paper %B IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) %D 2011 %T Multiantenna detection under noise uncertainty and primary user's spatial structure %A David Ramírez %A Gonzalo Vázquez-Vilar %A R. López-Valcarce %A Javier Vía %A Ignacio Santamaría %K cognitive radio %K generalized likelihood ratio test (GLRT) %K spectrum sensing %B IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) %I IEEE %C Prage, Czech Republic %P 2948-2951 %8 May %G eng %0 Journal Article %J IEEE Trans. on Wireless Communications %D 2011 %T Multiantenna Spectrum Sensing Exploiting Spectral a priori Information %A Gonzalo Vázquez-Vilar %A R. López-Valcarce %A Josep Sala %K cognitive radio %K dynacs %K spectrum sensing %B IEEE Trans. on Wireless Communications %V 10 %P 4345 - 4355 %8 12/2011 %G eng %N 12 %R 10.1109/TWC.2011.101211.110665 %0 Journal Article %J IEEE Trans. on Signal Processing %D 2011 %T Spectrum Sensing Exploiting Guard Bands and Weak Channels %A Gonzalo Vázquez-Vilar %A R. López-Valcarce %K cognitive radio %K dynacs %K spectrum sensing %XWe address the problem of primary user detection in Cognitive Radio from a wideband signal comprising multiple primary channels, exploiting a priori knowledge about the primary network: channelization and spectral shape of primary transmissions. Using this second-order statistical information, a multichannel Gaussian model is formulated. In order to obtain a Generalized Likelihood Ratio Test, we first address Maximum Likelihood (ML) estimation of the power levels at the different channels, as well as of the noise variance. The ML conditions suggest a suboptimal closed-form estimate, which takes the form of a constrained Least Squares estimator whose asymptotic efficiency is shown for flat bandpass spectra in white noise, a case of practical importance. The resulting detectors exploit those frequency bins corresponding to guard bands and to primary channels perceived as weak to improve noise variance estimation. Analytical expressions for the probabilities of detection and false alarm are presented. Performance is evaluated via simulations in the setting of a terrestrial TV primary network with realistic channelization parameters.

%B IEEE Trans. on Signal Processing
%V 59
%P 6045-6057
%8 12/2011
%G eng
%N 12
%R 10.1109/TSP.2011.2167615
%0 Journal Article
%J IEEE Transactions on Vehicular Technology
%D 2010
%T Dynamic spectrum leasing (DSL): A new paradigm for spectrum sharing in cognitive radio networks
%A Sudhaman K. Jayaweera
%A Gonzalo Vázquez-Vilar
%A C. Mosquera
%K cognitive radio
%K DSL
%K dynamic spectrum access
%K dynamic spectrum leasing
%K dynamic spectrum sharing
%K game theory
%K power control
%B IEEE Transactions on Vehicular Technology
%V 59
%P 2328-2339
%G eng
%0 Conference Paper
%B ICC Workshop on Cognitive Radio Interfaces and Signal Processing (ICC CRISP)
%D 2010
%T Dynamic Spectrum Leasing (DSL) in Dynamic Channels
%A Georges El-Howayek
%A Sudhaman K. Jayaweera
%A Kamrul Hakim
%A Gonzalo Vázquez-Vilar
%A C. Mosquera
%K cognitive radio
%K DSL
%K dynamic spectrum leasing
%K game theory
%K Rayleigh fading
%K time-varying channels
%K time-varying secondary system
%B ICC Workshop on Cognitive Radio Interfaces and Signal Processing (ICC CRISP)
%C Cape Town, South Africa
%8 May 23
%G eng
%0 Conference Paper
%B IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
%D 2010
%T Multiantenna spectrum sensing: detection of spatial correlation among time-series with unknown spectra
%A David Ramírez
%A Javier Vía
%A Ignacio Santamaría
%A R. López-Valcarce
%A L. L. Scharf
%K cognitive radio
%K coherence spectrum
%K generalized likelihood ratio test
%K Hadamard ratio
%K multiple-channel signal detection
%B IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
%C Dallas, TX
%G eng
%0 Conference Paper
%B IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
%D 2010
%T Wideband Spectral Estimation from Compressed Measurements Exploiting Spectral a priori Information in Cognitive Radio Systems
%A Gonzalo Vázquez-Vilar
%A R. López-Valcarce
%A C. Mosquera
%A Nuria González-Prelcic
%K cognitive radio
%K compressive sampling
%K Spectral estimation
%B IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
%C Dallas, U.S.A.
%8 March 14-19
%G eng