@conference {ICASSP2010_QuaternionWL,
	title = {Widely and semi-widely linear processing of quaternion vectors},
	booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)},
	year = {2010},
	month = {March},
	address = {Dallas, USA},
	author = {V{\'\i}a, Javier and Ram{\'\i}rez, David and Santamar{\'\i}a, Ignacio and Vielva, Luis}
}
@conference {205_vhgpr_icml,
	title = {Variational Heteroscedastic Gaussian Process Regression},
	booktitle = {The 28th International Conference on Machine Learning},
	year = {2011},
	month = {July},
	address = {Bellevue, Washington},
	author = {L{\'a}zaro-Gredilla, Miguel and Titsias, Michalis}
}
@conference {Icassp02_ICA,
	title = {Underdetermined Blind Source Separation in a Time-Varying Environment},
	booktitle = {IEEE Int. Conf. on Acoust., Speech, and Signal Processing (ICASSP 2002)},
	year = {2002},
	month = {May},
	address = {Orlando, FL, USA},
	author = {Vielva, Luis and Erdogmus, Deniz and Pantale{\'o}n, Carlos and Santamar{\'\i}a, Ignacio and Pereda, J. A. and Pr{\'\i}ncipe, Jos{\'e} C.}
}
@conference {Nnsp2003_Ica,
	title = {Underdetermined blind separation of sparse sources with instantaneous and convolutive mixtures},
	booktitle = {Int. Workshop on Neural Networks for Signal Processing (NNSP 2003)},
	year = {2003},
	month = {September},
	address = {Toulouse, France},
	author = {Luengo, David and Santamar{\'\i}a, Ignacio and Vielva, Luis and Pantale{\'o}n, Carlos}
}
@conference {Icassp2011_Lazaro,
	title = {Tracking Performance of Adaptively Biased Adaptive Filters},
	booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011)},
	year = {2011},
	month = {May},
	address = {Prague, Czech Republic},
	author = {Arenas-Garc{\'\i}a, J. and L{\'a}zaro-Gredilla, Miguel}
}
@conference {435,
	title = {Time and Power Allocation for the Gaussian Wiretap Channel with Feedback of Secret Keys},
	booktitle = {16th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2015)},
	year = {2015},
	month = {June},
	address = {Stockholm},
	author = {V{\'\i}a, Javier}
}
@conference {Via - QLMPIT - EUSIPCO2011,
	title = {Testing Quaternion Properness: Generalized Likelihood Ratios and Locally Most Powerful Invariants},
	booktitle = {19th European Signal Processing Conference (EUSIPCO 2011)},
	year = {2011},
	month = {August},
	address = {Barcelona, Spain},
	author = {V{\'\i}a, Javier and Vielva, Luis}
}
@conference {Icassp03_teaching,
	title = {Teaching digital communications: A {DSP} approach},
	booktitle = {IEEE Int. Conf. on Acoust., Speech, and Signal Processing (ICASSP 2003)},
	year = {2003},
	month = {April},
	address = {Hong Kong, China},
	author = {Ib{\'a}{\~n}ez, Jes{\'u}s and Pantale{\'o}n, Carlos and Vielva, Luis and Santamar{\'\i}a, Ignacio}
}
@conference {IJCNN2004,
	title = {{SVM}-based blind beamforming of constant modulus signals},
	booktitle = {International Joint Conference on Neural Networks (IJCNN 2004)},
	year = {2004},
	month = {July},
	address = {Budapest, Hungary},
	author = {Santamar{\'\i}a, Ignacio and V{\'\i}a, Javier and J. Merino}
}
@conference {Nnsp2003_svm,
	title = {Support Vector Machine for the simultaneous approximation of a function and its derivative},
	booktitle = {Int. Workshop on Neural Networks for Signal Processing (NNSP 2003)},
	year = {2003},
	month = {September},
	address = {Toulouse, France},
	author = {L{\'a}zaro, Marcelino and Santamar{\'\i}a, Ignacio and P{\'e}rez-Cruz, Fernando and Art{\'e}s, Antonio}
}
@conference {IST_2001_a,
	title = {{SUITED} vehicular {Ka} band satellite terminal},
	booktitle = {IST Mobile Communications Summit},
	year = {2001},
	month = {September},
	address = {Barcelona, Spain},
	author = {J. Alonso and P{\'e}rez, Jes{\'u}s and Gonz{\'a}lez, L. and V. Schena and M. Holzbock}
}
@conference {SPAWC2006_Sufficient,
	title = {A sufficient condition for blind identifiability of {MIMO-OSTBC} channels based on second order statistics},
	booktitle = {Seventh IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2006)},
	year = {2006},
	month = {June},
	address = {Cannes, France},
	author = {V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and P{\'e}rez, Jes{\'u}s}
}
@conference {560,
	title = {Subspace Averaging in Multi-Sensor Array Processing},
	booktitle = {SIAM Conference on Applied Algebraic Geometry},
	year = {2019},
	month = {July},
	address = {Bern, Switzerland},
	author = {Santamar{\'\i}a, Ignacio and Louis L. Scharf and Garg, Vaibhav and Ram{\'\i}rez, David}
}
@conference {514,
	title = {Subspace Averaging for Source Enumeration in Large Arrays},
	booktitle = {IEEE Statistical Signal Processing Workshop (SSP)},
	year = {2018},
	month = {June},
	address = {Freiburg, Germany},
	abstract = {Subspace averaging is proposed and examined as a method of enumerating sources in large linear arrays, under conditions of low sample support. The key idea is to exploit shift invariance as a way of
extracting many subspaces, which may then be approximated by a
single extrinsic average. An automatic order determination rule for
this extrinsic average is then the rule for determining the number
of sources. Experimental results are presented for cases where the
number of array snapshots is roughly half the number of array elements, and sources are well separated with respect to the Rayleigh
limit.},
	author = {Santamar{\'\i}a, Ignacio and Ram{\'\i}rez, David and Louis L. Scharf}
}
@conference {Eusipco2008_STBC_TimeVarying,
	title = {A Subspace Approach for Blind Estimation of {Time-Varying} Channels Under {STBC} Transmissions},
	booktitle = {16th European Signal Processing Conference (EUSIPCO 2008)},
	year = {2008},
	month = {August},
	address = {Lausanne, Switzerland},
	author = {V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and P{\'e}rez, Jes{\'u}s}
}
@conference {Dongho_spawc05,
	title = {Structural risk minimization for robust blind identification of sparse {SIMO} channels},
	booktitle = {Sixth IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2005),},
	year = {2005},
	month = {June},
	address = {New York, USA},
	author = {Han, D. and Pr{\'\i}ncipe, Jos{\'e} C. and Yang, L. and Santamar{\'\i}a, Ignacio and V{\'\i}a, Javier}
}
@conference {463,
	title = {Statistical Analysis of Single-Beam Interference Alignment Schemes},
	booktitle = {IEEE Workshop on Signal Processing Advances on Wireless Communications (SPAWC)},
	year = {2016},
	month = {July},
	address = {Edimburgh, UK},
	abstract = {In this work, we derive analytical approximate expressions for the user rates achievable by interference alignment (IA) algorithms in single-beam multiple-input multiple-output (MIMO) networks for a fixed channel realization. Unlike previous works that perform a large-system analysis in which the number of users, antennas, or streams is required to tend to infinity, in this paper we only require that the number of different IA solutions (precoders and decoders) for the given scenario is sufficiently high, which typically happens even for moderate-size feasible networks. Based on the assumption that the IA beamformers for a given channel realization are random vectors isotropically distributed on the complex unit sphere, we characterize the user rates by averaging over the (possible finite) set of IA solutions. Some simulation results show the accuracy of the proposed rate expressions.},
	author = {Santamar{\'\i}a, Ignacio and Fanjul, Jacobo}
}
@conference {473,
	title = {A Split Kernel Adaptive Filtering Architecture for Nonlinear Acoustic Echo Cancellation},
	booktitle = {24th European Signal Processing Conference (EUSIPCO 2016)},
	year = {2016},
	month = {September},
	address = {Budapest, Hungary},
	abstract = {We propose a new linear-in-the-parameters (LIP) nonlinear filter based on kernel methods to address the problem of nonlinear acoustic echo cancellation (NAEC). For this purpose we define a framework based on a parallel scheme in which any kernel-based adaptive filter (KAF) can be incorporated efficiently. This structure is composed of a classic adaptive filter on one branch, committed to estimating the linear part of the echo path, and a kernel adaptive filter on the other branch, to model the nonlinearities rebounding in the echo path. In addition, we propose a novel low-complexity least mean square (LMS) KAF with very few parameters, to be used in the parallel architecture. Finally, we demonstrate the effectiveness of the proposed scheme in real NAEC scenarios, for different choices of the KAF.},
	isbn = {978-0-9928-6265-7},
	author = {Van Vaerenbergh, Steven and Comminiello, Danilo and Azpicueta-Ruiz, Luis A.}
}
@conference {Eusipco02_spl,
	title = {Spline pulse-shaping with {ISI}-free matched filter receiver},
	booktitle = {XI European Signal Processing Conference (Eusipco 2002)},
	year = {2002},
	month = {September},
	address = {Toulouse, France},
	author = {Ib{\'a}{\~n}ez, Jes{\'u}s and Pantale{\'o}n, Carlos and D{\'\i}ez, J. and Santamar{\'\i}a, Ignacio}
}
@conference {Eusipco2007_FFF_MIMO,
	title = {A Spectral Clustering Algorithm for Decoding Fast Time-Varying {BPSK} {MIMO}},
	booktitle = {15th European Signal Processing Conference (EUSIPCO 2007)},
	year = {2007},
	month = {September},
	address = {Poznan, Poland},
	author = {Van Vaerenbergh, Steven and E. Est{\'e}banez and Santamar{\'\i}a, Ignacio}
}
@conference {icspat98_1,
	title = {Specific DSP based Monitoring System for Hydro-generator Sets},
	booktitle = {9th International Conf. on Signal Processing Applications and Technology},
	year = {1998},
	month = {September},
	address = {Toronto, Canada},
	author = {Ib{\'a}{\~n}ez, Jes{\'u}s and Pantale{\'o}n, Carlos and Santamar{\'\i}a, Ignacio and Luengo, David and L{\'a}zaro, Marcelino}
}
@conference {390,
	title = {Spatial Shaping and Precoding Design for Underlay MIMO Interference Channels},
	booktitle = {18th International ITG Workshop on Smart Antennas (WSA) },
	year = {2014},
	month = {March},
	address = {Erlangen, Germany},
	author = {Lameiro, Christian and Utschick, Wolfgang and Santamar{\'\i}a, Ignacio}
}
@conference {CogArt_2011_pub,
	title = {Spatial rank estimation in Cognitive Radio Networks with uncalibrated multiple antennas},
	booktitle = {4th International Conference on Cognitive Radio and Advanced Spectrum Management},
	year = {2011},
	month = {October},
	address = {Barcelona, Spain},
	author = {Vazquez-Vilar, G. and Ram{\'\i}rez, David and L{\'o}pez-Valcarce, Roberto and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {476,
	title = {On the Spatial Degrees of Freedom Benefits of Reverse TDD in Multicell MIMO Networks},
	booktitle = {24th European Signal Processing Conference (EUSIPCO 2016)},
	year = {2016},
	month = {September},
	pages = {1363-1367},
	address = {Budapest, Hungary},
	abstract = {In this paper we study the degrees of freedom (DoF) achieved by interference alignment (IA) for cellular networks in reverse time division duplex (R-TDD) mode, a new configuration associated to heterogeneous networks. We derive a necessary feasibility condition for interference alignment in the multi-cell R-TDD scenario, which is then specialized to the particular case of symmetric demands and antenna distribution. We show that, for those symmetric networks for which the properness condition holds with equality, R-TDD does not improve the DoF performance of conventional synchronous TDD systems. Nevertheless, our simulation results indicate that, in more
asymmetric scenarios, significant DoF benefits can be achieved by applying the R-TDD approach},
	author = {Fanjul, Jacobo and Santamar{\'\i}a, Ignacio}
}
@conference {292,
	title = {Spatial correlation beamforming scheme for MISO channel emulation},
	booktitle = {International Symposium on Wireless Communication Systems (ISWCS 2012)},
	year = {2012},
	month = {August},
	address = {Paris, France},
	author = {Guti{\'e}rrez, Jes{\'u}s and Ib{\'a}{\~n}ez, Jes{\'u}s and P{\'e}rez, Jes{\'u}s}
}
@conference {605,
	title = {Sparse subspace averaging for order estimation},
	booktitle = {IEEE Statistical Signal Processing Workshop},
	year = {2021},
	month = {July},
	abstract = {This paper addresses the problem of source enumeration for arbitrary geometry arrays in the presence of spatially correlated noise. The method combines a sparse reconstruction (SR) step with a subspace averaging (SA) approach, and hence it is named sparse subspace averaging (SSA). In the first step, each received snapshot is
approximated by a sparse linear combination of the rest of snapshots. The SR problem is regularized by the logarithm-based surrogate of the l0-norm and solved using a majorization-minimization approach. Based on the SR solution, a sampling mechanism is proposed in the second step to generate a collection of subspaces, all of which approximately span the same signal subspace. Finally, the dimension of the average of this collection of subspaces provides a robust estimate for the number of sources. Our simulation results show that SSA provides robust order estimates under a variety of noise models.},
	author = {Garg, Vaibhav and Ram{\'\i}rez, David and Santamar{\'\i}a, Ignacio}
}
@conference {Dspw94,
	title = {Sparse Deconvolution Using Gaussian Mixtures},
	booktitle = {Sixth IEEE Digital Signal Proc. Workshop},
	year = {1994},
	month = {October},
	address = {Yosemite, USA},
	author = {Santamar{\'\i}a, Ignacio and Figueiras-Vidal, Anibal R.}
}
@conference {570,
	title = {Source Enumeration via Toeplitz Matrix Completion},
	booktitle = {Int. Conf. Acoustics, Speech and Signal Processing (ICASSP)},
	year = {2020},
	month = {May},
	pages = {6004-6008},
	address = {Barcelona, Spain},
	abstract = {This paper addresses the problem of source enumeration by an array of sensors in the presence of noise whose spatial covariance structure is a diagonal matrix with possibly different variances, referred to non-iid noise hereafter, when the sources are uncorrelated. The diagonal terms of the sample covariance matrix are removed and, after applying Toeplitz rectification as a denoising step, the signal covariance matrix is reconstructed by using a low-rank matrix completion method adapted to enforce the Toeplitz structure of the sought solution. The proposed source enumeration criterion is based on the Frobenius norm of the reconstructed signal covariance matrix obtained for increasing rank values. As illustrated by simulation examples, the proposed method performs robustly for both small and large-scale arrays with few snapshots, i.e. small-sample regime.},
	author = {Garg, Vaibhav and Gimenez-Febrer, Pere and Pages-Zamora, Alba and Santamar{\'\i}a, Ignacio}
}
@conference {553,
	title = {Source Enumeration in Non-White Noise and Small Sample Size via Subspace Averaging},
	booktitle = {European Signal Processing Conference (EUSIPCO)},
	year = {2019},
	month = {September},
	address = {La Coru{\~n}a, Spain},
	abstract = {This paper addresses the problem of source enumeration by an array of sensors in the challenging conditions of: i) large uniform arrays with few snapshots, and ii) non-white or spatially correlated noises with arbitrary correlation. To solve this problem, we combine a subspace averaging (SA) technique, recently proposed for the case of independent and identically distributed (i.i.d.) noises, with a majority vote approach. The number of sources is detected for increasing dimensions of the SA technique and then a majority vote is applied to determine the final estimate. As illustrated by some simulation examples, this simple modification, makes SA a very robust method of enumerating sources in these challenging scenarios.},
	author = {Garg, Vaibhav and Santamar{\'\i}a, Ignacio}
}
@conference {SPAWC2007_2,
	title = {{SOS}-Based blind channel estimation under space-time block coded transmissions},
	booktitle = {Eighth IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2007)},
	year = {2007},
	month = {June},
	address = {Helsinki, Finland},
	author = {V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and Sezgin, A. and Paulraj, A. J.}
}
@conference {eusipco2007_STBC,
	title = {{SOS}-based blind channel estimation in multiuser space-time block coded systems},
	booktitle = {15th European Signal Processing Conference (EUSIPCO 2007)},
	year = {2007},
	month = {September},
	address = {Poznan, Poland},
	author = {V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and Sezgin, A. and Paulraj, A. J.}
}
@conference {Eusipco94,
	title = {Some Weighted Objective Approaches for Sparse Deconvolution},
	booktitle = {Seventh European Signal Proc. Conf.},
	year = {1994},
	month = {September},
	address = {Edinburgh, Scotland},
	author = {Santamar{\'\i}a, Ignacio and Figueiras-Vidal, Anibal R.}
}
@conference {Icassp2007_OSTBC_Id,
	title = {Some results on the blind identifiability of orthogonal space-time block codes from second order statistics},
	booktitle = {IEEE Int. Conf. on Acoust., Speech, and Signal Processing (ICASSP 2007)},
	year = {2007},
	month = {April},
	address = {Hawaii, USA},
	author = {V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {ISCAS2000,
	title = {A Smooth and Derivable Large-Signal Model for Microwave {HEMT} Transistors},
	booktitle = {The IEEE International Symposium on Circuits and Systems},
	year = {2000},
	month = {May},
	address = {Geneva, Switzerland},
	author = {L{\'a}zaro, Marcelino and Santamar{\'\i}a, Ignacio and Pantale{\'o}n, Carlos}
}
@conference {vanvaerenbergh2006sliding,
	title = {A Sliding-Window Kernel {RLS} Algorithm and its Application to Nonlinear Channel Identification},
	booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)},
	year = {2006},
	month = {May},
	address = {Toulouse, France},
	abstract = {In this paper we propose a new kernel-based version of the recursive least-squares (RLS) algorithm for fast adaptive nonlinear filtering. Unlike other previous approaches, we combine a sliding-window approach (to fix the dimensions of the kernel matrix) with conventional -norm regularization (to improve generalization). The proposed kernel RLS algorithm is applied to a nonlinear channel identification problem (specifically, a linear filter followed by a memoryless nonlinearity), which typically appears in satellite communications or digital magnetic recording systems. We show that the proposed algorithm is able to operate in a time-varying environment and tracks abrupt changes in either the linear filter or the nonlinearity.},
	keywords = {kernel adaptive filtering, KRLS},
	author = {Van Vaerenbergh, Steven and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {Imtc1997,
	title = {Simultaneous Sampling by Digital Phase Correction},
	booktitle = {IEEE Instrumentation and Measurement Technology Conference},
	year = {1997},
	month = {May},
	address = {Ottawa, Canada},
	author = {Luengo, David and Pantale{\'o}n, Carlos and Santamar{\'\i}a, Ignacio and Ib{\'a}{\~n}ez, Jes{\'u}s and G{\'o}mez, E.}
}
@conference {CTMobileSummit2009_Paper_ref_194_Michael_pub,
	title = {Simulation Framework for Performance Evaluation of RF Antenna Combining Systems},
	booktitle = {ICT-MobileSummit 2009},
	year = {2009},
	month = {June},
	address = {Santander, Spain},
	author = {Wickert, M. and Mayer, U. and Eickhoff, R. and Ellinger, F. and Ib{\'a}{\~n}ez, Jes{\'u}s and Santamar{\'\i}a, Ignacio}
}
@conference {ICT2009_Simplified_Analog_Combining,
	title = {Simplified Architectures for Analogue Antenna Combining},
	booktitle = {ICT-MobileSummit 2009},
	year = {2009},
	month = {June},
	address = {Santander, Spain},
	author = {Gholam, Fouad and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and Wickert, M. and Eickhoff, R.}
}
@conference {Icassp2011_Semisupervised,
	title = {Semi-Supervised Handwritten Digit Recognition Using Very Few Labeled Data},
	booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011)},
	year = {2011},
	month = {May},
	address = {Prague, Czech Republic},
	author = {Van Vaerenbergh, Steven and Santamar{\'\i}a, Ignacio and Barbano, Paolo Emilio}
}
@conference {Vtc2005_Luengo_pub,
	title = {Secure communications using {OFDM} with chaotic modulation in the subcarriers},
	booktitle = {IEEE Vehicular Technology Conference, Spring (VTC 2005)},
	year = {2005},
	month = {May},
	address = {Stockholm, Sweden},
	author = {Luengo, David and Santamar{\'\i}a, Ignacio}
}
@conference {389,
	title = {Robust Secret Key Capacity for the MIMO Induced Source Model},
	booktitle = {International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
	year = {2014},
	month = {May},
	address = {Florence, Italy},
	author = {V{\'\i}a, Javier}
}
@conference {Icassp2005_pub,
	title = {A robust {RLS} algorithm for adaptive canonical correlation analysis},
	booktitle = {IEEE Int. Conf. on Acoust., Speech, and Signal Processing (ICASSP 2005)},
	year = {2005},
	month = {March},
	address = {Philadelphia, USA},
	author = {V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and P{\'e}rez, Jes{\'u}s}
}
@conference {Eusipco_Kfda,
	title = {Robust matched filtering in the feature space},
	booktitle = {13th European Signal Processing Conference (EUSIPCO 2005)},
	year = {2005},
	month = {September},
	address = {Antalya, Turkey},
	author = {Santamar{\'\i}a, Ignacio and Erdogmus, Deniz and R. Agrawal and Pr{\'\i}ncipe, Jos{\'e} C.}
}
@conference {icassp2006_Adatron_pub,
	title = {Robust blind {SIMO} channel estimation using Adatron},
	booktitle = {IEEE Int. Conf. on Acoust., Speech, and Signal Processing (ICASSP 2006)},
	year = {2006},
	month = {May},
	address = {Toulouse, France},
	author = {Han, D. and Pr{\'\i}ncipe, Jos{\'e} C. and Yang, L. and Santamar{\'\i}a, Ignacio and V{\'\i}a, Javier}
}
@conference {261,
	title = {Robust blind identification of {SIMO} channels: a support vector regression approach},
	booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2004)},
	year = {2004},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Montreal, Canada},
	author = {Santamar{\'\i}a, Ignacio and V{\'\i}a, Javier and Gaudes, C. C.}
}
@conference {SPAWC2004,
	title = {Robust array beamforming with sidelobe control using support vector machines},
	booktitle = {Fifth IEEE Workshop on Signal Processing Advances in Wireless Communications, (SPAWC 2004)},
	year = {2004},
	month = {July},
	address = {Lisboa, Portugal},
	author = {Gaudes, C. C. and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {471,
	title = {On The Relationship Between Online Gaussian Process Regression And Kernel Least Mean Squares Algorithms},
	booktitle = {2016 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2016)},
	year = {2016},
	month = {September},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Salerno, Italy},
	abstract = {We study the relationship between online Gaussian process (GP) regression and kernel least mean squares (KLMS) algorithms. While the latter have no capacity of storing the entire posterior distribution during online learning, we discover that their operation corresponds to the assumption of a fixed posterior covariance that follows a simple parametric model. Interestingly, several well-known KLMS algorithms correspond to specific cases of this model. The probabilistic perspective allows us to understand how each of them handles uncertainty, which could explain some of their performance differences.},
	keywords = {gaussian processes, kernel adaptive filtering, KLMS},
	author = {Van Vaerenbergh, Steven and Fern{\'a}ndez-Bes, Jes{\'u}s and Elvira, Victor}
}
@conference {424,
	title = {A Regularized Maximum Likelihood Estimator for the Period of a Cyclostationary Process},
	booktitle = {Asilomar Conference on Signals, Systems, and Computers},
	year = {2014},
	month = {November},
	address = {Pacific Grove, USA},
	author = {Ram{\'\i}rez, David and Schreier, Peter J. and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and Louis L. Scharf}
}
@conference {Icecs2001,
	title = {A Regularized Digital Filtering Technique for the Simultaneous Reconstruction of a Function and its Derivatives},
	booktitle = {8th International Conference on Electronics, Circuits and Systems, (ICECS2001)},
	year = {2001},
	month = {September},
	address = {Malta},
	author = {L{\'a}zaro, Marcelino and Santamar{\'\i}a, Ignacio and Pantale{\'o}n, Carlos}
}
@conference {493,
	title = {Recursive multikernel filters exploiting nonlinear temporal structure},
	booktitle = {25th European Signal Processing Conference (EUSIPCO 2017)},
	year = {2017},
	month = {August},
	address = {Kos, Greece},
	isbn = {978-0-9928626-7-1},
	author = {Van Vaerenbergh, Steven and Scardapane, Simone and Santamar{\'\i}a, Ignacio}
}
@conference {525,
	title = {Recurrent Neural Networks With Flexible Gates Using Kernel Activation Functions},
	booktitle = {IEEE International Workshop on Machine Learning for Signal Processing},
	year = {2018},
	month = {September},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Aalborg, Denmark},
	abstract = {Gated recurrent neural networks have achieved remarkable results in the analysis of sequential data. Inside these networks, gates are used to control the flow of information, allowing to model even very long-term dependencies in the data. In this paper, we investigate whether the original gate equation (a linear projection followed by an element-wise sigmoid) can be improved. In particular, we design a more flexible architecture, with a small number of adaptable parameters, which is able to model a wider range of gating functions than the classical one. To this end, we replace the sigmoid function in the standard gate with a non-parametric formulation extending the recently proposed kernel activation function (KAF), with the addition of a residual skip-connection. A set of experiments on sequential variants of the MNIST dataset shows that the adoption of this novel gate allows to improve accuracy with a negligible cost in terms of computational power and with a large speed-up in the number of training iterations.},
	author = {Scardapane, Simone and Van Vaerenbergh, Steven and Comminiello, Danilo and Totaro, Simone and Uncini, Aurelio}
}
@conference {572,
	title = {Rate Region of the K-user MIMO Interference Channel with Imperfect Transmitters},
	booktitle = {European Signal Processing Conference (EUSIPCO 2020)},
	year = {2020},
	month = {August},
	pages = {1638-1642},
	address = {Amsterdamd, The Netherlands},
	abstract = {This paper studies the rate region of a multiple-input, multiple-output (MIMO) system with imperfect transmitters when interference is treated as noise at the receiver side. We consider a K-user MIMO interference channel (IC) in which the transmitters suffer from an additive hardware distortion (HWD) modeled as spatially uncorrelated Gaussian noise with covariance matrix proportional to the transmit covariance matrix. We employ the difference of convex programming (DCP) technique to solve the rate-region optimization problem and obtain its stationary points. Our proposed HWD-aware algorithm outperforms the HWD-unaware design that disregards HWD. Our results show that the performance of the K-user MIMO IC is highly affected by HWD, especially in high signal-to-noise-ratio scenarios.},
	author = {Mohammad Soleymani and Santamar{\'\i}a, Ignacio and Maham, Behrouz and Schreier, Peter J.}
}
@conference {635,
	title = {Rate region of MIMO RIS-assisted broadcast channels with rate splitting and improper signaling},
	booktitle = {International ITG 26th Workshop on Smart Antennas},
	year = {2023},
	month = {March},
	address = {Braunschweig, Germany},
	author = {Mohammad Soleymani and Santamar{\'\i}a, Ignacio and Jorswieck, Eduard}
}
@conference {365,
	title = {Rate adaptation in cognitive radio links with time-varying channels},
	booktitle = {21st European Signal Processing Conference (EUSIPCO)},
	year = {2013},
	month = {September},
	publisher = { European Signal Processing (EURASIP) Society},
	organization = { European Signal Processing (EURASIP) Society},
	address = {Marrakech, Morocco},
	abstract = {In this work we address the optimal rate adaptation problem of a cognitive radio (CR) link in time-variant channels. A secondary user (SU) link detects an idle channel and starts the transmission with the goal of transmitting a given amount of data packets. During the transmission the transmitter dynamically adapts the frames rate, from a finite number of available rates, according to the channel state. If a frame is decoded with error, the corresponding data must be retransmitted in further frames. If a primary user (PU) access the channel during  the process, the CR link immediately stops the transmission.The rate adaptation problem is formulated as an infinite horizon Markov decision process (MDP). We split the problem
in a finite number of much simpler MDP problems that can be efficiently solved by conventional MDP solving algorithms. So, the optimal policy and the corresponding maximum probability of successful transmission can be easily obtained.},
	keywords = {Cognitive radio (CR), Markov decision processes (MDP), rate control},
	isbn = { ISSN 2219-5491},
	author = {{\'A}lvaro Gonzalo and P{\'e}rez, Jes{\'u}s}
}
@conference {AP2000_b,
	title = {Radio coverage study of airports using {GTD/UTD} techniques},
	booktitle = {AP2000 Millennium Conference on Antennas and Propagation},
	year = {2000},
	month = {April},
	address = {Davos, Switzerland},
	author = {Guti{\'e}rrez, O. and Gonz{\'a}lez, I. and Saez de Adana, F. and P{\'e}rez, Jes{\'u}s and C{\'a}tedra, M. F.}
}
@conference {503,
	title = { A quaternion-based approach to interference alignment with Alamouti coding},
	booktitle = {IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)},
	year = {2017},
	month = {December},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Bilbao, Spain},
	abstract = {Based on the representation of Alamouti space-time codewords as quaternions, this paper proposes a scheme that combines interference alignment (IA) with Alamouti signals. The proposed formulation allows for a separation of the space-time block coding (to gain spatial diversity) and the IA precoding (to reduce or ideally suppress interference). Although this separation is not necessarily optimal, the splitting of alignment precoding and Alamouti encoding is particularly convenient because it enables the independent optimization of the IA solution using quaternionic versions of standard alternating optimization techniques such as the maximum signal-to-interference-plus-noise algorithm. Some numerical simulations are included to compare the performance of the proposed quaternion IA+Alamouti algorithm with standard IA algorithms in the complex domain as well as with interference cancellation schemes at the receiver side.},
	author = {Fanjul, Jacobo and Santamar{\'\i}a, Ignacio and Loucera, Carlos}
}
@conference {259,
	title = {Quasi-Smart Optical Fibre Sensor System for Real Time and Predictive Monitoring on Large Rotating Machinery},
	booktitle = {Conference on Lasers and Electro-Optics Europe (CLEO 1998)},
	year = {1998},
	author = {L{\'o}pez-Higuera, J. M. and Santamar{\'\i}a, Ignacio and Cobo, A. and Pantale{\'o}n, Carlos and Morante, M. A. and Ib{\'a}{\~n}ez, Jes{\'u}s and Echevarria, J.}
}
@conference {260,
	title = {Protection and monitoring system for hydroelectric generating sets},
	booktitle = {EUROMAINTENANCE 96},
	year = {1996},
	address = {Copenhagen, Denmark},
	author = {Arregui, F. and Mazzieri, C. and Pantale{\'o}n, Carlos and G{\'o}mez, E. and Mottier, P. and Marcou, J. and Garc{\'\i}a, J. L. and Santamar{\'\i}a, Ignacio and L{\'o}pez-Higuera, J. M. and Viadero, F.}
}
@conference {431,
	title = {A Probabilistic Least-Mean-Squares Filter},
	booktitle = {2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
	year = {2015},
	month = {April},
	address = {Brisbane, Queensland, Australia},
	abstract = {We introduce a probabilistic approach to the LMS filter. By means of an efficient approximation, this approach provides an adaptable step-size LMS algorithm together with a measure of uncertainty about the estimation. In addition, the proposed approximation preserves the linear complexity of the standard LMS. Numerical results show the improved performance of the algorithm with respect to standard LMS and state-of-the-art algorithms with similar complexity. The goal of this work, therefore, is to open the door to bring some more Bayesian machine learning techniques to adaptive filtering.},
	keywords = {adaptive filtering, least-mean-squares, probabilistic models, state-space models},
	doi = {10.1109/ICASSP.2015.7178361},
	author = {Fern{\'a}ndez-Bes, Jes{\'u}s and Elvira, Victor and Van Vaerenbergh, Steven}
}
@conference {393,
	title = {Probabilistic Kernel Least Mean Squares Algorithms},
	booktitle = {2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
	year = {2014},
	month = {05/2014},
	abstract = {The kernel least mean squares (KLMS) algorithm is a computationally efficient nonlinear adaptive filtering method that "kernelizes" the celebrated (linear) least mean squares algorithm. We demonstrate that the least mean squares algorithm is closely related to the Kalman filtering, and thus, the KLMS can be interpreted as an approximate Bayesian filtering method. This allows us to systematically develop extensions of the KLMS by modifying the underlying state-space and observation models. The resulting extensions introduce many desirable properties such as "forgetting", and the ability to learn from discrete data, while retaining the computational simplicity and time complexity of the original algorithm.},
	keywords = {kernel adaptive filtering, KLMS, sequential Bayesian learning, state-space model},
	isbn = {978-1-4799-2892-7},
	author = {Park, Il Memming and Seth, Sohan and Van Vaerenbergh, Steven}
}
@conference {281,
	title = {Pre- and Post-FFT Interference Leakage Minimization for MIMO OFDM Networks},
	booktitle = {The Ninth International Symposium on Wireless Communication Systems (ISWCS 2012)},
	year = {2012},
	month = {August},
	address = {Paris, France},
	author = {Lameiro, Christian and Gonz{\'a}lez, {\'O}scar and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and Heath Jr., Robert W.}
}
@conference {348,
	title = {Power-CCA: Maximizing the Correlation Coefficient between the Power of Projections},
	booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)},
	year = {2013},
	month = {May},
	address = {Vancouver, Canada},
	doi = {10.1109/ICASSP.2013.6638864},
	author = {Ram{\'\i}rez, David and Schreier, Peter J. and V{\'\i}a, Javier and Nikulin, Vadim V.}
}
@conference {540,
	title = {Power Minimization in Multi-tier Networks with Flexible Duplexing},
	booktitle = {IEEE Int. Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
	year = {2019},
	month = {May},
	address = {Brighton, UK},
	abstract = {In this paper we present an algorithm to minimize transmit power in multiple-input multiple-output (MIMO) heterogeneous
networks (HetNets) with flexible duplexing, a promising strategy that allows the coexistence of uplink and downlink cells within the same time and frequency resource block. First, the proposed algorithm minimizes transmit power for a given uplink/downlink (UL/DL) combination, and afterwards, the optimal solution out of the explored UL/DL combinations is selected. To reduce
the computational cost of exploring all the UL/DL settings, we propose a hierarchical switching (HS) approach
that considers a reduced subset of transmit directions. By means of Monte Carlo simulations, we show that the proposed
technique provides significant power savings with respect to a conventional time-division duplex (TDD) scheme.},
	author = {Fanjul, Jacobo and Santamar{\'\i}a, Ignacio}
}
@conference {394,
	title = {Physical Layer Authentication based on Channel Response Tracking using Gaussian Processes},
	booktitle = {2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
	year = {2014},
	month = {May},
	pages = {2429--2433},
	abstract = {Physical-layer authentication techniques exploit the unique properties of the wireless medium to enhance traditional higher-level authentication procedures. We propose to reduce the higher-level authentication overhead by using a state-of-the-art multi-target tracking technique based on Gaussian processes. The proposed technique has the additional advantage that it is capable of automatically learning the dynamics of the trusted user{\textquoteright}s channel response and the time-frequency fingerprint of intruders. Numerical simulations show very low intrusion rates, and an experimental validation using a wireless test bed with programmable radios demonstrates the technique{\textquoteright}s effectiveness.},
	keywords = {gaussian processes, multi-target tracking, physical-layer authentication, wireless communications},
	isbn = {978-1-4799-2892-7},
	author = {Van Vaerenbergh, Steven and Gonz{\'a}lez, {\'O}scar and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {IST_Mobile_Summit_2007,
	title = {Performance of {STBC} transmissions with real data},
	booktitle = {16th IST Mobile \& Wireless Communications Summit},
	year = {2007},
	month = {July},
	address = {Budapest, Hungary},
	author = {Garc{\'\i}a-Naya, J. A. and Fern{\'a}ndez-Caram{\'e}s, T. M. and H{\'e}ctor J. P{\'e}rez Iglesias and Gonz{\'a}lez L{\'o}pez, M. and Castedo, Luis and Ram{\'\i}rez, David and Santamar{\'\i}a, Ignacio and P{\'e}rez, Jes{\'u}s and V{\'\i}a, Javier and Torres-Royo, J. M.}
}
@conference {VTC_2004,
	title = {Performance of MIMO systems based on dual polarized antennas in urban microcellular environments},
	booktitle = {IEEE Vehicular Technology Conference, Fall (VTC 2004)},
	year = {2004},
	month = {September},
	address = {Los Angeles, CA, USA},
	author = {P{\'e}rez, Jes{\'u}s and Ib{\'a}{\~n}ez, Jes{\'u}s and Vielva, Luis and Santamar{\'\i}a, Ignacio}
}
@conference {ICTMobileSummit2009_Paper_ref_11_Ralf_pub,
	title = {Performance Evaluation of Wireless MIMO Radios},
	booktitle = {ICT-MobileSummit 2009},
	year = {2009},
	month = {June},
	address = {Santander, Spain},
	author = {Eickhoff, R. and Mayer, U. and Ellinger, F. and Santamar{\'\i}a, Ignacio and Gonz{\'a}lez, L.}
}
@conference {bmsb_2009,
	title = {Performance Analysis of Transmit Antenna Selection in Broadcast {MISO} Channels},
	booktitle = {2009 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting},
	year = {2009},
	month = {May},
	address = {Bilbao, Spain},
	author = {P{\'e}rez, Jes{\'u}s and Guti{\'e}rrez, Jes{\'u}s and Vielva, Luis}
}
@conference {512,
	title = {Performance analysis of maximally improper signaling for multiple-antenna systems},
	booktitle = {IEEE Wireless Communications and Networking Conference (WCNC)},
	year = {2018},
	month = {April},
	address = {Barcelona, Spain},
	author = {Lameiro, Christian and Santamar{\'\i}a, Ignacio and Schreier, Peter J.}
}
@conference {507,
	title = {Pattern Localization in Time Series through Signal-To-Model Alignment in Latent Space},
	booktitle = {2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
	year = {2018},
	month = {April},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Calgary, Alberta, Canada},
	abstract = {In this paper, we study the problem of locating a predefined sequence of patterns in a time series. In particular, the studied scenario assumes a theoretical model is available that contains the expected locations of the patterns. This problem is found in several contexts, and it is commonly solved by first synthesizing a time series from the model, and then aligning it to the true time series through dynamic time warping. We propose a technique that increases the similarity of both time series before aligning them, by mapping them into a latent correlation space. The mapping is learned from the data through a machine-learning setup. Experiments on data from non-destructive testing demonstrate that the proposed approach shows significant improvements over the state of the art.},
	author = {Van Vaerenbergh, Steven and Santamar{\'\i}a, Ignacio and Elvira, Victor and Salvatori, Matteo}
}
@conference {MLSP09_Clustering_Time_Varying_MIMO,
	title = {Path-Based Spectral Clustering for Decoding Fast Time-Varying {MIMO} Channels},
	booktitle = {2009 International Workshop on Machine Learning for Signal Processing (MLSP)},
	year = {2009},
	month = {September},
	address = {Grenoble, France},
	author = {Van Vaerenbergh, Steven and Santamar{\'\i}a, Ignacio and Barbano, Paolo Emilio and Ozertem, Umut and Erdogmus, Deniz}
}
@conference {475,
	title = {Passive Detection of Rank-One Signals with a Multiantenna Reference Channel},
	booktitle = { 24th European Signal Processing Conference (EUSIPCO 2016)},
	year = {2016},
	month = {September},
	pages = {140-144},
	address = {Budapest, Hungary},
	abstract = {In this work we consider a two-channel passive detection problem,
in which there is a surveillance array where the presence/absence of a target signal is to be detected, and a reference array that provides a noise-contaminated version of the target signal. We assume that the transmitted signal is an unknown rank-one signal, and that the noises are uncorrelated between the two channels, but each one having an unknown and arbitrary spatial covariance matrix. We show that the generalized likelihood ratio test (GLRT) for this problem rejects the null hypothesis when the largest canonical correlation of the sample coherence matrix between the surveillance and the reference channels exceeds a threshold. Further, based on recent results from random matrix theory, we provide an approximation for the null distribution of the test statistic.},
	author = {Santamar{\'\i}a, Ignacio and Louis L. Scharf and Cochran, D. and V{\'\i}a, Javier}
}
@conference {641,
	title = {Passive Detection of Rank-one Gaussian Signals for Known Channel Subspaces and Arbitrary Noise},
	booktitle = {IEEE International Conference on Acoustics Speech and Signal Processing},
	year = {2023},
	month = {June},
	address = {Rhodes, Greece},
	author = {Ram{\'\i}rez, David and Santamar{\'\i}a, Ignacio and Louis L. Scharf}
}
@conference {Icassp2004_splines,
	title = {Parametric smoothing of spline interpolation},
	booktitle = {IEEE Int. Conf. on Acoust., Speech, and Signal Processing (ICASSP 2004)},
	year = {2004},
	month = {May},
	address = {Montreal, Canada},
	author = {Ib{\'a}{\~n}ez, Jes{\'u}s and Santamar{\'\i}a, Ignacio and Pantale{\'o}n, Carlos and Vielva, Luis}
}
@conference {466,
	title = {An order fitting rule for optimal subspace averaging},
	booktitle = {IEEE Workshop on Statistical Signal Processing (SSP)},
	year = {2016},
	month = {June },
	address = {Palma de Mallorca},
	abstract = {The problem of estimating a low-dimensional subspace from a collection of experimentally measured subspaces arises in many applications of statistical signal processing. In this paper we address this problem, and give a solution for the average subspace that minimizes an extrinsic mean-squared error, defined by the squared Frobenius norm between projection matrices. The solution automatically returns the dimension of the optimal average subspace, which is the novel result of the paper. The proposed order fitting rule is based on thresholding the eigenvalues of the average projection matrix, and thus it is free of penalty terms or other tuning parameters commonly used by other rank estimation techniques. Several numerical examples demonstrate the usefulness and applicability of the proposed criterion, showing how the dimension of the average subspace captures the variability of the measured subspaces. },
	author = {Santamar{\'\i}a, Ignacio and Louis L. Scharf and Peterson, Chris and Kirby, Michael and Francos, Joseph}
}
@conference {291,
	title = {Optimal rate and delay performance in non-cooperative opportunistic spectrum access},
	booktitle = {9th International Symposium on Wireless Communication Systems (ISWCS 2012)},
	year = {2012},
	month = {August},
	address = {Paris, France},
	author = {P{\'e}rez, Jes{\'u}s and M. Khodaian}
}
@conference {SPAWC2009 OBDM_Corr,
	title = {Optimal Precoding for a Novel RF-MIMO Scheme in Transmit Correlated Rayleigh Channels},
	booktitle = {10th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2009)},
	year = {2009},
	month = {June},
	address = {Perugia, Italy},
	author = {V{\'\i}a, Javier and Elvira, Victor and Ib{\'a}{\~n}ez, Jes{\'u}s and Santamar{\'\i}a, Ignacio}
}
@conference {Eusipco2008_MIMAX,
	title = {Optimal {MIMO} transmission schemes with adaptive antenna combining in the {RF} path},
	booktitle = {16th European Signal Processing Conference (EUSIPCO 2008)},
	year = {2008},
	month = {August},
	address = {Lausanne, Switzerland},
	author = {Santamar{\'\i}a, Ignacio and Elvira, Victor and V{\'\i}a, Javier and Ram{\'\i}rez, David and P{\'e}rez, Jes{\'u}s and Ib{\'a}{\~n}ez, Jes{\'u}s and Eickhoff, R. and Ellinger, F.}
}
@conference {Icsp2000,
	title = {Optimal Estimation of a Class of Chaotic Signals},
	booktitle = {5th International Conference on Signal Processing},
	year = {2000},
	month = {August},
	address = {Beijing, China},
	author = {Pantale{\'o}n, Carlos and Luengo, David and Santamar{\'\i}a, Ignacio}
}
@conference {IJCNN_2006,
	title = {Online kernel canonical correlation analysis for supervised equalization of {Wiener} systems},
	booktitle = {IEEE International Joint Conference on Neural Networks (IJCNN 2006)},
	year = {2006},
	month = {July},
	address = {Vancouver, Canada},
	author = {Van Vaerenbergh, Steven and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {icspat98_2,
	title = {A Novel Simultaneous Sampling Technique and its Application to Multipoint Optical Fibre Sensor Accelerometers},
	booktitle = {9th International Conf. on Signal Processing Applications \& Technology},
	year = {1998},
	month = {September},
	address = {Toronto, Canada},
	author = {Luengo, David and Pantale{\'o}n, Carlos and Santamar{\'\i}a, Ignacio and Ib{\'a}{\~n}ez, Jes{\'u}s and C. L{\'o}pez-Salaverri and Madruga, F. J. and Cobo, A. and L{\'o}pez-Higuera, J. M.}
}
@conference {Imtc00_under,
	title = {Nonlinearity Estimation in Power Amplifiers Based on Undersampled Temporal Data},
	booktitle = {IEEE Instrumentation and Measurement Technology Conference},
	year = {2000},
	month = {May},
	address = {Baltimore, Maryland, USA},
	author = {Ib{\'a}{\~n}ez, Jes{\'u}s and Pantale{\'o}n, Carlos and Santamar{\'\i}a, Ignacio and T. Fern{\'a}ndez and D. Mart{\'\i}nez}
}
@conference {642,
	title = {Noncoherent Multiuser Grassmannian Constellations for the MIMO Multiple Access Channel},
	booktitle = {IEEE International Conference on Acoustics Speech and Signal Processing},
	year = {2023},
	month = {June},
	address = {Rhodes, Greece},
	author = {Alvarez-Vizoso, Javier and Cuevas, Diego and Beltr{\'a}n, Carlos and Santamar{\'\i}a, Ignacio and Tucek, V{\'\i}t and Peters, Gunnar}
}
@conference {664,
	title = {NOMA-based Improper Signaling for MIMO STAR-RIS-assisted Broadcast Channels with Hardware Impairments},
	booktitle = {IEEE Global Communications Conference (GLOBECOM)},
	year = {2023},
	month = {Dec.},
	author = {Mohammad Soleymani and Santamar{\'\i}a, Ignacio and Jorswieck, Eduard}
}
@conference {557,
	title = {Node activity monitoring in heterogeneous networks using energy sensors},
	booktitle = {European Signal Processing Conference (EUSIPCO)},
	year = {2019},
	month = {September},
	author = {P{\'e}rez, Jes{\'u}s and V{\'\i}a, Javier and Vielva, Luis}
}
@conference {SAM08_STBC_OFDM,
	title = {A New Subspace Algorithm for Blind Channel Estimation in Broadband {Space-Time} Block Coded Communication Systems},
	booktitle = {Fifth IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2008)},
	year = {2008},
	month = {July},
	address = {Darmstadt, Germany},
	author = {V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and P{\'e}rez, Jes{\'u}s}
}
@conference {Icassp96,
	title = {A New Inverse Filter Criterion for Blind Deconvolution of Spiky Signals Using Gaussian Mixtures},
	booktitle = {Proc. of the 1996 IEEE Int. Conf. on Acoust., Speech, and Signal Processing},
	year = {1996},
	month = {May},
	address = {Atlanta, USA},
	author = {Santamar{\'\i}a, Ignacio and Pantale{\'o}n, Carlos and D{\'\i}az de Mar{\'\i}a, F. and Art{\'e}s, Antonio}
}
@conference {Ijcnn2000_wave,
	title = {Neuronal Architecture for Waveguide Inductive Iris Bandpass Filter Optimization},
	booktitle = {IEEE International Joint Conference on Neural Networks (IJCNN 2000)},
	year = {2000},
	month = {July},
	address = {Como, Italy},
	author = {Mediavilla, A. and Taz{\'o}n, A. and Pereda, J. A. and L{\'a}zaro, Marcelino and Santamar{\'\i}a, Ignacio and Pantale{\'o}n, Carlos}
}
@conference {Imtc00_nn,
	title = {Neural Networks for Large and Small-Signal Modeling of {MESFET/HEMT} Transistors: A Comparative Study},
	booktitle = {IEEE Instrumentation and Measurement Technology Conference},
	year = {2000},
	month = {May},
	address = {Baltimore, Maryland, USA},
	author = {L{\'a}zaro, Marcelino and Santamar{\'\i}a, Ignacio and Pantale{\'o}n, Carlos}
}
@conference {SSPNice2011_ML_beamsteering,
	title = {Multi-Sensor Beamsteering Based on the Asymptotic Likelihood for Colored Signals},
	booktitle = {IEEE Workshop on Statistical Signal Processing (SSP 2011)},
	year = {2011},
	month = {June},
	address = {Nice, France},
	author = {Ram{\'\i}rez, David and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and Louis L. Scharf}
}
@conference {CIP2008,
	title = {Multiple-Channel Signal Detection using the Generalized Coherence spectrum},
	booktitle = {1st IAPR Workshop on Cognitive Information Processing (CIP 2008)},
	year = {2008},
	month = {June},
	address = {Santorini, Greece},
	author = {Ram{\'\i}rez, David and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {ICASSP2011Prague_GLRT_flat_fading,
	title = {Multiple-Channel Detection of a Gaussian Time Series over Frequency-Flat Channels},
	booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011)},
	year = {2011},
	month = {May},
	address = {Prague, Czech Republic},
	author = {Ram{\'\i}rez, David and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and Louis L. Scharf}
}
@conference {604,
	title = {Multi-output kernel adaptive filtering with reduced complexity},
	booktitle = {IEEE Statistical Signal Processing Workshop},
	year = {2021},
	month = {July},
	abstract = {In this paper, two new multi-output kernel adaptive filtering algorithms are developed that exploit the temporal and spatial correlations among the input-output multivariate time series. They are multi-output versions of the popular kernel least mean squares
(KLMS) algorithm with two different sparsification criteria. The first one, denoted as MO-QKLMS, uses the coherence criterion in order to limit the dictionary size. The second one, denoted as MORFF-KLMS, uses random Fourier features (RFF) to approximate
the kernel functions by linear inner products. Simulation results with synthetic and real data are presented to assess convergence speed, steady-state performance and complexities of the proposed algorithms.},
	author = {Cuevas, Diego and Santamar{\'\i}a, Ignacio}
}
@conference {443,
	title = {Multi-instance multi-label learning in the presence of novel class instances},
	booktitle = {32nd International Conference on Machine Learning (ICML)},
	year = {2015},
	month = {July},
	address = {Lille, France},
	abstract = {Multi-instance multi-label learning (MIML) is a framework for learning in the presence of label ambiguity. In MIML, experts provide labels for groups of instances (bags), instead of directly providing a label for every instance. When labeling efforts are focused on a set of target classes, instances outside this set will not be appropriately modeled. For example, ornithologists label bird audio recordings with a list of species present. Other additional sound instances, e.g., a rain drop or a moving vehicle sound, are not labeled. The challenge is due to the fact that for a given bag, the presence or absence of novel instances is latent. In this paper, this problem is addressed using a discriminative probabilistic model that accounts for novel instances. We propose an exact and efficient implementation of the maximum likelihood approach to determine the model parameters and consequently learn an instance-level classifier for all classes including the novel class. Experiments on both synthetic and real datasets illustrate the effectiveness of the proposed approach.},
	url = {http://icml.cc/2015/?page_id=825$\#$SupervisedLearning~I},
	author = {Pham, Anh T. and Raviv Raich and Fern, Xiaoli Z. and P{\'e}rez, Jes{\'u}s}
}
@conference {SAM2010_CR,
	title = {Multiantenna spectrum sensing: The case of wideband rank-one primary signals},
	booktitle = {6th IEEE Sensor Array and Multichannel Signal Processing Workshop},
	year = {2010},
	month = {October},
	address = {Israel},
	author = {Ram{\'\i}rez, David and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {ICASSP2010_CR_SpecSensing,
	title = {Multiantenna Spectrum Sensing: Detection of Spatial Correlation Among Time-Series With Unknown Spectra},
	booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)},
	year = {2010},
	month = {March},
	address = {Dallas, USA},
	author = {Ram{\'\i}rez, David and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and L{\'o}pez-Valcarce, Roberto and Louis L. Scharf}
}
@conference {ICASSP2011Prague_rankP_noIID,
	title = {Multiantenna Detection under Noise Uncertainty and Primary Users Spatial Structure},
	booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011)},
	year = {2011},
	month = {May},
	address = {Prague, Czech Republic},
	author = {Ram{\'\i}rez, David and Vazquez-Vilar, G. and L{\'o}pez-Valcarce, Roberto and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {258,
	title = {A Monitoring and Protection System for Hydro Turbine and Generator sets},
	booktitle = {CIGRE},
	year = {1996},
	address = {Paris},
	author = {Arregui, F. and G{\'o}mez Cossio, E. and Mazzieri, C. and Mottier, P. and Garc{\'\i}a, J. L. and L{\'o}pez-Higuera, J. M. and Pantale{\'o}n, Carlos and Santamar{\'\i}a, Ignacio and Lucifredi, A. and Rossi, M.}
}
@conference {Ijcnn2000,
	title = {A Modular Neural Network for Global Modeling of Microwave Transistors},
	booktitle = {IEEE International Joint Conference on Neural Networks (IJCNN 2000)},
	year = {2000},
	month = {July},
	address = {Como, Italy},
	author = {L{\'a}zaro, Marcelino and Santamar{\'\i}a, Ignacio and Pantale{\'o}n, Carlos and Navarro, C. and Taz{\'o}n, A. and T. Fern{\'a}ndez}
}
@conference {368,
	title = {Model-free Adaptive Rate Selection in Cognitive Radio Links},
	booktitle = {5th International Conference on Mobile Networks and Management (MONAMI)},
	year = {2013},
	month = {September},
	publisher = {Springer-Verlag. LNICST series},
	organization = {Springer-Verlag. LNICST series},
	address = {Cork, Ireland},
	abstract = {In this work we address the rate adaptation problem of a cognitive radio (CR) link in time-variant fading channels. Every time the primary users (PU) liberate the channel the secondary user (SU) selects a transmission rate (from a finite number of available rates) and begins the transmission of fixed sized packets until a licensed user reclaims the channel back. After each transmission episode the number of successfully transmitted packets is used by the SU to update its optimal rate selection ahead of the next episode. The problem is formulated as an n-armed bandit problem and it is solved by means of a Monte Carlo control algorithm.},
	keywords = {Cognitive radio (CR), n-armed bandit problem, rate control, re- inforcement learning (RL)},
	author = {{\'A}lvaro Gonzalo and P{\'e}rez, Jes{\'u}s}
}
@conference {523,
	title = {MoCap multichannel time series representation and relevance analysis by kernel adaptive filtering and multikernel learning oriented to action recognition tasks},
	booktitle = {International Conference on Time Series and Forecasting (ITISE 2018)},
	year = {2018},
	month = {September},
	pages = {1316-1327},
	address = {Granada, Spain},
	isbn = {978-84-17293-57-4},
	author = {Pulgarin-Giraldo, Juan Diego and Alvarez-Meza, Andres Marino and Van Vaerenbergh, Steven and Santamar{\'\i}a, Ignacio and Castellanos, German}
}
@conference {ICSSC_2003,
	title = {The {MOBILITY} project - Providing {DVB-S} services on the move},
	booktitle = {The 21th AIAA International Communications Satellite Systems Conference (ICSSC 03)},
	year = {2003},
	month = {April},
	address = {Yokohama, Japan},
	author = {L{\"u}cke, Oliver and P{\'e}rez, Jes{\'u}s and J. A. Guerra and A. Rodr{\'\i}guez and V. Gennatos}
}
@conference {IST_2003,
	title = {The {MOBILITY} project},
	booktitle = {The 12th IST Summit on Mobile and Wireless Communications},
	year = {2003},
	month = {June},
	address = {Aveiro, Portugal},
	author = {E. Alonso and J. A. Guerra and P{\'e}rez, Jes{\'u}s and L{\"u}cke, Oliver}
}
@conference {IST_2001_b,
	title = {{MOBILITY} antenna for {Ku} band satellite terminal on board ships},
	booktitle = {IST Mobile Communications Summit},
	year = {2001},
	month = {September},
	address = {Barcelona, Spain},
	author = {J. Alonso and P{\'e}rez, Jes{\'u}s and J. A. Guerra and J. R. L{\'o}pez and A. M. Molina}
}
@conference {Icassp2009_BERBeamforming,
	title = {Minimum {BER} beamforming in the {RF} domain for {OFDM} transmissions and linear receivers},
	booktitle = {IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP 2009)},
	year = {2009},
	month = {April},
	address = {Taipei, Taiwan},
	author = {V{\'\i}a, Javier and Elvira, Victor and Santamar{\'\i}a, Ignacio and Eickhoff, R.}
}
@conference {Nnsp2001_svm,
	title = {Minimizing {BER} in {DFEs} with the Adatron Algorithm},
	booktitle = {Neural Networks for Signal Processing XI (NNSP 2001)},
	year = {2001},
	month = {September},
	address = {Falmouth, MA, USA},
	author = {Santamar{\'\i}a, Ignacio and Pantale{\'o}n, Carlos and Pr{\'\i}ncipe, Jos{\'e} C.}
}
@conference {ICT_MIMAX_2008,
	title = {{MIMAX} - Exploiting the maximum performance and minimum system costs of wireless {MIMO} systems},
	booktitle = {17th ICT Mobile and Wireless Summit},
	year = {2008},
	month = {June},
	address = {Stockholm, Sweden},
	author = {Eickhoff, R. and Ellinger, F. and Mayer, U. and Wickert, M. and Santamar{\'\i}a, Ignacio and Kraemer, R. and Gonz{\'a}lez, L. and Sperandio, P. and Theodosiou, T.}
}
@conference {ICTMobileSummit2009_Paper_ref_80_MIFA_pub,
	title = {MIFA: Modified IFA Radiating Element for Small Handheld Devices},
	booktitle = {ICT-MobileSummit 2009},
	year = {2009},
	month = {June},
	address = {Santander, Spain},
	author = {O. Gago and Gonz{\'a}lez, L. and Eickhoff, R. and Santamar{\'\i}a, Ignacio}
}
@conference {647,
	title = {Method of Moments Estimation for Energy Spectrum Sensing},
	booktitle = {31th European Signal Processing Conference (EUSIPCO)},
	year = {2023},
	month = {September},
	address = {Helsinki, Finland},
	abstract = {Energy detection is a well-known detection method for spectrum sensing in cognitive radio. Its low complexity and the fact that it does not require any prior knowledge of the primary signals, has made it a popular method. Despite its sim- plicity, energy detectors require knowing some parameters to set the decision threshold (according to a predefined criterion) and also to estimate its detection performance. Those parameters are the noise power, the primary signal power, and the duty cycle of the primary network. In this work, we propose a new sequential estimation method for jointly estimating those parameters from the energy measurements exclusively. Applying the Method of Moments, we derive the estimators as closed-form functions of the energy values. Their estimation performance is experimentally evaluated by means of over-the-air experiments with a testbed based on software-define-radio devices. The experiments also show the performance of the energy detectors with the estimated parameters.},
	author = {P{\'e}rez, Jes{\'u}s and Ib{\'a}{\~n}ez, Jes{\'u}s}
}
@conference {629,
	title = {A measure preserving mapping for structured Grassmannian constellations in SIMO channels},
	booktitle = {IEEE Global Communications Conference (GLOBECOM)},
	year = {2022},
	month = {Dec.},
	address = {Rio de Janeiro, Brazil},
	author = {Cuevas, Diego and Alvarez-Vizoso, Javier and Beltr{\'a}n, Carlos and Santamar{\'\i}a, Ignacio and Tucek, V{\'\i}t and Peters, Gunnar}
}
@conference {MONAMI_2010,
	title = {Maximum Sum-Rate Interference Alignment Schemes for the 3-user Deterministic {MIMO} Channel},
	booktitle = {2nd International ICST Conference on Mobile Networks and Management (MONAMI 2010)},
	year = {2010},
	month = {September},
	address = {Santander, Spain},
	author = {Gonz{\'a}lez, {\'O}scar and Santamar{\'\i}a, Ignacio}
}
@conference {Globecom_2010,
	title = {Maximum sum-rate interference alignment algorithms for MIMO channels},
	booktitle = {IEEE Global Communications Conference (GLOBECOM 2010)},
	year = {2010},
	month = {December},
	address = {Miami, FL, USA},
	author = {Santamar{\'\i}a, Ignacio and Gonz{\'a}lez, {\'O}scar and Heath Jr., Robert W. and Peters, S. W.}
}
@conference {ICASSP2011_ML_QICA,
	title = {Maximum Likelihood {ICA} of Quaternion Gaussian Vectors},
	booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011)},
	year = {2011},
	month = {May},
	address = {Prague, Czech Republic},
	author = {V{\'\i}a, Javier and Palomar, Daniel P. and Vielva, Luis and Santamar{\'\i}a, Ignacio}
}
@conference {Via_ML_IVA_MLSP2011,
	title = {A {Maximum Likelihood} Approach For {Independent Vector Analysis} of {Gaussian} Data Sets},
	booktitle = {IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2011)},
	year = {2011},
	month = {September},
	address = {Beijing, China},
	author = {V{\'\i}a, Javier and Anderson, M. and Li, X. L. and Adali, T.}
}
@conference {666,
	title = {Maximization of Minimum Rate in MIMO OFDM RIS-assisted Broadcast Channels},
	booktitle = {IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing},
	year = {2023},
	month = {Dec.},
	address = {Los Sue{\~n}os, Costa Rica},
	author = {Mohammad Soleymani and Santamar{\'\i}a, Ignacio and Sezgin, Aydin and Jorswieck, Eduard}
}
@conference {461,
	title = {Maximally Improper Interference in Underlay Cognitive Radio Networks},
	booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing},
	year = {2016},
	month = {March},
	address = {Shanghai, China},
	author = {Lameiro, Christian and Santamar{\'\i}a, Ignacio and Utschick, Wolfgang and Schreier, Peter J.}
}
@conference {Icassp03_equal_ent,
	title = {Matched {PDF}-based blind equalization},
	booktitle = {IEEE Int. Conf. on Acoust., Speech, and Signal Processing (ICASSP 2003)},
	year = {2003},
	month = {April},
	address = {Hong Kong, China},
	author = {L{\'a}zaro, Marcelino and Santamar{\'\i}a, Ignacio and Pantale{\'o}n, Carlos and Erdogmus, Deniz and Pr{\'\i}ncipe, Jos{\'e} C.}
}
@conference {ECCSC_10,
	title = {MAC and Baseband Hardware Platforms for RF-MIMO WLAN},
	booktitle = {5th European Conference on Circuits and Systems for Communications},
	year = {2010},
	month = {November},
	address = {Belgrade, Serbia},
	author = {Stamenkovic, Z. and Tittelbach-Helmrich, K. and Krstic, M. and Ib{\'a}{\~n}ez, Jes{\'u}s and Elvira, Victor and Santamar{\'\i}a, Ignacio}
}
@conference {510,
	title = {Locally Optimal Invariant Detector for Testing Equality of Two Power Spectral Densities},
	booktitle = { IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
	year = {2018},
	month = {April},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Calgary, Canada},
	author = {Ram{\'\i}rez, David and Romero, Daniel and V{\'\i}a, Javier and L{\'o}pez-Valcarce, Roberto and Santamar{\'\i}a, Ignacio}
}
@conference {C22_ICASSP_2012,
	title = {The Locally Most Powerful Test For Multiantenna Spectrum Sensing With Uncalibrated Receivers},
	booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012)},
	year = {2012},
	month = {March},
	address = {Kyoto, Japan},
	author = {Ram{\'\i}rez, David and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {309,
	title = {The Locally Most Powerful Invariant Test for Detecting a Rank-P Gaussian Signal in White Noise},
	booktitle = {7th IEEE Sensor Array and Multichannel Signal Processing Workshop},
	year = {2012},
	month = {June},
	address = {Hoboken, NJ, USA},
	abstract = {Spectrum sensing has become one of the main components of a cognitive transmitter. Conventional detectors suffer from noise power uncertainties and multiantenna detectors have been proposed to overcome this difficulty, and to improve the detection performance. However, most of the proposed multiantenna detectors are based on non-optimal techniques, such as the generalized likelihood ratio test (GLRT), or even heuristic approaches that are not based on first principles. In this work, we derive the locally most powerful invariant test (LMPIT), that is, the optimal invariant detector for close hypotheses, or equivalently, for a low signal-to-noise ratio (SNR). The traditional approach, based on the distributions of the maximal invariant statistic, is avoided thanks to Wijsman{\textquoteright}s theorem, which does not need these distributions. Our findings show that, in the low SNR regime, and in contrast to the GLRT, the additional spatial structure imposed by the signal model is irrelevant for optimal detection. Finally, we use Monte Carlo simulations to illustrate the good performance of the LMPIT.},
	author = {Ram{\'\i}rez, David and Iscar, Jorge and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and Louis L. Scharf}
}
@conference {COST_Bordeaux_94,
	title = {A Linearized Search to Refine Frequency Estimates},
	booktitle = {2nd Cost 229 Workshop on Adaptive Algorithms in Communications},
	year = {1992},
	month = {September},
	address = {Bordeaux, France},
	author = {Santamar{\'\i}a, Ignacio and Figueiras-Vidal, Anibal R.}
}
@conference {392,
	title = {Kernel-Based Identification of Hammerstein Systems for Nonlinear Acoustic Echo-Cancellation},
	booktitle = {2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
	year = {2014},
	month = {05/2014},
	abstract = {Traditional acoustic echo cancelers use a linear model to represent the echo path. Nevertheless, many consumer devices include loudspeakers and audio power amplifiers that may generate significant nonlinear distortions, creating the need for acoustic echo cancelers to produce a nonlinear filter response. To address this issue, we propose a nonlinear acoustic echo cancellation algorithm based on the framework of kernel methods. We model the echo path as a Hammerstein system, and we propose a resource-efficient strategy to identify the nonlinear and linear parts. While the basic algorithm is presented as an iterative batch method, we show that a simple extension allows it to be used in online scenarios as well. Results for both types of scenarios show that the algorithm produces good results on a system with a clipping nonlinearity and a realistic room impulse response.},
	keywords = {acoustic echo cancellation, Hammerstein systems, kernel methods, nonlinear distortions},
	isbn = {978-1-4799-2892-7},
	author = {Van Vaerenbergh, Steven and Azpicueta-Ruiz, Luis A.}
}
@conference {MLSP_2008_pub,
	title = {A kernel canonical correlation analysis algorithm for blind equalization of oversampled Wiener systems},
	booktitle = {IEEE International Workshop on Machine Learning for Signal Processing},
	year = {2008},
	month = {October},
	address = {Cancun, Mexico},
	author = {Van Vaerenbergh, Steven and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {362,
	title = {Kernel Adaptive Filtering: Which Technique to Choose in Practice},
	booktitle = {International Workshop on Advances in  Regularization, Optimization, Kernel Methods and Support Vector Machines: theory and applications (ROKS 2013)},
	year = {2013},
	month = {July},
	pages = {101--102},
	abstract = {The field of kernel adaptive filtering has produced a myriad of techniques throughout the past decade. While each algorithm provides some advantages over others in certain scenarios, it is often not clear which technique should be used on a practical problem, in which specific restrictions are in place. We propose a set of empirical performance measures and we provide a framework that can be used to decide which algorithm to use in practice. We include results on several benchmark data sets.},
	keywords = {kernel adaptive filtering},
	isbn = {978-94-6018-700-1},
	author = {Van Vaerenbergh, Steven and Santamar{\'\i}a, Ignacio}
}
@conference {nsip97,
	title = {Joint Segmentation and {AR} Modeling of Quasistationary Signals Using the {EM} Algorithm},
	booktitle = {IEEE Workshop on Nonlinear Signal and Image Processing},
	year = {1997},
	month = {September},
	address = {Mackinac Island, Michigan},
	author = {Santamar{\'\i}a, Ignacio and Pantale{\'o}n, Carlos and Figueiras-Vidal, Anibal R.}
}
@conference {ICASSP2011_JBSS_ID,
	title = {Joint Blind Source Separation from Second-Order Statistics: Necessary and Sufficient Identifiability Conditions},
	booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011)},
	year = {2011},
	month = {May},
	address = {Prague, Czech Republic},
	author = {V{\'\i}a, Javier and Anderson, M. and Li, X. L. and Adali, T.}
}
@conference {SAM2004,
	title = {An {IRWLS} procedure for robust beamforming with sidelobe control},
	booktitle = {Third IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2004)},
	year = {2004},
	month = {July},
	address = {Barcelona, Spain},
	author = {Gaudes, C. C. and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {419,
	title = {Interference-Temperature Limit for Cognitive Radio Networks with MIMO Primary Users},
	booktitle = {Asilomar Conference on Signals, Systems, and Computers},
	year = {2014},
	month = {November},
	address = {Pacific Grove, CA, USA},
	author = {Lameiro, Christian and Utschick, Wolfgang and Santamar{\'\i}a, Ignacio}
}
@conference {391,
	title = {Interference Shaping Constraints for Underlay MIMO Interference Channels},
	booktitle = {International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
	year = {2014},
	month = {May},
	address = {Florence, Italy},
	author = {Lameiro, Christian and Santamar{\'\i}a, Ignacio and Utschick, Wolfgang}
}
@conference {643,
	title = {Interference Leakage Minimization in RIS-assisted MIMO Interference Channels},
	booktitle = {IEEE International Conference on Acoustics Speech and Signal Processing},
	year = {2023},
	month = {June},
	address = {Rhodes, Greece},
	author = {Santamar{\'\i}a, Ignacio and Mohammad Soleymani and Jorswieck, Eduard and Mohammad Soleymani}
}
@conference {Icassp12_IA_pub,
	title = {Interference Leakage Minimization for Convolutive {MIMO} Interference Channels},
	booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012)},
	year = {2012},
	month = {March},
	address = {Kyoto, Japan},
	author = {Gonz{\'a}lez, {\'O}scar and Lameiro, Christian and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and Heath Jr., Robert W.}
}
@conference {ICASSP_2011_IA_HC,
	title = {Interference Alignment in Single-Beam {MIMO} Networks via Homotopy Continuation},
	booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011)},
	year = {2011},
	month = {May},
	address = {Prague, Czech Republic},
	abstract = {In this paper we consider the application of a homotopy-continuation based method for finding interference alignment (IA) solutions for the deterministic K-user multiple-input multiple-output (MIMO) channel, when all users wish to send one stream of data. Homotopy continuation is based on the idea of deforming a start system, whose solution can easily be found, to reach the target system that we want to solve. For the IA problem we show that a good initial system is obtained by considering a rank-one approximation of the original MIMO interference channels. Specifically, as long as the original system is feasible, a rank-one approximation of the MIMO channels allow us to find a closed-form interference-free solution. The proposed algorithm is shown to have a lower complexity than previous methods with comparable sum-rate performance. Furthermore, it is also shown that the trivial system (rank-one MIMO channels) and target system (full-rank MIMO channels) have exactly the same number of solutions. Exploiting this equivalence, an efficient method to enumerate all the IA solutions that exist in a single-beam MIMO network is proposed.},
	author = {Gonz{\'a}lez, {\'O}scar and Santamar{\'\i}a, Ignacio}
}
@conference {349,
	title = {An Interference Alignment Algorithm for Structured Channels},
	booktitle = {IEEE 14th Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2013)},
	year = {2013},
	month = {June},
	address = {Darmstadt, Germany},
	author = {Lameiro, Christian and Gonz{\'a}lez, {\'O}scar and Santamar{\'\i}a, Ignacio}
}
@conference {SAM2010_QICA,
	title = {Independent Component Analysis of Quaternion Gaussian Vectors},
	booktitle = {6th IEEE Sensor Array and Multichannel Signal Processing Workshop},
	year = {2010},
	month = {October},
	address = {Israel},
	author = {V{\'\i}a, Javier and Vielva, Luis and Santamar{\'\i}a, Ignacio and Palomar, Daniel P.}
}
@conference {521,
	title = {Improving Graph Convolutional Networks with Non-Parametric Activation Functions},
	booktitle = {26th European Signal Processing Conference (EUSIPCO 2018)},
	year = {2018},
	month = {September},
	publisher = {EURASIP},
	organization = {EURASIP},
	address = {Rome, Italy},
	abstract = {Graph neural networks (GNNs) are a class of neural networks that allow to efficiently perform inference on data that is associated to a graph structure, such as, e.g., citation networks or knowledge graphs. While several variants of GNNs have been proposed, they only consider simple nonlinear activation functions in their layers, such as rectifiers or squashing functions. In this paper, we investigate the use of graph convolutional networks (GCNs) when combined with more complex activation functions, able to adapt from the training data. More specifically, we extend the recently proposed kernel activation function, a non-parametric model which can be implemented easily, can be regularized with standard l?p-norms techniques, and is smooth over its entire domain. Our experimental evaluation shows that the proposed architecture can significantly improve over its baseline, while similar improvements cannot be obtained by simply increasing the depth or size of the original GCN.},
	author = {Scardapane, Simone and Van Vaerenbergh, Steven and Comminiello, Danilo and Uncini, Aurelio}
}
@conference {imtc97,
	title = {Improved Procedures for Estimating Amplitudes and Phases of Harmonics with Application to Vibration Analysis},
	booktitle = {IEEE Instrumentation and Measurement Technology Conference},
	year = {1997},
	month = {May},
	address = {Ottawa, Canada},
	author = {Gonz{\'a}lez, R. and Santamar{\'\i}a, Ignacio and Pantale{\'o}n, Carlos and Ib{\'a}{\~n}ez, Jes{\'u}s and G{\'o}mez, E.}
}
@conference {MLSP2010_QuaternionMeasures,
	title = {Improperness Measures for Quaternion Random Vectors},
	booktitle = {IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2010)},
	year = {2010},
	month = {August},
	address = {Kittil{\"a}, Finland},
	author = {V{\'\i}a, Javier and Ram{\'\i}rez, David and Santamar{\'\i}a, Ignacio and Vielva, Luis}
}
@conference {516,
	title = {Improper Signaling for OFDM Underlay Cognitive Radio Systems},
	booktitle = {IEEE Statistical Signal Processing Workshop (SSP)},
	year = {2018},
	month = {June},
	address = {Freiburg, Germany},
	abstract = {Improper signaling, where real and imaginary parts of the transmit
signal are correlated and/or have unequal power, has received a lot
of attention lately because it has been shown to increase achievable
rates in many interference-limited communication systems. In this paper, we study whether improper signaling can also benefit an orthogonal frequency-division multiplexing (OFDM) underlay cognitive radio (UCR) system. We assume that the primary user (PU) transmits proper signals, while the secondary user (SU) is allowed to employ improper signaling. We consider two different rate constraints for the rate of the PU: i) the total rate of the PU, and ii) the rate of the PU in each subband. We propose an algorithm to implement improper signaling for each constraint. In both cases, we show that the benefits of improper signaling are relatively small and decrease rapidly with increasing number of subbands. This rather negative result shows that the use of improper signaling in interference scenarios needs to be justified on a case-by-case basis.},
	author = {Mohammad Soleymani and Lameiro, Christian and Schreier, Peter J. and Santamar{\'\i}a, Ignacio}
}
@conference {539,
	title = {Improper Gaussian Signaling for the Two-user Broadcast Channel Treating Interference as Noise},
	booktitle = {IEEE Int. Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
	year = {2019},
	month = {May},
	address = {Brighton, UK},
	abstract = {Improper Gaussian signaling (IGS) has been shown to enlarge the rate region achievable by conventional proper Gaussian signaling (PGS) schemes in several interference-limited multiuser networks. In this work, we consider the 2-user broadcast channel (BC) when treating interference as noise {\textquotedblleft}TIN{\textquotedblright} at every receiver. For this scenario, we derive a closed-formcharacterization of the rate region boundary with IGS. ThePareto-optimal points are achieved when at least one of the users employs maximally improper (rectilinear) signals. Differently from other interference-limited networks, our results show that IGS always outperforms PGS for the 2-user BC with TIN. Furthermore, IGS also enlarges the PGS rate region with time-sharing for this scenario.},
	author = {Lameiro, Christian and Santamar{\'\i}a, Ignacio and Schreier, Peter J.}
}
@conference {ReCoSoC2011_MIMAX_WLAN_Modem,
	title = {Implementation, integration, and verification of MIMAX WLAN modem},
	booktitle = {6th International Workshop on Reconfigurable Communication-centric Systems-on-Chip (ReCoSoC 2011)},
	year = {2011},
	month = {June},
	address = {Montpellier, France},
	author = {Stamenkovic, Z. and Tittelbach-Helmrich, K. and Wickert, M. and Ib{\'a}{\~n}ez, Jes{\'u}s and Ruiz, S. and Dimosthenous, G.}
}
@conference {661,
	title = {Identifiability in Multi-Channel Factor Analysis},
	booktitle = {Asilomar Conference on Signals, Systems, and Computers},
	year = {2023},
	month = {November},
	address = {Pacific Grove, CA, USA},
	author = {Stanton, Gray and Ram{\'\i}rez, David and Santamar{\'\i}a, Ignacio and Louis L. Scharf and Wang, Haonan}
}
@conference {399,
	title = {Homotopy Continuation for Vector Space Interference Alignment in MIMO X Networks},
	booktitle = {2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
	year = {2014},
	month = {May},
	pages = {6232--6236},
	author = {Gonz{\'a}lez, {\'O}scar and Fanjul, Jacobo and Santamar{\'\i}a, Ignacio}
}
@conference {311,
	title = {GLRT For Testing Separability Of A Complex-Valued Mixture Based On The Strong Uncorrelating Transform},
	booktitle = {2012 IEEE International Workshop on Machine Learning for Signal Processing},
	year = {2012},
	month = {September},
	address = {Santander, Spain},
	abstract = {The Strong Uncorrelating Transform (SUT) allows blind separation of a mixture of complex independent sources if and only if all sources have distinct circularity coefficients. In practice, the circularity coefficients need to be estimated from observed data. We propose a generalized likelihood ratio test (GLRT) for separability of a complex mixture using the SUT, based on estimated circularity coefficients. For distinct circularity coefficients (separable case), the maximum likelihood (ML) estimates, required for the GLRT, are straightforward. However, for circularity coefficients with multiplicity larger than one  (non-separable case), the ML estimates are much more difficult to find. Numerical simulations show the good performance of the proposed detector.},
	author = {Ram{\'\i}rez, David and Schreier, Peter J. and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {491,
	title = {A GLRT approach for detecting correlated signals in white noise in two MIMO channels},
	booktitle = {European Signal Processing Conference (EUSIPCO)},
	year = {2017},
	month = {August},
	address = {Kos, Greece},
	author = {Santamar{\'\i}a, Ignacio and V{\'\i}a, Javier and Louis L. Scharf and Wang, Yuan}
}
@conference {COST_Liu_94,
	title = {A Genetic Approach to Sparse Deconvolution},
	booktitle = {4th Cost 229 Workshop on Adaptive Methods and Emergent Techniques for Signal proc. and Comm.},
	year = {1994},
	month = {April},
	address = {Ljubljana, Slovenia},
	author = {A. Malanda and Santamar{\'\i}a, Ignacio and Figueiras-Vidal, Anibal R.}
}
@conference {ICASSP_2008,
	title = {A generalization of the magnitude squared coherence spectrum for more than two signals: definition, properties and estimation},
	booktitle = {IEEE Int. Conf. on Acoust., Speech, and Signal Processing (ICASSP 2008)},
	year = {2008},
	month = {April},
	address = {Las Vegas, USA},
	author = {Ram{\'\i}rez, David and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {278,
	title = {A general test to check the feasibility of linear interference alignment},
	booktitle = {IEEE International Symposium on Information Theory (ISIT 2012), Cambridge, MA, USA},
	year = {2012},
	month = {July, 2012},
	keywords = {feasibility, IA},
	author = {Gonz{\'a}lez, {\'O}scar and Santamar{\'\i}a, Ignacio and Beltr{\'a}n, Carlos}
}
@conference {ICC2010_AnalogBeam,
	title = {A general {Pre-FFT} criterion for {MIMO-OFDM} beamforming},
	booktitle = {IEEE International Conference on Communications (ICC 2010)},
	year = {2010},
	month = {May},
	address = {Cape Town, South Africa},
	author = {V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and Elvira, Victor and Eickhoff, R.}
}
@conference {ISWCS_2006_b,
	title = {A flexible testbed for the rapid prototyping of {MIMO} baseband modules},
	booktitle = {3rd International Symposium on Wireless Communication Systems (ISWCS 2006)},
	year = {2006},
	month = {September},
	address = {Valencia, Spain},
	author = {Ram{\'\i}rez, David and Santamar{\'\i}a, Ignacio and P{\'e}rez, Jes{\'u}s and V{\'\i}a, Javier and Taz{\'o}n, A. and Garcia-Naya, J. A. and Fern{\'a}ndez-Caram{\'e}s, T. M. and Gonz{\'a}lez L{\'o}pez, M. and H{\'e}ctor J. P{\'e}rez Iglesias and Castedo, Luis}
}
@conference {536,
	title = {Flexible Duplexing for Maximum Downlink Rate in Multi-tier MIMO Networks},
	booktitle = {26th Telecommunications Forum TELFOR 2018},
	year = {2018},
	month = {November},
	address = {Belgrade, Serbia},
	abstract = {In this paper, we propose an algorithm to maximize downlink rate performance in the context of multiple-input multiple-output (MIMO) Heterogeneous Networks (HetNets). Specifically, we evaluate the benefits of flexible duplexing, a promising strategy that consists in combining uplink and downlink cells within the same channel use. In order to handle intercell interference, we rely on the interference alignment (IA) technique, taking into account the impact of the channel estimation errors on the inter-cell interference leakage. Determining the best uplink/downlink configuration is a combinatorial problem, and therefore we consider several approaches to reduce the computational demands of the problem. First, we use a statistical characterization for the average rates achieved by IA in order to avoid the calculation of alignment solutions for all possible settings in the network. Additionally, we propose two hierarchical switching (HS) strategies so that only a subset among the total number of combinations is explored. As a performance baseline, we include in the comparison the conventional time division duplex (TDD) approach and the well-known minimum mean square error (MMSE) decoder. The obtained results show that downlink rates achieved by implementing flexible duplexing
and applying inter-cell IA significantly outperform conventional TDD transmissions. Finally, the proposed hierarchical schemes are shown to obtain almost the same rates as exhaustive search with much lower computational cost.},
	author = {Fanjul, Jacobo and Santamar{\'\i}a, Ignacio}
}
@conference {vanvaerenbergh2010_fbkrls,
	title = {Fixed-Budget Kernel Recursive Least-Squares},
	booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2010)},
	year = {2010},
	month = {March},
	address = {Dallas, USA},
	keywords = {kernel adaptive filtering, KRLS},
	author = {Van Vaerenbergh, Steven and Santamar{\'\i}a, Ignacio and Liu, Weifeng and Pr{\'\i}ncipe, Jos{\'e} C.}
}
@conference {347,
	title = {Fitting Sparse Gaussian Function Mixtures on Power Spectra},
	booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)},
	year = {2013},
	month = {May},
	address = {Vancouver, Canada},
	author = {Luis Weruaga and V{\'\i}a, Javier}
}
@conference {359,
	title = {Finding the Number of Feasible Solutions for Linear Interference Alignment Problems},
	booktitle = {2013 IEEE International Symposium on Information Theory},
	year = {2013},
	month = {July},
	pages = {384--388},
	address = {Istanbul, Turkey},
	abstract = {In this paper, we study how many different solutions exist for a feasible interference alignment (IA) problem. We focus on linear IA schemes without symbol extensions for the K-user multiple-input multiple-output (MIMO) interference channel. When the IA problem is feasible and the number of variables matches the number of equations in the polynomial system, the number of solutions is known to be finite. Unfortunately, the exact number of solutions is only known for a few particular cases, mainly single-beam MIMO networks. In this paper, we prove that the number of IA solutions is given by an integral formula that can be numerically approximated using Monte Carlo integration methods. More precisely, the number of solutions is the scaled average over a subset of the solution variety (formed by all triplets of channels, precoders and decoders satisfying the IA polynomial equations) of the determinant of certain Hermitian matrix related to the geometry of the problem. Our results can be applied to arbitrary interference MIMO networks, with any number of users, antennas and streams per user.},
	isbn = {978-1-4799-0446-4},
	author = {Gonz{\'a}lez, {\'O}scar and Santamar{\'\i}a, Ignacio and Beltr{\'a}n, Carlos}
}
@conference {618,
	title = {A fast algorithm for designing Grassmannian constellations},
	booktitle = {25th ITG Workshop on Smart Antennas},
	year = {2021},
	month = {November},
	address = {EURECOM, French Riviera, France},
	author = {Cuevas, Diego and Beltr{\'a}n, Carlos and Santamar{\'\i}a, Ignacio and Tucek, V{\'\i}t and Peters, Gunnar}
}
@conference {Icassp02_ent,
	title = {A Fast Algorithm for Adaptive Blind Equalization usind order-a {Renyi Entropy}},
	booktitle = {IEEE Int. Conf. on Acoust., Speech, and Signal Processing (ICASSP 2002)},
	year = {2002},
	month = {May},
	address = {Orlando, FL, USA},
	author = {Santamar{\'\i}a, Ignacio and Pantale{\'o}n, Carlos and Vielva, Luis and Pr{\'\i}ncipe, Jos{\'e} C.}
}
@conference {WSA_2011,
	title = {Experimental Validation of Interference Alignment Techniques using a Multiuser {MIMO} Testbed},
	booktitle = {International ITG Workshop on Smart Antennas (WSA 2011)},
	year = {2011},
	month = {February},
	address = {Aachen, Germany},
	author = {Gonz{\'a}lez, {\'O}scar and Ram{\'\i}rez, David and Santamar{\'\i}a, Ignacio and Garc{\'\i}a-Naya, J. A. and Castedo, Luis}
}
@conference {496,
	title = {Experimental Evaluation of Non-Coherent MIMO Grassmannian Signaling Schemes},
	booktitle = {16th International Conference on Ad Hoc Networks and Wireless (AdHoc-Now 2017)},
	year = {2017},
	month = {September},
	address = {Messina, Italy},
	abstract = {In this paper, we present an over-the-air (OTA) performance
analysis of Grassmannian signaling strategies in an orthogonal frequencydivision
multiplexing (OFDM) single-user multiple-input multiple-output
(SU-MIMO) scenario. Specically, we compare the Grassmannian signaling
technique to the dierential Alamouti scheme and a novel space-time
non-coherent scheme recently proposed in the context of 5G. As a performance
benchmark we include in the comparison the coherent Alamouti
scheme. We study the practical impairments associated to frequency
synchronization mismatches (frequency osets), as well as the eects of
time-varying channels for dierent spectral eciencies. The experimental
results show that non-coherent techniques are more robust to the
aforementioned impairments than the coherent Alamouti approach, while
Grassmannian methods are close to the dierential Alamouti scheme with
2 transmit antennas.},
	keywords = {Grassmannian signaling, MIMO testbed, Non-coherent communications, OFDM, Over-the-air (OTA) experiments},
	author = {Fanjul, Jacobo and Santamar{\'\i}a, Ignacio and Ib{\'a}{\~n}ez, Jes{\'u}s and Loucera, Carlos}
}
@conference {295,
	title = {Experimental Evaluation of Multiantenna Spectrum Sensing Detectors using a Cognitive Radio Testbed},
	booktitle = {International Symposium on Signals, Systems and Electronics (ISSSE 2012)},
	year = {2012},
	month = {October},
	address = {Potsdam, Germany},
	author = {Manco-V{\'a}squez, Julio and Guti{\'e}rrez, Jes{\'u}s and P{\'e}rez, Jes{\'u}s and Ib{\'a}{\~n}ez, Jes{\'u}s and Santamar{\'\i}a, Ignacio}
}
@conference {Eusipco2011_IA,
	title = {Experimental Evaluation of Interference Alignment Under Imperfect Channel State Information},
	booktitle = {19th European Signal Processing Conference (EUSIPCO 2011)},
	year = {2011},
	month = {August},
	address = {Barcelona, Spain},
	author = {Garc{\'\i}a-Naya, J. A. and Castedo, Luis and Gonz{\'a}lez, {\'O}scar and Ram{\'\i}rez, David and Santamar{\'\i}a, Ignacio}
}
@conference {445,
	title = {An Experimental Evaluation of Broadband Spatial IA for Uncoordinated MIMO-OFDM Systems},
	booktitle = {IEEE International Conference on Digital Signal Processing (DSP)},
	year = {2015},
	month = {July},
	pages = {570--574},
	address = {Singapore},
	author = {Fanjul, Jacobo and Lameiro, Christian and Santamar{\'\i}a, Ignacio and Garc{\'\i}a-Naya, J. A. and Castedo, Luis}
}
@conference {FutureNetworkMobileSummit_2010,
	title = {Experimental evaluation of an {RF-MIMO} transceiver for 802.11a {WLAN}},
	booktitle = {Future Network and MobileSummit 2010},
	year = {2010},
	month = {June},
	address = {Florence, Italy},
	author = {Gonz{\'a}lez, {\'O}scar and Guti{\'e}rrez, Jes{\'u}s and Ib{\'a}{\~n}ez, Jes{\'u}s and Vielva, Luis and Eickhoff, R.}
}
@conference {404,
	title = {Experimental Evaluation of a Cooperative Kernel-Based Approach for Robust Spectrum Sensing},
	booktitle = {8th IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)},
	year = {2014},
	month = {June},
	address = {A Coru{\~n}a, Spain},
	isbn = {978-1-4799-1479-1},
	author = {Manco-V{\'a}squez, Julio and Van Vaerenbergh, Steven and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {SPAWC2007_1,
	title = {Exact closed-form expressions for the sum capacity and individual users rates in broadcast ergodic Rayleigh fading channels},
	booktitle = {Eighth IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2007)},
	year = {2007},
	month = {June},
	address = {Helsinki, Finland},
	author = {P{\'e}rez, Jes{\'u}s and Ib{\'a}{\~n}ez, Jes{\'u}s and Santamar{\'\i}a, Ignacio}
}
@conference {ICA04,
	title = {On the estimation of the mixing matrix for underdetermined blind source separation in an arbitrary number of dimensions},
	booktitle = {5th International Conference on Independent Component Analysis and Blind Signal Separation (ICA 2004)},
	year = {2004},
	month = {September},
	address = {Granada, Spain},
	author = {Vielva, Luis and Santamar{\'\i}a, Ignacio and Ib{\'a}{\~n}ez, Jes{\'u}s and Erdogmus, Deniz and Pr{\'\i}ncipe, Jos{\'e} C.}
}
@conference {Eusipco02_bss,
	title = {Estimation of the mixing matrix for underdetermined blind source separation using spectral estimation techniques},
	booktitle = {XI European Signal Processing Conference (Eusipco 2002)},
	year = {2002},
	month = {September},
	address = {Toulouse, France},
	author = {Vielva, Luis and Santamar{\'\i}a, Ignacio and Pantale{\'o}n, Carlos and Ib{\'a}{\~n}ez, Jes{\'u}s and Erdogmus, Deniz and Pr{\'\i}ncipe, Jos{\'e} C.}
}
@conference {Icassp2007_CCA_MSC,
	title = {Estimation of the magnitude squared coherence spectrum based on reduced-rank canonical coordinates},
	booktitle = {IEEE Int. Conf. on Acoust., Speech, and Signal Processing (ICASSP 2007)},
	year = {2007},
	month = {April},
	address = {Hawaii, USA},
	author = {Santamar{\'\i}a, Ignacio and V{\'\i}a, Javier}
}
@conference {314,
	title = {Estimation of the Forgetting Factor in Kernel Recursive Least Squares},
	booktitle = {2012 IEEE International Workshop On Machine Learning For Signal Processing (MLSP)},
	year = {2012},
	month = {September},
	abstract = {In a recent work we proposed a kernel recursive least-squares tracker (KRLS-T) algorithm that is capable of tracking in non-stationary environments, thanks to a forgetting mechanism built on a Bayesian framework. In order to guarantee optimal performance its parameters need to be determined, specifically its kernel parameters, regularization and, most importantly in non-stationary environments, its forgetting factor. This is a common difficulty in adaptive filtering techniques and in signal processing algorithms in general. In this paper we demonstrate the equivalence between KRLS-T{\textquoteright}s recursive tracking solution and Gaussian process (GP) regression with a specific class of spatio-temporal covariance. This result allows to use standard hyperparameter estimation techniques from the Gaussian process framework to determine the parameters of the KRLS-T algorithm. Most notably, it allows to estimate the optimal forgetting factor in a principled manner. We include results on different benchmark data sets that offer interesting new insights.},
	keywords = {kernel adaptive filtering},
	author = {Van Vaerenbergh, Steven and Santamar{\'\i}a, Ignacio and L{\'a}zaro-Gredilla, Miguel}
}
@conference {Icassp02_caos,
	title = {Estimation of a Certain Class of Chaotic Signals: an {EM}-Based Approach},
	booktitle = {IEEE Int. Conf. on Acoust., Speech, and Signal Processing (ICASSP 2002)},
	year = {2002},
	month = {May},
	address = {Orlando, FL, USA},
	author = {Pantale{\'o}n, Carlos and Vielva, Luis and Luengo, David and Santamar{\'\i}a, Ignacio}
}
@conference {469,
	title = {Estimating the mean manifold of a deformable object from noisy observations},
	booktitle = {IEEE Image Video and Multidimensional Signal Processing Workshop (IVMSP) },
	year = {2016},
	month = {July},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Bordeaux,France},
	abstract = {Assume we have a set of noisy observations (for example, images) of different objects, each undergoing a different
geometric deformation, yet all the deformations belong to the same family. As a result of the action of these deformations,
the set of different observations on each object is generally a manifold in the ambient space of observations. It has been shown, [1], that in the absence of noise, in those cases where the set
of deformations admits a finite-dimensional representation, the universal manifold embedding (UME) provides a mapping from the space of observations to a low dimensional linear space. The
manifold corresponding to each object is mapped to a distinct linear subspace of Euclidean space, and the dimension of the
subspace is the same as that of the manifold. In the presence of noise, different observations are mapped to different subspaces. In this paper we derive a method for {\textquotedblleft}averaging{\textquotedblright} the different subspaces, obtained from different observations made on the same object, in order to estimate the mean representation of the object manifold. The mean manifold representation is then employed to minimize the effects of noise in matched manifold detectors and to improve the separability of data sets in the context of object detection and classification.},
	author = {Yavo, Z and Francos, Joseph and Santamar{\'\i}a, Ignacio and Louis L. Scharf}
}
@conference {Mobilight2010_EPC,
	title = {Equal-Phase beamforming architecture for {RF-MIMO} antenna systems},
	booktitle = {2nd International ICST Conference on Mobile Lightweight Wireless Systems (Mobilight 2010)},
	year = {2010},
	month = {May},
	address = {Barcelona, Spain},
	author = {Gholam, Fouad and V{\'\i}a, Javier and Naz{\'a}bal, Alfredo and Santamar{\'\i}a, Ignacio}
}
@conference {Mobilight2010_EGC,
	title = {Equal Gain {MIMO} beamforming in the {RF} domain for {OFDM-WLAN} systems},
	booktitle = {2nd International ICST Conference on Mobile Lightweight Wireless Systems (Mobilight 2010)},
	year = {2010},
	month = {May},
	address = {Barcelona, Spain},
	author = {{\'A}lvaro Gonzalo and Santamar{\'\i}a, Ignacio and V{\'\i}a, Javier and Gholam, Fouad and Eickhoff, R.}
}
@conference {Eusipco2009_entropy,
	title = {Entropy and Kullback-Leibler divergence estimation based on Szeg{\"o}{\textasciiacute}s Theorem},
	booktitle = {17th European Signal Processing Conference (EUSIPCO 2009)},
	year = {2009},
	month = {August},
	address = {Glasgow, Scotland},
	author = {Ram{\'\i}rez, David and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and Crespo, P.}
}
@conference {648,
	title = {Energy-efficient Rate Splitting for MIMO STAR-RIS-assisted Broadcast Channels with I/Q Imbalance},
	booktitle = {31th European Signal Processing Conference (EUSIPCO)},
	year = {2023},
	month = {September},
	address = {Helsinki, Finland},
	author = {Mohammad Soleymani and Santamar{\'\i}a, Ignacio and Jorswieck, Eduard}
}
@conference {554,
	title = {Energy-Efficient Improper Signaling for K-user Interference Channels},
	booktitle = {European Signal Processing Conference (EUSIPCO)},
	year = {2019},
	month = {September},
	abstract = {This paper investigates the energy efficiency (EE) of improper Gaussian signaling (IGS) in a K-user interference channel (IC). IGS allows unequal variances and/or correlation between the real and imaginary parts, and it has recently been shown to be advantageous in various interference-limited scenarios. In this paper, we propose an energy-efficient IGS design for the K-user IC, which is based on a separate optimization of the powers and complementary variances of the users. We compare the EE region achieved by the proposed scheme with that achieved by conventional proper signaling and show that IGS can significantly improve the EE region.},
	author = {Mohammad Soleymani and Lameiro, Christian and Santamar{\'\i}a, Ignacio and Schreier, Peter J.}
}
@conference {541,
	title = {Energy-Efficient Design for Underlay Cognitive Radio using Improper Signaling},
	booktitle = {IEEE Int. Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
	year = {2019},
	month = {May},
	address = {Brighton, UK},
	abstract = {Improper Gaussian signaling (IGS) has been used as an effective interference management tool in interference limited systems. Improper Gaussian signals are correlated with their complex conjugates. In this paper, we investigate theoptimality of IGS from an energy efficiency (EE) perspective. First, we obtain closed form optimality conditions for
IGS.We then leverage these conditions to devise a bisection method that finds the optimal transmission parameters. Our results show that IGS can improve the EE of an underlay cognitive radio system.},
	author = {Mohammad Soleymani and Lameiro, Christian and Schreier, Peter J. and Santamar{\'\i}a, Ignacio}
}
@conference {566,
	title = {Efficient SER Estimation for MIMO Detectors via Importance Sampling Schemes},
	booktitle = {Asilomar Conference on Signals, Systems, and Computer},
	year = {2019},
	month = {November},
	pages = {712-716},
	address = {Pacific Grove, CA, USA},
	abstract = {In this paper we propose two importance sampling methods for the efficient symbol error rate (SER) estimation of maximum likelihood (ML) multiple-input multiple-output (MIMO) detectors. Conditioned to a given transmitted symbol, computing the SER requires the evaluation of an integral outside a given polytope in a high-dimensional space, for which a closed-form solution does not exist. Therefore, Monte Carlo (MC) simulation is typically used to estimate the SER, although a naive or raw MC implementation can be very inefficient at high signal-to-noise-ratios or for systems with stringent SER requirements. A reduced variance estimator is provided by the Truncated Hypersphere Importance Sampling (THIS) method, which samples from a proposal density that excludes the largest hypersphere circumscribed within the Voronoi region of the transmitted vector. A much more efficient estimator is provided by the existing ALOE (which stands for {\textquoteleft}{\textquoteleft}At Least One rare Event{\textquoteright}{\textquoteright}) method, which samples conditionally on an error taking place. The paper describes in detail these two IS methods, discussing their advantages and limitations, and comparing their performances.},
	author = {Elvira, Victor and Santamar{\'\i}a, Ignacio}
}
@conference {Eusipco2000_chaos,
	title = {An Efficient Method for Chaotic Signal Parameter Estimation},
	booktitle = {European Signal Processing Conference (EUSIPCO 2000)},
	year = {2000},
	month = {September},
	address = {Tampere, Finland},
	author = {Pantale{\'o}n, Carlos and Luengo, David and Santamar{\'\i}a, Ignacio}
}
@conference {577,
	title = {Efficient Iteratively Reweighted LASSO Algorithm for Cross-Products Penalized Sparse Solutions},
	booktitle = {European Signal Processing Conference (EUSIPCO 2020)},
	year = {2020},
	month = {August},
	address = {Amsterdamd, The Netherlands},
	author = {Luengo, David and V{\'\i}a, Javier and Tom Trigano}
}
@conference {360,
	title = {Dynamic rate adaptation in cognitive radio considering time-dependent channel access models},
	booktitle = {8th International Conference on Cognitive Radio Oriented Wireless Networks (CROWNCOM)},
	year = {2013},
	month = {July},
	address = {Washington DC, USA},
	abstract = {Recent studies showed that, in practical situations,
the primary user (PU) access to the channel is better modeled
as a time dependent random process. Taking this into account,
we address the optimal rate adaptation problem of a cognitive
radio (CR) link. A secondary user (SU) link detects an idle
channel and starts the transmission with the goal of transmitting
a given amount of data packets within a given time. During the
transmission, and taking into account frame retransmission, the
transmitter dynamically adapts the frames rate, from a finite
number of available rates. If the PU accesses the channel, the SU
immediately stops the transmission. The problem is formulated
as an episodic Markov decision process (MDP). We show that
selecting the best stationary policy (using the same rate for the
whole transmission) can perform close to optimal.},
	isbn = {978-1-936968-83-1},
	author = {{\'A}lvaro Gonzalo and P{\'e}rez, Jes{\'u}s}
}
@conference {Eusipco2009_AnalogComb_Diversity,
	title = {Diversity Techniques for RF-Beamforming in MIMO-OFDM Systems: Design and Performance Evaluation},
	booktitle = {17th European Signal Processing Conference (EUSIPCO 2009)},
	year = {2009},
	month = {August},
	address = {Glasgow, United Kingdom},
	author = {Elvira, Victor and V{\'\i}a, Javier}
}
@conference {276,
	title = {A Distributed Algorithm for Two-Way Multiple-Relay Networks},
	booktitle = {IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2012)},
	year = {2012},
	month = {June},
	address = {Hoboken, NJ, USA},
	author = {Lameiro, Christian and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {SAM08_ MIMO_Order_CCA,
	title = {Deterministic {MIMO} Channel Order Estimation Based On Canonical Correlation Analysis},
	booktitle = {Fifth IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2008)},
	year = {2008},
	month = {July},
	address = {Darmstadt, Germany},
	author = {Arroyo, Marta and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {eusipco2005_matchedfilter_umut,
	title = {Detection of nonlinearly distorted signals using mutual information},
	booktitle = {13th European Signal Processing Conference (EUSIPCO 2005)},
	year = {2005},
	month = {September},
	address = {Antalya, Turkey},
	author = {Ozertem, Umut and Erdogmus, Deniz and Santamar{\'\i}a, Ignacio}
}
@conference {326,
	title = {Detection of Gaussian Signal in Unknown Time-Varying Channels},
	booktitle = {IEEE Statistical Signal Processing Workshop (SSP 2012)},
	year = {2012},
	month = {August},
	address = {Ann Arbor, USA},
	author = {Romero, Daniel and V{\'\i}a, Javier and L{\'o}pez-Valcarce, Roberto and Santamar{\'\i}a, Ignacio}
}
@conference {338,
	title = {Degrees-of-Freedom for the 4-User SISO Interference Channel with Improper Signaling},
	booktitle = {IEEE International Conference on Communications (ICC)},
	year = {2013},
	month = {June},
	address = {Budapest, Hungary},
	author = {Lameiro, Christian and Santamar{\'\i}a, Ignacio}
}
@conference {517,
	title = {Decision Support System for Plan and Crop Treatment and Protection based on Wireless Sensor Networks},
	booktitle = {41st International Spring Seminar on Electronics Technology (ISSE)},
	year = {2018},
	month = {May},
	address = {Zlatibor, Serbia},
	abstract = {A decision support system (DSS) able to control the course of agricultural production and protect healthy and treat diseased plants and crops taking into account the temporal and spatial variability of environmental parameters has been described. It is based on remote sensing and the most sophisticated machine learning techniques: Gaussian Processes (GPs) and Deep Neural Networks (DNNs). An example of knowledge extraction and actionable rule definition has been presented too. },
	author = {Stamenkovic, Z. and Randji{\'c},S and Santamar{\'\i}a, Ignacio and Markovic, D and Van Vaerenbergh, Steven and Pe{\v s}ovi{\'c}, U}
}
@conference {Eusipco2000_spect,
	title = {A Data Adaptive Regularization Method for Line Spectrum Estimation},
	booktitle = {European Signal Processing Conference (EUSIPCO 2000)},
	year = {2000},
	month = {September},
	address = {Tampere, Finland},
	author = {Santamar{\'\i}a, Ignacio and Art{\'e}s, Antonio and Gonz{\'a}lez, R. and Pantale{\'o}n, Carlos}
}
@conference {346,
	title = {Cross-Products LASSO},
	booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)},
	year = {2013},
	month = {May},
	address = {Vancouver, Canada},
	author = {Luengo, David and V{\'\i}a, Javier and Sandra Monz{\'o}n and Tom Trigano and Antonio Art{\'e}s-Rodr{\'\i}guez}
}
@conference {Eusipco2008_OSTBC_Correlation,
	title = {Correlation and Kullback Matching Approaches: Application to Blind Channel Estimation in {OSTBC} Systems},
	booktitle = {16th European Signal Processing Conference (EUSIPCO 2008)},
	year = {2008},
	month = {August},
	address = {Lausanne, Switzerland},
	author = {V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {492,
	title = {Constrained subspace estimation via convex optimization},
	booktitle = {European Signal Processing Conference (EUSIPCO)},
	year = {2017},
	month = {August},
	address = {Kos, Greece},
	author = {Santamar{\'\i}a, Ignacio and V{\'\i}a, Javier and Kirby, Michael and Marrinan, Timothy and Peterson, Chris and Louis L. Scharf}
}
@conference {354,
	title = {Computing the Degrees of Freedom for Arbitrary MIMO Interference Channels},
	booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)},
	year = {2013},
	month = {May},
	address = {Vancouver, Canada},
	abstract = {In this paper we provide an efficient procedure to compute the total number of degrees of freedom (DoF), achievable by linear beamforming, of the K-user multiple-input multiple-output (MIMO) interference channel with an arbitrary number of Tx-Rx antennas at each link. Firstly, we derive an analytical outer bound that generalizes the results that exist for the symmetric K-user M x N interference channel. Secondly, we obtain a tighter bound by solving a convex optimization problem that includes as constraints the DoF characterizations for point-to-point MIMO links and for 2-user interference channels. The solution to this convex problem admits an interesting waterfilling interpretation. Finally, exploiting this outer bound and using a recently proposed feasibility test, we show that it is possible to obtain the DoF for any interference channel in an efficient way. Some simulations results are included to illustrate the tightness of the derived bounds, as well as to study the DoF achievable for the 4-user channel when we distribute the total number of antennas among users and between transmitters and receivers in different ways.},
	keywords = {convex optimization, degrees of freedom, interference alignment, multiple-input multiple-output},
	isbn = {978-1-4799-0356-6},
	author = {Gonz{\'a}lez, {\'O}scar and Lameiro, Christian and V{\'\i}a, Javier and Beltr{\'a}n, Carlos and Santamar{\'\i}a, Ignacio}
}
@conference {Nnsp2001_chaos,
	title = {Competitive Chaotic {AR}(1) Model Estimation},
	booktitle = {Neural Networks for Signal Processing XI (NNSP 2001)},
	year = {2001},
	month = {September},
	address = {Falmouth, MA, USA},
	author = {Luengo, David and Pantale{\'o}n, Carlos and Santamar{\'\i}a, Ignacio}
}
@conference {356,
	title = {A Comparative Study of Kernel Adaptive Filtering Algorithms},
	booktitle = {2013 IEEE Digital Signal Processing (DSP) Workshop and IEEE Signal Processing Education (SPE)},
	year = {2013},
	month = {August},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Kernel adaptive filtering is a growing field of signal processing that is concerned with nonlinear adaptive filtering. When implemented naively, the time and memory complexities of these algorithms grow at least linearly with the amount of data processed. A large number of practical solutions have been proposed throughout the last decade, based on sparsification or pruning mechanisms. Nevertheless, there is a lack of understanding of their relative merits, which often depend on the data they operate on. We propose to study the quality of the solution as a function of either the time or the memory complexity. We empirically test six different kernel adaptive filtering algorithms on three different benchmark data sets. We make our code available through an open source toolbox that includes additional algorithms and allows to measure the complexities explicitly in number of floating point operations and bytes needed, respectively.},
	keywords = {kernel adaptive filtering},
	isbn = {978-1-4799-1616-0},
	doi = {10.1109/DSP-SPE.2013.6642587 },
	author = {Van Vaerenbergh, Steven and Santamar{\'\i}a, Ignacio}
}
@conference {SSPCardiff2009,
	title = {Coherent Fusion of Information for Optimal Detection in Sensor Networks},
	booktitle = {IEEE Workshop on Statistical Signal Processing (SSP 09)},
	year = {2009},
	month = {September},
	address = {Cardiff, UK},
	author = {Ram{\'\i}rez, David and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {627,
	title = {Coherence-based subspace packings for MIMO noncoherent communications},
	booktitle = {30th European Signal Processing Conference (EUSIPCO 2022)},
	year = {2022},
	month = {August},
	address = {Belgrade, Serbia},
	author = {Alvarez-Vizoso, Javier and Cuevas, Diego and Beltr{\'a}n, Carlos and Santamar{\'\i}a, Ignacio and Tucek, V{\'\i}t and Peters, Gunnar}
}
@conference {Eusipco2006_outageOFDM_pub,
	title = {Closed-form approximation for the outage capacity of {OFDM-STBC} and {OFDM-SFBC} systems},
	booktitle = {14th European Signal Processing Conference (EUSIPCO 2006)},
	year = {2006},
	month = {September},
	address = {Florence, Italy},
	author = {P{\'e}rez, Jes{\'u}s and Ib{\'a}{\~n}ez, Jes{\'u}s and Vielva, Luis and Santamar{\'\i}a, Ignacio}
}
@conference {Icassp2001,
	title = {Chaotic {AR}(1) Model Estimation},
	booktitle = {IEEE Int. Conf. on Acoust., Speech, and Signal Processing (ICASSP 2001)},
	year = {2001},
	month = {May},
	address = {Salt Lake City, Utah, USA},
	author = {Pantale{\'o}n, Carlos and Luengo, David and Santamar{\'\i}a, Ignacio}
}
@conference {SSP05_03_version_5pag,
	title = {{CCA} based algorithms for blind equalization of {FIR} {MIMO} systems},
	booktitle = {IEEE Workshop on Statistical Signal Processing (SSP 2005)},
	year = {2005},
	month = {July},
	address = {Bordeaux, France},
	author = {V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {Mobiligth2011_-_TWRC-RFAF,
	title = {Capacity Region of the Two-Way Multi-Antenna Relay Channel with Analog Tx-Rx Beamforming},
	booktitle = {3rd International ICST Conference on Mobile Lightweight Wireless Systems (Mobilight 2011)},
	year = {2011},
	month = {May},
	address = {Bilbao, Spain},
	author = {Lameiro, Christian and Naz{\'a}bal, Alfredo and Gholam, Fouad and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {Chinacom2010_MIMOBC,
	title = {Capacity region of the multiantenna Gaussian broadcast channel with analog TX-RX beamforming},
	booktitle = {5th International ICST Conference on Communications and Networking in China (CHINACOM)},
	year = {2010},
	month = {August},
	address = {Beijing, China},
	author = {Santamar{\'\i}a, Ignacio and V{\'\i}a, Javier and Naz{\'a}bal, Alfredo and Lameiro, Christian}
}
@conference {PIMRC_2004,
	title = {Capacity estimation of polarization-diversity MIMO systems in urban microcellular environments},
	booktitle = {15th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2004)},
	year = {2004},
	month = {September},
	address = {Barcelona, Spain},
	author = {P{\'e}rez, Jes{\'u}s and Ib{\'a}{\~n}ez, Jes{\'u}s and Vielva, Luis and Santamar{\'\i}a, Ignacio}
}
@conference {481,
	title = {Canonical Correlations for Target Detection in a Passive Radar Network},
	booktitle = {Asilomar Conference on Signals, Systems and Computers (ASILOMAR)},
	year = {2016},
	month = {November},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Pacific Grove (CA), USA},
	author = {Wang, Yuan and Louis L. Scharf and Santamar{\'\i}a, Ignacio and Wang, Haonan}
}
@conference {EUSIPCO2005_CCA,
	title = {Canonical correlation analysis ({CCA}) algorithms for multiple data sets: application to blind {SIMO} equalization},
	booktitle = {13th European Signal Processing Conference (EUSIPCO 2005)},
	year = {2005},
	month = {September},
	address = {Antalya, Turkey},
	author = {V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and P{\'e}rez, Jes{\'u}s}
}
@conference {ICASSP2010_MIMOPlatform,
	title = {Building a Web Platform for Learning Advanced Digital Communications using a {MIMO} Testbed},
	booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)},
	year = {2010},
	month = {March},
	address = {Dallas, USA},
	author = {Vielva, Luis and V{\'\i}a, Javier and Guti{\'e}rrez, Jes{\'u}s and Gonz{\'a}lez, {\'O}scar and Ib{\'a}{\~n}ez, Jes{\'u}s and Santamar{\'\i}a, Ignacio}
}
@conference {eus04_pba,
	title = {Blind restoration of binary signals using a line spectrum fitting approach},
	booktitle = {12th European Signal Processing Conference (EUSIPCO 2004)},
	year = {2004},
	month = {September},
	address = {Vienna, Austria},
	author = {V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and L{\'a}zaro, Marcelino}
}
@conference {Eusicpo2006_OSTBC_pub,
	title = {Blind Identification of {MIMO-OSTBC} Channels combining second and higher order statistics},
	booktitle = {14th European Signal Processing Conference (EUSIPCO 2006)},
	year = {2006},
	month = {September},
	address = {Florence, Italy},
	author = {V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and P{\'e}rez, Jes{\'u}s}
}
@conference {Eusipco04_svm,
	title = {Blind equalization of multilevel signals using support vector machines},
	booktitle = {12th European Signal Processing Conference (EUSIPCO 2004)},
	year = {2004},
	month = {September},
	address = {Vienna, Austria},
	author = {L{\'a}zaro, Marcelino and Santamar{\'\i}a, Ignacio and V{\'\i}a, Javier and Erdogmus, Deniz}
}
@conference {Icassp03_equal_svm,
	title = {Blind equalization of constant modulus signals via support vector regression},
	booktitle = {IEEE Int. Conf. on Acoust., Speech, and Signal Processing (ICASSP 2003)},
	year = {2003},
	month = {April},
	address = {Hong Kong, China},
	author = {Santamar{\'\i}a, Ignacio and Ib{\'a}{\~n}ez, Jes{\'u}s and Vielva, Luis and Pantale{\'o}n, Carlos}
}
@conference {ICA03,
	title = {Blind equalization by sampled {PDF} fitting},
	booktitle = {4th Int. Symposium on Independent Component Analisys and BSS},
	year = {2003},
	month = {April},
	address = {Nara, Japan},
	author = {L{\'a}zaro, Marcelino and Santamar{\'\i}a, Ignacio and Pantale{\'o}n, Carlos and Erdogmus, Deniz and Hild II, K. E. and Pr{\'\i}ncipe, Jos{\'e} C.}
}
@conference {icassp2006_OSTBC_pub,
	title = {Blind decoding of {MISO-OSTBC} systems based on principal component analysis},
	booktitle = {IEEE Int. Conf. on Acoust., Speech, and Signal Processing (ICASSP 2006)},
	year = {2006},
	month = {May},
	address = {Toulouse, France},
	author = {V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and P{\'e}rez, Jes{\'u}s and Ram{\'\i}rez, David}
}
@conference {556,
	title = {Benefits of Improper Signaling for Overlay Cognitive Radio},
	booktitle = {IEEE Global Communication Conference (GLOBECOM)},
	year = {2019},
	month = {December},
	address = {Waikoloa, HI, USA},
	abstract = {This paper considers improper Gaussian signaling (IGS) in an overlay cognitive radio scenario. We follow a protocol in which the secondary user (SU) uses part of its power to relay the message for the primary user (PU) and consider a simple yet illustrative 2-user scenario. We analyze two communication schemes depending on whether or not the
PU cooperates with the SU and derive closed-form expressions for the optimal transmission parameters that maximize the SU rate while ensuring a specified minimum performance of the PU. Our numerical results show that IGS may significantly outperform proper signaling and that, interestingly, the cooperative approach provides negligible performance gains over its non-cooperative
counterpart.},
	author = {Lameiro, Christian and Santamar{\'\i}a, Ignacio and Schreier, Peter J.}
}
@conference {294,
	title = {Beamforming-based emulation of spatial and temporal correlated MISO channels},
	booktitle = {International Symposium on Signals, Systems and Electronics (ISSSE 2012)},
	year = {2012},
	month = {October},
	address = {Potsdam, Germany},
	author = {Guti{\'e}rrez, Jes{\'u}s and Ib{\'a}{\~n}ez, Jes{\'u}s and P{\'e}rez, Jes{\'u}s}
}
@conference {310,
	title = {Bayesian Multiantenna Sensing for Cognitive Radio},
	booktitle = {7th IEEE Sensor Array and Multichannel Signal Processing Workshop},
	year = {2012},
	month = {June},
	address = {Hoboken, NJ, USA},
	abstract = {In this paper, the problem of multiantenna spectrum sensing in cognitive radio (CR) is addressed within a Bayesian framework. Unlike previous works, our Bayesian model places priors directly on the spatial covariance matrices under both hypotheses, as well as on the probability of channel occupancy. Specifically, we use inverse-gamma and complex inverse-Wishart distributions as conjugate priors for the null and alternative hypotheses, respectively; and a Bernoulli distribution as the prior for channel occupancy. At each sensing period, Bayesian inference is applied and the posterior of channel occupancy is thresholded for detection. After a suitable approximation, the posteriors are employed as priors for the next sensing frame, which can be beneficial in slowly time-varying environments. By means of simulations, the proposed detector is shown to outperform the Generalized Likelihood Ratio Test (GLRT) detector.},
	author = {Manco-V{\'a}squez, Julio and L{\'a}zaro-Gredilla, Miguel and Ram{\'\i}rez, David and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {Eusipco02_mcmc,
	title = {Bayesian estimation of discrete chaotic signals by {MCMC}},
	booktitle = {XI European Signal Processing Conference (Eusipco 2002)},
	year = {2002},
	month = {September},
	address = {Toulouse, France},
	author = {Luengo, David and Pantale{\'o}n, Carlos and Santamar{\'\i}a, Ignacio}
}
@conference {icassp2000,
	title = {Bayesian Estimation of a Class of Chaotic Signals},
	booktitle = {IEEE Int. Conf. on Acoust., Speech, and Signal Processing (ICASSP 2000)},
	year = {2000},
	month = {June},
	address = {Istanbul, Turkey},
	author = {Pantale{\'o}n, Carlos and Luengo, David and Santamar{\'\i}a, Ignacio}
}
@conference {Miguel_KRLS_MLSP2011,
	title = {A {Bayesian} Approach To Tracking With Kernel Recursive Least-Squares},
	booktitle = {IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2011)},
	year = {2011},
	month = {September},
	address = {Beijing, China},
	abstract = {In this paper we introduce a kernel-based recursive least-squares (KRLS) algorithm that is able to track nonlinear, time-varying relationships in data. To this purpose we first derive the standard KRLS equations from a Bayesian perspective (including a principled approach to pruning) and then take advantage of this framework to incorporate forgetting in a consistent way, thus enabling the algorithm to perform tracking in non-stationary scenarios. In addition to this tracking ability, the resulting algorithm has a number of appealing properties: It is online, requires a fixed amount of memory and computation per time step and incorporates regularization in a natural manner. We include experimental results that support the theory as well as illustrate the efficiency of the proposed algorithm.},
	keywords = {kernel adaptive filtering, KRLS},
	author = {L{\'a}zaro-Gredilla, Miguel and Van Vaerenbergh, Steven and Santamar{\'\i}a, Ignacio}
}
@conference {ICECS_2010_pub,
	title = {Baseband processor for RF-MIMO WLAN},
	booktitle = {17th IEEE International Conference on Electronics, Circuits, and Systems (ICECS 2010)},
	year = {2010},
	month = {December},
	address = {Athens, Greece},
	author = {Elvira, Victor and Ib{\'a}{\~n}ez, Jes{\'u}s and Santamar{\'\i}a, Ignacio and Krstic, M. and Tittelbach-Helmrich, K. and Stamenkovic, Z.}
}
@conference {455,
	title = {Balanced Least Squares: Linear Model Estimation with Noisy Inputs},
	booktitle = {IEEE workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)},
	year = {2015},
	month = {December},
	address = {Canc{\'u}n, Mexico},
	author = {V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {467,
	title = {Balanced least squares: estimation in linear systems with noisy inputs and multiple outputs},
	booktitle = {IEEE Workshop on Statistical Signal Processing (SSP)},
	year = {2016},
	month = {June},
	address = {Palma de Mallorca},
	abstract = {This paper revisits the linear model with noisy inputs, in which the performance of the total least squares (TLS) method is far from acceptable. Under the assumption of Gaussian noises, the maximum likelihood (ML) estimation of the system response is reformulated as a general balanced least squares (BLS) problem. Unlike TLS, which minimizes the trace of the product between the empirical and inverse theoretical covariance matrices, BLS promotes solutions with similar values of both the empirical and theoretical error covariance matrices. The general BLS problem is reformulated as a semidefinite program with a rank constraint, which can be relaxed in order to obtain polynomial time algorithms. Moreover, we provide new theoretical results regarding the scenarios in which the relaxation is tight, as well as additional insights on the performance and interpretation of BLS. Finally, some simulation results illustrate the satisfactory performance of the proposed method.},
	author = {V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {luengo_final_Eusipco,
	title = {Asymptotically optimal maximum-likelihood estimator of a class of chaotic signals using the Viterbi algorithm},
	booktitle = {13th European Signal Processing Conference (EUSIPCO 2005)},
	year = {2005},
	month = {September},
	address = {Antalya, Turkey},
	author = {Luengo, David and Santamar{\'\i}a, Ignacio and Vielva, Luis}
}
@conference {433,
	title = {An asymptotic LMPI test for cyclostationarity detection with application to cognitive radio},
	booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
	year = {2015},
	month = {April},
	address = {Brisbane, Australia},
	author = {Ram{\'\i}rez, David and Schreier, Peter J. and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and Louis L. Scharf}
}
@conference {388,
	title = {An asymptotic GLRT for the detection of cyclostationary signals},
	booktitle = {International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
	year = {2014},
	month = {May},
	address = {Florence, Italy},
	author = {Ram{\'\i}rez, David and Louis L. Scharf and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio and Schreier, Peter J.}
}
@conference {ICT2009_Analog_Combining_Architecture,
	title = {Architecture of an Analog Combining MIMO System Compliant to {IEEE802.11a}},
	booktitle = {ICT-MobileSummit 2009},
	year = {2009},
	month = {June},
	address = {Santander, Spain},
	author = {Stamenkovic, Z. and Tittelbach-Helmrich, K. and Krstic, M. and P{\'e}rez, Jes{\'u}s and V{\'\i}a, Javier and Ib{\'a}{\~n}ez, Jes{\'u}s}
}
@conference {VTC_2005,
	title = {Approximate closed-form expression for the ergodic capacity of {MISO} and {SIMO} systems},
	booktitle = {IEEE Vehicular Technology Conference, Spring (VTC 2005)},
	year = {2005},
	month = {May},
	address = {Stockholm, Sweden},
	author = {P{\'e}rez, Jes{\'u}s and Ib{\'a}{\~n}ez, Jes{\'u}s and Vielva, Luis and Santamar{\'\i}a, Ignacio}
}
@conference {AP2000_a,
	title = {Application of {GTD/UTD} to the analysis of antennas on board the {ISS}},
	booktitle = {AP2000 Millennium Conference on Antennas and Propagation},
	year = {2000},
	month = {April},
	address = {Davos, Switzerland},
	author = {Guti{\'e}rrez, O. and Gonz{\'a}lez, I. and Saez de Adana, F. and P{\'e}rez, Jes{\'u}s and C{\'a}tedra, M. F.}
}
@conference {454,
	title = {Antenna Grouping for General Discriminatory Channel Estimation},
	booktitle = {Wireless Communications and Signal Processing (WCSP)},
	year = {2015},
	month = {October},
	address = {Nanjing, China},
	author = {Bezanilla, Juan and V{\'\i}a, Javier}
}
@conference {ISWCS_2006_a,
	title = {Analytical approximations for the capacity of orthogonal {SFBC}},
	booktitle = {3rd International Symposium on Wireless Communication Systems (ISWCS 2006)},
	year = {2006},
	month = {September},
	address = {Valencia, Spain},
	author = {P{\'e}rez, Jes{\'u}s and Ib{\'a}{\~n}ez, Jes{\'u}s and Vielva, Luis and Santamar{\'\i}a, Ignacio}
}
@conference {430,
	title = {Analysis of maximally improper signalling schemes for underlay cognitive radio},
	booktitle = {IEEE International Conference on Communications (ICC)},
	year = {2015},
	month = {June},
	address = {London, UK},
	author = {Lameiro, Christian and Santamar{\'\i}a, Ignacio and Schreier, Peter J.}
}
@conference {535,
	title = {Analysis and classification of MoCap data by Hilbert space embedding-based distance and multikernel learning},
	booktitle = {The 23rd Iberoamerican Congress on Pattern Recognition},
	year = {2018},
	month = {November},
	address = {Madrid, Spain},
	author = {Pulgarin-Giraldo, Juan Diego and Alvarez-Meza, Andres Marino and Van Vaerenbergh, Steven and Santamar{\'\i}a, Ignacio and Castellanos, German}
}
@conference {ICASSP2011_MultiuserAnalogBF,
	title = {Analog Antenna Combining in Multiuser OFDM Systems: Beamforming Design and Power Allocation},
	booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011)},
	year = {2011},
	month = {May},
	address = {Prague, Czech Republic},
	author = {Naz{\'a}bal, Alfredo and V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {Icc2009_BeamMaxCAP,
	title = {Analog Antenna Combining for Maximum Capacity under {OFDM} Transmissions},
	booktitle = {IEEE International Conference on Communications (ICC 2009)},
	year = {2009},
	month = {June},
	address = {Dresden, Germany},
	author = {V{\'\i}a, Javier and Elvira, Victor and Santamar{\'\i}a, Ignacio and Eickhoff, R.}
}
@conference {518,
	title = {An alternating optimization algorithm for two-channel factor analysis with common and uncommon factors},
	booktitle = {52nd Asilomar Conference on Signals, Systems and Computers},
	year = {2018},
	month = {October},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Pacific Grove (CA), USA},
	author = {Ram{\'\i}rez, David and Santamar{\'\i}a, Ignacio and Van Vaerenbergh, Steven and Louis L. Scharf}
}
@conference {479,
	title = {Advanced Wireless Sensor Nodes and Networks for Agricultural Applications},
	booktitle = {24th Telecommunications Forum, (TELFOR 2016)},
	year = {2016},
	month = {November},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Belgrade, Serbia},
	abstract = {A review of advanced wireless sensor nodes, networks, and applications in precision agriculture has been presented. Features of several commercial and prototype sensor node platforms designed and implemented for agricultural applications have been described. Basics of sensor network protocols and topologies have been reviewed together with numerous applications. Advanced machine learning approaches in this field (especially, Kernel Methods, Gaussian Processes, and Deep Neural Networks) have also been discussed.},
	author = {Stamenkovic, Z. and Randji{\'c},S and Santamar{\'\i}a, Ignacio and Pe{\v s}ovi{\'c}, U and Pani{\'c}, G and Tanaskovi{\'c}, S}
}
@conference {SSP_2011_jperez,
	title = {Adaptive Modulation and Power in Wireless Communication Systems with Delay Constraints},
	booktitle = {IEEE Workshop on Statistical Signal Processing (SSP 2011)},
	year = {2011},
	month = {June},
	address = {Nice, France},
	author = {P{\'e}rez, Jes{\'u}s and Ib{\'a}{\~n}ez, Jes{\'u}s}
}
@conference {345,
	title = {Adaptive Kernel Canonical Correlation Analysis Algorithms for Maximum and Minimum Variance},
	booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)},
	year = {2013},
	month = {May},
	address = {Vancouver, Canada},
	abstract = {We describe two formulations of the kernel canonical correlation analysis (KCCA) problem for multiple data sets. The kernel-based algorithms, which allow one to measure nonlinear relationships between the data sets, are obtained as nonlinear extensions of the classical maximum variance (MAXVAR) and minimum variance (MINVAR) canonical correlation analysis (CCA) formulations. We then show how adaptive versions of these algorithms can be obtained by reformulating KCCA as a set of coupled kernel recursive least-squares algorithms. We illustrate the performance of the proposed algorithms on a nonlinear identification application and a cognitive radio detection problem.},
	author = {Van Vaerenbergh, Steven and V{\'\i}a, Javier and Manco-V{\'a}squez, Julio and Santamar{\'\i}a, Ignacio}
}
@conference {515,
	title = {Adaptive EM-based Algorithm for Cooperative Spectrum Sensing in Mobile Environments},
	booktitle = {IEEE Statistical Signal Processing Workshop (SSP)},
	year = {2018},
	month = {June},
	address = {Freiburg, Germany},
	abstract = {In this work we propose a new adaptive algorithm for cooperative
spectrum sensing in dynamic environments where the channels are time varying. We assume a cooperative sensing procedure based on the soft fusion of the signal energy levels measured at the sensors. The detection problem is posed as a composite hypothesis testing problem. Then, we consider the Generalized Likelihood Ratio Test approach where the maximum likelihood estimate of the unknown parameters (which are the signal-to-noise ratio under the different hypotheses) are
obtained from the most recent energy levels at the sensors by means of the Expectation-Maximization algorithm. We derive simple closed-form expressions for both, the E and the M steps. The algorithm can operate even when only a subset of sensors report their energy estimates, which makes it suited to be used with any sensor selection strategy (active sensing). Simulation results show the feasibility and efficiency of the method in realistic slow-fading environments.},
	author = {P{\'e}rez, Jes{\'u}s and Santamar{\'\i}a, Ignacio and V{\'\i}a, Javier}
}
@conference {509,
	title = {Adaptive Clustering Algorithm for Cooperative Spectrum Sensing in Mobile Environments},
	booktitle = { IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
	year = {2018},
	month = {April},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Calgary,Canada},
	author = {P{\'e}rez, Jes{\'u}s and Santamar{\'\i}a, Ignacio}
}
@conference {Eusipco02_ent,
	title = {Adaptive blind equalization through quadratic pdf matching},
	booktitle = {XI European Signal Processing Conference (Eusipco 2002)},
	year = {2002},
	month = {September},
	address = {Toulouse, France},
	author = {Santamar{\'\i}a, Ignacio and Pantale{\'o}n, Carlos and Vielva, Luis and Pr{\'\i}ncipe, Jos{\'e} C.}
}
@conference {SPAWC2005_cca,
	title = {Adaptive blind equalization of {SIMO} systems based on canonical correlation analysis},
	booktitle = {Sixth IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2005)},
	year = {2005},
	month = {June},
	address = {New York, USA},
	author = {V{\'\i}a, Javier and Santamar{\'\i}a, Ignacio}
}
@conference {Iwann2001,
	title = {Accelerating the Convergence of {EM}-Based Training Algorithms for {RBF} Networks},
	booktitle = {6th International Work Conference on Artificial and Natural Neural Networks (IWANN 2001)},
	year = {2001},
	month = {June},
	address = {Granada, Spain},
	author = {L{\'a}zaro, Marcelino and Santamar{\'\i}a, Ignacio and Pantale{\'o}n, Carlos}
}
