Articles de revista
http://hdl.handle.net/2117/1256
20150829T06:30:20Z

Nonuniform sampling walls in wideband signal detection
http://hdl.handle.net/2117/26802
Nonuniform sampling walls in wideband signal detection
Font Segura, Josep; Vázquez Grau, Gregorio; Riba Sagarra, Jaume
This work shows the existence of sampling walls in detection of wideband signals from Bernoulli nonuniform sampling (BNS) in the presence of noise uncertainty. A sampling wall is defined as the sampling density below which the target error probabilities, i.e., the missed detection and false alarm probabilities, cannot be guaranteed at a given signal to noise ratio (SNR) regardless the number of acquired samples. The BNS is adopted because it exhibits good tradeoff properties between complexity and performance. It is shown that BNS suffers from noise enhancement, which translates into a whitening effect in the correlation of the legacy signal. Contrarily to the existing literature, the signal detection problem is addressed without having to reconstruct neither the signal nor its spectrum. More specifically, the optimal low SNR detector is formulated as a generalized likelihood ratio test (GLRT) to exploit the available side information of the problem, i.e., the noise variance, the sampling density and the legacy signal autocorrelation. By deriving the asymptotic performance of the GLRT in the presence of noise uncertainty, explicit expressions for sampling walls are obtained as a function of the legacy signal occupancy, the SNR and the noise uncertainty. Further, numerical results are provided to assess the behavior of the sampling walls and signal detection performance.
20140101T00:00:00Z

The DoF of the 3User (p, p+1) MIMO Interference Channel
http://hdl.handle.net/2117/25955
The DoF of the 3User (p, p+1) MIMO Interference Channel
Torrellas Socastro, Marc; Agustín de Dios, Adrián; Vidal Manzano, José; Muñoz Medina, Olga
The degrees of freedom (DoF) of the 3user multipleinput multipleoutput (MIMO) interference channel (IC) with full channel state information and constant channel coefficients are investigated when (p, p + 1) antennas are deployed at the transmitters and receivers, respectively. The point of departure of this paper is the work of Wang et al., which conjectured but did not prove the DoF for the antenna settings with p > 1. Here the achievability of the DoF outer bound is formally proved using linear methods, thereby avoiding the use of the rational dimensions framework. The proposed transmission scheme exploits asymmetric complex signaling together with symbol extensions in time and space interference alignment concepts. While the paper deals with the p = 2, 3, ... , 6 cases, providing the specific transmit and receive filters, there are also provided the tools needed for proving the achievability of the optimal DoF for p > 6, whose DoF characterization is conjectured.
20141101T00:00:00Z

Single and multifrequency wideband spectrum sensing with sideinformation
http://hdl.handle.net/2117/25065
Single and multifrequency wideband spectrum sensing with sideinformation
Font Segura, Josep; Vázquez Grau, Gregorio; Riba Sagarra, Jaume
This study addresses the optimal spectrum sensing detection based on the complete or partial sideinformation on the signal and noise statistics. The use of the generalisedlikelihood ratio test (GLRT) involves maximumlikelihood (ML) estimation of the nuisances. ML estimation of the unknowns is especially challenging for wideband cognitive radio because closedform solutions are often not available. Based on the equivalence between the wideband regime and the lowsignaltonoise ratio regime, this study provides a general kernel framework for GLRT spectrum sensing. It is shown that any GLRT detector exclusively depends on the projection of the sample covariance matrix of the data onto a given underlying kernel that reflects the available sideinformation in the problem. The kernels in several scenarios of interest are derived, including the widespread single and multifrequency channelisation cases. Theoretical interpretations and numerical results show the tradeoff between detection performance and the degree of sideinformation on the most informative statistics for detection, that is, the modulation format and spectrum distribution of the primary users.
20141001T00:00:00Z

Asymptotically optimal linear shrinkage of sample LMMSE and MVDR filters
http://hdl.handle.net/2117/24612
Asymptotically optimal linear shrinkage of sample LMMSE and MVDR filters
Serra, Jordi; Nájar Martón, Montserrat
Conventional implementations of the linearminimum meansquare (LMMSE) and minimum variance distortionless response (MVDR) estimators rely on the sample matrix inversion (SMI) technique, i.e., on the sample covariance matrix (SCM). This approach is optimal in the large sample size regime. Nonetheless, in small sample size situations, those sample estimators suffer a large performance degradation. Thus, the aim of this paper is to propose corrections of these sample methods that counteract their performance degradation in the small sample size regime and keep their optimality in large sample size situations. To this aim, a twofold approach is proposed. First, shrinkage estimators are considered, as they are known to be robust to the small sample size regime. Namely, the proposed methods are based on shrinking the sample LMMSE or sample MVDR filters towards a variously called matched filter or conventional (Bartlett) beamformer in array processing. Second, random matrix theory is used to obtain the optimal shrinkage factors for large filters. The simulation results highlight that the proposed methods outperform the sample LMMSE and MVDR. Also, provided that the sample size is higher than the observation dimension, they improve classical diagonal loading (DL) and LedoitWolf (LW) techniques, which counteract the small sample size degradation by regularizing the SCM. Finally, compared to stateoftheart DL, the proposed methods reduce the computational cost and the proposed shrinkage of the LMMSE obtains performance gains.
20140715T00:00:00Z

Pattern matching for building feature extraction
http://hdl.handle.net/2117/24251
Pattern matching for building feature extraction
Lagunas Targarona, Eva; Amin, Moeness G.; Ahmad, Fauzia; Nájar Martón, Montserrat
We address the problem of detecting building dominant scatterers using a reduced number of measurements with applications to throughthewall radar (TWR) and urban sensing. We consider oblique illumination, which specially enhances the radar returns from the corners formed by the orthogonal intersection of two walls. This letter uses a novel type of image descriptor, named correlogram, which encodes information about spatial correlation of complex amplitudes of each TWR image pixel. The proposed technique compares the known correlogram of the scattering response of an isolated canonical corner reflector with the correlogram of the received radar signal. The featurebased nature of the proposed detector enables corner separation from other indoor scatterers, such as humans. © 20042012 IEEE.
20141201T00:00:00Z

Energyaware broadcast multiuserMIMO precoder design with imperfect channel and battery knowledge
http://hdl.handle.net/2117/23699
Energyaware broadcast multiuserMIMO precoder design with imperfect channel and battery knowledge
Rubio López, Javier; Pascual Iserte, Antonio
This paper addresses the problem of resource allocation and precoder design in a multiuser MIMO broadcast system where the terminals are batterypowered devices provided with energy harvesting capabilities. Energy harvesting is a promising technology based on which it is possible to recharge the battery of the terminals using energy collected from the environment. Models for the power consumption of the frontend and decoding stages are discussed and included in the design of the proposed scheme. In addition, the information concerning the battery level plays an explicit role and has an impact on the design of our proposed allocation strategy. Sumrate maximization is considered as optimization policy and energyrelated constraints are taken into account explicitly in the resource allocation in order to increase the lifetime of the batteries. In the first part of the paper, we consider the transmitter to have perfect channel state information (CSI) and battery knowledge, assuming an ideal feedback link. Then, a robust design based on imperfect channel information at the transmitter is studied and its effect on the energy consumed by the terminals is analyzed. Finally, an extended robust approach considering also imperfect battery knowledge (quantized battery status) at the transmitter is also addressed. Simulation results show that our proposed technique not only improves the usage of the batteries when compared with other traditional allocation policies, but also enhances the average data rate
20140601T00:00:00Z

A ratesplitting approach to fading channels with imperfect channelstate information
http://hdl.handle.net/2117/23656
A ratesplitting approach to fading channels with imperfect channelstate information
Pastore, Adriano; Koch, Tobias; Rodríguez Fonollosa, Javier
As shown by Médard, the capacity of fading channels with imperfect channelstate information can be lowerbounded by assuming a Gaussian channel input X with power P and by upperbounding the conditional entropy h(XY,H) by the entropy of a Gaussian random variable with variance equal to the linear minimum meansquare error in estimating X from \(Y, H). We demonstrate that, using a ratesplitting approach, this lower bound can be sharpened: by expressing the Gaussian input X as the sum of two independent Gaussian variables X1 and X2 and by applying Médard's lower bound first to bound the mutual information between X1 and Y while treating X2 as noise, and by applying it a second time to the mutual information between X2 and Y while assuming X1 to be known, we obtain a capacity lower bound that is strictly larger than Médard's lower bound. We then generalize this approach to an arbitrary number L of layers, where X is expressed as the sum of L independent Gaussian random variables of respective variances Pl, l = 1, ¿ ,L summing up to P. Among all such ratesplitting bounds, we determine the supremum over power allocations Pl and total number of layers L. This supremum is achieved for L 8 and gives rise to an analytically expressible capacity lower bound. For Gaussian fading, this novel bound is shown to converge to the Gaussianinput mutual information as the signaltonoise ratio (SNR) grows, provided that the variance of the channel estimation error HH tends to zero as the SNR tends to infinity.
20140701T00:00:00Z

Noncooperative dayahead bidding strategies for demandside expected cost minimization with realtime adjustments: a GNEP approach
http://hdl.handle.net/2117/23344
Noncooperative dayahead bidding strategies for demandside expected cost minimization with realtime adjustments: a GNEP approach
Atzeni, Italo; García Ordoñez, Luis; Scutari, Gesualdo; Palomar, Daniel P.; Rodríguez Fonollosa, Javier
The envisioned smart grid aims at improving the interaction between the supplyand the demandside of the electricity network, creating unprecedented possibilities for optimizing the energy usage at different levels of the grid. In this paper, we propose a distributed demandside management (DSM) method intended for smart grid users with load prediction capabilities, who possibly employ dispatchable energy generation and storage devices. These users participate in the dayahead market and are interested in deriving the bidding, production, and storage strategies that jointly minimize their expected monetary expense. The resulting dayahead grid optimization is formulated as a generalized Nash equilibrium problem (GNEP), which includes global constraints that couple the users' strategies. Building on the theory of variational inequalities, we study the main properties of the GNEP and devise a distributed, iterative algorithm converging to the variational solutions of the GNEP. Additionally, users can exploit the reduced uncertainty about their energy consumption and renewable generation at the time of dispatch. We thus present a complementary DSM procedure that allows them to perform some unilateral adjustments on their generation and storage strategies so as to reduce the impact of their realtime deviations with respect to the amount of energy negotiated in the dayahead. Finally, numerical results in realistic scenarios are reported to corroborate the proposed DSM technique.
20140501T00:00:00Z

Frequencydomain GLR detection of a secondorder cyclostationary signal over fading channels
http://hdl.handle.net/2117/22790
Frequencydomain GLR detection of a secondorder cyclostationary signal over fading channels
Riba Sagarra, Jaume; Font Segura, Josep; Villares Piera, Nemesio J.; Vázquez Grau, Gregorio
Cyclostationary processes exhibit a form of frequency diversity. Based on that, we show that a digital waveform with symbol period T can be asymptotically represented as a rank1 frequencydomain vector process which exhibits uncorrelation at different frequencies inside the Nyquist spectral support of 1/T. By resorting to the fast Fourier transform (FFT), this formulation obviates the need of estimating a cumbersome covariance matrix to characterize the likelihood function. We then derive the generalized likelihood ratio test (GLRT) for the detection of a cyclostationary signal in unknown white noise without the need of a assuming a synchronized receiver. This provides a sound theoretical basis for the exploitation of the cyclostationary feature and highlights an explicit link with classical square timing recovery schemes, which appear implicitly in the core of the GLRT. Moreover, to avoid the wellknown sensitivity of cyclostationarybased detection schemes to frequencyselective fading channels, a parametric channel model based on a lower bound on the coherence bandwidth is adopted and incorporated into the GLRT. By exploiting the rank1 structure of small spectral covariance matrices, the obtained detector outperforms the classical spectral correlation magnitude detector.
20140401T00:00:00Z

Radio context awareness and applications
http://hdl.handle.net/2117/21937
Radio context awareness and applications
Reggiani, Luca; Fiorina, Jocelyn; Gezici, Sinan; Morosi, Simone; Nájar Martón, Montserrat
The context refers to “any information that can be used to characterize the situation of an entity, where an entity can be a person, place, or physical object.” Radio context awareness is defined as the ability of detecting and estimating a system state or parameter, either globally or concerning one of its components, in a radio system for enhancing performance at the physical, network, or application layers. In this paper, we review the fundamentals of context awareness and the recent advances in the main radio techniques that increase the context awareness and smartness, posing challenges and renewed opportunities to addedvalue applications in the context of the next generation of wireless networks.
20130101T00:00:00Z