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  • Compressive sensing based candidate detector and its applications to spectrum sensing and through-the-wall radar imaging.  Open access

     Lagunas Targarona, Eva
    Defense's date: 2014-03-07
    Department of Signal Theory and Communications, Universitat Politècnica de Catalunya
    Theses

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    L¿adquisició de dades es un tema fonamental en el processament de senyals. El teorema de Shannon-Nyquist hasigut la base dels mètodes convencionals de conversió analògic-digital. El teorema diu que per recuperar la informació,qualsevol senyal ha de ser mostrejada a una freqüència igual al doble de la màxima freqüència present a la senyal. Noobstant, aquest teorema assumeix el pitjor dels casos: quan les senyales ocupen tot l'espectre. En aquest context apareix lateoria del mostreig compressiu o Compressed Sensing (CS). CS ha suposat una autèntica revolució pel que fa al'adquisició i mostreig de dades analògiques en un esforç cap a resoldre la problemàtica de recuperar un procés continuocomprimible si únicament es realitza un número molt reduït de mesures del mateix. El requisit para l'èxit d'aquesta tècnicaés que la senyal ha de poder ser expressada de forma dispersa en algun domini. Això és, que la majoria dels seuscomponents siguin zero o es puguin considerar despreciables. L¿aplicació del mostreig compressiu suposa una nova líniagran interès investigador en àrees com la transmissió de dades, imatges mèdiques, biologia computacional, entre altres.A diferència de la majoria de publicacions relacionades amb CS, en aquesta tesi s'estudiarà CS aplicat a detecció,estimació i classificació de senyals, que no requereix la recuperació perfecta ni completa de la senyal. En concret, esproposa un nou detector basat en cert coneixement a priori sobre la senyal a detectar. La idea bàsica és escanejar el dominide la senyal amb una senyal anomenada candidata, que s'obté a partir de la informació que es té a priori de la senyal adetectar.El detector és aplicat a dos problemes particulars de detecció. En primer lloc, la teoria de CS és aplicada al sensatd'espectre. El principal problema radica en que les polítiques actuals d'assignació de bandes freqüencials són massaestrictes i no permeten l'ús òptim de l'espectre disponible. L'ús de l'espectre pot ser millorat si es possibilita que un usuarisecundari (sense llicència) pugui accedir a un canal desocupat per un usuari primari. La radio cognitiva és una solucióprometedora d¿aquest problema. Un requeriment essencial dels dispositius cognitius és la capacitat de detectar lapresència d'usuaris primaris. Un dels problemes que s'afronta en aquest context és la necessitat d'escanejar grans amplesde banda que requereixen freqüències de mostreig elevades. El detector proposat relaxa els requeriments de mostreig, itambé per proporcionar una estimació de la freqüència, potència i angle d'arribada dels usuaris primaris.La segona aplicació és en radars amb visió a través de paret (TWRI). Veure a través de les parets és possiblemitjançant l'enviament d'ones de radio, capaç de travessar objectes opacs, que reboten en els objectius i retornen alsreceptors. Aquest és un tipus de radar amb una gran varietat d'aplicacions, tant civils como militars. La resolució de lasimatges proporcionades per aquests radars millora quan s'usen grans amples de banda i més nombre d'antenes, el quedirectament implica la necessitat d'adquirir un major nombre de mostres i major volum de dades que processar. A vegades,reduir el nombre de mostres és interessant en TWRI des de un punt de vista logístic, ja que pot ser que algunes mostresfreqüencials o espacials siguin difícils o impossibles d'obtenir. En aquesta tesis focalitzarem el treball en la detecciód'estructures internes per reconstruir l'estructura de l'edifici. Les parets i/o díedres formats per la intersecció de dos paretsinternes formaran les nostres senyals candidates per al detector proposat. La validació de la proposta es durà a terme ambexperiments realitzats en el Radar Imaging Lab del Center for Advanced Communications, Villanova University, USA.

    Signal acquisition is a main topic in signal processing. The well-known Shannon-Nyquist theorem lies at the heart of any conventional analog to digital converters stating that any signal has to be sampled with a constant frequency which must be at least twice the highest frequency present in the signal in order to perfectly recover the signal. However, the Shannon-Nyquist theorem provides a worst-case rate bound for any bandlimited data. In this context, Compressive Sensing (CS) is a new framework in which data acquisition and data processing are merged. CS allows to compress the data while is sampled by exploiting the sparsity present in many common signals. In so doing, it provides an efficient way to reduce the number of measurements needed for perfect recovery of the signal. CS has exploded in recent years with thousands of technical publications and applications being developed in areas such as channel coding, medical imaging, computational biology and many more. Unlike majority of CS literature, the proposed Ph.D. thesis surveys the CS theory applied to signal detection, estimation and classification, which not necessary requires perfect signal reconstruction or approximation. In particular, a novel CSbased detection technique which exploits prior information about some features of the signal is presented. The basic idea is to scan the domain where the signal is expected to lie with a candidate signal estimated from the known features. The proposed detector is called candidate-based detector because their main goal is to react only when the candidate signal is present. The CS-based candidate detector is applied to two topical detection problems. First, the powerful CS theory is used to deal with the sampling bottleneck in wideband spectrum sensing for open spectrum scenarios. The radio spectrum is a natural resource which is recently becoming scarce due to the current spectrum assignment policy and the increasing number of licensed wireless systems. To deal with the crowded spectrum problem, a new spectrum management philosophy is required. In this context, the revolutionary Cognitive Radio (CR) emerges as a solution. CR benefits from the poor usage of the spectrum by allowing the use of temporarily unused licensed spectrum to secondary users who have no spectrum licenses. The identification procedure of available spectrum is commonly known as spectrum sensing. However, one of the most important problems that spectrum sensing techniques must face is the scanning of wide band of frequencies, which implies high sampling rates. The proposed CS-based candidate detector exploits some prior knowledge of primary users, not only to relax the sampling bottleneck, but also to provide an estimation of the candidate signals' frequency, power and angle of arrival without reconstructing the whole spectrum. The second application is Through-the-Wall Radar Imaging (TWRI). Sensing through obstacles such as walls, doors, and other visually opaque materials, using microwave signals is emerging as a powerful tool supporting a range of civilian and military applications. High resolution imaging is achieved if large bandwidth signals and long antenna arrays are used. However, this implies acquisition and processing of large amounts of data volume. Decreasing the number of acquired samples can also be helpful in TWRI from a logistic point of view, as some of the data measurements in space and frequency can be difficult, or impossible to attain. In this thesis, we addressed the problem of imaging building interior structures using a reduced number of measurements. The proposed technique for the determination of the building layout is based on prior knowledge about common construction practices. Real data collection experiments in a laboratory environment, using Radar Imaging Lab facility at the Center for Advanced Communications, Villanova University, USA, are conducted to validate the proposed approach.

    La adquisición de datos es un tema fundamental en el procesamiento de señales. Hasta ahora, el teorema de Shannon-Nyquist ha sido el núcleo de los métodos convencionales de conversión analógico-digital. El teorema dice que para recuperar perfectamente la información, cualquier señal debe ser muestreada a una frecuencia constante igual al doble de la máxima frecuencia presente en la señal. Sin embargo, este teorema asume el peor de los casos: cuando las señales ocupan todo el espectro. En este contexto aparece la teoría del muestreo compresivo (conocido en inglés como Compressed Sensing (CS)). CS ha supuesto una auténtica revolución en lo que se refiere a la adquisición y muestreo de datos analógicos en un esfuerzo hacia resolver la problemática de recuperar un proceso continuo comprimible con un nivel suficiente de similitud si únicamente se realiza un número muy reducido de medidas o muestras del mismo. El requerimiento para el éxito de dicha técnica es que la señal debe poder expresarse de forma dispersa en algún dominio. Esto es, que la mayoría de sus componentes sean cero o puedan considerarse despreciables. La aplicación de este tipo de muestreo compresivo supone una línea de investigación de gran auge e interés investigador en áreas como la transmisión de datos, procesamiento de imágenes médicas, biología computacional, entre otras. A diferencia de la mayoría de publicaciones relacionadas con CS, en esta tesis se estudiará CS aplicado a detección, estimación y clasificación de señales, que no necesariamente requiere la recuperación perfecta ni completa de la señal. En concreto, se propone un nuevo detector basado en cierto conocimiento a priori sobre la señal a detectar. La idea básica es escanear el dominio de la señal con una señal llamada Candidata, que se obtiene a partir de la información a priori de la señal a detectar. Por lo tanto, el detector únicamente reaccionará cuando la señal candidata esté presente. El detector es aplicado a dos problemas particulares de detección. En primer lugar, la novedosa teoría de CS es aplicada al sensado de espectro o spectrum sensing, en el contexto de Radio Cognitiva (CR). El principal problema radica en que las políticas actuales de asignación de bandas frecuenciales son demasiado estrictas y no permiten un uso óptimo del espectro radioeléctrico disponible. El uso del espectro radioeléctrico puede ser mejorado significativamente si se posibilita que un usuario secundario (sin licencia) pueda acceder a un canal desocupado por un usuario primario en ciertas localizaciones y momentos temporales. La tecnología CR se ha identificado recientemente como una solución prometedora al denominado problema de escasez de espectro, es decir, la creciente demanda de espectro y su actual infrautilización. Un requerimiento esencial de los dispositivos cognitivos es la capacidad de detectar la presencia de usuarios primarios (para no causarles interferencia). Uno de los problemas que se afronta en este contexto es la necesidad de escanear grandes anchos de banda que requieren frecuencias de muestreo extremadamente elevadas. El detector propuesto basado en CS aprovecha los huecos libres de espectro no sólo para relajar los requerimientos de muestreo, sino también para proporcionar una estimación precisa de la frecuencia, potencia y ángulo de llegada de los usuarios primarios, todo ello sin necesidad de reconstruir el espectro. La segunda aplicación es en radar con visión a través de paredes (Through-the-Wall Radar Imaging - TWRI). Hace ya tiempo que la capacidad de ver a través de las paredes ya no es un asunto de ciencia ficción. Esto es posible mediante el envío de ondas de radio, capaces de atravesar objetos opacos, que rebotan en los objetivos y retornan a los receptores. Este es un tipo de radar con gran variedad de aplicaciones, tanto civiles como militares. La resolución de las imágenes proporcionadas por dichos radares mejora cuando se usan grandes anchos de banda y mayor número de antenas, lo que directamente implica la necesidad de adquirir un mayor número de muestras y un mayor volumen de datos que procesar. A veces, reducir el número de muestras es interesante en TWRI desde un punto de vista logístico, ya que puede que algunas muestras frecuenciales o espaciales sean difíciles o imposibles de obtener. En esta tesis focalizaremos el trabajo en la detección de estructuras internas como paredes internas para reconstruir la estructura del edificio. Las paredes y/o diedros formados por la intersección de dos paredes internas formaran nuestras señales candidatas para el detector propuesto. En general, las escenas de interiores de edificios están formadas por pocas estructuras internas dando paso a la aplicaci´on de CS. La validación de la propuesta se llevará a cabo con experimentos realizados en el Radar Imaging Lab (RIL) del Center for Advanced Communications (CAC), Villanova University, PA, USA

    L’adquisició de dades és un tema fonamental en el processament de senyals. Fins ara, el teorema de Shannon-Nyquist ha sigut la base dels mètodes convencionals de conversió analògic-digital. El teorema diu que per recuperar perfectament la informació, qualsevol senyal ha de ser mostrejada a una freqüència constant igual al doble de la màxima freqüència present a la senyal. No obstant, aquest teorema assumeix el pitjor dels casos: quan les senyals ocupen tot l’espectre. En aquest context apareix la teoria del mostreig compressiu (conegut en anglès amb el nom de Compressed Sensing (CS)). CS ha suposat una autèntica revolució pel que fa a l’adquisició i mostreig de dades analògiques en un esforç cap a resoldre la problemàtica de recuperar un procés continu comprimible amb un nivell suficient de similitud si únicament es realitza un número molt reduït de mesures o mostres del mateix. El requisit para l’èxit d’aquesta tècnica és que la senyal ha de poder ser expressada de forma dispersa en algun domini. Això és, que la majoria dels seus components siguin zero o puguin considerar-se despreciables. L’aplicació d’aquest tipus de mostreig compressiu suposa una l’ínia de investigació de gran interès en àrees com la transmissió de dades, el processament d’imatges mèdiques, biologia computacional, entre altres. A diferència de la majoria de publicacions relacionades amb CS, en aquesta tesi s’estudiarà CS aplicat a detecció, estimació i classificació de senyals, que no necessàriament requereix la recuperació perfecta ni completa de la senyal. En concret, es proposa un nou detector basat en cert coneixement a priori sobre la senyal a detectar. La idea bàsica és escanejar el domini de la senyal amb una senyal anomenada Candidata, que s’obté a partir de la informació a priori de la senyal a detectar. Per tant, el detector únicament reaccionarà quan la senyal candidata estigui present. El detector és aplicat a dos problemes particulars de detecció. En primer lloc, la teoria de CS és aplicada al sensat d’espectre o spectrum sensing, en el context de Radio Cognitiva (CR). El principal problema radica en que les polítiques actuals d’assignació de bandes freqüencials són massa estrictes i no permeten l’ús òptim de l’espectre radioelèctric disponible. L’ús de l’espectre radioelèctric pot ser significativament millorat si es possibilita que un usuari secundari (sense llicència) pugui accedir a un canal desocupat per un usuari primari en certes localitzacions i moments temporals. La tecnologia CR s’ha identificat recentment com una solució prometedora al problema d’escassetat d’espectre, és a dir, la creixent demanda d’espectre i la seva actual infrautilització. Un requeriment essencial dels dispositius cognitius és la capacitat de detectar la presència d’usuaris primaris (per no causar interferència). Un dels problemes que s’afronta en aquest context és la necessitat d’escanejar grans amples de banda que requereixen freqüències de mostreig extremadament elevades. El detector proposat basat en CS aprofita els espais buits lliures d’espectre no només per relaxar els requeriments de mostreig, sinó també per proporcionar una estimació precisa de la freqüència, potència i angle d’arribada dels usuaris primaris, tot això sense necessitat de reconstruir l’espectre. La segona aplicació ´es en radars amb visió a través de parets (Through-the-Wall Radar Imaging - TWRI). Ja fa un temps que la capacitat de veure a través de les parets no és un assumpte de ciència ficció. Això ´es possible mitjançant l’enviament d’ones de radio, capaços de travessar objectes opacs, que reboten en els objectius i retornen als receptors. Aquest és un tipus de radar amb una gran varietat d’aplicacions, tant civils como militars. La resolució de las imatges proporcionades per aquests radars millora quan s’usen grans amples de banda i més nombre d’antenes, cosa que directament implica la necessitat d’adquirir un major nombre de mostres i un major volum de dades que processar. A vegades, reduir el nombre mostres és interessant en TWRI des de un punt de vista logístic, ja que pot ser que algunes mostres freqüencials o espacials siguin difícils o impossibles d’obtenir. En aquesta tesis focalitzarem el treball en la detecció d’estructures internes com per exemple parets internes per reconstruir l’estructura de l’edifici. Les parets i/o díedres formats per la intersecció de dos parets internes formaran les nostres senyals candidates per al detector proposat. En general, les escenes d’interiors d’edificis estan formades per poques estructures internes donant pas a l’aplicació de CS. La validació de la proposta es durà a terme amb experiments realitzats en el Radar Imaging Lab (RIL) del Center for Advanced Communications (CAC), Villanova University, PA, USA

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    Determining building interior structures using compressive sensing  Open access

     Lagunas Targarona, Eva; Amin, Moeness G.; Ahmad, Fauzia; Najar Marton, Montserrat
    Journal of electronic imaging
    Date of publication: 2013-01-22
    Journal article

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    We consider imaging of the building interior structures using Compressive Sensing (CS) with applications to through-the-wall imaging and urban sensing. We consider a monostatic synthetic aperture radar imaging system employing stepped frequency waveform. The proposed approach exploits prior information of building construction practices to form an appropriate sparse representation of the building interior layout. We devise a dictionary of possible wall locations, which is consistent with the fact that interior walls are typically parallel or perpendicular to the front wall. The dictionary accounts for the dominant normal angle reflections from exterior and interior walls for the monostatic imaging system. Compressive sensing is applied to a reduced set of observations to recover the true positions of the walls. Additional information about interior walls can be obtained using a dictionary of possible corner reflectors, which is the response of the junction of two walls. Supporting results based on simulation and laboratory experiments are provided. It is shown that the proposed sparsifying basis outperforms the conventional through-the-wall CS model, the wavelet sparsifying basis, and the block sparse model for building interior layout detection.

  • Joint wall mitigation and compressive sensing for indoor image reconstruction

     Lagunas Targarona, Eva; Amin, Moeness G.; Ahmad, Fauzia; Najar Marton, Montserrat
    IEEE transactions on geoscience and remote sensing
    Date of publication: 2013-02
    Journal article

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    Compressive sensing (CS) for urban operations and through-the-wall radar imaging has been shown to be successful in fast data acquisition and moving target localizations. The research in this area thus far has assumed effective removal of wall elec- tromagnetic backscatterings prior to CS application. Wall clutter mitigation can be achieved using full data volume which is, how- ever, in contradiction with the underlying premise of CS. In this paper, we enable joint wall clutter mitigation and CS application using a reduced set of spatial-frequency observations in stepped frequency radar platforms. Specifically, we demonstrate that wall mitigation techniques, such as spatial filtering and subspace pro- jection, can proceed using fewer measurements. We consider both cases of having the same reduced set of frequencies at each of the available antenna locations and also when different frequency measurements are employed at different antenna locations. The latter casts a more challenging problem, as it is not amenable to wall removal using direct implementation of filtering or projection techniques. In this case, we apply CS at each antenna individually to recover the corresponding range profile and estimate the scene response at all frequencies. In applying CS, we use prior knowl- edge of the wall standoff distance to speed up the convergence of the orthogonal matching pursuit for sparse data reconstruction. Real data are used for validation of the proposed approach

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    Radio Context Awareness and Applications  Open access

     Reggiani, Luca; Fiorina, Jocelyn; Gezici, Sinan; Morosi, Simone; Najar Marton, Montserrat
    Journal of sensors
    Date of publication: 2013-01-01
    Journal article

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    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 added-value applications in the context of the next generation of wireless networks.

    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 added-value applications in the context of the next generation of wireless networks.

  • Assessment of direct positioning for IR-UWB in IEEE 802.15.4a channels

     Navarro, Mònica; Closas Gómez, Pau; Najar Marton, Montserrat
    IEEE International Conference on Ultra-WideBand
    Presentation's date: 2013-09
    Presentation of work at congresses

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    This paper assesses the problem of localization in IR-UWB under realistic channel models for Direct Position Estimation (DPE) approaches. DPE schemes have been proposed for positioning and localization for well developed systems like GNSS, where it has been analytically proved that the Maximum-likelihood single-step estimator outperforms two-step procedures. The extension to wideband systems and less favorable scenarios like indoor UWB channels is less explored. We derive a DPE algorithm and analyze its performance against two-step TOA based localization for an IR-UWB system. Numerical results are provided for IEEE 802.15.4a channel model showing positioning performance of the two approaches and highlighting the tradeoffs.

    This paper assesses the problem of localization in IR-UWB under realistic channel models for Direct Position Estimation (DPE) approaches. DPE schemes have been proposed for positioning and localization for well developed systems like GNSS, where it has been analytically proved that the Maximum-likelihood single-step estimator outperforms two-step procedures. The extension to wideband systems and less favorable scenarios like indoor UWB channels is less explored. We derive a DPE algorithm and analyze its performance against two-step TOA based localization for an IR-UWB system. Numerical results are provided for IEEE 802.15.4a channel model showing positioning performance of the two approaches and highlighting the tradeoffs.

  • Double shrinkage correction in sample LMMSE estimation

     Serra, Jordi; Najar Marton, Montserrat
    European Signal Processing Conference
    Presentation's date: 2013-09
    Presentation of work at congresses

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    The sample linear minimum mean square error (LMMSE) es- timator undergoes high performance degradation in the small sample size regime. Herein a double shrinkage correction is proposed to alleviate this problem. First, an afne transfor- mation of the sample covariance matrix (SCM) is considered within the LMMSE. Second, a linear transformation of that modied lter is proposed. The linear transformation mini- mizes the asymptotic MSE of the lter given a shrinkage of the SCM. And the shrinkage of the SCM optimizes the as- ymptotic MSE of the data covariance. Simulations highlight that the proposed estimator outperforms robust methods to the small sample size, namely LMMSE based on diagonal load- ing (DL) or Ledoit-Wolf (LW) regularizations of the SCM

    The sample linear minimum mean square error (LMMSE) es- timator undergoes high performance degradation in the small sample size regime. Herein a double shrinkage correction is proposed to alleviate this problem. First, an af ne transfor- mation of the sample covariance matrix (SCM) is considered within the LMMSE. Second, a linear transformation of that modi ed lter is proposed. The linear transformation mini- mizes the asymptotic MSE of the lter given a shrinkage of the SCM. And the shrinkage of the SCM optimizes the as- ymptotic MSE of the data covariance. Simulations highlight that the proposed estimator outperforms robust methods to the small sample size, namely LMMSE based on diagonal load- ing (DL) or Ledoit-Wolf (LW) regularizations of the SCM

  • Compressive spectrum sensing based on spectral shape feature detection

     Lagunas, Eva; Najar Marton, Montserrat
    International Symposium of Wireless Communication Systems
    Presentation's date: 2013-08
    Presentation of work at congresses

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    In this paper, we address sparsity-based spectrum sensing for Cognitive Radio (CR) applications. Motivated by the sparsity described by the low spectral occupancy of the licensed radios, the proposed approach utilizes the novel Compressive Sensing (CS) technique to alleviate the sampling burden in CR when processing very wide bandwidth. Instead of detecting underutilized subbands of the radio spectrum, this paper propose a feature-based strategy to detect the licensed holder activity from compressive measurements. The procedure follows the framework of correlation matching, changing the traditional single frequency scan to a spectral scan with the a priori known spectral shape of the licensed holder. In addition to the frequencylocation estimate, the proposed technique is able to provide a power-level estimate and an estimation of the angle-of-arrival (AoA) of the primary users by circumventing the complex nonlinear CS reconstruction.

    In this paper, we address sparsity-based spectrum sensing for Cognitive Radio (CR) applications. Motivated by the sparsity described by the low spectral occupancy of the licensed radios, the proposed approach utilizes the novel Compressive Sensing (CS) technique to alleviate the sampling burden in CR when processing very wide bandwidth. Instead of detecting underutilized subbands of the radio spectrum, this paper propose a feature-based strategy to detect the licensed holder activity from compressive measurements. The procedure follows the framework of correlation matching, changing the traditional single frequency scan to a spectral scan with the a priori known spectral shape of the licensed holder. In addition to the frequencylocation estimate, the proposed technique is able to provide a power-level estimate and an estimation of the angle-of-arrival (AoA) of the primary users by circumventing the complex nonlinear CS reconstruction.

  • Sparse covariance fitting for direction of arrival estimation

     Blanco, Luis; Najar Marton, Montserrat
    EURASIP Journal on Advances in Signal Processing
    Date of publication: 2012-05-17
    Journal article

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  • GRE3N-LINK-MAC. Conceptos radio generales para comunicaciones móviles eficientes energéticamente: aspectos de las capas de enlace y de acceso al medio

     Pérez Neira, Ana Isabel; Najar Marton, Montserrat; Caus López, Marius; Lagunas Targarona, Eva; Pascual Iserte, Antonio
    Participation in a competitive project

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  • Network of Excellence in Wireless COMmunications #

     Pascual Iserte, Antonio; Pérez Neira, Ana Isabel; Najar Marton, Montserrat; Agusti Comes, Ramon; Umbert Juliana, Anna; Casadevall Palacio, Fernando-jose; Sanchez Gonzalez, Juan; Pérez Romero, Jordi
    Participation in a competitive project

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    Sparse correlation matching-based spectrum sensing for open spectrum communications  Open access

     Lagunas Targarona, Eva; Najar Marton, Montserrat
    EURASIP Journal on Advances in Signal Processing
    Date of publication: 2012-02
    Journal article

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    To deal with the current spectrum scarcity problem and exploiting the fact that exclusive access through tightly regulated licensing leads to idle spectrum, cognitive radio has been proposed as a way to reuse this underutilized spectrum in an opportunistic manner, i.e., allowing the use of temporarily unused licensed spectrum to secondary users who have no spectrum licenses. To protect the licensed users from the cognitive users ’ interference, the opportunistic user requires knowledge of the original license holder activity. In this article, a feature-based approach for spectrum sensing based on periodic non-uniform sampling is addressed. In particular, we face the compressed-sampling version of detecting predetermined spectral shapes in sparse wideband regimes by means of a correlation-matching procedure.

  • Wall mitigation techniques for indoor sensing within the compressive sensing framework

     Lagunas Targarona, Eva; Amin, Moeness G.; Ahmad, Fauzia; Najar Marton, Montserrat
    IEEE Sensor Array and Multichannel Signal Processing Workshop
    Presentation's date: 2012
    Presentation of work at congresses

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  • Compressive sensing for through wall radar imaging of stationary scenes using arbitrary data measurements

     Lagunas Targarona, Eva; Amin, Moeness G.; Ahmad, Fauzia; Najar Marton, Montserrat
    International Conference on Information Science, Signal Processing and their Applications
    Presentation's date: 2012
    Presentation of work at congresses

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    In this paper, we deal with removal of wall EM reflections prior to image reconstruction using step-frequency radars. The goal is to enable behind-the-wall target detection and localization from reduced data measurements. In the underlying problem, few frequency observations are available and they differ from one antenna position to another in a SAR imaging system. Because of using a different set of frequencies for different antennas, direct applications of wall clutter mitigation methods, such as subspace and spatial filtering, prove ineffective. To provide these methods with the response measured at the same set of frequencies, a compressive sensing approach is used to reconstruct the range profiles. We use prior knowledge of the wall standoff distance to speed up the convergence of the Orthogonal Matching Pursuit for sparse data reconstruction.

  • Optimal linear correction in LMMSE estimation using moments of the complex inverse Wishart distribution

     Serra, Jordi; Najar Marton, Montserrat
    IEEE Statistical Signal Processing Workshop
    Presentation's date: 2012
    Presentation of work at congresses

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    The conventional linear minimum mean square error esti- mator (LMMSE) suffers a severe performance degradation whenever the sample size is comparable to the observation dimension. In order to tackle this problem, we propose an optimal linear correction of the conventional LMMSE, which minimizes the average mean square error (MSE) by using the moments of the complex inverse Wishart distribution. Numerical simulations highlight that the proposed estimator dramatically outperforms the conventional LMMSE in the small sample size regime

    The conventional linear minimum mean square error esti- mator (LMMSE) suffers a severe performance degradation whenever the sample size is comparable to the observation dimension. In order to tackle this problem, we propose an optimal linear correction of the conventional LMMSE, which minimizes the average mean square error (MSE) by using the moments of the complex inverse Wishart distribution. Numerical simulations highlight that the proposed estimator dramatically outperforms the conventional LMMSE in the small sample size regime

  • Sparsity-based radar imaging of building structures

     Lagunas, Eva; Amin, Moeness G.; Ahmad, Fauzia; Najar Marton, Montserrat
    European Signal Processing Conference
    Presentation's date: 2012-08
    Presentation of work at congresses

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    In this paper, we address imaging of the interior structure of a building using a reduced number of measurements in through-the-wall imaging and urban sensing applications. Unlike majority of the feature detection methods that are applied in the image domain, the proposed approach works in the data domain and exploits prior information of construction practices together with the sparsity described by the features. More specifically, the interior walls are assumed to be either parallel or perpendicular to the front wall and a dictionary of possible wall locations is proposed as a sparse representation of the scene. Compressive sensing is then applied to the reduced set of observations to recover the true positions of the walls. Supporting results based on laboratory experiments are provided.

    In this paper, we address imaging of the interior structure of a building using a reduced number of measurements in through-the-wall imaging and urban sensing applications. Unlike majority of the feature detection methods that are applied in the image domain, the proposed approach works in the data domain and exploits prior information of construction practices together with the sparsity described by the features. More specifically, the interior walls are assumed to be either parallel or perpendicular to the front wall and a dictionary of possible wall locations is proposed as a sparse representation of the scene. Compressive sensing is then applied to the reduced set of observations to recover the true positions of the walls. Supporting results based on laboratory experiments are provided.

  • Frequency domain joint TOA and DOA estimation in IR-UWB

     Navarro, M; Najar Marton, Montserrat
    IEEE transactions on wireless communications
    Date of publication: 2011-10
    Journal article

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  • COGNITIVE RADIO AND NETWORKING FOR COOPERATIVE COEXISTENCE OF HETEROGENEOUS WIRELESS NETWORKS

     Najar Marton, Montserrat
    Participation in a competitive project

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  • Casting signal processing to reall-world data

     Closas Gómez, Pau; Conti, Andrea; Dardari, Davide; Decarli, Nicoló; Falletti, Emanuela; Fernandez Prades, Carles; Gholami, Mohammad Reza; Najar Marton, Montserrat; Lagunas Targarona, Eva; Pini, Marco; Rydström, Mats; Sottile, Francesco; Ström, Erik G.
    Date of publication: 2011-10
    Book chapter

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    This chapter presents the results of a testing and validation activity carried out to analyze the performance of signal-processing techniques related to positioning and navigation. The steps included the setup of a measurement campaign and the setup of a shared database, the usage of this database to test algorithms, and the development of a software defined radio (SDR)-based architecture for a GNSS receiver, to be used for advanced laboratory tests on innovative GNSS-related signal processing algorithms. During the measurement campaign, a total of 22 ZigBee-based devices, model CC2430 made by Texas Instruments, were used to measure RSS values. Each of them is a single chip solution which integrates microprocessor and radio interface compliant with the IEEE 802.15.4 standard at 2.4 GHz. Two UWB-based devices, model PulsOn220 made by Time Domain, were used to perform TOA ranging measurements in both static and dynamic scenarios. During the test, the receiver in light-indoor condition could autonomously track only one satellite, identified as PRN 9. This PRN was also tracked by the aiding user; therefore, it was used to estimate the clock offset among the two PCs.

  • Fundamental limits in the accuracy of wireless positioning

     Bacci, Giacomo; Closas Gómez, Pau; D'Amico, Antonio; Dardari, Davide; Fernandez Prades, Carles; Fontanella, Diana; Gezici, Sinan; Luise, Marco; Mallat, Achraf; Mengali, Umberto; Najar Marton, Montserrat; Nicoli, Monica; Oestges, Claude; Vandendorpe, Luc
    Date of publication: 2011-10
    Book chapter

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  • Innovative signal processing techniques for wireless positioning

     Dardari, Davide; Di Dio, Mario; Emmanuele, Andrea; Fontanella, Diana; Gezici, Sinan; Gholami, Mohammad Reza; Kieffer, Michel; Lagunas Targarona, Eva; Louveaux, Jérôme; Mallat, Achraf; Najar Marton, Montserrat; Navarro, Mònica; Nicoli, Monica; Reggiani, Luca; Rydström, Mats; Ström, Erik G.; Vandendorpe, Luc; Zanier, Francesca
    Date of publication: 2011-10
    Book chapter

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  • Signal processing for hybridization

     Caceres Duran, Mauricio A.; Closas Gómez, Pau; Falletti, Emanuela; Fernandez Prades, Carles; Najar Marton, Montserrat; Sottile, Francesco
    Date of publication: 2011-10
    Book chapter

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    This chapter presents several signal processing strategies to combine together, in a seamless estimation process, position-related measurements coming from different technologies and/or systems (e.g., TOA and TDOA measurements in terrestrial networks, TOA and RSS measurements, or even satellite and terrestrial systems, or satellite and inertial navigation systems). This approach, generally indicated as “hybridization”, promises to provide better accuracy with respect to its stand-alone counterparts, or better availability thanks to the diversity of the employed technologies. For example, hybridization between satellite and inertial systems is expected to compensate for the respective fragilities of the two systems, namely the relatively high error variance of the former and the drift of the latter. The mathematical framework where hybridization is developed is Bayesian filtering: the generic structure is reviewed and the well-known Kalman filter and its variants are inserted in the framework, with examples of applications to positioning problems. Then the particle filter approach is explained, with its most used variants. Examples of hybrid localization algorithms are then shown, starting from a hybrid terrestrial architecture, then passing to the architectures that blend GNSS and inertial measurements, using either the Kalman filter approach or the direct position estimation approach. Finally, an example of hybrid localization based on GNSS and peer-to-peer terrestrial signaling is presented.

  • Access to the full text
    Prototyping with SDR: a quick way to play with next-gen communications systems  Open access

     Baranda, J.; Henarejos, Pol; Grunenberger, Yan; Najar Marton, Montserrat
    IEEE International Symposium on Wireless Communication Systems
    Presentation's date: 2011-11
    Presentation of work at congresses

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    Abstract—In this paper we present our approach regarding the implementation of new wireless radio receiver exploiting filterbank techniques, using a software-development driven approach. Since most of the common radio communications systems share a similar structure, this can be exploited creating a framework which provides a generic layout and tools to construct a reconfigurable transmitter and/or receiver. By combining the use of the Universal Software Radio Peripheral version 2 (USRP2) with a generic object-oriented framework of our own built on top of the GNU Radio software framework, we have been able to quickly implement a working proof of concept of an Uplink (UL) Filterbank Multicarrier (FBMC) receiver, both for Single- Input Single-Output (SISO) and Multiple-Input Multiple-Output (MIMO) scenario, within the project of the 7th European framework called PHYDYAS. We described here the methodology we have applied from software engineering in order to build this demonstrator, which shows the suitability of using Software Defined Radio (SDR) technologies for fast prototyping of new wireless communication systems.

  • Space-time-frequency candidate methods for spectrum sensing

     Lagunas Targarona, Eva; Najar Marton, Montserrat; Lagunas Hernandez, Miguel Angel
    European Signal Processing Conference
    Presentation's date: 2011-09
    Presentation of work at congresses

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    The basic idea behind Cognitive Radio (CR) is to allow unlicensed users to utilize licensed frequency bands when they do not interfere to the primary (licensed) users. Thus, an important requirement of CR systems is to sense the spectrum in order to obtain awareness about the spectrum usage. In this paper, a new spectral estimation procedure for monitoring the radio spectrum which exploits frequency, time and angle diversity is presented. The procedure is a feature-based method able to detect predetermined spectral shape, providing at the same time an estimate of its power level, an estimate of its frequency location and an estimate of its angle of arrival. The specific spectral shape is called the candidate spectrum and gives name to the different methods.

  • Energy efficiency communications over the AWGN relay channel

     Gomez-Vilardebo, Jesus; Pérez Neira, Ana Isabel; Najar Marton, Montserrat
    IEEE transactions on wireless communications
    Date of publication: 2010
    Journal article

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  • Access to the full text
    Energy efficient communications over the AWGN relay channel  Open access

     Gómez Vilardebó, Jesús; Pérez Neira, Ana Isabel; Najar Marton, Montserrat
    IEEE transactions on wireless communications
    Date of publication: 2010-01-08
    Journal article

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    This paper addresses the energy efficiency analysis of the relay channel under additive white Gaussian noise. We consider the rate bounds given by decode and forward and the cut set bound and assume that resources are optimally allocated to maximize the spectral efficiency according to the channel information and the sum network energy. The low energy analysis tools are used to compute the maximum rate per energy (RPE) and the slope of the spectral efficiency as a function of the energy per bit. Using these metrics, the energy efficiency benefit of several capabilities at terminals is investigated. Specifically, we take into account: i) the phase synchronization between transmitters, ii) the full duplex capability at the relay and iii) the channel access via superposition.

  • Minimum variance time of arrival estimation for positioning

     Blanco, Luis; Serra, Jordi; Najar Marton, Montserrat
    Signal processing
    Date of publication: 2010-08
    Journal article

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  • Access to the full text
    Performance of a filterBank multiCarrier (FBMC) physical layer in the WiMAX context  Open access

     Ringset, Vidar; Rustad, Helge; Schaich, Frank; Vandermont, Jurgen; Najar Marton, Montserrat
    Future Netwok and Mobile Summit
    Presentation of work at congresses

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    This paper describes some of the outcome of the FP7 project PHYDYAS, whose main objective was to propose a new physical layer that will enable introduction of cognitive radios and dynamic access spectrum management. During the project both a software simulator and a demonstrator have been developed. A description of the demonstrator and some simulation results that show the differences in spectral efficiency and the sensititvity to synchronisation errors between OFDM and FBMC are given. The simulator, which is written in Matlab, was used to evaluate the performance of both OFDM and FBMC in a WiMAX context, i.e. the frame format is kept as close as possible to WiMAX. From the simulation results it has been possible to analyze the performance differences between the two systems. In addition to that the simulator was used as a reference in the validation of the demonstrator. The transmitter in the demonstrator is implemented in hardware and operates in real time. The channel emulation and up-conversion to RF is done using commercially available instruments from Agilent which have been modified to fit to the task. In the demonstrator receiver the hardware front-end converts the signal to baseband and digitizes it. The OFDM/FBMC signal processing is done in near real time on a general purpose computer connected to the front- end hardware.

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    TOA Estimation in UWB: Comparison between time and frequency domain processing  Open access

     Lagunas Targarona, Eva; Taponecco, Lorenzo; Najar Marton, Montserrat; D'Amico, Antonio
    International ICST Conference on Mobile Lightweight Wireless Systems
    Presentation of work at congresses

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    A comparison between time and frequency domain TOA estimators compliant with the 802.15.4a Standard has been made. The time domain estimator is done in two stages. One has the goal of identify the rst pulse in each symbol interval and the other aims to acquire the start of frame delimiter. The frequency domain estimator is also based in two stages. A simple coarse estimation stage provides the symbol synchronization required by the ne estimation stage which nds the rst delay of the rst arriving path in a power delay pro le developed in the frequency domain by using high resolution spectral estimation techniques. An accuracy of few centimeters is asymptotically achieved by both estimators. While time domain estimator shows slightly more accurate results at high values of SNR, frequency domain estimators works slightly better at low SNR.1

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    Filter bank transceiver design for ultra wideband  Open access

     Ibars, C.; Navarro, Mònica; Fernandez Prades, Carles; Artiga, Xavier; Moragrega, Ana; George-Gavrincea, Ciprian; Mollfulleda, Antonio; Najar Marton, Montserrat
    Date of publication: 2010-09
    Book chapter

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    Joint TOA and DOA estimation compliant with IEEE 802.15.4a standard  Open access

     Lagunas Targarona, Eva; Najar Marton, Montserrat; Navarro, Mònica
    IEEE International Symposium on Wireless Pervasive Computing
    Presentation of work at congresses

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    Ultra-WideBand (UWB) technology offers the potential of achieving high ranging accuracy through signal Time-Of-Arrival (TOA) measurements, even in harsh enviroments due to its ability to resolve multipath and penetrate obstacles. This paper evaluates a joint TOA and DOA estimator compliant with the IEEE 802.15.4a Standard. The estimator proposed here is an adaptation of to comply with the Standard specifications. The estimation is developed in the frequency domain in order to exploit the high accurate time-based measures of the UWB signals.

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    Performance comparison between FBMC and OFDM in MIMO systems under channel uncertainty  Open access

     Pascual Iserte, Antonio; Najar Marton, Montserrat; Payaró Llisterri, Miquel
    European Wireless Conference
    Presentation's date: 2010-04
    Presentation of work at congresses

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  • FILTER-BANK MULTICARRIER TECHNOLOGIES FOR MULTI-ANTENNA TRANSCEIVERS

     Pascual Iserte, Antonio; Najar Marton, Montserrat; Caus López, Marius; Lagunas Targarona, Eva; Pérez Neira, Ana Isabel
    Participation in a competitive project

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  • Cramer-rao bound for time-delay estimation in the frequency domain

     Serra, Jordi; Blanco, Luis; Najar Marton, Montserrat
    European Signal Processing Conference
    Presentation's date: 2009
    Presentation of work at congresses

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    In this paper a measure of performance of time delay estimators arising from a frequency model of the received signal is presented. The aim is to derive theoretical analysis of the Cramer-Rao bound (CRB) for time delay estimation under realistic wireless channel propagation conditions. The derivation of the CRB is considered from the frequency domain signal model yielding a closed-form expression without imposing any constraints on the different propagation paths.

  • NEWCOM++ (Network of Excellence in Wireless Communications)

     Pérez Romero, Jordi; Umbert Juliana, Anna; Agusti Comes, Ramon; Casadevall Palacio, Fernando-jose; Sallent Roig, Jose Oriol; Ferrús Ferré, Ramon; López Benítez, Miguel; Bezerra Rodrigues, Emanuel; Gelonch Bosch, Antoni; Marojevic, Vuk; Gomez Miguelez, Ismael; Pérez Neira, Ana Isabel; Pascual Iserte, Antonio; Najar Marton, Montserrat
    Participation in a competitive project

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  • Sincronización y Demodulación en IR-UWB

     Navarro, Mònica; Najar Marton, Montserrat
    Simposium Nacional de la Unión Científica Internacional de Radio
    Presentation of work at congresses

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  • Conformal Transformation for efficient root-TOA estimatio

     Blanco, Luis; Jordi, Serra; Najar Marton, Montserrat
    Internacional Symposium on Communications, Control and Signal Processing
    Presentation of work at congresses

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  • Joint synchronization and demodulation for IR-UWB

     Najar Marton, Montserrat; Navarro, Mònica
    IEEE International Conference on Ultra-Wideband
    Presentation of work at congresses

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  • PHYDYAS. PHYsical layer for DYnamic AccesS and cognitive radio

     Najar Marton, Montserrat; Pascual Iserte, Antonio
    Participation in a competitive project

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  • Joint Demodulation and Synchronization in Ultra Wideband Systems

     Najar Marton, Montserrat; Navarro, Mònica
    Date of request: 2008-09-08
    Invention patent

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  • Joint TOA and DOA estimation for IR-UWB

     Navarro, Mònica; Najar Marton, Montserrat
    8th IEEE Workshop on Signal Processing Advances in Wireless Communications
    Presentation of work at congresses

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  • Root Minimum Variance TOA estimation for wireless location

     Blanco, Luis; Jordi, Serra; Najar Marton, Montserrat
    European Signal Processing Conference
    Presentation of work at congresses

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  • TOA and DOA Estimation for Positioning and Tracking in IR-UWB

     Navarro, Mònica; Najar Marton, Montserrat
    IEEE International Conference on Ultra-Wideband
    Presentation of work at congresses

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  • Signal processing in UWB communications - Editorial

     Najar Marton, Montserrat; Navarro, Mònica
    Signal processing
    Date of publication: 2006-09
    Journal article

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  • Definición y evaluación de algoritmos de posicionamiento

     Najar Marton, Montserrat; Navarro, Mònica
    Date: 2006-03
    Report

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  • Algoritmos de Ranging: Definición y Evaluación

     Navarro, Mònica; Najar Marton, Montserrat
    Date: 2006-03
    Report

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  • Low Complexity Frquency Domain TOA Estimation for IR-UWB Communicactions

     Navarro, Mònica; Simon, Prior; Najar Marton, Montserrat
    IEEE Vehicular Technology Conference
    Presentation of work at congresses

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  • Root spectral estimation for location based on TOA

     Blanco, Luis; Jordi, Serra; Najar Marton, Montserrat
    European Signal Processing Conference
    Presentation of work at congresses

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  • Unscented Kalman Filter for location in Non-Line-Of-Sight

     Bosch, Marc; Najar Marton, Montserrat
    European Signal Processing Conference
    Presentation of work at congresses

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  • QUETZAL: Qualified Ultra-wideband Testbed For Reduced Data-rates And Location

     Mollfulleda, Antonio; Najar Marton, Montserrat; Miskovsky, Pavel; Anton, Joan Leyva; Berenguer Comas, Luis; Christian, Ibars; Navarro, Mònica
    2nd International IEEE/Create-Net Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities
    Presentation of work at congresses

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  • Low complexity TOA estimation for wireless location

     Blanco, Luis; Jordi, Serra; Najar Marton, Montserrat
    IEEE Global Communications Conference
    Presentation of work at congresses

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