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  • A rate-splitting approach to fading channels with imperfect channel-state information

     Pastore, Adriano; Koch, Tobias; Rodriguez Fonollosa, Javier
    IEEE transactions on information theory
    Vol. 60, num. 7, p. 4266-4285
    DOI: 10.1109/TIT.2014.2321567
    Date of publication: 2014-07
    Journal article

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    As shown by Médard, the capacity of fading channels with imperfect channel-state information can be lower-bounded by assuming a Gaussian channel input X with power P and by upper-bounding the conditional entropy h(X|Y,H) by the entropy of a Gaussian random variable with variance equal to the linear minimum mean-square error in estimating X from \(Y, H). We demonstrate that, using a rate-splitting 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 rate-splitting 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 Gaussian-input mutual information as the signal-to-noise ratio (SNR) grows, provided that the variance of the channel estimation error H-H tends to zero as the SNR tends to infinity.

    As shown by Médard, the capacity of fading channels with imperfect channel-state information can be lower-bounded by assuming a Gaussian channel input X with power P and by upper-bounding the conditional entropy h(X|Y,H) by the entropy of a Gaussian random variable with variance equal to the linear minimum mean-square error in estimating X from \(Y, H). We demonstrate that, using a rate-splitting 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 rate-splitting 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 Gaussian-input mutual information as the signal-to-noise ratio (SNR) grows, provided that the variance of the channel estimation error H-H tends to zero as the SNR tends to infinity.

  • Noncooperative day-ahead bidding strategies for demand-side expected cost minimization with real-time adjustments: a GNEP approach

     Atzeni, Italo; Garcia Ordoñez, Luis; Scutari, Gesualdo; Palomar, Daniel P.; Rodriguez Fonollosa, Javier
    IEEE transactions on signal processing
    Vol. 62, num. 9, p. 2397-2412
    DOI: 10.1109/TSP.2014.2307835
    Date of publication: 2014-05-01
    Journal article

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    The envisioned smart grid aims at improving the interaction between the supply-and the demand-side 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 demand-side 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 day-ahead market and are interested in deriving the bidding, production, and storage strategies that jointly minimize their expected monetary expense. The resulting day-ahead 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 real-time deviations with respect to the amount of energy negotiated in the day-ahead. Finally, numerical results in realistic scenarios are reported to corroborate the proposed DSM technique.

    The envisioned smart grid aims at improving the interaction between the supply-and the demand-side 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 demand-side 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 day-ahead market and are interested in deriving the bidding, production, and storage strategies that jointly minimize their expected monetary expense. The resulting day-ahead 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 real-time deviations with respect to the amount of energy negotiated in the day-ahead. Finally, numerical results in realistic scenarios are reported to corroborate the proposed DSM technique.

  • Técnicas distribuidas para la gestión y operación de redes de comunicaciones celulares inalámbricas, de sensores y de la red eléctrica

     Cabrera Bean, Margarita Asuncion; Fernandez Rubio, Juan-antonio; Muñoz Medina, Olga; Rodriguez Fonollosa, Javier; Vidal Manzano, Jose; Agustin de Dios, Adrian; Garcia Ordoñez, Luis; Silva Pereira, Silvana; Perez Palomar, Daniel; Pages Zamora, Alba Maria
    Competitive project

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  • Distributed demand-side optimization in the Smart grid  Open access

     Atzeni, Italo
    Department of Signal Theory and Communications, Universitat Politècnica de Catalunya
    Theses

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    La xarxa elèctrica moderna s'enfronta a enormes reptes en la transició cap a un sector energètic de baixa generació de carboni. La creixent demanda d'energia i les preocupacions ambientals requereixen revisar acuradament com es genera, transmet, i consumeix l'electricitat, amb l'objectiu de la integració de les fonts d'energia renovables. S'espera que el concepte de smart grid pugui abordar aquestes qüestions mitjançant la introducció d'informació avançada, control i tecnologies de la comunicació en la infraestructura energètica. En aquest context, el concepte de gestió de la demanda (DSM) fa que els usuaris finals siguin responsables de millorar l'eficiència, la fiabilitat i la sostenibilitat del sistema de potència obrint possibilitats sense precedents per a l'optimització de l'ús i el cost de l'energia en els diferents nivells de la xarxa. El disseny de tècniques de DSM s'ha debatut àmpliament en la literatura durant l'última dècada, tot i que el rendiment d'aquests mètodes ha estat poc investigat des del punt de vista analític. En aquesta tesi es considera la demanda de la xarxa elèctrica com un sistema multiusuari format per consumidors actius amb capacitats de DSM i es proposa un marc general per analitzar i resoldre problemes de gestió. Donat que els mètodes de solució centralitzats són excessivament exigents per a aplicacions pràctiques per la seva complexitat computacional i al inherent sobrecost de comunicació, ens centrem en el desenvolupament d'algorismes distribuïts, amb especial èmfasi en temes crucials com la velocitat de convergència, l'intercanvi d'informació, l'escalabilitat i la privacitat. En aquest sentit, oferim un rigorós anàlisi teòric de les condicions que garanteixen l'existència de solucions òptimes i la convergència dels algorismes proposats. Entre la gran quantitat de mètodes de DSM, els programes de programació del consum d'energia ( ECS ) permeten modificar el perfil de la demanda dels usuaris a través de la reprogramació de càrregues flexibles durant hores de baix consum. D'altra banda, la incorporació de generació distribuïda ( DG ) i d'emmagatzematge distribuït ( DS ) ha demostrat ser igualment eficaç disminuint la relació entre potència de pic i mitja de la corba de demanda, evitant els inconvenients introduïts pel ECS als usuaris. Sorprenentment, si bé que la literatura s'ha concentrat sobretot en les tècniques de ECS, les tècniques de DSM basades en DG i DS no han atret l'atenció merescuda malgrat el seu potencial de conformació de la càrrega i la seva capacitat de facilitar la integració de les fonts renovables. En aquesta tesi, omplim aquest buit i elaborem models precisos de DSM per estudiar l'impacte de DG i DS a nivell dels usuaris finals i de tota la infraestructura elèctrica . Tenint present aquest objectiu, fem front a diversos escenaris de DSM, partint d'una optimització sobre les previsions amb un dia d'antelació (day-ahead). Es considera des del cas determinista amb restriccions locals fins al cas estocàstic combinat amb ajustos en temps real i amb restriccions locals i globals. Cada tasca es complementa amb la definició de models de xarxa i de tarifació apropiats que permetin la posada en pràctica del paradigma de DSM en entorns realistes del mercat energètic. En aquest sentit vam dissenyar marcs d'optimització de DSM globals i orientats als usuaris, que són respectivament aplicables a situacions de mercat competitives i regulades externament. Els resultats numèrics reportats corroboren els esquemes distribuïts presentats. D'una banda, les despeses d'electricitat dels usuaris es redueixen de forma consistent, el que fomenta la seva participació activa en els programes de DSM proposats; per una altra banda, aquesta optimització resulta en un cost de generació inferior i millora la robustesa de tota la xarxa.

    Tesi per compendi de publicacions. DOI els articles publicats per IEEE: 10.1109/TSG.2012.2206060, 10.1109/TSP.2013.2248002, 10.1109/TSP.2014.2307835

    The modern power grid is facing major challenges in the transition to a low-carbon energy sector. The growing energy demand and environmental concerns require carefully revisiting how electricity is generated, transmitted, and consumed, with an eye to the integration of renewable energy sources. The envisioned smart grid is expected to address such issues by introducing advanced information, control, and communication technologies into the energy infrastructure. In this context, demand-side management (DSM) makes the end users responsible for improving the efficiency, reliability and sustainability of the power system: this opens up unprecedented possibilities for optimizing the energy usage and cost at different levels of the network. The design of DSM techniques has been extensively discussed in the literature in the last decade, although the performance of these methods has been scarcely investigated from the analytical point of view. In this thesis, we consider the demand-side of the electrical network as a multiuser system composed of coupled active consumers with DSM capabilities and we propose a general framework for analyzing and solving demand-side management problems. Since centralized solution methods are too demanding in most practical applications due to their inherent computational complexity and communication overhead, we focus on developing efficient distributed algorithms, with particular emphasis on crucial issues such as convergence speed, information exchange, scalability, and privacy. In this respect, we provide a rigorous theoretical analysis of the conditions ensuring the existence of optimal solutions and the convergence of the proposed algorithms. Among the plethora of DSM methods, energy consumption scheduling (ECS) programs allow to modify the user's demand profile by rescheduling flexible loads to off-peak hours. On the other hand, incorporating dispatchable distributed generation (DG) and distributed storage (DS) into the demand-side of the network has been shown to be equally successful in diminishing the peak-to-average ratio of the demand curve, plus overcoming the limitations in terms users' inconvenience introduced by ECS. Quite surprisingly, while the literature has mostly concentrated on ECS techniques, DSM approaches based on dispatchable DG and DS have not attracted the deserved attention despite their load-shaping potential and their capacity to facilitate the integration of renewable sources. In this dissertation, we fill this gap and devise accurate DSM models to study the impact of dispatchable DG and DS at the level of the end users and on the whole electricity infrastructure. With this objective in mind, we tackle several DSM scenarios, starting from a deterministic day-ahead optimization with local constraints and culminating with a stochastic day-ahead optimization combined with real-time adjustments under both local and global requirements. Each task is complemented by defining appropriate network and pricing models that enable the implementation of the DSM paradigm in realistic energy market environments. In this regard, we design both user-oriented and holistic-based DSM optimization frameworks, which are respectively applicable to competitive and externally regulated market scenarios. Numerical results are reported to corroborate the presented distributed schemes. On the one hand, the users' electricity expenditures are consistently reduced, which encourages their active and voluntary participation in the proposed DSM programs; on the other hand, this results in a lower generation costs and enhances the robustness of the whole grid.

    La xarxa elèctrica moderna s'enfronta a enormes reptes en la transició cap a un sector energètic de baixa generació de carboni. La creixent demanda d'energia i les preocupacions ambientals requereixen revisar acuradament com es genera, transmet, i consumeix l'electricitat, amb l'objectiu de la integració de les fonts d'energia renovables. S'espera que el concepte de smart grid pugui abordar aquestes qüestions mitjançant la introducció d’informació avançada, control i tecnologies de la comunicació en la infraestructura energètica. En aquest context, el concepte de gestió de la demanda (DSM) fa que els usuaris finals siguin responsables de millorar l’eficiència, la fiabilitat i la sostenibilitat del sistema de potència obrint possibilitats sense precedents per a l’optimització de l’ús i el cost de l'energia en els diferents nivells de la xarxa. El disseny de tècniques de DSM s'ha debatut àmpliament en la literatura durant l’ultima dècada, tot i que el rendiment d'aquests mètodes ha estat poc investigat des del punt de vista analític. En aquesta tesi es considera la demanda de la xarxa elèctrica com un sistema multiusuari format per consumidors actius amb capacitats de DSM i es proposa un marc general per analitzar i resoldre problemes de gestió. Donat que els mètodes de solució centralitzats són excessivament exigents per a aplicacions pràctiques per la seva complexitat computacional i al inherent sobrecost de comunicació, ens centrem en el desenvolupament d'algorismes distribuïts, amb especial èmfasi en temes crucials com la velocitat de convergència, l'intercanvi d’informació, l'escalabilitat i la privacitat. En aquest sentit, oferim un rigorós anàlisi teòric de les condicions que garanteixen l’existència de solucions òptimes i la convergència dels algorismes proposats. Entre la gran quantitat de mètodes de DSM, els programes de programació del consum d'energia (ECS) permeten modificar el perfil de la demanda dels usuaris a través de la reprogramació de càrregues flexibles durant hores de baix consum. D'altra banda, la incorporació de generació distribuïda (DG) i d'emmagatzematge distribuït (DS) ha demostrat ser igualment eficaç disminuint la relació entre potència de pic i mitja de la corba de demanda, evitant els inconvenients introduïts pel ECS als usuaris. Sorprenentment, si bé que la literatura s'ha concentrat sobretot en les tècniques de ECS, les tècniques de DSM basades en DG i DS no han atret l’atenció merescuda malgrat el seu potencial de confirmació de la càrrega i la seva capacitat de facilitar la integració de les fonts renovables. En aquesta tesi, omplim aquest buit i elaborem models precisos de DSM per estudiar l'impacte de DG i DS a nivell dels usuaris finals i de tota la infraestructura elèctrica . Tenint present aquest objectiu, fem front a diversos escenaris de DSM, partint d'una optimització sobre les previsions amb un dia d’antelació (day-ahead). Es considera des del cas determinista amb restriccions locals fins al cas estocàstic combinat amb ajustos en temps real i amb restriccions locals i globals. Cada tasca es complementa amb la definició de models de xarxa i de tarifació apropiats que permetin la posada en pràctica del paradigma de DSM en entorns realistes del mercat energètic. En aquest sentit vam dissenyar marcs d’optimització de DSM globals i orientats als usuaris, que són respectivament aplicables a situacions de mercat competitives i regulades externament. Els resultats numèrics reportats corroboren els esquemes distribuïts presentats. D'una banda, les despeses d'electricitat dels usuaris es redueixen de forma consistent, el que fomenta la seva participació activa en els programes de DSM proposats; per una altra banda, aquesta optimització resulta en un cost de generació inferior i millora la robustesa de tota la xarxa.

    La red eléctrica moderna se enfrenta a enormes retos en la transición hacia un sector energético de baja generación de carbono. La creciente demanda de energía y las preocupaciones ambientales requieren revisar cuidadosamente cómo se genera, transmite y consume la electricidad, con vista a la integración de las fuentes de energía renovable. Se espera que el concepto de smart grid pueda abordar estas cuestiones mediante la introducción de información avanzada, control y tecnologías de la comunicación en la infraestructura energética. En este contexto, el concepto de gestión de la demanda (DSM) hace que los usuarios finales sean responsables de mejorar la eficiencia, la fiabilidad y la sostenibilidad del sistema de potencia abriéndose posibilidades sin precedentes para la optimización del uso y el coste de la energía en los diferentes niveles de la red. El diseño de técnicas de DSM se ha debatido ampliamente en la literatura en la última década, aunque el rendimiento de estos métodos ha sido poco investigado desde el punto de vista analítico. En esta tesis se considera la demanda de la red eléctrica como un sistema multiusuario compuesto por consumidores activos con capacidades de DSM y se propone un marco general para analizar y resolver problemas de gestión de demanda. Dado que los métodos de solución centralizados son excesivamente exigentes para aplicaciones prácticas debido a su complejidad computacional y al inherente sobrecoste de comunicación, nos centramos en el desarrollo de algoritmos distribuidos, con especial énfasis en temas cruciales como la velocidad de convergencia, el intercambio de información, la escalabilidad y la privacidad. En este sentido, ofrecemos un riguroso análisis teórico de las condiciones que garantizan la existencia de soluciones óptimas y la convergencia de los algoritmos propuestos. Entre la gran cantidad de métodos de DSM, los programas de programación del consumo de energía (ECS) permiten modificar el perfil de la demanda de los usuarios a través de la reprogramación de cargas flexibles durante horas de bajo consumo. Por otro lado, la incorporación de generación distribuida (DG) y de almacenamiento distribuido (DS) ha demostrado ser igualmente eficaz disminuyendo la relación entre potencia de pico y media de la curva de demanda, evitando los inconvenientes introducidos por el ECS a los usuarios. Sorprendentemente, mientras que la literatura se ha concentrado sobre todo en las técnicas de ECS, los programas de DSM basados en DG y DS no han atraído la atención merecida a pesar de su potencial de conformación de la carga y su capacidad de facilitar la integración de las fuentes renovables. En esta tesis, llenamos este vacío y elaboramos modelos precisos de DSM para estudiar el impacto de DG y DS a nivel de los usuarios finales y de toda la infraestructura eléctrica. Teniendo presente este objetivo, hacemos frente a varios escenarios de DSM, a partir de una optimización sobre las previsiones con un día de antelación (day-ahead). Se considera desde el caso determinista con restricciones locales hasta el caso estocástico combinado con ajustes en tiempo real y con restricciones locales y globales. Cada tarea se complementa con la definición de modelos de red y de tarificación apropiados que permitan la puesta en práctica del paradigma de DSM en entornos realistas del mercado energético. En este sentido diseñamos marcos de optimización de DSM globales y orientados a los usuarios, que son respectivamente aplicables a situaciones de mercado competitivas y reguladas externamente. Los resultados numéricos reportados corroboran los esquemas distribuidos presentados. Por un lado, los gastos de electricidad de los usuarios se reducen de forma consistente, lo que fomenta su participación activa en los programas de DSM propuestos; por otra parte, esta optimización resulta en un coste de generación inferior y mejora la robustez de toda la red

  • Communication Rates for Fading Channels with Imperfect Channel-State Information

     Pastore, Adriano
    Department of Signal Theory and Communications, Universitat Politècnica de Catalunya
    Theses

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    Aquesta tesi estudia les taxes d'informació per la transmissió fiable d'informació en canals amb esvaïments sota la hipòtesi realista de que el receptor té un coneixement tan sols imperfecte de l'esvaïment aleatori. De particular interès són les expressions analítiques de les taxes de transmissió assolibles amb coneixement imperfecte i sense coneixement de l'estat del canal, és a dir, cotes inferiors de la informació mútua i de la capacitat de Shannon. Una cota inferior de la informació mútua per a codis gaussians ben coneguda s'obté combinant el soroll additiu (tèrmic) amb el terme de soroll multiplicatiu causat per les imperfeccions del coneixement de l'estat del canal en un únic soroll efectiu, i assumint que el soroll és gaussià i independent. Aquesta aproximació del pitjor soroll permet obtenir una expressió molt simple i ben coneguda de la informació mútua del canal.Una primera part d'aquesta tesi proposa un procediment senzill per a millorar aquesta cota associada al pitjor cas mitjançant una estratègia de repartiment de taxa: expressant l'entrada gaussiana del canal com a la suma de diverses entrades gaussianes independents i suposant que el receptor realitza una descodificació seqüencial dels fluxos d'informació, es mostra com obtenir una major cota inferior de la informació mútua del canal. En canals amb una única antena en transmissió, la distribució òptima de potència als diferents fluxos s'obté quan el seu nombre (capes) tendeix a infinit, i la potència associada a cada capa tendeix a zero. El límit associat a un nombre infinit de capes dóna lloc a una expressió integral de la cota de la informació mútua. En canals amb múltiples antenes s'obté un resultat similar. No obstant això, atès que la utilització de múltiples antenes proporciona més possibilitats de multiplexat espacial, el procediment dóna lloc a tota una família de cotes inferiors de la informació mútua associades a una combinació de capes infinita.S'estudia en detall aquesta família de cotes per al cas de coeficients d'esvaïments gaussians de mitjana zero, independents i idènticament distribuïts (conegut com esvaïment i.i.d. Rayleigh). S'obtenen diverses propietats de la família de cotes. És important destacar que per a coneixement asimptòtic perfecte del canal en recepció, qualsevol membre de la família de cotes és asimptòticament ajustat per alta relació senyal a soroll (SNR). En concret, la diferència entre la informació mútua i la seva cota inferior tendeix a zero quan la SNR tendeix a infinit sempre que el coneixement del canal tendeixi a ser exacte a mesura que la SNR tendeix a infinit.Una segona part d'aquesta tesi proposa un marc per a l'optimització d'una classe de funcions d'utilitat en canals amb múltiples antenes i esvaïments Rayleigh per blocs amb correlació en transmissió i sense informació sobre el canal a recepció. Una fracció temporal de cada bloc d'esvaïment es reserva per transmetre una seqüència de símbols d'entrenament mentre que la resta de mostres temporals s'utilitzen per transmetre informació. El receptor estima la matriu del canal partint de la seva observació sorollosa i descodifica la informació mitjançant la seva estimació del canal. Per a una classe de funcions d'utilitat que són funcions simètriques dels autovalors de la SNR matricial efectiva, els problemes consistents en optimitzar la seqüència pilot i el precodificador lineal són transformats en problemes convexos (o quasi-convexos) per a funcions d'utilitat còncaves (o quasi-còncaves). També s'estudia un subproblema important de l'optimització conjunta, que consisteix en el càlcul de les seqüències d'entrenament i dels precodificadors conjuntament Pareto-òptims. Integrant aquests procediments d'optimització en una iteració cíclica, s'obté un algoritme que convergeix a un òptim local conjunt per a qualsevol utilitat quasi-còncava.

  • A rate-splitting approach to fading multiple-access channels with imperfect channel-state information

     Pastore, Adriano; Koch, Tobias; Rodriguez Fonollosa, Javier
    International Zurich Seminar on Communications
    p. 9-12
    Presentation's date: 2014-02-26
    Presentation of work at congresses

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    As shown by Medard, the capacity of fading channels with imperfect channel-state information (CSI) can be lowerbounded by assuming a Gaussian channel input and by treating the unknown portion of the channel multiplied by the channel input as independent worst-case (Gaussian) noise. Recently, we have demonstrated that this lower bound can be sharpened by a rate-splitting approach: by expressing the channel input as the sum of two independent Gaussian random variables (referred to as layers), say X = X1+X2, and by applying M´edard¿s bounding technique to first lower-bound the capacity of the virtual channel from X1 to the channel output Y (while treating X2 as noise), and then lower-bound the capacity of the virtual channel from X2 to Y (while assuming X1 to be known), one obtains a lower bound that is strictly larger than M´edard¿s bound. This ratesplitting approach is reminiscent of an approach used by Rimoldi and Urbanke to achieve points on the capacity region of the Gaussian multiple-access channel (MAC). Here we blend these two rate-splitting approaches to derive a novel inner bound on the capacity region of the memoryless fading MAC with imperfect CSI. Generalizing the above rate-splitting approach to more than two layers, we show that, irrespective of how we assign powers to each layer, the supremum of all rate-splitting bounds is approached as the number of layers tends to infinity, and we derive an integral expression for this supremum. We further derive an expression for the vertices of the best inner bound, maximized over the number of layers and over all power assignments.

    As shown by Medard, the capacity of fading channels with imperfect channel-state information (CSI) can be lowerbounded by assuming a Gaussian channel input and by treating the unknown portion of the channel multiplied by the channel input as independent worst-case (Gaussian) noise. Recently, we have demonstrated that this lower bound can be sharpened by a rate-splitting approach: by expressing the channel input as the sum of two independent Gaussian random variables (referred to as layers), say X = X1+X2, and by applying M´edard’s bounding technique to first lower-bound the capacity of the virtual channel from X1 to the channel output Y (while treating X2 as noise), and then lower-bound the capacity of the virtual channel from X2 to Y (while assuming X1 to be known), one obtains a lower bound that is strictly larger than M´edard’s bound. This ratesplitting approach is reminiscent of an approach used by Rimoldi and Urbanke to achieve points on the capacity region of the Gaussian multiple-access channel (MAC). Here we blend these two rate-splitting approaches to derive a novel inner bound on the capacity region of the memoryless fading MAC with imperfect CSI. Generalizing the above rate-splitting approach to more than two layers, we show that, irrespective of how we assign powers to each layer, the supremum of all rate-splitting bounds is approached as the number of layers tends to infinity, and we derive an integral expression for this supremum. We further derive an expression for the vertices of the best inner bound, maximized over the number of layers and over all power assignments.

  • Demand-side management via distributed energy generation and storage optimization

     Atzeni, Italo; Garcia Ordoñez, Luis; Scutari, Gesualdo; Palomar, Daniel P.; Rodriguez Fonollosa, Javier
    IEEE Transactions on Smart Grid
    Vol. 4, num. 2, p. 866-876
    DOI: 10.1109/TSG.2012.2206060
    Date of publication: 2013-06
    Journal article

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    Demand-side management, together with the integration of distributed energy generation and storage, are considered increasingly essential elements for implementing the smart grid concept and balancing massive energy production from renewable sources. We focus on a smart grid in which the demand-side comprises traditional users as well as users owning some kind of distributed energy sources and/or energy storage devices. By means of a day-ahead optimization process regulated by an independent central unit, the latter users intend to reduce their monetary energy expense by producing or storing energy rather than just purchasing their energy needs from the grid. In this paper, we formulate the resulting grid optimization problem as a noncooperative game and analyze the existence of optimal strategies. Furthermore, we present a distributed algorithm to be run on the users' smart meters, which provides the optimal production and/or storage strategies, while preserving the privacy of the users and minimizing the required signaling with the central unit. Finally, the proposed day-ahead optimization is tested in a realistic situation.

  • Noncooperative and cooperative optimization of distributed energy generation and storage in the demand-side of the smart grid

     Atzeni, Italo; Garcia Ordoñez, Luis; Scutari, Gesualdo; Palomar, Daniel P.; Rodriguez Fonollosa, Javier
    IEEE transactions on signal processing
    Vol. 61, num. 10, p. 2454-2472
    DOI: 10.1109/TSP.2013.2248002
    Date of publication: 2013-05
    Journal article

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    The electric energy distribution infrastructure is undergoing a startling technological evolution with the development of the smart grid concept, which allows more interaction between the supply-and the demand-side of the network and results in a great optimization potential. In this paper, we focus on a smart grid in which the demand-side comprises traditional users as well as users owning some kind of distributed energy source and/or energy storage device. By means of a day-ahead demand-side management mechanism regulated through an independent central unit, the latter users are interested in reducing their monetary expense by producing or storing energy rather than just purchasing their energy needs from the grid. Using a general energy pricing model, we tackle the grid optimization design from two different perspectives: a user-oriented optimization and an holistic-based design. In the former case, we optimize each user individually by formulating the grid optimization problem as a noncooperative game, whose solution analysis is addressed building on the theory of variational inequalities. In the latter case, we focus instead on the joint optimization of the whole system, allowing some cooperation among the users. For both formulations, we devise distributed and iterative algorithms providing the optimal production/storage strategies of the users, along with their convergence properties. Among all, the proposed algorithms preserve the users' privacy and require very limited signaling with the central unit.

  • Rate balancing in the vector BC with erroneous CSI at the receivers

     Joham, Michael; Gründinger, Andreas; Pastore, Adriano; Rodriguez Fonollosa, Javier; Utschick, Wolfgang
    Conference on Information Sciences and Systems
    p. 1-6
    DOI: 10.1109/CISS.2013.6552294
    Presentation's date: 2013
    Presentation of work at congresses

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    For the vector broadcast channel (BC), the case of erroneous channel state information (CSI) at the receiver is considered. Employing a well established lower bound for the mutual information with Gaussian signaling, a rate balancing problem is formulated where the rates of the different users are maximized under a transmit power constraint, but the rates of the different users have fixed ratios. A duality w.r.t. the signal-to-interference-and-noise ratio (SINR) between the vector BC with erroneous receiver CSI and an appropriately constructed vector multiple access channel (MAC) is established. Based on the observation that an interference function can be defined in the dual vector MAC that is standard, an iterative algorithm can be found for an appropriately formulated quality-of-service (QoS) optimization that is used for solving the balancing problem.

    For the vector broadcast channel (BC), the case of erroneous channel state information (CSI) at the receiver is considered. Employing a well established lower bound for the mutual information with Gaussian signaling, a rate balancing problem is formulated where the rates of the different users are maximized under a transmit power constraint, but the rates of the different users have fixed ratios. A duality w.r.t. the signal-to-interference-and-noise ratio (SINR) between the vector BC with erroneous receiver CSI and an appropriately constructed vector multiple access channel (MAC) is established. Based on the observation that an interference function can be defined in the dual vector MAC that is standard, an iterative algorithm can be found for an appropriately formulated quality-of-service (QoS) optimization that is used for solving the balancing problem.

  • Cooperative day-ahead bidding strategies for demand-side expected cost minimization

     Atzeni, Italo; Garcia Ordoñez, Luis; Scutari, Gesualdo; Palomar, Daniel P.; Rodriguez Fonollosa, Javier
    IEEE International Conference on Acoustics, Speech, and Signal Processing
    p. 5224-5228
    DOI: 10.1109/ICASSP.2013.6638659
    Presentation's date: 2013-05-30
    Presentation of work at congresses

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    The envisioned smart grid aims to improve the interaction between the supply-side and demand-side of the network, resulting in a great optimization potential. In this paper, we propose an holisticbased, fully distributed day-ahead DSM method where active users, i.e., subscribers participating actively in the bidding process, are interested in accurately deriving the bidding strategies that minimize their expected monetary expense and simultaneously optimize eventual energy generation and storage strategies. With this objective in mind, such users are allowed to collaborate in order to increase their saving with respect to the correspondent user-oriented optimization. Under this setup, we devise a cooperative, distributed, and iterative algorithm providing the optimal bidding, production, and storage strategies of the users, along with its convergence properties.

  • Sharpened capacity lower bounds of fading MIMO channels with imperfect CSI

     Pastore, Adriano; Hoydis, Jakob; Rodriguez Fonollosa, Javier
    IEEE International Symposium on Information Theory
    p. 2089-2093
    DOI: 10.1109/ISIT.2013.6620594
    Presentation's date: 2013-07-11
    Presentation of work at congresses

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    A well-established capacity lower bound of multipleinput multiple-output (MIMO) single-user fading channels operating with imperfect receiver-side channel-state information (CSI) is improved using a simple rate-splitting and successive-decoding scheme. The potential improvement is shown to increase with the number of allowed decoding steps (layers) to such extent that the best layering strategy is approached in the limit as the number of layers tends to infinity. We give a general analytic expression of this limit, which constitutes a new capacity lower bound that is sharper than the conventional bound. Using large random matrix theory, we derive an asymptotic approximation of this novel bound, which is shown via numerical simulation to be highly accurate over the whole range of signal-to-noise ratios.

  • Array gain in the DMT framework for MIMO channels

     Garcia Ordoñez, Luis; Palomar, Daniel P.; Rodriguez Fonollosa, Javier
    IEEE transactions on information theory
    Vol. 58, num. 7, p. 4577-4593
    DOI: 10.1109/TIT.2012.2191933
    Date of publication: 2012
    Journal article

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    Following the seminal work by Zheng and Tse on the diversity and multiplexing tradeoff (DMT) of multiple-input multiple-output (MIMO) channels, in this paper, we introduce the array gain to investigate the fundamental relation between transmission rate and reliability inMIMO systems. The array gain gives information on the power offset that results from exploiting channel state information at the transmitter or as a consequence of the channel model. Hence, the diversity, multiplexing, and array gain (DMA) analysis is able to cope with the limitations of the original DMT and provide an operational meaning in the sense that the DMA gains of a particular system can be directly translated into a parameterized characterization of its associated outage probability performance. In this paper, we derive the best DMA gains achievable by any scheme employing isotropic signaling in uncorrelated Rayleigh, semicorrelated Rayleigh, and uncorrelated Rician block-fading MIMO channels. We use these results to analyze the effect of important channel parameters on the outage performance at different points of the DMT curve.

  • Day-ahead bidding strategies for demand-side expected cost minimization

     Atzeni, Italo; Garcia Ordoñez, Luis; Scutari, Gesualdo; Palomar, Daniel P.; Rodriguez Fonollosa, Javier
    IEEE International Conference on Smart Grid Communications
    p. 91-96
    DOI: 10.1109/SmartGridComm.2012.6485965
    Presentation's date: 2012-11-05
    Presentation of work at congresses

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    Day-ahead DSM techniques in the smart grid allow the supply-side to know in advance an estimation of the amount of energy to be provided to the demand-side during the upcoming day. However, a pure day-ahead optimization process cannot accommodate potential real-time deviations from the expected energy consumption by the demand-side users, neither the randomness of their renewable sources. This paper proposes a day-ahead bidding system based on a pricing model that combines: i) a price per unit of energy depending on the day-ahead bid energy needs of the demand-side users, and ii) a penalty system that limits the real-time fluctuations around the bid energy loads. In this day-ahead bidding process, demand-side users, possibly having energy production and storage capabilities, are interested in minimizing their expected monetary expense. The resulting optimization problem is formulated as a noncooperative game and is solved by means of suitable distributed algorithms. Finally, the proposed procedure is tested in a realistic setup.

    Day-ahead DSM techniques in the smart grid allow the supply-side to know in advance an estimation of the amount of energy to be provided to the demand-side during the upcoming day. However, a pure day-ahead optimization process cannot accommodate potential real-time deviations from the expected energy consumption by the demand-side users, neither the randomness of their renewable sources. This paper proposes a day-ahead bidding system based on a pricing model that combines: i) a price per unit of energy depending on the day-ahead bid energy needs of the demand-side users, and ii) a penalty system that limits the real-time fluctuations around the bid energy loads. In this day-ahead bidding process, demand-side users, possibly having energy production and storage capabilities, are interested in minimizing their expected monetary expense. The resulting optimization problem is formulated as a noncooperative game and is solved by means of suitable distributed algorithms. Finally, the proposed procedure is tested in a realistic setup.

  • Optimal pilot design and power control in correlated MISO links

     Pastore, Adriano; Rodriguez Fonollosa, Javier
    IEEE International Conference on Communications
    p. 2542-2546
    DOI: 10.1109/ICC.2012.6364657
    Presentation's date: 2012-06-14
    Presentation of work at congresses

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    We study the maximization of an achievable ergodic rate expression of a multiple-input single-output (MISO) channel where both ends are cognizant of the same erroneous estimate of the current fading state, yet they have complete knowledge of channel statistics. A training procedure estimates each channel state by means of dedicated pilot symbols whose sum energy is fixed, while for data transmission a fixed average energy per channel access (i.e., average power) is available. The optimization consists, on one hand, in finding the optimal beamforming strategy and temporal power control policy, and on the other hand, in optimally constructing the pilot sequence according to the channel's correlation structure.

  • Improved capacity lower bounds for fading channels with imperfect CSI using rate splitting

     Pastore, Adriano; Koch, Tobias; Rodriguez Fonollosa, Javier
    IEEE Convention of Electrical and Electronics Engineers in Israel
    p. 1-5
    Presentation's date: 2012-11-15
    Presentation of work at congresses

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    FREEDOM D3.2 Interference Coordination Protocols in Femto-based Networks  Open access

     Agustin de Dios, Adrian; Muñoz Medina, Olga; Vidal Manzano, Jose; Goldhammer, Mariana; Rodriguez Fonollosa, Javier; Pastore, Adriano; Sardellitti, Stefania; Pescosolido, Loreto; di Lorenzo, Paolo; Barbarossa, Sergio; Baiocchi, Andrea; de Marinis, Enrico; Imponente, Giovanni; Pucci, Fabrizio; Rosi, Guido
    Date: 2011-11-28
    Report

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    This document looks into coordinated radio resource allocation algorithms in deployments of huge number of femto-access points (FAP) by exploiting the message exchange at control-plane level through the wired ISP backhaul link. The algorithms present in this document are based on decentralized cooperative strategies supported by Game Theory. Decentralized resource allocation algorithms based on price exchange have been derived under different criteria: guaranteeing a minimum rate with the minimum power, maximizing the weighted sum-rate of the system, maximizing the opportunistic throughput when there are different source of randomness like random link failures and noise quantization or when the activity of macro-users is not known by FAPs (coordinated channel sensing or modelling the activity). Additionally, a genetic-based resource allocation is investigated, providing centralized and decentralized algorithms, to which the Game Theory solutions are challenged . In all cases, the techniques derived require modifications of the current LTE-A standard which are identified. Finally, some of those algorithms have been evaluated in a realistic corporate scenario elucidating the advantages of coordinated resource allocation techniques proposed.

    This document looks into coordinated radio resource allocation algorithms in deployments of huge number of femto-access points (FAP) by exploiting the message exchange at control-plane level through the wired ISP backhaul link. The algorithms present in this document are based on decentralized cooperative strategies supported by Game Theory. Decentralized resource allocation algorithms based on price exchange have been derived under different criteria: guaranteeing a minimum rate with the minimum power, maximizing the weighted sum-rate of the system, maximizing the opportunistic throughput when there are different source of randomness like random link failures and noise quantization or when the activity of macro-users is not known by FAPs (coordinated channel sensing or modelling the activity). Additionally, a genetic-based resource allocation is investigated, providing centralized and decentralized algorithms, to which the Game Theory solutions are challenged . In all cases, the techniques derived require modifications of the current LTE-A standard which are identified. Finally, some of those algorithms have been evaluated in a realistic corporate scenario elucidating the advantages of coordinated resource allocation techniques proposed.

    This document looks into coordinated radio resource allocation algorithms in deployments of huge number of femto-access points (FAP) by exploiting the message exchange at control-plane level through the wired ISP backhaul link.

  • Access to the full text
    FREEDOM Project. Interference coordination protocols in femto-based networks  Open access

     Agustin de Dios, Adrian; Muñoz Medina, Olga; Vidal Manzano, Jose; Goldhamer, M.; Rodriguez Fonollosa, Javier; Pastore2, A.; Sardellitti, Stefania; Pescosolido, Loreto; di Lorenzo, Paolo; Barbarossa, Sergio; Baiocchi, Andrea; de Marinis, Enrico; Imponente, Giovanni; Pucci, Fabrizio; Rosi, Guido
    Date: 2011-11-28
    Report

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    This document looks into coordinated radio resource allocation algorithms in deployments of huge number of femto-access points (FAP) by exploiting the message exchange at control-plane level through the wired ISP backhaul link. The algorithms present in this document are based on decentralized cooperative strategies supported by Game Theory. Decentralized resource allocation algorithms based on price exchange have been derived under different criteria: guaranteeing a minimum rate with the minimum power, maximizing the weighted sum-rate of the system, maximizing the opportunistic throughput when there are different source of randomness like random link failures and noise quantization or when the activity of macro-users is not known by FAPs (coordinated channel sensing or modelling the activity). Additionally, a genetic-based resource allocation is investigated, providing centralized and decentralized algorithms, to which the Game Theory solutions are challenged. In all cases, the techniques derived require modifications of the current LTE-A standard which are identified. Finally, some of those algorithms have been evaluated in a Realistic corporate scenario elucidating the advantages of coordinated resource allocation techniques proposed.

    Postprint (author’s final draft)

  • Macrocelulas y Femtocelulas en Sistemas con Técnicas Avanzadas de Coordinación de la Interferencia y Cooperación

     Vidal Manzano, Jose; Rodriguez Fonollosa, Javier; Cabrera Bean, Margarita Asuncion; Fernandez Rubio, Juan-antonio; Pages Zamora, Alba Maria; Agustin de Dios, Adrian; Silva Pereira, Silvana; Garcia Ordoñez, Luis; Vila Valls, Jordi; Muñoz Medina, Olga
    Competitive project

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  • Decentralized weighted sum rate maximization in MIMO-OFDMA femtocell networks

     Agustin de Dios, Adrian; Vidal Manzano, Jose; Muñoz Medina, Olga; Rodriguez Fonollosa, Javier
    IEEE Global Communications Conference
    p. 1-5
    DOI: 978-1-4673-0040-7/11
    Presentation's date: 2011-12
    Presentation of work at congresses

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    We propose a decentralized strategy for downlink interference management in overlaid MIMO femtocell-macrocell deployments operating in the same band under OFDMA access. The resource allocation, consisting of MIMO precoders at the macro base station (MBS) and femto access points (FAPs) and possibly the resource block (RB) assignment, is designed to maximize the Weighted Sum Rate (WSR) of the system. Being the overall problem non-convex, we propose to solve it in a decentralized way where each transmitter designs its resource allocation using interference prices exchanged with other transmitters (FAPs and MBS) by exploiting the wired backhaul connection. The problem includes a rate restriction per FAP that accounts for the limited bitrate provided by the Internet Service Provider (ISP) wired backhaul. Two efficient algorithms are provided for: 1) optimizing MIMO precoders and 2) optimizing both MIMO precoders and RB assignment. Numerical results compare decentralized strategies based on pricing exchange and on pure competition in dense FAP deployments.

  • On a rate region approximation of MIMO channels under partial CSI

     Pastore2, A.; Joham, Michael; Rodriguez Fonollosa, Javier
    International ITG Workshop on Smart Antennas
    p. 1-8
    DOI: 10.1109/WSA.2011.5741953
    Presentation's date: 2011
    Presentation of work at congresses

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    When the receiver of a multiple-input multiple-output (MIMO) channel does not know the channel state, but only a linear estimate thereof, the rates achieved with (suboptimal) Gaussian codebooks become difficult to compute. However, one can resort to upper and lower bounds known from literature. Extending the ideas of earlier works on the resource allocation (time and energy) between pilot and data symbols, we first show that, at high SNR, the optimal training length is min(M,N) (where M and N are the number of receive and transmit antennas), and that in no case more than half the coherence time should be used for training. By simple arguments, we show that the basic training scheme-which allocates separate time slots for training and data transmission-achieves the diversity-multiplexing tradeoff of block-fading channels. In a second part, we propose a generalization of the mutual information bounds to inner and outer rate region bounds of the multiple-access channel.

  • Fundamental diversity, multiplexing, and array gain tradeoff under different MIMO channel models

     Garcia Ordoñez, Luis; Pérez Palomar, Daniel; Rodriguez Fonollosa, Javier
    IEEE International Conference on Acoustics, Speech and Signal Processing
    p. 3252-3255
    DOI: 10.1109/ICASSP.2011.5946715
    Presentation's date: 2011-05-25
    Presentation of work at congresses

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    Following the seminal work of Zheng and Tse on the diversity and multiplexing tradeoff (DMT) of MIMO channels, in this paper we introduce the array gain to investigate the fundamental relation between transmission rate and reliability in MIMO systems. The array gain gives information on the power offset that results from exploiting channel state information at the transmitter or as a consequence of the channel model. Hence, the diversity, multiplexing, and array gain (DMA) analysis can be directly translated into a parameterized characterization of its associated outage probability performance. In this paper we derive the fundamental DMA tradeoff achievable by any scheme in uncorrelated Rayleigh, semicorrelated Rayleigh, and uncorrelated Rician block-fading MIMO channels. We use these results to analyze the effect of important channel parameters in the outage performance at different points of the DMT curve.

  • DMA tradeoff for the MIMO static half-duplex relay

     Garcia Ordoñez, Luis; Pérez Palomar, Daniel; Rodriguez Fonollosa, Javier
    IEEE International Workshop on Signal Processing Advances in Wireless Communications
    p. 361-365
    DOI: 10.1109/SPAWC.2011.5990430
    Presentation's date: 2011-06-28
    Presentation of work at congresses

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    The diversity and multiplexing tradeoff (DMT) has been extensively applied in the literature to compare the high-SNR outage performance of relaying techniques and to propose new design guidelines. The problem with this approach is that the DMT provides only a coarse measure of performance and, hence, it is more convenient to adopt the diversity, multiplexing, and array gain (DMA) framework, in which the error probability is characterized by two parameters: the diversity gain (associated with the SNR exponent) and the array gain (related to the SNR offset). In this paper, we derive the DMA tradeoff associated with the cut-set bound outage probability of the static half-duplex MIMO relay under uncorrelated/semicorrelated Rayleigh fading and uncorrelated Rician fading. This provides an upper bound to the DMA tradeoff achievable by any relaying scheme.

  • On a mutual information and a capacity bound gap of pilot-aided MIMO channels

     Pastore2, A.; Joham, Michael; Rodriguez Fonollosa, Javier
    IEEE International Conference on Communications
    p. 1-6
    DOI: 10.1109/icc.2011.5962951
    Presentation's date: 2011-06-08
    Presentation of work at congresses

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  • Balancing egoistic and altruistic transmit beamforming in femtocell networks

     Husso, Mika; Dowhuszko, Alexis; Hamalainen, K.; Pastore2, A.; Rodriguez Fonollosa, Javier
    Future Network and MobileSummit
    p. 1-10
    Presentation's date: 2011-06-15
    Presentation of work at congresses

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  • Joint pilot and precoder design for optimal throughput

     Pastore2, A.; Joham, Michael; Rodriguez Fonollosa, Javier
    IEEE International Symposium on Information Theory
    p. 371-375
    DOI: 10.1109/ISIT.2011.6034149
    Presentation's date: 2011-08-01
    Presentation of work at congresses

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  • MÉTODO Y SISTEMA PARA LA GESTIÓN DESCENTRALIZADA DE FEMTOCÉLULAS VECINAS

     Rodriguez Fonollosa, Javier; Agustin de Dios, Adrian; Vidal Manzano, Jose; Muñoz Medina, Olga
    Date of request: 2011-11-28
    Invention patent

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    Método y sistema para la gestión descentralizada de femtocélulas vecinas.

    El método comprende:

    - la comunicación, a una primera femtocélula desde una segunda femtocélula, de la siguiente información:

    i) la restricción de requerimientos de interferencia de un usuario activo de la segunda femtocélula, y

    ii) uno o más parámetros que caracterizan un canal radio físico definido desde la primera femtocélula hasta dicho al menos un usuario activo de la segunda femtocélula;

    - la autoconfiguración de los parámetros de transmisión de la primera femtocélula usando la información comunicada i) y ii).

    El sistema está configurado para implementar el método de la invención.

  • On the computation of the capacity region of the discrete MAC

     Calvo, Eduard; Pérez Palomar, Daniel; Rodriguez Fonollosa, Javier; Vidal Manzano, Jose
    IEEE transactions on communications
    Vol. 58, num. 12, p. 3512-3525
    DOI: 10.1109/TCOMM.2010.091710.090239
    Date of publication: 2010-12
    Journal article

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  • Toward a reconfigurable MIMO downlink air interface and radio resource management: the SURFACE concept

     Kovacs, István Zsolt; Garcia Ordoñez, Luis; Navarro, M.; Calvo, Eduard; Rodriguez Fonollosa, Javier
    IEEE communications magazine
    Vol. 48, num. 6, p. 22-29
    DOI: 10.1109/MCOM.2010.5473860
    Date of publication: 2010-06
    Journal article

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  • FEMTOCELL-BASED NETWORK ENHANCEMENT BY INTERFERENCE MANAGEMENT AND COORDINATION OF INFORMATION FOR SEAMLESS CONNECTIVITY

     Muñoz Medina, Olga; Rodriguez Fonollosa, Javier; Agustin de Dios, Adrian; Fernandez Rubio, Juan-antonio; Vidal Manzano, Jose
    Competitive project

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  • Ordered Eigenvalues of a General Class of Hermitian Random Matrices With Application to the Performance Analysis of MIMO System

     Ordonez, LG; Palomar, Daniel P.; Rodriguez Fonollosa, Javier; Garcia Ordoñez, Luis
    IEEE transactions on signal processing
    Vol. 57, num. 2, p. 672-689
    Date of publication: 2009-02
    Journal article

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  • Optimal Resource Allocation in Relay-Assisted Cellular Networks With Partial CSI

     Calvo, E; Vidal Manzano, Jose; Rodriguez Fonollosa, Javier
    IEEE transactions on signal processing
    Vol. 57, num. 7, p. 2809-2823
    Date of publication: 2009-07
    Journal article

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  • Minimum BER Linear MIMO Transceivers With Adaptive Number of Substreams

     Ordonez, LG; Palomar, Daniel P.; Pages Zamora, Alba Maria; Rodriguez Fonollosa, Javier; Garcia Ordoñez, Luis
    IEEE transactions on signal processing
    Vol. 57, num. 6, p. 2336-2353
    Date of publication: 2009-06
    Journal article

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  • Performance Limits of Spatial Multiplexing MIMO Systems  awarded activity

     Garcia Ordoñez, Luis
    Department of Signal Theory and Communications, Universitat Politècnica de Catalunya
    Theses

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  • PROCESSAMENT DEL SENYAL EN COMUNICACIONS

     Pages Zamora, Alba Maria; Lamarca Orozco, M. Meritxell; Silva Pereira, Silvana; Font Segura, Josep; Matas Navarro, David; Muñoz Medina, Olga; Rey Micolau, Francesc; Ramirez Javega, Francisco; Rodriguez Fonollosa, Javier; Vidal Manzano, Jose; Riba Sagarra, Jaume; Vazquez Grau, Gregorio; Villares Piera, N. Javier; Garcia Ordoñez, Luis; Cabrera Bean, Margarita Asuncion; Fernandez Rubio, Juan-antonio; Agustin de Dios, Adrian; Sala Alvarez, Jose
    Competitive project

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  • INTERFERENCE IN WIRELESS NETWORKS: Cancelation, Impact, Practical Management, and Complexity.

     Calvo Page, Eduardo
    Department of Signal Theory and Communications, Universitat Politècnica de Catalunya
    Theses

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    On the totally asynchronous interference channel with single-user receivers  Open access

     Calvo Page, Eduard; Rodriguez Fonollosa, Javier; Vidal Manzano, Jose
    IEEE International Symposium on Information Theory
    p. 2587-2591
    Presentation's date: 2009-07-03
    Presentation of work at congresses

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    The performance characterization of decentralized wireless networks with uncoordinated sender-destination pairs motivates the study of the totally asynchronous interference channel with single-user receivers. Since this channel is not information stable, its capacity region is determined resorting to information density, although more amenable single-letter inner and outer bounds are provided as well. Aiming at numerical evaluation of the achievable rates, we subsequently concentrate on the inner bound for the Gaussian case. We show that taking Gaussian inputs is not the best choice in general and derive analytical conditions under which other input distributions may be optimal. Essentially, these conditions require the channel to be interference-limited. Finally, the existence of such non-Gaussian distributions with superior performance is validated numerically in different scenarios.

  • Diversity and multiplexing tradeoff of spatial multiplexing MIMO systems with CSI

     Garcia Ordoñez, Luis; Pages Zamora, Alba Maria; Rodriguez Fonollosa, Javier
    IEEE transactions on information theory
    Vol. 54, num. 7, p. 2959-2975
    DOI: 10.1109/TIT.2008.924670
    Date of publication: 2008-07
    Journal article

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  • Transmit and Receive Architecture Development and Algorithmic Implementation

     István, Z Kovács (NSN); Garcia Ordoñez, Luis; Eduard, Calvo (UPC); Rodriguez Fonollosa, Javier; Sorensen, Troels B (AAU)
    Date: 2008-07
    Report

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  • Foundations and Methodologies for Future Communication and Sensor Networks (COMONSENS)

     Rodriguez Fonollosa, Javier; Pages Zamora, Alba Maria; Muñoz Medina, Olga; Vidal Manzano, Jose; Cabrera Bean, Margarita Asuncion; Fernandez Rubio, Juan-antonio; Rey Micolau, Francesc; Villares Piera, N. Javier; Vazquez Grau, Gregorio; Lamarca Orozco, M. Meritxell; Sala Alvarez, Jose; Riba Sagarra, Jaume
    Competitive project

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  • FINANÇAMENT PER ELABORACIÓ DE PROJECTES ADREÇATS AL 7PM

     Rodriguez Fonollosa, Javier
    Competitive project

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  • SELF-OPTIMIZING DISTRIBUTED AND COOPERATIVE NETWORKS (SONNET)

     Rodriguez Fonollosa, Javier
    Competitive project

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  • Ordered Eigenvalues of a General Class of Hermitian Random Matrices and Performance Analysis of MIMO Systems

     Garcia Ordoñez, Luis; Palomar, Daniel Pérez; Rodriguez Fonollosa, Javier
    IEEE International Conference on Communications
    p. 1-5
    Presentation of work at congresses

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  • A Reconfigurable Downlink Air Interface: Design, Simulation Methodology, and Performance Evaluation

     Eduard, Calvo; István, Z Kovacs; Garcia Ordoñez, Luis; Rodriguez Fonollosa, Javier
    17th ICT Mobile and Wireless Communications Summit (ICT 2008)
    p. 1-8
    Presentation of work at congresses

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  • A Reconfigurable Downlink Air Interface: Design, Simulation Methodology, and Performance Evaluation

     Rodriguez Fonollosa, Javier
    17th ICT Mobile and Wireless Communications Summit (ICT 2008)
    Presentation's date: 2008-06-10
    Presentation of work at congresses

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  • The computation of the capacity region of the discrete degraded BC is a nonconvex DC problem

     Eduard, Calvo; Palomar, Daniel P.; Rodriguez Fonollosa, Javier; Vidal Manzano, Jose
    2008 IEEE International Symposium on Information Theory
    p. 1721-1725
    Presentation of work at congresses

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  • Contribución de las técnicas de diversidad en transmisión para sistemas de comunicaciones móviles de tercera generación

     Carrasco Espinosa, Hector
    Department of Signal Theory and Communications, Universitat Politècnica de Catalunya
    Theses

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  • High-SNR Analytical Performance of Spatial Multiplexing MIMO Systems With CSI

     Garcia Ordoñez, Luis; Palomar, Daniel P.; Pages Zamora, Alba Maria; Rodriguez Fonollosa, Javier
    IEEE transactions on signal processing
    Vol. 55, num. 11, p. 5447-5463
    Date of publication: 2007-11
    Journal article

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  • D4.1. Preliminary Design of the Multi-User Optimal Transmit and Receive Strategy

     Calvo Page, Eduardo; Garcia Ordoñez, Luis; Rodriguez Fonollosa, Javier; Pages Zamora, Alba Maria; Sorensen, T B; Lin, Z; Figueiredo, D V P; Kovacs, I Z; Fasano, A; Barbarossa, S; Pescosolido, L; Scutari, G; Baiocchi, A
    Date: 2007-01
    Report

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  • D4.2. Design of the Multi-User Optimal Transmit and Receive Strategy

     Calvo Page, Eduardo; Garcia Ordoñez, Luis; Rodriguez Fonollosa, Javier; Pages Zamora, Alba Maria; Sørensen, T B; Lin, Z; Figueiredo, D V P; Kovács, I Z; Barbarossa, S; Fasano, A; Pescosolido, L; Scutari, G; Baiocchi, A; et, al
    Date: 2007-07
    Report

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  • D7.1. Definition of the link-to-system level interface

     Canto, R; Warzanskyj, W; Kovács, I Z; Sørensen, T B; Pages Zamora, Alba Maria; Rodriguez Fonollosa, Javier; Garcia Ordoñez, Luis; Calvo Page, Eduardo
    Date: 2007-01
    Report

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