Ponències/Comunicacions de congressos
http://hdl.handle.net/2117/1257
2016-05-26T01:31:26ZSimultaneous wireless information and power transfer in multiuser MIMO systems
http://hdl.handle.net/2117/86262
Simultaneous wireless information and power transfer in multiuser MIMO systems
Rubio López, Javier; Pascual Iserte, Antonio
In this paper, we focus on a broadcast multiuser
multiple-input multiple-output (MIMO) system in a network
with short links. In this scenario we consider that some
terminals harvest power and, thus, recharge their batteries,
through wireless power transfer from the transmitter while
others are simultaneously being served with data transmission.
We assume that the nodes are battery powered devices and,
consequently, such solution provides a convenient energy supply.
The sum-rate for the users being served with data is considered
as the optimization policy where power harvesting per user
constraints are taken into account. We provide the optimal
structure of the resulting transmit covariance matrices and
precoders for the users in the general case (i.e., in scenarios
where both types of nodes are present in the network) and we
also study the case where only harvesting nodes are to be served.
Finally, we analyze and characterize the fundamental tradeoff
between the data transmission sum-rate and the powers
harvested by the network nodes using the concept of the rateenergy
(R-E) region.
2016-04-27T13:16:43ZRubio López, JavierPascual Iserte, AntonioIn this paper, we focus on a broadcast multiuser
multiple-input multiple-output (MIMO) system in a network
with short links. In this scenario we consider that some
terminals harvest power and, thus, recharge their batteries,
through wireless power transfer from the transmitter while
others are simultaneously being served with data transmission.
We assume that the nodes are battery powered devices and,
consequently, such solution provides a convenient energy supply.
The sum-rate for the users being served with data is considered
as the optimization policy where power harvesting per user
constraints are taken into account. We provide the optimal
structure of the resulting transmit covariance matrices and
precoders for the users in the general case (i.e., in scenarios
where both types of nodes are present in the network) and we
also study the case where only harvesting nodes are to be served.
Finally, we analyze and characterize the fundamental tradeoff
between the data transmission sum-rate and the powers
harvested by the network nodes using the concept of the rateenergy
(R-E) region.Energy-aware broadcast MU-MIMO precoder design with imperfect battery knowledge
http://hdl.handle.net/2117/86261
Energy-aware broadcast MU-MIMO precoder design with imperfect battery knowledge
Rubio López, Javier; Pascual Iserte, Antonio
This paper addresses the problem of precoder
design in a MIMO broadcast scenario where the terminals
are battery-powered devices provided with energy harvesting
capabilities. Models for the power consumption of the RF and
decoding stages are discussed and included in the design of
the proposed scheme. Sum-rate maximization is taken as optimization
policy and energy-related constraints are considered
to increase the duration of the batteries and, thus, the network
lifetime. Simulation results show that not only the usage of
battery is improved when compared with other traditional
allocation policies, but also the average data rate is enhanced.
2016-04-27T13:13:19ZRubio López, JavierPascual Iserte, AntonioThis paper addresses the problem of precoder
design in a MIMO broadcast scenario where the terminals
are battery-powered devices provided with energy harvesting
capabilities. Models for the power consumption of the RF and
decoding stages are discussed and included in the design of
the proposed scheme. Sum-rate maximization is taken as optimization
policy and energy-related constraints are considered
to increase the duration of the batteries and, thus, the network
lifetime. Simulation results show that not only the usage of
battery is improved when compared with other traditional
allocation policies, but also the average data rate is enhanced.Filtrado transversal adaptativo de varianza constante para la ecualización de canal
http://hdl.handle.net/2117/86209
Filtrado transversal adaptativo de varianza constante para la ecualización de canal
Vázquez Grau, Gregorio; Gasull Llampallas, Antoni; Sánchez Umbría, Juan; Oliveras Vergés, Albert
This paper describes the problem of lineal filtering of noisy data under a Maximum Likelihood objective. In this sense, the paper shows that a weighted square error cost function deals and it is necessary to weight the filtering error sequence by a factor that, basically, depends the probability density function of the error sequence and on its first derivate. As it is well known, this information used to be not available and other proposals must be made. For this purpose, going around this problem, the paper discusses the design of this weighting factor for including sorne kind of data-selection mechanism for the final filter weight-vector solution design. The underlying of the proposal is the development of a recursive algorithm in such a way that for any measure or observation, its associated
2016-04-26T14:37:29ZVázquez Grau, GregorioGasull Llampallas, AntoniSánchez Umbría, JuanOliveras Vergés, AlbertThis paper describes the problem of lineal filtering of noisy data under a Maximum Likelihood objective. In this sense, the paper shows that a weighted square error cost function deals and it is necessary to weight the filtering error sequence by a factor that, basically, depends the probability density function of the error sequence and on its first derivate. As it is well known, this information used to be not available and other proposals must be made. For this purpose, going around this problem, the paper discusses the design of this weighting factor for including sorne kind of data-selection mechanism for the final filter weight-vector solution design. The underlying of the proposal is the development of a recursive algorithm in such a way that for any measure or observation, its associatedAdaptive spectrum estimation with linear constrains
http://hdl.handle.net/2117/86201
Adaptive spectrum estimation with linear constrains
Vázquez Grau, Gregorio; Vallverdú Bayés, Francesc
A general constrained adaptive metbod is developed to be applied to the spectral estimation problem. The method presented can be used in a wide range of situatious, this is, we can get different estimators wíth it. The algorithm is formulated in a varíational approach context,and tbe non linear system obtained is solved with a constrained adaptive method applied to a digitized version of the spedrum. The set of constraínts is considered to be a set of known correlation values, and they can be located in non consecutíve lags. A generalization of the method is done, so it can be used in a rnu lt idimensional framework. As an example, a bidimensional ma.ximum entropy spectrum is presented.
2016-04-26T13:05:44ZVázquez Grau, GregorioVallverdú Bayés, FrancescA general constrained adaptive metbod is developed to be applied to the spectral estimation problem. The method presented can be used in a wide range of situatious, this is, we can get different estimators wíth it. The algorithm is formulated in a varíational approach context,and tbe non linear system obtained is solved with a constrained adaptive method applied to a digitized version of the spedrum. The set of constraínts is considered to be a set of known correlation values, and they can be located in non consecutíve lags. A generalization of the method is done, so it can be used in a rnu lt idimensional framework. As an example, a bidimensional ma.ximum entropy spectrum is presented.On the Use of Higher Order Information in SVD Based Methods
http://hdl.handle.net/2117/86199
On the Use of Higher Order Information in SVD Based Methods
Vázquez Grau, Gregorio; Vallverdú Bayés, Francesc
2016-04-26T12:50:19ZVázquez Grau, GregorioVallverdú Bayés, FrancescMétodo MLNq para arrays de alta resolución
http://hdl.handle.net/2117/86149
Método MLNq para arrays de alta resolución
Gasull Llampallas, Antoni; Lagunas Hernandez, Miguel A.; Fernández Rubio, Juan Antonio; Moreno Bilbao, M. Asunción
Spectral analysis techniques are used to bearing estimation problem. Each one of this gives a different array beamforming. We show here a generalized normalized Maximum Likehood Method which present a high resolution comparable to the singular value decomposition methods, but with a smaller computational load .
2016-04-25T13:36:49ZGasull Llampallas, AntoniLagunas Hernandez, Miguel A.Fernández Rubio, Juan AntonioMoreno Bilbao, M. AsunciónSpectral analysis techniques are used to bearing estimation problem. Each one of this gives a different array beamforming. We show here a generalized normalized Maximum Likehood Method which present a high resolution comparable to the singular value decomposition methods, but with a smaller computational load .System identification through first and second order information from the periodogram
http://hdl.handle.net/2117/86138
System identification through first and second order information from the periodogram
Vázquez Grau, Gregorio; Lagunas Hernandez, Miguel A.
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The use of first- and second-order information in the characterization of linear systems is considered. Consideration is given to the case when this information is not available but some samples are given of a random process which are the result of filtering white noise through the system. The authors examine an approach which, starting from one estimate of the autocorrelation function, gives rise to an ARMA (autoregressive moving-average) model for the system considered. The derivation of the model is achieved from an optimization point of view.
2016-04-25T12:42:39ZVázquez Grau, GregorioLagunas Hernandez, Miguel A.Email
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The use of first- and second-order information in the characterization of linear systems is considered. Consideration is given to the case when this information is not available but some samples are given of a random process which are the result of filtering white noise through the system. The authors examine an approach which, starting from one estimate of the autocorrelation function, gives rise to an ARMA (autoregressive moving-average) model for the system considered. The derivation of the model is achieved from an optimization point of view.Data pre-processing for high-resolution adaptive algorithms
http://hdl.handle.net/2117/86134
Data pre-processing for high-resolution adaptive algorithms
Vázquez Grau, Gregorio; Gasull Llampallas, Antoni
The inclusion of adaptive methods in high-resolution spectral estimation algorithms is considered. The generation of a complete family of spectral estimators from the normalized maximum-likelihood method (MLM) is discussed. It is shown how the generalized power MLM can be used to generate adaptive schemes for improving resolution. The authors propose the substitution of the conventional mean-square filtering error by quadratic objectives built as inner products of the coefficient error vector of the estimator filter
2016-04-25T12:34:14ZVázquez Grau, GregorioGasull Llampallas, AntoniThe inclusion of adaptive methods in high-resolution spectral estimation algorithms is considered. The generation of a complete family of spectral estimators from the normalized maximum-likelihood method (MLM) is discussed. It is shown how the generalized power MLM can be used to generate adaptive schemes for improving resolution. The authors propose the substitution of the conventional mean-square filtering error by quadratic objectives built as inner products of the coefficient error vector of the estimator filterData pre-processing for high-resolution adaptive algorithms
http://hdl.handle.net/2117/86074
Data pre-processing for high-resolution adaptive algorithms
Vázquez Grau, Gregorio; Gasull Llampallas, Antoni
The inclusion of adaptive methods in high-resolution spectral estimation algorithms is considered. The generation of a complete family of spectral estimators from the normalized maximum-likelihood method (MLM) is discussed. It is shown how the generalized power MLM can be used to generate adaptive schemes for improving resolution. The authors propose the substitution of the conventional mean-square filtering error by quadratic objectives built as inner products of the coefficient error vector of the estimator filter
2016-04-21T14:41:58ZVázquez Grau, GregorioGasull Llampallas, AntoniThe inclusion of adaptive methods in high-resolution spectral estimation algorithms is considered. The generation of a complete family of spectral estimators from the normalized maximum-likelihood method (MLM) is discussed. It is shown how the generalized power MLM can be used to generate adaptive schemes for improving resolution. The authors propose the substitution of the conventional mean-square filtering error by quadratic objectives built as inner products of the coefficient error vector of the estimator filterKnown Input Power Spectrum in Adaptive L.M.S. and A. G. Algorithms
http://hdl.handle.net/2117/85856
Known Input Power Spectrum in Adaptive L.M.S. and A. G. Algorithms
Vázquez Grau, Gregorio; Gasull Llampallas, Antoni; Lagunas Hernandez, Miguel A.
This work deals with the use of previous or colateral information to improve the behaviour of adaptive algorithms. The study is made on gradient-baseq methods due te the relatively simple and good performances that they use to exhibit. This paper shows that the complete knowledge of the data at the input of the adaptive filter (and in consequence of its autocorrelation matrix and its inverse) can be used to modify the classic L.M.S. algorithm leading to new expressions for the gradient and for the optimum 1step size 1 , alternative, in sorne cases, to the Powell expression. Finally, the description is completed with the comparison between the variation ranges and VLSI implementation cost for this two optimum 'step size' values anda natural generalization set of parameter is obtained.
2016-04-19T07:34:25ZVázquez Grau, GregorioGasull Llampallas, AntoniLagunas Hernandez, Miguel A.This work deals with the use of previous or colateral information to improve the behaviour of adaptive algorithms. The study is made on gradient-baseq methods due te the relatively simple and good performances that they use to exhibit. This paper shows that the complete knowledge of the data at the input of the adaptive filter (and in consequence of its autocorrelation matrix and its inverse) can be used to modify the classic L.M.S. algorithm leading to new expressions for the gradient and for the optimum 1step size 1 , alternative, in sorne cases, to the Powell expression. Finally, the description is completed with the comparison between the variation ranges and VLSI implementation cost for this two optimum 'step size' values anda natural generalization set of parameter is obtained.