Articles de revista
http://hdl.handle.net/2117/1256
Thu, 08 Dec 2016 10:15:01 GMT2016-12-08T10:15:01ZAdaptive blind system identification using weighted cumulant slices
http://hdl.handle.net/2117/97875
Adaptive blind system identification using weighted cumulant slices
Vidal Manzano, José; Rodríguez Fonollosa, José Adrián
Many linear methods have been proposed in the literature to blindly estimate the ARMA parameters of a time series using HOS. Nevertheless, they are mainly off-line and not much has been done in the adaptive case. The method proposed in this contribution is the adaptive version of the w-slice method. The recursion is based on the inversion lemma when attempting the solution of an underdetermined matrix equation. The system impulse response can be recovered regardless of the ARMA or MA character of the system. The number of operations depends on the square of the system order and is considerably reduced with respect to previous approaches. Application to channel deconvolution is shown.
Wed, 07 Dec 2016 14:26:26 GMThttp://hdl.handle.net/2117/978752016-12-07T14:26:26ZVidal Manzano, JoséRodríguez Fonollosa, José AdriánMany linear methods have been proposed in the literature to blindly estimate the ARMA parameters of a time series using HOS. Nevertheless, they are mainly off-line and not much has been done in the adaptive case. The method proposed in this contribution is the adaptive version of the w-slice method. The recursion is based on the inversion lemma when attempting the solution of an underdetermined matrix equation. The system impulse response can be recovered regardless of the ARMA or MA character of the system. The number of operations depends on the square of the system order and is considerably reduced with respect to previous approaches. Application to channel deconvolution is shown.Motion estimation using higher-order statistics
http://hdl.handle.net/2117/97801
Motion estimation using higher-order statistics
Sayrol Clols, Elisa; Gasull Llampallas, Antoni; Rodríguez Fonollosa, Javier
The objective of this paper is to introduce a fourth-order cost function of the displaced frame difference (DFD) capable of estimating motion even for small regions or blocks. Using higher than second-order statistics is appropriate in case the image sequence is severely corrupted by additive Gaussian noise. Some results are presented and compared to those obtained from the mean kurtosis and the mean square error of the DFD.
Mon, 05 Dec 2016 16:29:03 GMThttp://hdl.handle.net/2117/978012016-12-05T16:29:03ZSayrol Clols, ElisaGasull Llampallas, AntoniRodríguez Fonollosa, JavierThe objective of this paper is to introduce a fourth-order cost function of the displaced frame difference (DFD) capable of estimating motion even for small regions or blocks. Using higher than second-order statistics is appropriate in case the image sequence is severely corrupted by additive Gaussian noise. Some results are presented and compared to those obtained from the mean kurtosis and the mean square error of the DFD.Senyal i comunicacions digitals per satel.lit. metodes de descomposicio sva, per estimacio conjunta de frequencia i sincronisme de bit
http://hdl.handle.net/2117/97647
Senyal i comunicacions digitals per satel.lit. metodes de descomposicio sva, per estimacio conjunta de frequencia i sincronisme de bit
Cabrera Beán, Margarita Asuncion
Thu, 01 Dec 2016 17:33:13 GMThttp://hdl.handle.net/2117/976472016-12-01T17:33:13ZCabrera Beán, Margarita AsuncionEstimacio de frequencia en comunicacions via satel.lit amb dfd's adaptatius
http://hdl.handle.net/2117/97645
Estimacio de frequencia en comunicacions via satel.lit amb dfd's adaptatius
Lamarca Orozco, M. Meritxell; Vázquez Grau, Gregorio
Senyal i comunicacions digitals per satèl·lit. Mètodes de descomposició en valors singulars, per estimació conjunta de freqüència i sincronisme de bit SENYAL I COMUNICACIONS DIGI
Thu, 01 Dec 2016 17:28:39 GMThttp://hdl.handle.net/2117/976452016-12-01T17:28:39ZLamarca Orozco, M. MeritxellVázquez Grau, GregorioSenyal i comunicacions digitals per satèl·lit. Mètodes de descomposició en valors singulars, per estimació conjunta de freqüència i sincronisme de bit SENYAL I COMUNICACIONS DIGIDevelopment and implementation of an adaptive digital beamforming network for satellite communication systems
http://hdl.handle.net/2117/97343
Development and implementation of an adaptive digital beamforming network for satellite communication systems
Barrett, M; Fernández Rubio, Juan Antonio
The use of adaptive digital beamforming techniques has, until recently, been largely restricted to high performance military radar systems. Recent advances in digital technology, however, have enabled the design of single chip digital beamforming networks. This, coupled with advances in digital signal processor technology, enables complete beamforming systems to be constructed at a lower cost, thus making the application of these techniques to commercial communications systems attractive. The design and development of such an adaptative digital beamforming network are described. The system is being developed as a proof of concept laboratory based demonstrator to enable the feasibility of adaptive digital beamforming techniques for communication systems to be determined. Ultimately, digital beamforming could be used in conjunction with large array antennas for communication satellite systems. This will enable the simultaneous steering of high gain antenna beams in the direction of gr...
Mon, 28 Nov 2016 14:57:19 GMThttp://hdl.handle.net/2117/973432016-11-28T14:57:19ZBarrett, MFernández Rubio, Juan AntonioThe use of adaptive digital beamforming techniques has, until recently, been largely restricted to high performance military radar systems. Recent advances in digital technology, however, have enabled the design of single chip digital beamforming networks. This, coupled with advances in digital signal processor technology, enables complete beamforming systems to be constructed at a lower cost, thus making the application of these techniques to commercial communications systems attractive. The design and development of such an adaptative digital beamforming network are described. The system is being developed as a proof of concept laboratory based demonstrator to enable the feasibility of adaptive digital beamforming techniques for communication systems to be determined. Ultimately, digital beamforming could be used in conjunction with large array antennas for communication satellite systems. This will enable the simultaneous steering of high gain antenna beams in the direction of gr...A stochastic approach for resource allocation with backhaul and energy harvesting constraints
http://hdl.handle.net/2117/90765
A stochastic approach for resource allocation with backhaul and energy harvesting constraints
Rubio López, Javier; Muñoz Medina, Olga; Pascual Iserte, Antonio
We propose a novel stochastic radio-resource-allocation strategy that achieves long-term fairness considering backhaul and air-interface capacity limitations. The base station (BS) is powered only with a finite battery that is recharged by an energy harvester. The energy harvesting is also taken into account in the proposed resource-allocation strategy. The constrained scenario is often found in remote rural areas where the backhaul connection is limited, and the BSs are fed with solar panels of reduced size. Our results show that the proposed scheme achieves higher fairness among the users and provides greater worst user rate and sum rate if an average backhaul constraint is considered.
Thu, 13 Oct 2016 16:17:13 GMThttp://hdl.handle.net/2117/907652016-10-13T16:17:13ZRubio López, JavierMuñoz Medina, OlgaPascual Iserte, AntonioWe propose a novel stochastic radio-resource-allocation strategy that achieves long-term fairness considering backhaul and air-interface capacity limitations. The base station (BS) is powered only with a finite battery that is recharged by an energy harvester. The energy harvesting is also taken into account in the proposed resource-allocation strategy. The constrained scenario is often found in remote rural areas where the backhaul connection is limited, and the BSs are fed with solar panels of reduced size. Our results show that the proposed scheme achieves higher fairness among the users and provides greater worst user rate and sum rate if an average backhaul constraint is considered.Multiantenna GLR detection of rank-one signals with known power spectral shape under spatially uncorrelated noise
http://hdl.handle.net/2117/90744
Multiantenna GLR detection of rank-one signals with known power spectral shape under spatially uncorrelated noise
Sala Álvarez, José; Vázquez Vilar, Gonzalo; López Valcarce, Roberto; Sedighi, Saeid; Taherpour, Abbas
We establish the generalized likelihood ratio (GLR)
test for a Gaussian signal of known power spectral shape and
unknown rank-one spatial signature in additive white Gaussian
noise with an unknown diagonal spatial correlation matrix. This
is motivated by spectrum sensing problems in dynamic spectrum
access, in which the temporal correlation of the primary signal
can be assumed known up to a scaling, and where the noise is
due to an uncalibrated receive array. For spatially independent
identically distributed (i.i.d.) noise, the corresponding GLR test
reduces to a scalar optimization problem, whereas the GLR detector
in the general non-i.i.d. case yields a more involved expression,
which can be computed via alternating optimization methods. Low
signal-to-noise ratio (SNR) approximations to the detectors are
given, together with an asymptotic analysis showing the influence
on detection performance of the signal power spectrum and SNR
distribution across antennas. Under spatial rank-P conditions, we
show that the rank-one GLR detectors are consistent with a statistical
criterion that maximizes the output energy of a beamformer
operating on filtered data. Simulation results support our theoretical
findings in that exploiting prior knowledge on the signal power
spectrum can result in significant performance improvement.
Thu, 13 Oct 2016 13:08:29 GMThttp://hdl.handle.net/2117/907442016-10-13T13:08:29ZSala Álvarez, JoséVázquez Vilar, GonzaloLópez Valcarce, RobertoSedighi, SaeidTaherpour, AbbasWe establish the generalized likelihood ratio (GLR)
test for a Gaussian signal of known power spectral shape and
unknown rank-one spatial signature in additive white Gaussian
noise with an unknown diagonal spatial correlation matrix. This
is motivated by spectrum sensing problems in dynamic spectrum
access, in which the temporal correlation of the primary signal
can be assumed known up to a scaling, and where the noise is
due to an uncalibrated receive array. For spatially independent
identically distributed (i.i.d.) noise, the corresponding GLR test
reduces to a scalar optimization problem, whereas the GLR detector
in the general non-i.i.d. case yields a more involved expression,
which can be computed via alternating optimization methods. Low
signal-to-noise ratio (SNR) approximations to the detectors are
given, together with an asymptotic analysis showing the influence
on detection performance of the signal power spectrum and SNR
distribution across antennas. Under spatial rank-P conditions, we
show that the rank-one GLR detectors are consistent with a statistical
criterion that maximizes the output energy of a beamformer
operating on filtered data. Simulation results support our theoretical
findings in that exploiting prior knowledge on the signal power
spectrum can result in significant performance improvement.The K-filter: a new architecture to model and design non-linear systems from Kolmogorov's theorem
http://hdl.handle.net/2117/88138
The K-filter: a new architecture to model and design non-linear systems from Kolmogorov's theorem
Pagès Zamora, Alba Maria; Lagunas Hernandez, Miguel A.; Nájar Martón, Montserrat; Pérez Neira, Ana Isabel
A new architecture to model and design nonlinear transfer functions is presented using a new formulation for nonlinear systems. This approach follows the guidelines of the mapping theorem due to A. Kolmogorov and it is based on the direct Fourier transform of the transfer function. The resulting scheme is formed by two stages; the first stage contains phase modulators, which, based on random sampling concepts reported by I. Bilinskis, are duplicated with a small perturbation in the modulation factor. This stage depends on the number of diversity data and it is independent of the function. The second step reduces to Volterra systems and a direct combiner of the new diversity kernels. The reported architecture and design seem to be able to cope with both linear and nonlinear filtering problems, which can be considered as a formal framework for generalised signal processing.
Fri, 17 Jun 2016 14:29:15 GMThttp://hdl.handle.net/2117/881382016-06-17T14:29:15ZPagès Zamora, Alba MariaLagunas Hernandez, Miguel A.Nájar Martón, MontserratPérez Neira, Ana IsabelA new architecture to model and design nonlinear transfer functions is presented using a new formulation for nonlinear systems. This approach follows the guidelines of the mapping theorem due to A. Kolmogorov and it is based on the direct Fourier transform of the transfer function. The resulting scheme is formed by two stages; the first stage contains phase modulators, which, based on random sampling concepts reported by I. Bilinskis, are duplicated with a small perturbation in the modulation factor. This stage depends on the number of diversity data and it is independent of the function. The second step reduces to Volterra systems and a direct combiner of the new diversity kernels. The reported architecture and design seem to be able to cope with both linear and nonlinear filtering problems, which can be considered as a formal framework for generalised signal processing.Robust non-linear precoding for downlink multiuser multiple-input multiple-output orthogonal frequency-division multiplexing systems with limited feedback
http://hdl.handle.net/2117/87169
Robust non-linear precoding for downlink multiuser multiple-input multiple-output orthogonal frequency-division multiplexing systems with limited feedback
Font Segura, Josep; Su, Y.; Wang, Xiaodong
The authors consider the robust Tomlinson–Harashima precoding (THP) for downlink multiuser multiple-input
multiple-output orthogonal frequency-division multiplexing systems with quantised feedback. The authors discuss vector
channel feedback strategies in the frequency and time domains, and develop a robust version of THP that takes into account
of error statistics of the channel state information, that consists of the optimal feedforward filters, feedback filters and the
receive filters. Feedback techniques are developed to exploit the spatial correlations in realistic 3GPP channel models by
applying dimension reduction and scalar-quantisation. Extensive simulations results are provided to demonstrate the
performance of the proposed robust THP design as well as the channel feedback scheme.
Wed, 18 May 2016 15:24:43 GMThttp://hdl.handle.net/2117/871692016-05-18T15:24:43ZFont Segura, JosepSu, Y.Wang, XiaodongThe authors consider the robust Tomlinson–Harashima precoding (THP) for downlink multiuser multiple-input
multiple-output orthogonal frequency-division multiplexing systems with quantised feedback. The authors discuss vector
channel feedback strategies in the frequency and time domains, and develop a robust version of THP that takes into account
of error statistics of the channel state information, that consists of the optimal feedforward filters, feedback filters and the
receive filters. Feedback techniques are developed to exploit the spatial correlations in realistic 3GPP channel models by
applying dimension reduction and scalar-quantisation. Extensive simulations results are provided to demonstrate the
performance of the proposed robust THP design as well as the channel feedback scheme.A diffusion-based em algorithm for distributed estimation in unreliable sensor networks
http://hdl.handle.net/2117/86785
A diffusion-based em algorithm for distributed estimation in unreliable sensor networks
Silva Pereira, Silvana; López Valcarce, Roberto; Pagès Zamora, Alba Maria
We address the problem of distributed estimation of
a parameter from a set of noisy observations collected by a sensor
network, assuming that some sensors may be subject to data failures
and report only noise. In such scenario, simple schemes such
as the Best Linear Unbiased Estimator result in an error floor in
moderate and high signal-to-noise ratio (SNR), whereas previously
proposed methods based on hard decisions on data failure events
degrade as the SNR decreases. Aiming at optimal performance
within the whole range of SNRs, we adopt a Maximum Likelihood
framework based on the Expectation-Maximization (EM) algorithm.
The statistical model and the iterative nature of the EM
method allow for a diffusion-based distributed implementation,
whereby the information propagation is embedded in the iterative
update of the parameters. Numerical examples show that the proposed
algorithm practically attains the Cramer–Rao Lower Bound
at all SNR values and compares favorably with other approaches.
Mon, 09 May 2016 13:09:07 GMThttp://hdl.handle.net/2117/867852016-05-09T13:09:07ZSilva Pereira, SilvanaLópez Valcarce, RobertoPagès Zamora, Alba MariaWe address the problem of distributed estimation of
a parameter from a set of noisy observations collected by a sensor
network, assuming that some sensors may be subject to data failures
and report only noise. In such scenario, simple schemes such
as the Best Linear Unbiased Estimator result in an error floor in
moderate and high signal-to-noise ratio (SNR), whereas previously
proposed methods based on hard decisions on data failure events
degrade as the SNR decreases. Aiming at optimal performance
within the whole range of SNRs, we adopt a Maximum Likelihood
framework based on the Expectation-Maximization (EM) algorithm.
The statistical model and the iterative nature of the EM
method allow for a diffusion-based distributed implementation,
whereby the information propagation is embedded in the iterative
update of the parameters. Numerical examples show that the proposed
algorithm practically attains the Cramer–Rao Lower Bound
at all SNR values and compares favorably with other approaches.