Ponències/Comunicacions de congressos
http://hdl.handle.net/2117/1257
Fri, 02 Dec 2016 18:07:02 GMT
20161202T18:07:02Z

Distributed multivariate regression with unknown noise covariance in the presence of outliers: an MDL approach
http://hdl.handle.net/2117/97423
Distributed multivariate regression with unknown noise covariance in the presence of outliers: an MDL approach
López Valcarce, Roberto; Romero Gonzalez, Daniel; Sala Álvarez, José; Pagès Zamora, Alba Maria
We consider the problem of estimating the coefficients in a multivariable linear model by means of a wireless sensor network which may be affected by anomalous measurements. The noise covariance matrices at the different sensors are assumed unknown. Treating outlying samples, and their support, as additional nuisance parameters, the Maximum Likelihood estimate is investigated, with the number of outliers being estimated according to the Minimum
Description Length principle. A distributed implementation based on iterative consensus techniques is then proposed, and it is shown effective for managing outliers in the data.
Tue, 29 Nov 2016 13:31:08 GMT
http://hdl.handle.net/2117/97423
20161129T13:31:08Z
López Valcarce, Roberto
Romero Gonzalez, Daniel
Sala Álvarez, José
Pagès Zamora, Alba Maria
We consider the problem of estimating the coefficients in a multivariable linear model by means of a wireless sensor network which may be affected by anomalous measurements. The noise covariance matrices at the different sensors are assumed unknown. Treating outlying samples, and their support, as additional nuisance parameters, the Maximum Likelihood estimate is investigated, with the number of outliers being estimated according to the Minimum
Description Length principle. A distributed implementation based on iterative consensus techniques is then proposed, and it is shown effective for managing outliers in the data.

Distributed AOAbased source positioning in NLOS with sensor networks
http://hdl.handle.net/2117/97377
Distributed AOAbased source positioning in NLOS with sensor networks
Giménez Febrer, Pedro Juan; Pagès Zamora, Alba Maria; Silva Pereira, Silvana; López Valcarce, Roberto
This paper focuses on the problem of positioning a
source using angleofarrival measurements taken by a wireless
sensor network in which some of the nodes experience non lineofsight
(LOS) propagation conditions. In order to mitigate the
errors induced by the nodes in NLOS, we derive an algorithm
that combines the expectationmaximization algorithm with a
weighted leastsquares estimation of the source position so that
the nodes in NLOS are eventually identified and discarded.
Moreover, a distributed version of this algorithm based on a
diffusion strategy that iteratively refines the position estimate
while driving the network to a consensus is presented.
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Tue, 29 Nov 2016 08:59:43 GMT
http://hdl.handle.net/2117/97377
20161129T08:59:43Z
Giménez Febrer, Pedro Juan
Pagès Zamora, Alba Maria
Silva Pereira, Silvana
López Valcarce, Roberto
This paper focuses on the problem of positioning a
source using angleofarrival measurements taken by a wireless
sensor network in which some of the nodes experience non lineofsight
(LOS) propagation conditions. In order to mitigate the
errors induced by the nodes in NLOS, we derive an algorithm
that combines the expectationmaximization algorithm with a
weighted leastsquares estimation of the source position so that
the nodes in NLOS are eventually identified and discarded.
Moreover, a distributed version of this algorithm based on a
diffusion strategy that iteratively refines the position estimate
while driving the network to a consensus is presented.

Analysis of LDPC code syndrome entropy based on subgraphs
http://hdl.handle.net/2117/96486
Analysis of LDPC code syndrome entropy based on subgraphs
Matas Navarro, David; Lamarca Orozco, M. Meritxell
We propose a method to bound the syndrome entropy of linear block codes from their factor graph representation. It is specially suited for sparse graphs such as those of low density parity check codes. It is based on the chain rule decomposition of the entropy and the confinement of dependencies within code subgraphs. After
forcing or assuming the subgraphs to have a tree structure, the computation is done by means of density evolution as for a belief propagation analysis. We employ this method to compute upper bounds of the LDPC code syndrome entropy, which allows us to obtain asymptotic MAP upper bounds that match the ones obtained by the generalized area theorem.
Thu, 10 Nov 2016 13:54:08 GMT
http://hdl.handle.net/2117/96486
20161110T13:54:08Z
Matas Navarro, David
Lamarca Orozco, M. Meritxell
We propose a method to bound the syndrome entropy of linear block codes from their factor graph representation. It is specially suited for sparse graphs such as those of low density parity check codes. It is based on the chain rule decomposition of the entropy and the confinement of dependencies within code subgraphs. After
forcing or assuming the subgraphs to have a tree structure, the computation is done by means of density evolution as for a belief propagation analysis. We employ this method to compute upper bounds of the LDPC code syndrome entropy, which allows us to obtain asymptotic MAP upper bounds that match the ones obtained by the generalized area theorem.

Distributed TLS estimation under random data faults
http://hdl.handle.net/2117/91173
Distributed TLS estimation under random data faults
Silva Pereira, Silvana; Pagès Zamora, Alba Maria; López Valcarce, Roberto
This paper addresses the problem of distributed estimation of a parameter vector in the presence of noisy input and noisy output data, as well as data faults, performed by a wireless sensor network in which only local interactions among the nodes are allowed. In the presence of unreliable observations, standard estimators become biased and perform poorly in low signaltonoise ratios. We propose therefore two different distributed approaches based on the ExpectationMaximization algorithm: in the first one the regressors are estimated at each iteration, whereas the second one does not require explicit regressor estimation. Numerical results show that the proposed methods approach the performance of a clairvoyant scheme with knowledge of the random data faults.
Thu, 27 Oct 2016 14:48:23 GMT
http://hdl.handle.net/2117/91173
20161027T14:48:23Z
Silva Pereira, Silvana
Pagès Zamora, Alba Maria
López Valcarce, Roberto
This paper addresses the problem of distributed estimation of a parameter vector in the presence of noisy input and noisy output data, as well as data faults, performed by a wireless sensor network in which only local interactions among the nodes are allowed. In the presence of unreliable observations, standard estimators become biased and perform poorly in low signaltonoise ratios. We propose therefore two different distributed approaches based on the ExpectationMaximization algorithm: in the first one the regressors are estimated at each iteration, whereas the second one does not require explicit regressor estimation. Numerical results show that the proposed methods approach the performance of a clairvoyant scheme with knowledge of the random data faults.

Efficient bitlevel design of an onboard digital TV demultiplexer
http://hdl.handle.net/2117/88670
Efficient bitlevel design of an onboard digital TV demultiplexer
Sala Álvarez, José; Pagès Zamora, Alba Maria; Vázquez Grau, Gregorio
A bitlevel description of the signal processing stage of an onboard integrated VLSI multicarrier demodulator is presented in this paper, along with a description of the optimization procedure that has been developed for the signal processing functions1. The demultiplexer is capable of handling a varying number of carriers in a 36 MHz bandwidth on the satellite uplink. Its architecture has been optimized at bitlevel in a way dependent on the known input signal statistics and carrier distributions allowed by the frequency plan.
Mon, 11 Jul 2016 11:00:59 GMT
http://hdl.handle.net/2117/88670
20160711T11:00:59Z
Sala Álvarez, José
Pagès Zamora, Alba Maria
Vázquez Grau, Gregorio
A bitlevel description of the signal processing stage of an onboard integrated VLSI multicarrier demodulator is presented in this paper, along with a description of the optimization procedure that has been developed for the signal processing functions1. The demultiplexer is capable of handling a varying number of carriers in a 36 MHz bandwidth on the satellite uplink. Its architecture has been optimized at bitlevel in a way dependent on the known input signal statistics and carrier distributions allowed by the frequency plan.

A distributed arithmetics architecture for quantization SNR improvement based on LUT recoding
http://hdl.handle.net/2117/88669
A distributed arithmetics architecture for quantization SNR improvement based on LUT recoding
Rubio Fernández, José; Sala Álvarez, José
Mon, 11 Jul 2016 10:59:44 GMT
http://hdl.handle.net/2117/88669
20160711T10:59:44Z
Rubio Fernández, José
Sala Álvarez, José

HISPANET: a digital television/multimedia payload
http://hdl.handle.net/2117/88668
HISPANET: a digital television/multimedia payload
Sala Álvarez, José; Sergio, Calvo; Pagès Zamora, Alba Maria; Vázquez Grau, Gregorio; Riba Sagarra, Jaume
Mon, 11 Jul 2016 10:57:26 GMT
http://hdl.handle.net/2117/88668
20160711T10:57:26Z
Sala Álvarez, José
Sergio, Calvo
Pagès Zamora, Alba Maria
Vázquez Grau, Gregorio
Riba Sagarra, Jaume

A fast OFDMCDMA user demultiplexing architecture
http://hdl.handle.net/2117/88665
A fast OFDMCDMA user demultiplexing architecture
Marti Puig, Pere; Sala Álvarez, José
A fast algorithm based on a butterfly structure is presented that demultiplexes the symbols of a particular type of MCMA (multicarrier multipleaccess) modulation previously proposed for indoor radio communications. A special transform is used to packetize the different symbols on the downlink such that the code sequences associated with the different symbols are transmitted synchronously at the base station. The input to the FFT bins is defined as a symboldependent combination of WalshHadamard codes. We derive a fast architecture that can combine the common redundancy found in the WalshHadamard and the inverse Fourier transform. In the direct implementation, the receiver would compute the IFFT (as in OFDM) before the WalshHadamard transform. The proposed algorithm evaluates both transforms in a single step. A general expression for the butterfly weights is derived and the savings in computational complexity in terms of the frame length is evaluated.
Mon, 11 Jul 2016 10:52:18 GMT
http://hdl.handle.net/2117/88665
20160711T10:52:18Z
Marti Puig, Pere
Sala Álvarez, José
A fast algorithm based on a butterfly structure is presented that demultiplexes the symbols of a particular type of MCMA (multicarrier multipleaccess) modulation previously proposed for indoor radio communications. A special transform is used to packetize the different symbols on the downlink such that the code sequences associated with the different symbols are transmitted synchronously at the base station. The input to the FFT bins is defined as a symboldependent combination of WalshHadamard codes. We derive a fast architecture that can combine the common redundancy found in the WalshHadamard and the inverse Fourier transform. In the direct implementation, the receiver would compute the IFFT (as in OFDM) before the WalshHadamard transform. The proposed algorithm evaluates both transforms in a single step. A general expression for the butterfly weights is derived and the savings in computational complexity in terms of the frame length is evaluated.

Design and implementation of a DVB onBoard multicarrier demodulator
http://hdl.handle.net/2117/88656
Design and implementation of a DVB onBoard multicarrier demodulator
Sala Álvarez, José; Pagès Zamora, Alba Maria; Sergio, Calvo; Prat Gomà, Josep Joan
A description of the signal processing stage of an onboard integrated VLSI multicarrier demodulator at the demultiplexing level is presented, along with a description of the optimization procedure that has been developed for the signal processing functions. The varying adjacent carrier interference and channel noise distribution are modeled to provide the best performing demultiplexing scheme under the given carrier distribution with minimum complexity.
Mon, 11 Jul 2016 09:47:15 GMT
http://hdl.handle.net/2117/88656
20160711T09:47:15Z
Sala Álvarez, José
Pagès Zamora, Alba Maria
Sergio, Calvo
Prat Gomà, Josep Joan
A description of the signal processing stage of an onboard integrated VLSI multicarrier demodulator at the demultiplexing level is presented, along with a description of the optimization procedure that has been developed for the signal processing functions. The varying adjacent carrier interference and channel noise distribution are modeled to provide the best performing demultiplexing scheme under the given carrier distribution with minimum complexity.

A statistical reference criterion for adaptive filtering
http://hdl.handle.net/2117/88652
A statistical reference criterion for adaptive filtering
Sala Álvarez, José; Vázquez Grau, Gregorio
A cost function for adaptive filtering is proposed, based on the statistical reference criterion. The purpose of this criterion is to enforce a given probability density function at the output of a system. The only aprioristical knowledge utilized is that of the target PDF. This makes it particularly suitable for blind adaptation in the context of arrays in contrast to temporal or spatial reference techniques. Applications that are foreseen are: blind channel equalization, adaptive beamforming for single or multiple signals and source separation. The main goal is blind signal recovery in unfavourable wanted signaltoinference power ratios.
Mon, 11 Jul 2016 09:20:43 GMT
http://hdl.handle.net/2117/88652
20160711T09:20:43Z
Sala Álvarez, José
Vázquez Grau, Gregorio
A cost function for adaptive filtering is proposed, based on the statistical reference criterion. The purpose of this criterion is to enforce a given probability density function at the output of a system. The only aprioristical knowledge utilized is that of the target PDF. This makes it particularly suitable for blind adaptation in the context of arrays in contrast to temporal or spatial reference techniques. Applications that are foreseen are: blind channel equalization, adaptive beamforming for single or multiple signals and source separation. The main goal is blind signal recovery in unfavourable wanted signaltoinference power ratios.