Papers by Raimundo Sampaio-Neto
In this paper, cooperation in CS-CDMA wireless sensor networks (WSN) is considered in order to im... more In this paper, cooperation in CS-CDMA wireless sensor networks (WSN) is considered in order to improve the quality of the estimates of the sensor messages used by the fusion center to generate the final decision. In the proposed cooperative wireless sensor networks each node forwards its own decisions and relays the message of a neighbor sensor deploying the detectand-forward cooperation. Simulations have shown that with cooperative distributed detection and exploitation of spatial diversity, better detection error performance is achieved and the number of sensor can be reduced. The performance gain is however more significant in flat fading environment, since in multipath environment the non-cooperative CS-CDMA WSN already exploits efficiently the multipath diversity.
18th IEEE International Symposium on Power Line Communications and Its Applications, 2014
This work aims at offering an initial analysis of coherence time and sparsity of power line commu... more This work aims at offering an initial analysis of coherence time and sparsity of power line communication (PLC) channels, which were measured in the outdoor and low-voltage electric distribution networks in Brazil. In this regard, a procedure for estimating coherence time and sparsity of PLC channels is described. In the sequel, estimates of coherence time and sparsity of several measures of Brazilian PLC channels are reported. The attained results confirm that only the coefficients of channel impulse responses with the largest amplitudes are relevant to estimate the coherence time. Moreover, they also indicate that the sparsity of PLC channel is a random variable that deserves more investigation and analysis.
2014 11th International Symposium on Wireless Communications Systems (ISWCS), 2014
In this work we propose an adaptive fusion procedure to perform data detection in distributed det... more In this work we propose an adaptive fusion procedure to perform data detection in distributed detection systems with a decode-then-fuse type of receiver. Differently from previously proposed fusion rules, where nodes statistics (i.e. miss detection, false alarm and a priori probabilities) and channel transition probabilities are generally needed, the proposed nonassisted adaptive fusion algorithm adapts its coefficients and decision threshold based only on the received signals, so that time-varying or inhomogeneous distributed detection systems are well suited. Computer simulations show that the proposed adaptive fusion strategy delivers a performance very close to the optimal fusion rule.
SBrT 2013, 2013
In this paper, cooperation in CS-CDMA wireless sensor networks (WSN) is considered in order to im... more In this paper, cooperation in CS-CDMA wireless sensor networks (WSN) is considered in order to improve the quality of the estimates of the sensor messages used by the fusion center to generate the final decision. In the proposed cooperative wireless sensor networks each node forwards its own decisions and relays the message of a neighbor sensor deploying the detectand-forward cooperation. Simulations have shown that with cooperative distributed detection and exploitation of spatial diversity, better detection error performance is achieved and the number of sensor can be reduced. The performance gain is however more significant in flat fading environment, since in multipath environment the non-cooperative CS-CDMA WSN already exploits efficiently the multipath diversity.
Enhanced blind minimum variance CDMA receivers with joint channel estimation for frequency selective channels
IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004, 2004
We propose an enhanced blind constrained minimum variance (CMV) CDMA receiver with joint channel ... more We propose an enhanced blind constrained minimum variance (CMV) CDMA receiver with joint channel estimation for frequency selective channels. We develop a CMV solution for multipath using a recently proposed enhanced correlation matrix and investigate the performance of the proposed approach with a low complexity blind channel estimation algorithm based on the power method. Simulation results show significant improvements for
Low Complexity Blind Constrained Data-Reusing Algorithms Based on Minimum Variance and Constant Modulus Criteria
2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, 2006
This work presents low complexity blind constrained data-reusing adaptive filtering algorithms ba... more This work presents low complexity blind constrained data-reusing adaptive filtering algorithms based on the minimum variance and constant modulus cost functions. Constrained minimum variance (CMV) and constrained constant modulus (CCM) affine projection type algorithms are developed and investigated in a CDMA interference suppression scenario. Computer simulations are used to analyze the proposed techniques and compare them with existing stochastic gradient (SG) and recursive least-squares (RLS) type techniques. The results show that the new algorithms outperform previously reported SG techniques with small additional computational requirements and achieve a performance very close to RLS algorithms at greatly reduced complexity
Adaptive Decision Feedback Multiuser Detectors with Recurrent Neural Networks for DS-CDMA in Fading Channels
In this work we propose adaptive decision feedback (DF) multiuser detectors (MUDs) for DS-CDMA sy... more In this work we propose adaptive decision feedback (DF) multiuser detectors (MUDs) for DS-CDMA systems using recurrent neural networks (RNN). A DF CDMA receiver structure is presented with dynamically driven RNNs in the feedforward section and finite impulse response (FIR) linear filters in the feedback section for performing interference cancellation. A stochastic gradient (SG) algorithm is developed for estimation of the parameters of the proposed receiver structure. A comparative analysis of adaptive minimum mean squared error (MMSE) receivers operating with SG algorithms is carried out for linear and DF receivers with FIR filters and neural receiver structures with and without DF. Simulation experiments including fading channels show that the DF neural MUD outperforms DF MUDs with linear FIR filters, linear receivers and the neural receiver without interference cancellation.
IEEE Transactions on Vehicular Technology
In this paper, we examine blind adaptive and iterative decision-feedback (DF) receivers for direc... more In this paper, we examine blind adaptive and iterative decision-feedback (DF) receivers for direct-sequence codedivision multiple-access systems in frequency-selective channels. Code-constrained minimum variance and constant modulus design criteria for DF receivers based on constrained optimization techniques are investigated for scenarios subject to multipath. Computationally efficient blind adaptive stochastic gradient and recursive least squares algorithms are developed for estimating the parameters of DF detectors along with successive, parallel, and iterative DF structures. A novel successive parallel arbitrated DF scheme is presented and combined with iterative techniques for use with cascaded DF stages in order to mitigate the deleterious effects of error propagation. Simulation results for an uplink scenario assess the algorithms and the blind adaptive DF detectors against linear receivers and evaluate the effects of error propagation of the new cancellation techniques against previously reported approaches.
IEEE Transactions on Audio Speech and Language Processing
This paper presents a new approach to efficient acoustic echo cancellation (AEC) based on reduced... more This paper presents a new approach to efficient acoustic echo cancellation (AEC) based on reduced-rank adaptive filtering equipped with selective-decimation and adaptive interpolation. We propose a novel structure of an AEC scheme that jointly optimizes an interpolation filter, a decimation unit, and a reduced-rank filter. With a practical choice of parameters in AEC, the total computational complexity of the proposed reduced-rank scheme with the normalized least mean square (NLMS) algorithm is approximately half of that of the full-rank NLMS algorithm. We discuss the convergence properties of the proposed scheme and present a convergence condition. First, we examine the performance of the proposed scheme in a single-talk situation with an error-minimization criterion adopted in the decimation selection. Second, we investigate the potential of the proposed scheme in a double-talk situation by employing an ideal decimation selection. In addition to mean squared error (MSE) and power spectrum analysis of the echo estimation error, subjective assessments based on absolute category rating are performed, and the results demonstrate that the proposed structure provides significant improvements compared to the full-rank NLMS algorithm.
Signal Detection and Parameter Estimation in Massive MIMO Systems
Advances and Results in Speech, Estimation, Compression, Recognition, Filtering, and Processing, 2015
n this work we examine blind adaptive and iterative decision feedback (DF) receivers for direct s... more n this work we examine blind adaptive and iterative decision feedback (DF) receivers for direct sequence code division multiple access (DS-CDMA) systems in frequency selective channels. Code-constrained minimum variance (CMV) and constant modulus (CCM) design criteria for DF receivers based on constrained optimization techniques are investigated for scenarios subject to multipath. Computationally efficient blind adaptive stochastic gradient (SG) and recursive least squares (RLS) algorithms are developed for estimating the parameters of DF detectors along with successive, parallel and iterative DF structures. A novel successive parallel arbitrated DF scheme is presented and combined with iterative techniques for use with cascaded DF stages in order to mitigate the deleterious effects of error propagation. Simulation results for an uplink scenario assess the algorithms, the blind adaptive DF detectors against linear receivers and evaluate the effects of error propagation of the new cancellations techniques against previously reported approaches.n this work we examine blind adaptive and iterative decision feedback (DF) receivers for direct sequence code division multiple access (DS-CDMA) systems in frequency selective channels. Code-constrained minimum variance (CMV) and constant modulus (CCM) design criteria for DF receivers based on constrained optimization techniques are investigated for scenarios subject to multipath. Computationally efficient blind adaptive stochastic gradient (SG) and recursive least squares (RLS) algorithms are developed for estimating the parameters of DF detectors along with successive, parallel and iterative DF structures. A novel successive parallel arbitrated DF scheme is presented and combined with iterative techniques for use with cascaded DF stages in order to mitigate the deleterious effects of error propagation. Simulation results for an uplink scenario assess the algorithms, the blind adaptive DF detectors against linear receivers and evaluate the effects of error propagation of the new cancellations techniques against previously reported approaches.I
In this work we propose an adaptive linear receiver structure based on interpolated finite impuls... more In this work we propose an adaptive linear receiver structure based on interpolated finite impulse response (FIR) filters with adaptive interpolators for direct sequence code division multiple access (DS-CDMA) systems in multipath channels.
This paper presents a novel adaptive reducedrank multi-input-multi-output (MIMO) decision feedbac... more This paper presents a novel adaptive reducedrank multi-input-multi-output (MIMO) decision feedback equalization structure based on joint iterative optimization of adaptive estimators. The novel reduced-rank equalization structure consists of a joint iterative optimization of two equalization stages, namely, a projection matrix that performs dimensionality reduction and a reduced-rank estimator that retrieves the desired transmitted symbol. The proposed reducedrank structure is followed by a decision feedback scheme that is responsible for cancelling the inter-antenna interference caused by the associated data streams. We describe least squares (LS) expressions for the design of the projection matrix and the reduced-rank estimator along with computationally efficient recursive least squares (RLS) adaptive estimation algorithms. Simulations for a MIMO equalization application show that the proposed scheme outperforms the state-of-the-art reduced-rank and the conventional estimation algorithms at about the same complexity.
Massive Multiple-input Multiple-output (MIMO) systems offer exciting opportunities due to their h... more Massive Multiple-input Multiple-output (MIMO) systems offer exciting opportunities due to their high spectral efficiencies capabilities. On the other hand, one major issue in these scenarios is the high-complexity detectors of such systems. In this work, we present a low-complexity, near maximumlikelihood (ML) performance achieving detector for the uplink in large MIMO systems with tens to hundreds of antennas at the base station (BS) and similar number of uplink users. The proposed algorithm is derived from the likelihood-ascent search (LAS) algorithm and it is shown to achieve near ML performance as well as to possess excellent complexity attribute. The presented algorithm, termed as random-list based LAS (RLB-LAS), employs several iterative LAS search procedures whose starting-points are in a list generated by random changes in the matched filter detected vector and chooses the best LAS result. Also, a stop criterion was proposed in order to maintain the algorithm's complexity at low levels. Near-ML performance detection is demonstrated by means of Monte Carlo simulations and it is shown that this performance is achieved with complexity of just O(K 2 ) per symbol, where K denotes the number of single-antenna uplink users.
Resumo— Os sistemas de transmissão em blocos, permitem a transmissão de N símbolos de forma simul... more Resumo— Os sistemas de transmissão em blocos, permitem a transmissão de N símbolos de forma simultânea , seja em modulaç ao de portadorá unica ou multiportadora. A recepç aó otima, no sentido de máxima verossimilhança em canais com multipercursos apresenta um custo computacional elevado de A N , onde A ´ e a ordem da constelaç ao (A = 2 para BPSK). Para evitar este alto custo computacionaí e usual fazer a detecç ao símbolo a símbolo após a equalizaç ao. Neste trabalhó e proposto um receptor com detecç ao por grupos que apresenta um bom compromisso entre complexidade computacional e desempenho em termos de taxa de erro médio de bit. Palavras-Chave— OFDM, sistemas de portadorá unica, detecç ao por grupos, detecç ao ML Abstract— Block transmission system, allows transmissions of N symbols simultaneously, with single carrier or multi-carrier modulation. Maximum likelihood optimal reception in multipath channels have a high computational cost of A N , where A is the constellation order (...
Block transmission system, allows transmissions of N symbols simultaneously, with single carrier ... more Block transmission system, allows transmissions of N symbols simultaneously, with single carrier or multi-carrier modulation. Maximum likelihood optimal reception in multipath channels have a high computational cost of AN, where A is the constellation order (A = 2 for BPSK). To avoid this cost is usual to make symbol by symbol detection after equalization. In this work we propose a receiver with group detection having a good trade of between computation complexity and bit error rate performance.
Performance comparison of minimum variance single carrier and multicarrier cdma receivers
This work provides comparisons between CDMA-based multiple access systems in a single and multica... more This work provides comparisons between CDMA-based multiple access systems in a single and multicarrier fashion. Both zero padding and cyclic prefix types of guard intervals are considered. Comparisons include different performance measures such as signal-to-interference plus noise ratio (SINR), bit error rate (BER), and robustness against channel order overestimation. We also address the effects of finite number of samples when estimating the detector filter. In order to allow a fair comparison, blind detection based on the minimum variance is assumed for all considered systems. It is shown through computer simulations that multicarrier CDMA performs better than single carrier CDMA and is more robust against channel order overestimation.
Sparse IR-UWB Channel Identification Based on Successive Relaxations and Least Squares Estimation
In this article, a simple method for sparse impulseradio ultra-wideband (IR-UWB) channel estimati... more In this article, a simple method for sparse impulseradio ultra-wideband (IR-UWB) channel estimation is presented. The aim of the proposed method is to find a sparse channel estimate by making successive relaxations of the full-rank channel estimate. The idea of relaxation is to build a new vector by zeroing, in a successive and appropriate fashion, one or more elements of the full-rank least squares estimate, until the cost function exceeds an appropriate threshold. This is done while the least squares estimate associated with the reduced support (set of the indexes of the nonzero elements) of the vector is computed. This procedure is successively repeated until there is no further reduction in the cardinality of the support. The proposed algorithm can incorporate any technique for computing least squares estimates. Simulation results show that a significant convergence performance improvement of the proposed method over the conventional least squares solution with or without the l1...
Equalização De Canal Em Sistemas Com Transmissão Em Blocos
Projection-Based List Detection in Generalized Spatial Modulation MIMO Systems
IEEE Communications Letters, 2015
ABSTRACT
Uploads
Papers by Raimundo Sampaio-Neto