arXiv subjects

R. C. de Lamare

Publications and source records attributed to R. C. de Lamare.

At least 127 records · Page 7Linked to original sources

arXiv2016

Distributed Space-Time Coding Techniques with Dynamic Buffers for Cooperative DS-CDMA Systems

In this work, we propose a dynamic buffer-aided distributed space-time coding (DSTC) scheme for cooperative direct-sequence code-division multiple access systems. We first devise a relay selection algorithm that can automatically select the optimum set of relays among both the source-relay phase and the relay-destination phase for DSTC transmission according to the signal-to-interference-plus-noise ratio (SINR) criterion. Multiple relays equipped with dynamic buffers are introduced in the network, which allows the relays to store data received from the sources and wait until the most appropriate time for transmission. The proposed technique improves the quality of the transmission with an acceptable delay as the buffer size is adjustable. Simulation results show that the proposed dynamic buffer-aided DSTC scheme and algorithm outperforms prior art.

cs.IT↗

arXiv2016

Design of Robust Adaptive Beamforming Algorithms Based on Low-Rank and Cross-Correlation Techniques

This work presents cost-effective low-rank techniques for designing robust adaptive beamforming (RAB) algorithms. The proposed algorithms are based on the exploitation of the cross-correlation between the array observation data and the output of the beamformer. Firstly, we construct a general linear equation considered in large dimensions whose solution yields the steering vector mismatch. Then, we employ the idea of the full orthogonalization method (FOM), an orthogonal Krylov subspace based method, to iteratively estimate the steering vector mismatch in a reduced-dimensional subspace, resulting in the proposed orthogonal Krylov subspace projection mismatch estimation (OKSPME) method. We also devise adaptive algorithms based on stochastic gradient (SG) and conjugate gradient (CG) techniques to update the beamforming weights with low complexity and avoid any costly matrix inversion. The main advantages of the proposed low-rank and mismatch estimation techniques are their cost-effectiveness when dealing with high dimension subspaces or large sensor arrays. Simulations results show excellent performance in terms of the output signal-to-interference-plus-noise ratio (SINR) of the beamformer among all the compared RAB methods.

cs.CE↗

arXiv2016

Study of Relay Selection for Physical-Layer Security in Buffer-Aided Relay Networks Based on the Secrecy Rate Criterion

In this paper, we investigate an opportunistic relay and jammer scheme along with relay selection algorithms based on the secrecy rate criterion in multiple-input multiple-output buffer-aided down link relay networks, which consist of one source, a number of relay nodes, legitimate users and eavesdroppers, with the constraints of physical layer security. The opportunistic relay and jammer scheme is employed to improve the transmission rate and different relay selection policies are performed to achieve better secrecy rate with the consideration of eavesdroppers. Among all the investigated relay selection policies, a relay selection policy which is developed to maximize the secrecy rate based on exhaustive searches outperforms other relay selection policies in terms of secrecy rate. Based on the secrecy rate criterion, we develop a relay selection algorithm without knowledge of the channels of the eavesdroppers. We also devise a greedy search algorithm based on the secrecy rate criterion to reduce the computational complexity of the exhaustive search technique. Simulations show the superiority of the secrecy rate criterion over competing approaches.

cs.IT↗

arXiv2016

Study of Distributed Spectrum Estimation Using Alternating Mixed Discrete-Continuous Adaptation

This paper proposes a distributed alternating mixed discrete-continuous (DAMDC) algorithm to approach the oracle algorithm based on the diffusion strategy for parameter and spectrum estimation over sensor networks. A least mean squares (LMS) type algorithm that obtains the oracle matrix adaptively is developed and compared with the existing sparsity-aware and conventional algorithms. The proposed algorithm exhibits improved performance in terms of mean square deviation and power spectrum estimation accuracy. Numerical results show that the DAMDC algorithm achieves excellent performance.

cs.DC↗

arXiv2016

Study of Interference Cancellation and Relay Selection Algorithms Using Greedy Techniques for Cooperative DS-CDMA Systems

In this work, we study interference cancellation techniques and a multi-relay selection algorithm based on greedy methods for the uplink of cooperative direct-sequence code-division multiple access (DS-CDMA) systems. We first devise low-cost list-based successive interference cancellation (GL-SIC) and parallel interference cancellation (GL-PIC) algorithms with RAKE receivers as the front-end that can approach the maximum likelihood detector performance and be used at both the relays and the destination of cooperative systems. Unlike prior art, the proposed GL-SIC and GL-PIC algorithms exploit the Euclidean distance between users of interest and the potential nearest constellation point with a chosen threshold in order to build an effective list of detection candidates. A low-complexity multi-relay selection algorithm based on greedy techniques that can approach the performance of an exhaustive search is also proposed. A cross-layer design strategy that brings together the proposed multiuser detection algorithms and the greedy relay selection is then developed along with an analysis of the proposed techniques. Simulations show an excellent bit error rate performance of the proposed detection and relay selection algorithms as compared to existing techniques.

cs.IT↗

arXiv2016

Study of Distributed Conjugate Gradient Strategies for Distributed Estimation Over Sensor Networks

This paper presents distributed conjugate gradient algorithms for distributed parameter estimation and spectrum estimation over wireless sensor networks. In particular, distributed conventional conjugate gradient (CCG) and modified conjugate gradient (MCG) are considered, together with incremental and diffusion adaptive solutions. The distributed CCG and MCG algorithms have an improved performance in terms of mean square error as compared with least--mean square (LMS)--based algorithms and a performance that is close to recursive least--squares (RLS) algorithms. In comparison with existing centralized or distributed estimation strategies, key features of the proposed algorithms are: 1) more accurate estimates and faster convergence speed can be obtained; 2) the design of preconditioners for CG algorithms, which have the ability to improve the performance of the proposed CG algorithms is presented and 3) the proposed algorithms are implemented in the area of distributed parameter estimation and spectrum estimation. The performance of the proposed algorithms for distributed estimation is illustrated via simulations and the resulting algorithms are distributed, cooperative and able to respond in real time to change in the environment.

cs.DC↗

arXiv2015

Study of Opportunistic Cooperation Techniques using Jamming and Relays for Physical-Layer Security in Buffer-aided Relay Networks

In this paper, we investigate opportunistic relay and jammer cooperation schemes in multiple-input multiple-output (MIMO) buffer-aided relay networks. The network consists of one source, an arbitrary number of relay nodes, legitimate users and eavesdroppers, with the constraints of physical layer security. We propose an algorithm to select a set of relay nodes to enhance the legitimate users' transmission and another set of relay nodes to perform jamming of the eavesdroppers. With Inter-Relay interference (IRI) taken into account, interference cancellation can be implemented to assist the transmission of the legitimate users. Secondly, IRI can also be used to further increase the level of harm of the jamming signal to the eavesdroppers. By exploiting the fact that the jamming signal can be stored at the relay nodes, we also propose a hybrid algorithm to set a signal-to-interference and noise ratio (SINR) threshold at the node to determine the type of signal stored at the relay node. With this separation, the signals with high SINR are delivered to the users as conventional relay systems and the low SINR performance signals are stored as potential jamming signals. Simulation results show that the proposed techniques obtain a significant improvement in secrecy rate over previously reported algorithms.

cs.IT↗

arXiv2015

Flexible Widely-Linear Multi-Branch Decision Feedback Detection Algorithms for Massive MIMO Systems

This paper presents widely-linear multi-branch decision feedback detection techniques for large-scale multiuser multiple-antenna systems. We consider a scenario with impairments in the radio-frequency chain in which the in-phase (I) and quadrature (Q) components exhibit an imbalance, which degrades the receiver performance and originates non-circular signals. A widely-linear multi-branch decision feedback receiver is developed to mitigate both the multiuser interference and the I/Q imbalance effects. An iterative detection and decoding scheme with the proposed receiver and convolutional codes is also devised. Simulation results show that the proposed techniques outperform existing algorithms.

cs.IT↗

arXiv2015

Study of Structured Root-LDPC Codes and PEG Techniques for Block-Fading Channels

In this work, we propose structured Root-Low-Density Parity-Check (LDPC) codes and design techniques for block-fading channels. In particular, Quasi-Cyclic Root-LDPC codes, Irregular repeat-accumulate Root-LDPC codes and Controlled Doping Root-LDPC codes based on Progressive Edge Growth (PEG) techniques for block-fading channels are proposed. The proposed Root-LDPC codes are both suitable for channels under $F = 2, 3$ and $4$ independent fading per codeword. The performance of the proposed codes is investigated in terms of Frame Error Rate (FER). The proposed Root-LDPC codes are capable of achieving the channel diversity and outperform standard LDPC codes. For block-fading channel with $F = 2$ our proposed PEG-based Root-LDPC codes outperform PEG-based LDPC codes by $7.5$dB at a FER close to $10^{-3}$.

cs.IT↗

arXiv2015

Study of Efficient Robust Adaptive Beamforming Algorithms Based on Shrinkage Techniques

This paper proposes low-complexity robust adaptive beamforming (RAB) techniques based on shrinkage methods. We firstly briefly review a Low-Complexity Shrinkage-Based Mismatch Estimation (LOCSME) batch algorithm to estimate the desired signal steering vector mismatch, in which the interference-plus-noise covariance (INC) matrix is also estimated with a recursive matrix shrinkage method. Then we develop low complexity adaptive robust version of the conjugate gradient (CG) algorithm to both estimate the steering vector mismatch and update the beamforming weights. A computational complexity study of the proposed and existing algorithms is carried out. Simulations are conducted in local scattering scenarios and comparisons to existing RAB techniques are provided.

cs.IT↗

arXiv2015

Adaptive Reduced-Rank Minimum Symbol-Error-Rate Receive Processing for Large-Scale Multiple-Antenna Systems

In this work, we propose a novel adaptive reduced-rank receive processing strategy based on joint preprocessing, decimation and filtering (JPDF) for large-scale multiple-antenna systems. In this scheme, a reduced-rank framework is employed for linear receive processing and multiuser interference suppression based on the minimization of the symbol-error-rate (SER) cost function. We present a structure with multiple processing branches that performs a dimensionality reduction, where each branch contains a group of jointly optimized preprocessing and decimation units, followed by a linear receive filter. We then develop stochastic gradient (SG) algorithms to compute the parameters of the preprocessing and receive filters, along with a low-complexity decimation technique for both binary phase shift keying (BPSK) and $M$-ary quadrature amplitude modulation (QAM) symbols. In addition, an automatic parameter selection scheme is proposed to further improve the convergence performance of the proposed reduced-rank algorithms. Simulation results are presented for time-varying wireless environments and show that the proposed JPDF minimum-SER receive processing strategy and algorithms achieve a superior performance than existing methods with a reduced computational complexity.

cs.IT↗

arXiv2015

Dynamic Topology Adaptation Based on Adaptive Link Selection Algorithms for Distributed Estimation

This paper presents adaptive link selection algorithms for distributed estimation and considers their application to wireless sensor networks and smart grids. In particular, exhaustive search--based least--mean--squares(LMS)/recursive least squares(RLS) link selection algorithms and sparsity--inspired LMS/RLS link selection algorithms that can exploit the topology of networks with poor--quality links are considered. The proposed link selection algorithms are then analyzed in terms of their stability, steady--state and tracking performance, and computational complexity. In comparison with existing centralized or distributed estimation strategies, key features of the proposed algorithms are: 1) more accurate estimates and faster convergence speed can be obtained; and 2) the network is equipped with the ability of link selection that can circumvent link failures and improve the estimation performance. The performance of the proposed algorithms for distributed estimation is illustrated via simulations in applications of wireless sensor networks and smart grids.

eess.SY↗

arXiv2015

Interference Suppression in Multiuser Systems Based on Bidirectional Algorithms

This paper presents adaptive bidirectional minimum mean-square error parameter estimation algorithms for fast-fading channels. The time correlation between successive channel gains is exploited to improve the estimation and tracking capabilities of adaptive algorithms and provide robustness against time-varying channels. Bidirectional normalized least mean-square and conjugate gradient algorithms are devised along with adaptive mixing parameters that adjust to the time-varying channel correlation properties. An analysis of the proposed algorithms is provided along with a discussion of their performance advantages. Simulations for an application to interference suppression in multiuser DS-CDMA systems show the advantages of the proposed algorithms.

cs.IT↗

arXiv2015

Study of Buffer-Aided Space-Time Coding for Multiple-Antenna Cooperative Wireless Networks

In this work we propose an adaptive buffer-aided space-time coding scheme for cooperative wireless networks. A maximum likelihood receiver and adjustable code vectors are considered subject to a power constraint with an amplify-and-forward cooperation strategy. Each multiple-antenna relay is equipped with a buffer and is capable of storing the received symbols before forwarding them to the destination. We also present an adaptive relay selection and optimization algorithm, in which the instantaneous signal to noise ratio in each link is calculated and compared at the destination. An adjustable code vector obtained by a feedback channel at each relay is employed to form a space-time coded vector which achieves a higher coding gain than standard schemes. A stochastic gradient algorithm is developed to compute the parameters of the adjustable code vector with reduced computational complexity. Simulation results show that the proposed buffer-aided scheme and algorithm obtain performance gains over existing schemes.

cs.IT↗

arXiv2015

Low-Complexity Robust Adaptive Beamforming Algorithms Based on Shrinkage for Mismatch Estimation

In this paper, we propose low-complexity robust adaptive beamforming (RAB) techniques that based on shrinkage methods. The only prior knowledge required by the proposed algorithms are the angular sector in which the actual steering vector is located and the antenna array geometry. We firstly present a Low-Complexity Shrinkage-Based Mismatch Estimation (LOCSME) algorithm to estimate the desired signal steering vector mismatch, in which the interference-plus-noise covariance (INC) matrix is estimated with Oracle Approximating Shrinkage (OAS) method and the weights are computed with matrix inversions. We then develop low-cost stochastic gradient (SG) recursions to estimate the INC matrix and update the beamforming weights, resulting in the proposed LOCSME-SG algorithm. Simulation results show that both LOCSME and LOCSME-SG achieve very good output signal-to-interference-plus-noise ratio (SINR) compared to previously reported adaptive RAB algorithms.

cs.IT↗

arXiv2015

Distributed Compressed Estimation for Wireless Sensor Networks Based on Compressive Sensing

This letter proposes a novel distributed compressed estimation scheme for sparse signals and systems based on compressive sensing techniques. The proposed scheme consists of compression and decompression modules inspired by compressive sensing to perform distributed compressed estimation. A design procedure is also presented and an algorithm is developed to optimize measurement matrices, which can further improve the performance of the proposed distributed compressed estimation scheme. Simulations for a wireless sensor network illustrate the advantages of the proposed scheme and algorithm in terms of convergence rate and mean square error performance.

cs.IT↗

arXiv2014

Coordinate Tomlinson-Harashima Precoding Design for Overloaded Multi-user MIMO Systems

Tomlinson-Harashima precoding (THP) is a nonlinear processing technique employed at the transmit side to implement the concept of dirty paper coding (DPC). The perform of THP, however, is restricted by the dimensionality constraint that the number of transmit antennas has to be greater or equal to the total number of receive antennas. In this paper, we propose an iterative coordinate THP algorithm for the scenarios in which the total number of receive antennas is larger than the number of transmit antennas. The proposed algorithm is implemented on two types of THP structures, the decentralized THP (dTHP) with diagonal weighted filters at the receivers of the users, and the centralized THP (cTHP) with diagonal weighted filter at the transmitter. Simulation results show that a much better bit error rate (BER) and sum-rate performances can be achieved by the proposed iterative coordinate THP compared to the previous linear art.

cs.IT↗

arXiv2014

Multi-User Flexible Coordinated Beamforming using Lattice Reduction for Massive MIMO Systems

The application of precoding algorithms in multi-user massive multiple-input multiple-output (MU-Massive-MIMO) systems is restricted by the dimensionality constraint that the number of transmit antennas has to be greater than or equal to the total number of receive antennas. In this paper, a lattice reduction (LR)-aided flexible coordinated beamforming (LR-FlexCoBF) algorithm is proposed to overcome the dimensionality constraint in overloaded MU-Massive-MIMO systems. A random user selection scheme is integrated with the proposed LR-FlexCoBF to extend its application to MU-Massive-MIMO systems with arbitary overloading levels. Simulation results show that significant improvements in terms of bit error rate (BER) and sum-rate performances can be achieved by the proposed LR-FlexCoBF precoding algorithm.

cs.IT↗