arXiv subjects

R. C. de Lamare

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

At least 109 records · Page 6Linked to original sources

arXiv2018

Tomlinson-Harashima Precoded Rate-Splitting for Multiuser MIMO Systems

In this work, we investigate the performance of Rate-Splitting (RS) based on Tomlinson-Harashima Precoding (THP) in a multiple-antenna broadcast channel with perfect and imperfect Channel State Information at the Transmitter (CSIT). In particular, we consider RS using centralized and decentralized THP structures, where only one user splits its message into a common and private part, and develop expressions to describe the signal-to-interference-plus-noise (SINR) ratio and the sum rates associated with these schemes. Furthermore, we also assess the performance achieved by RS combined with Dirty-Paper Coding (DPC). Simulations show that RS with THP outperforms existing standard THP and RS with linear precoding schemes.

cs.IT↗

arXiv2018

Study of Switched Max-Link Buffer-Aided Relay Selection for Cooperative MIMO Systems

In this paper, we investigate relay selection for cooperative multiple-antenna systems that are equipped with buffers, which increase the reliability of wireless links. In particular, we present a novel relay selection technique based on switching and the Max-Link protocol that is named Switched Max-Link. We also introduce a novel relay selection criterion based on the maximum likelihood (ML) principle denoted maximum minimum distance that is incorporated into. Simulations are then employed to evaluate the performance of the proposed and existing techniques.

cs.IT↗

arXiv2018

Study of BEM-Type Channel Estimation Techniques for 5G Multicarrier Systems

In this paper, we investigate channel estimation techniques for 5G multicarrier systems. Due to the characteristics of the 5G application scenarios, channel estimation techniques have been tested in Orthogonal Frequency Division Multiplexing (OFDM) and Generalized Frequency Division Multiplexing (GFDM) systems. The orthogonality between subcarriers in OFDM systems permits inserting and extracting pilots without interference. However, due to pulse shaping, subcarriers in GFDM are no longer orthogonal and interfere with each other. Due to such interference, the channel estimation for GFDM is not trivial. A robust and low-complexity channel estimator can be obtained by combining a minimum mean-square error (MMSE) regularization and the basis expansion model (BEM) approach. In this work, we develop a BEM-type channel estimator along with a strategy to obtain the covariance matrix of the BEM coefficients. Simulations show that the BEM-type channel estimation shows performance close to that of the linear MMSE (LMMSE), even though there is no need to know the channel power delay profile, and its complexity is low.

cs.IT↗

arXiv2018

Study of Unique-Word Based GFDM Transmission Systems

In this paper, we propose the use of a deterministic sequence, known as unique word (UW), instead of the cyclic prefix (CP) in generalized frequency division multiplexing (GFDM) systems. The UW consists of known sequences that, if not null, can be used advantageously for synchronization and channel estimation purposes. In addition, UW allows the application of a highly efficient linear minimum mean squared error (LMMSE) smoother for noise reduction at the receiver. To avoid the conditions of non-orthogonality caused by the insertion of the UW and performance degradation in time varying frequency-selective channels, we use frequency-shift offset quadrature amplitude modulation (FS-OQAM). We present a signal model of a UW-GFDM system considering a single and multiple UWs. We then develop an LMMSE receive filter for signal reception of the proposed UW-GFDM system. Simulations show that the proposed UW-GFDM system outperforms prior work.

cs.IT↗

arXiv2018

Multi-Step Knowledge-Aided Iterative ESPRIT for Direction Finding

In this work, we propose a subspace-based algorithm for DOA estimation which iteratively reduces the disturbance factors of the estimated data covariance matrix and incorporates prior knowledge which is gradually obtained on line. An analysis of the MSE of the reshaped data covariance matrix is carried out along with comparisons between computational complexities of the proposed and existing algorithms. Simulations focusing on closely-spaced sources, where they are uncorrelated and correlated, illustrate the improvements achieved.

eess.SP↗

arXiv2018

Study of Knowledge-Aided Iterative Detection and Decoding for Multiuser MIMO Systems

In this work, we consider the problem of reduced latency of low-density parity-check (LDPC) codes with iterative detection and decoding (IDD) receiver in multiuser multiple-antenna systems. The proposed knowledge-aided IDD (KA-IDD) system employs a minimum mean-square error detector with refined iterative processing and a reweighted belief propagation (BP) decoding algorithm. We present reweighted BP decoding algorithms, which exploit the knowledge of short cycles in the graph structure and reweighting factors derived from the expansion of hypergraphs. Simulation results show that the proposed KA-IDD scheme and algorithms outperform prior art and require a reduced number of decoding iterations.

cs.IT↗

arXiv2017

Effective Optimization Criteria and Relay Selection Algorithms for Physical-Layer Security in Multiple-Antenna Relay Networks

Physical-layer security for wireless networks has become an effective approach and recently drawn significant attention in the literature. In particular, the deployment and allocation of resources such as relays to assist the transmission have gained significant interest due to their ability to improve the secrecy rate of wireless networks. In this work, we examine relay selection criteria with arbitrary knowledge of the channels of the users and the eavesdroppers. We present alternative optimization criteria based on the signal-to-interference and the secrecy rate criteria that can be used for resource allocation and that do not require knowledge of the channels of the eavesdroppers and the interference. We then develop effective relay selection algorithms that can achieve a high secrecy rate performance without the need for the knowledge of the channels of the eavesdroppers and the interference. Simulation results show that the proposed criteria and algorithms achieve excellent performance.

cs.IT↗

arXiv2017

Study of Robust Distributed Beamforming Based on Cross-Correlation and Subspace Projection Techniques

In this work, we present a novel robust distributed beamforming (RDB) approach to mitigate the effects of channel errors on wireless networks equipped with relays based on the exploitation of the cross-correlation between the received data from the relays at the destination and the system output. The proposed RDB method, denoted cross-correlation and subspace projection (CCSP) RDB, considers a total relay transmit power constraint in the system and the objective of maximizing the output signal-to-interference-plus-noise ratio (SINR). The relay nodes are equipped with an amplify-and-forward (AF) protocol and we assume that the channel state information (CSI) is imperfectly known at the relays and there is no direct link between the sources and the destination. The CCSP does not require any costly optimization procedure and simulations show an excellent performance as compared to previously reported algorithms.

eess.SP↗

arXiv2017

Study of Set-Membership Kernel Adaptive Algorithms and Applications

Adaptive algorithms based on kernel structures have been a topic of significant research over the past few years. The main advantage is that they form a family of universal approximators, offering an elegant solution to problems with nonlinearities. Nevertheless these methods deal with kernel expansions, creating a growing structure also known as dictionary, whose size depends on the number of new inputs. In this paper we derive the set-membership kernel-based normalized least-mean square (SM-NKLMS) algorithm, which is capable of limiting the size of the dictionary created in stationary environments. We also derive as an extension the set-membership kernelized affine projection (SM-KAP) algorithm. Finally several experiments are presented to compare the proposed SM-NKLMS and SM-KAP algorithms to the existing methods.

cs.LG↗

arXiv2017

Study of Joint MMSE Consensus and Relay Selection Algorithms for Distributed Beamforming

This work presents joint minimum mean-square error (MMSE) consensus algorithm and relay selection algorithms for distributed beamforming. We propose joint MMSE consensus relay and selection schemes with a total power constraint and local communications among the relays for a network with cooperating sensors. We also devise greedy relay selection algorithms based on the MMSE consensus approach that optimize the network performance. Simulation results show that the proposed scheme and algorithms outperform existing techniques for distributed beamforming.

cs.IT↗

arXiv2017

Study of Anomaly Detection Based on Randomized Subspace Methods in IP Networks

In this paper we propose novel randomized subspace methods to detect anomalies in Internet Protocol networks. Given a data matrix containing information about network traffic, the proposed approaches perform a normal-plus-anomalous matrix decomposition aided by random subspace techniques and subsequently detect traffic anomalies in the anomalous subspace using a statistical test. Experimental results demonstrate improvement over the traditional principal component analysis-based subspace methods in terms of robustness to noise and detection rate.

cs.IT↗

arXiv2017

Report on Two-Step Knowledge-Aided Iterative ESPRIT Algorithm

In this work, we propose a subspace-based algorithm for direction-of-arrival (DOA) estimation, referred to as two-step knowledge-aided iterative estimation of signal parameters via rotational invariance techniques (ESPRIT) method (Two-Step KAI-ESPRIT), which achieves more accurate estimates than those of prior art. The proposed Two-Step KAI-ESPRIT improves the estimation of the covariance matrix of the input data by incorporating prior knowledge of signals and by exploiting knowledge of the structure of the covariance matrix and its perturbation terms. Simulation results illustrate the improvement achieved by the proposed method.

math.NA↗

arXiv2016

Distributed Estimation for Adaptive Networks Based on Serial-Inspired Diffusion

Distributed estimation and processing in networks modeled by graphs have received a great deal of interest recently, due to the benefits of decentralised processing in terms of performance and robustness to communications link failure between nodes of the network. Diffusion-based algorithms have been demonstrated to be among the most effective for distributed signal processing problems, through the combination of local node estimate updates and sharing of information with neighbour nodes through diffusion. In this work, we develop a serial-inspired approach based on message-passing strategies that provides a significant improvement in performance over prior art. The concept of serial processing in the graph has been successfully applied in sum-product based algorithms and here provides inspiration for an algorithm which makes use of the most up-to-date information in the graph in combination with the diffusion approach to offer improved performance.

cs.MA↗

arXiv2016

Decoupled Signal Detection for the Uplink of Large-Scale MIMO Systems in Heterogeneous Networks

Massive multiple-input multiple-output (MIMO) systems are strong candidates for future fifth generation (5G) heterogeneous cellular networks. For 5G, a network densification with a high number of different classes of users and data service requirements is expected. Such a large number of connected devices needs to be separated in order to allow the detection of the transmitted signals according to different data requirements. In this paper, a decoupled signal detection (DSD) technique which allows the separation of the uplink signals, for each user class, at the base station (BS) is proposed for massive MIMO systems. A mathematical signal model for massive MIMO systems with centralized and distributed antennas in heterogeneous networks is also developed. The performance of the proposed DSD algorithm is evaluated and compared with existing detection schemes in a realistic scenario with distributed antennas. A sum-rate analysis and a computational cost study for DSD are also presented. Simulation results show an excellent performance of the proposed DSD algorithm when combined with linear and successive interference cancellation detection techniques.

cs.IT↗

arXiv2016

Study of Tomlinson-Harashima Precoding Strategies for Physical-Layer Security in Wireless Networks

In this paper, we propose novel non-linear precoders for the downlink of a multi-user MIMO system with the existence of multiple eavesdroppers. The proposed non-linear precoders are designed to improve the physical-layer secrecy rate. Specifically, we combine the non-linear successive optimization Tomlinson-Harashima precoding (SO-THP) with generalized matrix inversion (GMI) technique to maximize the physical-layer secrecy rate. For the purpose of comparison, we examine different traditional precoders with the proposed algorithm in terms of secrecy rate as well as BER performance. We also investigate simplified generalized matrix inversion (S-GMI) and lattice-reduction (LR) techniques in order to efficiently compute the parameters of the precoders. We further conduct computational complexity and secrecy rate analysis of the proposed and existing algorithms. In addition, in the scenario without knowledge of channel state information (CSI) to the eavesdroppers, a strategy of injecting artificial noise (AN) prior to the transmission is employed to enhance the physical-layer secrecy rate. Simulation results show that the proposed non-linear precoders outperform existing precoders in terms of BER and secrecy rate performance.

cs.IT↗

arXiv2016

Review of Buffer-Aided Distributed Space-Time Coding Schemes and Algorithms for Cooperative Wireless Systems

In this work, we propose buffer-aided distributed space-time coding (DSTC) schemes and relay selection algorithms for cooperative direct-sequence code-division multiple access (DS-CDMA) systems. We first devise a relay pair selection algorithm that can form relay pairs and then select the optimum set of relays among both the source-relay phase and the relay-destination phase according to the signal-to-interference-plus-noise ratio (SINR) criterion. Multiple relays equipped with dynamic buffers are then introduced in the network, which allows the relays to store data received from the sources and wait until the most appropriate time for transmission. { A greedy relay pair selection algorithm is then developed to reduce the high cost of the exhaustive search required when a large number of relays are involved.} The proposed techniques effectively improve the quality of the transmission with an acceptable delay as the buffer size is adjustable. An analysis of the computational complexity of the proposed algorithms, the delay and a study of the greedy algorithm are then carried out. Simulation results show that the proposed dynamic buffer-aided DSTC schemes and algorithms outperform prior art.

cs.IT↗

arXiv2016

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

This work proposes adaptive buffer-aided distributed space-time coding schemes and algorithms with feedback for wireless networks equipped with buffer-aided relays. The proposed schemes employ a maximum likelihood receiver at the destination and adjustable codes subject to a power constraint with an amplify-and-forward cooperative strategy at the relays. Each relay is equipped with a buffer and is capable of storing blocks of received symbols and forwarding the data to the destination if selected. Different antenna configurations and wireless channels, such as static block fading channels, are considered. The effects of using buffer-aided relays to improve the bit error rate (BER) performance are also studied. Adjustable relay selection and optimization algorithms that exploit the extra degrees of freedom of relays equipped with buffers are developed to improve the BER performance. We also analyze the pairwise error probability and diversity of the system when using the proposed schemes and algorithms in a cooperative network. Simulation results show that the proposed schemes and algorithms obtain performance gains over previously reported techniques.

cs.IT↗

arXiv2016

Design of LDPC Codes using Multipath EMD Strategies and Progressive Edge Growth

Low-density parity-check (LDPC) codes are capable of achieving excellent performance and provide a useful alternative for high performance applications. However, at medium to high signal-to-noise ratios (SNR), an observable error floor arises from the loss of independence of messages passed under iterative graph-based decoding. In this paper, the error floor performance of short block length codes is improved by use of a novel candidate selection metric in code graph construction. The proposed Multipath EMD approach avoids harmful structures in the graph by evaluating certain properties of the cycles which may be introduced in each edge placement. We present Multipath EMD based designs for several structured LDPC codes including quasi-cyclic and irregular repeat accumulate codes. In addition, an extended class of diversity-achieving codes on the challenging block fading channel is proposed and considered with the Multipath EMD design. This combined approach is demonstrated to provide gains in decoder convergence and error rate performance. A simulation study evaluates the performance of the proposed and existing state-of-the-art methods.

cs.IT↗