arXiv subjects

Taufik Abrao

Publications and source records attributed to Taufik Abrao.

At least 19 recordsLinked to original sources

arXiv2026

Hybrid-Field Channel Estimation for XL-MIMO Systems: Dictionary-based Sparse Signal Recovery

Extremely large-scale multiple-input multiple-output (XL-MIMO) systems are a key technology for future wireless networks, but the large array aperture naturally creates a hybrid-field (HF) propagation regime in which far-field (FF) planar-wave and near-field (NF) spherical-wave components coexist. This work considers the problem of HF channel estimation (CE) and introduces a unified model that superimposes FF and NF contributions according to the Rayleigh distance boundary. By exploiting the inherent sparsity of the channel in the angular and polar domains, we formulate the estimation task as a sparse recovery problem. Unlike conventional approaches that require prior knowledge of the channel sparsity level, the proposed method operates without requiring knowledge of the sparsity level L and the NF/FF ratio γ, which are used only for synthetic channel generation in simulations. The channel estimator determines the number of paths adaptively through a residual-based stopping rule. A combined FF/NF dictionary is employed to initialize the support, and each selected atom undergoes continuous parameter refinement to mitigate grid mismatch. Simulation results demonstrate that the proposed estimator achieves accurate HF channel reconstruction under both line-of-sight (LoS) and non-line-of-sight (NLoS) conditions, offering a practical and computationally efficient solution for XL-MIMO systems. Extremely Large-Scale MIMO (XL-MIMO); Channel State Information (CSI); Channel estimation (CE); hybrid-field (HF) wave propagation; near-field (NF) spherical wave model; far-field (FF) planar wave model

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arXiv2025

Dual-Function Beam Pattern Design for Multi-Target ISAC Systems: A Decoupled Approach

We investigate the beampattern design problem for mono-static multi-user (MU) multi-point-target integrated sensing and communication (ISAC) systems, where a dual-function multiple-input multiple-output (DF-MIMO) base station (BS) performs downlink communication and radar sensing simultaneously. In ISAC systems, sensing and communication inherently compete for resources. As communication demand increases, the beam pattern is reshaped, which might degrade the direction of arrival (DoA) sensing accuracy, measured in terms of mean-squared error (MSE) and lower-bounded by the Cramer-Rao lower bound (CRLB). Since conventional joint formulations of the sensing-based problem often overlook this trade-off, our work addresses it by decomposing the sensing-based problem into two subproblems (SPs). This decomposition enables a more effective exploitation of the beam pattern's physical properties, which we refer to as the Sensing-Guided Communication Dual-Function (SGCDF) beam pattern design. We further develop a low-complexity extension using the Riemannian Manifold Optimization (RMO) and convex closed-set projection. Simulation results confirm that the proposed method improves multi-target estimation accuracy, compared to traditional joint optimization strategies, by preserving the beam pattern, while the low-complexity version offers an excellent performance-complexity tradeoff, maintaining high accuracy with significantly reduced computational cost.

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arXiv2025

The ISAC systems aided by MIMO, RIS and with Beamforming Techniques

This paper explores the integration of communication and sensing in modern wireless systems through the configuration of BS and RIS antenna elements. By leveraging time multiplexing for both communication and sensing, the proposed system optimizes spectral efficiency and operational performance. The use of static RIS configurations tailored to specific environments eliminates the need for dynamic reconfigurations, enhancing system agility, reducing processing complexity, and improving sensing accuracy. The system incorporates trilateration, angle of arrival, and time of arrival techniques to enable precise user localization by combining signals reflected along multiple paths. This method helps choose the best connections and lowers sensing costs while preventing interference with communication data, highlighting the need to bring together new technologies like passive and adaptive beamforming in one system.

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arXiv2023

Energy Efficiency Maximization for Intelligent Surfaces Aided Massive MIMO with Zero

In this work, we address the energy efficiency (EE) maximization problem in a downlink communication system utilizing reconfigurable intelligent surface (RIS) in a multi-user massive multiple-input multiple-output (mMIMO) setup with zero-forcing (ZF) precoding. The channel between the base station (BS) and RIS operates under a Rician fading with Rician factor K1. Since systematically optimizing the RIS phase shifts in each channel coherence time interval is challenging and burdensome, we employ the statistical channel state information (CSI)-based optimization strategy to alleviate this overhead. By treating the RIS phase shifts matrix as a constant over multiple channel coherence time intervals, we can reduce the computational complexity while maintaining an interesting performance. Based on an ergodic rate (ER) lower bound closed-form, the EE optimization problem is formulated. Such a problem is non-convex and challenging to tackle due to the coupled variables. To circumvent such an obstacle, we explore the sequential optimization approach where the power allocation vector p, the number of antennas M, and the RIS phase shifts v are separated and sequentially solved iteratively until convergence. With the help of the Lagrangian dual method, fractional programming (FP) techniques, and Lemma 1, insightful compact closed-form expressions for each of the three optimization variables are derived. Simulation results validate the effectiveness of the proposed method across different generalized channel scenarios, including non-line-of-sight (NLoS) and partially line-of-sight (LoS) conditions. This underscores its potential to significantly reduce power consumption, decrease the number of active antennas at the base station, and effectively incorporate RIS structure in mMIMO communication setup with just statistical CSI knowledge.

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arXiv2023

Reconfigurable Intelligent Surfaces-Enabled Intra-Cell Pilot Reuse in Massive MIMO Systems

Channel state information (CSI) estimation is a critical issue in the design of modern massive multiple-input multiple-output (mMIMO) networks. With the increasing number of users, assigning orthogonal pilots to everyone incurs a large overhead that strongly penalizes the system's spectral efficiency (SE). It becomes thus necessary to reuse pilots, giving rise to pilot contamination, a vital performance bottleneck of mMIMO networks. Reusing pilots among the users of the same cell is a desirable operation condition from the perspective of reducing training overheads; however, the intra-cell pilot contamination might worsen due to the users' proximity. Reconfigurable intelligent surfaces (RISs), capable of smartly controlling the wireless channel, can be leveraged for intra-cell pilot reuse. In this paper, our main contribution is a RIS-aided approach for intra-cell pilot reuse and the corresponding channel estimation method. Relying upon the knowledge of only statistical CSI, we optimize the RIS phase shifts based on a manifold optimization framework and the RIS positioning based on a deterministic approach. The extensive numerical results highlight the remarkable performance improvements the proposed scheme achieves (for both uplink and downlink transmissions) compared to other alternatives.

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arXiv2023

Machine Learning-based Methods for Joint {Detection-Channel Estimation} in OFDM Systems

In this work, two machine learning (ML)-based structures for joint detection-channel estimation in OFDM systems are proposed and extensively characterized. Both ML architectures, namely Deep Neural Network (DNN) and Extreme Learning Machine (ELM), are developed {to provide improved data detection performance} and compared with the conventional matched filter (MF) detector equipped with the minimum mean square error (MMSE) and least square (LS) channel estimators. The bit-error-rate (BER) performance vs. computational complexity trade-off is analyzed, demonstrating the superiority of the proposed DNN-OFDM and ELM-OFDM detectors methodologies.

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arXiv2023

Improving Spectral Efficiency via Pilot Assignment and Subarray Selection Under Realistic XL-MIMO Channels

The main requirements for 5G and beyond connectivity include a uniform high quality of service, which can be attained in crowded scenarios by extra-large MIMO (XL-MIMO) systems. Another requirement is to support increasing connected users in (over)crowded machine-type communication (mMTC). In such scenarios, pilot assignment (PA) becomes paramount to reduce pilot contamination and consequently improve spectral efficiency (SE). We propose a novel quasi-optimal low-complexity iterative pilot assignment strategy for XL-MIMO systems based on a genetic algorithm (GA). The proposed GA-based PA procedure turns the quality of service more uniform, taking into account the normalized mean-square error (NMSE) of channel estimation from each candidate of the population. The simulations reveal that the proposed iterative procedure minimizes the channel estimation NMSE averaged over the UEs. The second procedure is the subarray (SA) selection. In XL-MIMO systems, commonly, a UE is close to a SA antenna subset such that a sufficient data rate can be achieved if only a specific SA serves that UE. Thus, a SA selection procedure is investigated to make the system scalable by defining the maximum number of UEs each SA can help. Hence, the SA clusters are formatted based on the PA decision. Furthermore, we introduce an appropriate channel model for XL-MIMO, which considers a deterministic LoS component with a distance-dependent probability of existence combined with a stochastic spatially correlated Rayleigh NLoS fading component. The developed simulations and analyses rely on this suitable channel model under realistic assumptions of pilot contamination and correlated channels.

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arXiv2023

Improving Random Access with NOMA in mMTC XL-MIMO

The extra-large multiple-input multiple-output (XL-MIMO) architecture has been recognized as a technology for supporting the massive MTC (mMTC), providing very high-data rates in high-user density scenarios. However, the large dimension of the array increases the Rayleigh distance (dRayl), in addition to obstacles and scatters causing spatial non-stationarities and distinct visibility regions (VRs) across the XL array extension. We investigate the random access (RA) problem in crowded XL-MIMO scenarios; the proposed grant-based random access (GB-RA) protocol combining the advantage of non-orthogonal multiple access (NOMA) and strongest user collision resolutions in extra-large arrays (SUCRe-XL) named NOMA-XL can allow access of two or three colliding users in the same XL sub-array (SA) selecting the same pilot sequence. The received signal processing in a SA basis changes the dRayl, enabling the far-field planar wavefront propagation condition, while improving the system performance. The proposed NOMA-XL GB-RA protocol can reduce the number of attempts to access the mMTC network while improving the average sum rate, as the number of SA increases.

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arXiv2023

NOMA-aided double RIS under Nakagami-m fading: Channel and System Modelling

We investigate the downlink outage performance of double-RIS-aided non-orthogonal multiple access (NOMA), where a near-BS and a near-users RISs setup are deployed. To extend the coverage to 360 degrees, we deploy a simultaneously transmitting and reflecting RIS (STAR-RIS) structure to improve communication reliability for indoor and outdoor users. New channel statistics for the end-to-end channel with Nakagami-m considering both the conventional-RIS and the STAR-RIS antenna elements features are derived using the moment-matching (MM) technique. The numerical results reveal that the double-RIS setup can outperform the single-RIS designs when the number of elements of STAR- RIS (RS) and conventional RIS (RC) is suitably adjusted. Moreover, the double-RIS setup outperforms the single-RIS design when the link between the base station and the near-user RIS is in good condition. Finally, the proposed analytical equations are accurate under different channel and system configurations.

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arXiv2023

OnRMap: An Online Radio Mapping Approach for Large Intelligent Surfaces

We introduce OnRMap, an online radio mapping (RMap) approach for the sensing and localization of active users (AUs), devices that are transmitting radio signals, and passive elements (PEs), elements that are in the environment and are illuminated by the AUs' radio signals. OnRMap processes the signals received by a large intelligent surface and produces a radio map (RM) of the environment based on signal processing techniques. The method then senses and locate the different elements without the need for offline scanning phases, which is important for environments with frequently changing spatial layouts. Empirical results demonstrate that OnRMap presents a higher localization accuracy than an offline method, but the price paid for being an online method is a moderate reduction in the detection rate.

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arXiv2022

RIS-aided Cooperative FD-SWIPT-NOMA Outage Performance in Nakagami-m Channels

In this work, we investigate reconfigurable intelligent surfaces (RIS)-assisted cooperative non-orthogonal multiple access (C-NOMA) consisting of two paired users, where the phases of RIS are configured to boost the cell-center device. The cell-center device is designated to act as a full-duplex (FD) relay to assist the cell-edge device. The cell-center device does not use its battery energy to cooperate but harvests energy using simultaneous wireless information power transfer (SWIPT). A more practical non-linear energy harvesting model is considered. Expressions for outage probability (OP) and ergodic rate (ER) are devised, assuming that all users' links undergo Nakagami-$m$ channel fading. We first approximate the harvested power as Gamma random variables via the moments matching technique. This allows us to derive analytical OP/ER expressions that are simple to compute yet accurate for a wide range of RIS passive elements configurations, energy harvesting (EH) coefficients, and residual self-interference (SI) levels, being extensively validated by numerical simulations. The OP expressions reveal how paramount is to mitigate the SI in the FD relay mode since for reasonable values of residual SI coefficient ($ω\geq -20$dB), it is notable its detrimental effect on the system performance. Also, numerical results reveal that increasing the number of RIS elements can benefit the cooperative system more than the non-cooperative one.

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arXiv2022

QoS-Aware User Scheduling in Crowded XL-MIMO Systems Under Non-Stationary Multi-State LoS/NLoS Channels

Providing minimum quality-of-service (QoS) in crowded wireless communications systems, with high user density, is challenging due to the network structure with limited transmit power budget and resource blocks. Smart resource allocation methods, such as user scheduling, power allocation, and modulation and coding scheme selection, must be implemented to cope with the challenge. Aiming to enhance the number of served users with minimum QoS in the downlink (DL) channel of crowded extra-large scale massive multiple-input multiple-output (XL-MIMO) systems, in this paper we propose a QoS-aware joint user scheduling and power allocation technique. The proposed technique is constituted by two sequential procedures: the clique search-based scheduling (CBS) algorithm for user scheduling followed by optimal power allocation with transmit power budget and minimum achievable rate per user constraints. To accurately evaluate the proposed technique in the XL-MIMO scenario, we propose a generalized non-stationary multi-state channel model based on spherical-wave propagation assuming that users under LoS and NLoS transmission coexist in the same communication cell. Such model considers that users under different channel states experience different propagation aspects both in the multipath fading model and the path loss rule. Numerical results on the achievable sum-rate, number of scheduled users, and distribution of the scheduled users reveal that the proposed CBS algorithm provides a fair coverage over the whole cell area, achieving remarkable numbers of scheduled users when users under the LoS and NLoS channel states coexist in the communication cell.

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arXiv2021

Throughput and Latency in the Distributed Q-Learning Random Access mMTC Networks

In mMTC mode, with thousands of devices trying to access network resources sporadically, the problem of random access (RA) and collisions between devices that select the same resources becomes crucial. A promising approach to solve such an RA problem is to use learning mechanisms, especially the Q-learning algorithm, where the devices learn about the best time-slot periods to transmit through rewards sent by the central node. In this work, we propose a distributed packet-based learning method by varying the reward from the central node that favors devices having a larger number of remaining packets to transmit. Our numerical results indicated that the proposed distributed packet-based Q-learning method attains a much better throughput-latency trade-off than the alternative independent and collaborative techniques in practical scenarios of interest. In contrast, the number of payload bits of the packet-based technique is reduced regarding the collaborative Q-learning RA technique for achieving the same normalized throughput.

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arXiv2021

Quasi-Distributed Antenna Selection for Spectral Efficiency Maximization in Subarray Switching XL-MIMO Systems

In this paper, we consider the downlink (DL) of a zero-forcing (ZF) precoded extra-large scale massive MIMO (XL-MIMO) system. The base-station (BS) operates with limited number of radio-frequency (RF) transceivers due to high cost, power consumption and interconnection bandwidth associated to the fully digital implementation. The BS, which is implemented with a subarray switching architecture, selects groups of active antennas inside each subarray to transmit the DL signal. This work proposes efficient resource allocation (RA) procedures to perform joint antenna selection (AS) and power allocation (PA) to maximize the DL spectral efficiency (SE) of an XL-MIMO system operating under different loading settings. Two metaheuristic RA procedures based on the genetic algorithm (GA) are assessed and compared in terms of performance, coordination data size and computational complexity. One algorithm is based on a quasi-distributed methodology while the other is based on the conventional centralized processing. Numerical results demonstrate that the quasi-distributed GA-based procedure results in a suitable trade-off between performance, complexity and exchanged coordination data. At the same time, it outperforms the centralized procedures with appropriate system operation settings.

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arXiv2020

NOMA Systems Optimization to Ensure Maximum Fairness to Users

In this contribution, the optimization of power proportion allocated for each user in the downlink (DL) non-orthogonal multiple access (NOMA) systems have been developed. Successive interference cancellation (SIC) technique recovers users' signal with high difference between channel gains, in order to find the lowest optimum power proportion {required to guarantee} an equal data rate for all active users. Following the same approach, the optimum power proportion for each user and also the minimum total power to achieve the same rate for all users (maximum fairness) were obtained as a design goal. Moreover, the same design methodology was developed seeking to maximize the NOMA system energy efficiency (EE). It was possible to find the {maximum EE point} and the respective power distribution among the users for a certain circuitry power consumption. For all NOMA users in which the optimal operation point for EE maximization was parameterized, it was possible to find the total power, power ratio and the equal rate values. As a result, one can find the tradeoff point between EE and sum rate for each system scenario, as well as the best resource efficiency operation point. By considering the same rate for all users, the system attains maximum fairness among the users.

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arXiv2020

Closed-Form Bit Error Probabilities for FBMC Systems

This paper analyses the data reconstruction effects emerged from the deployment of non-perfect prototype filters in Filter Bank MultiCarrier (FBMC) systems operating over Additive White Gaussian Noise (AWGN) and frequency-flat Rayleigh channels considering frequency-flatness for each subcarrier. This goal is attained by studying the Bit Error Rate (BER) effects of the prototype filters, increasing the scenario complexity progressively. Despite the complexity, both exact and approximate Bit Error Probability (BEP) expressions portray the BER degradation analytically for any FBMC prototype filter. Numerical results demonstrate that the proposed BEP expressions match perfectly with the simulated BER performance for FBMC systems, regardless of the prototype filter choice.

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arXiv2019

Randomized Kaczmarz Algorithm for Massive MIMO Systems with Channel Estimation and Spatial Correlation

To exploit the benefits of massive multiple-input multiple-output (M-MIMO) technology in scenarios where base stations (BSs) need to be cheap and equipped with simple hardware, the computational complexity of classical signal processing schemes for spatial multiplexing of users shall be reduced. This calls for suboptimal designs that perform well the combining/precoding steps and simultaneously achieve low computational complexities. An approach based on the iterative Kaczmarz algorithm (KA) has been recently investigated, assuring well execution without the knowledge of second order moments of the wireless channels in the BS, and with easiness, since no tuning parameters, besides the number of iterations, are required. In fact, the randomized version of KA (rKA) has been used in this context due to global convergence properties. Herein, modifications are proposed on this first rKA-based attempt, aiming to improve its performance-complexity trade-off solution for M-MIMO systems. We observe that long-term channel effects degrade the rate of convergence of the rKA-based schemes. This issue is then tackled herein by means of a hybrid rKA initialization proposal that lands within the region of convexity of the algorithm and assures fairness to the communication system. The effectiveness of our proposal is illustrated through numerical results which bring more realistic system conditions in terms of channel estimation and spatial correlation than those used so far. We also characterize the computational complexity of the proposed rKA scheme, deriving upper bounds for the number of iterations. A case study focused on a dense urban application scenario is used to gather new insights on the feasibility of the proposed scheme to cope with the inserted BS constraints.

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arXiv2019

Pre-distortion and Pre-equalization for Non-Linearities and Low-Pass Effect Mitigation in OFDM-VLC Systems

The orthogonal frequency division multiplexing (OFDM) transmission has shown promise in applications of visible light communication (VLC). However, the variation of the nonlinearity of the optical power emitted by the high power light emitting diode (HPLED) as a function of current and temperature implies in drastic OFDM-VLC performance degradation. The first part of this work, experimentally confirms and models this degradation due to temperature in a high power white HPLED. The higher attenuation at high frequencies, which is inherent to the HPLED and which is accentuated by the effect of the intrinsic capacitance of the photodiode, is another factor of degradation due to the reduction of the signal-to-noise ratio (SNR) at the receiver for such frequencies. For the mitigation of these effects, we propose a pre-distortion and digital pre-equalization scheme using a luminous feedback signal in the transmitter module. The system is modeled so that the operating points are mathematically deduced and evaluated by simulations and by an experimental setup. By allowing the linearization of the transmitted light signal and the maintenance of an average SNR in all OFDM subcarriers, the performance improvement is confirmed in comparison with other schemes, such as with non-predistortion, pre-distortion with fixed parameters, and simple post-equalization.

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