arXiv subjects

Rausley A. A. de Souza

Publications and source records attributed to Rausley A. A. de Souza.

18 recordsLinked to original sources

arXiv2026

Cascaded Multiwire-PLC/Multiple-VLC System: Characterization and Performance

This paper proposes a cascaded multiwire-power line communication (PLC)/multiple-visible light communication (VLC) system. This hybrid architecture offers low installation cost, enhanced performance, practical feasibility, and a wide range of applications. Novel analytical expressions are derived for key statistics and outage probability, bit error probability, and ergodic channel capacity metrics. Furthermore, the analytical results are validated through Monte Carlo simulations, with several performance curves presented under various channel and PLC/VLC system parameters. All expressions derived in this work are original and have not been previously published. Our proposed system proves feasible for smart environments, green communication systems, internet of things networks, industrial environments, and next-generation networks.

eess.SP↗

arXiv2026

Trellis-Based Noise Modulation with Soft-Decision Viterbi Detection

Noise modulation conveys information through the statistical properties of noise rather than conventional deterministic signal parameters. This paper investigates a trellis-based noise modulation framework that exploits temporal dependencies between successive noise-power symbols. A binary filtering-based configuration is first developed as an illustrative finite-state model for comparing hard- and soft-decision sequence detection. A joint soft Viterbi receiver is then proposed, which directly incorporates the received noise energy into a likelihood-based branch metric, avoiding the information loss associated with intermediate hard decisions. The framework is further extended to an N-ary state-dependent trellis-based noise modulation scheme, where the transmitted noise-power level depends jointly on the current input symbol and trellis state. A Bhattacharyya-distance-based method is employed for systematic power-level design. Simulation results demonstrate the advantage of soft-decision sequence detection over hard-decision processing and investigate the effects of power-level design, traceback depth, energy-per-bit-to-noise ratio, symbol duration, and modulation order. The results also reveal the trade-off between spectral efficiency, detection reliability, and trellis complexity in higher-order noise modulation.

eess.SP↗

arXiv2026

Fluid Antenna-Aided Noise Modulation: Spatial Diversity for Variance-Based Wireless Communication

Noise modulation (NoiseMod) encodes information in the \emph{variance} of a transmitted noise-like waveform rather than in its amplitude, phase, or frequency, and is attractive for ultra-low-power and covert links. Its main weakness is that, unlike classical modulation, it exhibits \emph{no} diversity under Rayleigh fading: its bit error probability (BEP) decays only as $1/(N_sδ)$, where $N_s$ is the number of noise samples per bit and $δ$ the useful-to-thermal noise variance ratio. Independently, fluid antenna systems (FAS) have been shown to recover substantial selection diversity from a single radiating element that switches among $N_p$ closely spaced ports, without extra radio-frequency chains. This paper combines the two: we equip a NoiseMod receiver with a fluid antenna and derive its average BEP. For idealized, mutually independent ports, we obtain an exact closed-form BEP via order statistics of the port envelopes. For the physically accurate, spatially correlated case governed by Jake's model, we build a semi-analytical BEP using the two-stage channel approximation of Khammassi \emph{et al.} We validate both regimes against full signal-level Monte Carlo simulation and show that (i) FAS restores a diversity order that grows with the number of ports $N_p$ when ports are weakly correlated, (ii) this gain saturates once the fluid-antenna aperture $Wλ$ is fixed and $N_p$ grows, mirroring the outage-probability saturation reported for FAS, now observed for BEP, and (iii) an intrinsic, correlation-independent (and $δ$-independent) BEP floor set only by $N_s$ and the variance ratio $α$ persists regardless of the antenna diversity order.

cs.IT↗

arXiv2026

On the Practical Performance of Noise Modulation for Ultra-Low-Power IoT: Limitations, Capacity, and Energy Trade-offs

Ultra-low-power (ULP) Internet of Things (IoT) applications demand communication architectures with minimal energy consumption. Noise Modulation (NoiseMod) addresses this by encoding data through the statistical variance of a noise-like signal, eliminating the need for a coherent carrier. To bridge the gap between theoretical potential and practical deployment, this paper benchmarks NoiseMod against standard modulations like BPSK and NC-FSK. We analytically derive the optimal detection threshold and Bit Error Rate (BER) for AWGN and Rayleigh fading channels. Our results show that non-coherent NoiseMod suffers a catastrophic error floor in fading environments, making architectural additions like channel state information (CSI) estimation and 2-antenna selection diversity desirable. Using an ADC-aware energy model, we reveal that NoiseMod's oversampling severely bottlenecks capacity and imposes an 8 dB SNR penalty compared to NC-FSK for a $10^{-3}$ BER in AWGN. Despite its oscillator-free design drastically reducing baseline circuit power, these limitations establish a critical energy crossover distance, which decreases with frequency. Below this distance, NoiseMod offers superior energy efficiency; beyond it, the radiated power needed to overcome its SNR penalty makes coherent schemes like BPSK vastly superior.

cs.IT↗

arXiv2026

Performance Limits of FRIS Systems in Nakagami-$m$ Fading

Fluid reconfigurable intelligent surfaces (FRIS) have recently emerged as a promising technology for enhancing wireless link reliability through spatial decorrelation. However, their performance analysis remains challenging due to the sum-product structure of the cascaded channel. This letter develops a rigorous analytical framework for FRIS-assisted wireless systems over arbitrarily correlated Nakagami-$m$ fading channels. Specifically, we introduce a physically consistent correlation model for Nakagami-$m$ fading and derive tractable statistical characterizations for the cascaded channel. These results lead to rigorous lower bounds for the outage probability (OP), with a simplified expression also obtained for the independent and identically distributed case. To the best of our knowledge, these are the first strict OP lower bounds reported for an FRIS-aided wireless system under arbitrarily correlated Nakagami-$m$ fading. CLT- and Gamma-based approximations are included as benchmark methods. Notably, the numerical results show that the proposed OP bound not only provides rigorous performance guarantees but also yields a noticeably tighter OP characterization than the CLT approximation in the high-SNR regime.

eess.SP↗

arXiv2026

Fast-TurboQuant: A Multiplier-Free Online Vector Quantization Approach

As large language models scale, memory bandwidth for key-value caches and retrieval-augmented generation systems becomes a critical bottleneck. While 1-bit quantization addresses this constraint, recent TurboQuant relies on dense random rotation matrices to condition the vector distribution before quantization. This projection demands millions of floating-point multiplications per embedding, making it difficult to deploy on constrained edge silicon. We introduce Fast-TurboQuant, a multiplier-free projection architecture that replaces the dense matrix with a structured fast Johnson-Lindenstrauss transform. By applying a Rademacher phase inversion followed by a fast Walsh-Hadamard transform (FWHT), the method leverages sub-Gaussian concentration to satisfy the prerequisites of scalar Lloyd-Max quantization without Gaussian projections. This substitution reduces the arithmetic complexity to only additions, eliminating hardware multipliers. Evaluation on DBpedia OpenAI-3 Large embeddings demonstrates a 19.7 times algorithmic speedup under sequential execution. Furthermore, the dimension expansion due to the FWHT zero-padding reduces the mean squared error and improves Recall@10.

cs.LG↗

arXiv2026

Exact Statistical Characterization and Performance Analysis of Fluid Reconfigurable Intelligent Surfaces

Fluid reconfigurable intelligent surfaces (FRIS) extend conventional RIS architectures by enabling physical reconfiguration of element positions, thereby introducing a fundamentally new degree of freedom for controlling spatial correlation and improving link reliability. Despite this promise, rigorous performance analysis of FRIS-assisted wireless systems has remained challenging, as exact statistical analyses of the end-to-end cascaded channels have been unavailable. This paper addresses this gap by providing the first exact closed-form characterization of the end-to-end cascaded channel gain in FRIS-aided systems under general spatial correlation. By exploiting the spectral structure of the FRIS-induced correlation matrix, we show that the channel gain statistics can be represented as a finite linear combination of K-distributions. This unified formulation naturally captures fully correlated, effectively decorrelated, and intrinsically uncorrelated operating regimes as special cases. Building on the derived channel statistics, we further obtain exact closed-form expressions for the outage probability and ergodic capacity. We also conduct an outage-based asymptotic analysis, which reveals the true diversity order of the system. Numerical results corroborate the proposed analytical framework via Monte Carlo simulations, benchmark its accuracy against state-of-the-art approximation-based approaches, and demonstrate that fluidic reconfiguration can yield tangible reliability gains by reshaping the spatial correlation structure.

eess.SP↗

arXiv2025

Optimal Bit Detection in Thermal Noise Communication Systems Under Rician Fading

Thermal noise communication (TNC) enables ultra-low-power wireless links for Internet of Things (IoT) devices by modulating the variance of thermal noise, rather than using active carriers. Existing analyses often rely on Gaussian approximations and overlook fading effects, which limits their accuracy. This paper presents an accurate analytical framework for optimal bit detection in TNC systems under Rician fading. Using chi-squared statistics, we derive the optimal maximum-likelihood detection threshold and an expression for the bit error probability (BEP) via Gauss-Laguerre quadrature. The proposed model eliminates approximation errors and accurately characterizes performance for finite sample sizes. Monte Carlo simulations confirm the analytical results and demonstrate significant improvements in BEP compared with suboptimal Gaussian-based detection. Furthermore, the influence of key parameters, sample size, resistance ratio, and Rician K-factor, is quantified. The proposed framework provides a solid foundation for designing energy-efficient TNC receivers in future B5G/6G and large-scale IoT systems.

eess.SP↗

arXiv2025

3D 8-Ary Noise Modulation Using Bayesian- and Kurtosis-based Detectors

This paper presents a novel three-dimensional (3D) 8-ary noise modulation scheme that introduces a new dimension: the mixture probability of a Mixture of Gaussian (MoG) distribution. This proposed approach utilizes the dimensions of mean and variance, in addition to the new probability dimension. Within this framework, each transmitted symbol carries three bits, each corresponding to a distinct sub-channel. For detection, a combination of specialized detectors is employed: a simple threshold based detector for the first sub-channel bit (modulated by the mean), a Maximum-Likelihood (ML) detector for the second sub-channel bit (modulated by the variance), a Kurtosis-based, Jarque-Bera (JB) test, and Bayesian Hypothesis (BHT)-based detectors for the third bit (modulated by the MoG probability). The Kurtosis- and JB-based detectors specifically distinguish between Gaussian (or near-Gaussian) and non-Gaussian MoG distributions by leveraging higher-order statistical measures. The Bit Error Probabilities (BEPs) are derived for the threshold-, Kurtosis-, and BHT-based detectors. The optimum threshold for the Kurtosis-based detector is also derived in a tractable manner. Simulation results demonstrate that a comparably low BEP is achieved for the third sub-channel bit relative to existing two-dimensional (2D) schemes. Simultaneously, the proposed scheme increases the data rate by a factor of 1.5 and 3 compared to the Generalized Quadratic noise modulator and the classical binary KLJN noise modulator, respectively. Furthermore, the Kurtosis-based detector offers a low-complexity solution, achieving an acceptable BEP of approximately 0.06.

eess.SP↗

arXiv2025

Composite Generalized Quadratic Noise Modulation via Signal Addition: Towards Higher Dimensional Noise Modulations

This letter proposes superposing two Generalized Quadratic Noise Modulators (GQNM) by simply adding their outputs. It creates a 16-ary noise modulator that resembles QAM modulators in classical communication. It modulates the information bits on four different means and four different variances. It could also be applied to reach higher-order modulations than 16-ary schemes by adding the outputs of more than two modulators, which is not discussed in detail in this letter and left for future work. By selecting the parameters necessary for satisfying the theoretical distinguishability conditions provided in the paper, we can reach better performances in comparison to the Kirchhoff-Law Johnson Noise (KLJN) modulator and the GQNM modulator, which is verified by the simulations. The better result in terms of smaller Bit Error Probability (BEP) is achieved by increasing the complexity in the modulator, the transmitter, and the detectors in the receiver.

eess.SP↗

arXiv2025

Resistor Hopping KLJN Noise Communication Using Small Bias Voltages Supported by ML and Optimum Threshold-Based Detectors

In this paper, a Resistor Hopping (RH) scheme with the addition of biases is proposed for secure Kirchhoff Law Johnson-Noise (KLJN) communication. The RH approach enables us to increase the bit rate of secure communication between Alice and Bob, while also ensuring that the inherent unconditional security of KLJN is satisfied. The biases are added to the proposed scheme to better distinguish between Gaussian distributed noises in terms of their means, rather than just using variances. Throughout the paper, we strive to minimize biases to achieve a power-efficient scheme. For the detection part of the proposed algorithm, a Maximum-Likelihood (ML) detector is derived. The separability condition of Gaussian distributions is investigated, along with the provision of a threshold-based detector that offers both simple and optimal thresholds in terms of minimizing the error probability. Some analysis of the proposed RH-KLJN communication scheme is provided, including Physical Layer Security (PLS) equations. Simulation results demonstrate the advantages of the proposed scheme over the classical KLJN scheme, offering a higher data rate and lower bit error probability at the expense of increased complexity.

eess.SP↗

arXiv2025

A Generalized Framework for Quadratic Noise Modulation Using Non-Gaussian Distributions

This letter generalizes noise modulation by introducing two voltage biases and employing non-Gaussian noise distributions, such as Mixture of Gaussian (MoG) and Laplacian, in addition to traditional Gaussian noise. The proposed framework doubles the data rate by enabling discrimination in both the mean and variance of transmitted noise symbols. This novel modulation scheme is referred to as Generalized Quadratic Noise Modulation (GQNM). Closed-form expressions for the Bit Error Probability (BEP) are derived for the Generalized Gaussian (GG) and Gaussian Mixture of Two Gaussians (GMoTG) cases. Simulation results demonstrate the advantages of the generalized modulation scheme, particularly under non-Gaussian noise assumptions, highlighting its potential for enhanced performance in low-power and secure communication systems.

eess.SP↗

arXiv2025

LNN-powered Fluid Antenna Multiple Access

Fluid antenna systems represent an innovative approach in wireless communication, recently applied in multiple access to optimize the signal-to-interference-plus-noise ratio through port selection. This letter frames the port selection problem as a multi-label classification task for the first time, improving best-port selection with limited port observations. We address this challenge by leveraging liquid neural networks (LNNs) to predict the optimal port under emerging fluid antenna multiple access scenarios alongside a more general $α$-$μ$ fading model. We also apply hyperparameter optimization to refine LNN architectures for different observation scenarios. Our approach yields lower outage probability values than existing methods.

eess.SP↗

arXiv2025

On the Secrecy Performance of $α$-$\mathcal{F}$ Channels with Pointing Errors

This paper investigates the physical layer security (PLS) performance of $α$-$\mathcal{F}$ fading channels with pointing errors under passive and active eavesdropping scenarios. Novel analytical expressions are derived for key PLS metrics, including the probability of strictly positive secrecy capacity, the average secrecy capacity, and the secure outage probability. An asymptotic analysis is also investigated to provide further insights into the system behavior under high signal-to-noise ratio conditions. The analytical results are validated through Monte Carlo simulations, with several performance curves presented for a range of channel and system parameters. All expressions derived in this work are original and have not been previously published.

cs.IT↗

arXiv2023

An Efficient Machine Learning-based Channel Prediction Technique for OFDM Sub-Bands

The acquisition of accurate channel state information (CSI) is of utmost importance since it provides performance improvement of wireless communication systems. However, acquiring accurate CSI, which can be done through channel estimation or channel prediction, is an intricate task due to the complexity of the time-varying and frequency selectivity of the wireless environment. To this end, we propose an efficient machine learning (ML)-based technique for channel prediction in orthogonal frequency-division multiplexing (OFDM) sub-bands. The novelty of the proposed approach lies in the training of channel fading samples used to estimate future channel behaviour in selective fading.

cs.IT↗

arXiv2023

Low-Complexity Dynamic Directional Modulation: Vulnerability and Information Leakage

In this paper, the privacy of wireless transmissions is improved through the use of an efficient technique termed dynamic directional modulation (DDM), and is subsequently assessed in terms of the measure of information leakage. Recently, a variation of DDM termed low-power dynamic directional modulation (LPDDM) has attracted significant attention as a prominent secure transmission method due to its ability to further improve the privacy of wireless communications. Roughly speaking, this modulation operates by randomly selecting the transmitting antenna from an antenna array whose radiation pattern is well known. Thereafter, the modulator adjusts the constellation phase so as to ensure that only the legitimate receiver recovers the information. To begin with, we highlight some privacy boundaries inherent to the underlying system. In addition, we propose features that the antenna array must meet in order to increase the privacy of a wireless communication system. Last, we adopt a uniform circular monopole antenna array with equiprobable transmitting antennas in order to assess the impact of DDM on the information leakage. It is shown that the bit error rate, while being a useful metric in the evaluation of wireless communication systems, does not provide the full information about the vulnerability of the underlying system.

cs.IT↗

arXiv2023

Semantic-Functional Communications in Cyber-Physical Systems

This paper explores the use of semantic knowledge inherent in the cyber-physical system (CPS) under study in order to minimize the use of explicit communication, which refers to the use of physical radio resources to transmit potentially informative data. It is assumed that the acquired data have a function in the system, usually related to its state estimation, which may trigger control actions. We propose that a semantic-functional approach can leverage the semantic-enabled implicit communication while guaranteeing that the system maintains functionality under the required performance. We illustrate the potential of this proposal through simulations of a swarm of drones jointly performing remote sensing in a given area. Our numerical results demonstrate that the proposed method offers the best design option regarding the ability to accomplish a previously established task -- remote sensing in the addressed case -- while minimising the use of radio resources by controlling the trade-offs that jointly determine the CPS performance and its effectiveness in the use of resources. In this sense, we establish a fundamental relationship between energy, communication, and functionality considering a given end application.

cs.IT↗

arXiv2023

A novel semantic-functional approach for multiuser event-trigger communication

This work introduces a new perspective for physical media sharing in multiuser communication by jointly considering (i) the meaning of the transmitted message and (ii) its function at the end user. Specifically, we have defined a scenario where multiple users (sensors) are continuously transmitting their own states concerning a predetermined event. On the receiver side there is an alarm monitoring system, whose function is to decide whether such a predetermined event has happened in a certain time period and, if yes, in which user. The media access control protocol proposed constitutes an alternative approach to the conventional physical layer methods, because the receiver does not decode the received waveform directly; rather, the relative position of the absence or presence of energy within a multidimensional resource space carries the (semantic) information. The protocol introduced here provides high efficiency in multiuser networks that operate with event-triggered sampling by enabling a constructive reconstruction of transmission collisions. We have demonstrated that the proposed method leads to a better event transmission efficiency than conventional methods like TDMA and slotted ALOHA. Remarkably, the proposed method achieves 100\% efficiency and 0\% error probability in almost all the studied cases, while consistently outperforming TDMA and slotted ALOHA.

cs.IT↗