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Fernando D. A. García

Publications and source records attributed to Fernando D. A. García.

2 recordsLinked to original sources

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↗

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↗