In this letter, the impact of the non-linearity of the propagation medium is studied in fluid antennas systems (FAS) systems. First and second order statistics are deduced for FAS under α-μ fading channels. Based on this and in order to evaluate the performance of the mentioned systems, expressions are also deduced for the outage probability (OP) and ergodic channel capacity. Furthermore, an exact reduction of the OP due to N-th port for an (N-1)-port is also presented. All the expressions emerging from this study are entirely new, marking a significant contribution to the existing body of knowledge. Several curves are shown under different values for the system parameters and channel non-linearity. This is the first work in which the effect of the channel non-linearity is evidenced in a FAS.

In this correspondence, the physical layer security of wireless systems under generalized α- $\mathcal{k}$ -μ and α- $\eta$ -μ fading with arbitrary fading parameters is analyzed in terms of the secrecy outage probability (SOP). Novel analytical expressions for the lower bound of the SOP are attained. Moreover, an asymptotic secrecy analysis is investigated for each corresponding SOP to get the secrecy diversity gain. Monte Carlo simulations are provided to corroborate the proposed analytical framework.

A thorough millimeter-wave measurement campaign is carried out in an indoor environment with an aim at characterizing the short-term fading channel behavior. The measurements are conducted in a variety of scenarios, with frequencies ranging from 55 GHz to 65 GHz, in line-of-sight and non-line-of-sight conditions, and combinations of horizontal and vertical polarizations at both transmitter and receiver. A number of fading models are tested, namely Rayleigh, Rice, Nakagami-m, α-μ, κ-μ, η-μ, and α-η-κ-μ. The statistics under analysis are those characterizing the fading amplitude and the frequency selectivity. In particular, the probability density and cumulative distribution functions for the former and level crossing rate per bandwidth unit for the latter are the respective first-and second-order statistics used. To this end, from the experimental data, the parameters of the models are estimated and the corresponding theoretical curves are plotted and compared with the empirical ones. Whereas the required theoretical formulations of the first-order statistics of these models are already well known, those of the second-order statistics as well as these fitting process.

Multicarrier modulation allows for deploying wideband systems resilient to multipath fading channels, impulsive noise, and intersymbol interference compared to single-carrier systems. Despite this, multicarrier signals suffer from different types of distortion, including channel noise sources and long- and short-term fading. Consequently, the receiver must estimate the channel features and compensate it for data recovery based on channel estimation techniques, such as non-blind, blind, and semi-blind approaches. These techniques are model-based and designed with accurate mathematical channel models encompassing their features. Nevertheless, complex environments challenge accurate mathematical channel estimation modeling, which might neither be accurate nor correspond to reality. This impairment decreases the system performance due to the channel estimation accuracy loss. Fortunately, (AI) algorithms can learn the relationship among different system variables using a model-driven or model-free approach. Thereby, AI algorithms are used for channel estimation by exploiting its complexity without unrealistic assumptions, following a better performance than conventional techniques under the same channel. Hence, this paper comprehensively surveys AI-based channel estimation for multicarrier systems. First, we provide essential background on conventional channel estimation techniques in the context of multicarrier systems. Second, the AI-aided channel estimation strategies are investigated using the following approaches: classical learning, neural networks, and reinforcement learning. Lastly, we discuss current challenges and point out future research directions based on recent findings.

In this letter, we propose a simple and highly efficient random sequence generator for κ -μ and η -μ variates and a near-100% efficient algorithm for generating α -μ variates. The proposed algorithm may yield an efficiency higher than 80% for η -μ , 87.5% for κ -μ and almost 100% for α -μ . These generators are implemented via the rejection technique and allow for arbitrary fading parameters. The goodness-of-fit is objectively measured using the the p-value of the Kolmogorov-Smirnov test.

Recent standardization of portions of the millimeter-wave (mm-wave) band for fifth-generation (5G) operation has called for further research on how short-term fading behaves in that unexplored part of the spectrum. With such a target, this paper reports on a thorough measurement campaign conducted in an indoor environment characterized by rich-multipath scattering, a part of a modern building, with floor and ceiling constructed of reinforced concrete over steel plates with wood and plasterboard-paneled walls. Particularly, measurements have been performed in a variety of scenarios, under line-of-sight (LoS) and non-line-of-sight (nLoS) conditions, for a wide range of frequencies, namely from 25 to 40 GHz- a span of 15 GHz- therefore, including 26, 28 and 39 GHz. First and second order statistics of representative fading models, namely Rayleigh, Rice, Nakagami, folded normal, α- μ, η- μ, κ- μ, and α- η- κ- μ have been investigated. The metrics used in the analysis were the normalized mean square error (NMSE), the Kolmogorov-Smirnov (KS), and the Akaike information criterion (AIC). Additionally, the study of the κ- μ model is advanced, in which new, exact, simple closed-form expressions for probability density function, cumulative distribution function, and level crossing rate are derived for some particular cases, namely for μ = n+ 1/2 in which n ∈ \mathbb N.