Several practical wireless scenarios exist where the transmitted signal might undergo severe channel fading. This work presents the Extreme Two-Wave (ETW) fading model, encompassing simultaneously the Two-Ray and the k-µ Extreme fading models, which have been shown to provide a tight fit to empirical measurements in harsh propagation conditions. The ETW model is a limiting case of the recently introduced Multicluster Two-Ray (MTW) fading model and can be used to model wireless communications links in some of the new use cases defined in 5G and beyond wireless networks in environments experiencing severe fading. The chief probability functions are obtained for the proposed ETW model, as well as the outage probability. In addition, the ETW model is extended to incorporate shadowing effects.

We introduce and characterize the Multi-cluster Two-Wave (MTW) fading model, which generalizesboththe Durgin’s Two-Wave with Diffuse Power (TWDP) and the$\kappa $-$\mu $models under a common umbrella. The MTW model consists of an arbitrary number of clusters of waves each of which may include one or two dominant (specular) components. The chief probability functions of the MTW fading model are obtained, including the probability density function, the cumulative distribution function and the generalized moment-generating function. The proposed model is empirically validated using channel measurements in the sub-THz band and a number of applications are exemplified, including the outage probability in noise-limited and interference-limited scenarios and the energy detection probability. A composite Inverse Gamma (IG)/MTW model is also investigated, thus extending the proposed propagation model to include shadowing.

The recently introduced independent fluctuating two-ray (IFTR) fading model, consisting of two specular components fluctuating independently plus a diffuse component, has proven to provide an excellent fit to different wireless environments, including the millimeter-wave band. However, the original formulations of the probability density function (PDF) and cumulative distribution function (CDF) of this model are not applicable to all possible values of its defining parameters, and are given in terms of multifold generalized hypergeometric functions, which prevents their widespread use for the derivation of performance metric expressions. A new formulation of the IFTR model is here presented as a countable mixture of Gamma distributions which greatly facilitates the performance evaluation for this model in terms of the metrics already known for the much simpler and widely used Nakagami-mfading, and is shown to provide a better fit to empirical measurements than the original formulation. Additionally, a closed-form expression is presented for the generalized moment generating function (GMGF), which permits to readily obtain all the moments of the distribution of the model, as well as several relevant performance metrics. Based on these new derivations, performance results are presented for the IFTR model considering different metrics, which are verified by Monte Carlo simulations.

We introduce, characterize and validate the independent fluctuating two-ray (IFTR) fading model, which consists of two specular (dominant) components that fluctuate independently, plus a diffuse one resulting from the reception of multiple scattered waves. The IFTR model complements the fluctuating two-ray (FTR) model, in which the specular components are fully correlated and fluctuate jointly. The chief probability functions of the received SNR of this new model, including the PDF, CDF and MGF, are given in closed-form. The IFTR model is empirically validated using measured data from Line-Of-Sight (LOS) millimeter-wave channels, showing a better fit than the FTR model and other models previously used in these channels, and providing a remarkable improvement at 73 GHz.

We present a composite wireless fading model encompassing multipath fading and shadowing based on fluctuating two-ray (FTR) fading and inverse gamma (IG) shadowing. We first determine an alternative framework for the statistical characterization and performance evaluation of the FTR fading model, which is based on the fact that the FTR fading distribution can be described as an underlying Rician Shadowed (RS) distribution with continuously varying parameter$K_{T}$(ratio of specular to diffuse components). We demonstrate that this new formulation permits to obtain a closed-form expression of the generalized moment generating function (GMGF) of the FTR model, from which the PDF and CDF of the composite IG/FTR model can be obtained in closed-form. The exact and asymptotic outage probability of the IG/FTR model are analyzed and verified by Monte Carlo simulations.

We present two alternative frameworks for the statistical characterization and performance evaluation of the fluctuating two-ray (FTR) fading model which simplify previous approaches. The new formulations are based on the fact that the FTR fading distribution can be described, for arbitrary$m$, as an underlying Rician Shadowed (RS) distribution with continuously varying parameter$K_{r}$(ratio of specular to diffuse power components), while for the special case of$m$being an integer, it is demonstrated that the FTR fading model can be described in terms of a finite number of underlying squared Nakagami-$m$distributions. It is shown that any performance metric that is computed by averaging over the probability density function (PDF) of the FTR fading model can be expressed in terms of a finite-range integral over the corresponding performance metric for the simpler RS (for arbitrary$m$) or Nakagami-$m$(for integer$m$) fading models, for which many results are available in closed-form. New expressions for some Laplace-domain statistics of interest are also obtained; these are used to analyze the outage probability of FTR fading under co-channel interference, as well as to obtain closed-form expressions for the main statistics of a composite wireless channel model encompassing FTR fading and shadowing.

Massive multiple‐input multiple‐output (MIMO) technology employs hundreds of antennas at the base station (BS) of a cellular system. Activating hundreds of antennas requires hundreds of radio‐frequency (RF) chains that lead to high cost and high energy consumption. Antenna selection techniques reduce the number of RF chains while curtailing the resulting performance loss. In this study, the authors consider massive‐MIMO downlink with zero‐forcing (ZF) precoding in a single cell. In ZF precoding with antenna selection, the number of users must always be less than or equal to the number of selected antennas, which may require adopting user selection (scheduling) algorithms. They propose a joint user and antenna selection algorithm to increase BS's energy efficiency (EE) and show that its performance is very close to that of the optimum exhaustive‐search based scheme. Using an analytical approximation for EE of the proposed scheme in asymptotically large numbers of users region, they find the optimum number of antennas to be selected.