In this paper, we perform a systematic investigation of the statistics associated with the product of two independent and non-identically distributed κ-μ random variables. More specifically, we develop novel analytical formulations for many of the fundamental statistics of interest, namely, the probability density function, cumulative distribution function, and moment-generating function. Using these new results, closedform expressions are obtained for the higher order moments, amount of fading and channel quality estimation index, while analytical formulations are obtained for the outage probability, average channel capacity, average symbol error probability, and average bit error probability. These general expressions can be reduced to a number of fading scenarios, such as the double Rayleigh, double Rice, double Nakagami-m, κ-μ/Nakagami-m, and Rice/Nakagami-m, which all occur as special cases. Additionally, as a byproduct of the work performed here, formulations for the κ-μ/κ-μ composite fading model can also be deduced. To illustrate the efficacy of the novel expressions proposed here, we provide useful insights into the outage probability of a dualhop system used in body area networks, and demonstrate the suitability of the κ-μ/κ-μ composite fading for characterizing shadowed fading in device-to-device channels.

This paper presents exact, novel formulations for the probability density function and cumulative distribution function for the product of two independent and non-identically distributed α-μ, κ-μ, and η-μ variates. The expressions are given in terms of both 1) generalized Fox H-function and 2) easily computable series expansions. The formulations derived can be directly used to explore the performance of a number of wireless communication processes, including multihop systems, cascaded channels, radar communications, multiple-input multiple-output links, and others. Due to the high flexibility of the above-mentioned distributions, the results presented here comprise a substantial number of useful product distributions. As application examples, performance metrics for the cascaded fading channel are derived. The validity of the expressions is confirmed via Monte Carlo simulation. It is noteworthy that, because any composite multipath-shadowing fading model is obtained as a particular case of the product of two fading variables, the results given here provide a plethora of composite multipath-shadowing fading scenarios.

Exact, closed-form expressions for the probability density function and the cumulative distribution function for the ratio of the products of an arbitrary number of independent and non-identically distributed α-μ variates are derived. The only restriction placed on the participating distributions is that there must be a rational relationship between their α parameters, which, in practical terms, represents no impairment. The expressions are given in terms of the Meijer G-function and, alternatively, in terms of a finite sum of hypergeometric functions. These results can be used to investigate the performance of wireless communication systems in a variety of realistic propagation environments in which the numerator and denominator products might be used to represent the signal and the interference. In addition, the results given comprise those for the ratio of the products of arbitrary combinations of other useful distributions such as one-sided Gaussian, negative exponential, Rayleigh, Weibull, Gamma, and Nakagami-m. Simulation is used to confirm the results. An application example is given in order to illustrate the use of the formulations.

This work compares the statistical fitting performance of the fading models α-μ, Nakagami-Lognormal, Generalized-K, and Fisher-Snedecor, to field measurements conducted at 1.8 GHz in a composite fading environment. The aim is to investigate whether a substantially easily computable, simpler model, namely α-μ, can be used instead of more intricate ones, namely, Nakagami-Lognormal, Generalized-K, and Fisher-Snedecor, the former first explicitly derived for that scenario and the latter three obtained as an approximation of it. The comparison uses metrics such as normalized mean square error (NMSE) and the modified Kolmogorov-Smirnov test (modified K-S). In overwhelmed cases, α-μ. outperformed all the other models or, otherwise, gave a comparable performance.

Having an infrastructure capable of exchanging data at high speed is an efficient way to drive the evolution and development of new applications and existing services. The 5G technology has emerged as a trusted source to meet the increased demand of Internet of Things (IoT) devices connected to the network, in addition to enabling Internet connectivity at high broadband speeds. Another important feature of 5G is to allow the use of Software Defined Network (SDN) and Network Function Virtualization (NFV), mechanisms responsible for performing network configurations through software, as well as the control and management of devices using the configuration network functions or device virtualization. The concern with information security in the 5G network is increasing, as cybercriminals try to access important data that is transported over the network, since the demand for connected IoT devices will be greater, allowing for several possibilities of attacks. The understanding of possible threats and attacks is necessary, so that new measures are taken against cybercrimes presented in the 5G and IoT networks. This paper aims to elucidate some conceptions of what 5G technology is and the use of IoT in this network, contextualizing the SDN and NFV paradigms to allow the configuration of the functionality and management of the network by software. In addition, concerns are reported about possible information security attacks that can occur in 5G networks.