We consider the use of the Fisher-Snedecor F distribution, which is defined as the ratio of two chi-squared variates, to model composite fading channels. In this context, the root-mean-square power of a Nakagami-m signal is assumed to be subject to variations induced by an inverse Nakagamim random variable. Comparisons with physical channel data demonstrate that the proposed composite fading model provides as good, and in most cases better, fit to the data compared to the generalized-K composite fading model. Motivated by this result, simple novel expressions are derived for the key statistical metrics and performance measures of interest.
Using device-to-device communications as an underlay for cellular communications will provide an exciting opportunity to increase network capacity as well as improving spectral efficiency. The unique geometry of device-to-device links, where user equipment is often held or carried at low elevation and in close proximity to the human body, will mean that they are particularly susceptible to shadowing events caused not only by the local environment but also by the user's body. In this paper, the shadowed κ − μ fading model is proposed, which is capable of characterizing shadowed fading in wireless communication channels. In this model, the statistics of the received signal are manifested by the clustering of multipath components. Within each of these clusters, a dominant signal component with arbitrary power may exist. The resultant dominant signal component, which is formed by the phasor addition of these leading contributions, is assumed to follow a Nakagami-m distribution. The probability density function, moments, and the moment-generating function are also derived. The new model is then applied to device-to-device links operating at 868 MHz in an outdoor urban environment. It was found that shadowing of the resultant dominant component can vary significantly depending upon the position of the user equipment relative to the body and the link geometry. Overall, the shadowed κ − μ fading model is shown to provide a good fit to the field data as well as providing a useful insight into the characteristics of the received signal.
Emerging cellular technologies such as those proposed for use in 5G communications will accommodate a wide range of usage scenarios with diverse link requirements. This will include the necessity to operate over a versatile set of wireless channels ranging from indoor to outdoor, from line-of-sight (LOS) to non-LOS, and from circularly symmetric scattering to environments which promote the clustering of scattered multipath waves. Unfortunately, many of the conventional fading models lack the flexibility to account for such disparate signal propagation mechanisms. To bridge the gap between theory and practical channels, we consider κ-µ shadowed fading, which contains every linear fading models proposed in the open literature as special cases. In particular, we propose an analytic framework to evaluate the average of an arbitrary function of the SINR over κ-µ shadowed fading channels by using a simplified orthogonal expression with tools from stochastic geometry. Using the proposed method, we evaluate the spectral efficiency, moments of the SINR, and outage probability of a K-tier HetNet with K classes of BSs, differing in terms of the transmit power, BS density, shadowing and fading. Building upon these results, we provide important new insights into the network performance of these emerging wireless applications while considering a diverse range of fading conditions and link qualities.
While the deployment of 5G cellular systems will continue well in to the next decade, much interest is already being generated towards technologies that will underlie its successor, 6G. Undeniably, 5G will have transformative impact on the way we live and communicate, yet, it is still far away from supporting the Internet-of-Everything (IoE), where upwards of a million devices per km 3 (both terrestrial and aerial) will require ubiquitous, reliable, low-latency connectivity. This article looks at some of the fundamental problems that pertain to key physical layer enablers for 6G. This includes highlighting challenges related to intelligent reflecting surfaces, cell-free massive MIMO and THz communications. Our analysis covers theoretical modeling challenges, hardware implementation issues and scalability among others. The article concludes by delineating the critical role of signal processing in the new era for wireless communications.
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