Stochastic Fading Channel Models With Multiple Dominant Specular Components

Abstract

We introduce a comprehensive statistical characterization of the multipath wireless channel built as a superposition of scattered waves with random phases. We consider an arbitrary number <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$N$</tex-math></inline-formula> of specular (dominant) components plus an undetermined number of other weak diffusely propagating waves. Our approach covers the cases in which the specular components have constant amplitudes, as well as when these components experience random fluctuations. We show that this class of fading models can be expressed in terms of a continuous mixture of an underlying Rician (or Rician shadowed) fading model, averaged over the phase distributions of the specular waves. The proposed model parameters can be adjusted to tailor the statistical distribution of the received radio signal power to a wide variety of wireless scenarios, some of which are not covered by other state-of-the-art stochastic wireless channel models. In this regard, we verify that the proposed models accurately fit experimental measurements for which their multi-modality cannot be properly captured by other current stochastic models. It is shown that the fluctuations of the specular components have a detrimental impact on performance, and it is formally demonstrated that the lower error rate is obtained when the signal power is concentrated on a single specular component, regardless of whether it fluctuates or not.