Performance analysis for adaptive smart wireless system computational modelling and simulation methods

Abstract

In wireless communication channels, the signals arriving at the receiver may be of stochastic newlinenature or be super-positioned due to non-uniform scattering and shadowing. This occurs due to newlinethe signal interfering with several obstacles over its path viz., buildings, mountains etc. These newlineobstacles lead to several phenomena viz., reflection, scattering, and diffraction which results in newlinegeneration of multipath components while arriving at the receiver subject to different delays. The newlinesuperposition of these multipath components results in rapid variation in average received signal newlinepower, commonly known as the fading phenomena in wireless communication. In this context, newlinethe modeling of wireless propagation channels can be realized considering its substantial newlinesignificance for design and performance evaluation of complex communication systems. In newlinegeneral, fading can be broadly classified into fast fading/ short term fading, and slow fading/ newlinelong term fading. In a typical wireless propagation scenario, the signal received depicts rapid newlinesmall scale fluctuations in its strength which occurs due to multipath propagation superimposed newlineover long-term fluctuations and is termed as shadowing. This phenomenon is conventionally newlineexperienced as a consequence of large obstacles present between the receiving and transmitting newlinestations. Thus, small-scale fading is observed due to rapid fluctuations in the signal level, while newlinethe effects of shadowing induce slow fluctuations in the mean signal strength. However, in newlinerealistic scenarios both fading and shadowing occurs simultaneously, referred to as composite newlinefading or shadowed fading and is modeled using composite distributions. The modeling of newlinelognormal based composite distributions poses severe mathematical complexities for which newlineseveral tight and close approximations have been used. In this context, several alternate models newlineto characterize the composite scenarios have been proposed and different performance measures newlineviz., amount of fading, outage probability, average