Statistical analysis of the received signal over multipath fading channels via generalization of shot-noise (original) (raw)
Related papers
Paper on Second Order Statistics of Various Fading Channels
2014
Radio-wave propagation through wireless channel is a complicated phenomenon characterized by fading which is the result of multipath propagation. In wireless communication system, random process associated with fading channels can usually characterized by their PDF (Probability Density Function) and CDF (Cumulative Distribution Function). Signal fading can drastically affect the performance of terrestrial communication systems. Several statistical models are available for describing the fading envelope of the received signal in which Rayleigh, Rician and Nakagami are the most frequently applied models. Higher-order statistics such as Level Crossing Rate (LCR) & Average Fade Duration render (AFD) insight into signals which is not always available at lower orders.
Review Paper on Second Order Statistics ofVarious Fading Channels
International Journal of Advanced Research in Electrical, Electronics and Instrumentation Energy, 2014
Radio-wave propagation through wireless channel is a complicated phenomenon characterized by fading which is the result of multipath propagation. In wireless communication system, random process associated with fading channels can usually characterized by their PDF (Probability Density Function) and CDF (Cumulative Distribution Function). Signal fading can drastically affect the performance of terrestrial communication systems. Several statistical models are available for describing the fading envelope of the received signal in which Rayleigh, Rician and Nakagami are the most frequently applied models. Higher-order statistics such as Level Crossing Rate (LCR) & Average Fade Duration render (AFD) insight into signals which is not always available at lower orders.
Conference on Decision and Control, 1999
This paper discusses the use of stochastic differential equations to model signal envelope variations over areas, which are subject to short-term fading effects. The short-term fading effects are modeled using Ornstein-Uhlenbeck processes and they are derived from first principles, using the scattering assumption of electromagnetic waves. This gives rise to signal envelope variations which follow a mean-reverting square-root process, which is elastically pulled towards a long-term mean which characterizes the propagation environment. The derived signal envelope distributions include generalizations of Rayleigh, Rician, Nakagami etc. distributions to their nonstationary analogs and thus generalizing channel models to include time variations. From these computations the second order statistics of the received signal are obtained