Flat Fading Modeling in Fixed Microwave Radio Links Based on ITU-R P. 530-11

Abstract

This paper mainly discusses the ITU-R P.530 flat fading model in fixed wireless channels.This empirical model introduces a more precise model than the traditional models. To evaluate the effect of this model on the system performance, the PDF of this flat fading model has been derived and used in the Monte Carlo simulation. According to the simulation results, the behavior of ITU-R P.530 model is significantly different from the lognormal model used conventionally in fixed wireless channel modeling, so using the lognormal distribution drastically causes to overestimate or underestimate the system power and fade margin in fixed wireless systems. INTRDUCTIONA microwave radio link suffers various signal fluctuation in time for a number of reasons. In fixed/mobile radio links, radio wave that propagates from transmitter to receiver, traveling through free space, undergoes absorption, reflection, refraction, diffraction, and scattering. In multi path situation, several rays with different delays and amplitudes, receiving by the receiver antenna, add to the ray of direct or line-of-sight (LOS) path constructively or destructively which introduce signal fluctuation. These signal random variations around the nominal receive level are commonly referred to as fading [1,2]. A receiver signal is said to undergo flat fading if the radio channel has a constant gain and linear phase response over a wideband larger than the bandwidth of the transmitter signal [3]. The multi path signals are not fixed in number, amplitude, phase, and arrival times, and the ability to predict these parameters is a continuing challenge for even the more advance site-specific propagation models [4]. ITU-R P.530-11 [5] includes the most practical and reliable prediction models in fixed LOS radio links. According to the measured results, [5] and [6] introduce outage prediction methods in multi path fading (flat and selective fading) conditions in worst month of year. Methods of converting from average worst month figures to the average annual figures are also given. The organization of this paper is as follow: First, the prediction method of flat fading is based on ITU-R P.530 standard reviewed. Then, the numerical simulation has been performed to demonstrate how different the system performance is by using ITU-R P.530 model and the conventional model (Lognormal Model). Finally, the simulation results are considered and concluded.