Abstract
In this contribution, we use fading measurements at 2.45, 5.25, 29, and 60 GHz, and wind speed data, to study the dynamic effects of vegetation on propagating radiowaves. A new simulation model for generating signal fading due to a swaying tree has been developed by utilizing a multiple mass-spring system to represent a tree and a turbulent wind model. The model is validated in terms of the cumulative distribution function (CDF), autocorrelation function (ACF), level crossing rate (LCR), and average fade duration (AFD) using measurements. The agreements found between the measured and simulated first- and second-order statistics of the received signals through vegetation are satisfactory. In addition, Ricean K-factors for different wind speeds are estimated from measurements. Generally, the new model has similar dynamical and statistical characteristics as those observed in measurements and can thus be used for synthesizing signal fading due to a swaying tree. The synthesized fading can be used for simulating different capacity enhancing techniques such as adaptive coding and modulation and other fade mitigation techniques.
Highlights
In a given environment, radiowaves are subjected to different propagation degradations
Fade mitigation techniques (FMTs) such as adaptive coding and modulation can be used to counteract the signal fading caused by swaying vegetation
During windy conditions, power efficient modulation schemes such as BPSK and QPSK can be used to increase the link availability, while spectral efficient modulation schemes such as 16 QAM and 64 QAM can be applied during calm wind conditions [1]
Summary
Radiowaves are subjected to different propagation degradations. Vegetation movement due to wind can both attenuate and cause a fading effect to the propagating signal. Optimize, and test FMT, data collected from propagation measurements are needed Such data may not be available at the preferred frequency, wind speed conditions, and so forth. For accurate prediction of the channel characteristics, the motion of trees under the influence of wind should be taken into account. We develop a theoretical model based on the motion of trees under the influence of wind, and is validated in terms of first- and second-order statistics using available measurements.
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