The effect of land cover is incorporated in the radio
propagation prediction algorithm of Q-Rap. It is implemented
by optimizing both the effective height of the land cover, hence
affecting obstruction-loss calculations, and by adding terms to
the basic transmission loss algorithm. A complete set of separate
coefficients to these terms is determined for each land cover type.
The optimization method improves the standard deviation of the
error from 9.6 to 6.3 dB for measurements and predictions done
at 390 MHz. This is an improvement of 3.3 dB over the original
model that comprises the free-space loss equation with obstruction
loss calculations for multiple knife edges. At this frequency, the
correlation coefficient between the measured and predicted values
improved from 79.5% to 85.6%. At 2145 MHz, the optimization
method improves the standard deviation of the error from 16.2
to 8.6 dB, as well as the correlation coefficient between the measurements
and predicted values from 56.2% to 70.5%. The use
of the correlation coefficient between the measured and predicted
signal values, in addition to the standard deviation of the error
and mean error as criteria to be used when evaluating propagation
prediction models, is also proposed in this paper. A basis for best
practices in tuning propagation prediction algorithms in radio
planning tools using semi-empirical models is presented.
Palmer, Andrew J(University of Pretoria, 2005-09-22)
The objective of this study was to provide an adequate model of the k-factor for scientific radio planning in South Africa for terrestrial propagation. An extensive literature survey played an essential role in the research ...
Chiwewe, Tapiwa Moses; Hancke, Gerhard P.(Institute of Electrical and Electronics Engineers, 2018-08)
Cognitive radio and dynamic spectrum access can reform the way that radiofrequency spectrum is accessed. Problems of spectrum scarcity, coexistence, and unreliable wireless communication that affect industrial wireless ...
Resources available for operation in cognitive radio networks (CRN) are generally limited, making it imperative for efficient
resource allocation (RA) models to be designed for them. However, in most RA designs, a significant ...