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In this paper, the validity of Recommendation ITU-R P.1546 in a short-range terrestrial environment is analyzed. Its three versions (P.1546, P.1546-1, and P.1546-2) are compared against simple models and evaluated using measurement results that were obtained by utilizing the pilot signal of a commercial code-division multiple-access mobile telephone network. Measurement results show that P.1546-2, on average, underestimates the field strength by more than 10 dB for typical Australian rural areas. However, it improves the error standard deviation compared to previous versions. The causes of these effects and the suggestions for further development of the Recommendation are discussed and evaluated. Index Terms--Field strength measurements, Okumura-Hata model, point-to-area, propagation prediction, Recommendation ITU-R P.1546.

This paper presents a new frustum ray tracing technique (FRTT) for the prediction of channel characteristic maps in a complex in-building environment. FRTT utilizes a fast line-clipping algorithm and does not rely on the convention time-consuming ray intersection tests. Dielectric properties of building materials are empirically derived from in situ transmission coefficient measurements, which have enhanced the accuracy of prediction results. The FRTT is found to be more accurate and computationally efficient than the conventional ray tracing technique for area-type predictions. A detailed comparison has been made using measured narrow-band and wide-band channel characteristic maps with high spatial resolution (0.2 wavelength) at line-of-sight (LOS), non-LOS, and a corner transition region inside a multifloored building. The agreement between FRTT prediction and measurement appears to be excellent. Index Terms--Channel modeling, indoor propagation, ray tracing.

This paper presents and evaluates artificial neural network (ANN) models used for macrocell path-loss prediction. Measurement data obtained by utilizing the IS-95 pilot signal from a commercial code-division multiple-access (CDMA) mobile network in rural Australia are used to train and evaluate the models. A simple neuron model and feed-forward networks with different numbers of hidden layers and neurons are evaluated regarding their training time, prediction accuracy, and generalization properties. Furthermore, different backpropagation training algorithms, such as gradient descent and Levenberg--Marquardt, are evaluated. The artificial neural network inputs are chosen to be distance to base station, parameters easily obtained from terrain path profiles, land usage, and vegetation type and density near the receiving antenna. The path-loss prediction results obtained by using the ANN models are evaluated against different versions of the semi-terrain based propagation model Recommendation ITU-R P.1546 and the Okumura--Hata model. The statistical analysis shows that a non-complex ANN model performs very well compared with traditional propagation models with regard to prediction accuracy, complexity, and prediction time. The average ANN prediction results were 1) maximum error: 22 dB; 2) mean error: 0 dB; and 3) standard deviation: 7 dB. A multilayered feedforward network trained using the standard backpropagation algorithm was compared with a neuron model trained using the Levenberg--Marquardt algorithm. It was found that the training time decreases from 150 000 to 10 iterations, while the prediction accuracy is maintained. [ABSTRACT FROM AUTHOR]

In this paper, the validity of Recommendation ITU-R P.1546 in a short-range terrestrial environment is analyzed. Its three versions (P.1546, P.1546-1, and P.1546-2) are compared against simple models and evaluated using measurement results that were obtained by utilizing the pilot signal of a commercial code-division multiple-access mobile telephone network. Measurement results show that P.1546-2, on average, underestimates the field strength by more than 10 dB for typical Australian rural areas. However, it improves the error standard deviation compared to previous versions. The causes of these effects and the suggestions for further development of the Recommendation are discussed and evaluated. [ABSTRACT FROM AUTHOR]