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Author: search.filters.author.Phaiboon, SupachaiSubject: search.filters.subject.Path loss prediction

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    Mobile path loss prediction with image segmentation and classification
    (2007-10-01)
    Phaiboon, Supachai
    ;
    Phokharatkul, Pisit
    ;
    Kittithamavongs, Piti
    This paper presents an intelligent radio wave propagation prediction model by using the 2-dimension aerial image which is taken from the actual area. An suburban area is used as examples. The prediction procedure is done in three steps. First, the image segmentation is employed to divide the area image into subgroups by using Maximum Likelihood algorithm. The second step uses the subgroup images from step 1 to determine the parameters for the fuzzy model that we use to classify the propagation areas. The final step is to plot the path loss contour on the image so the cellular cell site can be chosen. The research results show that the proposed segmentation provides an accuracy of 80-90% compared with the actual area. Therefore, cell site selection can be designed on the 2-dimension aerial map with the error less than 8 dB.
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    Microwave line-of-sight path loss prediction on urban street by fuzzy logic model
    (2005-12-01)
    Phaiboon, Supachai
    ;
    Phokharatkul, Pisit
    ;
    Somkuarnpanit, Suripon
    ;
    Boonpiyathud, Sitchai
    This paper proposes a method to model the path loss characteristics on urban streets in the microwave band. We applied the concept of fuzzy logic to predict path losses. The input fuzzy sets were classified into five sets, namely 1) Distance between transmitter and receiver, 2) Frequency, 3) Time of day, 4) Transmitting antenna height and 5) Receiving antenna height. These inputs are then inferenced into output path loss via linguistic rules which were trained by measurement. To check the proposed model, we compared the fuzzy prediction with the same and an another measurement. The results show that the fuzzy logic models provided a better prediction. © 2005 IEEE.