Vol. 95

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Path Loss Prediction for Low-Rise Buildings with Image Classification on 2-D Aerial Photographs

By Supachai Phaiboon and Pisit Phokharatkul
Progress In Electromagnetics Research, Vol. 95, 135-152, 2009


This paper presents a radio wave propagation prediction method for low-rise buildings using 2-D aerial images taken from actual areas. The prediction procedure was done in three steps. Firstly, the images were classified in order to identify the objects by Color Temperature Properties with Maximum Likelihood Algorithm (CTP_MLA). The objects in the images consist of buildings, trees, roads, water and plain. These objects influence wave propagation highly. The MLA classification is a common supervised image segmentation technique in remote sensing domain. However it still needs human editing in case of classification errors. Secondly, the appropriate path loss models were selected to predict path loss. The original Xia path loss model was modified to include the effects of airy buildings and vegetation around the buildings. Finally, preliminary tests provide a better solution compared with measured path losses with the root mean square error (RMSE) and maximum relative error (MRE) of 3.47 and 0.16, respectively. Therefore, the positions for micro-cell base stations could be designed on a 2-D aerial map.


Supachai Phaiboon and Pisit Phokharatkul, "Path Loss Prediction for Low-Rise Buildings with Image Classification on 2-D Aerial Photographs," Progress In Electromagnetics Research, Vol. 95, 135-152, 2009.


    1. Xia, H. H., "A simplified model for prediction path loss in urban and suburban environments," IEEE Trans. Veh. Technol., Vol. 46, No. 4, 1040-1046, Nov. 1997.

    2. Har, D., H. H. Xia, and H. L. Bertoni, "Path-loss prediction model for microcells," IEEE Trans. Veh. Technol., Vol. 48, No. 5, 1453-1462, Sep. 1999.

    3. Walfisch, J. and H. L. Bertoni, "A theoretical model of UHF propagation in urban environments," IEEE Trans. Ant. Prop., Vol. 36, No. 12, 1788-1796, 1988.

    4. Ikegami, F., S. Yoshida, T. Takeuchi, and M. Umehira, "Propagation factors controlling mean field strength on urban streets ," IEEE Trans. Ant. Prop., Vol. 32, 822-829, 1984.

    5. Oda, Y., K. Tsunekawa, and M. Hata, "Advanced LOS path loss model in microwave mobile communications," IEEE Trans. Veh. Technol., Vol. 49, 2121-2125, Nov. 2000.

    6. Jiang, L. and S. Y. Tan, "A simple analytical path loss model for urban cellular communication systems," Journal of Electromagnetic Waves and Applications, Vol. 18, No. 8, 1017-1032, 2004.

    7. Masui, H., T. Kobayashi, and M. Akaike, "Microwave path loss modeling in urban line-of-sight. Environments," IEEE J. Select. Areas Commun., Vol. 20, No. 6, 1151-1155, Aug. 2002.

    8. Durgin, G., T. S. Rappaport, and H. Xu, "Measurements and models for radio path loss and penetration loss in and around homes and trees at 5.85 GHz," IEEE Trans. on Commun., Vol. 46, No. 11, 1484-1485, Nov. 1998.

    9. Karlsson, A., R. E. Schuh, C. Bergljung, P. Karlsson, and N. Lowendahl, "The influence of trees on radio channels at frequencies of 3 and 5 GHz," VTC 2001 Fall. IEEE VTS 54th, Vol. 4, 2008-2012, Oct. 2001.

    10. Torrico, S. A., H. L. Bertoni, and R. H. Lang, "Modeling tree effects on path loss in a residential environment," IEEE Trans. Ant. Prop., Vol. 46, No. 6, 872-880, Jun. 1998.

    11. Torrico, S. A. and R. H. Lang, "A simplified analytical model to predict the specific attenuation of a tree canopy," IEEE Trans. Veh. Technol., Vol. 56, No. 2, 696-703, Mar. 2007.

    12. Meng, Y. S., Y. H. Lee, and B. C. Ng, "Measurement and characterization of a tropical foliage channel in VHF and UHF bands," 10th IEEE Singapore Inter. Conf. (ICCS 2006), 1-5, Oct. 2006.

    13. Kurner, T. and A. Meier, "Prediction of outdoor-to-indoor coverage in urban areas at 1.8 GHz," IEEE J. on Selected Areas in Commun., Vol. 20, No. 3, 496-506, April. 2002.

    14. Teeranachaideekul, N., P. Phokharatkul, S. Ongwattanakul, B. Emaruchi, and S. Phaiboon, "A maximum likelihood method for the classification of aerial photographs," Proc. JCSSE2007, 254-259, May 2-4, 2007.

    15. Perkins, T. C., "Remote sensing image classification and fusion for terrain reconstruction,", B.S.E.E., University of Louisville, 1999.

    16. Lee, W. C. Y., "Estimate of local average power of a mobile radio signal," IEEE Trans. Veh. Technol., Vol. 34, No. 1, 22-27, Feb. 1985.