Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: A Practical Radiosity Method for Predicting Transmission Loss in Urban Environments | EURASIP Journal on Wireless Communications and Networking 2004 2 357-364 2004 Hindawi Publishing Corporation A Practical Radiosity Method for Predicting Transmission Loss in Urban Environments Ming Liang Research Center of Information Electric Power Techniques North China Electric Power University Zhuxinzhuang Beijing 102206 China Email lm@ Qin Liu Institute of Electrotechnical Fundament and Theory Vienna University of Technology Gusshausstrasse 25 351 1040 Vienna Austria Email Received 15 January 2004 Revised 7 July 2004 Recommended for Publication by Arumugam Nallanathan The ability to predict transmission loss or field strength distribution is crucial for determining coverage in planning personal communication systems. This paper presents a practical method to accurately predict entire average transmission loss distribution in complicated urban environments. The method uses a 3D propagation model based on radiosity and a simplified city information database including surfaces of roads and building groups. Narrowband validation measurements with line-of-sight LOS and non-line-of-sight NLOS cases at 1800 MHz give excellent agreement in urban environments. Keywords and phrases propagation model power coverage prediction tool transmission loss urban environment radiosity. 1. INTRODUCTION The increasing demand for commercial personal communication services PCS system and the consequent reduction of cell size has led to the need for efficient prediction tools and coverage predictions especially in complicated urban microcellular environments where conventional empirical models fail. These models do not take into account the physics of the problem and in spite of their low computation time they have a restricted area of application. The need for more accurate models has stimulated the development of theoretical methods considering the structure of real buildings and the influence of rough surfaces. Except for the empirical models for .
