An Open-Source Radio Coverage Prediction Tool ANDREJ HROVAT * , IGOR OZIMEK * , ANDREJ VILHAR * , TINE CELCER * , IZTOK SAJE + and TOMAŽ JAVORNIK * * Department of Communication Systems, * Jozef Stefan Institute, + Mobitel, d.d. * Jamova cesta 39, SI-1000 Ljubljana, + Vilharjeva 23, SI-1000 Ljubljana *+ SLOVENIA andrej.hrovat@ijs.si http://www-e6.ijs.si Abstract: - The cellular concept applied in mobile communication systems enables significant increase of overall system capacity, but requires careful radio network planning and dimensioning. Wireless and mobile network operators typically rely on various commercial radio network planning and dimensioning tools, which incorporate different radio signal propagation models. In this paper we present the use of open-source Geographical Resources Analysis Support System (GRASS) for the calculation of radio signal coverage. We developed GRASS modules for radio coverage prediction for a number of different radio channel models, with antenna radiation patterns given in the standard MSI format. The results are stored in a data base (e.g. MySQL, PostgreSQL) for further processing and in a simplified form as a bit-map file for displaying in GRASS. The accuracy of prediction was confirmed by comparison with results obtained by a dedicated professional prediction tool as well as with measurement results. Key-Words: network planning tool, open-source, GRASS GIS, path loss, raster, clutter, radio signal coverage 1 Introduction Emerging user applications call for increased bandwidth of communication systems. Consequently, higher frequencies are used in wireless systems while the size of radio cells is becoming smaller. The cellular concept enables lower transmission power and frequency reuse in cells which are far enough from each other. However, due to the increased complexity, a wireless system has to be planned carefully. Cellular system planning involves determining the number and the locations of base stations, their hardware and software, frequency and code planning. One of the aims is to efficiently use the allocated frequency band and to assure high radio coverage. For the calculation of radio coverage, various mathematical radio propagation models are being used [1, 2, 3, 4]. They can be divided into three groups: (i) statistical models, (ii) deterministic (or theoretical) models and (iii) combinatorial models. Various commercial programming tools are available for radio coverage calculation. The first representative tools were designed for mobile operators and national regulators, e.g. Planet [5], decibel Planner [5], Vulcano [6] and CS telecom nG [7]. Accordingly, their price was high while their accessibility and spread of usage were low. Later on, some cheaper yet functionally limited tools have appeared on the market, e.g. WinProp [8], RPS [9] and TAP [10]. These tools do not comprise modules for radio network optimization and are intended for specific tasks such as WLAN network planning, calculation of radio coverage inside buildings, design of radio-relay links, etc. Those mentioned tools do not allow users to add new propagation prediction modules or to adjust the existing ones. From the scientific point of view their usage is therefore very limited. These limitations can be avoided by using an open-source platform which can be upgraded by an arbitrary propagation model. As the terrain relief significantly influences radio wave propagation, a logical choice is to use an open- source geographical information system (GIS). These systems also include built-in functions for displaying results on geographical maps, importing different raster and vector GIS formats, converting geographical coordinates, etc. Geographical Resources Analysis Support System (GRASS) is one of the most wide-spread open source GIS systems, which has been successfully used for many years and has a wide spectrum of already implemented modules [11]. In the paper, the following section presents the GRASS system with its main structure, characteristics and its applicability in the field of radio communications. Next, a description of the radio coverage prediction software developed in GRASS is presented. The essential building blocks calculating path loss, sectorisation, radio coverage, and converting and evaluating input/output data are LATEST TRENDS on COMMUNICATIONS ISSN: 1792-4243 135 ISBN: 978-960-474-200-4