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Land terrain and environmental contributors’ data are used extensively to predict propagation conditions, to optimally select locations for installing cellular base stations. There have been several models developed to predict the pattern of the losses attributed to propagated signals between two antennas (one at the cellular base station and the other at the mobile phone receiver). This project focuses on the use of the Walfisch-Ikegami model in predicting path loss of GSM signals within the University of Ilorin campus. This is done by comparing some measured data with calculated values.
To determine the location where measurements were taken, the Google earth application was used in conjunction with a GPS device. The measurement of the signals getting to the mobile devices was determined through a process of sending Attention commands (AT commands) through a personal computer’s serial port to mobile devices over a period of time as mentionedearlier.The phones are such that they are compatible with the AT commands instruction set (reason being that not all phones can respond to these commands). An algorithm was developed for the calculation to be done using the theoretical Walfisch-Ikegami model.The measured values were compared with the results of the predictions to determine the suitability of the model for the selected areas within the University of Ilorin campus.
Growth in mobile telecommunications was met with great enthusiasm in Nigeria at its early stages but later resulted in frustration due to diminished quality of service (QoS)(1). In Nigeria and many other countries, mobile communication has been troubled with complications spanning across human and technical issues. However, because good quality of service must have been enjoyed before the time of bad receptions, it becomes important to study the underlying reasons for such drop in signal quality delivered(2). Obstacles and surfaces within the vicinity of the device have an effect on the path characteristics (3). Signal propagation models then, are used largely in network planning, most especially for conducting feasibility studies and during initial deployment of mobile communications systems. They are also very useful for performing analyses on interference as the deployment of these networks proceed.
These models may be broadly categorized into three kinds namely; empirical, deterministic and stochastic. Empirical models are those based on observations and measurements alone. These models are mainly used to predict the path loss, but models that predict rain-fade and multipath have also been proposed. The deterministic models make use of the laws governing electromagnetic wave propagation to determine the received signal power at a particular location. Deterministic models often require a complete 3-D map of the propagation environment (e.g. ray-tracing model). Stochastic models, however, see the environment as a collection of random variables making them the least accurate but requiring very minimal information about the environment and make use much less processing power to generate their predictions (4).
The Walfisch-Ikegami model is an empirical model from J. Walfisch and F. Ikegami and was further developed by the COST 231 project. This is now called the COST- Walfisch-Ikegami Model. The accuracy of this model is limited to its consideration of buildings only in the vertical plane and quite high because in urban environments, multiple diffractions over rooftops are predominant. Wave guiding effects due to several reflections are not considered however, in the model(5).
The study is borne out of the need to understand why hitherto good quality of service enjoyed by end users of GSM telecommunications suddenly deteriorates and in a way as to understand how physical and environmental factors play a part in this phenomenon.
1.3 Problem Statement
The problem addressed here is to compare the results of Walfisch-Ikegami model for pathloss with observed path loss by determiningthe strength of GSM signals at different locations of varied site parameters with respect to base stations’ within the University of Ilorin Campus.
1.4Aim and Objectives
The aim of the studies is to determine the suitability of the Walfisch-Ikegami model in the determination of path-loss and signal strength of mobile communication lines within the University of Ilorin Campus.
The objectives in this project work are to:
i. Measure signal strength and collect data and parameters for the verification of the Walfisch-Ikegami pathloss model.
ii. Develop an algorithm for an application to calculate the Walfisch-Ikegami prediction model
iii. Compare predicted with observed signal strength and consequent path-loss hence, identify the criteria determining the suitability and usefulness of the Walfisch-Ikegami path-loss model.
The work done here, is focused on studying the behavior of propagated signals making use of the Walfisch-Ikegami pathloss model to predict the signal strength of which the Unilorin campus (located in Ilorin, Kwara state and covers about 75,000 hectares north and south) (6)serves as a quasi-laboratory to confirm the theory.The area of interest are characterized by sets of two-storey buildings that have evenly spaced pattern within the University of Ilorin campus.
Ø Determine path-loss parameters;
Ø Take readings of signal strength obtained from mobiles device using a named method;
Ø Compare readings with the theoretical Walfisch-Ikegami path-loss model calculations; and hence make inferences from results
Chapter twopresents essential and related background knowledge including the basics of path loss modelling paying credence to how the GSM works vis-à-vis features and GSM network parameter and workdone on the Walfisch-Ikegami Model. In Chapter three, a more detailed work is presented on the actual methodology employed in the course of the project work.
Chapter four analyses theoretical model calculation with respect to observed values. Comments and judgment are passed on the data obtained from the studies. Finally, chapter five summarizes the project work, avails recommendations and conclusions of the studies.
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