Traffic Analysis of Global System for Mobile Communication Networks in Port Harcourt

Abstract

Call signal quality is largely affected by traffic in networks leading to dropped calls or call waiting for available servers or voice channels. Several authors have illustrated how factors such as physical obstructions, network range and distances between devices, wireless network interference and signal sharing affects network signal quality. This dissertation analyses traffic for Global Systems of Mobile Communications in some selected location in Port-Harcourt. This was achieved by conducting field test of GSM service networks from June 2020 to December 2020 in five selected locations of Port-Harcourt using dongle measurement tools. The Data Measured was further analyzed and categorized into tables. The Data was then analyzed by using the Erlang C Model to determine the probability that a call will wait based on existing traffic conditions. The results showed that at the beginning of each day, after midnight, the traffic load is low with a value of 1Erl, increasing as the day progresses with a calculated overall maximum value of 92Erl and dropping back again in the evening as the day winds up. The result also showed a positive relationship between traffic load and the probability that a call waits, and a negative relationship between the probability that a call waits and the service level or the percentage of calls answered immediately. The Probability that a call waits was calculated to have a minimum value of 33.19% and a maximum value of 87.87%. The service level was calculated to have a minimum value of 25.62% and an overall maximum of 71.83%. The results as also points to the need for network optimization and upgrade so as to increase the service level and reduce the probability that a call waits. Finally, the work was a success as the field test and analysis was successful carried out. The results showed that service level was below standard threshold of 80% and to improve this, the number of voice channels needs to be increased to compensate for the traffic intensity and to reduce the call waiting probability. At the end of the analysis, we can visualize the network from a customer’s perspective initiating a call at an instant in time and from the point of one viewing the network over the total range of time. The information gathered and computed will prove to be beneficial to the network provider as a means of estimating network signal quality and teletraffic parameters.