Abstract
In this paper, teletraffic data were collected from Airtel Nigeria Ltd. for a period of 18 months. Frequencies of occurrence of congestion in the network were derived from the teletraffic data using the Nigerian Communications Commission (NCC) benchmark. The dominant causes of congestion in the network were identified from the data and their value of occurrence was seen to be random in nature. A Poisson probability distribution model was therefore implemented for the prediction of congestion in the network. The identified four dominant causes of congestion and their percentage relative weights based on frequency of occurrence were: (i) X1: Faulty System (50.63%); (ii) X2: Faulty Trunk(s) (29.11%); (iii) X3: Power Failure (16.46%) and (iv) X4: Cable Cut (03.80%). MATLAB (M-file Data Acquisition Toolbox) programming environment was used to write a software program in C++ language that simulated the four dominant causes of congestion. Pearson Product Moment Correlation Coefficient formula was used to test the relationship between the measured and simulated congestion. The value r = 0.7487 was the correlation coefficient obtained between the measured and simulated results. This shows that the model is reasonably reliable.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IOSR Journal of Electronics and Communication Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
