Abstract:
Global System for Mobile Communications (GSM) has brought communication to the doorstep of everyone due to the clarity of the voice communication and the availability of the services anywhere, anytime. Data services were added to the GSM services as a result of the high demand for these services. A lot of services are being offered on the GSM which have led to congestion on the Network. This thesis focuses on how the congestion experienced on the GSM network can be minimized. This work recognises voice and data as the two major classes of services on the GSM network. Each of the classes was later broken into sub-classes of services according to the characteristics of each service. A level of priority was established among the classes so that the most urgent and important service will have access to the channel on the network by preempting the lower priority services when there is congestion and there is no free channel to communicate. The voice and data communications over the GSM network using the different classes of subscribers were analyzed with Markov chain’s model. The steady state probabilities for voice and data services were derived. The blocking and dropping probabilities models for the different services were also developed. The models were implemented based on the blocking and dropping probabilities models to show how the congestion can be minimised for different subscribers based on their priority levels. The impacts of priorities on different subscribers in the network were shown through the graphical display of the results. The work shows that the models used gave significant reduction in congestion when compared to the traditional Erlang-B model normally used to control congestion in GSM.
