Introduction: The world is fast becoming a global village and a necessary tool for this process is communication of which telecommunication is a key player. A major breakthrough is the wireless telephone system which comes in either fixed wireless telephone line or the Global system of mobile communication (GSM). Communication without doubt is a major driver of any economy. Emerging trends in socio-economic growth shows a high premium being placed on information and communication technology (ICT) by homes, organizations and nations. GSM recently has been widely used in Nigeria due to the introduction of SMS, e-mail, multi-media and other use of data through telephone. In view of this wider acceptability and usage of GSM, mobile network providers have experience problems of congestion.

Network Congestion

According to pragyan et al (2012), Network congestion occurs when a link or node is carrying so much data which affect the quality of service. Typical effects include queuing delay and loss of packet or the blocking of new connections. A consequence of these two is that incremental increase in offered load lead either only to small increase in network Throughput, or to an actual reduction in network Throughput. Thus, congestion is caused when the offered load to the network is more than the available resources. In other words, it is a condition that arises when a system or a network experiences a level of offered calling activity or message traffic that exceed its capacity.

Reasons for call congestion

Pragyan (2012) gave various reasons for congestion in mobile network to include the following:

Heavy call Traffic in peak hour Traffic jams become the most problematic situation in any case or area.

Increase of signaling load

This occurs due to calls, bulk message and other applications being used in festive periods and seasons. With the rising use of mobile, the number of signaling required to set up and maintain radio bearers are changing.

Network congestion through bandwidth management

Wrong configuration in mobile network when network is not configured to audit network performance. If this is wrongly done, this can cause congestion.

Overloading of network equipment’sKuboye(2010) added that other factors that could lead to congestion are:

Inadequate radio channels and infrastructure to support the vast number of subscribers on the network.

Redialing of subscribers when they experience blocking.

Too many users on the network.

Use of the old equipment or facilities instead of new ones.

The consequence of this congestion is the fact that it reduces or degrades the quality of service on the part of the GSM operators and also cause dissatisfaction on the part of subscribers, this has raised many issues on the GSM sector, which leads to researchers undertaking studies on the models of minimizing congestion in Nigeria.

Motivation

The explosive growth of GSM services has brought huge revenues to the operators as well as government through tax and license fees (Adegoke et al, 2008).

Similarly, the citizenries, who are the users of these services, have benefited immensely from them as a means of communication. However, the recent development that mars these benefits is the widespread use of GSM network, which has caused congestionin the network, thereby leading to a reduction in the quality of service rendered by GSM operators. This has also led to dissatisfaction on the part of subscribers. Consequently, many researchers have done researches and come up with models of minimizing or controlling congestion in GSM network, yet it is still a cause for concern in communication sector. Moreso, many of these models proposed by researchers tackles mostly congestion involving mainly operators; but little  has been done on developing a model that takes care of the subscribers’ behavior or attitude on the use of GSM network. The researcher therefore seeks to propose a congestion minimization model which will also take into account subscribers’ discipline on the use of GSM network, especially in making calls. The performance of this model will also be evaluated using Erlang B and Erlang C mathematical models.