Evaluation and optimisation of GSM network in Jenien City, Palestine

Abstract

This paper presents a case study about the evaluation and optimisation of GSM network in Jenien City, Palestine. Two approaches are used to evaluate the network performance, namely: key performance indicators (KPIs) and drive test. The initial evaluation of the network showed that about 0.76% of the initiated connections are dropped. In addition, about 7.76% of the collected samples from the drive test lie in level 4 which is the worst level in terms of signal quality and signal strength. Moreover, only 65.5% of the collected samples lie in level 1 which is the best level in terms of signal quality and strength. A new traffic channel (TCH) and broadcast control channel (BCCH) frequency plans are proposed to decrease TCH drop rate, reduce interference level and boost signal quality. The proposed plans are implemented into the network. Two kinds of optimisation procedures are adopted. The first one is manual optimisation while the second one is by using specific optimisation tools. According to the comparative study, we carried-out between the performance of the network before and after optimisation, the average TCH drop rate is reduced from 0.76% to 0.62%. In addition, the percentage of samples in level 1 is increased from 65.5% to 76.8% while the percentage of samples in level 4 is decreased from 7.76% to 5.16%. His research interests are in the field of signal processing for wireless communications with focus on mobile fading channel modelling and estimation, multicarrier techniques, cellular network planning and optimisation. He is a member of the IEEE Communications Society.

Chaotic assessment of the key performance indicators for a GSM Network congestion in an election period in Nigeria

“…Therefore, it is wrong to generalize the QoS of a network for a large number of cells covering an entire state or country. Network operation status can be understood with regard to the traffic volume on the network, as well as providing statistical data to understand network performance [13]. KPIs are commonly used to characterize the performance of a network operator for a sizeable land mass such as community, village, city, local government area e.t.c where only one Base station controls the activity of a number of BTSs (cells).…”

“…For the fact that primary Election Day usually involve massive political party members from all the 36 states of the federation, hence a heavy traffic is ascertained within the FCT and the environs. To this effect, the steps involved in optimization of traffic or congestion of network consist of two parts, namely: neighbour relation plan and capacityinterference analysis [13]. The capacity and interference analysis involve determination of peak carried traffic for each cell of the base stations.…”

“…Performance and quality of service (QoS) evaluation are the most important to mobile operators as the revenue generation and customer satisfaction are directly related to network performance and quality. Mkheimer and Jamoos (2012), used two approaches to evaluate the network performance namely: key performance indicators (KPIs) and drive test. They suggested that the average TCH of about 0.76% in November 2010 to 0.62% in October 2011 are dropped.…”

“…In addition, about 7.76% of the collected samples from the drive test lie in level 4 which is the worst level in terms of signal quality and signal strength. Moreover, only 65.5% of the collected samples lie in level 1 which is the best level in terms of signal quality and strength [13]. In Nigeria, the telecommunication industry is rapidly growing and many operators and their operations put forth different services, but in the diverse services provided, most of the subscribers do not receive satisfaction due to the poor nature of services available on these networks.…”

Consumer Behavior Towards Introducing 3g Mobile in Palestine: The Case of Bethlehem Governorate

“…In addition, it was proven that mobile telecommunication has led to increase the competition in local market among providers, due to users' demand for transmission speed and application services (Mardikyan, 2012;Gandal et al, 2003). Mobile telecommunication technologies have evolved in sequential generations (Jamoos et al, 2019;Mkheimer and Jamoos, 2012). The first generation was launched in the 1980's, followed by the introduction of second generation in 1990's.…”