The Study of Quality of Service on a Major Mobile Network Operator in Ghana

Akanbasiam, Joshua Apigagua; Ngala, Daniel Kuyoli

doi:10.9790/2834-1204012125

Cited by 8 publications

(14 citation statements)

References 4 publications

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“…Cellular networks are regulated in Nigeria by the Nigerian Communication Commission (NCC) and their performance is judged using specific telecommunication key performance indicators (KPIs) which are segmented into categories; service integrity, service accessibility, service retainability, service mobility and service reliability [1][2][3][4]. One KPI investigated under service reliability in a cellular network is the received signal quality (RxQual).…”

Section: Introductionmentioning

confidence: 99%

Quality of Service Reliability: A Study of Received Signal Quality in GSM Networks

Iloke

Ekah²,

Oduobuk³

et al. 2022

AJOPACS

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Every radio frequency (RF) design, after its implantation, should be regularly evaluated. The kernel of this article is to evaluate the performance of four GSM networks, taking its received signal quality (RxQual) into consideration. A total of 10501, 10140, 10415 and 10690 RxQual measurements were obtained for MTN, 9mobile, Airtel and Globacom network. These generated data were subjected to statistical analysis in the form of bar charts, quality plots and calculations of measures of central tendency and dispersion. Result shows that 78.43%, 92.18%, 90.68% and 86.93% of the drive test route for MTN, 9mobile, Airtel and Globacom network had good signal quality and met with the Nigerian telecommunication regulatory benchmark of at least 4dB for RxQual. It is therefore deduced that in terms of RxQual, 9mobile was the best GSM network, followed by Airtel network, Globacom network and then MTN network. The result provided in this article will help mobile network operators to improve signal quality, ensure improved network coverage and increase network capacity in the future.

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Section: Introductionmentioning

confidence: 99%

Quality of Service Reliability: A Study of Received Signal Quality in GSM Networks

Iloke

Ekah²,

Oduobuk³

et al. 2022

AJOPACS

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“…Cellular network subscribers' resort to purchasing Subscribers Identity Module (SIM) cards of all existing cellular network operators, as one cannot predict when one will obtain good QoS from any of the telecommunication operators. To judge mobile network QoS, regulatory authorities and telecommunication operators, use Key Performance Indicators (KPIs), which hinges on the end user's perspective [1]. These KPIs are classified into service reliability [2], service integrity [3], service accessibility, service mobility and service retainability [4].…”

Section: Introductionmentioning

confidence: 99%

Tropospheric influence on dropped calls in mobile networks

Ekah¹,

Iloke²,

Ekah³

2022

Global J. Eng. Tech. Adv.

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It is common knowledge that tropospheric variables affect signals, thereby distorting coverage. Since the major factor affecting dropped calls is coverage and the penetration depth of the signal strength transmitted by a wireless system determines its coverage, therefore, there is a tendency for tropospheric variables to affect dropped calls. This research investigates the effects of relative humidity, wind speed, rainfall and temperature on dropped calls for four mobile networks (MTN, Airtel, Globacom and 9mobile) in Cross River State, Nigeria. Six years data of weather variables collected from the Nigerian Meteorological Agency (NiMet), Cross River State and six years Drop Call Rate (DCR) data obtained from the telecommunications regulatory body, Nigerian Communication Commission (NCC), was used for this study, both spanning from January 2015 to December 2020. From the collected data, graphs were plotted and, in each case, the DCR of the mobile networks were the dependent variables while the tropospheric variables were the independent variables. Also, regression models were obtained to forecast the DCR of each network, provided the tropospheric variable at each given period is known. Finally, the variables were correlated to give a picture of how each tropospheric variable related to the DCR of the mobile networks. For MTN and 9mobile networks, a low positive correlation was obtained for rainfall and relative humidity, a highly positive correlation was obtained for wind speed while a lowly negative correlation was obtained for temperature. For Airtel network, a moderately negative correlation exists between DCR and relative humidity/temperature while a low positive relationship existed for rainfall. However, a low negative relationship was observed for wind speed. For Globacom network, a moderately negative and a moderately positive relationship was obtained for rainfall and relative humidity respectively while a highly positive and a lowly negative correlation was obtained for temperature/wind speed against DCR. This result will be very useful to the meteorologist, mobile network planners and the network operators.

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“…In addition to the Markov chain, cluster-based approaches, decision trees, and artificial neural networks were employed in [10][11][12] to estimate a network accessibility-related parameters. These and papers such as [13][14][15] addressed related performance measures for various generations of cellular mobile systems. This paper's primary goal is to forecast mobile network accessibility and retainability status using real-time data gathered from the NMS of a major network operator in the capital city of Addis Ababa, Ethiopia.…”

Section: Introductionmentioning

confidence: 99%

Hybrid K-Mean Clustering and Markov Chain for Mobile Network Accessibility and Retainability Prediction

Omer

Yemer²,

Woldegebreal

2022

The 8th International Conference on Time Series and Forecasting

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The Study of Quality of Service on a Major Mobile Network Operator in Ghana

Abstract: Quality of service is an important key performance indicator (KPI) that is used to determine

Cited by 8 publications

References 4 publications

Quality of Service Reliability: A Study of Received Signal Quality in GSM Networks

Quality of Service Reliability: A Study of Received Signal Quality in GSM Networks

Tropospheric influence on dropped calls in mobile networks

Hybrid K-Mean Clustering and Markov Chain for Mobile Network Accessibility and Retainability Prediction

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