Abstract—All GSM operators use Key Performance Indicators (original) (raw)
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IMPROVEMENT OF KEY PERFORMANCE INDICATORS AND QoS EVALUATION IN OPERATIONAL GSM NETWORK
All GSM operators use Key Performance Indicators (KPIs) to judge their network performance and evaluate the Quality of Service (QoS) regarding end user perspective. All the events being occurred over air interface are triggering different counters in the Base Station Controller(BSC). The KPIs are derived with the help of these counters using different formulations. In this paper, a well established real GSM radio frequency (RF) network performance evaluation is presented on the basis of several KPIs. It has been focused to analyze the live network performance; irrespective of the discussions and modeling available in the literature. Different issues, findings, trials and improvements have been summarized and observations/recommendations have been listed to correlate the practical aspects of RF optimization, which affect the performance, and QoS of an operational cellular network.
A Survey of Key Performance Indicators for Generic Cellular Networks
International Journal for Modern Trends in Science and Technology, 2019
The increasing offer of advanced services in cellular networks forces operators to provide stringent quality of service (QoS) guarantees. The contentment level of different customers depends on different QoS levels based on key performance indicators (KPIs). Monitoring QoS of any telecommunications network requires continuous processes that estimate values of the KPIs in real-time that determine the quality of service rendered to the subscribers. System coverage, trunking efficiency, spectrum efficiency, carrier-to-interference ratio (C/I), drop-call probability and call blocking probability are some of the important KPIs used to estimate the performance of cellular networks. The system coverage in an area is dependent on the area covered by the signal. Trunking efficiency relates to the number of customers per channel to the number of channels per cell for a particular grade of service. Spectrum efficiency is a measure of how efficiently space, frequency and time are used. The C/I factor arises because wireless users communicate over the air and there is significant interference between them. Call dropping refers to the event described by the termination of calls in progress before either involved party intentionally ends the call. Blocking occurs when a base station has no free channel to allocate to a mobile user. In this paper, the KPIs' concepts are reviewed and presented in a more coherent and unified manner than have been previously done including the illustration of the concepts in an experimental context for an operative cellular network.
The delivering of both good quality of service (QoS) and Grade of Service (GoS) in any competitive mobile communication environment is a major factor to reducing subscribers’ churn rate. Therefore, it is important for wireless mobile network operators to ensure stability and efficiency by delivering a consistent, reliable and high-quality end user (subscriber) satisfaction. This can only be achieve by conducting a regular network performance monitoring and optimisation as it directly impacts the quality of the offered services and hence user satisfaction. In this paper, we present the results of network performance evaluation and optimisation of a GSM network on cell cluster-basis, in Asaba region, South East Nigeria. We employ a combination of essential key performance indicators such as dropped call rate, call setup success rate and outage call rate to examine overall QoS and GoS performance of the GSM network. Our results after network optimisation showed significant performance ...
Performance Assessment of the Quality of Service of a GSM Network in Kaduna State Nigeria
1st International Conference on Engineering and Applied Natural Sciences, 2022
As the number of mobile subscribers exponentially increase, one of the key goals of Mobile Network Operators (MNOs) nowadays is to keep its subscribers satisfied with good Quality of Service (QoS) in order to increase the Quality of Experience (QoE) for the end user. In order to achieve the best performance, MNOs need to be continuously monitored in order to for them to optimize their network continuously. On this premise, this research work utilizes the statistical data of call traffic from the Base Station Controller (BSC_KDBH14) in Kaduna State, which takes into account the KPI obtained from 48 BTSs. The evaluation of the KPI measurements taken from the MNO showed that 2% of the Call Setup Success Rate (CSSR) failed to be within Nigerian Communications Commission (NCC's) benchmark (≥98%), and as a result, 2% of the dataset generated for the Call Setup Failure Rate (CSFR) failed to be within NCC's benchmark (≤2%). The Call Completion Rate (CCR) had all the datasets within NCCs benchmark (≥96%), but unfortunately, the Call Drop Rate had 15% of its BTSs Key Performance Indicators (KPIs) outside the NCC's benchmark (≤2%). To this end, this work highlighted the BTSs that needed close attention in order to optimize the network.
QUALITY OF SERVICE PARAMETERS EVALUATION IN CELLULAR NETWORKS
IJESRT INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY, 2020
Quality of Service refers to the evaluation of the overall performance of a service, such as a telephony or computer network particularly the performance seen by the users of the network. QoS is mostly observed from the subscriber's side. This includes aspects such as the mobile signal strength available to users and other call avaibility measurements. QoS is normally calculated during signal transmission called KPIs that is connected to the subscriber's happiness whilst using mobile services. QoS parameters are monitored through RF analysis by Drive Test. Some of these QoS parameters related to call and data are discussed in this paper. These parameters directly or indirectly represents the quality of service provided by the network operators in context of Nepal. This analysis of parameters has helped us identify problems like call performance, slow servicing, least ease of use in a service test area for different service providers in the country.
Performance Evaluation Of Selected Gsm Networks In Nigeria
Science and Technology Publishing (SCI & TECH), 2023
In this paper, performance evaluation of selected GSM networks in Nigeria is presented. The performance evaluation of the networks is based on requisite datasets pertaining to those networks and some key performance indicators (KPIs) which are applicable for Quality of Service (QoS) assessment of GSM networks. Specifically, seven (7) KPI parameters were computed, namely; Call Setup Success Rate (CSSR), Call Drop Rate (CDR), Standalone Dedicated Control Channel (SDCCH) congestion rate, Traffic Control Channel (TCC) congestion rate, Call Block Rate (CBR), Handover Success Rate (HOSR) and Handover Failure Rate (HOFR). The results show that from June, 2020 to May, 2022, MTN has the highest CSSR value of 99.73 % followed by Airtel with 99.41% then 9mobile with 99.19 % and Globacom 99.06 %. Also, MTN has lowest Call Drop Rate (CDR) value of 0.28, followed by Globacom with CDR value of 0.32, Airtel had CDR value of 0.35 and 9mobile had CDR value of 0.43. Again, only the network of MTN and Airtel have Standalone Dedicated Control Channel (SDCCH) < 0.2% as mandated by the Nigerian Communications Commission (NCC) while Globacom had SDCCH > 0.2% in October and 9mobile had SDCCH > 0.2% in about 13 month. In addition, Airtel, 9mobile, Globacom and MTN satisfied the NCC requirement of Traffic Control Channel (TCCH) ≤ 2%. Similarly, only Airtel and MTN have call blocked rate (CBR) ≤ 2.0% while Globacom exceeded 2% in October 2021 and 9mobile exceeded 2% in about 6months. Also, only MTN network was able to meet the Handover Success Rate (HOSR) ≥ 98 % requirement in all the months, while Airtel had HOSR < 98% for about 5 months, Globacom had HOSR < 98% for all the months and 9mobile had HOSR < 98% for about 17 months. In all, among the four GSM networks considered in the study, the best performance was recorded for the MTN network.
Performance Evaluation and Measurements of 3G Mobile Communication Networks: A Case Study
World Journal of Engineering and Technology, 2015
Communication networks have undergone rapid developments in the past few decades in many Sub-Saharan African countries. The increasing number of subscribers and demand for greater variety of services in these countries make it difficult for network operators to provide the service varieties subscribers want while maintaining acceptable levels of quality of service. This paper analyzes the radio network of cellular networks in terms of traffic distribution over the existing number of communication channels using MATLAB/Simulink. A scale-free user network, which takes into account user behavior in a realistic physical network, has been used to model a more realistic cause for call blockings in a typical cellular network deployment under a Sub-Saharan environment. Peak recorded traffic distribution was observed to have overwhelmed the existing number of channels provided by the network operators for some cells eventually leading to increase in call drop rates. This high call blocking probability was attributed to poor network monitoring by the network operators to match the ever changing traffic intensities.
A comparative assessment of GSM and UMTS Networks
World Journal Of Advanced Research and Reviews, 2022
It is common knowledge that the transition of mobile networks from one generation to another is basically for the improvement in the network's Quality of Service (QoS). Bearing this in mind, we will assumme that the Universal Mobile Telecommunication System (UMTS) will outperform the Global System for Mobile Communication (GSM), hence, the motivation to conduct this study in Calabar, Nigeria, for four mobile networks; MTN, Airtel, Globacom and 9mobile. With the aid of a TEMS investigation software installed in a laptop, a measurement campaign was carried out and log files collected, with focus on Call Setup Success Rate (CSSR), Dropped Call Rate (DCR), Handover Success Rate (HOSR), Call Setup Time (CST), network coverage and network quality. The collected data was analyzed with the aid of a TEMS discovery software. The analyzed data for each Key Performance Indicator (KPI) was compared with the minimum benchmark of the telecommunications regulatory body, the Nigerian Communication Commission (NCC). Result reveal that there was no outright improvement in the QoS and there was fluctuation in the QoS provided by the network operators. We therefore conclude that the network operators, either did not make accurate planning before installing their base stations or do not optimize their networks frequently and this led to poor QoS in most cases.