Mobile Operators Research Articles

VALIDATION OF KEY PERFORMANCE INDICATORS OF MOBILE TELECOMMUNICATION OPERATORS USING ENSEMBLE MODELS AND ARTIFICIAL NEURAL NETWORKS WITH NIGERIAN COMMUNICATION COMMISSION’S THRESHOLDS

This paper presents the comparative studies among the predictive models used for the validation of the key parameter indicators of mobile network operators with the Nigerian Communication Commission’s threshold. Four Key Performance Indicators were predicted using artificial neural networks and ensemble models which include bagging and LSBoost models. The Key Performance Indicators and weather parameters for six locations in Southwestern Nigeria were employed. MATLAB R2020a was employed to develop the three models. Microsoft Excel was used in the analysis of the dataset. The bagging model gave the best average compliance of 94% and 100% for CSSR and TCH Congestion Rate respectively while the ANN model yielded the best average compliance of 76.7% and 85.2% for DCR and SDCCH Congestion Rate respectively..

A Subsidization Scheme for Maximizing Social Welfare in Mobile Communications Markets

In contemporary mobile communications markets, various agents or players interact to pursue welfare. Regulatory policies enacted by governments in certain markets aim to maximize social welfare. However, some countries, both least developed and developing, often adopt successful models from developed nations without local market validation. Therefore, network economics serves as a pertinent framework for analyzing such policies. This paper introduces a novel scheme based on constrained optimization problems, where the constraints represent multilevel economic game equilibria within a system model involving three agents: the central planner, the mobile network operator, and the mobile data users. These agents strategically optimize their payoff functions by considering benefit factors and decision variables such as the subsidization factor, pricing, and data consumption. To this end, a three-stage dynamic game is proposed to model the players’ interactions, employing the backward induction method to ascertain the subgame perfect equilibrium from the Nash equilibrium. A case study is presented, demonstrating a 31.16% increase in social welfare between scenarios involving no adoption of the subsidization factor and its adoption at the optimal value when the central planner enacts it to other players in the game, even if they do not necessarily attain maximum payoff values. In countries aligning with this proposed model, social welfare is maximized through a subsidization scheme.

When spatial interpolation matters: Seeking an appropriate data transformation from the mobile network for population estimates

Analyses utilizing mobile positioning data rarely provide an exact method of data transformation to target spatial units. A common reason is likely the fact that researchers have already worked with spatially aggregated data prepared by the mobile operator or processing company. The article demonstrates the critical importance of employing an appropriate method to transform data from the mobile network into target spatial units, ensuring the precision and accuracy of the results. By evaluating ten different methods of data transformation from the mobile network topology to a population grid of 1 × 1 km, the optimal transformation has been sought. The most promising results were obtained through the methods using auxiliary information. While a dasymetric transformation utilizing building volume as the ancillary layer proved to be the most accurate, the utilization of free data from the Global Human Settlement Layer project also exhibits encouraging potential. Frequently used interpolation methods such as point-to-polygon (the user's location is considered to be the same as the base transceiver station's position.) or areal weighting are in fact the least appropriate methods of data transformation at a subregional level.

STABILITY ANALYSIS OF CELLULAR OPERATING SYSTEM MARKET SHARE IN INDONESIA WITH THE COMPETITIVE LOTKA-VOLTERRA MODEL

The current increase in smartphone users has caused various mobile device operating system companies to compete with each other to create a mobile device operating system that is suitable and acceptable to the public. Competition among mobile operating system market shares can be analyzed using the Lotka-Volterra model. This study aims to reconstruct the Lotka-Volterra model for the cellular operating system market share in Indonesia. In addition, a stability analysis was carried out, which aims to determine the stability of the competitive model for the market share of the operating system in Indonesia. The results of the study show that a competitive Lotka-Volterra model can be built on the Android and iOS operating system market share in Indonesia. In this model, there are four equilibrium points, one of which is unstable, and the other three equilibrium points are conditionally stable.

Network Type Recognition Using Machine Learning Techniques

The telecom industry is going through a massive digital transformation with the adoption of ML, AI, feedback-based automation and advanced analytics to handle the next generation of applications and services. AI concepts are not new; the algorithms used by Machine Learning and Deep Learning are being currently implemented in various industries and technology verticals. With growing data and an immense volume of information over 5G, the ability to predict data proactively, swiftly and with accuracy, is critically important. Data-driven decision-making will be vital in future communication networks due to the traffic explosion and Artificial Intelligence (AI) will accelerate the 5G network performance. Mobile operators are looking for a programmable solution that will allow them to accommodate multiple independent tenants on the same physical infrastructure and 5G networks allow for end-to-end network resource allocation using the concept of Network Slicing (NS). Network Slicing will play a vital role in enabling a multitude of 5G applications, use cases, and services. Network slicing functions will provide end-to-end isolation between slices with an ability to customize each slice based on the service demands (bandwidth, coverage, security, latency, reliability, etc). Index Terms: Supervised Learning, Feature Engineering, Python, Network Slicing, Telecom, Classification Problems, EDA – Exploratory Data Analysis.

Preparation of Low-Temperature Solution-Processed High-κ Gate Dielectrics Using Organic-Inorganic TiO2 Hybrid Nanoparticles.

Organic-inorganic hybrid dielectric nanomaterials are vital for OTFT applications due to their unique combination of organic dielectric and inorganic properties. Despite the challenges in preparing stable titania (TiO2) nanoparticles, we successfully synthesized colloidally stable organic-inorganic (O-I) TiO2 hybrid nanoparticles using an amphiphilic polymer as a stabilizer through a low-temperature sol-gel process. The resulting O-I TiO2 hybrid sols exhibited long-term stability and formed a high-quality dielectric layer with a high dielectric constant (κ) and minimal leakage current density. We also addressed the effect of the ethylene oxide chain within the hydrophilic segment of the amphiphilic polymer on the dielectric properties of the coating film derived from O-I TiO2 hybrid sols. Using the O-I TiO2 hybrid dielectric layer with excellent insulating properties enhanced the electrical performance of the gate dielectrics, including superior field-effect mobility and stable operation in OTFT devices. We believe that this study provides a reliable method for the preparation of O-I hybrid TiO2 dielectric materials designed to enhance the operational stability and electrical performance of OTFTs.

Impact of 5G on Internet of Things and its Challenges

In this era of rapid technological growth, the Internet of Things (IOT) refers to a system of interrelated, internet-connected objects that are able to collect and transfer data over a wireless network without human intervention. We see the IOT as billions of smart, connected things (a sort of ―universal global neural network in the cloud) that will encompass every aspect of our lives, and its foundation is the intelligence that embedded processing provides. The IOT is comprised of smart machines interacting and communicating with other machines, objects, environments and infrastructures. As a result, huge volumes of data are being generated, and that data is being processed into useful actions that can ―command and control things to make our lives much easier and safer—and to reduce our impact on the environment. The creativity of this new era is boundless, with amazing potential to improve our lives. The following thesis is an extensive reference to the possibilities, utility, applications and the evolution of the Internet of Things. The rollout of commercial 5G cellular networks has commenced, marking a significant milestone in the adoption of 5G and the Internet of Things (IoT). This adoption is propelled by various factors, such as rising consumer and enterprise demands, coupled with the availability of cost-effective devices. Notably, substantial investments by operators in 5G technology, spectrum allocation, and infrastructure development, alongside the establishment of global standards, are key drivers fuelling growth and generating heightened market interest in the IoT. The substantial investments made by operators in 5G technology, spectrum allocation, and infrastructure, coupled with the adoption of global standards, play a pivotal role in stimulating growth and generating heightened market interest in the Internet of Things (IoT). The ongoing evolution of 5G mobile cellular networks, derived from existing 4G frameworks, underscores their adaptability to diverse use cases, both present and future-oriented. With a forward- looking approach, 5G infrastructure is poised to address current demands like smart energy applications while proactively accommodating forthcoming innovations such as autonomous vehicles. In navigating this technological transition, mobile operators face the challenge of ensuring that their networks remain adept at supporting a spectrum of present and future use cases. Strategic investment management is imperative for operators to seamlessly transition their networks to 5G while upholding the continuity of service for their customers Key Words: Scalability, safety, security, rapid growth, interoperability, devices, interconnections, 5G with Internet of things, healthcare, smart city

ANALYSIS FF FACTORS AFFECTING PROFIT GROWTH OF CELLULAR TELECOMMNUNICATION OPERATOR COMPANIES ON THE INDONESIAN STOCK EXCHANGE

A comparison will be made between the Current Ratio (CR), Net Profit Margin (NPM), and Return on Assets (ROA) in connection to the increase of profits in infrastructure-related cellular telecommunications operator enterprises (XL, Telkomsel, Smartfren, and Indosat) between the years 2016 and 2022. A number of tests are included in the research protocol. These tests are as follows: the Chi-Square test (CoW) for selecting a common effect model, the likelihood ratio test (LM) for selecting a random effect model, the Breusch-Pagan test for detecting heteroscedasticity, the Multicollinearity test for identifying multicollinearity, the regression test with the common effect model (CEM) for determining the effect of independent variables on earnings growth, and the coefficient of determination test for determining the ability of CR, NPM, and ROA to explain earnings growth variability. The data indicates that the activities of mobile telecom operator enterprises operating within the infrastructure sector had a positive influence on the increase of profits derived from CR, NPM, and ROA. In accordance with the results of the LM test, the Common Effect Model is more appropriate than the Random Effect Model. In addition, the Breusch-Pagan test shows the absence of heteroscedasticity in the model. Multicol test also confirmed the absence of multicollinearity problem in the analysis. This study provides important insights into the factors that influence earnings growth in the mobile telecommunications industry in the infrastructure sector. These results can assist company management in designing more effective financial strategies to achieve better earnings growth.

Sensitivity Options of 5G Non-Standalone Deployment Strategies: A Simulation Model for Emerging Countries

Deploying cutting-edge 5G technology is a major challenge for mobile operators in emerging countries, facing hurdles on both the technical and economic fronts. This study provides specific ways in which mobile companies in developing countries can use 5G technology to benefit economically. This study utilizes a sensitivity option with a techno-economic analysis (TEA) simulation model to evaluate business options influencing successful 5G non-standalone (NSA) deployment in these markets, using Indonesia’s Bandung City as a case study. The analysis finds that Bandung requires 172 5G gNodeBs to meet traffic demand. Further, the 5G NSA deployment delivers strong key performance indicators (KPIs), with good signal synchronization received power (SS-RSRP) and signal-to-interference noise ratio (SS-SINR). Sensitivity analysis identifies the gNodeB amount as the most critical parameter impacting overall 5G NSA deployment feasibility. Overall, the analysis indicates mobile operators can recover investments after 3 years and 10 months, providing evidence for the viability of 5G NSA deployment in Bandung’s urban area.

EFFECT OF TACTICAL PLANNING ON THE PERFORMANCE OF MOBILE SERVICE PROVIDERS IN NIGERIA

Purpose: The research aimed to examine the impact of tactical planning on the performance of mobile service providers in Nigeria. Theoretical Framework: The theoretical framework employed in this research is rooted in the Resource-Based View (RBV) Theory. RBV offers a comprehensive framework for understanding how operational planning influences the performance of mobile service providers by aligning internal resources with external market conditions and contributing to sustained competitive advantage. Design/Methodology/Approach: Employing a survey research design, the study utilized a multistage sampling technique to gather primary data from a sample of 350 randomly chosen employees representing the workforce of the four major mobile network operators in Nigeria—MTN, Globacom, Airtel, and 9Mobile—comprising the study's target population. Findings: The result of the regression analysis established a positive and statistically significant (p<0.05) relationship between tactical planning and business growth in Nigeria's mobile communication sector. Based on the findings of the study, it was concluded that tactical planning is a substantial contributor to business growth in the telecom sector in Nigeria. Research, Practical & Social Implications: The study suggests that Nigerian mobile service providers should invest in refining their tactical planning processes, regularly assess their strategies, foster a culture of continuous improvement, engage in employee training, collaborate with industry peers, and stay updated with technological advancements. Companies should invest in comprehensive training programs and knowledge-sharing initiatives to build the strategic capabilities of their teams, ensuring a more effective implementation of tactical plans. Originality/Value: The findings of this study are likely to have practical implications for mobile service providers, informing their tactical strategies and decision-making processes for improved performance and competitiveness in the Nigerian market.

A Community Initiative to Help Children Who Are Homeless.

Children experiencing homelessness (CEH) have several health-related needs. It is necessary to address barriers posed by homelessness to improve health outcomes. Our objectives were to (1) conduct a health-related needs assessment and (2) determine acceptability/feasibility of the community-based initiative designed to identify and address health-related needs for CEH. The initiative involved a mobile care center, a health-focused education series for CEH, and resource provision, which included establishing connections with a stable source of health care. The needs assessment included standardized screening questions assessing health-related needs. We surveyed guardians of CEH who attended Summer360 between June and July 2022. Guardians were invited to evaluate our intervention via survey. We used descriptive statistics to characterize health-related needs. A needs assessment was completed on 36 of 100 children (42% white persons, 64% male), with 94% reporting at least 1 health-related need, and 61% with ≥3 needs. The most common needs identified were dental health and food insecurity. Twenty-four (24%) campers participated in a mobile health clinic that included hearing and vision screening, fluoride application, and vaccinations. The education series included dental hygiene, nutrition, and mental health. All families who desired assistance (73%) were connected to resources, and 91% of guardians agreed that the initiative helped meet their children’s health-related needs and provided helpful resources. Implementation required planning with contributors including dental partners, mobile clinic operators, and school leadership. A community-based health initiative may serve as a unique opportunity to identify and address health-related needs for CEH.

Health and Wellness App

The 'Health and Wellness' mobile operation combines AI to enhance the healthcare experience. Our user centric platform provides seamless access to state-of-the-art AI technology. By inputting symptoms, our advanced algorithms generate accurate predictions, empowering individuals with valuable health insights. Through online consultations with healthcare professionals and an interactive chatbot, our app revolutionizes healthcare by prioritizing convenience and quality. We aim to provide stoners with comprehensive and effective solutions for their health conditions, ushering in a new era of substantiated health results.

The influence of business process outsourcing on the productivity of the mobile telecommunication companies

Economics of business and increased focus on operating efficiencies are leading mobile telecom service providers to outsource non-core business process elements, infrastructure systems, and customer service, although the trade-off on the influence of business process outsourcing (BPO) on the firm’s productivity is still inconclusive. Few empirical studies or research have been conducted to analyze the influence of BPO on the firm’s productivity levels in the mobile telecom operators of Southern African developing countries. This research tries to redress the existing knowledge gap and the limited body of literature by providing both descriptive and empirical evidence on the influence of BPO on the firm‘s productivity levels of mobile telecom operators. A structured closed-ended questionnaire was used to collect raw data from 210 employees. Descriptive and chi-square tests were conducted to establish the statistically significant relationship between business process outsourcing and the firm’s productivity levels. The results reflect a statistically significant relationship between the implementation of BPO and the firm’s productivity. The study has practical implications for service and industrial practitioners, managers, scholars, and government policymakers in that they can strategically plan their BPO practices and link those practices to the organizations' productivity performance. Further research can be conducted in other industries in order to do comparison studies confirming lessons gained across industries on the effect of BPO on a firm’s productivity levels.

Mobile Network Operators’ Assessment Based on Drive-Test Campaign in Urban Area for iPerf Scenario

The development of new telecommunication services requires the implementation of advanced technologies and the next generations of networks. Currently, the Long-Term Evolution (LTE) is a widely used standard. On the other hand, more and more mobile network operators (MNOs) are implementing the fifth-generation (5G) New Radio standard in their networks. It allows for increasing throughput, spectral, and energy efficiency and maximizing coverage, while reducing latency. The effectiveness of the introduced changes is measured by assessing the quality of service (QoS) in mobile networks. The paper presents the result evaluation of the QoS measurement campaign carried out using the drive test method in an urban area for four MNOs. We analyze the data transmission scenario, which is the basis of most modern telecommunications services. The result comparison provides an assessment of the 5G service implementation advancement by MNOs. In this analysis, we consider many QoS metrics (e.g., session time, throughput, and round-trip time) and parameters defining the radio signal quality (i.e., reference signal received power, signal-to-interference-plus-noise ratio). Our work also included searching for relationships between these parameters, using a correlation analysis. It allows for the selection of uncorrelated parameters to assess the quality of network, i.e., MNO evaluation, in terms of the provided QoS.

Embedded-SIM (E-SIM) an Overview in Latin America: Implementation, Availability, Advantages and Disadvantages

Search new forms for data management and security is a continuous tendency for mobile operators. Proof of this is the trend of the latest technology related to the Embedded Subscriber Identity Module or Embedded-SIM (E-SIM). Recently there was an increase in the number of devices that offer this technology as a security element for the access to the network, however, it is clear the lack of consistent information for the implementation of this technology within Latin America. This research presents a current overview about the evolution of the embedded subscriber identity module, aiming to present the general characteristics that are part of the network, evaluate the current status of implementation and adoption with Latin America carriers, showing the obstacles in the process of acceptance of new technology by users as well as the advantages, disadvantages of E-SIM in relation to the traditional SIM Card. The investigation was carried out through documentary surveys and field research, the data was collected to demonstrate the current perspective of the implementation of E-SIM and adoption by customers and network operators in Latin America. The observed results showed that the adoption of E-SIM in Latin America has been increasing, it was observed that most countries have at least one carrier that makes available and offers this service. Regarding the advantages and disadvantages, evidence has been observed place E-SIM like a better technology than a SIM Card.

Analysis of surgical site infection and tumour-specific survival rate in patients with renal cell carcinoma after laparoscopic radical nephrectomy.

Surgical site infections (SSIs) may pose a significant risk to patients undergoing surgery. This study aims to explore the risk factors for SSIs in patients undergoing laparoscopic radical nephrectomy for renal cell carcinoma and the impact of infection on tumour-specific survival (CSS) after nephrectomy for renal cell carcinoma. To explore the risk factors for SSIs in patients undergoing laparoscopic radical nephrectomy for renal cell carcinoma and the impact of infection on tumour-specific survival (CSS) after nephrectomy for renal cell carcinoma. A retrospective analysis was conducted on 400 patients in our hospital from June 2021 to June 2023. This study divided patients into two groups: those with SSI and those without SSI. Collect general data and information related to the operating room. Clearly defined inclusion and exclusion criteria. Select surgical time, laminar mobile operating room use, and intraoperative hypothermia as observation indicators. Perform statistical analysis using SPSS 25.0 software, including univariate, multivariate, and survival analyses of wound-infected and uninfected patients. Out of 400 patients, 328 had no SSIs, 166 died during follow-up, 72 had SSIs, and 30 died during follow-up. There was no statistically significant difference (p > 0.05) in comparing primary data between individuals without SSIs and those with SSIs. There were statistically significant differences (p < 0.05) in surgical time, nonlaminar flow operating room use, and intraoperative hypothermia. The postoperative survival time of SSI patients with a tumour diameter of 7.0-9.9 cm was significantly longer than that of SSI patients, and the difference was statistically significant (p < 0.05). The occurrence of severe infection in patients with other tumour diameters did not affect postoperative survival, and the difference was not statistically significant (p > 0.05). After multiple factor analysis, it was found that severe infection can prolong the postoperative survival of patients with tumour diameter exceeding 7 cm (HR = 0.749, p < 0.05). This study identified nonlaminar flow operating rooms, prolonged surgical time, and intraoperative hypothermia as significant risk factors for SSIs. After nephrectomy for renal cell carcinoma patients with a tumour diameter of 7-9.9 μ m, perioperative infection can prolong their survival. However, it has no significant effect on patients with other tumour diameters.

Performance Analysis of 4x4 MIMO and 8x8 MIMO Antena Implementation of Private 5G Networks in Industrial Area

Private 5G represents a promising wireless network technology that offers a wide range of opportunities for mobile operators. It enables them to meet the increasing data demands of their customers and provide enhanced capacities and user experiences. However, before deploying Private 5G, it's crucial to prepare the foundation properly, especially when choosing the right antena and Radio Frequency (RF) band. This research project focuses on evaluating the implementation of 4x4 MIMO and 8x8 MIMO antenas in the Greater Jakarta industrial area, covering a 35 km2 area, operating at a frequency of 2300 MHz with a 40 MHz bandwidth. The study involved data rate measurements and determined the number of required sites based on different modulation schemes. The findings revealed that using an 8x8 MIMO antena resulted in a data rate twice as high as that achieved with a 4x4 MIMO antena and required only a quarter of the sites. Additionally, simulation results demonstrated that the 8x8 MIMO antena provided better SS-RSRP and SS-SINR values compared to the 4x4 MIMO antena, with values of -91.51 dBm and 8.52 dB

Design and Performance Analysis of Prioritized On-the-Spot Mobile Data Offloading Scheme

Recent years have witnessed a surge in the mobile data traffic which is only expected to grow exponentially in the coming years. To cope up with this huge data demand, mobile operators have restored to a novel scheme called on-the-spot mobile data offloading wherein mobile data is offloaded onto Wi-Fi network whenever the user enters a Wi-Fi coverage area. Further reports indicate that a sizable portion of the mobile data traffic is multimedia in nature that demands good quality of service. In this context, we design and analyze a scheme to prioritize different data traffic encountered in on-the-spot mobile data offloading. Using a Markov chain model for on-the-spot mobile data offloading scheme, we derive the packet transmission delay of different traffic categories that carry different priorities. We validate out analytical results against simulation and demonstrate the effectiveness of the proposed prioritization scheme.

Designing a Surveillance Sensor Network with Information Clearinghouse for Advanced Air Mobility

To ensure safe, secure, and efficient advanced air mobility (AAM) operations, an AAM surveillance network is needed to detect and track AAM traffic. Additionally, a cloud-based surveillance data collection, monitoring, and distribution center is needed, where AAM operators and service suppliers, law enforcement agencies, correctional facilities, and municipalities can subscribe to receiving relevant AAM traffic data to plan and monitor AAM operations. In this work, we developed an optimization model to design a surveillance sensor network for AAM that minimizes the total sensor cost while providing full coverage in the desired region of operation, considering terrain types of that region, terrain-based sensor detection probabilities, and meeting the minimum detection probability requirement. Moreover, we present a framework for the low altitude surveillance information clearinghouse (LASIC), connected to the optimized AAM surveillance network for receiving live surveillance feed. Additionally, we conducted a cost–benefit analysis of the AAM surveillance network and LASIC to justify an investment in it. We examine six potential types of AAM sensors and homogeneous and heterogeneous network types. Our analysis reveals the sensor types that are the most profitable options for detecting cooperative and non-cooperative aircraft. According to the findings, heterogeneous networks are more cost-effective than homogeneous sensor networks. Based on the sensitivity analysis, changes in parameters such as subscription fees, the number of subscribers, sensor detection probabilities, and the minimum required detection probability significantly impact the surveillance network design and cost–benefit analysis.

Innovative Approach to Android Malware Detection: Prioritizing Critical Features Using Rough Set Theory

The widespread integration of smartphones into modern society has profoundly impacted various aspects of our lives, revolutionizing communication, work, entertainment, and access to information. Among the diverse range of smartphones available, those operating on the Android platform dominate the market as the most widely adopted type. With a commanding 70% share in the global mobile operating systems market, the Android OS has played a pivotal role in the surge of malware attacks targeting the Android ecosystem in recent years. This underscores the pressing need for innovative methods to detect Android malware. In this context, our study pioneers the application of rough set theory in Android malware detection. Adopting rough set theory offers distinct advantages, including its ability to effectively select attributes and handle qualitative and quantitative features. We utilize permissions, API calls, system commands, and opcodes in conjunction with rough set theory concepts to facilitate the identification of Android malware. By leveraging a Discernibility Matrix, we assign ranks to these diverse features and subsequently calculate their reducts–streamlined subsets of attributes that enhance overall detection effectiveness while minimizing complexity. Our approach encompasses deploying various Machine Learning (ML) algorithms, such as Support Vector Machines (SVM), K-Nearest Neighbor, Random Forest, and Logistic Regression, for malware detection. The results of our experiments demonstrate an impressive overall accuracy of 97%, surpassing numerous state-of-the-art detection techniques proposed in existing literature.