Telecom Operators Research Articles

Telecom data analytics: Informed decision-making: A review across Africa and the USA

Telecom data analytics has emerged as a pivotal tool for transforming raw data into actionable insights, empowering telecom operators to make informed decisions and enhance the overall efficiency of their networks. This abstract provides an overview of the comprehensive review that explores the landscape of telecom data analytics in both Africa and the USA. The review delves into the diverse strategies, challenges, and opportunities associated with telecom data analytics in these regions. It examines how advanced analytics techniques, including machine learning and artificial intelligence, are being leveraged to extract valuable insights from vast datasets. The comparative analysis highlights contextual differences in regulatory environments, infrastructure development, and technological landscapes that influence the adoption and implementation of telecom data analytics. In Africa, where the telecom landscape is dynamic and diverse, the review explores how data analytics is playing a crucial role in addressing connectivity challenges, optimizing network performance, and expanding telecommunications services. It also considers the impact of regulatory frameworks and investment climates on the deployment of data analytics solutions. In the USA, a mature telecom market with high technological adoption, the review investigates how data analytics is shaping decision-making processes, improving customer experiences, and contributing to the development of innovative services. It delves into the regulatory landscape, market dynamics, and the role of data analytics in maintaining a competitive edge. Throughout the review, the focus is on identifying best practices, lessons learned, and cross-regional insights that can inform the future trajectory of telecom data analytics. The abstract encapsulates the broader themes of the review, offering a glimpse into the critical role played by data analytics in shaping the telecom industry across Africa and the USA.

Использование сторонами защиты и обвинения данных операторов связи в целях установления обстоятельств совершения преступлений

The article discusses non-standard directions for using data from telecom operators; the growing practice of using data from telecom operators by the defense side is analyzed; the relevance of the use of billing data in supervising the implementation of the law during the implementation of operational investigative activities and investigative actions is emphasized; the effectiveness of solving and investigating crimes when obtaining details of telephone connections is noted; materials from judicial and investigative practice are examined and recommendations are given to prevent violations of the law.

5G NETWORK MODEL DEVELOPMENT IN ANYLOGIC ENVIRONMENT

This article describes the analysis of programs for modeling 5G networks. In the selected AnyLogic program, a 5G network model with several base stations that have different characteristics was created. Studies of this model have been made taking into account various disciplines of the queue, the load on each station has been calculated at different priorities. It is proved that this model can be used to study and evaluate the of data transmission efficiency in 5G networks, as well as to analyze the impact of the characteristics of additional parameters (latency, load and priorities) on the quality of data processing. The studies confirmed that the developed 5G network model can help telecom operators optimize performance of their networks and ensure more efficient use of allocated resources.

Barriers and Implications of 5G Technology Adoption for Hospitals in Western China: Integrated Interpretive Structural Modeling and Decision-Making Trial and Evaluation Laboratory Analysis.

5G technology is gaining traction in Chinese hospitals for its potential to enhance patient care and internal management. However, various barriers hinder its implementation in clinical settings, and studies on their relevance and importance are scarce. This study aimed to identify critical barriers hampering the effective implementation of 5G in hospitals in Western China, to identify interaction relationships and priorities of the above-identified barriers, and to assess the intensity of the relationships and cause-and-effect relations between the adoption barriers. This paper uses the Delphi expert consultation method to determine key barriers to 5G adoption in Western China hospitals, the interpretive structural modeling to uncover interaction relationships and priorities, and the decision-making trial and evaluation laboratory method to reveal cause-and-effect relationships and their intensity levels. In total, 14 barriers were determined by literature review and the Delphi method. Among these, "lack of policies on ethics, rights, and responsibilities in core health care scenarios" emerged as the fundamental influencing factor in the entire system, as it was the only factor at the bottom level of the interpretive structural model. Overall, 8 barriers were classified as the "cause group," and 6 as the "effect group" by the decision-making trial and evaluation laboratory method. "High expense" and "organizational barriers within hospitals" were determined as the most significant driving barrier (the highest R-C value of 1.361) and the most critical barrier (the highest R+C value of 4.317), respectively. Promoting the integration of 5G in hospitals in Western China faces multiple complex and interrelated barriers. The study provides valuable quantitative evidence and a comprehensive approach for regulatory authorities, hospitals, and telecom operators, helping them develop strategic pathways for promoting widespread 5G adoption in health care. It is suggested that the stakeholders cooperate to explore and solve the problems in the 5G medical care era, aiming to achieve the coverage of 5G medical care across the country. To our best knowledge, this study is the first academic exploration systematically analyzing factors resisting 5G integration in Chinese hospitals, and it may give subsequent researchers a solid foundation for further studying the application and development of 5G in health care.

Evaluation of Competitive Strategies for Telecommunication Broadband Development in County-Level Cities: A Case Study

In today's digital era, broadband network has become the cornerstone of promoting economic and social development, especially county-level cities have become one of the crucial areas for telecom service providers to compete for market share. In order to deeply explore the development and competition strategy of telecom broadband in county-level cities, this thesis uses SWOT analysis to systematically analyze the advantages, disadvantages, opportunities and threats of telecom operators in county-level cities through the case of telecom broadband in Dengzhou City, Henan Province, and based on this analysis, analyzes the factors such as market positioning, pricing strategy, service quality, and promotional means, etc., and deeply analyzes the current situation and future development trend of the telecom broadband market in county-level cities. The current situation and future development trend of the telecom broadband market in county-level cities are analyzed in depth.

Adoption of Internet of Things in Telecommunications: An Emerging Market Case

This paper has presented a case of the adoption of Internet of Things (IoT) technology in telecommunications in Pakistan. Through an exploratory case study, it has explored the need for IoT technology, the role of the telecom sector in IoT development, IoT strategies and business models adopted, challenges confronted, and benefits gained by telecom operators in Pakistan. The business-centric, customer-centric, and country-centric approaches were the basis for IoT technology adoption by telecom operators. By providing networks and connectivity, the telecom sector has played a significant role in the development of IoT. The telecom operators have developed their business strategies and used different business models to capitalize on their digital enabler role in the IoT domain. They also have faced challenges related to technological integration, infrastructure resources, and human resources when adopting IoT technology. The benefits realized by telecom operators were improved operational planning and processes, increased productivity, enhanced organizational performance, and IoT knowledge. These findings can guide practitioners, regulators, and policymakers in understanding the opportunities and implications of IoT in telecommunications.

Creation and Sharing of Value in the Telecoms Sector. (How Telecom Operators’ Investments Benefit Content Providers Rather Than Themselves.)

Creation and Sharing of Value in the Telecoms Sector. (How Telecom Operators’ Investments Benefit Content Providers Rather Than Themselves.)

Modeling the Customer Experience Using Machine Learning for Optimizing the Performance of Telecommunications Networks: Case of Mobile Networks

Customer experience is a major issue for telecommunications companies seeking to offer quality and personalized services in an environment where customer expectations are constantly evolving. Measuring this experience is a complex challenge, particularly with regard to the impact of network performance on customer usage and, consequently, on their satisfaction. In this context, an in-depth analysis on the relationships between network performance indicators and customer experience was carried out in the network of the telecommunications operator Orange Cameroon (OCM). A method based on machine learning and deep learning was used to predict the behavior of network performance indicators. QoE value thresholds and network performance indicators have been defined for different levels of customer satisfaction. A machine learning model made it possible to obtain precise predictions of customer satisfaction. The results obtained showed that customer satisfaction can be reliably predicted from network performance indicators and QoE. This approach offers a better understanding of the customer experience and allows telecommunications operators to act proactively to improve user satisfaction across all actions related to their use. The application of the results of this study presents a significant impact at different levels. At the national level, telecommunications operators can optimize their services and react more quickly to network incidents, thus improving customer satisfaction and loyalty. This strengthens the competitiveness of telecommunications companies by providing a better customer experience. Globally, a better understanding of customer experience is driving the evolution of the telecommunications industry as a whole

The Efficacy of Autoencoders in the Utilization of Tabular Data for Classification Tasks

This article explores the effectiveness of applying auto encoders in the context of classical machine learning tasks, particularly classification tasks on tabular data. Significant emphasis is placed on a detailed comparison of this approach with other widely adopted methods in the field. As an applied task, the creation of a look-alike model for targeted advertising is pursued. Research into the requirements for this model reveals that conventional approaches to processing tabular data and model training cannot yield a solution that qualitatively meets all specified criteria. Evaluation is conducted on a closed dataset provided by a telecommunications operator. This de-identified dataset includes subscriber descriptions, their tariff plans, and mobile devices. The research goal is to assess non-traditional approaches from the domain of deep learning and neural networks in the context of classification tasks on tabular data and compare them with established methods in this context. The research findings demonstrate that the investigated approach yields a solution that surpasses traditional approaches across all specified criteria. Furthermore, the study provides insights into the universality of this approach, indicating its applicability in various domains for tabular data classification tasks. The ability to compress information into vector representations without significant loss and identify new hidden nonlinear dependencies in data enhances the practical value of the approach. Future research will address the formation of multiple autoencoders in different knowledge domains and their integration for specific tasks. Additionally, efforts will focus on identifying the most effective algorithm for finding similar subscribers based on the vector representations obtained from autoencoders.

5G network model development in AnyLogic environment

Problem statement. The development of mobile communication networks does not stop for a minute, new standards and various new technologies are emerging. The opportunities provided by mobile technologies have long gone beyond voice services. The sharp growth of Internet traffic in networks around the world is explained by the widespread use of devices connected to mobile networks. With the development of mobile networks, new and diverse requirements are being imposed on them. Technology development is aimed at increasing productivity and expanding opportunities. Therefore, it becomes necessary to study the influence of the characteristics of additional parameters (delays, station loads) on the quality of data packet processing in order to optimize the operation of 5G networks and ensure more efficient use of resources. Many scientists who conducted research on 5G networks using modeling did not take into account various variants of queue processing algorithms, did not consider how the values of data transmission delays and the number of lost packets would change with an increase or decrease in the number of base stations, models consisting of several base stations were not considered. Based on this, we will conclude that it is advisable to develop a 5G network model, with the help of which various studies can be carried out, which will take into account the above parameters. The goal is to investigate the resource model of data transmission in 5G networks, to analyze the operation of the 5G network model in the AnyLogic environment. Results. During the study of traffic maintenance in the 5G network, the optimal system parameters were determined, allowing the most efficient use of network resources. It turned out that the use of methods of dynamic resource allocation and automatic change of base station parameters reduces the load on the network and increases its performance. The developed model allows us to assess the reliability of the system and its ability to process user requests, because the probability of losing an application or non-fulfillment of an application is high, this can lead to user dissatisfaction and a decrease in the quality of service. Practical significance. The developed model can be used in practice to study and evaluate the parameters of the 5G network, as well as to analyze various characteristics that affect the quality of the network in order to improve it. This can help telecom operators optimize their networks and ensure more efficient use of resources.

ХАРАКТЕРИСТИКА, МЕСТО И РОЛЬ МЕЖОПЕРАТОРСКОГО РЫНКА УСЛУГ СВЯЗИ В ЦИФРОВОЙ ЭКОНОМИКЕ

The article looks into the structure of the digital economy, the place and role in the structure of telecommunication technologies in general and the interoperator market of communication services in particular. There are explored the features of the functioning of the inter-operator market as an infrastructure platform in the global telecommunications system, as an independent technological and consumer market within the communications industry, and as an established professional community based on the principles of partnership and mutually beneficial cooperation. The relevance of the study is caused by the need to solve organizational issues of interaction between structural elements, taking into account their importance for the effective development of the digital economy. The research is based on a set of general scientific methods: structural analysis, observation, logical method. Scientific novelty lies in identifying the place and role of the interoperator interaction in the modern digital economy structure, identifying organizational challenges and determining ways to solve them at the level of the market under study. In particular, to increase the operational efficiency of the interoperator interaction, the author recommends applying the provisions of the of supplier relationship management concept (SRM), adapted for the area of economic activity, and justifies the feasibility of introducing them in strategic and operational management in telecom operator companies.

Graphene-boosted ultra-wide band reconfigurable optical switch for SOI-based telecom applications: A numerical study

In this work, we propose the design of a compact optical switch featuring a wide bandwidth of 360 nm, suitable for telecom operations. The switch is a passive 3dB splitter realized through a Y-branch, electrically activated via a graphene/insulator/graphene (GIG) capacitor embedded within the rib waveguide (WG). The capacitor itself is embedded within an SOI-based hybrid WG composed of crystalline (c-Si) and hydrogenated amorphous silicon (a-Si:H), with the GIG between the two layers. Such a photonic structure optimizes the light-matter interaction and enables a compact device with a length of only 100 μm. By applying a voltage bias to the graphene layers, we achieve the condition necessary for efficient data transmission through the WG. Indeed, the electrical doping of graphene enables the modulation of optical losses within the waveguide, ranging from total light absorption to up to 70% transmission. The simplicity and ease of fabrication of this innovative design offer significant advantages for integration into existing photonic circuits. Its wide bandwidth allows compatibility with a variety of telecom wavelengths, providing flexibility in network configurations. Consequently, this compact optical switch presents a promising solution for modern data communication needs, demonstrating a balance between efficiency and scalability.

Performance Evaluation of Mobile Network Service Delivered Within Federal Polytechnic Bali and Its Environs; With a Focus on 2G and 3G Technologies

Monitoring the QoS (Quality of Service) of mobile network service providers is key if end users must derive maximum satisfaction from the numerous mobile services provided to them. In this research, data was collected via drive test, using mobile phones, Test Mobile System (TEMS) software a technology used by telecom operators to measure, analyze, and optimize their mobile networks, and Mapinfo software for post processing. For 2G technology, four parameters were analyzed which are Rx Lev (Received Signal Level), and Rx Qual (Received Signal Quality), while for 3G technology three parameters were analyzed which are RSCP (Received Signal Code Power), Ec/Io, and downlink throughput. The serving cells, Broadcast control channels as well as the Primary scrambling codes for all mobile network operators were recorded. The data collected was for MTN, Airtel and GLOBACOM (Glo) Networks, and the area of study comprised Bali metropolis, Maihula, Gazuba and Garbabi. It was deduced that the Rx_Lev range of negative 10dBm to negative 65dBm covered just 4.53%, 4.31% and 6.62% of the total route driven for MTN, Airtel and Glo respectively, which falls below the 75% requirement by the Nigerian Communication Commission (NCC). It was recommended amongst others the physical optimizations be carried out for PSC 19, 46, 70, 205, 313, 368 in order to improve coverage, quality and downlink throughput. The results of this study have practical implications for all mobile network operators within the area of study as it provides valuable information enabling them to enhance their network infrastructure and services in order to meet set key performance indicators (KPIs) by the regulator, as well as ensure user derive satisfaction.

Package for data management of a telecommunication device in a monitoring system

In order to identify the role of data storage in the monitoring system of a telecommunications device, a conceptual design method was used, which was based on the basic principles of the Telecommunication Management Network concept, which is a network management system for telecommunication operators. Based on this concept, it was possible to design a data storage model in the monitoring system of a telecommunications device, which clearly reflects the separation of databases involved in the telecommunications network at different levels of the concept. A description of the differences between the databases assigned to each specific level from each other and an explanation of the functional features of each of the databases under consideration, as well as a description of the data circulation process over the network, is presented. The work focuses on describing the contents of the database of a specific telecommunications device, which is the object of control in the communication network, with the possibility of developing an interface to this database, which makes it convenient to search, view and modify stored data. To designate the information stored in the database of a telecommunications device, a fragment of the database was developed containing a set of attributes characterizing the device, their values and parameters of attribute values. The role of the database interface is to enable the user to quickly and easily access the information contained in the database.

The relationship between human resources marketing and innovative work behaviour: an exploratory qualitative study in Tunisian telecommunications operator Tunisie Telecom

The relationship between human resources marketing and innovative work behaviour: an exploratory qualitative study in Tunisian telecommunications operator Tunisie Telecom

The relationship between human resources marketing and innovative work behaviour: An exploratory qualitative study in Tunisian telecommunications operator Tunisie Telecom

The relationship between human resources marketing and innovative work behaviour: An exploratory qualitative study in Tunisian telecommunications operator Tunisie Telecom

ОСОБЕННОСТИ РОЗЫСКНЫХ МЕРОПРИЯТИЙ ПРИ РАССЛЕДОВАНИИ ПРЕСТУПЛЕНИЙ, СОВЕРШАЕМЫХ В СФЕРЕ КОМПЬЮТЕРНОЙ ИНФОРМАЦИИ

It is difficult to overestimate the issues of improving the tactics of investigative measures in the investigation of crimes in the field of computer information. In recent years, due to the significant growth of digitalization, both quantitative indicators of crimes in the field of computer information and their qualitative level have been steadily increasing. It becomes more difficult for investigative bodies to collect the necessary evidence, detect electronic and digital traces, determine their authorship and establish cause-and-effect relationships. Modern operational investigative measures assume that law enforcement officers have the skills to detect and analyze digital data, extract electronic traces, as well as record these data as evidence. The investigation of crimes in the field of computer information requires specialized knowledge and skills to effectively counter the new methods and technologies used by offenders. The relevance of the search tactics is due to the need to adapt to the ever-changing cyber threat and ensure the security of information systems. It is determined that law enforcement agencies need to constantly improve their skills and enrich their knowledge, the need for appropriate material and technical equipment, assuming the availability of specialized tools, is obvious. It is especially important to modernize the tactics of searching for suspects. It has been revealed that wiretapping is an important element in conducting operational search activities. Listening involves installing audio tracking devices on telephone communication lines, as well as concluding an agreement with telecom operators to gain access to Internet traffic and telephone conversations. However, there are significant risks of abuse of authority by law enforcement agencies. Unfortunately, the law does not define a list of criteria by which it is possible to determine whether listening should be used in a particular case or not. This creates threats to users’ personal data and introduces uncertainty into law enforcement activities.

Implementation Licencing Regulations Telecommunications Network in The Omnibus Law

The form manifestation of the omnibus law form is Law Number 11 of 2020 concerning Copyright. The law on telecommunications relating to Main Licensing and Technical Licensing has undergone significant changes. Implementing the licensing process requires changes and a common perspective in understanding the articles associated with the licensing process, especially in telecommunications. The problem experienced is that several articles in the omnibus law regarding licensing for the operation of telecommunications networks still need to be clarified, which can potentially cause different perceptions among stakeholders. This study uses a normative juridical analysis method using primary law to analyze the problems that are the focus of the research. The conclusion drawn from this research is the need to clarify the articles in Law 11 of 2020 concerning Job Creation and its derivative regulations regarding procedures for telecommunications operations other than those that already exist, which a Ministerial Decree can stipulate. There needs to be clarity in the rules regarding risk-based business licensing regarding how long the essential and technical licensing process takes and the need to attach a licensing SOP flowchart so that licensing stakeholders have the same perception of the licensing process.

Policy Mechanism for Security of National Vital Objects in the Telecommunications Sector in Indonesia

Telecommunication infrastructure is part of critical infrastructure because it has a vital role in the community and affects the country's economy. Therefore, telecommunications infrastructure can be classified as a vital national object, requiring a particular security mechanism in its deployment. However, telecommunication infrastructure has different characteristics than other sectors, where the operation is fixed and mobile. Using a descriptive-analytical approach, data is obtained from benchmarks and interviews with resource persons from various fields through several Forum Group Discussion activities. Each telecommunications network operator can apply for National Vital Objects in the Telecommunications Sector based on the mechanism under the guidelines for determining the national vital object in the telecommunications sector stipulated through a Ministerial Regulation. The regulation covers various aspects, including the mechanism for determining, evaluating, fostering, and responsibilities of National Vital Objects in the Telecommunications Sector. In its implementation, the National Vital Objects in the Telecommunications Sector manager coordinates with various security parties, such as the Indonesian National Police. With the policy of the National Vital Objects in the Telecommunications Sector implementation mechanism, it is hoped that the telecommunications infrastructure can be well protected so that the business climate of telecommunications operations remains conducive and telecommunications services can always support the development and strengthening of the national economy.

Predicting People’s Concentration and Movements in a Smart City

With the rapid growth of urbanization and the proliferation of mobile phone usage, smart city initiatives have gained momentum in leveraging data-driven insights to enhance urban planning and resource allocation. This paper proposes a novel approach for predicting people’s concentration and movements within a smart city environment using mobile phone data provided by telecommunication operators. By harnessing the vast amount of anonymized and aggregated mobile phone data, we present a predictive framework that offers valuable insights into urban dynamics. The methodology involves collecting and processing location-based data obtained from telecommunication operators. Using machine learning techniques, including clustering and spatiotemporal analysis, we developed models to identify patterns in people’s movements and concentration across various city regions. Our proposed approach considers factors such as time of day, day of the week, and special events to capture the intricate dynamics of urban activities. The predictive models presented in this paper demonstrate the ability to predict areas of high concentration of people, such as commercial districts during peak hours, as well as the people flow during the time. These insights have significant implications for urban planning, traffic management, and resource allocation. Our approach respects user privacy by working with aggregated and anonymized data, ensuring compliance with privacy regulations and ethical considerations. The proposed models were evaluated using real-world mobile phone data collected from a smart city environment in Lisbon, Portugal. The experimental results demonstrate the accuracy and effectiveness of our approach in predicting people’s movements and concentration. This paper contributes to the growing field of smart city research by providing a data-driven solution for enhancing urban planning and resource allocation strategies. As cities continue to evolve, leveraging mobile phone data from telecommunication operators can lead to more efficient and sustainable urban environments.