Telecom Operators Research Articles

İnternet provayderlərin məsuliyyətinə dair təcrübənin Azərbaycan, Türkiyə və Avropa hüquqi tənzimlənməsi əsasında müqayisəli təhlili

In the article, a comparative analysis of the practice of the liability of Internet providers is carried out based on the legal regulation of Azerbaijan, Turkey and Europe. It is noted that the issue of responsibility of providers for the content shared in the virtual space is based on the regulation of the Internet and information legal responsibility as a unity of two main information legal research topics. In the end, it is concluded that Internet providers are not classified in the legislation of the Republic of Azerbaijan. Thus, the terms host provider, Internet information resource owner, and telecommunications operator and provider are used. Only the legal understanding given to the host provider complies with international norms and best foreign practices. The lack of basic legal concepts also makes it difficult to solve the issues of responsibility in case of violation of rights and freedoms. Keywords: Internet provider, virtual space, Internet regulation, information-legal responsibility, Internet information resource, rights and freedoms, legal regulation.

New methods of investment prioritization in the development of cellular networks in Russia

Subject. The article presents a new enhanced method of prioritizing investments in the construction of mobile networks to increase the effectiveness of management decisions. Objectives. The study aims to develop an improved methodology for prioritizing investments in the construction of cellular networks in Russia, taking into account market dynamics. Methods. I apply a comprehensive approach to the exploration of investment prioritization methods, general scientific and special methods of scientific knowledge, like system and functional-structural analysis, observation, classification, analysis of the best practices, synthesis and generalization of existing scientific and practical data. Results. The article offers a new method of investment prioritization based on more accurate forecasting of incremental revenues, considering the impact of the time lag between the change in market share by base stations and the change in market share by revenue. Conclusions. The proposed method relies on the assessment of incremental revenues, considering the impact of the time lag on increasing market share by revenue with an increase in market share for base stations. This factor directly affects the payback period of investments and allows more accurate ranking of regional branches of telecommunications operators, when deciding on investments in network construction for various subjects of the Russian Federation.

Hidden Markov models for predicting cell-level mobile networks performance degradation

The ubiquitous deployment of Fourth-generation (4G) and Fifth-generation (5G) networks, while expanding user connectivity over a larger geographic area, presents significant challenges for mobile network management. The surge in connected devices increase cell congestion, while user mobility, fading, and interference further deteriorate channel quality. The combined effect of these factors contribute to a gradual degradation in cell and network performance, straining the capabilities of Mobile Network Operators (MNOs) to maintain optimal service quality. The degradation progresses through distinct stages, and ultimately leading to cell outages. Existing cell degradation detection methods, such as key performance indicators (KPIs) monitoring and drive tests, rely on indicators such as signal strength (like reference signal received power (RSRP)), network measurements (like traffic volume and handover requests), and user complaints. However, these methods may not provide real-time insights, leading to delays in identifying and addressing performance issues. This paper proposes a Hidden Markov Model (HMM) approach for proactive cell degradation prediction using real-time time-series KPIs data collected from a telecom operator’s network management system. The NetMax system, a network management system specifically designed for ZTE networks, was used for KPIs data collection. RSRP, 3GPP-recommended signal strength metrics for degradation measure, defines hidden states, while traffic volume and handover requests represent the observable states. The HMM achieves an average prediction accuracy of 93.12%, F1 score of 91.81%, and precision of 92.82% with 23 observation lengths, demonstrating the models’s effectiveness in predicting mobile network’s cell degradation severity.

Internal OSH Regulation of Working at Height by Using Utilitarian Climbing Techniques In Telecommunication Operations

Internal OSH Regulation of Working at Height by Using Utilitarian Climbing Techniques In Telecommunication Operations

On the issue of the security of bank payments in modern Russian practice

he interaction of the banking sector with the external environment (which is not always favorable) determines the possibility of new threats, financial losses and, as a result, the need to use tools to ensure the security of bank payments. Its development is a priority task for the banking community and falls within the sphere of interests of each participant in the settlement and payment segment. In this publication, a dynamic and factor analysis of the number and volume of fraudulent transactions with bank customers' funds is carried out. It is possible to reduce their number thanks to the joint actions of IT specialists and employees of the security services of banks, telecom operators, law enforcement agencies, and the regulator. To achieve greater efficiency in protecting client funds, the entire arsenal of available methods should be used, starting from the simplest, such as training in selfsecurity skills, and ending with complex scientific, methodological and technological methods.

Modeling and Performance Analysis of LBT-Based RF-Powered NR-U Network for IoT.

Energy harvesting combined with spectrum sharing offers a promising solution to the growing demand for spectrum while keeping energy costs low. New Radio Unlicensed (NR-U) technology enables telecom operators to utilize unlicensed spectrum in addition to the licensed spectrum already in use. Along with this, the energy demands for the Internet of Things (IoT) can be met through energy harvesting. In this regard, the ubiquity and ease of implementation make the RF-powered NR-U network a sustainable solution for cellular IoT. Using a Markov chain, we model the NR-U network with nodes powered by the base station (BS). We derive closed-form expressions for the normalized saturated throughput of nodes and the BS, along with the mean packet delay at the node. Additionally, we compute the transmit outage probability of the node. These quality of service (QoS) parameters are analyzed for different values of congestion window size, TXOP parameter, maximum energy level, and energy threshold of the node. Additionally, the effect of network density on collision, transmission, and energy harvesting probabilities is observed. We validate our model through simulations.

Comparative Study of Base Transceiver Stations Infrastructure Planning Using Machine Learning for Under Construction Area: A Case Study of Ibu Kota Nusantara

Communication is a fundamental human need that occurs directly or through technologies like telephones and signal transmitters such as BTS and satellites. Satellites, including Starlink, serve as additional solutions for internet access needs, particularly in remote areas, albeit higher costs remain a factor necessitating conventional BTS infrastructure development. Telecommunication operators face challenges in constructing BTS in areas with limited access and complex financial considerations due to low demand in rural areas, requiring careful planning. This study utilizes several supporting variables with the aid of machine learning techniques such as Linear Regression, SVR, Random Forest, and Gradient Boosting to forecast BTS requirements. Comparative analysis shows that the random forest machine learning method provides the best modeling results compared to linear regression, Gradient Boosting, and SVR methods. Despite the superior performance of the random forest method, further fine-tuning is still needed through parameter adjustments and evaluation of variables used to achieve an even better model. The modeling results can be utilized to predict the BTS infrastructure needs in IKN, estimated at 61,135 units. In BTS development planning, mobile operators can collaborate both among themselves and with Internet Service Providers (ISPs) utilizing satellite media. Utilizing shared towers can be an option for cost-efficient BTS infrastructure development.

Impact of 5GTechnology on Mobile Internet Usage in Japan

Purpose: To aim of the study was to analyze the impact of 5G technology on mobile internet usage in Japan. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The rollout of 5G technology in Japan has led to a 35% increase in mobile internet usage, with users enjoying faster speeds and improved online experiences. This enhancement supports high-bandwidth applications like video streaming and gaming, and benefits businesses by facilitating remote work and innovative services such as augmented reality (AR) and the Internet of Things (IoT). However, substantial infrastructure investments are needed to ensure widespread coverage and reliability. Unique Contribution to Theory, Practice and Policy: Diffusion of innovations theory, technology acceptance model (TAM) & network externalities theory may be used to anchor future studies on impact of 5G technology on mobile internet usage in Japan. Practically, businesses and mobile service providers in Japan can leverage 5G to develop and deploy innovative services such as augmented reality (AR) applications, real-time gaming experiences, and immersive virtual communication platforms. Policymakers can develop frameworks that facilitate fair competition among telecom operators while promoting investment in 5G infrastructure.

Evaluating the Effectiveness of 5G Technology in Enhancing Mobile Network Performance in South Korea

Purpose: The aim of the study was to evaluate the effectiveness of 5G technology in enhancing mobile network performance in South Korea. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: South Korea's adoption of 5G technology has significantly enhanced mobile network performance. The deployment of 5G has resulted in vastly improved download and upload speeds, reduced latency, and better network reliability compared to previous technologies. This advancement has enabled smoother and more reliable mobile internet experiences, facilitating new applications such as augmented reality (AR), virtual reality (VR), and Internet of Things (IoT) devices. Unique Contribution to Theory, Practice and Policy: Diffusion of innovations theory, technology acceptance model (TAM) & resource-based view (RBV) theory may be used to anchor future studies on evaluating the effectiveness of 5G technology in enhancing mobile network performance in South Korea. Develop practical guidelines for telecom operators on the deployment and optimization of 5G networks. These guidelines should address best practices for infrastructure development, spectrum management, and network configuration to maximize performance. Advocate for the establishment of comprehensive regulatory frameworks that support the widespread deployment of 5G technology.

O-band QKD link over a multiple ONT loaded carrier-grade GPON for FTTH applications.

We have successfully demonstrated the integration of a commercial O-band Quantum Key Distribution (QKD) system over a testbed that replicates a carrier-grade Fiber-to-the-Home (FTTH) optical access network consisting of components and systems installed in real-life FTTH operational deployments. The experiment demonstrated a QKD transmission over a 1:16 user Gigabit Optical Passive Network (GPON) configuration featuring a total of 9 Optical Network Terminals (ONTs) at the premises of the Telecom Operator COSMOTE that followed the operator's standard FTTH divided in two splitting stages. The architecture we implemented was a downstream access network with the quantum transmitter located at the operator's Central Office (CO) and the quantum receiver located on the end user's side.

Development of novel intrusion detection in Internet of Things using improved dart game optimizer‐derived optimal cascaded ensemble learning

AbstractBackground of the StudyInternet of things (IoT) industry has accelerated its development with the support of advanced information technology and economic expansion. A complete industrial foundation includes software, chips, electronic components, IoT services, integrated systems, machinery, and telecom operators, which the gradual improvement in the IoT industry system has formulated. As the exponential growth of IoT devices increases, the attack surface available to cybercriminals enables them to carry out potentially more damaging operations. As a result, the security sector has witnessed a rise in cyberattacks. Hackers use several methods to copy and modify the information in the IoT environment. Machine learning techniques are used by the intrusion detection (ID) model to determine and categorize attacks in IoT networks.ObjectivesThus, this study explores the ID system with the heuristic‐assisted deep learning approaches for effectively detect the attacks in the IoT. At first, the IoT data are garnered in benchmark resources. Then, the gathered data is preprocessed to perform data cleaning. Next, the data is transformed and fed to the feature extraction stage. The feature extraction is performed with the help of one‐dimensional convolutional neural network (1D‐CNN), where the features are extracted from the target‐based pooling layer. Then, these attained deep features are fed to the ID phase, where the cascaded ensemble learning (CEL) approach is adopted for detecting the intrusions. Here, the hyperparameter tuning is done with a new suggested improved darts game optimizer (IDGO) algorithm. Here, the main objective of the developed algorithm helps to maximize accuracy in ID.FindingsThroughout the experimental findings, the developed model provides 86% of accuracy. Thus, the finding of the developed model shows less detecting time and higher detection efficiency.

Features and Perspectives of the Market of Information and Communication Technologies’ Functioning in Data-Driven Society

The article is intended to define the conceptual prospects for the development of the information and communication technologies market in a data-driven society. According to the results of the study, it was established that the implementation of innovative technological startups for the reorganization of information and communication networks using modern switching equipment, characterized by high performance, remains a relevant and global task for the development of the target market. This will provide potential opportunities for providing a high level of service to several numbering zones at once and maintaining the availability of a wide range of information and communication services in the modern conditions of digitalization of society. It was determined that the sphere of communication and information occupies an important place in the economic and social revival of Ukraine. Broad access to significant amounts of information and database management ensures the efficiency of organization and management of state, production and non-production processes of economic activity, thereby expanding the possibilities of successful business, optimizing costs and ensuring a high level of economic and information security of the business entities. The information and telecommunications market were analyzed and the activity of participating operators was diagnosed. It has been studied that in a data-driven society, the success of achieving goals in the digital development of information and communication enterprises directly depends on global information influence. A significant reduction in the number of telecommunications operators and providers was analyzed. It was determined that small operators of the target market are not able to ensure the appropriate level of quality, availability and continuity of service, in connection with which a significant part of the target audience switches to the services of large providers. Based on the analysis of the main indicators of the development of the information and communication technologies market, the main promising directions of development based on the formation of income from a diverse pool of services are determined.

Perception and social acceptance of 5G technology for sustainability development

This research was carried out to enable a better understanding of the attitudes of Hungarian consumers and future users towards 5G technology. The development of 5G technology supports social, economic and environmental sustainability together. Among other things, innovative communities, economic progress and a reduction of the carbon footprint can be positive outcomes of 5G. For example 5G benefits the environment in two ways: it helps telecom operators reduce their energy usage, thus lowering their environmental impact, and it provides tools that telecom companies can use to assist others in reducing their environmental footprint. The Partial Least Squares (PLS) regression method was used to establish the correlations between the five factor groups. Research indicates a prevalent skepticism among Hungarian consumers toward 5G technology, characterized by apprehensions regarding health risks and a lack of perceived competitive advantages or inherent business benefits to adopting 5G. This hesitancy must be countered by transparently addressing health concerns, debunking myths, and building a foundational trust in 5G technologies through comprehensive educational and awareness-raising initiatives, aligning technological advancements with consumer confidence and acceptance. 5G must be demystified so that consumers will come to trust the technology and embrace its adoption. Due to the similar technological conditions and historical backgrounds of the Central European Countries (CEC), the results of this research will prove useful to policymakers throughout the region.

Reducing carbon emissions through sustainable energy integration at off-grid cellular sites: a case study of Nepal

ABSTRACT Information and communication technology is the key enabler for digitalisation and increased productivity in cross-cutting sectors. Telephone towers are the main infrastructure to enable digital connectivity and renewable energy sources are used to supply power to mobile towers at off-grid areas. In this paper, the economic and environmental aspects of sustainable energy supply in off-grid sites have been evaluated. Three stand-alone sites having solar PV, diesel generators, and hybrid power solutions integrated with battery storage are taken for the study. The result shows the solar PV solution is economically feasible with an energy cost of 0.18$/kWh and environmentally adaptable. The diesel generator power supply has a higher energy cost of 0.59$/kWh and abundant CO2 emission of 421.85tCO2 for a life period. The hybrid power solution has better energy cost(0.38$/kWh) and CO2 emission (213.72tCO2) than the diesel generator. Considering reliability, the hybrid power solution has better performance in terms of energy cost and GHG emission. Solar PV solution has a key role in developing green infrastructure. A solar PV system integrated with a diesel generator and battery storage is a must for an uninterrupted power supply. The outcomes of the study encourage telecom operators to go for green cell towers sustainably.

A Stakeholder Needs Analysis in Cybersecurity: A Systemic Approach to Enhancing Digital Infrastructure Resilience

The escalating complexity and sophistication of cyber threats necessitate advanced solutions that not only counteract these threats but also proactively adapt to the evolving needs of diverse stakeholders involved in digital infrastructures, such as telecom operators, cloud service providers, and end-users in sectors like healthcare and finance. This research addresses a crucial gap by focusing on a systemic, AI-powered approach to stakeholder needs analysis in cybersecurity. By aligning closely with stakeholder requirements, the proposed framework aims to offer dynamic, responsive cybersecurity solutions that enhance the resilience of digital infrastructures against evolving cyber threats. This research systematically maps the landscape of stakeholder needs in cybersecurity across different sectors through qualitative methods like interviews and focus groups, supplemented by data from the CyberSecDome project’s pilot cases and open calls. Requirements for an AI-driven framework are then formulated based on these data to identify patterns and predict stakeholder needs. The analysis reveals critical challenges faced by stakeholders, including limited threat intelligence sharing, insufficient automation in incident response, and regulatory hurdles related to data protection laws and evolving cybersecurity legislation. There is a strong interest in leveraging AI for enhanced intrusion detection, real-time threat intelligence sharing, and privacy-preserving information exchange.

Assessing the effectiveness of OTT services, branded apps, and gamified loyalty giveaways on mobile customer churn in the telecom industry: A machine-learning approach

Telecom operators allocate a significant amount of resources to retain their customers as the organic growth in the number of customers is slowing down. Gamified loyalty programs, branded apps, and over-the-top (OTT) services emerged as ways to develop customer acquisition and retention strategies. Despite these strategies, some mobile customers still churn; therefore, churn prediction plays an essential role in the sustainable future of telecom businesses. Churn prediction is used both to detect customers with a high propensity to churn and to identify the reasons behind their churn behavior. This study examines several features affecting the churn behavior of mobile customers, including branded apps, gamified loyalty programs, and OTT services. In this study, the secondary data is provided by a telecom operator and contains the attributes of both churner and non-churner mobile customers. Logistic regression and random forest classifiers are compared in terms of their predictive power, and we used the latter as the machine learning algorithm in the churn prediction model. To understand the variable importance, mean decrease in impurity and permutation importance are performed. The key findings of this research reveal that while gamified loyalty giveaways and branded app strategies are effective, OTT service strategies show lower importance in predicting mobile customer churn behavior.

Research on optimal dispatch of 5G base station VPP with standby energy storage

Abstract With the rapid increase in the construction of 5G base stations, the backup battery of 5G base stations will be a huge potential energy storage resource. China’s electricity market reform is constantly advancing, and the study of 5G base stations’ standby energy storage to participate in power optimization dispatch is an effective way to realize the reciprocal benefits of power grids and telecommunication operators. Considering the special characteristics of 5G base station backup energy storage to participate in the power market, the article establishes a virtual power plant of 5G base station considering the backup energy storage. Then, the 5G base station VPP is added to the operation of the power grid as an adjustable resource, and the dual-5G base station VPP optimization matrix is built. Finally, a numerical example verifies that the standby energy storage of the 5G base station contains rich schedulable capacity and that the 5G base station VPP can validly improve the economy of power grid operation.

Design of a large language model for improving customer service in telecom operators

AbstractTelecommunications operators are tasked with enhancing service quality, reducing operational costs, and preserving customer privacy. This study presents an innovative application of large language models (LLMs) integrated with the LangChain technology framework, aimed at revolutionizing customer service in the telecom sector. The LangChain framework features a Knowledge Organizing Module and a Knowledge Search Module, both designed to refine customer support operations. The research develops an LLM‐based approach to improve the segmentation and organization of knowledge bases, tailored for the telecommunications industry. This approach ensures seamless integration with existing LLMs while preserving distinct knowledge domains, crucial for search accuracy. Additionally, the framework includes an advanced information security protocol with a robust filtering system that effectively excludes sensitive data from the model's outputs, enhancing data security. Empirical findings indicate that the ChatGLM2‐6B+LangChain model outperforms the baseline ChatGLM2, demonstrating heightened effectiveness in telecom‐specific tasks and outstripping even more sophisticated models like GPT‐4. The implementation of this LLM‐based framework within telecom customer service systems has significantly sharpened the precision of knowledge recommendations, as reflected by a dramatic increase in acceptance rates from 15% to 70%.

A decision model for OTT service users to adopt wireless D2D caching networks: Exploring the Korean case

As many Over-The-Top (OTT) users opt for mobile devices, mobile network traffic surges. However, current mobile communication technology faces difficulties. To provide a stable video content consumption experience to users, reliable alternatives must be found to resolve the limitation of the conventional approach. Accordingly, wireless Device-to-Device (D2D) caching networks have gained attention as a reliable alternative. Considering it can reduce network-related overheads, save related costs, and improve OTT video consumption environment, there is a high possibility that telecommunication operators want to commercialize this technology. To commercialize wireless D2D caching networks, users need to share their resources, such as personal information, smartphone storage, and battery. This study explores the decision-making process of mobile OTT users regarding D2D caching adoption on their mobile devices in Korea. An online survey of 94 respondents was conducted in South Korea. By using the analytic hierarchy process (AHP) approach, this study devised an evaluation model that includes three major factors: perceived benefits, perceived costs, and perceived situational conditions. The results reveal that risks, rather than situational factors and benefits, predominantly influence user intentions and strategies. Streaming video content via mobile data or Wi-Fi is viewed as the most feasible choice. Moreover, users show a preference for pre-downloading video content over adopting wireless D2D caching networks on their mobile devices. The findings provide a guideline for understanding the responses of mobile OTT service users and their priorities in responding to adopting wireless D2D caching networks.

Study of Consumer Behaviour Towards Reliance Jio

The main objective of this project is to study the awareness of Reliance Jio amongst the customers compared to other telecom service providers. The satisfaction of customers is very important and with various products and services offered by the company its customers seem to be meaningless if it‟s not beneficiary to the customer from their end, so the second objective of this research is to study the customer satisfaction level of customers towards Reliance Jio and its services. To achieve success in long run a company needs a thorough study of its SWOT analysis (Strength, Weakness, Opportunities, and Threats). So the third objective of this research is to find the market potential and market penetration of Reliance Jio products and services. Reliance JioInfocomm Limited (Commonly called RJIL) is an Indian Internet access (commonly called „Broadband‟) and telecommunications company headquartered in Mumbai India‟s largest private sector company, is the first telecom operator to hold pan India Unified License. Reliance Jio is setting up a pan India telecom infrastructure to provide fourth generation LTE TDD high speed wireless internet and mobile communication services which was then launched in June 2015. Reliance Jio was founded in 2010 by MukeshAmbani. Reliance Jio offers mobile telephony and wireless broadband. Parent company of Reliance Jio is Reliance Industries and its subsidiary is LYF. To study the objectives discussed two types of sources were used to collect the data: - Primary and Secondary data. Primary data is also called as „First-hand data‟ or „Raw data‟. The primary data primarily means the unfiltered raw data collected by the researcher in the research process. In this project for the primary data a sample of 40 people were surveyed.