Telecom Operators Research Articles

User acceptance of AI voice assistants in Jordan’s telecom industry

Purpose:This study aims to understand factors influencing consumer acceptance of artificial intelligence (AI) voice assistants used in customer support within telecom companies in Jordan. Methodology:A survey was conducted involving 248 individuals who have experience with telecom support services. To evaluate consumer acceptance, the study incorporates the Unified Theory of Acceptance and Use of Technology (UTAUT) framework and extends it with attributes specific to AI, such as Perceived Reliability, Voice Quality, and Quality of Information. Advanced statistical methods, including structural equation modeling with SPSS AMOS 28 and SmartPLS, were utilized to analyze the collected data. Findings:The results revealed that Perceived Reliability and Quality of Information were significant predictors of AI voice assistant adoption in the telecom sector, while traditional factors such as Perceived Usefulness and Trust showed no significant impact. These findings suggest that performance-related elements play a more crucial role in user acceptance of AI in this context compared to earlier technological acceptance models. Implications:The study offers an expansion to traditional technology acceptance models by highlighting the importance of AI-specific attributes over conventional factors like Perceived Usefulness and Trust. For telecom operators in developing markets, this research provides guidance on enhancing customer engagement with AI voice assistants. It suggests focusing on improving the reliability and quality of information provided by AI systems to boost user acceptance. Originality/value:The study provides valuable insights into the changing dynamics of consumer acceptance of AI in customer support, emphasizing a shift toward performance-based criteria. Telecom companies in Jordan can use these findings to inform their AI adoption strategies and enhance customer satisfaction.

The Power of TaaS: Challenges and Considerations of TaaS Adoption

Telecom as a Service (TaaS) is an emerging model based upon cloud infrastructure supporting telecommunications functions more cost-effectively and flexibly. The growth of TaaS adoption is explored in this research, and the major benefits to its adoption by telecom operators, including reduced cost, scalability, and perfect service delivery, are identified. However, organizations have to face several challenges when adopting TaaS. Security, regulatory compliance, and data privacy are all key issues. TaaS is a security vulnerability and compliance that is particularly complex across different legal jurisdictions, as it runs in a cloud environment. Also, safeguarding user data on privacy regulations remains a big deal. We discuss these challenges and propose strategies to overcome them so that telecom customers can have secure, compliant, and private TaaS.

AI-based optimization of EM radiation estimates from GSM base stations using traffic data

The fast expansion of mobile networks has sparked worries regarding base station EM radiation's health impacts. Traffic load is commonly ignored when evaluating EM radiation levels using maximum power output. This study proposes utilizing AI and ML on real network traffic data to optimize GSM base station EM radiation estimations. We obtained EM radiation measurements and traffic data from selecting GSM base stations by location and configuration. To predict EM radiation levels, traffic patterns were used to train linear regression, random forests, and neural networks. Base stations were clustered by radiation profile using unsupervised learning. Considering regulatory restrictions and measurement feasibility, an optimization methodology was created to minimize EM radiation estimate inaccuracy. The results show better prediction accuracy than power-based estimations and high generalisability across base station types. Site-specific factors influenced daily EM radiation patterns after clustering. EM radiation levels can be monitored using traffic data and the optimized AI/ML model. This research helps telecom operators and regulators analyze EM radiation more accurately and efficiently. Future projects should include 5G and small cell network extensions and intelligent city platform integration. The suggested method develops data-driven, AI-powered Public Safety and mobile network trust solutions.

Probability Modeling of Customer Switching Behavior and Voice Tariff Disparities in Tanzanian Telecom Markets

The telecommunications sector has experienced significant growth, driven by technological advances, improved internet access, investment from both the private and public sectors, and competitive pricing. Therefore, it is crucial to understand the factors that influence customer switching. This study examines voice tariff disparities between telecommunications operators in Tanzania and determines the probability of customer switching behavior. This was achieved by analyzing the relationship between tariff differences and the likelihood of customers switching service providers. A quantitative research approach was used using secondary data from the Tanzania Communications Regulatory Authority (TCRA), covering the period from the quarter ending March 2023 to the quarter ending June 2024. Descriptive statistics and logistic regression were used to model the effects of tariffs on switching behavior. Findings indicated that higher local SMS and on-net voice tariffs significantly increase the probability of customers switching providers, while higher international voice tariffs surprisingly reduce the likelihood of customer switching behavior. The study concluded that competitive pricing, particularly in SMS and local voice services, is essential for customer retention. It recommends that telecom operators focus on cost-effective service offerings and improve network quality to minimize churn. Future research should explore the dynamics behind the lower switching tendency for international services to enhance retention strategies for premium service users.

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.

Multi-point vibration positioning method for long-distance forward transmission distributed vibration sensing.

Observation of intensity, phase, or polarization properties of light propagating through telecom submarine cables can enable widespread monitoring of geological and undersea events, such as earthquakes, tsunamis, and shipping lane traffic. We conducted a comparative analysis of external physical perturbations acting on submarine optical cables and unprotected optical fibers; introduced both intensity and phase demodulation-based sensing systems for long-distance vibration sensing; presented an extension to the phase-spectrum time delay method for forward-transmission distributed sensing (same as optical communications) to distinguish and quantify multiple simultaneous vibration events; and overcame the previous spatial resolution fundamental lower limit set by the time-domain sampling rate. We experimentally demonstrated multi-vibration positioning over 202.3 km single-span sensing distance, with a positioning accuracy as small as 17.9 m for sinewave vibrations, and a spatial resolution of 1.25 m. Other key sensor parameters include phase sensitivity of 40.6 mrad/µε @ 80 Hz, a corresponding limit of detection (LoD) of 101.7 pε/Hz1/2, intensity sensitivity of 7.1%/µε @ 80 Hz, and a corresponding LoD of 20.1 pε/Hz1/2. The tested frequency range was 0.01-100 Hz. No signal averaging was performed during signal processing to allow faster real-time processing, which would otherwise further improve the results. This forward transmission approach has the potential to upgrade the existing submerged global internet fiber-optic network into a vast ocean-spanning observation network while allowing telecom operations to operate normally without sacrificing bandwidth.

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.