Search Results (195)

Call Detail Records (CDRs) from mobile networks offer valuable insights into both network performance and user behavior. With the growing importance of data analytics, analyzing CDRs has become critical for optimizing network resources by forecasting demand across spatial and temporal dimensions. In this study, we examine publicly available CDR data from Telecom Italia to explore the spatiotemporal dynamics of mobile network activity in Milan. This analysis reveals key patterns in traffic distribution highlighting both high- and low-demand regions as well as notable variations in usage over time. To anticipate future network usage, we employ both Automated Machine Learning (AutoML) and the transformer-based TimeGPT model, comparing their performance against traditional forecasting methods such as Long Short-Term Memory (LSTM), ARIMA and SARIMA. Model accuracy is assessed using standard evaluation metrics, including root mean square error (RMSE), mean absolute error (MAE) and the coefficient of determination (R²). Results show that AutoML delivers the most accurate forecasts, with significantly lower RMSE (2.4990 vs. 14.8226) and MAE (1.0284 vs. 7.7789) compared to TimeGPT and a higher R² score (99.96% vs. 98.62%). Our findings underscore the strengths of modern predictive models in capturing complex traffic behaviors and demonstrate their value in resource planning, congestion management and overall network optimization. Importantly, this study is one of the first to Comprehensively assess AutoML and TimeGPT on a high-resolution, real-world CDR dataset from a major European city. By merging machine learning techniques with advanced temporal modeling, this study provides a strong framework for scalable and intelligent mobile traffic prediction. It thus highlights the functionality of AutoML in simplifying model development and the possibility of TimeGPT to extend transformer-based prediction to the telecommunications domain. Full article

This study examines how contract structures influence coordination and innovation incentives in dual-channel telecommunications supply chains. We consider a setting where a mobile network operator (MNO) supplies services both directly to consumers and indirectly through a mobile virtual network operator (MVNO), which competes in the retail market. Using a game-theoretic framework, we evaluate how different contracts—single wholesale pricing, revenue sharing, and quantity discounts—shape strategic decisions, particularly in the presence of investment spillovers between parties. A key coordination problem emerges from the externalized gains of innovation, where one party’s investment generates value for both participants. Our results show that single wholesale and revenue sharing contracts often lead to suboptimal investment and profit outcomes. In contrast, quantity discount contracts, especially when combined with appropriate transfer payments, improve coordination and enhance the total performance of the supply chain. We also find that innovation led by the MVNO, while generally less impactful, can still yield reciprocal benefits for the MNO, reinforcing the value of cooperative arrangements. These findings emphasize the importance of contract design in managing interdependence and improving efficiency in decentralized supply chains. This study offers theoretical and practical implications for telecommunications providers and policymakers aiming to promote innovation and mutually beneficial outcomes through well-aligned contractual mechanisms. Full article

Ensuring reliable communication in remote or disaster-affected areas is a technical challenge due to unplanned deployment and mobilization, meaning placement difficulties and high operation costs of conventional telecommunications infrastructures. To address this problem, unmanned aerial vehicles (UAVs) have emerged as an excellent alternative to provide quick connectivity in remote or disaster-affected regions at a reasonable cost. However, the limited battery autonomy of UAVs restricts their flight service time. This paper proposes a communication system based on a tethered UAV (T-UAV) capable of continuous operation through a wired power network connected to a ground station. The communications system is based on low-cost devices, such as Raspberry Pi platforms, and offers wireless IP telephony services, providing high-quality and reliable communication. Experimental tests assessed power consumption, UAV stability, and data transmission performance. Our results prove that the T-UAV, based on a quadcopter drone, operates stably at 16 V and 20 A, ensuring consistent VoIP communications at a height of 10 m with low latency. These experimental findings underscore the potential of T-UAVs as cost-effective alternatives for extending or providing communication networks in remote regions, emergency scenarios, or underserved areas. Full article

The 3rd Generation Partnership Project (3GPP) evolution of mobile communication technologies from 5G to 6G has been a transformative journey spanning a decade, shaped by six releases from Release 15 to Release 20. This article provides a retrospective of this evolution, highlighting the technical advancements, challenges, and milestones that have defined the transition from the foundational 5G era to the emergence of 6G. Starting with Release 15, which marked the birth of 5G and its New Radio (NR) air interface, the journey progressed through Release 16, where 5G was qualified as an International Mobile Telecommunications-2020 (IMT-2020) technology, and Release 17, which expanded 5G into new domains such as non-terrestrial networks. Release 18 ushered in the 5G-Advanced era, incorporating novel technologies like artificial intelligence. Releases 19 and 20 continue this momentum, focusing on commercially driven enhancements while laying the groundwork for the 6G era. This article explores how 3GPP technology evolution has shaped the telecommunications landscape over the past decade, bridging two mobile generations. It concludes with insights into learned lessons, future challenges, and opportunities, offering guidelines on 6G evolution for 2030 and beyond. Full article

This paper presents two innovative wireless network designs for the automation system of the Sof-Algeen water station in Zintan, addressing the challenge of connecting field instruments—such as pressure switches, solenoid valves, and differential pressure sensors—over distances of up to 4 km. Due to high costs, limited flexibility, and scalability concerns, traditional hardwired solutions are impractical for such distances. A comprehensive analysis of various Industrial Internet of Things (IIoT) network designs determined that the IEEE 802.11 standard and Phoenix Contact’s Trusted Wireless technology best meet the project’s requirements for long-distance connectivity, real-time data acquisition, system compatibility, and compliance with national telecommunications regulations. This study proposes optimal network designs using the IEEE 802.11 standard and a hybrid mesh and star network for Trusted Wireless, and evaluates these technologies based on performance, reliability, and infrastructure compatibility using simulation. The network designs were validated using the Radio Mobile tool, considering the water station’s specific terrain and wireless module parameters. The findings indicate distinct differences in structure, operation, and cost-effectiveness between the two proposed solutions, highlighting the benefits of each in achieving optimal link feasibility for robust water station automation. Full article

The inherent characteristics of blockchain, including immutability, self-execution, and the removal of intermediaries, consistently generate increasing interest in its applications within the telecom sector, making it an exciting area for investment. This literature review aims to explore a promising research area known as blockchain interoperability. Interoperability seeks to connect two or more independent blockchains to effectively exchange information. Through leveraging the interoperability features of blockchain, independent telecom networks can seamlessly share information with other mobile, fixed, and next-generation networks. This results in improved security and efficiency, cost savings, and an enhanced customer experience. This study reviews highly cited research papers in the literature to assess blockchain’s relevance to telecom use cases for interoperability. Additionally, it presents prominent interoperability solutions and identifies essential requirements for the successful implementation of blockchain interoperability in the telecom sector. The findings highlight key research gaps and future directions for the adoption of blockchain in telecommunications, particularly for the forthcoming sixth generation (6G). Full article

(1) Research Highlights: Existing studies primarily focus on the supply-side evaluation of urban forest accessibility, emphasizing physical proximity while often overlooking real-time usage patterns and demographic-specific exposure. This study shifts the focus to social exposure, analyzing how diverse population groups interact with urban forests across different times of the day, integrating dynamic accessibility metrics. (2) Background and Objectives: Unlike previous research that predominantly assessed urban forest accessibility through conventional models based on static spatial proximity, this study incorporates spatiotemporal population distribution data to capture actual utilization patterns. By introducing a dynamic, exposure-based framework, this research aims to facilitate equitable and temporally sensitive access to green spaces across diverse demographic groups. (3) Materials and Methods: This study focuses on Seoul, South Korea, and applies the Gaussian-based Two-Step Floating Catchment Area (G2SFCA) methodology to assess urban forest accessibility. Living population data (2021–2024) from mobile telecommunications sources were used as demand indicators, while OpenStreetMap (OSM) green space data were utilized as supply indicators. Realistic travel distances were calculated using OSM pedestrian networks and Dijkstra’s algorithm, incorporating slope effects and distance decay functions. A K-means clustering algorithm was applied to classify four distinct exposure types based on demographic and temporal variations. (4) Results: The findings reveal significant disparities in urban forest exposure based on age group and time of day. Four major urban forest exposure patterns were identified: Type A—school-age children, with peak usage around midday; Type B—working-age adults, frequenting mid-sized urban forests during commuting and leisure hours; Type C—elderly individuals, utilizing large-scale urban forests and neighborhood parks mainly in the morning; Type D—young adults, engaging with small urban parks and rest areas at various times. (5) Conclusions: Urban forest management must move beyond the quantitative expansion of green spaces and instead implement customized policies that optimize accessibility and equitable distribution based on distinct temporal and demographic patterns of social exposure. By integrating real-time urban mobility data into urban forest planning, policies can better align green space supply with actual usage, fostering a more equitable, data-driven, and sustainable urban green infrastructure. Full article

A literature review is presented on energy consumption and heat transfer in recent fifth-generation (5G) antennas in network base stations. The review emphasizes on the role of computational science in addressing emerging design challenges for the coming 6G technology, such as reducing energy consumption and enhancing equipment thermal management in more compact designs. It examines the contributions of (i) advanced modeling and simulation sciences, including antenna modeling and design, the use of (ii) computational fluid dynamics (CFD) and heat transfer, and (iii) the application of artificial intelligence (AI) in these settings. The scientific interactions and collaborations between these scientific multidisciplinary approaches are vital in the effort to develop innovative 6G thermal equipment designs. This is essential if we are to overcome the current scientific barriers and challenges faced by this evolving technology, where the rapid transition from 5G to 6G will shape the expanding fields of deploying smaller satellites into lower orbits in outer space. Full article

Modern businesses increasingly rely on chatbots to enhance customer communication and automate routine tasks. The research aimed to determine the optimal configurations of a telecommunications chatbot on the Rasa Pro platform, including the selection of large language models (LLMs), prompt formats, and command structures. The impact of various LLMs, prompt formats, and command precision on response quality was analyzed. Smaller models, like Gemini-1.5-Flash-8B and Gemma2-9B-IT, can achieve results comparable to larger models, offering a cost-effective solution. Specifically, the Gemini-1.5-Flash-8B model achieved an accuracy improvement of 21.62 points when using the JSON prompt format. This emphasizes the importance of prompt engineering techniques, like using structured formats (YAML, JSON) and precise commands. The study utilized a dataset of 400 sample test phrases created based on real customer service conversations with a mobile phone operator’s customers. Results suggest optimizing chatbot performance does not always require the most powerful models. Proper prompt preparation and data format choice are crucial. The theoretical framework focuses on the interaction between model size, prompt format, and command precision. Findings provide insights for chatbot designers to optimize performance through LLM selection and prompt construction. These findings have practical implications for businesses seeking cost-effective and efficient chatbot solutions. Full article

The paper intends to contribute to readers’ comprehension of the Greek telecommunications market, focusing on the strategic decisions associated with network tower-sharing analysis in Greece. The Greek telecommunications industry is described for the first time following the Structure–Conduct–Performance (SCP) paradigm of Industrial Organisation (IO), as a methodological tool of analysis. In that respect, an SCP model in its extended form is constructed, aiming to examine how structure, conduct, and performance interrelate to each other. More precisely, the SCP model explains how strategic decisions regarding tower infrastructure sharing between 2013–2022 were developed, as a result of a series of interactions and feedback effects, amongst market structure, operators’ conducts, and performances, resulting in strengthening competition and reshaping market structure with the entrance of a new player in the Greek mobile market, an independent TowerCo (Athens, Greece) in Greece. International tendencies and competition issues influencing domestic growth potentialities and alternative operators’ concentration will be addressed, too. The paper concludes with presenting a basically qualitative, explanatory interpretive analysis of the perspectives of network tower-sharing analysis in the Greek telecommunication industry, including policy recommendations for the near future and thoughts on future research, as well. Full article

Spectrum auctions in international mobile telecommunications (IMT) are a representative method for selling the right to transmit signals within a specific band of electromagnetic waves to communication service providers (CSPs); it is important to design a fair spectrum auction that can benefit both government and auction bidders. The government should reduce the burden of maintenance costs by setting a reasonable initial price and selling it to bidders at the highest price they can afford. However, due to the complex auction rules and decision-making process, not many studies has been conducted on how to select an appropriate initial price for the auction. This study aims at introducing a novel simulation modeling approach to develop a spectrum auction policy for international mobile telecommunications (IMT) using agent-based simulation (ABS), which involves three telecommunications service provider types (i.e., the Aggressive bidder, the Moderate bidder, and the Conservative bidder) and the auction environment of IMT in South Korea. In particular, the proposed approach adopts the exponential utility theory to model the behavior of auction bidders and identify the optimal initial bid price. The devised ABS model is calibrated to the IMT spectrum auction conducted in 2018 in South Korea, and the best initial pricing policy identified (i.e., $85.24 million per spectrum block) regarding a sustainable market environment for existing service providers (i.e., 10 blocks for the Aggressive bidder, 10 blocks for the Moderate bidder, and 8 blocks for the Conservative bidder). The proposed approach will be beneficial to both government agencies and auction bidders under fair competition in the IMT market. Full article

Unmanned aerial vehicles (UAVs) significantly shape the evolution of 5G and 6G technologies in India, particularly in reconfiguring communication networks. Through their deployment as base stations or relays, these aerial vehicles substantially enhance communication performance and extend network coverage in areas characterized by high demand and challenging topographies. Accurate modelling of the UAV-to-ground channel is imperative for gaining valuable insights into UAV-assisted communication systems, particularly within India’s rapidly expanding metropolitan cities and their diverse topographical complexities. This study proposes an approach to model low-altitude channels in urban areas, offering specific scenarios and tailored solutions to facilitate radio frequency (RF) planning for Indian metropolitan cities. The proposed model leverages the International Telecommunication Union recommendation (ITU-R) for city mapping and utilizes frequency ranges from 1.8 to 6 GHz and altitudes up to 500 m to comprehensively model both line-of-sight (LoS) and non-line-of-sight (NLoS) communications. It employs the uniform theory of diffraction to calculate the additional path loss for non-line-of-sight (NLoS) communication for both vertical and horizontal polarizations. The normal distribution for additional shadowing loss is discerned from simulation results. This study outlined the approach to derive a comprehensive statistical channel model based on the elevation angle and evaluate model parameters at various frequencies and altitudes for both vertical and horizontal polarization. The model was subsequently compared with existing models for validation, showing close alignment. The ease of implementation and practical application of this proposed model render it an invaluable tool for planning and simulating mobile networks in urban areas, thus facilitating the seamless integration of advanced communication technologies in India. Full article

App-based marketing has been widely used in the telecommunications industry to both serve and draw in new customers. Typically, telecom providers must invest an amount of company resources to develop and maintain the operations mechanism of information technology platforms (e.g., mobile apps); therefore, it is important to take the issue of marketing effectiveness into account. For example, the mismatch between what telecom providers offer in their mobile apps and customers’ marketing requirements plays a significant role in determining unmet knowledge and presentation gaps that are related to the marketing domain. This research intends to propose an integrated Fuzzy MCDM model based on 4Ps (Product, Price, Place, Promotion) and 4Cs (Customer Needs, Cost, Convenience, Communication) models for evaluating mobile telecom applications (MTAs). Therefore, the 4Ps and 4Cs models are extended to develop a hierarchy model for evaluating MTAs. Next, fuzzy theory is applied to handle the subjectiveness of qualitative evaluation criteria while the Analytic Hierarchy Process (AHP) is applied to synthesize the weight and score of the evaluation criteria. The proposed model is applied to evaluate, rank, and analyze the MTA of three telecom providers in the Kingdom of Saudi Arabia (KSA) (e.g., STC, Zain, and Mobily). The conducted case study ensures the usability and applicability of the proposed model. The evaluation results offer several managerial actions for achieving ideal app-based marketing. Full article

Integrated Sensing and Communication (ISAC) systems have emerged as a key component for Sixth Generation (6G) networks, enhancing resource efficiency and enabling diverse applications. Currently, ISAC systems have been recognized as a leading trend for future standardization, i.e., International Mobile Telecommunications (IMT)-2030. As in the previous IMT-2020 standardization, the emphasis has been on developing a methodology for assessing network conditions, with one of the crucial approaches incorporating system-level simulations. However, within this framework, there has been a notable absence of proposed abstractions for the physical layer of ISAC systems, which are valuable for system-level simulators. The physical abstraction process helps reduce computational simulation costs, enabling efficient and rapid evaluation of system conditions. Therefore, this paper aims to fill this gap by outlining the key aspects and metrics recommended for a physical layer abstraction in sensing applications within ISAC frameworks. Applying physical abstraction in the context of target localization and detection algorithms may enable an initial understanding and evaluation of ISAC system performance. These algorithms are proposed as an example of simulating the sensing functionalities to be abstracted, which are based on a stochastic geometric channel model. Orthogonal Frequency Division Multiplexing (OFDM) symbols play a crucial role in target position estimation. The findings show that doubling OFDM symbols improves the detection probability by 3 dB in terms of Signal to Noise Ratio (SNR). Finally, the proposed Physical Layer Abstraction (PLA) method produces performance metrics as figures and lookup tables tailored for system-level simulators. Full article

Veterans living in rural areas of the United States face various health challenges that demand timely access to care to improve their well-being and quality of life. Telehealth (i.e., the use of telecommunications technology to connect people with care providers remotely) has become vital in addressing the accessibility gap for people constrained by vehicle ownership, income, geographic isolation, and limited access to specialists. This study aims to examine the current evidence on rural veterans’ use of telehealth for their healthcare needs, evaluates the cost savings associated with telehealth, as well as veterans’ use of telehealth during COVID-19. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic search was conducted on three databases (Google Scholar, PubMed, and Scopus) to select relevant articles published from 2017 to 2023. A total of 36 articles met the inclusion criteria and were categorized into three objectives: veterans’ medical conditions managed through telehealth (n = 24), veterans’ transportation cost savings using telehealth (n = 4), and telehealth use during the COVID-19 pandemic (n = 8). The results indicated that telehealth is a viable option for managing various medical conditions of rural veterans, including complex ones like diabetes and cancer. Additionally, telemedicine was a useful platform in bridging the healthcare accessibility gap during disasters or pandemics like COVID-19 evident from its increased usage during the pandemic. Lastly, telehealth was associated with cost and time savings between USD 65.29 and USD 72.94 per visit and 2.10 and 2.60 h per visit, respectively. However, the feasibility of telehealth for veterans’ medical conditions such as rheumatism, cancer, HIV, and diabetes is underexplored and calls for further investigation post-COVID-19. Lastly, the limited literature on rural veterans’ transportation cost savings using different mobility options—taxi, Uber, public transportation, and rides from friends and family—is another critical gap. Full article