Mobile Operators Research Articles

Market Structures for Service Providers in Advanced Air Mobility

Proposed concepts of operations for advanced air mobility rely on private service providers being responsible for providing air traffic management services to uncrewed aircraft such as drones and autonomous air taxis. While such proposals are unprecedented in the aviation context, one can draw parallels to the Internet and the role played by Internet service providers in managing web traffic. A study of the evolution of the Internet illustrates that, without clear rules for cooperation around a nascent market, private profit motives incentivize against service provider cooperation, especially for traffic flows that traverse multiple regions managed by different service providers. To address this problem, we propose a profit-sharing mechanism based on the Shapley value that incentivizes service providers to cooperate. We show that this mechanism i) ensures that service providers route flights along globally optimal routes, and ii) encourages service providers to work together in providing more efficient routes. We study the allocation of sectors to service providers and show that different allocations can cause large differences in profit earned. Finally, we discuss some of the remaining challenges with having a federated network of private service providers supporting traffic management for advanced air mobility operations.

A Multi-model Fusion Strategy for Android Malware Detection Based on Machine Learning Algorithms

In the digital age, the widespread use of Android devices has led to a surge in security threats, especially malware. Android, as the most popular mobile operating system, is a primary target for malicious actors. Conventional antivirus solutions often fall short in identifying new, modified, or zero-day attacks. To address this, researchers have explored various approaches for Android malware detection, including static and dynamic analysis, as well as machine learning (ML) techniques. However, traditional single-model ML approaches have limitations in generalizing across diverse malware behaviors. To overcome this, a multi-model fusion approach is proposed in this paper. The approach integrates multiple machine learning models, including logistic regression, decision tree, and K-nearest neighbors, to improve detection accuracy. Experimental results demonstrate that the fusion method outperforms individual models, offering a more balanced and robust approach to Android malware detection. This methodology showcases the potential of ensemble techniques in enhancing prediction accuracy, providing valuable insights for future research in cybersecurity.

Ant colony optimization-based solution to optimize load balancing and throughput for 5G and beyond heterogeneous networks

The escalating demand for data in wireless communication systems has posed significant challenges in recent years. This trend is predicted to continue, with explosive data usage and evolving quality of service demands from mobile users. The rapid increase in traffic demand, combined with the intricate nature of heterogeneous network (HetNet) scenarios, has significantly heightened the challenges confronting mobile network operators. These challenges encompass service quality, load distribution, coverage, and the overall user experience. Conventional approaches that prioritize maximum received power in the cell association mechanism tend to sustain network imbalances within the HetNets, making it difficult to cater for the diverse traffic requirements of mobile users. In this study, instead of focusing solely on enhancing individual user downlink rates, we maximize the number of users whose downlink needs are satisfied by integrating a cell range extension (CRE) technique with an ant colony optimization algorithm. Our proposed method considers both the workload of base stations and the signal to interference-plus-noise ratio of user devices to formulate an objective function aimed at calculating specific CRE bias values for individual small base stations. A comparative analysis of the proposed approach with existing techniques demonstrates its effectiveness. Simulation results underscore the success of our proposed strategy in meeting users’ throughput needs while reducing network imbalances and call drop rates.

Experimental analysis for comparison of wireless transmission technologies: Wi-Fi, Bluetooth, ZigBee and LoRa for mobile multi-robot in hostile sites

This research paper conducts a thorough comparison of four prominent transmission technologies suitable for mobile robots operating in challenging environments. Emphasizing key factors such as signal strength, noise resistance, and data transfer efficiency, the study aims to identify the optimal communication solution in hostile conditions. The exploration delves into the intricacies of received signal strength indication (RSSI) and signal-to-noise ratio (SNR), revealing distinctive traits and trade-offs among the technologies. Navigating through the complexities of frequency bands, modulation types, and communication topologies, the paper examines the impact of obstacles, energy consumption dynamics, and potential real-world applications. Beyond contributing to the fields of robotics and communication, the study offers practical insights for stakeholders seeking resilient and efficient transmission methods for mobile robotic applications. Advocating for long range (LoRa) as the preferred transmission technology in hostile environments, the paper highlights its unmatched immunity to noise, stability, and minimal energy consumption. These findings provide valuable guidance for technology choices in collaborative mobile robot operations under challenging conditions. This research sets the stage for future developments in robotic communication, underscoring the crucial role of selecting the right transmission means for mission-critical applications in hostile environments.

고성능 전해질 게이트 트랜지스터 응용을 위한 나노구조 유기물 반도체 박막 제조 연구

In this study, we present an innovative method for enhancing the performance of organic electrolyte-gated transistors (OEGTs) through the integration of nanostructures into their active layers. These nanostructures increase the surface area at the interface between the electrolyte and semiconductor, effectively boosting charge transport characteristics. Such structural enhancements also contribute to significant improvements in achieving high bias stability. The OEGT, characterized by high carrier mobility and low-voltage operation, opens up a new pathway for attaining high performance and low power consumption in flexible and wearable electronics. This research marks a significant step forward in the design and manufacturing of organic electronics, promising to substantially elevate the performance of future electronic devices.

Smart Safety with Password Based GSM Module Controlling Circuit Breaker

Abstract: This paper focus on Smart safety with password based GSM module controlling circuit breaker. In our daily life, Safety is the major concern for all activities. Accidental death of a lineman is often read and proven in current scenario. In view, safety measures to protect operators are considered to be very necessary in current working. Using passwords for security, Electrical lineman security systems are used to control circuit breakers. Serious electrical accidents occurs becoming increasingly, when repairing power lines. It is happen due to lack of communication and coordination between maintenance and substation personnel. In the proposed system, the on and off line turning operation with the lineman to ensure the safety of linemen. For that, a secure password is required to operate the breaker operation and maintenance point of view. First request is registered and password is sent to the line operator's mobile phone and GSM module by AVR microcontroller. Entered password and password received by the GSM receiver are compare. If password is match, the operation of circuit breaker will be smoothly operate. The operator gave three chances for incorrect password otherwise message will appear on the LCD display for security purposed. It also sent the message control room regarding unauthorized access to the system.

Mobile Network Subscribers Market Share Evolution Of Telecommunication Companies In Senegal From 1996 To 2022

This research examines the evolution of market shares of telecommunications companies in Senegal over a period of 26 years, from 1996 to 2022. The study focuses on subscriber’s market share as a key indicator of mobile network operators' performance and competitiveness. It analyzes the mix market share for the three main mobile network operators (ORANGE, FREE, and EXPRESSO) consolidation periods, key success factors, and challenges faced by these companies in a dynamic and competitive environment.The analysis reveals a significant evolution in the telecommunications landscape in Senegal, marked by the emergence of new players, the advancement of technologies, the diversification of offerings, and the increase in connectivity. Major historical operators had to contend with growing competition, stimulating innovation and service improvement to meet changing consumer needs.Key events such as the introduction of 3G and 4G technology, had a significant impact on market share distribution and companies' differentiation strategies. Regulatory policies such as mobile telephony licensing, investments in infrastructure, brand changes, order entry, strategic partnerships, and operators’ number of years of experience also influenced the sector's competitive dynamics.In conclusion, this research highlights the complex and dynamic evolution of market shares of telecommunications companies in Senegal, highlighting the technological, strategic, and regulatory factors that have shaped this sector over the years.

Optimized DM-RS Configuration for Improved 5G New Radio Network Capacity and Performance

Network load in mobile networks is continuously growing, putting pressure on mobile operators to deliver target network performance and user experience. This paper focuses on network capacity improvement through increased spectral efficiency, which can be achieved with overhead reduction by optimizing the demodulation reference signal (DM-RS) configuration, which is one of the channels/reference signals with the largest contribution to overhead. In a high-speed scenario, the Doppler effect noticeably influences the temporal nature of the channel such that a channel interpolation process is required within a slot. However, increasing the number of symbols used for DM-RS has a negative impact on capacity. The Doppler effect was analyzed for various 5G NR configurations of operating frequency and subcarrier spacing (SCS), and various use cases were considered using user equipment (UE) speed as the main parameter. For suitable use cases, the DM-RS configuration was optimized in networks with live traffic. The impact of the configuration change on 5G/NR spectral efficiency, user experience and link adaptation performance was assessed through a deep-dive analysis of active measurements, available performance Management (PM) counters and key performance indicators. An optimized DM-RS configuration is proposed, and it is demonstrated to achieve gains of 5–15%, depending on the metric used, use case analyzed, network load, traffic mix and other relevant network characteristics such as topology and clutter type.

A Comprehensive Overview of Network Slicing for Improving the Energy Efficiency of Fifth-Generation Networks.

The introduction of fifth-generation (5G) mobile networks leads to an increase in energy consumption and higher operational costs for mobile network operators (MNOs). Consequently, the optimization of 5G networks' energy efficiency is crucial, both in terms of reducing MNO costs and in terms of the negative environmental impact. However, many aspects of the 5G mobile network technology itself have been standardized, including the 5G network slicing concept. This enables the creation of multiple independent logical 5G networks within the same physical infrastructure. Since the only necessary resources in 5G networks need to be used for the realization of a specific 5G network slice, the question of whether the implementation of 5G network slicing can contribute to the improvement of 5G and future sixth-generation networks' energy efficiency arises. To tackle this question, this review paper analyzes 5G network slicing and the energy demand of different network slicing use cases and mobile virtual network operator realizations based on network slicing. The paper also overviews standardized key performance indicators for the assessment of 5G network slices' energy efficiency and discusses energy efficiency in 5G network slicing lifecycle management. In particular, to show how efficient network slicing can optimize the energy consumption of 5G networks, versatile 5G network slicing use case scenarios, approaches, and resource allocation concepts in the space, time, and frequency domains have been discussed, including artificial intelligence-based implementations of network slicing. The results of the comprehensive discussion indicate that the different implementations and approaches to network slicing pave the way for possible further reductions in 5G MNO energy costs and carbon dioxide emissions in the future.

An unmanned rice seeder with WiFi based mobile-control system for drudgery reduction

An unmanned rice seeder (URS) with WiFi based wireless communication system was developed to reduce surface seed dispersion, drudgery, human involvement, Occupational health hazards and environmental pollution. An android mobile phone with WIFI connectivity acts as wireless communication system to control the developed URS with operating range of 144.6 m which was surplus for small farms in hilly terrains of Sikkim. The factors of URS are found to be forward speed (Fs) and hopper fill level (HL) w.r.t responses of co-efficient of variation of number of seeds per hill (Cv), Seed rate (Sr), hill spacing uniformity (Us,), missing hill index (MI) and mean hill span (Hs). The optimum results of soil bin study are of Fs and HL of 2.4 km.h−1 and 75% w.r.t responses of Cv, Sr, MI, Us, Hs are 0.28, 18.5 kg. ha−1, 7.3%, 91.7%, and 6.4 cm. Test results showed that the seeding performance of developed seeder was similar to manual drum seeder. But, due to higher speed of operation in developed seeder showed better results in field operation. The results from the field evaluation revealed that URS has increase in field capacity of 41%, reduces labor requirement of 50% than manual rice seeder. In economic evaluation URS has reduced cost of operation (₹ ha−1) of 90% and increase net benefit (₹ year−1), Payback period of 61% and 91% over manual rice seeder (MRS). The operator's workload was decreased by up to 95% due to the machine's mobile operation as compared to the manual operation.

Important drivers for customer satisfaction – a Swedish crisis reflection

PurposeThe purpose of this study is to examine crisis effects on customer satisfaction and underlying drivers by adding a new set of data to previous research. The core questions are: are the findings from Hallencreutz and Parmler (2019, 2021) sustained or can new customer demands, needs, expectations and behaviours be traced in the wake of the ongoing crisis?Design/methodology/approachA first study covering 2005–2017 was completed in 2018, published online in 2019 and in print in 2021 (Hallencreutz and Parmler, 2021). This new study adds the years 2018–2023 to the data set and reuses the partial least squares (PLS) approach to structural equation models, also known as PLS path modelling.FindingsThis additional study sustains the results from the initial study (Hallencreutz and Parmler, 2019, 2021). The variable product quality has been substituted by service quality as one of the most crucial drivers for customer satisfaction together with brand image, and the current state of permacrisis has not changed that.Research limitations/implicationsThe study is built on Swedish data from the EPSI Rating Initiative (Eklöf and Westlund 2002) covering customer perceptions in banking, insurance (life and non-life), telco (mobile operators, broadband and Pay-tv) and energy (trade, distribution and heating) over the years 2005–2023.Practical implicationsThe study emphasizes the importance of understanding how customer satisfaction drivers evolve over time in different industries and societal sectors, especially during crises. This additional study sustains the paradigm shift in the studied industries – product quality has been substituted by service quality as one of the most crucial drivers for customer satisfaction, and the current state of economic downturn has not changed that.Social implicationsSociety will have to learn to live with political and economic instability and unpredictability for the foreseeable future. To recognize the increasing value deriving from firms’ intangible assets while providing flawless deliveries seems to be a way forward in troublesome times. This is also a catalyst for existing societal trends: the necessary reforms to master sustainable transformations will require an ongoing adaptation process, with both winners and losers across continents.Originality/valueThe world has coped with a global pandemic, and Europe is currently experiencing a humanitarian, political and economic crises caused by a war in Ukraine. This extended period of global instability and insecurity could be called a permacrisis (Collins dictionary, 2022). This study offers a unique quantitative analysis built on Swedish data from EPSI Rating initiative.

Meta-Learning for Multi-Family Android Malware Classification

With the emergence of smartphones, Android has become a widely used mobile operating system. However, it is vulnerable when encountering various types of attacks. Every day, new malware threatens the security of users’ devices and private data. Many methods have been proposed to classify malicious applications, utilizing static or dynamic analysis for classification. However, previous methods still suffer from unsatisfactory performance due to two challenges. First, they are unable to address the imbalanced data distribution problem, leading to poor performance for malware families with few members. Second, they are unable to address the zero-day malware (zero-day malware refers to malicious applications that exploit unknown vulnerabilities) classification problem. In this paper, we introduce an innovative meta -learning approach for m ulti-family A ndroid m alware c lassification named Meta-MAMC , which uses meta-learning technology to learn meta-knowledge (i.e. the similarities and differences among different malware families) of few-family samples and combines new sampling algorithms to solve the above challenges. Meta-MAMC integrates (i) the meta-knowledge contained within the dataset to guide models in learning to identify unknown malware, and (ii) more accurate and diverse tasks based on novel sampling strategies, as well as directly adapting meta-learning to a new few-sample and zero-sample task to classify families. We have evaluated Meta-MAMC on two popular datasets and a corpus of real-world Android applications. The results demonstrate its efficacy in accurately classifying malicious applications belonging to certain malware families, even achieving 100% classification in some families.

Security Analysis of the Consumer Remote SIM Provisioning Protocol

Remote SIM provisioning (RSP) for consumer devices is the protocol specified by the GSM Association for downloading SIM profiles into a secure element in a mobile device. The process is commonly known as eSIM, and it is expected to replace removable SIM cards. The security of the protocol is critical because the profile includes the credentials with which the mobile device will authenticate to the mobile network. In this paper, we present a formal security analysis of the consumer RSP protocol. We model the multi-party protocol in applied pi calculus, define formal security goals, and verify them in ProVerif. The analysis shows that the consumer RSP protocol protects against a network adversary when all the intended participants are honest. However, we also model the protocol in realistic partial compromise scenarios where the adversary controls a legitimate participant or communication channel. The security failures in the partial compromise scenarios reveal weaknesses in the protocol design. The most important observation is that the security of RSP depends unnecessarily on it being encapsulated in a TLS tunnel. Also, the lack of pre-established identifiers means that a compromised download server anywhere in the world or a compromised secure element can be used for attacks against RSP between honest participants. Additionally, the lack of reliable methods for verifying user intent can lead to serious security failures. Based on the findings, we recommend practical improvements to RSP implementations, future versions of the specification, and mobile operator processes to increase the robustness of eSIM security.

Competitive Pricing for Resource Trading in Sliced Mobile Networks: A Multi-Agent Reinforcement Learning Approach

The emergence of network slicing as a flagship technology in 5G networks has not only enhanced network expansion and flexibility in resource management for service continuity, but also provided an avenue for establishing a viable market for resource sharing. To optimize the network's resource usage, stakeholders are encouraged to take pragmatic steps toward dynamic resource sharing. This paper designs a techno-economic model for the strategic interactions among multiple competing mobile virtual network operators (MVNOs) and their users in a trading marketplace. We formulate the dynamic pricing problem as a two-stage Stackelberg game, where the MVNOs are leaders, and the users are followers. In the first stage, the MVNOs compete to set their differentiated unit prices using a negotiation mechanism while considering system-level network load. Then, the users decide their purchasing volumes to match the prices of the MVNOs. We transform the game-based optimization problem into a stochastic Markov decision process (MDP) problem and propose a multi-agent deep Q-network (MADQN) method that obtains an optimal solution for the formulated game. Simulation results and analysis reveal that the proposed algorithm achieves convergence under the competitive pricing scheme (CPS) and independent pricing scheme (IPS) while enhancing MVNOs and users' utilities at acceptable levels.

The welfare effects of mobile broadband internet: Evidence from Nigeria

This paper estimates the impacts of mobile broadband coverage on household welfare in Nigeria. The analysis exploits a unique data set that integrates a longitudinal household survey with information from Nigerian mobile operators on the deployment of mobile broadband internet between 2010 and 2016. Overall, estimates show that mobile broadband coverage had large and positive impacts on household consumption thereby reducing poverty significantly. This effect is if anything stronger among poorer households. Labor force participation explains a big part of this welfare-enhancing effect.

USING OF BIG DATA TECHNOLOGIES IN VEHICLE INDUSTRY

This work contains information about some aspects of the use of Big Data technologies in the transport sector, such as predictive analysis of vehicle breakdowns, issues of delivering large amounts of data from rolling stock. Some options for directions for further research on the use of Big Data technologies are considered. One of the problems of using Big Data technologies in the field of transport is the problem of delivering large amounts of information to data processing centers. If for urban transport, where coverage by networks of mobile cellular operators approaches 100%, there are no problems in sending large amounts of data (data can be accumulated on board the vehicle and transmitted at other times, for example, when the vehicle is in the park), then for this transport, such as trucks, trains, cargo planes, there is a certain problem in delivering large amounts of data. Keywords: Big Data technologies, vehicle industry, collecting data, DFM, risks.

Sensitivity analysis of urban air mobility aircraft design and operations including battery charging and swapping

Urban Air Mobility (UAM) is an evolving concept of passenger transportation providing on-demand flights within metropolitan environments, wherefore typically fully electric vertical take-off and landing aircraft are designed. Due to the underlying battery energy constraints, the design of UAM aircraft is very sensitive. Apart from the design considerations, the impact of aircraft operations on the entire UAM transport network must be examined. As there is no data from real-world operations available, this research article utilizes a system of systems simulation framework combining aircraft design with an agent-based simulation. The underlying approach offers the possibility of studying several parameters concerning UAM aircraft design and operations. In a case study focused on intra-city transport, aircraft design aspects regarding the payload capacity, the mission profile, and the reserve requirement are studied for a multirotor configuration. Furthermore, the aircraft operations aspects are focused on the turnaround procedures, the passenger demand, and the cruise speed. The multi-level sensitivity analysis ranging from the subsystem over the system of interest to the system of systems level allows us to trace the most sensitive aspects. Especially, the sensitivity analysis of battery fast-charging and swapping shows the importance of the holistic system of systems investigations for the successful development of UAM aircraft and services.

SEGUL: Ultrafast, memory-efficient and mobile-friendly software for manipulating and summarizing phylogenomic datasets.

Phylogenetic studies now routinely require manipulating and summarizing thousands of data files. For most of these tasks, currently available software requires considerable computing resources and substantial knowledge of command-line applications. We develop an ultrafast and memory-efficient software, SEGUL, that performs common phylogenomic dataset manipulations and calculates statistics summarizing essential data features. Our software is available as standalone command-line interface (CLI) and graphical user interface (GUI) applications, and as a library for Rust, R and Python, with possible support of other languages. The CLI and library versions run native on Windows, Linux and macOS, including Apple ARM Macs. The GUI version extends support to include mobile iOS, iPadOS and Android operating systems. SEGUL leverages the high performance of the Rust programming language to offer fast execution times and low memory footprints regardless of dataset size and platform choice. The inclusion of a GUI minimizes bioinformatics barriers to phylogenomics while SEGUL's efficiency reduces economic barriers by allowing analysis on inexpensive hardware. Our support for mobile operating systems further enables teaching phylogenomics where access to computing power is limited.

An investigation on the behavioral intention of existing bank clients in a developing country to use mobile banking services

Mobile banking has become very important in today’s life as technological advancements have led bank clients to use banking services. Clients’ attitudes toward mobile banking services are based on their expectations is the background of this research. So, the main objective is to observe the purposeful conduct in mind of clients to adopt mobile banking services. This study also examines the influence of six variables on financial services clients’ desire to utilize mobile banking services, including perceived benefits, perceived ease of use, trust, security, perceived privacy, and technology expertise. Consequently, the goal of this study is to find out the crucial and deciding factors that may influence clients’ willingness to use mobile banking features in Bangladesh as a developing country. The sample shaped for this research is 310 respondents from Bangladesh a developing country. For analytical purposes, SEM has been used to test hypotheses. The results show that in Bangladesh, factors like perceived value, security, and technological aptitude greatly determine whether a customer will utilize mobile banking. Financial institutions have proven to be successful in serving clients through mobile phones. Clients have made good use of mobile banking only to save money, cost, and labor. The research suggests that mobile banking operations must be timely and accurate, the transaction process must be short, interactivity, convenience of usage, and so on. The findings have important implications for bank regulatory authority, management, bankers, and executives who wish to increase mobile banking usage to secure their long-term profitability.

IoT CONTROLLED LED NOTICE BOARD

The IoT Controlled LED sign board design represents a slice- edge bid aimed at revolutionizing display results for a multitude of purposes including advertising, information dispersion, and aesthetic improvement. At its core, the sign board features an intricate array of LEDs strictly arranged in a grid pattern, each strictly orchestrated by a central microcontroller unit( MCU) harmoniously integrated with a Bluetooth module for flawless wireless communication. This community enables druggies to apply their smartphones or any Bluetooth- enabled bias as important remote controls, decreeing the content showcased on the LED board with unknown ease and perfection. Through a devoted mobile operation, druggies gain a gateway to a realm of creative expression, empowered to transmit a myriad of content types ranging from brief textbook dispatches to witching, robustness and images for immediate display. specially, the system's hallmark lies in its capability to grease real- time content operation, preventing the need for physical intervention and fostering dynamic rigidity to evolving demands and scripts. likewise, the mobile operation's robust point set extends beyond bare content transmission, offering sophisticated tools for communication scheduling and contemporaneous operation of multiple sign boards, thereby accelerating scalability and usability across different surroundings similar as bustling retail spaces, bulging transportation capitals, and bustling public spaces likewise. With its intimately designed interface and multifaceted functionality, the IoT Controlled LED sign board design emerges as a lamp of invention, promising to review the veritably geography of information dispersion and visual communication in the digital age. KEYWORDS: IoT Controlled LED subscribe Board, Microcontroller Unit( MCU), Wireless Communication, Mobile Application, Management, Remote Control.