Mobile Network Subscribers Research Articles

New policies, new behaviors: How digital taxation shapes mobile money use in Ghana

AbstractThe transition from traditional to digital payment platforms is reshaping domestic revenue mobilization, with significant impacts on sectors like agriculture, health, business, education and economy. This transition, while presenting both challenges and opportunities, has the potential to foster economic growth and boost revenue mobilization. This paper investigates how digital taxation or electronic levy (e‐levy) has shaped mobile money (MoMo) adoption in Ghana since the introduction of e‐levy on digital financial transactions. The underlying theories supporting this study include the Technology Acceptance Model (TAM), Social Norm Theory (SNT), and Expectancy‐Confirmation Theory (ECT). A cross‐sectional design was employed, and data was collected from 206 participants (mobile network subscribers) through a self‐administered online survey conducted and applied a partial least square structural equation modeling technique. The findings indicate that inherent innovativeness, the structure of the tax, and social tax compliance norms significantly influence citizens' compliance attitudes towards e‐levy in the context of a developing country. Conversely, the study found that potential taxpayers' attitudes towards e‐levy do not determine their intention to pay (actual use) e‐levy. In this respect, recommendations to drive the digital taxation agenda among government revenue agencies in developing countries are (i) continuous inherent innovativeness on the part of the government, (ii) ensuring compliance attitudes towards e‐levy, (iii) proper structuring of the tax components and (iv) ensuring ease of use of the system. These findings provide governments and revenue agencies, particularly those in developing countries, with valuable insights into citizens' behavioral change towards digital taxation on MoMo transactions. An effective convergence of the determinants discussed in this research would expedite government mobilization efforts for electronic levies and promote development.

Adaptive Antenna Array Control Algorithm in Radiocommunication Systems

An important element of modern telecommunications is wireless radio networks, which enable mobile subscribers to access wireless networks. The cell area is divided into independent sectors served by directional antennas. As the number of mobile network subscribers served by a single base station increases, the problem of interference related to the operation of the radio link increases. To minimize the disadvantages of omnidirectional antennas, base stations use antennas with directional radiation characteristics. This solution allows you to optimize the operating conditions of the mobile network in terms of reducing the impact of interference, better managing the frequency spectrum and improving the energy efficiency of the system. The work presents an adaptive antenna algorithm used in mobile telephony. The principle of operation of adaptive systems, the properties of their elements and the configurations in which they are used in practice are described. On this basis, an algorithm for controlling the radiation characteristics of adaptive antennas is presented. The control is carried out using a microprocessor system. The simulation model is described. An algorithm was developed based on the Mathcad mathematical program, and the simulation results of this algorithm, i.e., changes in radiation characteristics as a result of changing the mobile position of subscribers, were presented in the form of selected radiation characteristics charts.

Do subscribers of mobile networks care about Data Throttling?

Network neutrality mandates have been made out either as necessary to ensure a level playing field in online markets or, alternatively, as overly restrictive regulation preventing innovation and investment. However, there is little empirical research on the consequences of data throttling, which becomes legal without network neutrality regulations. We combine throughput levels measured for mobile ISPs in the United States with usage data to explore how sensitive users are to such practices. We find no evidence that users change their behavior when faced with throttled data rates.

ИССЛЕДОВАНИЕ КАЧЕСТВА ОБСЛУЖИВАНИЯ АБОНЕНТОВ ПРИ ЭСТАФЕТНОЙ ПЕРЕДАЧЕ В ЦИФРОВЫХ СЕТЯХ ПОДВИЖНОЙ РАДИОСВЯЗИ НА ЖЕЛЕЗНОДОРОЖНОМ ТРАНСПОРТЕ

The article proposes a new approach to determining the quality of service for subscribers of mobile communication networks using rail transport. Communication problems arising during the movement of the train are discussed. The processes of customer service transfer (handover) are considered from one base station to another. A methodology is proposed that analyzes statistics on all handover events. It is noted that the results of the study will help telecom operators to investigate in more detail the radio coverage of their network in order to improve the quality of communication of passengers en route.

Effects of mobile networks and Covid-19 on mobile shopping sales in South Korea

Covid-19 has driven us abruptly to a new world of contactless society. It also compelled us to use online shopping, especially mobile shopping in South Korea, where the dominant mode of wireless communication was already 4G services when Covid-19 broke out. This paper examines the different roles of mobile networks and the Covid-19 pandemic in transforming mobile shopping submarkets in South Korea by estimating the long-term and short-term effects of these two factors on mobile shopping sales. We used a cointegration and an error correction model to estimate long-term and short-term effects separately. This paper finds that Covid-19 was a major short-term factor affecting sales in mobile shopping submarkets, while mobile network subscribers were a key long-term driving factor of mobile shopping sales growth.

METHODS FOR ENSURING DATA SECURITY IN MOBILE STANDARDS

The analysis of mobile communication standards is carried out, the functional structure and interfaces of interaction between the structural elements of the cellular network are considered. To understand the principle of communication according to the GSM standard, a block diagram of a mobile switching center (MSC), base station equipment (BSS), control and service center (MCC), mobile stations (MS) is presented. The main algorithms for ensuring the confidentiality and security of mobile subscribers' data, in different types of standards, as well as the vulnerabilities of information flows are considered. In particular, the following dangerous types of attacks have been identified, to which mobile network subscribers are sensitive: sniffing; leakage of personal data; leakage of geolocation data; spoofing; remote capture of SIM-card, execution of arbitrary code (RCE); denial of service (DoS). It is established that the necessary function of the mobile network is the identification of subscribers, which is performed by IMSI, which is recorded in the SIM card of the subscriber and the HLR of the operator. To protect against spoofing, the network authenticates the subscriber before starting its service. In the case of subscriber identification, the subscriber and the network operator are protected from the effects of fraudulent access. In addition, the user must be protected from eavesdropping. This is achieved by encrypting the data transmitted over the radio interface. Thus, user authentication in UMTS, as well as in the GSM network, is carried out using encryption with a common key using the "hack-response" protocol (the authenticating party sends a random number to the authenticated party, which encrypts it according to a certain algorithm using a common key and returns the result back).

Estimating Call-Drop Probability Rates among Wireless Cellular Networks in Ghana

The increasing rate of call-drop among wireless cellular networks has become a headache for subscribers of mobile voice networks in Ghana. Despite the many studies that have been carried out on call-drop, most of them have failed to examine call-drop probability rates, a key metric of tackling the issue of call-drop. This study combines the probability distribution function of call-drop and maximum likelihood estimator to estimate call-drop probability rates among the wireless cellular networks in Ghana. The call-drop of the networks was, first of all, fitted to a probability distribution. The call-drop probability rate was then estimated using the maximum likelihood estimator of the fitted distribution. The call-drop probability distribution of Airtel-Tigo, Vodafone, and Glo follow the Geometric probability distribution, while that of MNT follows the Negative Binomial probability distribution. The call-drop probability rate of MTN is 7.6%, Vodafone is 3.3%, Airtel-Tigo, and Glo is 3.0%. These call-drop rates are found to be outside the prescribed NCA's acceptable limit of less than 3 %.

Valid Statements by the Crowd: Statistical Measures for Precision in Crowdsourced Mobile Measurements

Crowdsourced network measurements (CNMs) are becoming increasingly popular as they assess the performance of a mobile network from the end user’s perspective on a large scale. Here, network measurements are performed directly on the end-users’ devices, thus taking advantage of the real-world conditions end-users encounter. However, this type of uncontrolled measurement raises questions about its validity and reliability. The problem lies in the nature of this type of data collection. In CNMs, mobile network subscribers are involved to a large extent in the measurement process, and collect data themselves for the operator. The collection of data on user devices in arbitrary locations and at uncontrolled times requires means to ensure validity and reliability. To address this issue, our paper defines concepts and guidelines for analyzing the precision of CNMs; specifically, the number of measurements required to make valid statements. In addition to the formal definition of the aspect, we illustrate the problem and use an extensive sample data set to show possible assessment approaches. This data set consists of more than 20.4 million crowdsourced mobile measurements from across France, measured by a commercial data provider.

A Novel Anchor Selection Scheme for Distributed Mobility Management

The number of subscribers in mobile networks is growing rapidly, which challenges the network management and data delivery. The efficient management and routing are key solutions. An important one of the solutions is the Distributed Mobility Management (DMM) that to handles the mobility of subscribers at the edge of mobile networks and load balancing. Otherwise, mobility anchors are distributed across the network, which can manage the handover procedures. In this paper, we propose a novel mobility anchor selection scheme based on the results of a cost function with three factors, to select a suitable cell and anchor for moving subscribers and improve the handover performances of the network. Our results illustrate that the proposed scheme provides significantly enhanced handover performance.

RETRACTED: Structure optimization of big data financial industry based on 5g network processor and embedded system

Abstract More and more financial institutions are working with financial technology companies to enhance their services and attract customers in the mobile age. It appears 5 G technology provides new options and a 5 G ecosystem for financial institutions. Mobile operators and financial implications. Bank of self. It is clear. 5 G technology and embedded systems with powerful security and transaction speed significantly reduced latency and transaction cycle, marking the capital market revolution's arrival—5 G financial technology to bring more customers and market share. From the perspective of financial innovation and application services from the perspective point of view, 5 G can improve productivity and customer satisfaction. Security is crucial in the financial sector; 84 percent of financial services executives' pay more attention to the potential of 5 G. In today's world, more secure transactions, the heterogeneous surge in traffic, mobile network subscribers, and online services generate large amounts of data. This trend continued in the form of large data quickly and diversified development. Multifunction case scenarios with different requirements for 5 G constitute a major challenge. One of the most important requirements with the embodiment is highly scalable, low latency and high data rate connections generally optimal energy transfer, which is equally important 5 G. Require extensive data analysis. It handles large amounts of raw data and on a small scale to extract useful information. Arbitrators can use this information to make decisions consistent. This article describes the challenges 5 G technology scene, big data and the prospect of new 5 G technologies. For a detailed overview of the big data, the challenge will achieve the goal of 5 G. He is a built-banking problem that can be solved.

A Quantitative and Comparative Evaluation of Key Points Selection Algorithms for Mobile Network Data Sets Analysis

In recent years, network operators are receiving an outsize amount of data due to the increasing number of mobile network subscribers, network services and device signalling. This trend increases with the deployment of 5G that will provide advanced connectivity to wireless devices and develop new services. Network analytics must allow telecommunications operators to improve their services and the infrastructure extracting useful information from large amounts of data. A methodology based on orthogonal projections was developed in order to analyze the network information and facilitate the management and the operations to network providers. In the current study, different key points selection algorithms are investigated in order to make a quantitative and qualitative evaluation and analyze the performance of those algorithms which use different approaches to select these points, which will be utilized in the methodology. A novel synthetic data set has also been developed to statistically evaluate the effect of the key points selection algorithms in the clustering, as well as, measure the performance of the aforementioned methodology. Finally, these key points selection algorithms are used in a real scenario to evaluate the impact of the different approaches in the analysis.

Impact of After-Sales Service on Customers� Retention of Mobile Telecommunications in Nigeria

The idea of after-sales services has been adopted globally to provide the consumers after the product or services rendered. The study explored the impact of after-sales services on customers� retention of mobile telecommunication in Nigeria. Survey research was adopted, and the aim of using this design is premised on the fact that the study relied on obtaining information from the field using a questionnaire. The population consist of all the subscribers of MTN, Globacom, Airtel and 9mobile. Four hundred seventy-two (472) subscribers of mobile networks were proportionally drawn from the NCC website. Subsequently, a simple random sampling technique was used to select the respondents from each of the mobile networks. Data collected were analysed using an application of simple percentage method in computer software packages (SPSS), and the regression analysis adopted by the testing of a reported hypothesis. The regression of [t-statistics] value of .01 and [2.63] demonstrates that the relationship between after-sale service and retention of customers is essential because the alpha level of 0.05 is higher than the p-value. Hence, the assumption is that growth in after-sales activities is a significant contributor to customer retention. Management should pay attention to the employee position to the quality of after-sales service, which results in future procurement and further recommendations.

Mobile Privacy: Scalable Ensemble Matching for User Identification Attacks

Mobile privacy is broadly concerning in the mobile big data era, as user mobility behaviors are privacy-sensitive and unique. User identification attacks consist of one of the most critical privacy concerns on mobile big data. In this paper, we study mobile privacy in terms of user identifiability from the perspective of privacy adversaries. User identification in two datasets from the same data source or two different data sources is generally formulated as a linear assignment problem (LAP), in which the cost matrix of users is generated by a single distance measure. However, user identification via one single distance measure may lead to a large portion of false matches, especially when only a few users coexist across these two datasets. In addition, the cubic computational complexity of LAP limits the scale of user identification analysis. In this paper, we propose a multi-feature ensemble matching framework to improve the user identification precision based on a majority voting rule, by integrating multiple distance measures. The computational complexity of the proposed ensemble matching algorithm is an order of magnitude less than that of the single-distance based approach, which results from solving an LAP on a highly sparse matrix rather than a dense matrix. Experiments demonstrate the superior performance of our proposed scalable ensemble matching framework with respect to matching precision as well as the vulnerability of mobile network subscribers' privacy.

Private Identification of Subscribers in Mobile Networks: Status and Challenges

The privacy of individuals in the context of mobile networks is crucial nowadays. Nevertheless, too few improvements have been made over the years to secure the privacy of subscribers. As a consequence, current generations of mobile networks, including 4G/LTE, are susceptible to sensitive information leakage. In particular, individuals are exposed to location disclosure and movement tracking by revealing subscribers' permanent identifiers. In this article, we discuss the subscribers' private identification problem in light of the recent standardization for 5G. We introduce the problem and discuss existing cryptographic solutions, with a focus on the ECIES-based solution adopted for 5G. We then investigate to what extent the privacy protection mechanisms introduced by the 5G security architecture answer our problem. Finally, we identify challenges, and we distinguish domains of interest and specific research activities to address these challenges.

Swapped Sectors Detection Based on User Location During Inter-Site Handovers

Network roll-out is a process composed of several actions, which, if not completed correctly, may degrade the final system performance. A common error during the roll-out process is the case in which feeders from baseband units to radio units or feeders from radio units to antennas are interchanged. Consequently, in sectorized sites, the service areas of two or more co-sited cells become swapped, affecting the initial network design. This paper proposes to utilize the location of the user during mobility procedures to enhance the state-of-the-art methods to detect swapped sectors automatically. There are multiple solutions to obtain the location of subscribers in mobile communications networks. However, the most accurate ones are either costly or not possible in current networks. Therefore, this paper addresses the problem of applying time-of-arrival techniques based on multilateration in present-day mobile networks by proposing an alternative using standardized signaling. One of the main benefits of the proposed method is its ease of being implemented in real networks without adding additional costs to the operators. Finally, the results are presented to demonstrate that the proposed method improves the performance of state-of-the-art methods.

ПІДВИЩЕННЯ НАДІЙНІСНИХ ПОКАЗНИКІВ ПРОГРАМНО-ОРІЄНТОВАНОЇ МЕРЕЖІ

In this work the reliable indicators of the software-oriented network were analyzed, the comparison of centralized and decentralized management types was made, that program-managed networks need to optimize and increase reliability to the current standards of 3gpp. The model of calculation of the reliability of centralized and decentralized networks is proposed, with the help of which it is possible to identify weak or less susceptible sites in the mobile communication system. The method of estimation and enhancement of reliable characteristics of the information management system of the mobile communication network is developed, based on the hierarchical model of hardware and software reliability assessment. The dependence of equipment on applications or applications is taken into account. The system allows to optimize the process of deployment of the network, modernization and increase the reliability of servicing subscribers of mobile networks. This significantly improves the planning and modeling of the network infrastructure, which in turn increases the efficiency of use and reduces the cost of equipment and labor costs of man-hours. It is also proposed to use this mathematical model for software management model but less reliable sleep structure, so its optimization is a necessary factor in the use of these types of networks.

Handover with Buffering for Distributed Mobility Management in Software Defined Mobile Networks

The rapidly-growing number of mobile subscribers has led to the creation of a large number of signalling messages. This makes it difficult to efficiently handle the mobility of subscribers in mobile cellular networks. The long-term evolution (LTE) architecture provides software-defined networking (SDN) to meet the requirements of 5G networks and to forward massive mobile data traffic. The SDN solution proposes separation of the control and data planes of a network. Centralized mobility management (CMM) is widely used in current mobile network technologies, such as 4G networks. One of the problems related to CMM is a single point of failure. To solve the problems of CMM and in order to provide for efficient mobility management, IETF has developed a solution called distributed mobility management (DMM), in which mobility is handled via the nearest mobility anchor. In this paper, we propose a DMM solution with handover operations for SDN-enabled mobile networks. The advantage of the proposed solution is that intra and inter handover procedures are defined with the data buffering and forwarding processes between base stations and mobility anchors. We adopt a simulation model to evaluate and compare the proposed solution with the existing solution in terms of handover latency, packet loss and handover failures.

Handover with Buffering for Distributed Mobility Management in Software Defined Mobile Networks

The rapidly-growing number of mobile subscribers has led to the creation of a large number of signalling messages. This makes it difficult to efficiently handle the mobility of subscribers in mobile cellular networks. The long-term evolution (LTE) architecture provides software-defined networking (SDN) to meet the requirements of 5G networks and to forward massive mobile data traffic. The SDN solution proposes separation of the control and data planes of a network. Centralized mobility management (CMM) is widely used in current mobile network technologies, such as 4G networks. One of the problems related to CMM is a single point of failure. To solve the problems of CMM and in order to provide for efficient mobility management, IETF has developed a solution called distributed mobility management (DMM), in which mobility is handled via the nearest mobility anchor. In this paper, we propose a DMM solution with handover operations for SDN-enabled mobile networks. The advantage of the proposed solution is that intra and inter handover procedures are defined with the data buffering and forwarding processes between base stations and mobility anchors. We adopt a simulation model to evaluate and compare the proposed solution with the existing solution in terms of handover latency, packet loss and handover failures.

A Destination and Mobility Path Prediction Scheme for Mobile Networks

Mobile multimedia services are gaining great momentum among subscribers of mobile networks (MNs). An understanding of the network traffic behavior is essential in the evolution of today's MNs and, thus, leads to more efficient planning and management of the network's scarce bandwidth resources. The communication efficiency can be largely improved (i.e., optimizing the allocation of the network's limited resources and sustaining a desirable quality of service) if the network anticipates the needs of its users on the move and, thus, performs reservation of radio resources at cells along the path to the destination. In this vein, we propose a mobility prediction scheme for MNs; more specifically, we first apply probability and Dempster–Shafer processes for predicting the likelihood of the next destination, for an arbitrary user in an MN, based on the user's habits (e.g., frequently visited locations). Then, at each road junction, we apply the second-order Markov chain process for predicting the likelihood of the next road segment transition, given the path from the trip origin to that specific road junction and the direction to the destination. We evaluate our proposed scheme using real-life mobility traces; the simulation results show that the proposed scheme outperforms traditional schemes.

Engineering bioethanol without the food gap

Currently, the world is witnessing a mounting avalanche of data due to the increasing number of mobile network subscribers, Internet websites, and online services. This trend is continuing to develop in a quick and diverse manner in the form of big data. Big data analytics can process large amounts of raw data and extract useful, smaller-sized information, which can be used by different parties to make reliable decisions.In this paper, we conduct a survey on the role that big data analytics can play in the design of data communication networks. Integrating the latest advances that employ big data analytics with the networks’ control/traffic layers might be the best way to build robust data communication networks with refined performance and intelligent features. First, the survey starts with the introduction of the big data basic concepts, framework, and characteristics. Second, we illustrate the main network design cycle employing big data analytics. This cycle represents the umbrella concept that unifies the surveyed topics. Third, there is a detailed review of the current academic and industrial efforts toward network design using big data analytics. Forth, we identify the challenges confronting the utilization of big data analytics in network design. Finally, we highlight several future research directions. To the best of our knowledge, this is the first survey that addresses the use of big data analytics techniques for the design of a broad range of networks.