Mobile Subscribers Research Articles

Law, mobile money drivers and mobile money innovations in developing countries

This study investigates how the rule of law (i.e. law) modulates demand- and supply-side drivers of mobile money to influence mobile money innovations (i.e. mobile money accounts, the mobile phone used to send money and the mobile phone used to receive money) in developing countries. The following findings from Tobit regressions are established. First, from the demand-side linkages, law modulates: (i) bank accounts and automated teller machine (ATM) penetration for negative interactive relationships with mobile money innovations and (ii) bank sector concentration for a positive interactive relationship with mobile money accounts. Second, from supply-side linkages, law interacts with: (i) mobile subscriptions for a negative relationship with the mobile phone used to send money; (ii) mobile connectivity coverage for a negative nexus on the mobile phone used to receive money and (iii) mobile connectivity performance for a negative influence on the mobile phone used to send/receive money. Policy implications are discussed in the light of enhancing the rule of law as well as improving mobile phone subscription, connectivity and performance dynamics.

An Insight into Deployments of Green Base Stations (GBSs) for an Environmentally Sustainable World

Data traffic and the number of mobile subscribers have increased significantly prompting cellular network operators to install additional mobile cellular base stations (BSs) to meet the increasing demand. This proliferation of BSs has resulted in consequential increase in energy consumption and Green House Gases (GHGs) emission. Several techniques have been deployed to reduce the energy consumption of the base station in what is called a green base station. This paper presents an insight into these approaches and highlights key challenges and potential research directions. It also highlights what environmental sustainability activist, regulators and government can do to incentivize green BSs concept in Nigeria.

Bundling and Consumer Churn in Telecommunications Markets

Abstract In this paper, we analyze how fixed-mobile (quadruple-play) bundling impacts the decision of consumers to churn telecommunications services. We use a database from an European operator of fixed and mobile telecommunications services which includes information about 9.6 million fixed broadband subscribers and 14.2 million mobile subscribers between March 2014 and February 2015. These data is combined with socio-demographic characteristics from each municipality in this country. We find that consumers who bundle fixed and mobile services from the same provider are less likely to churn. Without fixed-mobile bundling the annual churn of fixed broadband consumers would increase from 8.4 to 9.2%. Furthermore, the consumer churn in the mobile market would increase from 11.5 to 13.1%. We conclude that in the current competitive environment in the country considered, bundling has a moderate impact on consumer retention on both fixed and mobile networks.

Study of microbial contamination of mobile phones of healthcare workers (HCWs)

Study of microbial contamination of mobile phones of healthcare workers (HCWs) - IJMMTD- Print ISSN No: - 2581-4753 Online ISSN No:- 2581-4761 Article DOI No:- 10.18231/j.ijmmtd.2021.003, IP International Journal of Medical Microbiology and Tropical Diseases-IP Int J Med Microbiol Trop Dis

Knowledge-Based Economy Capacity Building for Developing Countries: A Panel Analysis in Southern African Development Community

The Southern African Development Community is lagging behind in terms of knowledge economy relative to other regions worldwide. This dramatically reduces the chances of keeping up with their economically established counterparts in terms of sustainable development. This paper therefore, applies multivariate panel data analysis which is predicted on the Cobb–Douglas production function to analyze the affiliation flanked by knowledge-based economy pillars and economic growth from 1998–2018. The World Bank knowledge-based economy framework is employed. To achieve the study goal, the long-run effect regarding proxies of each pillar in the knowledge-based economy on economic growth is first estimated. Afterwards, the average impact of each pillar is examined using the average impact index (AII). Employment of both conventional unit root and co-integration tests showed all observed series are stationary and co-integrated. Further estimation of the long-run relationship using both static and dynamic models (fixed effect and generalized method of moment) portrayed that government effectiveness, adjusted savings on education expenditure, tertiary enrollment, scientific and technical journals, and mobile cellular subscriptions have significant positive impact on economic growth. Finally, the AII estimation unveiled that the innovation pillar is the most impactful aspect on economic growth followed by education and skills with the least being information and communication technology infrastructure. Feasible policy recommendations are further suggested.

5G Intelligent A+: A Pioneer Multi-Access Edge Computing Solution for 5G Private Networks

Multi-access edge computing (MEC) is a key technology for enabling various services in 5G applications. Existing works mainly focus on the key technologies of MEC. In this article, we, as a mobile operator, share our experience with a self-developed MEC system, called 5G Intelligent A+, for 5G private networks. This system is inline and transparent, and is located between the base station (BS) and the mobile core network. Therefore, it is not affected by changes in the BS and core network, and does not require pre-configuration. We demonstrate the key functions of the system, including versatile conditions for local breakout, flexible network access management, on-demand bandwidth allocation based on mobile subscriber ISDN number, time, and location. We also show how to support inter-region access via an innovative tunneling mechanism called tunnel MEC (T-MEC). We then demonstrate that the system can efficiently provide enterprises with diverse services, which can be performed online and in real time. This MEC system works well with many types of access networks and is applicable to non-standalone and standalone (SA) 5G networks. The proof of concept has been tested in Taiwan to prove the flexibility and usability of the MEC system. In addition, some functions and applications were also demonstrated at the Mobile World Congress 2018 and 2019.

Mobility Management in Heterogeneous Cellular Networks

This paper has analysed the mobility management schemes in heterogenous cellular networks (HCNs) considering their power consumptions and network selection delays. The HCNs are the key enabler for 5G cellular network to ensure better user connectivity in ultra-dense networks. Large numbers of small cells are deployed under a macro-cell targeting network hot spot. However, ensuring seamless coverage to the mobile subscribers in motion is challenging in such networks. Frequent handoff between the cells with different bandwidth, throughput, latency, and coverage penetrations, significantly increases the signalling overhead in network. In this context, an efficient mobility management scheme plays a key role for the success of HCN technology. In this paper, a detailed behavioural study of mobility management schemes used in HCN has been provided. For mobile users in the network, the power consumption and network selection delay has been evaluated for k-tier architecture of HCN.

Interleaver Assignment Solution for Multi Radio Access Technology Supported 5G Networks

Fifth Generation (5G) communication networks support multiple radio access technologies, popularly known as multi-RAT, to facilitate services to all the mobile subscribers irrespective of their subscription for any old generation network. Unique interleaver assignment to each active mobile subscriber within intra-RAT communication is comparatively easy task. However, the same becomes a challenging issue when multi-RAT supported communication is required to be dealt with. This paper reveals a theoretical backend control signaling solution to overcome this challenge. The proposed solution is named as Store-Regenerate-Recall (SRR) technique for interleaver assignment in multi-RAT supported 5G network. This solution is quite effective and easy-to-implement for handling interleaver assignment issue at the 5G network end in multi-RAT scenarios without any subscriber identity clash. Overall, the method is of great significance when multi-carrier multi-RAT solutions are intended to be developed for 5G networks.

ACCESS TO ELECTRICITY, INFORMATION AND COMMUNICATIONS TECHNOLOGY (ICT), AND FINANCIAL DEVELOPMENT: EVIDENCE FROM WEST AFRICA

Poor Access to electricity may hinder West African countries from raising levels of financial development with the aid of Information communication Technology (ICT). Using 16 West African countries, and data over the period of 2000 to 2018, this present study analyses the effect of greater access to electricity on financial development through ICT. ICT was measured using mobile use and internet use, while financial development was measured using private bank credit to GDP ratio and Broad Money Supply to GDP ratio. Panel data fixed effect instrumental variables estimation was used for analysis and the study found that access to electricity significantly boosts mobile use and internet use, while resulting from access to electricity mobile use significantly boosted both measures of financial development but internet use significantly reduced the measures. Further categorizing sample countries into Anglophone and Francophone West Africa countries, access to electricity through ICT boosted both measures of financial development for Francophone countries, while only boosting broad money supply to GDP ratio for Anglophone countries. Thus greater access to electricity through for example provision of electricity infrastructure and regulation of electricity charges to households and firms is important to boost levels of financial development in West Africa.Keywords: Access to Electricity, Information communication Technology (ICT), financial development, Mobile subscription, Internet Use, West Africa,JEL Classifications: O16, O33, E51DOI: https://doi.org/10.32479/ijeep.10344

Triggers and Obstacles to the Development of the FinTech Sector in Poland

The article aims to show the opportunities for the formation of new FinTech startups in Poland and further development of the sector, as well as to identify the most critical threats. The study offers the descriptive and deductive analysis based on the literature review. The empirical part relies on the data from external databases as well as the dataset collected in a survey run among the FinTechs in Poland in January 2020. The paper reveals that Poland is a fast-growing FinTech market which satisfies various requirements such as the number of secure Internet servers, mobile telephone subscriptions, the available labor force, as well as growing tertiary education enrolment. The crucial obstacles to the development of the sector is the uncertainty about the availability of skilled workers in the future and the lack of proper legal regulations.

Refining Sparse Cell-ID Trajectory of Public Service Vehicles by Spatiotemporal Modelling

Mobile phone data have become a critical data source for transportation research. While a cell-id trajectory was routinely reorganized by International Mobile Subscriber Identity (IMSI), it potentially allows to analyze transportation behaviors and social interaction of total population, with a full temporal coverage at low cost. However, cell-id trajectory is often sparse due to low reporting frequency and uncertainness of mobile holders’ position. So, the cell-id trajectory refinement has been recognized as challenging work to further facilitate trajectory data mining. This paper presents a comprehensive approach to identify cell-id trajectories of public service vehicles (PSVs) from large volume of trajectories and further refines these cell-id trajectories by a heuristic global optimization approach. The modified longest common subsequence (LCSS) method is used to match a cell-id trajectory and a public transportation route (PTR) and correspondingly calculates their similarities for determining whether the trajectory is PSV mode or not. Taking full advantages of the nature of a PSV tends to move on the PTR in uniform motion to meet a prescript visit to stops, a heuristic global optimization approach is deployed to build a spatiotemporal model of a PSV motion, which estimates new locations of cell-id trajectories on the PTR. The approach was finally tested using Beijing cellular network signaling datasets. The precision of PSV trajectory detection is 90%, and the recall is 88%. Evaluated by our GNSS-logged trajectories, the mean absolute error (MAE) of refined PSV trajectories is 144.5 m and the standard deviation (St. Dev) is 81.8 m. It shows a significant improvement in comparison of traditional interpolation methods.

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.

Green communication for OFDMA cellular networks with multiple antennas

The green communication which requires the maximum reduction of energy consumption has become a strong need for the new wireless system designs because of the massive increasing number of mobile subscriptions. Thus, in this paper, energy efficiency (EE) maximization problem is considered for multiple-input single-output orthogonal frequency division multiple access (MISO-OFDMA) cellular networks. The EE maximization problem is defined for a downlink communication model by considering the total transmit power and circuit power constraints. Quality of service (QoS) constraints which guarantee the minimum data rate requirement of the users are also accounted. The considered problem belongs to the category of mixed-integer non-linear programming problem (MINLP), and thus is NP-hard. To cope up with this complexity, a two-step resource allocation algorithm, which contains an heuristic subchannel allocation algorithm and the iterative power allocation algorithm with fast convergence based on the Dinkelbach method, is proposed. Numerical results are provided to demonstrate the effectiveness of the proposed algorithm and the convergence and energy efficiency performance of the proposed scheme is validated.

Machine Learning and Mobile Phone Data Can Improve the Targeting of Humanitarian Assistance

The COVID-19 pandemic has devastated many low- and middle-income countries (LMICs), causing widespread food insecurity and a sharp decline in living standards1. In response to this crisis, governments and humanitarian organizations worldwide have mobilized targeted social assistance programs2. Targeting is a central challenge in the administration of these programs: given available data, how does one rapidly identify the individuals and families with the greatest need3? This challenge is particularly acute in the large number of LMICs that lack recent and comprehensive data on household income and wealth4–6. Here we show that non-traditional “big” data from satellites and mobile phone networks can improve the targeting of anti-poverty programs. Our approach uses traditional survey-based measures of consumption and wealth to train machine learning algorithms that recognize patterns of poverty in non-traditional data; the trained algorithms are then used to prioritize aid to the poorest regions and mobile subscribers. We evaluate this approach by studying Novissi, Togo’s flagship emergency cash transfer program, which used these algorithms to determine eligibility for a rural assistance program that disbursed millions of dollars in COVID-19 relief aid. Our analysis compares outcomes – including exclusion errors, total social welfare, and measures of fairness – under different targeting regimes. Relative to the geographic targeting options considered by the Government of Togo at the time, the machine learning approach reduces errors of exclusion by 4-21%. Relative to methods that require a comprehensive social registry (a hypothetical exercise; no such registry exists in Togo), the machine learning approach increases exclusion errors by 9-35%. These results highlight the potential for new data sources to contribute to humanitarian response efforts, particularly in crisis settings when traditional data are missing or out of date.

BlockRoam: Blockchain-based Roaming Management System for Future Mobile Networks

Mobile service providers (MSPs) are particularly vulnerable to roaming frauds, especially ones that exploit the long delay in the data exchange process of the contemporary roaming management systems, causing multi-billion dollars loss each year. In this paper, we introduce BlockRoam, a novel blockchain-based roaming management system that provides an efficient data exchange platform among MSPs and mobile subscribers. Utilizing the Proof-of-Stake (PoS) consensus mechanism and smart contracts, BlockRoam can significantly shorten the information exchanging delay, thereby addressing the roaming fraud problems. Through intensive analysis, we show that the security and performance of such PoS-based blockchain network can be further enhanced by incentivizing more users (e.g., subscribers) to participate in the network. Moreover, users in such networks often join stake pools (e.g., formed by MSPs) to increase their profits. Therefore, we develop an economic model based on Stackelberg game to jointly maximize the profits of the network users and the stake pool, thereby encouraging user participation. We also propose an effective method to guarantee the uniqueness of this game's equilibrium. The performance evaluations show that the proposed economic model helps the MSPs to earn additional profits, attracts more investment to the blockchain network, and enhances the network's security and performance.

Law, mobile money drivers and mobile money innovations in developing countries

This study investigates how the rule of law (i.e. law) modulates demand- and supply-side drivers of mobile money to influence mobile money innovations (i.e. mobile money accounts, the mobile phone used to send money and the mobile phone used to receive money) in developing countries. The following findings from Tobit regressions are established. First, from the demand-side linkages, law modulates: (i) bank accounts and automated teller machine (ATM) penetration for negative interactive relationships with mobile money innovations and (ii) bank sector concentration for a positive interactive relationship with mobile money accounts. Second, from supply-side linkages, law interacts with: (i) mobile subscriptions for a negative relationship with the mobile phone used to send money; (ii) mobile connectivity coverage for a negative nexus on the mobile phone used to receive money and (iii) mobile connectivity performance for a negative influence on the mobile phone used to send/receive money. Policy implications are discussed in the light of enhancing the rule of law as well as improving mobile phone subscription, connectivity and performance dynamics.

Capacity enhancement in indoor environment by hybrid combiner circuit of multinetworks operator

This study focuses on providing a solution for a mobile service provider with Multi Network Operators (MNOs) to provide an excellent service attended by thousands of Mobile Subscribers (MS) at Nasional Bukit Jalil Kuala Lumpur Stadium in Malaysia using a single multi-beam antenna via a hybrid circuit. The Hybrid Combiner (HC) is the solution used to combine multiple MNOs in order to minimize space and cost while maintaining the aesthetic value of the national stadium. During a significant incident, MS users may encounter difficulties accessing the service due to network congestion. In this case, MNOs will need to add capacity to meet the demand for data transmission and voice call transactions. In the current situation, MS users have received poor service because they are unable to connect to the internet or make phone calls while attending a major event at a stadium. MS users will be able to access the network and enjoy live feeds via Facebook (FB) and other software applications without delay or interruption, as well as voice call congestion, following the implementation of the proposed solution. Using the Planning Methods, the results of the proposed solution will be compared to the results of the Walk Test and the coverage simulation analysis. Data statistics obtained from MNOs will explain the solution’s effectiveness in terms of signal quality level, with the Signal to Noise Ratio (SINR) recorded at -95 dBm below the threshold of -85 dBm to prevent interference with MS users. The Resource Block (RB) Utilization shows that all sectors are utilized at less than 70% of total available capacity, indicating that the congestion level is manageable and MS users can access the network without interruption. A key factor in the proposed study, known as Hybrid Combiner Circuit of Multi Network Operator for Capacity Enhancement Solution in Indoor Environment, is fast deployment, low maintenance, and a shared solution between MNOs.

Understanding Why People Change Their Technology Use in Protests: User Study on Ebonyi State Mobile Telecommunication Subscribers Experiences

The rise in consumers complains against their service/tech providers has empowered government of various nations to set up Consumer Complaint Commissions. Some corporate organizations who wish to handle the complaints of their customers usually set up an in-house/internal customer care centres, a platform through which they attend to their customers’ needs. This research therefore is interested in exploring the reasons for user-protests among the mobile telecommunication subscribers in Ebonyi State, Nigeria against their network service providers. To arrive at this, we designed a research questionnaire to capture the experiences of the subscribers of the 4 major mobile telecommunication network service provider companies operating in the state. The participants were recruited through physical administration of research instrument and social media such as facebook, whatsapp and email platforms with a total of 72 participants feedbacks received. The users responses on the various issues raised on our questionnaire were thematically analyzed and represented using adequate data presentation tools. Our results proved that there are growing numbers of disgruntled customers among subscribers of the various network providers. From our survey, we gathered that 81.90% of the respondents have engaged in protest use at one point or the other against their service providers with MTN network topping the list with 36.50%, followed by GLO network 27%, Airtel network 23.80% and 9 Mobile 12.70%. Finally, we proposed a design prototype named “Komplain” that will serve as rallying system for the protest users to use and prosecute their actions. The system can also recommend actions which the protesters may undertake.

Mental Health and Meditation Practices of Pregnant Women during COVID-19

Introduction: The purpose of this paper was to describe pregnant women’s COVID-19 perceptions, mental health and meditation habits compared to non-pregnant women in a sample of meditation mobile app subscribers.

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.