Development Of Mobile Communications Research Articles

Rating Prediction for Mobile Applications via Collective Matrix Factorization Considering App Categories

The rapid development of Internet and mobile communication, smart phone, tablet computer and other mobile devices become widespread, they have become an indispensable part of life, changing the human lifestyle, way of working and learning style, it brings great convenience and fun to us. This paper mainly discusses the status of personalized recommendation system, mobile application and analyse the main problems of recommendation system. This research proposes a rising mobile application domain, which uses web crawling technique to get explicit feedback from a real-world mobile application market. The explicit feedback is the users’ ratings data on Apps and the corresponding category information. To establish a mobile application recommendation model based on user interest and categorization information and propose a novel collective matrix factorization algorithm. Through the crawled data, the improved algorithm, and the traditional collaborative. The traditional mobile application recommendation systems are mostly based on keyword search, popularity, download usage and categories, thus they do not make personalized recommendation to users, and invalid to find applications that users are interested in. Through the user’s historical behaviour, a personalized recommendation system can be established to recommend the applications that fit user’s interests effectively. This paper is based on the collective matrix factorization using user interest such as user’s ratings and category information, designs a personalized recommendation system for mobile applications by using the relationship between them.

Emerging light-emitting diodes for next-generation data communications

The continuing development of consumer electronics, mobile communications and advanced computing technologies has led to a rapid growth in data traffic, creating challenges for the communications industry. Light-emitting diode (LED)-based communication links are of potential use in both free space and optical interconnect applications, and LEDs based on emerging semiconductor materials, which can offer tunable optoelectronics properties and solution-processable manufacturing, are of particular interest in the development of next-generation data communications. Here we review the development of emerging LED materials—organic semiconductors, colloidal quantum dots and metal halide perovskites—for use in optical communications. We examine efforts to improve the modulation performance and device efficiency of these LEDs, and consider potential applications in on-chip interconnects and light fidelity (Li-Fi). We also explore the challenges that exist in developing practical high-speed LED-based data communication systems. This Review examines the development of emerging semiconductor materials—organic semiconductors, colloidal quantum dots and metal halide perovskites—for light-emitting diodes, considering efforts to improve modulation performance and device efficiency, as well as potential applications in on-chip interconnects and light fidelity (Li-Fi).

Research on Enterprise Internal Audit Work in Big Data Environment

Enterprise internal audit and internal control work are important parts of enterprise management, To increase corporate operating profit and to promote sustainable development of enterprises, corporate managers should professionally cope with the relationship between the internal audit and internal control of the enterprise and enhance the performance in both tasks simultaneously. Recently, due to the rapid development of Internet equipment and mobile communications, the advent of the big data era has brought some challenges to the internal audit work of enterprises. This article focuses on the internal audit of enterprises in the era of big data. The problems with the internal audit work of the enterprise will be analyzed and the corresponding internal audit work countermeasures will be provided.

Urban geographical patterns of the relationship between mobile communication, social networks and economic development – the case of Hungary

In the post-industrial age, the transformation of urban networks and urban regions was fundamentally influenced by the rapid spread of infocommunication technologies (ICT) and the Internet. People share information in their daily lives with the help of various ICT devices and ultimately generate georeferenced data that could obtain important information about people’s use of space, spatial movement and social connections. The main aim of the study is to explore the urban geographical and spatial impacts of ICT and social media networks in Hungarian cities. We focus on drawing territorial and settlement hierarchical patterns and clusters based on the mobile communication and online social network relationship data of Hungarian cities. The paper highlights the relationship between the intensity of mobile communication and the density and expansion of intercity social relations and the settlements’ level of economic development, respectively. The methodology is based on mobile phone call detail record (CDR) analysis and intercity network analysis of social media activities. Our findings suggest that different communication networks follow divergent spatial patterns in Hungary. The traditional East–West dichotomy of the Hungarian spatial divide is still reflected in mobile communication, but intercity clusters based on social media activities are usually aligned to the borders of administrative structures. In several cases, we were able to identify strong intercity links between settlements with a similar level of economic development of the mesolevel spatial structure that traverses over different counties and regional borders. Results on social and demographic issues suggest that ‘generation Z’ could play a key role in dampening the social and economic tensions created by the digital divide in the long run. Using a multidimensional explanatory model, we could demonstrate the growing interconnectedness between digital networks and economic development.

Design and fabrication of 2.4GHz rectangular patch antenna for Wi-fi application

In the last few decades, the development of wireless and mobile communication has influenced social and economic development. Billions of devices demand wireless connection which runs on data, voice and other applications. The antenna is an integral part of any wireless communication system. From the design perspective, the antenna must be compact, easy to manufacture, and cost-effective. This paper presents a design of a rectangular patch antenna, operating at 2.4GHz. The antenna is initially simulated on CST, required parametric sweep is carried out in terms of length and width of the patch, to resonate at 2.4GHz. The simulated antenna is then printed using a PCB printing machine, PCB Prototyping System, Eleven Lab. The printed antenna was tested using Keysight’s PNA-LN-5232A (Vector Network Analyzer). The measurements/ variation in the reflection coefficient were observed /noted within the vicinity of the human body and gold metal plus the human body, at different positions. Near the ear. The simulation results and measured results are in a good match. The designed antenna is suitable for the Wi-fi, WLAN, communication application.

The Development of Mobile Communications in 5G and 6G

Extensive use of communication and information technologies has led to the introduction of different generations of mobile communications. The first to fourth generations (1G-4G) of communication are fully recognized in the world, the fifth generation (5G) is gradually being implemented in different countries, and studies and research on the sixth generation (6G) are in the early stages. The development and deployment of the new generation of mobile communication will have a significant influence on the development and presentation of mobile communications. In this paper, a brief review of the development trend of mobile communication generations with a focus on 5G and especially 6G has been done with respect to the visions, technologies, challenges and issues related to these two generations.

Network Security Monitoring Method Based on Deep Learning

AbsrtactWith the rise and rapid development of mobile communication, big data and artificial intelligence technology, we are entering the era of mobile Internet. With the continuous intellectualization of network security and infrastructure, information technology has been widely used in the field of industrial control, making network security more and more open, which brings a new network security control system to the traditional relatively closed industrial control system. This paper mainly introduces the network security monitoring method based on deep learning. In this paper, the network security monitoring method based on deep learning is studied, and the network security monitoring planning is designed by using image analysis, and the feasibility of detection model and deep learning is analyzed reasonably. A network security monitoring method based on deep learning is designed. Through data collection, feature extraction and neural network model training of network security power consumption information, non-invasive network security monitoring is realized. This method can detect network security information attacks that cannot be found at the network level, and improve the security performance of network security. The experimental results show that the network security monitoring method for deep learning increases the network security efficiency by 24%. The limitations of the research on network security monitoring method for deep learning and the methods and paths to provide good network security monitoring planning for image analysis application are analyzed, discussed and summarized, so as to enrich the academic research results.

A heterogenous network selection algorithm for internet of vehicles based on comprehensive weight

With the development of mobile communications and Internet of things (IoT), the Internet of vehicles (IoV) has become commonplace. To integrate the heterogenous IoV networks, this paper mainly explores the heterogenous network selection mechanism for the IoV. Considering the diversity of IoV networks, the authors proposed a heterogenous network selection algorithm based on comprehensive weight. Based on different service scenarios and user preferences, the proposed algorithm obtains the subjective weights of candidate networks, calculates the objective weights of judgement indices by entropy method, and combines the subjective and objective weights into a comprehensive weight. On this basis, the candidate networks were analyzed by the utility function (UF), and the optimal network was selected for access. The research results provide a reference for high-quality access to heterogenous networks.

A Precision Evaluation Index System for Remote Sensing Data Sampling Based on Hexagonal Discrete Grids

With the rapid development of earth observation, satellite navigation, mobile communication, and other technologies, the order of magnitude of the spatial data we acquire and accumulate is increasing, and higher requirements are put forward for the application and storage of spatial data. As a new form of data management, the global discrete grid can be used for the efficient storage and application of large-scale global spatial data, which is a digital multiresolution georeference model that helps to establish a new model of data association and fusion. It is expected to make up for the shortcomings in the organization, processing, and application of current spatial data. There are different types of grid systems according to the grid division form, including global discrete grids with equal latitude and longitude, global discrete grids with variable latitude and longitude, and global discrete grids based on regular polyhedrons. However, there is no accuracy evaluation index system for remote sensing images expressed on the global discrete grid to solve this problem. This paper is dedicated to finding a suitable way to express remote sensing data on discrete grids, as well as establishing a suitable accuracy evaluation system for modeling remote sensing data based on hexagonal grids to evaluate modeling accuracy. The results show that this accuracy evaluation method can evaluate and analyze remote sensing data based on hexagonal grids from multiple levels, and the comprehensive similarity coefficient of the images before and after conversion is greater than 98%, which further proves the availability of the hexagonal-grid-based remote sensing data of remote sensing images. This evaluation method is generally applicable to all raster remote sensing images based on hexagonal grids, and it can be used to evaluate the availability of hexagonal grid images.

A Survey of Computational Intelligence for 6G: Key Technologies, Applications and Trends

The ongoing deployment of 5G network involves the Internet of Things (IoT) as a new technology for the development of mobile communication, where the Internet of Everything (IoE) as the expansion of IoT has catalyzed the explosion of data and can trigger new eras. However, the fundamental and key component of the IoE depends on the computational intelligence (CI), which may be utilized in the sixth generation mobile communication system (6G). The motivation of this article presents the 6G enabled network in box (NIB) architecture as a powerful integrated solution that can support comprehensive network management and operations. The 6G enabled NIB can be used as an alternative method to meet the needs of next-generation mobile networks by dynamically reconfiguring the deployment of network functions, providing a high degree of flexibility for connection services in various situations. Especially the CI technology such as evolutionary computing, neural computing and fuzzy systems utilized as a part of NIB have inherent capabilities to handle various uncertainties, which have unique advantages in processing the variability and diversity of large amounts of data. Finally, CI technology for NIB, which is widely used is also introduced such as distributed computing, fog computing, and mobile edge computing in order to achieve different levels of sustainable computing infrastructure. This article discusses the key technologies, advantages, industrial scenario applications of CI technology as NIB, typical use cases and development trends based on IoE, which provides directional guidance for the development of CI technology as NIB for 6G.

Development of Campus Hotspot Network Infrastructure using Peer Connection Queue Method based on Voucher System

The use of wireless technology in today’s infrastructure has taken a very important role in the development of mobile communications. The use of wireless technology through the Wireless Distribution System (WDS) technique has also been widely applied to the hotspot network infrastructure in the campus area. WDS is a method of developing wireless network infrastructure that enables the development of wireless networks to become more extensive. However, distance and placement between access points become very important factors to consider that cause problem when sending data and when receiving data. Implementation of the PCQ method, which is one of the features of the proxy router, is aimed at ensuring the quality and performance of the network in good and optimal conditions. The quality of data services provided is regulated using a system voucher, the user is divided into several segments depending on the chosen service plan. This research begins with the planning stage which consists of design and topology selection, then continues with the design and implementation phase, and ends with the preparation phase. The test result data will then be compared with the standard determined by TIPHON which is 0% loss, 150 ms delay, and jitter under 75 ms.

GCNRDM: A Social Network Rumor Detection Method Based on Graph Convolutional Network in Mobile Computing

Mobile computing is a new technology emerging with the development of mobile communication, Internet, database, distributed computing, and other technologies. Mobile computing technology will enable computers or other information intelligent terminal devices to realize data transmission and resource sharing in the wireless environment. Its role is to bring useful, accurate, and timely information to any customer at anytime, anywhere, and to change the way people live and work. In mobile computing environment, a lot of Internet rumors hidden among the huge amounts of information communication network can cause harm to society and people’s life; this paper proposes a model of social network rumor detection based on convolution networks, the use of adjacency matrix between the nodes represent user and the relationship between the constructions of social network topology. We use a high‐order graph neural network (K‐GNN) to extract the rumor posting features. At the same time, the graph attention network (GAT) is used to extract the association features of other nodes of the network topology. The experimental results show that the method of the detection model in this paper improves the accuracy of prediction classification compared with deep learning methods such as RNN, GRU, and attention mechanism. The innovation of the paper proposes a rumor detection model based on the graph convolutional network, which lies in considering the propagation structure among users. It has a strong practical value.

An improved PCA-based multi-channel audio coding scheme

Abstract In recent years, multi-channel audio coding has become an important research area with the rapid development of mobile communication. This paper proposes a multi-channel audio coding scheme based on adaptive channel grouping and an improved principal component analysis algorithm. The channel grouping algorithm divides a multi-channel audio signal into multiple channel groups according to the correlation coefficient between channels. The improved principal component analysis averages the data to obtain the covariance matrix and it can concentrate the multi-channel audio signal components on as few channels as possible to achieve a reduction in signal dimensions. The experimental results show that the improved scheme achieves a higher reconstructed audio quality compared with the original scheme.

Joint Content Placement and Storage Allocation Based on Federated Learning in F-RANs

With the rapid development of mobile communication and the sharp increase of smart mobile devices, wireless data traffic has experienced explosive growth in recent years, thus injecting tremendous traffic into the network. Fog Radio Access Network (F-RAN) is a promising wireless network architecture to accommodate the fast growing data traffic and improve the performance of network service. By deploying content caching in F-RAN, fast and repeatable data access can be achieved, which reduces network traffic and transmission latency. Due to the capacity limit of caches, it is essential to predict the popularity of the content and pre-cache them in edge nodes. In general, the classic prediction approaches require the gathering of users’ personal information at a central unit, giving rise to users’ privacy issues. In this paper, we propose an intelligent F-RANs framework based on federated learning (FL), which does not require gathering user data centrally on the server for training, so it can effectively ensure the privacy of users. In the work, federated learning is applied to user demand prediction, which can accurately predict the content popularity distribution in the network. In addition, to minimize the total traffic cost of the network in consideration of user content requests, we address the allocation of storage resources and content placement in the network as an integrated model and formulate it as an Integer Linear Programming (ILP) problem. Due to the high computational complexity of the ILP problem, two heuristic algorithms are designed to solve it. Simulation results show that the performance of our proposed algorithm is close to the optimal solution.

Evaluating of Impact of Provision of Infrastructure on the Economic Development of Russian Regions

The article examines the impact of provision of infrastructure on the economic growth dynamics of Russian regions, taking into account spatial externalities. The main hypothesis of the study is that the characteristics of provision of transport, energy, and telecommunications infrastructure affect the growth rates of the real GRP of Russian regions, but the nature of this impact depends on their specialization and level of development. The results of panel regression estimation have shown that development of the road network and mobile communications has a significant impact on the economic growth dynamics in Russian regions, and the external effects from development of the corresponding infrastructure in neighboring regions are positive. Infrastructural restrictions affect the economic growth dynamics in the less developed eastern part of the country to a greater extent than in the western part. Regions with specialization in the manufacturing benefit the most from the development of transport infrastructure in neighboring regions, as well as from the increase in the volume of generating capacity in their territory. Although in 2001–2017 the development of mobile communications had a positive impact on the economic growth dynamics in many Russian regions, due to the completion of the process of expanding mobile communications throughout the country, the possibilities of using this growth factor in the future have been all but exhausted.

Empirical analysis on human dynamics of sharing-bicycles’ user behavior

With the development of mobile communication and global positioning system navigation and positioning technology, analysis of user behavior on mobile Internet has become a hot topic in research area. Sign in sharing-bicycles’ app, find bicycle location, and selected has become a part of mobile Internet user’s daily life. Based on the data analysis of the spatial and temporal characteristics, find out sharing-bicycle’s user behavior obeys power-law distribution. In the time interval, user behavior of sharing-bicycle has strong intermittency and weak memory; the exponent of probability that K edge nodes is three by fitting the distance of sharing-bicycle’s data curve. It is verified that mobile Internet is long to scale-free networks. We conclude seven characteristics of user’s behavior of sharing-bicycle in mobile Internet application from experimental results. The analysis of sharing-bicycle’s behavior has become a complement and extension in human dynamics research field.

Location Privacy-Preserving Method Based on Historical Proximity Location

With the rapid development of Internet services, mobile communications, and IoT applications, Location-Based Service (LBS) has become an indispensable part in our daily life in recent years. However, when users benefit from LBSs, the collection and analysis of users’ location data and trajectory information may jeopardize their privacy. To address this problem, a new privacy-preserving method based on historical proximity locations is proposed. The main idea of this approach is to substitute one existing historical adjacent location around the user for his/her current location and then submit the selected location to the LBS server. This method ensures that the user can obtain location-based services without submitting the real location information to the untrusted LBS server, which can improve the privacy-preserving level while reducing the calculation and communication overhead on the server side. Furthermore, our scheme can not only provide privacy preservation in snapshot queries but also protect trajectory privacy in continuous LBSs. Compared with other location privacy-preserving methods such as k-anonymity and dummy location, our scheme improves the quality of LBS and query efficiency while keeping a satisfactory privacy level.

ANALYSIS OF THE PROCESS OF CREATION AND USE OF MOBILE APPLICATIONS

At the present time, thanks to the fact that the world works in the information space with a large amount of information, it has become one of the most important measures for that, in a short time, for a short period of time. Therefore, for informing the world, only one computer connection became insufficient, it is very important to expand the connection through mobile devices, to use and develop mobile applications. Necessary information technologies for the integration of mobile communications are actively developing. This article discusses the widespread use of mobile applications for the development of mobile communications and their classification by structure and composition. Consider the features

Reliability-Aware and Deadline-Constrained Mobile Service Composition Over Opportunistic Networks

An opportunistic link between two mobile devices or nodes can be constructed when they are within each other’s communication range. Typically, cyber–physical environments consist of a number of mobile devices that are potentially able to establish opportunistic contacts and serve mobile applications in a cost-effective way. Opportunistic mobile service computing is a promising paradigm capable of utilizing the pervasive mobile computational resources around the users. Mobile users are thus allowed to exploit nearby mobile services to boost their computing capabilities without investment in their resource pool. Nevertheless, various challenges, especially its quality-of-service and reliability-aware scheduling, are yet to be addressed. Existing studies and related scheduling strategies consider mobile users to be fully stable and available. In this article, we propose a novel method for reliability-aware and deadline-constrained service composition over opportunistic networks. We leverage the Krill–Herd-based algorithm to yield a deadline-constrained, reliability-aware, and well-executable service composition schedule based on the estimation of completion time and reliability of schedule candidates. We carry out extensive case studies based on some well-known mobile service composition templates and a real-world opportunistic contact data set. The comparison results suggest that the proposed approach outperforms existing ones in terms of success rate and completion time of composed services. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Recently, the rapid development of mobile devices and mobile communication leads to the prosperity of mobile service computing. Services running on mobile devices within a limited range are allowed to be composed to coordinate through wireless communication technologies and perform complex tasks and business processes. Despite its great potential, mobile service compositions remains a challenge since the mobility of users and devices imposes high unpredictability on the execution of tasks. A careful investigation into existing methods has found their various limitations, e.g., assuming time-invariant availability of mobile services. This article presents a novel reliability-aware and deadline-constrained service composition method for mobile opportunistic networks. Instead of assuming time-invariant availability of mobile nodes, the proposed method is capable of estimating service availability at run-time and leveraging a Krill–Herd-based algorithm to yield the deadline-constrained, reliability-aware, and well-executable service composition schedules. Case studies based on well-known service composition templates and real-world data sets suggest that it outperforms traditional ones in terms of success and completion time of composed services. It can thus aid the design and optimization of composite services as well as their smooth execution in a mobile environment. It can help practitioners better manage the reliability and performance of real-world applications built upon mobile services.

Markov Model for HF Joint Spectrum Occupancy at Two Distant Locations

Abstract Even with the present-day development of mobile communications in UHF and SHF spectral bands and recent trends to move to mmWave, HF radio communications still offer advantages that make them exclusive in some application areas. Cognitive Radio principles can be applied to HF communications, to make use of the spectrum more efficiently. A significant improvement of Cognitive Radio technique can be achieved by spectrum occupancy prediction, which enables proactive efficient spectrum utilization. Hidden Markov Models (HMM) can be a useful tool for statistical spectrum occupancy prediction. In some of our previous works, we investigated a simple HMM in time domain, as well as a bidimensional model, that take into account both the time domain and the frequency domain. In this paper, we propose to extend the coverage of the model, by considering in addition to time and frequency the geographical position of the two points involved in the radio connection. The work is motivated by the fact that the two points of the radio link in HF can be far apart, and the channel availability at the two points could be different. Therefore, finding and exploiting correlations between the spectrum occupancy at the two points might improve the connectivity. The proposed model is validated using real spectrum occupancy data collected simultaneously at two locations situated in two cities, namely Timișoara and Sibiu, Romania. The measurements have been made using two identical USRP equipment, GPS coordinated, and identical HF broadband antennas.