Mobile Communication Networks Research Articles

Risk Area Alert Through Heterogeneous Mobile Networks: A New Approach to Fight COVID-19 and Beyond

COVID-19 has now been sweeping the whole world, and fundamentally affecting our daily life. An effective mechanism to further fight against COVID-19 and prevent the spread of this pandemic is to alert people when they are in the vicinity of areas with a high infection risk, yielding them to adjust their routes and consequently, leave these areas. Inspired by the fact that mobile communication networks are capable of precise positioning, data processing and information broadcasting, as well as are available for almost every person, in this article, we propose a mobile network assisted Risk arEa ALerting scheme, named REAL, which exploits heterogeneous mobile networks to alert users who are in/near to the areas with high risks of COVID-19 infection. Specifically, in REAL scheme, all base stations (BSs) periodically estimate their serving users' locations, which are then analyzed by macro BSs (MBSs) to identify risk areas. Next, each MBS transmits the information about risk areas to small BSs (SBSs), which in their turn adjust the beamforming direction to cover these areas and send alerts to users located therein. Simulation results validate the effectiveness of the proposed REAL scheme. In addition, some key challenges associated with implementing REAL are discussed at the end.

Optimal resource scheduling algorithm for cell boundaries users in heterogenous 5G networks

Deployment of small cells over the existing cellular network is an effective solution to improve the system coverage and throughput of fifth generation (5G) mobile communication networks. The arrival of the 5G mobile networks have demonstrated the importance of advanced scheduling techniques to manage the limited frequency spectrum available while achieving 5G transmission requirements. Cellular networks of the future necessitate the formulation of efficient resource allocation schemes that mitigate the interference between the different cells. In this research work, we formulate an optimization problem for heterogenous networks (HetNets) for resource allocation to maximize the system throughput among the cell center users (CCUs) and cell edge users (CEUs). We solve the optimization problem by effective utilization of the weight factors distribution for resource allocation. A novel Utility-based Resource Scheduling Algorithm (URSA) optimizes the resource sharing among the users with better delay budget of each application. The designed URSA ameliorates fairness along with reduced cross layer interference for real and non-real time applications. Performance of the URSA has been evaluated and compared most relevant state of art algorithms using the matlab based simulators. Furthermore, simulation results validate the superiority of the proposed scheduling scheme against conventional techniques in terms of throughput, fairness, and spectral efficiency.

Retraction Note: Application of combined kernel function artificial intelligence algorithm in mobile communication network security authentication mechanism

Retraction Note: Application of combined kernel function artificial intelligence algorithm in mobile communication network security authentication mechanism

Open-Air Microwave Entanglement Distribution for Quantum Teleportation

Microwave technology plays a central role in current wireless communications, standing among them mobile communication and local area networks (LANs). The microwave range shows relevant advantages with respect to other frequencies in open-air transmission, such as low absorption losses and low energy consumption, and it is additionally the natural working frequency in superconducting quantum technologies. Entanglement distribution between separate parties is at the core of secure quantum communications. Therefore, understanding its limitations in realistic open-air settings, specially in the rather unexplored microwave regime, is crucial for transforming microwave quantum communications into a mainstream technology. Here, we investigate the feasibility of an open-air entanglement distribution scheme with microwave two-mode squeezed states. First, we study the reach of direct entanglement transmission in open-air, obtaining a maximum distance of approximately 500 meters in a realistic setting with state-of-the-art experimental parameters. Afterwards, we adapt entanglement distillation and entanglement swapping protocols to microwave technology in order to reduce environmental entanglement degradation. While entanglement distillation helps to increase quantum correlations in the short-distance low-squeezing regime by up to $46\%$, entanglement swapping increases the reach by $14\%$. Then, we compute the fidelity of a continuous-variable quantum teleportation protocol using open-air-distributed entanglement as a resource. Finally, we adapt the machinery to explore the limitations of quantum communication between satellites, where the thermal noise impact is substantially reduced and diffraction losses are dominant.

An adaptive GA-based slice provisioning method for vertical industries in 5G and beyond networks

The fifth-generation of mobile communication networks are expected to support a large number of vertical industries requiring services with diverging requirements. In this vein, mobile networks have been witnessing a radical transformation to satisfy three key services types, ultra-reliable low-latency communication, enhanced mobile broadband, and massive machine-type communication, that will coexist on the same network infrastructure thanks to the network slicing paradigm. Moreover, a distributed user-plane deployment is introduced, allowing edge deployment of delay-sensitive applications thanks to the multi-access edge computing technology. However, designing resilient, elastic, end-to-end slice provisioning mechanisms is still an open issue. In this paper, we study the problem of end-to-end network slice provisioning for different vertical industries whose requested services are modeled as service function chains spanning from the radio access to the application and including user plane and control plane functionalities. Two slice provisioning strategies are considered by formulating a mixed integer linear programming problem and considering different objective functions allowing network operators to deploy the services while pursuing specific business logic. Further, an adaptive genetic algorithm based approach is proposed to solve the same problem in a short time scale by improving the search-space exploration while the population evolves. The simulation results demonstrate the effectiveness of the approach providing near-optimal solutions while drastically reducing the computational complexity.

Guest Editorial Special Issue on Antenna Array Enabled Space/Air/Ground Communications and Networking

With the rapid development of electronic and information technologies, the Internet of Everything (IoE) has become one of the trendiest topics in both academia and industry. Therein, many types of space/air/ground platforms need to be connected to networks for breaking down the isolation of information islands and providing various services. Space/air/ground platforms, such as satellites, unmanned aerial vehicles (UAVs), airships, balloons, terrestrial vehicles, and high-speed trains (HSTs) have emerged for accomplishing various complex tasks. Wireless communication is one of the most important technologies to support the real-time delivery of control commands and mission-related data. On the other hand, the space-air-ground integrated network has become a promising paradigm for the six-generation (6G) mobile communication network, where the aerospace and terrestrial vehicles may need to connect to existing mobile cellular networks or act as base stations (BSs) or relays to assist terrestrial wireless communications. To meet the ever-increasing demands of high capacity, wide coverage, low latency, and strong robustness for communications, it is promising to adopt large-scale antenna arrays at the transceivers to obtain considerable array gains and improve the channel quality. Antenna array-enabled beamforming technologies can facilitate spectrum reuse, interference mitigation, coverage enhancement, and physical-layer security. Antenna arrays can also be used to promote the sensing capability of space/air/ground networks, where the sensing information may be carefully processed to assist communications. However, enabling antenna array for space/air/ground communication networks poses specific, distinctive, and tricky challenges in antenna array design, physical layer, multiple access control layer, and network layer. As a result, numerous new research issues require to be addressed, which cover a wide range of disciplines including communication theory, network theory, antenna theory, signal processing, protocol design, resource allocation, optimization, hardware implementation, and experimentation.

Mathematical models of non-stationary random processes in the SVVP representation

The work examines methods and mathematical models that provide the possibility of researching the statistical characteristics of complex and non-stationary random processes describing a wide class of physical phenomena. The proposed models can be used to study the processes observed in various fields of human activity, namely, to analyze the trajectories of unmanned aerial vehicles, their acoustic signals, meteorological processes reflecting the state of the atmosphere.
 Real and simulated non-stationary random processes considered in the work are represented by the complex vector random process (CVRP) model. In this case, the length of the subvector is equal to the period of the seasonal component. In fact, in such a representation, the time series readings are replaced by their aggregate, i.e. subvectors. Statistical relationships are analyzed for subvectors, and not, as usual, for process counts. If the length of the subvector is equal to one, all operations in the SVVP representation are equivalent to the usual operations for time series.
 The mathematical apparatus developed in the article was used to analyze changes in time series of atmospheric temperature observed over a long period of time; average annual temperatures were estimated with subsequent smoothing with a low-pass filter. The results obtained can be used to analyze medium-term and long-term changes in atmospheric conditions, refine the results obtained by traditional methods of mathematical statistics, analyze and predict data flows in mobile communication networks, as well as in other areas of human activity.

Discussion on the Solution of Interference Problem in Mobile Communication Network

Discussion on the Solution of Interference Problem in Mobile Communication Network

Analyzing Zone-Based Registration under 2-Step Paging in Mobile Communication Network

In this study, we have considered zone-based registration (ZBR), which is the most widely adopted type in mobile communication networks. Based on a performance comparison between one-zone-based registration (1ZR) and two-zone-based registration (2ZR), 2ZR is known to be superior to 1ZR in most cases. However, the existing studies on the comparison of 1ZR and 2ZR have a critical problem: The basic assumption in 1ZR is that the entire zone is paged simultaneously when a call arrives, whereas, in 2ZR, the zone is paged by two steps. With these different paging schemes, a proper comparison cannot be made. Therefore, in this study, we analyzed the performance of 1ZR by adopting 2-step paging (2SP) such as 2ZR for a proper performance comparison under equivalent conditions. This study also presents an analytical model of assigning paging areas under 2SP in 1ZR when the zone consists of multiple cells. Considering the mobility characteristics assumed in the previous studies on 2ZR, we have presented the mobility model for movement among cells in a zone, obtained the steady-state probability of each cell by using the Markov chain model to calculate the paging cost under 2SP, and ultimately calculated the total signaling cost. Through various numerical results, it was observed that, when 1ZR also adopts 2SP such as 2ZR, 1ZR can be superior to 2ZR in many cases. In conclusion, by adopting 2SP in both 1ZR and 2ZR, it would be possible to reduce the total signaling cost by selecting the better 1ZR and 2ZR while considering traffic changes.

Tennis Video Target Tracking Based on Mobile Network Communication and Machine Learning Algorithm

The application of information technology has realized the transformation of people’s production and lifestyle and also promoted the development of the sports industry. At present, the application of informatization in the field of sports is becoming more and more powerful. By using the advanced methods and technologies of its information display, this paper aimed to realize the research on the tracking of tennis sports video objects in the mobile network environment. It is helpful to analyze and solve the objectivity problems such as most of the loopholes in the single research and traditional methods of tennis video target tracking research. By drawing on the principles and rules of machine learning algorithms, the tennis video target tracking research is carried out, and the informatization and dataization of tennis are realized. In the experiment of the target tracking algorithm, 12 tracking videos have higher tracking accuracy than other parameters. The overall tracking accuracy of the video sequence under grayscale feature was 0.694; the tracking accuracy was the highest, but the tracking speed was the lowest compared to other parameters in the experiment. Therefore, it is very important to study the target tracking of tennis sports in the tennis field.

Precision planter monitoring system based on mobile communication network

AbstractSowing is an important link in agricultural production and the basis for ensuring high yields and bumper harvests. Agriculture requires precision plows with good performance and stable work. However, the seeding process is in a completely closed state, and the operator relies mainly on experience to judge the operating state and performance of the plow. The purpose of this study is to analyse the analysis and research methods of the precision planter monitoring system based on mobile communication technology. In this study, a relatively advanced target detection algorithm based on prediction and mobile communication technology is adopted. The Kalman filter is applied to the precision planter monitoring tradition, in order to realise a more complete and customisable automatic monitoring system. The intelligent monitoring system and the corn precision planter can realise the stepless regulation of the planting spacing within 10–30 cm through the experimental design of three plant spacing parameter schemes of 10 , 20 and 30 cm. Its various operational performance indicators have met the standards stipulated by the state.

Simulation on Basketball Recognition Based on Mobile Network Communication and Panoramic Vision

At present, the application of information technology has realized the transformation of people’s production and lifestyle, and it has also promoted the transformation of the sports industry. At present, the application of informatization in the basketball field in the sports industry is increasing. By using the advanced methods and technologies of its information display, this article aims at realizing the optimization of the basketball recognition pattern in the mobile network communication environment to promote the ecological development of the sports industry. It proposes to use panoramic vision to guide the integration of computer network and basketball field, which is helpful to analyze and solve the objectivity problems of single action and system incompatibility in basketball recognition simulation. By referring to the principles and laws of panoramic vision, the identification module and simulation module of the basketball auxiliary training system are constructed and optimized, so as to realize the promotion of basketball and the ecologicalization of teaching. In the research on the basketball recognition simulation system, the three-dimensional skeleton key point coordinate data are input into the ST-GCN network for comparison and testing. Specifically, it includes 2D key point coordinate data and 3D key point coordinate data as input to conduct model research and testing in the self-made basketball dataset. The experimental results show that the recognition rates of 2D and 3D coordinates are 66.64% and 87.69%, respectively. Therefore, it is crucial to use the human panoramic vision algorithm to convert 2D coordinates to 3D coordinates.

Technique for Large-Scale Antenna Beamforming Based on Neural Network

The commercialization of the fifth-generation technology and the rapid development of Internet of Things technology have made mobile communication networks increasingly complex. Simultaneously, the massive terminal connections have caused serious interference between networks. Large-scale array antennas have become a hot topic of recent studies to improve the wireless transmission characteristics and spectrum resource utilization efficiency. This study was aimed at exploring using large-scale array antennas combined with neural networks in ultradense cells to improve the wireless signal transmission quality. The simulation results showed that the scheme realized not only the wireless signal transmission with a neural network but also the effective recovery of the source signal. Similarly, the application of this scheme effectively reduced the power consumption during signal transmission, the delay, and the interference.

Energy-efficient and high-spectrum-efficiency wireless transmission

With the deployment and commercialization of the fifth-generation (5G) mobile communication networks, the access nodes and data volume of wireless networks are showing massive and explosive growth. In this paper, we firstly review the research progress on the energy-efficient and spectrum-efficient wireless transmission, from the perspectives of both latency and energy consumption. We then provide several solutions to high-efficiency wireless transmission for the 5G wireless networks. Finally, we give some discussions about the future road for the design of energy-efficient and spectrum-efficient wireless transmission, which provides some theoretical reference for the system design of wireless networks and Internet of Things (IoT) networks.

Maintenance and Management Strategy of Mobile Communication Network Engineering

Maintenance and Management Strategy of Mobile Communication Network Engineering

Local-Partial Signal Combining Schemes for Cell-Free Large-Scale MU-MIMO Systems with Limited Fronthaul Capacity and Spatial Correlation Channels

Cell-free large-scale multi-user MIMO is a promising technology for the 5G-and-beyond mobile communication networks. Scalable signal processing is the key challenge in achieving the benefits of cell-free systems. This study examines a distributed approach for cell-free deployment with user-centric configuration and finite fronthaul capacity. Moreover, the impact of scaling the pilot length, the number of access points (APs), and the number of antennas per AP on the achievable average spectral efficiency are investigated. Using the dynamic cooperative clustering (DCC) technique and large-scale fading decoding process, we derive an approximation of the signal-to-interference-plus-noise ratio in the criteria of two local combining schemes: Local-Partial Regularized Zero Forcing (RZF) and Local Maximum Ratio (MR). The results indicate that distributed approaches in the cell-free system have the advantage of decreasing the fronthaul signaling and the computing complexity. The results also show that the Local-Partial RZF provides the highest average spectral efficiency among all the distributed combining schemes because the computational complexity of the Local-Partial RZF is independent of the UTs. Therefore, it does not grow as the number of user terminals (UTs) increases.

Security and Privacy in Artificial Intelligence-Enabled 6G

The sixth-generation (6G) mobile communication network is expected to provide world-connected smart and autonomous services by leveraging artificial intelligence (AI) technologies. In particular, federated learning (FL) is advocated to promote the implementations of ubiquitous AI applications in 6G, where massive distributed data is utilized to cooperatively train AI models as well as protect privacy and reduce resource consumption. However, due to the large number of interactions among mobile devices or infrastructures in FL, the AI inevitably suffers from a series of potential privacy and security risks. In this article, we investigate the security and privacy of AI-enabled 6G. Specifically, we first present the AI-enabled 6G architecture, including the space-air-ground-ocean integrated network (SAGOIN) architecture and two different FL-based AI model training frameworks in 6G. Furthermore, we discuss in detail the privacy and security threats, including cheating attack, low-quality local model training attack, and privacy stealing attack. Afterwards, we present a case study to design the security and privacy preservation scheme by integrating the trust evaluation, Q-learning based incentive, and local differential privacy (LDP) mechanism. Finally, we give out several future research directions in promising AI-enabled 6G.

GAN for Load Estimation and Traffic-Aware Network Selection for 5G Terminals

In the face of the user-centric access network architecture adopted by the fifth-generation (5G) mobile communication network terminals, the communication capability of terminals faces significant challenges. In this case, the combination of 5G and artificial intelligence (AI) has become a significant trend to meet the various communication needs of terminal devices. Toward the problem that the data analysis and decision making for cell load estimation are primarily accomplished on the access side of the network, terminals can only passively access the network, but cannot predict the load estimation on the access side of the network in advance and cannot make network selection decisions in real time. In this article, we propose a cell load estimation algorithm based on a generative adversarial network (GAN) for 5G mobile communication networks, which considers estimating the cell load according to the wireless information measured by the terminals. The algorithm effectively estimates the cell load at the terminal side, which reflects the intelligence of the terminals and solves the problems of low data transmission rate, high signaling cost, and time delay in the existing techniques for load estimation schemes at the network side, assisting users in making a real-time decision. The performance is evaluated through the system-level simulation, and the results indicate that the proposed model improves load estimation accuracy, simultaneously improving the network throughput and reducing the packet queuing delay, suitable for different heterogeneous network scenarios.

A State-of-the-Art Survey on Reconfigurable Intelligent Surface-Assisted Non-Orthogonal Multiple Access Networks

Reconfigurable intelligent surfaces (RISs) and nonorthogonal multiple access (NOMA) have been recognized as key enabling techniques for the envisioned sixth generation (6G) of mobile communication networks. The key feature of RISs is to intelligently reconfigure the wireless propagation environment, which was once considered to be fixed and untunable. The key idea of NOMA is to utilize users’ dynamic channel conditions to improve spectral efficiency and user fairness. Naturally, the two communication techniques are complementary to each other and can be integrated to cope with the challenging requirements envisioned for 6G mobile networks. This survey provides a comprehensive overview of the recent progress on the synergistic integration of RISs and NOMA. In particular, the basics of both techniques are introduced first, and then, the fundamentals of RIS-NOMA are discussed for two communication scenarios with different transceiver capabilities. Resource allocation is of paramount importance for the success of RIS-assisted NOMA networks, and various approaches, including artificial intelligence (AI)-empowered designs, are introduced. Security provisioning in RIS-NOMA networks is also discussed as wireless networks are prone to security attacks due to the nature of the shared wireless medium. Finally, the survey is concluded with detailed discussions of the challenges arising in the practical implementation of RIS-NOMA, future research directions, and emerging applications.

Corporate Environmental Governance Performance Evaluation and Index System Construction under the Mobile Communication System

As environmental pollution has become more and more serious, in order to alleviate environmental and energy problems, people have begun to find new ways of governance in environmental management. Many countries have proposed to incorporate environmental performance into corporate performance for assessment. Under the historical background that the construction of ecological civilization has risen to a national strategy, the research on corporate environmental performance has attracted more and more attention. This paper constructs an environmental performance evaluation index system, evaluates the environmental performance of the enterprise, finds out the problems in the environmental performance of the enterprise, and proposes improvement suggestions. This is conducive to the change of the environmental policy of the enterprise, the improvement of the environmental performance level of the enterprise, and the protection of the ecological environment. This article introduces the mobile communication network, constructs the LMS model of the satellite mobile communication system, and analyzes the structure and main functions of the model. The article explains the role of corporate environmental governance, builds an environmental performance indicator system, selects several companies to evaluate the environmental governance performance of the past two years, and obtains the comprehensive performance index, stress index, state improvement index, and response index of the four companies in 2020. The four indexes of company A are 1.28, 1.3, 12, and 1.45, and the four indexes of company B are 2.96, 3.1, 8, and 2.9.