Mobile Communication Networks Research Articles

Research on Dynamic Updating Technology of Digital Maps for Mobile Communications Based on Multi source Remote Sensing Images

Abstract. With the rapid development of 5G networks in China, mobile communication network simulation technology has gradually become a widely studied direction in the academic and application fields. This study focuses on three-dimensional digital geographic information data for mobile communication, including a large amount of geographic information data that significantly affects the propagation of mobile communication radio waves, such as terrain height and ground use types. These data play a crucial role in coverage prediction, interference analysis, and frequency planning in various telecommunications planning software. This article starts from the perspective of mobile communication network management, and combines typical large-scale terrain data production practice projects for mobile communication to deeply study the process and system function design of combining geographic information systems with multi-source remote sensing data in mobile communication network monitoring and management. On this basis, this study designed and implemented a dynamic updated terrain database for mobile communication. This database can update geographic information data in real-time, ensuring the timeliness and accuracy of the data. At the same time, by optimizing the database structure and query algorithms, the speed and efficiency of data processing have been improved, providing efficient and reliable solutions for coverage prediction, optimization analysis, and planning management of large-scale mobile communication networks.In summary, dynamic updating database of three-dimensional digital geographic information has important application value in mobile communication network simulation technology. Through in-depth research and application of this database, the performance and service quality of mobile communication networks can be effectively improved, laying a solid foundation for future communication technology development.

An optimized cooperative data transmission scheme in relay‐enabled cellular communication networks

SummaryCooperative transmission is of great significance in data transmission and resource schedule in mobile cellular communication networks. To attain the desired network transmission performance objectives over the whole cellular network system, we propose an appropriate cooperative data transmission scheme to optimize the data delivery efficiency in terms of the transmission time consumption for each and every transmission group. The proposed transmission optimization scheme includes the tasks of determining the transmission group, allocating the channel rate resource, specifying the cooperative transmission mechanism, and performing resource allocation and schedule as well. Firstly, we propose a utility function based rate allocation scheme to optimize the channel rate resource utilization for all those transmission groups over the cellular communication network. Based on it, we further present a cooperative data transmission scheme to deal with the data delivery and reception for all those subgroups with high efficiency over the whole network system. Particularly, we propose a resource efficiency function‐based coordination scheduling (EFCS) scheme to conduct the cooperative data transmission and resource schedule as well for each transmission group within the network. The EFCS scheme facilitates to determine the subgroups for schedule over each scheduling cycle, which can produce the best data transmission efficiency across both the direct and cooperative transmission hop. Both the theoretical analysis and the simulation evaluation results verify the superior performance of our proposed cooperative data transmission scheme.

Edge Caching Data Distribution Strategy with Minimum Energy Consumption.

In the context of the rapid development of the Internet of Vehicles, virtual reality, automatic driving and the industrial Internet, the terminal devices in the network show explosive growth. As a result, more and more information is generated from the edge of the network, which makes the data throughput increase dramatically in the mobile communication network. As the key technology of the fifth-generation mobile communication network, mobile edge caching technology which caches popular data to the edge server deployed at the edge of the network avoids the data transmission delay of the backhaul link and the occurrence of network congestion. With the growing scale of the network, distributing hot data from cloud servers to edge servers will generate huge energy consumption. To realize the green and sustainable development of the communication industry and reduce the energy consumption of distribution of data that needs to be cached in edge servers, we make the first attempt to propose and solve the problem of edge caching data distribution with minimum energy consumption (ECDDMEC) in this paper. First, we model and formulate the problem as a constrained optimization problem and then prove its NP-hardness. Subsequently, we design a greedy algorithm with computational complexity of O(n2) to solve the problem approximately. Experimental results show that compared with the distribution strategy of each edge server directly requesting data from the cloud server, the strategy obtained by the algorithm can significantly reduce the energy consumption of data distribution.

UAVs-assisted QoS guarantee scheme of IoT applications for reliable mobile edge computing

Unmanned aerial vehicles (UAVs) assisted mobile edge computing (MEC) is an emerging network architecture that has been considered as a promising transformative service paradigm. It enhances the coverage of intelligent mobile communication network and promotes the rapid development of a wide range of internet of things (IoT) applications. However, the ever-increasing data transmission demands given rise by these IoT applications based on MEC have posed significant challenges to the service of quality (QoS) guarantee of UAVs-assited MEC (UAVs-MEC) network. To address the issue, we propose a novel UAVs-MEC QoS guarantee scheme that can enhances the reliability of IoT applications in UAVs-MEC network. Specifically, a dynamic QoS-aware based service level agreement (SLA) compliance verification model for MEC service is proposed in the scheme. It can monitor and detect the consistency of dynamic QoS of IoT applications through UAVs to ensure the continuous SLA compliance of service provided by MEC. Additionally, an objective weight assignment method and an adaptive update method are presented to improve the accuracy and scalability of the scheme. Finally, the simulation experiments conducted using a real-world dataset show that the proposed scheme can efficiently and effectively verify the SLA compliance of MEC service for guaranteeing QoS of IoT applications in UAVs-MEC context while outperforms other existing SLA violation detection methods.

An NLOS Ranging Error Mitigation Method for 5G Positioning in Indoor Environments

Positioning based on wireless signals such as mobile communication networks has become an important means to provide high-precision location services in environments where satellite signals are blocked. In complex environments such as indoors and underground, wireless signal propagation is obstructed and non-line-of-sight (NLOS) phenomena appear due to serious occlusion and reflection. The time delay caused by NLOS effects has little impact on communication system but can significantly increase positioning errors in positioning systems. Therefore, the effective suppression of NLOS errors is crucial to improving 5G positioning accuracy. To address the insufficient feature extraction of existing NLOS error suppression methods, the neglect of residual NLOS measurement errors, and poor stability of position estimation results, this paper innovatively proposes an NLOS mitigation and location estimation method for 5G positioning terminals. Simulation and experimental test results demonstrate that the proposed method outperforms the comparative methods both theoretically and practically, achieving an average positioning accuracy of 1.85 m in complex indoor NLOS environments. The method proposed in this paper provides a new strategy for NLOS error suppression in indoor 5G positioning, which can significantly contribute to high-precision location services based on commercial 5G networks.

Analysis of mobility robustness optimization in ultra-dense heterogeneous networks

Stable and reliable wireless connections during the user equipment's mobility are the critical issue in future mobile communication networks especially during UE's high-speed scenarios over dense heterogeneous networks (HetNets). Thus, setting an accurate value for the handover control parameters (HCPs) (i.e., time-to-trigger (TTT) and handover margin (HOM)) at different speed scenarios is required for system performance. This study proposes six different systems and each one employs different HCP settings using various mobile speed scenarios over a HetNet. Several performance metrics (i.e., received signal reference power (RSRP), handover ping-pong (HOPP), radio link failure (RLF), handover probability (HOP), handover interruption time (HOIT), and handover failure (HOF)) were used as key performance indicators (KPIs) for systems evaluations. Furthermore, 20 users were evaluated in this study using a 40 ms measurement interval. The results show a different impacts of each system on the performance of the deployed HetNet. However, System 1 (lowest TTT & moderate HOM) was the best system in term of RSRP and RLF but on the expense of HOPP. Furthermore, assigning high level of the TTT and HOM (i.e., TTT >1000 ms and HOM >8 dB) leads to 0 HOPP but high RLFs. Moreover, the best system performance in term of HOP, HOIT, and HOF were System 6 (highest TTT & high HOM) with 0.06 %, 3 %, and 0.004 %, respectively. System 4 represents the best trading off system between HOPP and RLF due to the proper configuration of the HCPs. However, the aims of evaluating several systems based on fixed HCPs over several mobile speed scenarios were to see the behaviors of the systems performance when different setting values are applied. Furthermore, this study proposes a HO self-optimization algorithm for auto-tuning the HCPs. Weighted function algorithm along with a trigger timer is used for reducing unnecessary HOs while RLF minimized by setting a trigger timer under a certain conditions when the RSRP of the serving base station (BS) goes below the received signal strength indicators (RSSI). The proposed algorithm shows a significant improvement in term of HOPP, RLF, HOP, and HOF compared to System 4 and FLC algorithm. The RSRP of the proposed algorithm is kept within acceptable range. Thus, accurate setting values for the HCPs are significant to keep the tradeoff between RLF and HOPP at the minimum level.

Efficient and quantum‐secure authenticated key exchange scheme for mobile satellite communication networks

SummaryThe mobile satellite communication (MSC) system is a vital communication method in which mobile users and network control centers connect via satellites. Since the satellite's communication is wireless, communication security is a critical factor to ensure accountable communication. Key exchange and authentication (KEA) mechanism is widely used to achieve data security for data transmitted in an insecure or open channel. Different authentication systems are suggested in the last many years to establish safe communication, whereas most existing security protocols are based on factorization or discrete logarithm. However, these systems are no longer reliable by Shor's algorithm as any discrete logarithm and factorization can be resolved in polynomial time on quantum computers. Thus, developing a quantum secure KEA protocol for MSC systems is necessary. In this direction, recently a ring learning with an error‐based KEA technique is proposed to ensure a quantum‐safe environment. This scheme is quantum‐safe and satisfies desirable security attributes but has low efficiency in computation and communication. Moreover, establishing a secure session requires six communications among involved entities. As a result, replay attack detection at an early stage is not possible for the central authority (server), which could delay the server response, and the adversary gets the advantage of drawing a denial of service scenario for authorized entities. We propose a lattice‐based KEA protocol for the MSC system to improve computation, communication efficiency, and early‐stage replay attack detection. The security analysis of the proposed scheme is presented in the random oracle model. Calculation of performance is also presented to observe advantages in computation and communication overhead.

Cryptanalysis with improvement on lattice‐based authenticated key exchange protocol for mobile satellite communication networks

SummaryThe mobile satellite communication (MSC) system represents a crucial means of communication, facilitating connections between mobile users and network control centres through satellites. Given the wireless nature of satellite communication, ensuring communication security is paramount for maintaining accountability. Key exchange and authentication (KEA) mechanisms are commonly employed to secure data transmitted over insecure or open channels. Developing a lattice‐based KEA protocol for MSC systems is imperative to achieve both quantum security and efficient communication. In this direction, Yadav et al. devised ring learning with an error‐based KEA technique to ensure a quantum‐safe environment. Their scheme is quantum‐safe and satisfies desirable security attributes but has low efficiency in computation. Moreover, we have identified that their scheme is susceptible to denial of service attack and session key established at user and NCC ends is different. To overcome the flaws of Yadav et al., we propose a lattice‐based KEA protocol for the MSC system to improve computation efficiency, and get resistance against key mismatch attack. The security analysis of the proposed scheme is presented in the random oracle model. Comparative study is also presented to observe advantages in computation efficiency.

An approach for offloading with multi-hop considerations in an RSU signal overlay setting

In recent years, significant advancements in vehicle technology have spurred growing interest in Vehicular Ad hoc Networks (VANETs). This interest is driven by concerns for road safety and the need to alleviate network congestion, leading to the emergence of Intelligent Transport Systems (ITS). ITS focuses on improving road traffic management and safety through the utilization of wireless and mobile network communication technologies. VANETs play a pivotal role within the realm of ITS, facilitating tasks such as enhancing road safety, traffic monitoring, and ensuring passenger comfort by mitigating accidents and congestion. These objectives rely on the timely and accurate delivery of data to vehicle agents and relevant authorities, facilitated by reliable VANETs and Road Signal Units (RSUs). Achieving this necessitates identifying optimal routes with minimal distance, high radio access, and quality-awareness levels. To address these objectives, this study proposes the utilization of the Congestion Network with Predicted K-means multi-hop RSU algorithm (CN-MHMR) to enhance vehicular networking and communication. This algorithm facilitates efficient node transfer from base nodes to destination nodes via the shortest and energy-efficient paths, thereby enabling viable and reliable vehicular communications. The performance of the proposed model was evaluated based on various metrics, including energy consumption, throughput, delay, packet delivery ratio, accuracy, precision, and recall values.

Towards secure and efficient integration of blockchain and 6G networks.

The future of communication systems is undergoing a transformative shift towards intelligence, efficiency, and flexibility. Presently, the amalgamation of blockchain technology and the sixth-generation mobile communication network (6G) has garnered significant attention, as their fusion is poised to profoundly impact the digital economy and society at large. However, the convergence of blockchain and 6G networks poses challenges pertaining to security and performance. In this article, we propose an approach based on the design of secure mechanisms and performance optimization to delve into the key issues surrounding the integration of blockchain and 6G networks from both security and performance perspectives. Specifically, we first introduce the application scenarios of 6G networks and blockchain's empowerment of them to highlight the necessity of combining blockchain technology with 6G. Subsequently, in order to ensure the security of communication and data transmission between blockchain and 6G networks, we have investigated the design requirements for security mechanisms. Furthermore, we discuss the efficient realization of the amalgamation between blockchain and 6G networks by proposing a solution based on Directed Acyclic Graph (DAG) for blockchain's asynchronous consensus protocol, alongside optimization strategies for storage and communication to meet the desired characteristics and requirements of 6G networks. Lastly, we provide valuable research directions that serve as references and guidance for the future development of the integration between blockchain and 6G networks.

A Comprehensive Review of UAV-Assisted FSO Relay Systems

The evolving requirements of next-generation mobile communications networks can be met by leveraging vertically deployed Unmanned Aerial Vehicle (UAV) platforms integrated with Free Space Optical communications (FSO). This integration offers a flexible and scalable architecture capable of delivering high-rate communication without requiring licenses while aligning with the multi-gigabit paradigm. In recent times, the increasing availability of commercial aerial platforms has facilitated experimental demonstrations of UAV-enabled FSO systems, which play a crucial role in proposed backhaul networks and point-to-point communications by overcoming Line-of-Sight (LOS) challenges. These systems can be rapidly deployed to meet sudden demand scenarios. This document provides a comprehensive review of relevant field demonstrations of UAV-enabled FSO relay systems, with a particular focus on commercially available, free-flying platforms that are driving advancements in this domain. It categorizes the different platforms by considering the operational altitudes of these systems and their payload actuation capacity, which determines their adaptability to variables. The analysis aims to distill the design considerations that lead to optimal performance regarding communications throughput and other relevant metrics. Moreover, it also attempts to highlight areas where design choices have fallen short, indicating gaps in current research efforts toward the widespread adoption of UAV-enabled FSO relay systems. Finally, this work endeavors to outline effective design considerations, guidelines, and recommendations to bridge these identified gaps. It serves as a valuable reference guide for researchers involved in developing UAV-enabled FSO relay systems, enabling them to make informed decisions and pave the way for the successful implementation of such systems.

5G Indoor Positioning Error Correction Based on 5G-PECNN.

With the development of the mobile network communication industry, 5G has been widely used in the consumer market, and the application of 5G technology for indoor positioning has emerged. Like most indoor positioning techniques, the propagation of 5G signals in indoor spaces is affected by noise, multipath propagation interference, installation errors, and other factors, leading to errors in 5G indoor positioning. This paper aims to address these issues by first constructing a 5G indoor positioning dataset and analyzing the characteristics of 5G positioning errors. Subsequently, we propose a 5G Positioning Error Correction Neural Network (5G-PECNN) based on neural networks. This network employs a multi-level fusion network structure designed to adapt to the error characteristics of 5G through adaptive gradient descent. Experimental validation demonstrates that the algorithm proposed in this paper achieves superior error correction within the error region, significantly outperforming traditional neural networks.

Group Intelligent City Mobile Communication Network's Control Strategy based on Cellular Internet of Things

Mobile communication network optimization heavily depends on power control technology, which impacts the effectiveness of the network. This paper aims to enhance control over nonlinear mobile communication networks and achieve superior performance by applying the particle swarm optimization (PSO) algorithm in the control domain. Addressing limitations in the basic PSO algorithm, improvements are made and applied to urban mobile communication networks. The methodology involves modifying the PSO algorithm to address identified issues and applying the enhanced algorithm to communication network scenarios. Simulation results indicate that with an initial particle count of 10 and 100 iterations, the optimized values for and are 0.691 and 0.486, respectively, resulting in an objective function value of 55.514. This achievement validates the successful implementation of the optimization process for mobile communication network control. The findings reveal that the proposed grad particle swarm optimization (Grad-PSO) algorithm exhibits mobile network optimization by robust search capability and rapid convergence.

A Budget Constraint Incentive Mechanism Based on Risk Preferences of Collaborators in Edge Computing

Mobile Edge Computing (MEC) is a new distributed computing method based on the mobile communication network. It can provide cloud services and an IT service environment for application developers and service providers at the edge of the network. Computation offloading is a crucial technology of edge computing. However, computation offloading will consume the resources of the edge devices, and therefore the edge devices will not offload computation unconditionally. In addition, the service quality of edge computing applications is related to the cooperation rate of edge devices. Therefore, it is essential to design an appropriate incentive mechanism to motivate edge devices to execute computation offloading. However, the current existing incentive mechanisms have two problems: Firstly, existing mechanisms do not account for probability distortions under uncertainty in collaborator utility valuation models. Secondly, the platform ignores the risk preferences of collaborators in multiple rounds of decision-making. To address these issues, we propose an incentive mechanism based on risk preference, IMRP. The IMRP considers the collaborator’s probability distortion, introduces an uncertain utility bonus scheme, and builds a probability distortion model to influence the collaborator’s willingness to offload tasks. The IMRP also considers the collaborator’s risk preference and builds the collaborator’s risk preference model to influence the collaborator’s bidding decision. Simulation results show that our mechanism effectively improves the cooperation rate of edge devices and the utility of the requester.

Converging Towards Open Radio Access Networks – A Comprehensive Review

Radio Access Networks (RAN) have been an integral part of the cellular mobile communication systems since the deployment of Global System for Mobile Communication (GSM) networks and later for the legacy Universal Mobile Telecommunication Systems (UMTS) and Long Term Evolution (LTE) networks. However, due to increasing demands of the users, throughput, ultra-lower latency, virtualization of the network and to cater the seamless connectivity of millions of wireless devices with the cellular networks, the advent of RAN needs to be brought under consideration. In this paper the traditional RANs are discussed with the necessity for their transition into the Open RAN (ORAN), considering all its essential parameters. The constraints of the legacy RAN architectures are explored with an overview of the RAN intelligent controllers, ORAN and its types. This paper additionally examines the function of artificial intelligence in Common Public Radio Interface (CPRI), enhanched CPRI, and xApps in terms of use cases along with the challenges associated with their deployment. The paper also present challenges and future of ORAN.

Satellite-Terrestrial Integrated 6G: An Ultra-Dense LEO Networking Management Architecture

With the rapid development of low earth orbit (LEO) satellites, the ultra-dense LEO satellite-terrestrial integrated networking has become a promising paradigm to provide wide coverage, high capacity and flexible services for the sixth generation (6G) mobile communication networks. However, the natural heterogeneity, high dynamics, and large scale of ultradense LEO satellite networks pose new challenges to network control and management. To this end, in this article, we propose a medium earth orbit (MEO), low earth orbit (LEO) and satellite Earth stations (SESs) integrated multi-layered management architecture for the ultra-dense LEO satellite network, where global controllers and local controllers are introduced to reduce the network management complexity. With the aid of this hybrid multi-layered management framework, we can efficiently implement the network status control, mobility management, resource management, and service management in the satelliteterrestrial integrated network. To obtain proper global and local controllers with high management efficiency in the hybrid multilayered network management architecture, we further propose a novel and efficient grouping and clustering method for the ultradense LEO satellite network, where each group manager MEO satellite and cluster head (CH) LEO satellites are respectively considered as the global and local controllers of each LEO satellite group. Numerical simulations are carried out to evaluate the superiority and effectiveness of the proposed hybrid multilayered ultra-dense LEO networking management architecture.

An effective model for network selection and resource allocation in 5G heterogeneous network using hybrid heuristic-assisted multi-objective function

Multiple service requirements in various communication environments are fulfilled by the fifth-generation (5G) mobile communication network. Heterogeneous Networks (HetNet) have been introduced as a newly developed network structure. Conventional cellular networks have prominent limitations in terms of frequency utilization, coverage, proliferation of transmission services, and power consumption. The previously used approaches provide precise results but are time-consuming, making them tricky to apply for huge networks, and makes them complicated to solve multifaceted problems. In order to decrease complementary interference and accomplish spectrum sharing, an effective resource allocation technique is necessary. Likewise, interference produced by the potential Secondary Users (SUs) must be kept at a minimum value within the authorized network. Considering the perspective of the supplementary networks, it is vital to delegate networks to SUs in order to lower the gross contamination and manage the overall network’s quantity. An efficient method is developed on a heuristic basis in order to solve the issues regarding resource allocation in 5G networks. With the aid of every user device’s network properties, network selection, and resource allocation are considered the two major concerns that need to be attained in 5G heterogeneous network systems. To meet this requirement, the multi-objective constraints are considered with the help of the Integrated African Vultures with Grasshopper Optimization Algorithm (IAVGOA). The constraints that are taken into consideration are communication cost, interference between all the SU to the primary user, Quality of Service (QoS), and congestion control. The performance of the executed model is examined using various metrics. When compared with the existing models, the proposed method achieves impressive results in appropriately selecting the network and allocating the resources over 5G networks.

Secrecy outage performance of NOMA relay networks using partial relay selection in the presence of multiple colluding eavesdroppers

Nowadays, security becomes one of the utmost important issues in designing mobile communication networks, especially for non-orthogonal multiple access (NOMA), in which the users share the same bandwidth and time resource. Here, we rigorously derive the closed-form formulas of secrecy outage probability (SOP) for each user as well as the overall SOP of a NOMA relay networks consisting of two users, against the wiretap from multiple colluding eavesdroppers. All channels are assumed to be Rayleigh fading. To enhance the reliability of the legitimate communication, we exploit a partial relay selection (PRS) algorithm to select the best relay for forwarding instead of using the traditional multiple-relay (MR) forwarding scheme. For practical consideration, the successive interference cancellation (SIC) at the NOMA users is assumed to be imperfect, which is different from most of the previous works. The SOP obtained in this work is also benchmarked with the one that is obtained by using MR instead of PRS and OMA instead of NOMA, respectively. The analytical results are verified by Monte Carlo simulations, which also confirm that the PRS method outperforms the conventional MR approach.

An improved ACO based service composition algorithm in multi-cloud networks

In recent years, with the rapid development of mobile communication networks, some new services such as cloud virtual reality, holographic communication, and etc. continue to emerge. Service composition has been researched in cloud computing. however, as the fast development of edge clouds, the service components can be deployed on the edge clouds to reduce the composition latency, so the more flexible and intelligent service composition algorithms are urgently need to study. Based on this, we propose a service composition strategy under the multi-cloud environment, and we propose an ant colony optimization algorithm (ACO) based on the multi-pheromone mechanism to optimize the quality of service (QoS). To avoid the occurrence of local optima, we further introduce the mutation operation of the genetic algorithm. Finally, the simulation results show that the proposed algorithm can achieve better QoS parameters such as latency and response time while ensuring the stability of services.

Analyzing Distance-Based Registration with Two Location Areas: A Semi-Markov Process Approach

In order to connect an incoming call to the user equipment (UE) in a mobile communication network, the location information of the UE must be always kept in the network database. Therefore, the efficiency of the location registration method of reporting new location information to a mobile communication network whenever the location information of the UE changes directly affects the performance of the radio channel, which is a limited resource in a mobile communication network. This study deals with distance-based registration (DBR). DBR does not cause the ping-pong phenomenon known to be a main problem in zone-based registration. It shows good performance when assuming a random walk mobility model. To improve the performance of the original DBR with one location area (1D), a DBR with two location areas (2D) was proposed. It is known that 2D is better than 1D in most cases. However, unlike 1D, an accurate mathematical model for 2D has not been presented in previous studies, raising questions about whether an accurate performance comparison has been performed. In this study, we present an accurate mathematical model based on the semi-Markov process for performance analysis of 2D. We compared performances of 1D and 2D using the proposed mathematical model. Various numerical results showed that 2D with two-step paging was superior to 1D in most cases. However, when simultaneous paging was applied to 2D, 1D was better than 2D in most cases. In real situations, optimal performance can be achieved by reflecting the network situation in real time and dynamically changing the operating method using a better-performing model among these two methods.