The Fifth Generation of Mobile Communications for Railways(5G-R)brings significant opportunities for the rail industry.However,alongside the potential and benefits of the railway 5G network are complex security challe...The Fifth Generation of Mobile Communications for Railways(5G-R)brings significant opportunities for the rail industry.However,alongside the potential and benefits of the railway 5G network are complex security challenges.Ensuring the security and reliability of railway 5G networks is therefore essential.This paper presents a detailed examination of security assessment techniques for railway 5G networks,focusing on addressing the unique security challenges in this field.In this paper,various security requirements in railway 5G networks are analyzed,and specific processes and methods for conducting comprehensive security risk assessments are presented.This study provides a framework for securing railway 5G network development and ensuring its long-term sustainability.展开更多
The explosive growth of data traffic and heterogeneous service requirements of 5G networks—covering Enhanced Mobile Broadband(eMBB),Ultra-Reliable Low Latency Communication(URLLC),and Massive Machine Type Communicati...The explosive growth of data traffic and heterogeneous service requirements of 5G networks—covering Enhanced Mobile Broadband(eMBB),Ultra-Reliable Low Latency Communication(URLLC),and Massive Machine Type Communication(mMTC)—present tremendous challenges to conventional methods of bandwidth allocation.A new deep reinforcement learning-based(DRL-based)bandwidth allocation system for real-time,dynamic management of 5G radio access networks is proposed in this paper.Unlike rule-based and static strategies,the proposed system dynamically updates itself according to shifting network conditions such as traffic load and channel conditions to maximize the achievable throughput,fairness,and compliance with QoS requirements.By using extensive simulations mimicking real-world 5G scenarios,the proposed DRL model outperforms current baselines like Long Short-Term Memory(LSTM),linear regression,round-robin,and greedy algorithms.It attains 90%–95%of the maximum theoretical achievable throughput and nearly twice the conventional equal allocation.It is also shown to react well under delay and reliability constraints,outperforming round-robin(hindered by excessive delay and packet loss)and proving to be more efficient than greedy approaches.In conclusion,the efficiency of DRL in optimizing the allocation of bandwidth is highlighted,and its potential to realize self-optimizing,Artificial Intelligence-assisted(AI-assisted)resource management in 5G as well as upcoming 6G networks is revealed.展开更多
In the traditional manufacturing industry system,the ceramic industry occupies animportant position due to its unique technological characteristics.As the core equipment for theproduction of artistic and daily-use cer...In the traditional manufacturing industry system,the ceramic industry occupies animportant position due to its unique technological characteristics.As the core equipment for theproduction of artistic and daily-use ceramics,the intermittent kiln has become an indispensable keylink in the industry by virtue of its advantage of flexibly adapting to the production of multiplevarieties in small batches.However,the current operation mode of ceramic intermittent kilns facessevere challenges:although instrument control has been initially achieved,the dependence on on-site manual operation and supervision,combined with the characteristics of small-scale andworkshop-style production,has led to widespread blind spots in supervision and numerous safetyrisks.Existing technologies mainly focus on the improvement of the kiln structure and theoptimization of local control,which is difficult to meet the complex requirements of collaborativemanagement and control of multiple kilns.The centralized ceramic kiln management and controldevice proposed in this paper deeply integrates Internet of Things technology and constructs anintelligent management system covering the entire ceramic production area.By collecting andtransmitting the operation data of the kiln in real time,this device not only enables all-weatherprecise monitoring of the state of the intermittent kiln,but also has the functions of intelligentaccident warning and remote control,providing a new technical path and practical model for theintelligent and safe development of the ceramic industry.展开更多
Fault diagnosis of 5G networks faces the challenges of heavy reliance on human experience and insufficient fault samples and relevant monitoring data.The digital twin technology can realize the interaction between vir...Fault diagnosis of 5G networks faces the challenges of heavy reliance on human experience and insufficient fault samples and relevant monitoring data.The digital twin technology can realize the interaction between virtual space and physical space through the fusion of model and data,providing a new paradigm for fault diagnosis.In this paper,we first propose a network digital twin model and apply it to 5G network diagnosis.We then use an improved Average Wasserstein GAN with Gradient Penalty(AWGAN-GP)method to discover and predict failures in the twin network.Finally,we use XGBoost algorithm to locate the faults in physical network in real time.Extensive simulation results show that the proposed approach can significantly increase fault prediction and diagnosis accuracy in the case of a small number of labeled failure samples in 5G networks.展开更多
The advanced design of a 10 × 1 linear antenna array system with the capa-bility of frequency tunability using GT3-23001 liquid crystal (LC) is pro-posed. The design for this reconfigurable wideband antenna array...The advanced design of a 10 × 1 linear antenna array system with the capa-bility of frequency tunability using GT3-23001 liquid crystal (LC) is pro-posed. The design for this reconfigurable wideband antenna array for 5G ap-plications at Ka-band millimeter-wave (mmw) consists of a double layer of stacked patch antenna with aperture coupled feeding. The bias voltage over LC varies from 0 V to 10.6 V to achieve a frequency tunability of 1.18 GHz. The array operates from 25.3 GHz to 33.8 GHz with a peak gain of 19.2 dB and a beamwidth of 5.2<span style="white-space:nowrap;">°</span> at 30 GHz. The proposed reconfigurable antenna ar-ray represents a real and efficient solution for the recent and future mmw 5G networks. The proposed antenna is suitable for 5G base stations in stadiums, malls and convention centers. It is proper for satellite communications and radars at mmw.展开更多
At present, 5G network technology is being applied to various social network modes, and it can provide technical and traffic support for social networks. Potential friendship discovery technology in 5G-enabled social ...At present, 5G network technology is being applied to various social network modes, and it can provide technical and traffic support for social networks. Potential friendship discovery technology in 5G-enabled social networks is beneficial for users to make potential friends and expand their range of activities and social hierarchy, which is highly sought after in today's social networks and has great economic and application value. However, the sparsity of the dominant user association dataset in 5G-enabled social networks and the limitations of traditional collaborative filtering algorithms are two major challenges for the friend recommendation problem. Therefore, in order to overcome these problems regarding previous models, we propose a Hybrid Ensemble Multiple Collaborative Filtering Model (HEMCF) for discovering potential buddy relationships. The HEMCF model draws on a special autoencoder method that can effectively exploit the association matrix between friends and additional information to extract a hidden representation of users containing global structural information. Then, it uses the random walk-based graph embedding algorithm DeepWalk to extract another hidden representation of users in the buddy network containing local structural information. Finally, in the output module, the HEMCF model stacks and multiplies the two types of hidden representations of users to ensure that the information mentioned above is concentrated in the final output to generate the final prediction value. The magnitude of the prediction value represents the probability of the users being friends, with larger values representing a high probability of the two users being friends, and vice versa. Experimental results show that the proposed method boosts the accuracy of the relationship prediction over baselines on 3 real-world public datasets dramatically.展开更多
The next-generation wireless networks are expected to provide higher capacity,system throughput with improved energy efficiency.One of the key technologies,to meet the demand for high-rate transmission,is deviceto-dev...The next-generation wireless networks are expected to provide higher capacity,system throughput with improved energy efficiency.One of the key technologies,to meet the demand for high-rate transmission,is deviceto-device(D2D)communication which allows users who are close to communicating directly instead of transiting through base stations,and D2D communication users to share the cellular user chain under the control of the cellular network.As a new generation of cellular network technology,D2D communication technology has the advantages of improving spectrum resource utilization and improving system throughput and has become one of the key technologies that have been widely concerned in the industry.However,due to the sharing of cellular network resources,D2D communication causes severe interference to existing cellular systems.One of the most important factors in D2D communication is the spectrum resources utilization and energy consumption which needs considerable attention from research scholars.To address these issues,this paper proposes an efficient algorithm based on the idea of particle swarm optimization.The main idea is to maximize the energy efficiency based on the overall link optimization of D2D user pairs by generating an allocation matrix of spectrum and power.The D2D users are enabled to reuse multiple cellular user’s resources by enhancing their total energy efficiency based on the quality of service constraints and the modification of location and speed in particle swarm.Such constraint also provides feasibility to solve the original fractional programming problem.Simulation results indicate that the proposed scheme effectively improved the energy efficiency and spectrum utilization as compared with other competing alternatives.展开更多
Growing client population, ever-increasing service demand, and complexity of services are the driving factors for the mobile operators for a paradigm shift in their core technology and radio access networks. 5G mobile...Growing client population, ever-increasing service demand, and complexity of services are the driving factors for the mobile operators for a paradigm shift in their core technology and radio access networks. 5G mobile network is the result of this paradigm shift and currently under deployment in many developed countries such as United States, United Kingdom, South Korea, Japan, and China—to name a few. However, most of the Least Developed Countries (LDCs) have very recently been implemented 4G mobile networks for which the overall role out phase is still not complete. In this paper, we investigate how feasible it is for LDCs to emphasize on a possible deployment of 5G networks at the moment. At first, we take a holistic approach to show the major technical challenges LDCs are likely to face while deploying the 5G mobile networks. Then we argue that various security aspects of 5G networks are an ongoing issue and LDCs are not technologically competent to handle many security glitches of 5G networks. At the same time, we show that most of the use cases of 5G networks are not applicable in the context of many LDCs (at least at the present time). Finally, this paper concludes that the start of the 5G network deployment in LDCs would take much longer time than expected.展开更多
Caching and virtualization have been considered as the promising techniques in 5G Networks. In 5G networks with virtualization, the caching resources deployed by infrastructure providers (InPs) can be abstracted into ...Caching and virtualization have been considered as the promising techniques in 5G Networks. In 5G networks with virtualization, the caching resources deployed by infrastructure providers (InPs) can be abstracted into isolated slices and transparently shared by mobile virtual network operators (MVNOs). In this case, one of the most important issues is how the MVNOs to share the caching resource. To solve this issue, different from previous works, a hierarchical caching architecture that core network and radio access network (RAN) have the caching capability in 5G networks with virtualization is first considered in this paper. Then, we study the problem of hierarchical caching resource sharing for MVNOs, and a competitive game to maximize their expectation revenue based on the oligopoly market model is formulated. As it is a hard problem to find the optimal solution in the hierarchical caching resource sharing problem, we decompose the optimization problem into two independent caching resource sharing problems in RAN and core network, respectively. Then the local optimal solutions are solved and the global Nash equilibrium solution is achieved. Finally, simulation results are illustrated to demonstrate the performance of the proposed scheme.展开更多
The pursuit of the higher performance mobile communications forces the emergence of the fifth generation mobile communication(5G). 5G network, integrating wireless and wired domain, can be qualified for the complex vi...The pursuit of the higher performance mobile communications forces the emergence of the fifth generation mobile communication(5G). 5G network, integrating wireless and wired domain, can be qualified for the complex virtual network work oriented to the cross-domain requirement. In this paper, we focus on the multi-domain virtual network embedding in a heterogeneous 5G network infrastructure, which facilitates the resource sharing for diverse-function demands from fixed/mobile end users. We proposed the mathematical ILP model for this problem.And based on the layered-substrate-resource auxiliary graph and an effective six-quadrant service-type-judgment method, 5G embedding demands can be classified accurately to match different user access densities. A collection of novel heuristic algorithms of virtual 5G network embedding are proposed. A great deal of numerical simulation results testified that our algorithm performed better in terms of average blocking rate, routing latency and wireless/wired resource utilization, compared with the benchmark.展开更多
5G is the hottest topic in telecommunication area in recent years.ITU has defined 5G as IMT-2020,and presented the scenarios of IMT-2020.These scenarios for IMT-2020 can be concluded as follows：-Enhanced Mobile Broad...5G is the hottest topic in telecommunication area in recent years.ITU has defined 5G as IMT-2020,and presented the scenarios of IMT-2020.These scenarios for IMT-2020 can be concluded as follows：-Enhanced Mobile Broadband：Mobile Broadband addresses the human-centric use cases for access to multi-media content,services and data.The demand for mobile展开更多
Mobile cellular data networks have allowed users to access the Internet whilst on the move. Many companies use this technology in their products. Examples of this would be Smart Meters in the home and Tesla cars havin...Mobile cellular data networks have allowed users to access the Internet whilst on the move. Many companies use this technology in their products. Examples of this would be Smart Meters in the home and Tesla cars having their “over the air updates”. Both of these two companies use the 4G and 5G technology. So this report will include a technical overview of the technology and protocols (LTE Advanced) used in 4G and 5G networks and how they provide services to the user and how data is transferred within the networks. And there are lots of different parts about the network architecture between the 4G and 5G systems. This report will talk about some different parts between these two systems and some challenges in them.展开更多
With the increasing demand for data traffic and with the massive foreseen deployment of the Internet of Things (IoT), higher data rates and capacity are required in mobile networks. While Heterogeneous Networks (HetNe...With the increasing demand for data traffic and with the massive foreseen deployment of the Internet of Things (IoT), higher data rates and capacity are required in mobile networks. While Heterogeneous Networks (HetNets) are under study toward 5G technology, Wireless Fidelity (WiFi) Access Points (APs) are considered a potential layer within those multiple Radio Access Technologies (RATs). For this purpose, we have proposed in this paper a novel WiFi dimensioning method, to offload data traffic from Long Term Evolution (LTE) to WiFi, by transferring the LTE energy consuming heavy users, to the WiFi network. First, we have calculated the remaining available capacity of the WiFi network based on the estimated load of each WiFi physical channel using the overlapping characteristic of the channels. Then, we were able through this dimensioning method, to calculate the minimum needed number of WiFi APs that ensure the same or better throughput for the LTE transferred users. By this method, we have ensured additional capacity in the LTE network with minimum investment cost in the WiFi network. Finally, we have estimated the profit sharing between LTE and WiFi by considering data bundles subscription revenues and the infrastructure capital and operational costs. We have calculated for each network the profit share using a coalition game theory Shapley value that pinpoints the benefit of the cooperation using the proposed dimensioning method.展开更多
As investigated by 3GPP,support of UPF(user plane function)onboard satellite can reduce the latency of communications via satellite,and then it becomes a key enhancement in 5G network integrating with satellite commun...As investigated by 3GPP,support of UPF(user plane function)onboard satellite can reduce the latency of communications via satellite,and then it becomes a key enhancement in 5G network integrating with satellite communication.However,current 5G system cannot support UPF onboard LEO(low earth orbit)satellites,as it would face challenges like UPF mobility handling,synchronization between mobile network and satellite network,and condition of activating local data switching.To solve such challenges,this paper proposes a solution to support UPF onboard LEO satellite,which consists of enhanced network architecture,I-UPF(intermediate UPF)based local data switching scheme and communication latency based data path selection.We subsequently develop analytic models for performance evaluation and conduct simulations using the constellation configuration of iridium II.The simulation results show that the data switching via I-UPF onboard LEO satellite can reduce E2E(end to end)packet delivery latency and E2E packet loss ratio significantly compared with that of routing the data back to 5GC on the ground.The proposed scheme yet has increased signaling cost for handling UPF mobility.els,compared with existing similar companding algorithms.展开更多
Smart edge computing(SEC)is a novel paradigm for computing that could transfer cloud-based applications to the edge network,supporting computation-intensive services like face detection and natural language processing...Smart edge computing(SEC)is a novel paradigm for computing that could transfer cloud-based applications to the edge network,supporting computation-intensive services like face detection and natural language processing.A core feature of mobile edge computing,SEC improves user experience and device performance by offloading local activities to edge processors.In this framework,blockchain technology is utilized to ensure secure and trustworthy communication between edge devices and servers,protecting against potential security threats.Additionally,Deep Learning algorithms are employed to analyze resource availability and optimize computation offloading decisions dynamically.IoT applications that require significant resources can benefit from SEC,which has better coverage.Although access is constantly changing and network devices have heterogeneous resources,it is not easy to create consistent,dependable,and instantaneous communication between edge devices and their processors,specifically in 5G Heterogeneous Network(HN)situations.Thus,an Intelligent Management of Resources for Smart Edge Computing(IMRSEC)framework,which combines blockchain,edge computing,and Artificial Intelligence(AI)into 5G HNs,has been proposed in this paper.As a result,a unique dual schedule deep reinforcement learning(DS-DRL)technique has been developed,consisting of a rapid schedule learning process and a slow schedule learning process.The primary objective is to minimize overall unloading latency and system resource usage by optimizing computation offloading,resource allocation,and application caching.Simulation results demonstrate that the DS-DRL approach reduces task execution time by 32%,validating the method’s effectiveness within the IMRSEC framework.展开更多
Artificial intelligence(AI)has been widely envisioned as a key enabler for 5G and beyond networks.To integrate AI into mobile networks,the third generation partnership(3GPP)introduces the network data analytics functi...Artificial intelligence(AI)has been widely envisioned as a key enabler for 5G and beyond networks.To integrate AI into mobile networks,the third generation partnership(3GPP)introduces the network data analytics function(NWDAF)starting from Release 15 to support“in-network”learning and inference,and further supports federated learning(FL)from Release 16 to protect data privacy.However,practical deployment of federated learning in 5G networks still faces challenges of high communication overhead and potential risks of model and data leakage.Motivated by these challenges,we propose a hierarchical networking and privacy-preserving federated learning(HiNP-FL)framework for 5G networks.Specifically,in the HiNP-FL framework,1)we propose the hierarchical NWDAF based FL mechanism to reduce FL communication overhead in 5G networks;2)based on multi-party polynomial evaluation(OMPE),we design a FL model and data privacy protection mechanism for the hierarchical FL mechanism;3)we validate the privacy protection capability of the HiNP-FL framework through privacy analysis,and testify its effectiveness in terms of model accuracy and communication efficiency through extensive experiments.展开更多
The advent of 5G technology has revolutionized network communication by introducing network slicing(NS)and virtualization to allow multiple network service providers(NSPs)to share infrastructure,thereby reducing deplo...The advent of 5G technology has revolutionized network communication by introducing network slicing(NS)and virtualization to allow multiple network service providers(NSPs)to share infrastructure,thereby reducing deployment costs and accelerating 5G adoption.While this new open marketplace enables NSPs to trade resources dynamically,it also exposes the system to security concerns,such as front-running and selfish-validation attacks,which can lead to market manipulation and strategy leakage.This paper presents TRADE-5G,a secure blockchainbased marketplace for 5G resource trading that mitigates these attacks and ensures fair,transparent resource allocation while preserving the cofidentiality of NSP strategies.Through extensive simulations,TRADE-5G demonstrates a substantial 18%improvement in user satisfaction and a 36%reduction in wasted resources compared to traditional models.Additionally,it opens new profit opportunities for NSPs through unused resources,establishing a more competitive,secure,and transparent 5G trading environment that exceeds the capabilities of traditional mobile networks.展开更多
基金supported in part by the Fundamental Research Funds for the Central Universities under Grant No.2025JBXT010in part by NSFC under Grant No.62171021,in part by the Project of China State Railway Group under Grant No.N2024B004in part by ZTE IndustryUniversityInstitute Cooperation Funds under Grant No.l23L00010.
文摘The Fifth Generation of Mobile Communications for Railways(5G-R)brings significant opportunities for the rail industry.However,alongside the potential and benefits of the railway 5G network are complex security challenges.Ensuring the security and reliability of railway 5G networks is therefore essential.This paper presents a detailed examination of security assessment techniques for railway 5G networks,focusing on addressing the unique security challenges in this field.In this paper,various security requirements in railway 5G networks are analyzed,and specific processes and methods for conducting comprehensive security risk assessments are presented.This study provides a framework for securing railway 5G network development and ensuring its long-term sustainability.
文摘The explosive growth of data traffic and heterogeneous service requirements of 5G networks—covering Enhanced Mobile Broadband(eMBB),Ultra-Reliable Low Latency Communication(URLLC),and Massive Machine Type Communication(mMTC)—present tremendous challenges to conventional methods of bandwidth allocation.A new deep reinforcement learning-based(DRL-based)bandwidth allocation system for real-time,dynamic management of 5G radio access networks is proposed in this paper.Unlike rule-based and static strategies,the proposed system dynamically updates itself according to shifting network conditions such as traffic load and channel conditions to maximize the achievable throughput,fairness,and compliance with QoS requirements.By using extensive simulations mimicking real-world 5G scenarios,the proposed DRL model outperforms current baselines like Long Short-Term Memory(LSTM),linear regression,round-robin,and greedy algorithms.It attains 90%–95%of the maximum theoretical achievable throughput and nearly twice the conventional equal allocation.It is also shown to react well under delay and reliability constraints,outperforming round-robin(hindered by excessive delay and packet loss)and proving to be more efficient than greedy approaches.In conclusion,the efficiency of DRL in optimizing the allocation of bandwidth is highlighted,and its potential to realize self-optimizing,Artificial Intelligence-assisted(AI-assisted)resource management in 5G as well as upcoming 6G networks is revealed.
基金supported by Jiangxi 03 Special and 5G Project(20232ABC03A33)Ganpo Talent Support Program(20232BCJ23106)。
文摘In the traditional manufacturing industry system,the ceramic industry occupies animportant position due to its unique technological characteristics.As the core equipment for theproduction of artistic and daily-use ceramics,the intermittent kiln has become an indispensable keylink in the industry by virtue of its advantage of flexibly adapting to the production of multiplevarieties in small batches.However,the current operation mode of ceramic intermittent kilns facessevere challenges:although instrument control has been initially achieved,the dependence on on-site manual operation and supervision,combined with the characteristics of small-scale andworkshop-style production,has led to widespread blind spots in supervision and numerous safetyrisks.Existing technologies mainly focus on the improvement of the kiln structure and theoptimization of local control,which is difficult to meet the complex requirements of collaborativemanagement and control of multiple kilns.The centralized ceramic kiln management and controldevice proposed in this paper deeply integrates Internet of Things technology and constructs anintelligent management system covering the entire ceramic production area.By collecting andtransmitting the operation data of the kiln in real time,this device not only enables all-weatherprecise monitoring of the state of the intermittent kiln,but also has the functions of intelligentaccident warning and remote control,providing a new technical path and practical model for theintelligent and safe development of the ceramic industry.
基金supported by Natural Science Foundation of China(61871237,92067101)Program to Cultivate Middle-aged and Young Science Leaders of Universities of Jiangsu Province+1 种基金Key R&D plan of Jiangsu Province(BE2021013-3)。
文摘Fault diagnosis of 5G networks faces the challenges of heavy reliance on human experience and insufficient fault samples and relevant monitoring data.The digital twin technology can realize the interaction between virtual space and physical space through the fusion of model and data,providing a new paradigm for fault diagnosis.In this paper,we first propose a network digital twin model and apply it to 5G network diagnosis.We then use an improved Average Wasserstein GAN with Gradient Penalty(AWGAN-GP)method to discover and predict failures in the twin network.Finally,we use XGBoost algorithm to locate the faults in physical network in real time.Extensive simulation results show that the proposed approach can significantly increase fault prediction and diagnosis accuracy in the case of a small number of labeled failure samples in 5G networks.
文摘The advanced design of a 10 × 1 linear antenna array system with the capa-bility of frequency tunability using GT3-23001 liquid crystal (LC) is pro-posed. The design for this reconfigurable wideband antenna array for 5G ap-plications at Ka-band millimeter-wave (mmw) consists of a double layer of stacked patch antenna with aperture coupled feeding. The bias voltage over LC varies from 0 V to 10.6 V to achieve a frequency tunability of 1.18 GHz. The array operates from 25.3 GHz to 33.8 GHz with a peak gain of 19.2 dB and a beamwidth of 5.2<span style="white-space:nowrap;">°</span> at 30 GHz. The proposed reconfigurable antenna ar-ray represents a real and efficient solution for the recent and future mmw 5G networks. The proposed antenna is suitable for 5G base stations in stadiums, malls and convention centers. It is proper for satellite communications and radars at mmw.
基金supported by National Key R&D Program of China(Grant No:2018YFC0407904)Key Research Projects of Tibet Autonomous Region for Innovation and Entrepreneur(Grant No.Z2016D01G01/01).
文摘At present, 5G network technology is being applied to various social network modes, and it can provide technical and traffic support for social networks. Potential friendship discovery technology in 5G-enabled social networks is beneficial for users to make potential friends and expand their range of activities and social hierarchy, which is highly sought after in today's social networks and has great economic and application value. However, the sparsity of the dominant user association dataset in 5G-enabled social networks and the limitations of traditional collaborative filtering algorithms are two major challenges for the friend recommendation problem. Therefore, in order to overcome these problems regarding previous models, we propose a Hybrid Ensemble Multiple Collaborative Filtering Model (HEMCF) for discovering potential buddy relationships. The HEMCF model draws on a special autoencoder method that can effectively exploit the association matrix between friends and additional information to extract a hidden representation of users containing global structural information. Then, it uses the random walk-based graph embedding algorithm DeepWalk to extract another hidden representation of users in the buddy network containing local structural information. Finally, in the output module, the HEMCF model stacks and multiplies the two types of hidden representations of users to ensure that the information mentioned above is concentrated in the final output to generate the final prediction value. The magnitude of the prediction value represents the probability of the users being friends, with larger values representing a high probability of the two users being friends, and vice versa. Experimental results show that the proposed method boosts the accuracy of the relationship prediction over baselines on 3 real-world public datasets dramatically.
文摘The next-generation wireless networks are expected to provide higher capacity,system throughput with improved energy efficiency.One of the key technologies,to meet the demand for high-rate transmission,is deviceto-device(D2D)communication which allows users who are close to communicating directly instead of transiting through base stations,and D2D communication users to share the cellular user chain under the control of the cellular network.As a new generation of cellular network technology,D2D communication technology has the advantages of improving spectrum resource utilization and improving system throughput and has become one of the key technologies that have been widely concerned in the industry.However,due to the sharing of cellular network resources,D2D communication causes severe interference to existing cellular systems.One of the most important factors in D2D communication is the spectrum resources utilization and energy consumption which needs considerable attention from research scholars.To address these issues,this paper proposes an efficient algorithm based on the idea of particle swarm optimization.The main idea is to maximize the energy efficiency based on the overall link optimization of D2D user pairs by generating an allocation matrix of spectrum and power.The D2D users are enabled to reuse multiple cellular user’s resources by enhancing their total energy efficiency based on the quality of service constraints and the modification of location and speed in particle swarm.Such constraint also provides feasibility to solve the original fractional programming problem.Simulation results indicate that the proposed scheme effectively improved the energy efficiency and spectrum utilization as compared with other competing alternatives.
文摘Growing client population, ever-increasing service demand, and complexity of services are the driving factors for the mobile operators for a paradigm shift in their core technology and radio access networks. 5G mobile network is the result of this paradigm shift and currently under deployment in many developed countries such as United States, United Kingdom, South Korea, Japan, and China—to name a few. However, most of the Least Developed Countries (LDCs) have very recently been implemented 4G mobile networks for which the overall role out phase is still not complete. In this paper, we investigate how feasible it is for LDCs to emphasize on a possible deployment of 5G networks at the moment. At first, we take a holistic approach to show the major technical challenges LDCs are likely to face while deploying the 5G mobile networks. Then we argue that various security aspects of 5G networks are an ongoing issue and LDCs are not technologically competent to handle many security glitches of 5G networks. At the same time, we show that most of the use cases of 5G networks are not applicable in the context of many LDCs (at least at the present time). Finally, this paper concludes that the start of the 5G network deployment in LDCs would take much longer time than expected.
基金support by the Major National Science and Technology Projects (No. 2018ZX03001019-003, 2018ZX03001014-003)
文摘Caching and virtualization have been considered as the promising techniques in 5G Networks. In 5G networks with virtualization, the caching resources deployed by infrastructure providers (InPs) can be abstracted into isolated slices and transparently shared by mobile virtual network operators (MVNOs). In this case, one of the most important issues is how the MVNOs to share the caching resource. To solve this issue, different from previous works, a hierarchical caching architecture that core network and radio access network (RAN) have the caching capability in 5G networks with virtualization is first considered in this paper. Then, we study the problem of hierarchical caching resource sharing for MVNOs, and a competitive game to maximize their expectation revenue based on the oligopoly market model is formulated. As it is a hard problem to find the optimal solution in the hierarchical caching resource sharing problem, we decompose the optimization problem into two independent caching resource sharing problems in RAN and core network, respectively. Then the local optimal solutions are solved and the global Nash equilibrium solution is achieved. Finally, simulation results are illustrated to demonstrate the performance of the proposed scheme.
基金supported in part by Open Foundation of State Key Laboratory of Information Photonics and Optical Communications (Grant No. IPOC2014B009)Fundamental Research Funds for the Central Universities (Grant Nos. N130817002, N150401002)+1 种基金Foundation of the Education Department of Liaoning Province (Grant No. L2014089)National Natural Science Foundation of China (Grant Nos. 61302070, 61401082, 61471109, 61502075, 91438110)
文摘The pursuit of the higher performance mobile communications forces the emergence of the fifth generation mobile communication(5G). 5G network, integrating wireless and wired domain, can be qualified for the complex virtual network work oriented to the cross-domain requirement. In this paper, we focus on the multi-domain virtual network embedding in a heterogeneous 5G network infrastructure, which facilitates the resource sharing for diverse-function demands from fixed/mobile end users. We proposed the mathematical ILP model for this problem.And based on the layered-substrate-resource auxiliary graph and an effective six-quadrant service-type-judgment method, 5G embedding demands can be classified accurately to match different user access densities. A collection of novel heuristic algorithms of virtual 5G network embedding are proposed. A great deal of numerical simulation results testified that our algorithm performed better in terms of average blocking rate, routing latency and wireless/wired resource utilization, compared with the benchmark.
文摘5G is the hottest topic in telecommunication area in recent years.ITU has defined 5G as IMT-2020,and presented the scenarios of IMT-2020.These scenarios for IMT-2020 can be concluded as follows：-Enhanced Mobile Broadband：Mobile Broadband addresses the human-centric use cases for access to multi-media content,services and data.The demand for mobile
文摘Mobile cellular data networks have allowed users to access the Internet whilst on the move. Many companies use this technology in their products. Examples of this would be Smart Meters in the home and Tesla cars having their “over the air updates”. Both of these two companies use the 4G and 5G technology. So this report will include a technical overview of the technology and protocols (LTE Advanced) used in 4G and 5G networks and how they provide services to the user and how data is transferred within the networks. And there are lots of different parts about the network architecture between the 4G and 5G systems. This report will talk about some different parts between these two systems and some challenges in them.
文摘With the increasing demand for data traffic and with the massive foreseen deployment of the Internet of Things (IoT), higher data rates and capacity are required in mobile networks. While Heterogeneous Networks (HetNets) are under study toward 5G technology, Wireless Fidelity (WiFi) Access Points (APs) are considered a potential layer within those multiple Radio Access Technologies (RATs). For this purpose, we have proposed in this paper a novel WiFi dimensioning method, to offload data traffic from Long Term Evolution (LTE) to WiFi, by transferring the LTE energy consuming heavy users, to the WiFi network. First, we have calculated the remaining available capacity of the WiFi network based on the estimated load of each WiFi physical channel using the overlapping characteristic of the channels. Then, we were able through this dimensioning method, to calculate the minimum needed number of WiFi APs that ensure the same or better throughput for the LTE transferred users. By this method, we have ensured additional capacity in the LTE network with minimum investment cost in the WiFi network. Finally, we have estimated the profit sharing between LTE and WiFi by considering data bundles subscription revenues and the infrastructure capital and operational costs. We have calculated for each network the profit share using a coalition game theory Shapley value that pinpoints the benefit of the cooperation using the proposed dimensioning method.
基金supported by the national key research and development program of China under Grant 2020YFB1807901the National Science Foundation Project in China under grant 61931005.
文摘As investigated by 3GPP,support of UPF(user plane function)onboard satellite can reduce the latency of communications via satellite,and then it becomes a key enhancement in 5G network integrating with satellite communication.However,current 5G system cannot support UPF onboard LEO(low earth orbit)satellites,as it would face challenges like UPF mobility handling,synchronization between mobile network and satellite network,and condition of activating local data switching.To solve such challenges,this paper proposes a solution to support UPF onboard LEO satellite,which consists of enhanced network architecture,I-UPF(intermediate UPF)based local data switching scheme and communication latency based data path selection.We subsequently develop analytic models for performance evaluation and conduct simulations using the constellation configuration of iridium II.The simulation results show that the data switching via I-UPF onboard LEO satellite can reduce E2E(end to end)packet delivery latency and E2E packet loss ratio significantly compared with that of routing the data back to 5GC on the ground.The proposed scheme yet has increased signaling cost for handling UPF mobility.els,compared with existing similar companding algorithms.
文摘Smart edge computing(SEC)is a novel paradigm for computing that could transfer cloud-based applications to the edge network,supporting computation-intensive services like face detection and natural language processing.A core feature of mobile edge computing,SEC improves user experience and device performance by offloading local activities to edge processors.In this framework,blockchain technology is utilized to ensure secure and trustworthy communication between edge devices and servers,protecting against potential security threats.Additionally,Deep Learning algorithms are employed to analyze resource availability and optimize computation offloading decisions dynamically.IoT applications that require significant resources can benefit from SEC,which has better coverage.Although access is constantly changing and network devices have heterogeneous resources,it is not easy to create consistent,dependable,and instantaneous communication between edge devices and their processors,specifically in 5G Heterogeneous Network(HN)situations.Thus,an Intelligent Management of Resources for Smart Edge Computing(IMRSEC)framework,which combines blockchain,edge computing,and Artificial Intelligence(AI)into 5G HNs,has been proposed in this paper.As a result,a unique dual schedule deep reinforcement learning(DS-DRL)technique has been developed,consisting of a rapid schedule learning process and a slow schedule learning process.The primary objective is to minimize overall unloading latency and system resource usage by optimizing computation offloading,resource allocation,and application caching.Simulation results demonstrate that the DS-DRL approach reduces task execution time by 32%,validating the method’s effectiveness within the IMRSEC framework.
基金supported by the Climbing Program of Institute of Information Engineering,Chinese Academy of Sciences under Grant E3Z0031.
文摘Artificial intelligence(AI)has been widely envisioned as a key enabler for 5G and beyond networks.To integrate AI into mobile networks,the third generation partnership(3GPP)introduces the network data analytics function(NWDAF)starting from Release 15 to support“in-network”learning and inference,and further supports federated learning(FL)from Release 16 to protect data privacy.However,practical deployment of federated learning in 5G networks still faces challenges of high communication overhead and potential risks of model and data leakage.Motivated by these challenges,we propose a hierarchical networking and privacy-preserving federated learning(HiNP-FL)framework for 5G networks.Specifically,in the HiNP-FL framework,1)we propose the hierarchical NWDAF based FL mechanism to reduce FL communication overhead in 5G networks;2)based on multi-party polynomial evaluation(OMPE),we design a FL model and data privacy protection mechanism for the hierarchical FL mechanism;3)we validate the privacy protection capability of the HiNP-FL framework through privacy analysis,and testify its effectiveness in terms of model accuracy and communication efficiency through extensive experiments.
文摘The advent of 5G technology has revolutionized network communication by introducing network slicing(NS)and virtualization to allow multiple network service providers(NSPs)to share infrastructure,thereby reducing deployment costs and accelerating 5G adoption.While this new open marketplace enables NSPs to trade resources dynamically,it also exposes the system to security concerns,such as front-running and selfish-validation attacks,which can lead to market manipulation and strategy leakage.This paper presents TRADE-5G,a secure blockchainbased marketplace for 5G resource trading that mitigates these attacks and ensures fair,transparent resource allocation while preserving the cofidentiality of NSP strategies.Through extensive simulations,TRADE-5G demonstrates a substantial 18%improvement in user satisfaction and a 36%reduction in wasted resources compared to traditional models.Additionally,it opens new profit opportunities for NSPs through unused resources,establishing a more competitive,secure,and transparent 5G trading environment that exceeds the capabilities of traditional mobile networks.
