Rapid development in Information Technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)transmission.Vehicular networks give a safe and more effect...Rapid development in Information Technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)transmission.Vehicular networks give a safe and more effective driving experience by presenting time-sensitive and location-aware data.The communication occurs directly between V2V and Base Station(BS)units such as the Road Side Unit(RSU),named as a Vehicle to Infrastructure(V2I).However,the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with time.Therefore,the scheme of an effectual routing protocol for reliable and stable communications is significant.Current research demonstrates that clustering is an intelligent method for effectual routing in a mobile environment.Therefore,this article presents a Falcon Optimization Algorithm-based Energy Efficient Communication Protocol for Cluster-based Routing(FOA-EECPCR)technique in VANETS.The FOA-EECPCR technique intends to group the vehicles and determine the shortest route in the VANET.To accomplish this,the FOA-EECPCR technique initially clusters the vehicles using FOA with fitness functions comprising energy,distance,and trust level.For the routing process,the Sparrow Search Algorithm(SSA)is derived with a fitness function that encompasses two variables,namely,energy and distance.A series of experiments have been conducted to exhibit the enhanced performance of the FOA-EECPCR method.The experimental outcomes demonstrate the enhanced performance of the FOA-EECPCR approach over other current methods.展开更多
The current resource allocation in 5G vehicular networks for mobile cloud communication faces several challenges,such as low user utilization,unbalanced resource allocation,and extended adaptive allocation time.We pro...The current resource allocation in 5G vehicular networks for mobile cloud communication faces several challenges,such as low user utilization,unbalanced resource allocation,and extended adaptive allocation time.We propose an adaptive allocation algorithm for mobile cloud communication resources in 5G vehicular networks to address these issues.This study analyzes the components of the 5G vehicular network architecture to determine the performance of different components.It is ascertained that the communication modes in 5G vehicular networks for mobile cloud communication include in-band and out-of-band modes.Furthermore,this study analyzes the single-hop and multi-hop modes in mobile cloud communication and calculates the resource transmission rate and bandwidth in different communication modes.The study also determines the scenario of one-way and two-way vehicle lane cloud communication network connectivity,calculates the probability of vehicle network connectivity under different mobile cloud communication radii,and determines the amount of cloud communication resources required by vehicles in different lane scenarios.Based on the communication status of users in 5G vehicular networks,this study calculates the bandwidth and transmission rate of the allocated channels using Shannon’s formula.It determines the adaptive allocation of cloud communication resources,introduces an objective function to obtain the optimal solution after allocation,and completes the adaptive allocation process.The experimental results demonstrate that,with the application of the proposed method,the maximum utilization of user communication resources reaches approximately 99%.The balance coefficient curve approaches 1,and the allocation time remains under 2 s.This indicates that the proposed method has higher adaptive allocation efficiency.展开更多
In this paper,joint location and velocity estimation(JLVE)of vehicular terminals for 6G integrated communication and sensing(ICAS)is studied.We aim to provide a unified performance analysis framework for ICAS-based JL...In this paper,joint location and velocity estimation(JLVE)of vehicular terminals for 6G integrated communication and sensing(ICAS)is studied.We aim to provide a unified performance analysis framework for ICAS-based JLVE,which is challenging due to random fading,multipath interference,and complexly coupled system models,and thus the impact of channel fading and multipath interference on JLVE performance is not fully understood.To address this challenge,we exploit structured information models of the JLVE problem to render tractable performance quantification.Firstly,an individual closedform Cramer-Rao lower bound for vehicular localization,velocity detection and channel estimation,respectively,is established for gaining insights into performance limits of ICAS-based JLVE.Secondly,the impact of system resource factors and fading environments,e.g.,system bandwidth,the number of subcarriers,carrier frequency,antenna array size,transmission distance,spatial channel correlation,channel covariance,the number of interference paths and noise power,on the JLVE performance is theoretically analyzed.The associated closed-form JLVE performance analysis can not only provide theoretical foundations for ICAS receiver design but also provide a perfor mance benchmark for various JLVE methods。展开更多
When there is an increasing interest in visible light communication(VLC), outdoor vehicle VLC has emerged as a promising candidate technology for future intelligent transportation systems. However, in VLC based vehicu...When there is an increasing interest in visible light communication(VLC), outdoor vehicle VLC has emerged as a promising candidate technology for future intelligent transportation systems. However, in VLC based vehicular applications, several challenges impede successful commercial application of VLC based products. This article first provides a thorough overview of the existing challenges. To overcome these challenges, we propose a novel architecture with tracking and environment sensing ability for practical vehicular applications. Moreover, a proof-ofconcept prototype is implemented to validate the feasibility of the proposed system. Experimental and simulation results show that the proposed VLC system can provide reliable communications with a bit-error rate less than 10-4for vehicles under strong interference lights. Finally, based on the evaluations, we propose some key design issues for future studies in this research area.展开更多
With the development of EMC technology, EMC assessment has become increasingly important in EMC design. Although numerous EMC assessment models are available today, few of them can provide a tradeoff between efficienc...With the development of EMC technology, EMC assessment has become increasingly important in EMC design. Although numerous EMC assessment models are available today, few of them can provide a tradeoff between efficiency and accuracy for the specific case of military vehicular communication systems. Face to this situation, a modified four-level assessment model is proposed in the paper. First, the development of EMC assessment technology is briefly reviewed, and the theoretical mechanism of EMI environment is introduced. Then, the architecture of the proposed model is outlined, and the assessment methods are explored. To demonstrate the application of it, an example involving a communication system in a military vehicle is presented. From the physical layer to the signal layer, a hierarchical assessment on the entire system is successfully performed based on the proposed model, and we can make a qualitative EMC assessment on the EMC performance of the system. Based on a comparison with the traditional model, we conclude that the proposed model is more accurate, more efficient and less time-consuming, which is suitable for the EMC assessment on militaryvehicular communication systems. We hope that the proposed model will serve as a useful reference for system-level EMC assessments for other systems.展开更多
Intelligent transportation system (ITS) is proposed as the most effective way to improve road safety and traffic efficiency. However, the future of ITS for large scale transportation infrastructures deployment highl...Intelligent transportation system (ITS) is proposed as the most effective way to improve road safety and traffic efficiency. However, the future of ITS for large scale transportation infrastructures deployment highly depends on the security level of vehicular communication systems (VCS). Security applications in VCS are fulfilled through secured group broadcast. Therefore, secure key management schemes are considered as a critical research topic for network security. In this paper, we propose a framework for providing secure key management within heterogeneous network. The seeurity managers (SMs) play a key role in the framework by retrieving the vehicle departnre infi^rmation, encapsulating block to transport keys and then executing rekeying to vehicles within the same security domain. The first part of this framework is a novel Group Key Management (GKM) scheme basing on leaving probability (LP) of vehicles to depart current VCS region. Vehicle's LP factor is introduced into GKM scheme to achieve a more effieient rekeying scheme and less rekeying costs. The second component of the framework using the blockchain concept to simplify the distributed key management in heterogeneous VCS domains. Extensive simulations and analysis are provided to show the effectiveness and effieiency of the proposed framework: Our GKM results demonstrate that probability-based BR reduees rekeying eost compared to the benchmark scheme, while the blockchain deereases the time eost of key transmission over heterogeneous net-works.展开更多
This paper derives a non-stationary multiple-input multiple-output(MIMO) from the one-ring scattering model. The proposed channel model characterizes vehicular radio propagation channels with considerations of moving ...This paper derives a non-stationary multiple-input multiple-output(MIMO) from the one-ring scattering model. The proposed channel model characterizes vehicular radio propagation channels with considerations of moving base and mobile stations, which makes the angle of arrivals(AOAs) along with the angle of departures(AODs) time-variant. We introduce the methodology of including the time-variant impacts when characterizing non-stationary radio propagation channels through the geometrical channel modelling approach. We analyze the statistical properties of the proposed channel model including the local time-variant autocorrelation function(ACF) and the space cross-correlation functions(CCFs). We show that the model developed in this paper for non-stationary scenarios includes the existing one-ring wide-sense stationary channel model as its special case.展开更多
Vehicle-to-vehicle(V2V)communication appeals to increasing research interest as a result of its applications to provide safety information as well as infotainment services.The increasing demand of transmit rates and v...Vehicle-to-vehicle(V2V)communication appeals to increasing research interest as a result of its applications to provide safety information as well as infotainment services.The increasing demand of transmit rates and various requirements of quality of services(QoS)in vehicular communication scenarios call for the integration of V2V communication systems and potential techniques in the future wireless communications,such as full duplex(FD)and non-orthogonal multiple access(NOMA)which enhance spectral efficiency and provide massive connectivity.However,the large amount of data transmission and user connectivity give rise to the concern of security issues and personal privacy.In order to analyze the security performance of V2V communications,we introduce a cooperative NOMA V2V system model with an FD relay.This paper focuses on the security performance of the FD-NOMA based V2V system on the physical layer perspective.We first derive several analytical results of the ergodic secrecy capacity.Then,we propose a secrecy sum rate optimization scheme utilizing the instantaneous channel state information(CSI),which is formulated as a non-convex optimization problem.Based on the differential structure of the non-convex constraints,the original problem is approximated and solved by a series of convex optimization problems.Simulation results validate the analytical results and the effectiveness of the secrecy sum rate optimization algorithm.展开更多
To achieve the better system performance for cooperative communication in non-orthogonal cognitive radio vehicular adhoc networks(CR-VANETs),this paper investigates the power allocation considering the interference to...To achieve the better system performance for cooperative communication in non-orthogonal cognitive radio vehicular adhoc networks(CR-VANETs),this paper investigates the power allocation considering the interference to the main system in a controllable range.We propose a three-slot one-way vehicle system model where the mobile vehicle nodes complete information interaction with the assistance of other independent nodes by borrowing the unused radio spectrum with the primary networks.The end-to-end SNR relationship in overlay and underlay cognitive communication system mode are analyzed by using two forwarding protocol,namely,decode-and-forward(DF)protocol and amplify-and-forward(AF)protocol,respectively.The system outage probability is derived and the optimal power allocation factor is obtained via seeking the minimum value of the approximation of system outage probability.The analytical results have been confirmed by means of Monte Carlo simulations.Simulation results show that the proposed system performance in terms of outage under the optimal power allocation is superior to that under the average power allocation,and is also better than that under other power allocation systems.展开更多
Vehicular safety applications, such as cooperative collision warning systems, rely on beaconing to provide situational awareness that is needed to predict and therefore to avoid possible collisions. Beaconing is the c...Vehicular safety applications, such as cooperative collision warning systems, rely on beaconing to provide situational awareness that is needed to predict and therefore to avoid possible collisions. Beaconing is the continual exchange of vehicle motion-state information, such as position, speed, and heading, which enables each vehicle to track its neighboring vehicles in real time. This work presents a context-aware adaptive beaconing scheme that dynamically adapts the beaconing repetition rate based on an estimated channel load and the danger severity of the interactions among vehicles. The safety, efficiency, and scalability of the new scheme is evaluated by simulating vehicle collisions caused by inattentive drivers under various road traffic densities. Simulation results show that the new scheme is more efficient and scalable, and is able to improve safety better than the existing non-adaptive and adaptive rate schemes.展开更多
Vehicular communications and networking can improve road safety, faeilitate intelligenl transporlation, support infotainment, dala sharing, and location based serviees, and will be a eritical component in the Internet...Vehicular communications and networking can improve road safety, faeilitate intelligenl transporlation, support infotainment, dala sharing, and location based serviees, and will be a eritical component in the Internet of Things. This special issue aims to present the state of the art in research and development of vehicular communication technology and its potential applications. We are soliciting original contribulions. The topics of interest include, but arc not limited to:展开更多
Avehicular ad hoc network (VANET) is a packet-switched network, consisting of mobile communication nodes mounted on vehicles, with very limited or no infrastructure support [1]. It supports communications among near...Avehicular ad hoc network (VANET) is a packet-switched network, consisting of mobile communication nodes mounted on vehicles, with very limited or no infrastructure support [1]. It supports communications among nearby vehicles,展开更多
Task offloading is a potential solution to satisfy the strict requirements of computation-intensive and latency-sensitive vehicular applications due to the limited onboard computing resources.However,the overwhelming ...Task offloading is a potential solution to satisfy the strict requirements of computation-intensive and latency-sensitive vehicular applications due to the limited onboard computing resources.However,the overwhelming upload traffic may lead to unacceptable uploading time.To tackle this issue,for tasks taking environmental data as input,the data perceived by roadside units(RSU)equipped with several sensors can be directly exploited for computation,resulting in a novel task offloading paradigm with integrated communications,sensing and computing(I-CSC).With this paradigm,vehicles can select to upload their sensed data to RSUs or transmit computing instructions to RSUs during the offloading.By optimizing the computation mode and network resources,in this paper,we investigate an I-CSC-based task offloading problem to reduce the cost caused by resource consumption while guaranteeing the latency of each task.Although this nonconvex problem can be handled by the alternating minimization(AM)algorithm that alternatively minimizes the divided four sub-problems,it leads to high computational complexity and local optimal solution.To tackle this challenge,we propose a creative structural knowledge-driven meta-learning(SKDML)method,involving both the model-based AM algorithm and neural networks.Specifically,borrowing the iterative structure of the AM algorithm,also referred to as structural knowledge,the proposed SKDML adopts long short-term memory(LSTM)networkbased meta-learning to learn an adaptive optimizer for updating variables in each sub-problem,instead of the handcrafted counterpart in the AM algorithm.Furthermore,to pull out the solution from the local optimum,our proposed SKDML updates parameters in LSTM with the global loss function.Simulation results demonstrate that our method outperforms both the AM algorithm and the meta-learning without structural knowledge in terms of both the online processing time and the network performance.展开更多
Recently,in the researches on vehicular Internet-of-Things(IoT),platooning have received lots of attentions due to its potential to improve the fuel efficiency and driving experience.Platoon is a group of vehicles tha...Recently,in the researches on vehicular Internet-of-Things(IoT),platooning have received lots of attentions due to its potential to improve the fuel efficiency and driving experience.Platoon is a group of vehicles that act as smart agents,they travel collaboratively by following the leading human-driven vehicle.A vehicle in the platoon utilizes radar and wireless communication to share important information to other vehicles in the same platoon such as speed and acceleration,to realize the safe and efficient driving.The quality of wireless communication is of great importance to manage and maintain the platoons.However,in a scenario that a large number of vehicles exist,communication delay and packet loss caused by channel congestion may endanger the safe intervehicle distance.In this paper,we introduce intervehicle communication with directional antenna into platooning.By extensive simulations,we evaluate the packet delay and inter-vehicle distance in both normal driving and braking scenarios,and verify the usefulness of directional antenna in platooning for vehicular IoT.展开更多
Vehicular ad-hoc networks(VANETs)are mobile networks that use and transfer data with vehicles as the network nodes.Thus,VANETs are essentially mobile ad-hoc networks(MANETs).They allow all the nodes to communicate and...Vehicular ad-hoc networks(VANETs)are mobile networks that use and transfer data with vehicles as the network nodes.Thus,VANETs are essentially mobile ad-hoc networks(MANETs).They allow all the nodes to communicate and connect with one another.One of the main requirements in a VANET is to provide self-decision capability to the vehicles.Cognitive memory,which stores all the previous routes,is used by the vehicles to choose the optimal route.In networks,communication is crucial.In cellular-based vehicle-to-everything(CV2X)communication,vital information is shared using the cooperative awareness message(CAM)that is broadcast by each vehicle.Resources are allocated in a distributed manner,which is known as Mode 4 communication.The support vector machine(SVM)algorithm is used in the SVM-CV2X-M4 system proposed in this study.The k-fold model with different values of k is used to evaluate the accuracy of the SVM-CV2XM4 system.The results show that the proposed system achieves an accuracy of 99.6%.Thus,the proposed system allows vehicles to choose the optimal route and is highly convenient for users.展开更多
Autonomous platooning technology is regarded as one of the promising technologies for the future and the research is conducted actively.The autonomous platooning task generally requires highly complex computations so ...Autonomous platooning technology is regarded as one of the promising technologies for the future and the research is conducted actively.The autonomous platooning task generally requires highly complex computations so it is difficult to process only with the vehicle’s processing units.To solve this problem,there are many studies on task offloading technique which transfers complex tasks to their neighboring vehicles or computation nodes.However,the existing task offloading techniques which mainly use learning-based algorithms are difficult to respond to the real-time changing road environment due to their complexity.They are also challenging to process computation tasks within 100 ms which is the time limit for driving safety.In this paper,we propose a novel offloading scheme that can support autonomous platooning tasks being processed within the limit and ensure driving safety.The proposed scheme can handle computation tasks by considering the communication bandwidth,delay,and amount of computation.We also conduct simulations in the highway environment to evaluate the existing scheme and the proposed scheme.The result shows that our proposed scheme improves the utilization of nearby computing nodes,and the offloading tasks can be processed within the time for driving safety.展开更多
Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the decision.In this article,these issues are handled...Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the decision.In this article,these issues are handled by proposing a novel framework for traffic control using vehicular communications and Internet of Things data.The framework integrates Kalman filtering and Q-learning.Unlike smoothing Kalman filtering,our data fusion Kalman filter incorporates a process-aware model which makes it superior in terms of the prediction error.Unlike traditional Q-learning,our Q-learning algorithm enables adaptive state quantization by changing the threshold of separating low traffic from high traffic on the road according to the maximum number of vehicles in the junction roads.For evaluation,the model has been simulated on a single intersection consisting of four roads:east,west,north,and south.A comparison of the developed adaptive quantized Q-learning(AQQL)framework with state-of-the-art and greedy approaches shows the superiority of AQQL with an improvement percentage in terms of the released number of vehicles of AQQL is 5%over the greedy approach and 340%over the state-of-the-art approach.Hence,AQQL provides an effective traffic control that can be applied in today’s intelligent traffic system.展开更多
With the increasing attention to front-edge vehicular communication applications,distributed resource allocation is beneficial to the direct communications between vehicle nodes.However,in highly dynamic distributed v...With the increasing attention to front-edge vehicular communication applications,distributed resource allocation is beneficial to the direct communications between vehicle nodes.However,in highly dynamic distributed vehicular networks,quality of service(QoS)of the systems would degrade dramatically because of serious packet collisions in the absence of sufficient link knowledge.Focusing on the fairness optimization,a Q-learning-based collision avoidance(QCA)scheme,which is characterized by an ingenious bidirectional backoff reward model RQCA corresponding to arbitrary backoff stage transitions,has been proposed in an intelligent distributed media access control protocol.In QCA,an intelligent bidirectional backoff agent based on the Markov decision process model can actively motivate each vehicle agent to update itself toward an optimal backoff sub-intervel BSIopt through either positive or negative bidirectional transition individually,resulting in the distinct fair communication with a proper balance of the resource allocation.According to the reinforcement learning theory,the problem of goodness evaluation on the backoff stage self-selection policy is equal to the problem of maximizing Q function of the vehicle in the current environment.The final decision on BSI_(opt) related to an optimal contention window range was solved through maximizing the Q value or Q_(max).The ε-greedy algorithm was used to keep a reasonable convergence of the Q_(max) solution.For the fairness evaluation of QCA,four kinds of dynamic impacts on the vehicular networks were investigated:mobility,density,payload size,and data rate with a network simulator NS2.Consequently,QCA can achieve fair communication efficiently and robustly,with advantages of superior Jain’s fairness index,relatively high packet delivery ratio,and low time delay.展开更多
This paper analyses the performance of fullduplex(FD)dual-hop vehicular cooperative network with decode-and-forward(DF)protocol.At FD relay nodes,we examine the effects of non-linear hybrid power time splitting(PTS)ba...This paper analyses the performance of fullduplex(FD)dual-hop vehicular cooperative network with decode-and-forward(DF)protocol.At FD relay nodes,we examine the effects of non-linear hybrid power time splitting(PTS)based energy harvesting(EH).All three nodes—source(S),relay(R),and destination(D)are assumed to be moving vehicles.The expressions for the system's outage probability(OP)over double(cascaded)Rayleigh fading channels are derived.We also analyse the impact of residual self-interference(RSI)caused at FD relay on system's performance.We compare the performance of system with two relay selection techniques,namely,maximum channel gain-based(Max-G)relay selection and minimum RSI-based(Min-SI)relay selection.This paper considers the joint effect of time splitting ratio and self-interference cancellation(SIC)level to find the optimum EH duration.Additionally,the effect of time splitting ratio and average signal-to-noise ratio(SNR)on outage and throughput performance of the system are also investigated in this paper.The derived expressions are validated through Monte Carlo simulations.展开更多
This paper deals with the co-design problem of event-triggered communication scheduling and platooning control over vehicular ad-hoc networks(VANETs)subject to finite communication resource.First,a unified model is pr...This paper deals with the co-design problem of event-triggered communication scheduling and platooning control over vehicular ad-hoc networks(VANETs)subject to finite communication resource.First,a unified model is presented to describe the coordinated platoon behavior of leader-follower vehicles in the simultaneous presence of unknown external disturbances and an unknown leader control input.Under such a platoon model,the central aim is to achieve robust platoon formation tracking with desired inter-vehicle spacing and same velocities and accelerations guided by the leader,while attaining improved communication efficiency.Toward this aim,a novel bandwidth-aware dynamic event-triggered scheduling mechanism is developed.One salient feature of the scheduling mechanism is that the threshold parameter in the triggering law is dynamically adjusted over time based on both vehicular state variations and bandwidth status.Then,a sufficient condition for platoon control system stability and performance analysis as well as a co-design criterion of the admissible event-triggered platooning control law and the desired scheduling mechanism are derived.Finally,simulation results are provided to substantiate the effectiveness and merits of the proposed co-design approach for guaranteeing a trade-off between robust platooning control performance and communication efficiency.展开更多
文摘Rapid development in Information Technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)transmission.Vehicular networks give a safe and more effective driving experience by presenting time-sensitive and location-aware data.The communication occurs directly between V2V and Base Station(BS)units such as the Road Side Unit(RSU),named as a Vehicle to Infrastructure(V2I).However,the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with time.Therefore,the scheme of an effectual routing protocol for reliable and stable communications is significant.Current research demonstrates that clustering is an intelligent method for effectual routing in a mobile environment.Therefore,this article presents a Falcon Optimization Algorithm-based Energy Efficient Communication Protocol for Cluster-based Routing(FOA-EECPCR)technique in VANETS.The FOA-EECPCR technique intends to group the vehicles and determine the shortest route in the VANET.To accomplish this,the FOA-EECPCR technique initially clusters the vehicles using FOA with fitness functions comprising energy,distance,and trust level.For the routing process,the Sparrow Search Algorithm(SSA)is derived with a fitness function that encompasses two variables,namely,energy and distance.A series of experiments have been conducted to exhibit the enhanced performance of the FOA-EECPCR method.The experimental outcomes demonstrate the enhanced performance of the FOA-EECPCR approach over other current methods.
基金This research was supported by Science and Technology Research Project of Education Department of Jiangxi Province,China(Nos.GJJ2206701,GJJ2206717).
文摘The current resource allocation in 5G vehicular networks for mobile cloud communication faces several challenges,such as low user utilization,unbalanced resource allocation,and extended adaptive allocation time.We propose an adaptive allocation algorithm for mobile cloud communication resources in 5G vehicular networks to address these issues.This study analyzes the components of the 5G vehicular network architecture to determine the performance of different components.It is ascertained that the communication modes in 5G vehicular networks for mobile cloud communication include in-band and out-of-band modes.Furthermore,this study analyzes the single-hop and multi-hop modes in mobile cloud communication and calculates the resource transmission rate and bandwidth in different communication modes.The study also determines the scenario of one-way and two-way vehicle lane cloud communication network connectivity,calculates the probability of vehicle network connectivity under different mobile cloud communication radii,and determines the amount of cloud communication resources required by vehicles in different lane scenarios.Based on the communication status of users in 5G vehicular networks,this study calculates the bandwidth and transmission rate of the allocated channels using Shannon’s formula.It determines the adaptive allocation of cloud communication resources,introduces an objective function to obtain the optimal solution after allocation,and completes the adaptive allocation process.The experimental results demonstrate that,with the application of the proposed method,the maximum utilization of user communication resources reaches approximately 99%.The balance coefficient curve approaches 1,and the allocation time remains under 2 s.This indicates that the proposed method has higher adaptive allocation efficiency.
基金supported by the National Natural Science Foundation of China under 62001526by Natural Science Foundation of Guangdong Province under 2021A1515012021+2 种基金by National Key R&D Plan of China under Grant 2021YFB2900200partly by Major Talent Program of Guangdong Province under Grant 2021QN02X074by Fundamental Research Funds for the Central Universities, Sun Yat-sen University, under Grant 23QNPY22
文摘In this paper,joint location and velocity estimation(JLVE)of vehicular terminals for 6G integrated communication and sensing(ICAS)is studied.We aim to provide a unified performance analysis framework for ICAS-based JLVE,which is challenging due to random fading,multipath interference,and complexly coupled system models,and thus the impact of channel fading and multipath interference on JLVE performance is not fully understood.To address this challenge,we exploit structured information models of the JLVE problem to render tractable performance quantification.Firstly,an individual closedform Cramer-Rao lower bound for vehicular localization,velocity detection and channel estimation,respectively,is established for gaining insights into performance limits of ICAS-based JLVE.Secondly,the impact of system resource factors and fading environments,e.g.,system bandwidth,the number of subcarriers,carrier frequency,antenna array size,transmission distance,spatial channel correlation,channel covariance,the number of interference paths and noise power,on the JLVE performance is theoretically analyzed.The associated closed-form JLVE performance analysis can not only provide theoretical foundations for ICAS receiver design but also provide a perfor mance benchmark for various JLVE methods。
基金supported by the Key Technology Research Project of Jiangxi Province(20213AAE01007)National Natural Science Foundation of China(61871047,61901047)the Proof-of-concept project of Zhongguancun Open Laboratory under Grant(202103001)。
文摘When there is an increasing interest in visible light communication(VLC), outdoor vehicle VLC has emerged as a promising candidate technology for future intelligent transportation systems. However, in VLC based vehicular applications, several challenges impede successful commercial application of VLC based products. This article first provides a thorough overview of the existing challenges. To overcome these challenges, we propose a novel architecture with tracking and environment sensing ability for practical vehicular applications. Moreover, a proof-ofconcept prototype is implemented to validate the feasibility of the proposed system. Experimental and simulation results show that the proposed VLC system can provide reliable communications with a bit-error rate less than 10-4for vehicles under strong interference lights. Finally, based on the evaluations, we propose some key design issues for future studies in this research area.
基金supported by the National Moon Exploration Program of China (No. TY3Q20110020)in part supported by the 13th Five-Year Community Technology Research Program of National Equipment Development Department of China (No.41409020301)the National Natural Science Foundation of China (50971094)
文摘With the development of EMC technology, EMC assessment has become increasingly important in EMC design. Although numerous EMC assessment models are available today, few of them can provide a tradeoff between efficiency and accuracy for the specific case of military vehicular communication systems. Face to this situation, a modified four-level assessment model is proposed in the paper. First, the development of EMC assessment technology is briefly reviewed, and the theoretical mechanism of EMI environment is introduced. Then, the architecture of the proposed model is outlined, and the assessment methods are explored. To demonstrate the application of it, an example involving a communication system in a military vehicle is presented. From the physical layer to the signal layer, a hierarchical assessment on the entire system is successfully performed based on the proposed model, and we can make a qualitative EMC assessment on the EMC performance of the system. Based on a comparison with the traditional model, we conclude that the proposed model is more accurate, more efficient and less time-consuming, which is suitable for the EMC assessment on militaryvehicular communication systems. We hope that the proposed model will serve as a useful reference for system-level EMC assessments for other systems.
文摘Intelligent transportation system (ITS) is proposed as the most effective way to improve road safety and traffic efficiency. However, the future of ITS for large scale transportation infrastructures deployment highly depends on the security level of vehicular communication systems (VCS). Security applications in VCS are fulfilled through secured group broadcast. Therefore, secure key management schemes are considered as a critical research topic for network security. In this paper, we propose a framework for providing secure key management within heterogeneous network. The seeurity managers (SMs) play a key role in the framework by retrieving the vehicle departnre infi^rmation, encapsulating block to transport keys and then executing rekeying to vehicles within the same security domain. The first part of this framework is a novel Group Key Management (GKM) scheme basing on leaving probability (LP) of vehicles to depart current VCS region. Vehicle's LP factor is introduced into GKM scheme to achieve a more effieient rekeying scheme and less rekeying costs. The second component of the framework using the blockchain concept to simplify the distributed key management in heterogeneous VCS domains. Extensive simulations and analysis are provided to show the effectiveness and effieiency of the proposed framework: Our GKM results demonstrate that probability-based BR reduees rekeying eost compared to the benchmark scheme, while the blockchain deereases the time eost of key transmission over heterogeneous net-works.
基金supported by Shandong Agricultural University Funding of First-class DisciplinesShandong Agricultural University Key Cultivation Discipline Funding for NSFC Proposers+1 种基金supported by Grant of Beihang University Beidou Technology Transformation and Industrialization (BARI1709)Open Project of National Engineering Research Center for Information Technology in Agriculture (No.KF2015W003)
文摘This paper derives a non-stationary multiple-input multiple-output(MIMO) from the one-ring scattering model. The proposed channel model characterizes vehicular radio propagation channels with considerations of moving base and mobile stations, which makes the angle of arrivals(AOAs) along with the angle of departures(AODs) time-variant. We introduce the methodology of including the time-variant impacts when characterizing non-stationary radio propagation channels through the geometrical channel modelling approach. We analyze the statistical properties of the proposed channel model including the local time-variant autocorrelation function(ACF) and the space cross-correlation functions(CCFs). We show that the model developed in this paper for non-stationary scenarios includes the existing one-ring wide-sense stationary channel model as its special case.
基金supported in part by the National Key R&D Program of China under Grant 2018YFB2202202in part by Fundamental Research Funds for the Central Universities under Grants 21620351.
文摘Vehicle-to-vehicle(V2V)communication appeals to increasing research interest as a result of its applications to provide safety information as well as infotainment services.The increasing demand of transmit rates and various requirements of quality of services(QoS)in vehicular communication scenarios call for the integration of V2V communication systems and potential techniques in the future wireless communications,such as full duplex(FD)and non-orthogonal multiple access(NOMA)which enhance spectral efficiency and provide massive connectivity.However,the large amount of data transmission and user connectivity give rise to the concern of security issues and personal privacy.In order to analyze the security performance of V2V communications,we introduce a cooperative NOMA V2V system model with an FD relay.This paper focuses on the security performance of the FD-NOMA based V2V system on the physical layer perspective.We first derive several analytical results of the ergodic secrecy capacity.Then,we propose a secrecy sum rate optimization scheme utilizing the instantaneous channel state information(CSI),which is formulated as a non-convex optimization problem.Based on the differential structure of the non-convex constraints,the original problem is approximated and solved by a series of convex optimization problems.Simulation results validate the analytical results and the effectiveness of the secrecy sum rate optimization algorithm.
基金funded by the Six Talent Peaks Project in Jiangsu Province(No.KTHY-052)the National Natural Science Foundation of China(No.61971245)+1 种基金the Science and Technology program of Nantong(Contract No.JC2018048)the Key Lab of Advanced Optical Manufacturing Technologies of Jiangsu Province&Key Lab of Modern Optical Technologies of Education Ministry of China,Soochow University(No.KJS1858).
文摘To achieve the better system performance for cooperative communication in non-orthogonal cognitive radio vehicular adhoc networks(CR-VANETs),this paper investigates the power allocation considering the interference to the main system in a controllable range.We propose a three-slot one-way vehicle system model where the mobile vehicle nodes complete information interaction with the assistance of other independent nodes by borrowing the unused radio spectrum with the primary networks.The end-to-end SNR relationship in overlay and underlay cognitive communication system mode are analyzed by using two forwarding protocol,namely,decode-and-forward(DF)protocol and amplify-and-forward(AF)protocol,respectively.The system outage probability is derived and the optimal power allocation factor is obtained via seeking the minimum value of the approximation of system outage probability.The analytical results have been confirmed by means of Monte Carlo simulations.Simulation results show that the proposed system performance in terms of outage under the optimal power allocation is superior to that under the average power allocation,and is also better than that under other power allocation systems.
文摘Vehicular safety applications, such as cooperative collision warning systems, rely on beaconing to provide situational awareness that is needed to predict and therefore to avoid possible collisions. Beaconing is the continual exchange of vehicle motion-state information, such as position, speed, and heading, which enables each vehicle to track its neighboring vehicles in real time. This work presents a context-aware adaptive beaconing scheme that dynamically adapts the beaconing repetition rate based on an estimated channel load and the danger severity of the interactions among vehicles. The safety, efficiency, and scalability of the new scheme is evaluated by simulating vehicle collisions caused by inattentive drivers under various road traffic densities. Simulation results show that the new scheme is more efficient and scalable, and is able to improve safety better than the existing non-adaptive and adaptive rate schemes.
文摘Vehicular communications and networking can improve road safety, faeilitate intelligenl transporlation, support infotainment, dala sharing, and location based serviees, and will be a eritical component in the Internet of Things. This special issue aims to present the state of the art in research and development of vehicular communication technology and its potential applications. We are soliciting original contribulions. The topics of interest include, but arc not limited to:
文摘Avehicular ad hoc network (VANET) is a packet-switched network, consisting of mobile communication nodes mounted on vehicles, with very limited or no infrastructure support [1]. It supports communications among nearby vehicles,
基金supported in part by National Key Research and Development Program of China(2020YFB1807700)in part by National Natural Science Foundation of China(62201414)+2 种基金in part by Qinchuangyuan Project(OCYRCXM-2022-362)in part by Science and Technology Project of Guangzhou(2023A04J1741)in part by Chongqing key laboratory of Mobile Communications Technologg(cqupt-mct-202202).
文摘Task offloading is a potential solution to satisfy the strict requirements of computation-intensive and latency-sensitive vehicular applications due to the limited onboard computing resources.However,the overwhelming upload traffic may lead to unacceptable uploading time.To tackle this issue,for tasks taking environmental data as input,the data perceived by roadside units(RSU)equipped with several sensors can be directly exploited for computation,resulting in a novel task offloading paradigm with integrated communications,sensing and computing(I-CSC).With this paradigm,vehicles can select to upload their sensed data to RSUs or transmit computing instructions to RSUs during the offloading.By optimizing the computation mode and network resources,in this paper,we investigate an I-CSC-based task offloading problem to reduce the cost caused by resource consumption while guaranteeing the latency of each task.Although this nonconvex problem can be handled by the alternating minimization(AM)algorithm that alternatively minimizes the divided four sub-problems,it leads to high computational complexity and local optimal solution.To tackle this challenge,we propose a creative structural knowledge-driven meta-learning(SKDML)method,involving both the model-based AM algorithm and neural networks.Specifically,borrowing the iterative structure of the AM algorithm,also referred to as structural knowledge,the proposed SKDML adopts long short-term memory(LSTM)networkbased meta-learning to learn an adaptive optimizer for updating variables in each sub-problem,instead of the handcrafted counterpart in the AM algorithm.Furthermore,to pull out the solution from the local optimum,our proposed SKDML updates parameters in LSTM with the global loss function.Simulation results demonstrate that our method outperforms both the AM algorithm and the meta-learning without structural knowledge in terms of both the online processing time and the network performance.
基金This research was supported by Grant-in-Aid for Scientific Research(C)(20K11764)the Telecommunications Advancement Foundation and ROIS NII Open Collaborative Research 21FA01.
文摘Recently,in the researches on vehicular Internet-of-Things(IoT),platooning have received lots of attentions due to its potential to improve the fuel efficiency and driving experience.Platoon is a group of vehicles that act as smart agents,they travel collaboratively by following the leading human-driven vehicle.A vehicle in the platoon utilizes radar and wireless communication to share important information to other vehicles in the same platoon such as speed and acceleration,to realize the safe and efficient driving.The quality of wireless communication is of great importance to manage and maintain the platoons.However,in a scenario that a large number of vehicles exist,communication delay and packet loss caused by channel congestion may endanger the safe intervehicle distance.In this paper,we introduce intervehicle communication with directional antenna into platooning.By extensive simulations,we evaluate the packet delay and inter-vehicle distance in both normal driving and braking scenarios,and verify the usefulness of directional antenna in platooning for vehicular IoT.
文摘Vehicular ad-hoc networks(VANETs)are mobile networks that use and transfer data with vehicles as the network nodes.Thus,VANETs are essentially mobile ad-hoc networks(MANETs).They allow all the nodes to communicate and connect with one another.One of the main requirements in a VANET is to provide self-decision capability to the vehicles.Cognitive memory,which stores all the previous routes,is used by the vehicles to choose the optimal route.In networks,communication is crucial.In cellular-based vehicle-to-everything(CV2X)communication,vital information is shared using the cooperative awareness message(CAM)that is broadcast by each vehicle.Resources are allocated in a distributed manner,which is known as Mode 4 communication.The support vector machine(SVM)algorithm is used in the SVM-CV2X-M4 system proposed in this study.The k-fold model with different values of k is used to evaluate the accuracy of the SVM-CV2XM4 system.The results show that the proposed system achieves an accuracy of 99.6%.Thus,the proposed system allows vehicles to choose the optimal route and is highly convenient for users.
基金This work was supported in part by the Chung-Ang University Research Scholarship Grants in 2021,and in part by R&D Program for Forest Science Technology(Project No.“2021338B10-2223-CD02)provided by Korea Forest Service(Korea Forestry Promotion Institute).
文摘Autonomous platooning technology is regarded as one of the promising technologies for the future and the research is conducted actively.The autonomous platooning task generally requires highly complex computations so it is difficult to process only with the vehicle’s processing units.To solve this problem,there are many studies on task offloading technique which transfers complex tasks to their neighboring vehicles or computation nodes.However,the existing task offloading techniques which mainly use learning-based algorithms are difficult to respond to the real-time changing road environment due to their complexity.They are also challenging to process computation tasks within 100 ms which is the time limit for driving safety.In this paper,we propose a novel offloading scheme that can support autonomous platooning tasks being processed within the limit and ensure driving safety.The proposed scheme can handle computation tasks by considering the communication bandwidth,delay,and amount of computation.We also conduct simulations in the highway environment to evaluate the existing scheme and the proposed scheme.The result shows that our proposed scheme improves the utilization of nearby computing nodes,and the offloading tasks can be processed within the time for driving safety.
文摘Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the decision.In this article,these issues are handled by proposing a novel framework for traffic control using vehicular communications and Internet of Things data.The framework integrates Kalman filtering and Q-learning.Unlike smoothing Kalman filtering,our data fusion Kalman filter incorporates a process-aware model which makes it superior in terms of the prediction error.Unlike traditional Q-learning,our Q-learning algorithm enables adaptive state quantization by changing the threshold of separating low traffic from high traffic on the road according to the maximum number of vehicles in the junction roads.For evaluation,the model has been simulated on a single intersection consisting of four roads:east,west,north,and south.A comparison of the developed adaptive quantized Q-learning(AQQL)framework with state-of-the-art and greedy approaches shows the superiority of AQQL with an improvement percentage in terms of the released number of vehicles of AQQL is 5%over the greedy approach and 340%over the state-of-the-art approach.Hence,AQQL provides an effective traffic control that can be applied in today’s intelligent traffic system.
文摘With the increasing attention to front-edge vehicular communication applications,distributed resource allocation is beneficial to the direct communications between vehicle nodes.However,in highly dynamic distributed vehicular networks,quality of service(QoS)of the systems would degrade dramatically because of serious packet collisions in the absence of sufficient link knowledge.Focusing on the fairness optimization,a Q-learning-based collision avoidance(QCA)scheme,which is characterized by an ingenious bidirectional backoff reward model RQCA corresponding to arbitrary backoff stage transitions,has been proposed in an intelligent distributed media access control protocol.In QCA,an intelligent bidirectional backoff agent based on the Markov decision process model can actively motivate each vehicle agent to update itself toward an optimal backoff sub-intervel BSIopt through either positive or negative bidirectional transition individually,resulting in the distinct fair communication with a proper balance of the resource allocation.According to the reinforcement learning theory,the problem of goodness evaluation on the backoff stage self-selection policy is equal to the problem of maximizing Q function of the vehicle in the current environment.The final decision on BSI_(opt) related to an optimal contention window range was solved through maximizing the Q value or Q_(max).The ε-greedy algorithm was used to keep a reasonable convergence of the Q_(max) solution.For the fairness evaluation of QCA,four kinds of dynamic impacts on the vehicular networks were investigated:mobility,density,payload size,and data rate with a network simulator NS2.Consequently,QCA can achieve fair communication efficiently and robustly,with advantages of superior Jain’s fairness index,relatively high packet delivery ratio,and low time delay.
文摘This paper analyses the performance of fullduplex(FD)dual-hop vehicular cooperative network with decode-and-forward(DF)protocol.At FD relay nodes,we examine the effects of non-linear hybrid power time splitting(PTS)based energy harvesting(EH).All three nodes—source(S),relay(R),and destination(D)are assumed to be moving vehicles.The expressions for the system's outage probability(OP)over double(cascaded)Rayleigh fading channels are derived.We also analyse the impact of residual self-interference(RSI)caused at FD relay on system's performance.We compare the performance of system with two relay selection techniques,namely,maximum channel gain-based(Max-G)relay selection and minimum RSI-based(Min-SI)relay selection.This paper considers the joint effect of time splitting ratio and self-interference cancellation(SIC)level to find the optimum EH duration.Additionally,the effect of time splitting ratio and average signal-to-noise ratio(SNR)on outage and throughput performance of the system are also investigated in this paper.The derived expressions are validated through Monte Carlo simulations.
基金This work was supported in part by the Australian Research Council Discovery Early Career Researcher Award under Grant DE200101128.
文摘This paper deals with the co-design problem of event-triggered communication scheduling and platooning control over vehicular ad-hoc networks(VANETs)subject to finite communication resource.First,a unified model is presented to describe the coordinated platoon behavior of leader-follower vehicles in the simultaneous presence of unknown external disturbances and an unknown leader control input.Under such a platoon model,the central aim is to achieve robust platoon formation tracking with desired inter-vehicle spacing and same velocities and accelerations guided by the leader,while attaining improved communication efficiency.Toward this aim,a novel bandwidth-aware dynamic event-triggered scheduling mechanism is developed.One salient feature of the scheduling mechanism is that the threshold parameter in the triggering law is dynamically adjusted over time based on both vehicular state variations and bandwidth status.Then,a sufficient condition for platoon control system stability and performance analysis as well as a co-design criterion of the admissible event-triggered platooning control law and the desired scheduling mechanism are derived.Finally,simulation results are provided to substantiate the effectiveness and merits of the proposed co-design approach for guaranteeing a trade-off between robust platooning control performance and communication efficiency.