A Secure Key Management Scheme for Heterogeneous Secure Vehicular Communication Systems

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.

Visible Light Communication for Vehicular Applications: A Novel Architecture with Proof-of-Concept Prototype

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.

Secure Performance Analysis and Optimization for FD-NOMA Vehicular Communications

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.

Vehicular Communications,Networks,and Applications

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,

ZTE Communications Special Issue on Vehicular Communications,Networks,and Applications

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：

Traffic Control Based on Integrated Kalman Filtering and Adaptive Quantized Q-Learning Framework for Internet of Vehicles

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.

A Fairness-Enhanced Intelligent MAC Scheme Using Q-Learning-Based Bidirectional Backoff for Distributed Vehicular Communication Networks

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.

Simulation analysis on co-site interference of vehicular digital communication system based on IM prediction method by BER

The co-site interference exists in kinds of communication systems, especially in digital communication systems, also is one of the biggest threats ＂in electromagnetic compatibility （EMC） designation of the systems. Analyzing the co-site interference is an important process in achieving EMC performance of the system. Under the situation, the co-site interference simulation analysis of a vehicular digital communication system based on interference margin （IM） prediction method by bit error ratio （BER） was proposed in the paper. In the simulation analysis, some physical models of the vehicular communication system were established on SIMULINK environment, the upper limit of BER level for audio signals was defined as the IM, three different types of co-site interference was analyzed respectively, and the simulation results were obtained in the form of system interference bandwidth. From these results, the EMC performance evaluation of the vehicular communication system was predicted based on the IM prediction method. By comparing with the actual test results, the correctness of the simulation results was validated and the simulation analysis method can be used for reference by other communication systems was indicated.

Prior information based channel estimation for millimeter-wave massive MIMO vehicular communications in 5G and beyond

Millimeter wave(mm Wave) has been claimed as the viable solution for high-bandwidth vehicular communications in 5 G and beyond. To realize applications in future vehicular communications, it is important to take a robust mm Wave vehicular network into consideration. However, one challenge in such a network is that mm Wave should provide an ultra-fast and high-rate data exchange among vehicles or vehicle-to-infrastructure(V2 I). Moreover,traditional real-time channel estimation strategies are unavailable because vehicle mobility leads to a fast variation mm Wave channel. To overcome these issues, a channel estimation approach for mm Wave V2 I communications is proposed in this paper. Specifically, by considering a fast-moving vehicle secnario, a corresponding mathematical model for a fast time-varying channel is first established. Then, the temporal variation rule between the base station and each mobile user and the determined direction-of-arrival are used to predict the time-varying channel prior information(PI). Finally, by exploiting the PI and the characteristics of the channel, the time-varying channel is estimated. The simulation results show that the scheme in this paper outperforms traditional ones in both normalized mean square error and sum-rate performance in the mm Wave time-varying vehicular system.

Artificial Intelligence Based Clustering with Routing Protocol for Internet of Vehicles

With recent advances made in Internet of Vehicles(IoV)and Cloud Computing(CC),the Intelligent Transportation Systems(ITS)find it advantageous in terms of improvement in quality and interactivity of urban transportation service,mitigation of costs incurred,reduction in resource utilization,and improvement in traffic management capabilities.Many trafficrelated problems in future smart cities can be sorted out with the incorporation of IoV in transportation.IoV communication enables the collection and distribution of real-time essential data regarding road network condition.In this scenario,energy-efficient and reliable intercommunication routes are essential among vehicular nodes in sustainable urban computing.With this motivation,the current research article presents a new Artificial Intelligence-based Energy Efficient Clustering with Routing(AI-EECR)Protocol for IoV in urban computing.The proposed AI-EECR protocol operates under three stages namely,network initialization,Cluster Head(CH)selection,and routing protocol.The presented AI-EECR protocol determines the CHs from vehicles with the help of Quantum Chemical Reaction Optimization(QCRO)algorithm.QCROalgorithmderives a fitness function with the help of vehicle speed,trust level,and energy level of the vehicle.In order to make appropriate routing decisions,a set of relay nodeswas selected usingGroup Teaching Optimization Algorithm(GTOA).The performance of the presented AI-EECR model,in terms of energy efficiency,was validated against different aspects and a brief comparative analysis was conducted.The experimental outcomes established that AI-EECR model outperformed the existing methods under different measures.

Implementation of K-Means Algorithm and Dynamic Routing Protocol in VANET

With the growth of Vehicular Ad-hoc Networks,many services delivery is gaining more attention from the intelligent transportation system.However,mobility characteristics of vehicular networks cause frequent disconnection of routes,especially during the delivery of data.In both developed and developing countries,a lot of time is consumed due to traffic congestion.This has significant negative consequences,including driver stress due to increased time demand,decreased productivity for various personalized and commercial vehicles,and increased emissions of hazardous gases especially air polluting gases are impacting public health in highly populated areas.Clustering is one of the most powerful strategies for achieving a consistent topological structure.Two algorithms are presented in this research work.First,a k-means clustering algorithm in which dynamic grouping by k-implies is performed that fits well with Vehicular network’s dynamic topology characteristics.The suggested clustering reduces overhead and traffic management.Second,for inter and intra-clustering routing,the dynamic routing protocol is proposed,which increases the overall Packet Delivery Ratio and decreases the End-to-End latency.Relative to the cluster-based approach,the proposed protocol achieves improved efficiency in terms of Throughput,Packet Delivery Ratio,and End-to-End delay parameters comparing the situations by taking different number of vehicular nodes in the network.

Networking-GPS: Cooperative Vehicle Localization Using Commodity GPS in Urban Area

A challenging issue in intelligent transportation systems （ITS） is to accurately locate moving vehicles in urban area. Considerable ef- forts have been made to improve the localization accuracy of standalone GPS receivers. However, through empirical study, we found that the latitude and longitude values generated by GPS receivers fluctuate significantly because of the muhipath effect in urban ar- eas. The relative distances between neighboring vehicles with similar GPS signal data in terms of satellite sets and signal strength are much more stable in such a scenario. In this paper, we propose a cooperative localization algorithm, Networking-GPS, to improve the accuracy of location information for vehicular networks in urban area using commodity GPS receivers. First, atom redundantly rigid graphs of vehicles are constructed according to the similarity of neighboring GPS data. Then, through rigidity expansion, local accura- cy can enforce global accuracy. Extensive simulations based on the real road network and trace data of vehicle mobility demonstrate that Networking-GPS can improve the accuracy of the entire system.

Beam steering application for W-band data links with moving targets in 5G wireless networks

Abstract:Ubiquitous broadband Internet access is one of the major goals of the next generation of wireless communications.However,there are still some locations where this is diffcult to achieve.This is the case on moving vehicles and,particularly,on trains.Among the possible solutions to this problem,RoF(Radio-over-Fiber)architectures have been proposed as low-latency,cost-e ective candidates.Two elements are introduced to extend the RoF approach.First,the carrier frequency is raised into the W-band(75-110 GHz)to increase the available capacity.Second,a mechanical beam-steering solution based on a Stewart platform is adopted for the transmitter antenna to allow it to follow a moving receiver along a known path,thereby enhancing the coverage area.The performance of a system transmitting a 2.5 Gbit/s non-return-to-zero signal generated by photonic up-conversion over a wireless link is evaluated in terms of real-time BER(Bit Error Rate)measurements.The receiver is situated in di erent positions,and the orientation of the transmitter is changed accordingly.Values below the forward error correction limit for 7%overhead are obtained over a range of 60 cm around a center point situated 2 m away from the transmitter.