Novel Sum-of-Sinusoids Simulation Channel Modeling for 6G Multiple-Input Multiple-Output Vehicle-to-Everything Communications

In this paper,a statistical cluster-based simulation channel model with a finite number of sinusoids is proposed for depicting the multiple-input multiple-output(MIMO)communications in vehicleto-everything(V2X)environments.In the proposed sum-of-sinusoids(SoS)channel model,the waves that emerge from the transmitter undergo line-of-sight(LoS)and non-line-of-sight(NLoS)propagation to the receiver,which makes the model suitable for describing numerous V2X wireless communication scenarios for sixth-generation(6G).We derive expressions for the real and imaginary parts of the complex channel impulse response(CIR),which characterize the physical propagation characteristics of V2X wireless channels.The statistical properties of the real and imaginary parts of the complex CIRs,i.e.,autocorrelation functions(ACFs),Doppler power spectral densities(PSDs),cross-correlation functions(CCFs),and variances of ACFs and CCFs,are derived and discussed.Simulation results are generated and match those predicted by the underlying theory,demonstrating the accuracy of our derivation and analysis.The proposed framework and underlying theory arise as an efficient tool to investigate the statistical properties of 6G MIMO V2X communication systems.

MPC-based time synchronizationmethod for V2V (vehicle-tovehicle)communication

Purpose–As the strategy of 5G new infrastructure is deployed and advanced,5G-R becomes the primary technical system for future mobile communication of China’s railway.V2V communication is also an important application scenario of 5G communication systems on high-speed railways,so time synchronization between vehicles is critical for train control systems to be real-time and safe.How to improve the time synchronization performance in V2V communication is crucial to ensure the operational safety and efficiency of high-speed railways.Design/methodology/approach–This paper proposed a time synchronization method based on model predictive control(MPC)for V2V communication.Firstly,a synchronous clock for V2V communication was modeled based on the fifth generation mobile communication-railway(5G-R)system.Secondly,an observation equation was introduced according to the phase and frequency offsets between synchronous clocks of two adjacent vehicles to construct an MPC-based space model of clock states of the adjacent vehicles.Finally,the optimal clock offset was solved through multistep prediction,rolling optimization and other control methods,and time synchronization in different V2V communication scenarios based on the 5G-R system was realized through negative feedback correction.Findings–The results of simulation tests conducted with and without a repeater,respectively,show that the proposed method can realize time synchronization of V2V communication in both scenarios.Compared with other methods,the proposed method has faster convergence speed and higher synchronization precision regardless of whether there is a repeater or not.Originality/value–This paper proposed an MPC-based time synchronization method for V2V communication under 5G-R.Through the construction of MPC controllers for clocks of adjacent vehicles,time synchronization was realized for V2V communication under 5G-R by using control means such as multistep prediction,rolling optimization,and feedback correction.In view of the problems of low synchronization precision and slow convergence speed caused by packet loss with existing synchronization methods,the observer equation was introduced to estimate the clock state of the adjacent vehicles in case of packet loss,which reduces the impact of clock error caused by packet loss in the synchronization process and improves the synchronization precision of V2V communication.The research results provide some theoretical references for V2V synchronous wireless communication under 5G-R technology.

V2I Based Environment Perception for Autonomous Vehicles at Intersections

In recent years,autonomous driving technology has made good progress,but the noncooperative intelligence of vehicle for autonomous driving still has many technical bottlenecks when facing urban road autonomous driving challenges.V2I(Vehicle-to-Infrastructure)communication is a potential solution to enable cooperative intelligence of vehicles and roads.In this paper,the RGB-PVRCNN,an environment perception framework,is proposed to improve the environmental awareness of autonomous vehicles at intersections by leveraging V2I communication technology.This framework integrates vision feature based on PVRCNN.The normal distributions transform(NDT)point cloud registration algorithm is deployed both on onboard and roadside to obtain the position of the autonomous vehicles and to build the local map objects detected by roadside multi-sensor system are sent back to autonomous vehicles to enhance the perception ability of autonomous vehicles for benefiting path planning and traffic efficiency at the intersection.The field-testing results show that our method can effectively extend the environmental perception ability and range of autonomous vehicles at the intersection and outperform the PointPillar algorithm and the VoxelRCNN algorithm in detection accuracy.

Pricing Based Power Control for Inter-Cell UAV-Assisted Vehicle-to-Vehicle Underlay Communication

The high-capacity vehicle-to-vehicle(V2 V) communication provides a promising solution to support ubiquitous media streaming and content sharing among vehicles.To extend the V2 V links to multiple cells and manage the inter-cell interference,we proposed an UAV-assisted inter-cell V2 V communication model,in which a shared UAV node is placed in the center of V2 V users.By charging the V2 V users underlay spectrum access fee,the cellular network earn profit at the cost of encountering co-channel interference from V2 V links.A Stackelberg game is formulated to model the interactions between the V2 V links and the cellular links,which are the game follower and the leader respectively.Their utility functions are maximized in terms of accessing price as well as transmit power of V2 V users and UAV relays.Simulation evaluations verify that the power-price tradeoff between V2 V network and cellular network has significant potentials to enhance their utility.

Development Status and Application Analysis of Vehicle to Grid (V2G)

With the shortages of resources,environmental pollution,climate change,and other issues becoming more and more serious,it is extremely urgent to vigorously develop new energy vehicles.As the cost of batteries decrease year by year,the production and quantity of sales of electric vehicles(EVs)in the world,especially in China,increased substantially.In order to make vehicles to grid(V2G)technology better developed and applied in China.The brief introduction to V2G is given at first.Then the development status and specific cases of V2G at home and abroad are summarized.Finally,the problems that V2G may encounter during promotion and application in China are analyzed.Based on the development of the United States and Japan,specific policy recommendations are given in line with the basic national conditions of China.

A Comprehensive Analysis of Plug in Hybrid Electric Vehicles to Commercial Campus (V2C)

Vehicle to grid is an emerging technology that utilizes plug in hybrid electric vehicle batteries to benefit electric utilities during times when the vehicle is parked and connected to the electric grid. In its current form however, vehicle to grid implementation poses many challenges that may not be easily overcome and many existing studies neglect critical aspects such as battery cost or driving profiles. The goal of this research is to ease some of these challenges by examining a vehicle to grid scenario on a university campus, as an example of a commercial campus, based on time of use electricity rates. An analysis of this scenario is conducted on a vehicle battery as well as a stationary battery for comparison. It is found that vehicle to campus and a stationary battery both have the potential to prove economical based on battery cost and electricity rates.

Misbehavior Detection Method by Time Series Change of Vehicle Position in Vehicle-to-Everything Communication

In recent years, research has been conducted on connected vehicles (CVs) that are equipped with communication devices and can be connected to networks. CVs share their own position information and surrounding information with other vehicles using Vehicle-to-Everything (V2X) communication. CVs can recognize obstacles on non-line-of-sight (NLoS), which cannot be recognized by autonomous vehicles, and reduce travel time to a destination by cooperative driving. Therefore, CVs are expected to provide safe and efficient transportation. On the other hand, problems of security of V2X communication by CVs have been discussed. Safe and efficient transportation by CVs is on the basis of the assumption that correct vehicle information is shared. If fake vehicle information is shared, it will affect the driving of CVs. In particular, vehicle position faking has been shown that it can induce traffic congestion and accidents, which is a serious problem. In this study, we define position faking by CV as misbehavior and propose a method to detect misbehavior on the basis of changes in vehicle position time series data composed of vehicle position information. We evaluated the proposed method using four different misbehavior models. F-measure of misbehavior models that CV sends random position information detected by the proposed method is higher than one by a related method. Therefore, the proposed method is suitable for detecting misbehavior in which the position information changes over time.

电动汽车动力电池采用V2G的有序充放电策略研究

本文针对电动汽车充电站现状问题,介绍了动力V2G有序充放电技术的背景并提出了相应的控制方法。通过建立仿真模型,验证了本文提出的有序充放电控制方法的有效性。研究结果表明,该控制方法可以提高充电站的服务质量和效率,为电动汽车的普及和推广提供有力支持。

Big Wave of the Intelligent Connected Vehicles

Internet of things is deemed as the one of the great revolution after the age of Industrial Revolution.With the development of the communication technology,more and more entities are connected to the communication network and become one of the elements in the network.Over recent decades,in the area of intelligent transportation,pedestrian and transport infrastructure are connected to the communication network to improve the driving safety and traffic efficiency which is known as the ICV(Intelligent Connected Vehicle).This paper summarizes the global ICV progresses in the past decades and the latest activities of ICV in China,and introduces various aspects regarding the recent development of the ICV,including industry development,spectrum and standard,at the same time.

A 3D Geometry-Based Scattering Model for Vehicleto-Vehicle Wideband MIMO Relay-Based Cooperative Channels

In this paper, a three-dimensional(3D) geometry- based stochastic scattering model(GBSSM) for wideband multi-input multi-output(MIMO) vehicle-to-vehicle(V2V) relay-based cooperative fading channel based on geometrical three-cylinder is proposed. Non-line-of-sight(NLOS) propagation condition is assumed in amplify-and-forward(AF) cooperative networks from the source mobile station(S) to the destination mobile station(D) via the mobile relay station(R). We extend the proposed narrowband model to wideband and also introduce the carrier frequency and bandwidth into the model. To avoid complicated procedure in deriving the analytical expressions of the channel parameters and functions, the channel is realized first. By using the realized channel matrix, the channel properties are further investigated.

A Multi-Objective Coordinated Charging and Discharging Strategy for Electric Vehicles Based on Stackelberg Game

For the negative impact of large-scale electric vehicles (EVs) disorderly charging on the power grid, a multi-objective optimization strategy for coordinated charging and discharging of EVs based on Stackelberg game is proposed. As the leader, the grid company aims to stabilize load fluctuations and formulate a reasonable electricity price strategy to guide EVs to participate in vehicle-to-grid (V2G);As followers, EV users optimize their charging plans based on electricity price information with the objective of reducing costs and obtaining good comfort. This paper uses the MOPSO algorithm to solve the proposed multi-objective Stackelberg problem, and calculates the optimization results under various preferences, which proves the effectiveness of the proposed model and method.

Charging infrastructure planning for electric vehicle in India:Present status and future challenges

The challenge to deal with environmental contamination along with national goals such as energy security,reliability,and self-dependency due to depleting fossil fuel resources has motivated researchers to find an alternate solution in the transport sector.Due to this,electrification of the transport sector has become an achievable solution that has caught attention with increasing penetration in the market share.India is a participant in the Paris Agreement which aims to curtail the production of greenhouse gases and limit the escalating temperature.Public intervention and changes in policy and regulations are the key aspects of technological transition.Compared to internal combustion engine(ICE)-based vehicles,the consumers’frame of mind concerns about adapting to e-mobility is anxiety over charging times and driving range.Thus,the development of charging stations plays a crucial role in promoting electric vehicles(EVs).This study investigates to identify different barriers that exist in the Indian context related to the adoption of e-mobility.Furthermore,this work emphasizes the recent developments in charging infrastructure planning in India.Also,the status of installed charging stations is examined.Developing appropriate charging stations are associated with several challenges,which are also highlighted to provide guidance to public and private entities that can be adopted in their respective business model.As India has the second largest population and is the seventh largest country in the world,the EV adoption rate of India is considerably low compared to other countries;for India,there is a long way to match the growth rate of EV adoption.Hence it becomes essential to develop a robust and suitable charging infrastructure to promote the sale and use of EVs in India.

Impact of Electric Vehicles on Travel and Electricity Demand in Metropolitan Area： A Case Study in Nagoya

In this study, we examine the impacts that EVs （electric vehicles） have on vehicle usage patterns and environmental improvements, using our integrated travel demand forecasting model, which can simulate an individual activity-travel behavior in each time period, as well as consider an induced demand by decreasing travel cost. In order to examine the effects that charging/discharging have on the demand in electricity, we analyze scenarios based on the simulation results of the EVs＇ parking location, parking duration and the battery state of charge. From the simulation, result under the ownership rate of EVs in the Nagoya metropolitan area in 2020 is about 6%, which turns out that the total CO2 emissions have decreased by 4% although the situation of urban transport is not changed. After calculating the electricity demand in each zone using architectural area and basic units of hourly power consumption, we evaluate the effect to decrease the peak load by V2G （vehicle-to-grid）. According to the results, if EV drivers charge at home during the night and discharge at work during the day, the electricity demand in Nagoya city increases by approximately 1%, although changes in each individual zone range from -7% to ＋8%, depending on its characteristics.

Reduction of global effects on vehicles after IED detonations

Global effects caused by the detonation of an IED near a military vehicle induce subsequent severe acceleration effects on the vehicle occupants.Two concepts to minimize these global effects were developed,with the help of a combined method based on a scaled experimental technology and numerical simulations.The first concept consists in the optimization of the vehicle shape to reduce the momentum transfer and thus the occupant loading.Three scaled V-shaped vehicles with different ground clearances were built and compared to a reference vehicle equipped with a flat floor.The second concept,called dynamic impulse compensation(DIC),is based on a momentum compensation technique.The principal possibility of this concept was demonstrated on a scaled vehicle.In addition,the numerical simulations have been performed with generic full size vehicles including dummy models,proving the capability of the DIC technology to reduce the occupant loading.

Vehicle-to-Grid Technology： State-of-the-Art and Future Scenarios

An overview of V2G （vehicle-to-grid） technology is presented in this paper, it aims to highlight the main features, opportunities and requirements of V2G. Thus, after briefly resuming the most popular charging strategies lbr PEVs （plug-in electric vehicles）, the V2G concept is introduced, especially highlighting its potentiality as a revenue opportunity ｜br PEV owners： this is mainly due to the V2G ability to provide ancillary services, such as load leveling, regulation and reserve. Such solutions have been thoroughly investigated in the literature from both the economic and technical points of view and are here reported. In addition, V2G requirements such as mobility needs, charging stations availability and appropriate PEV aggregative architectures are properly taken into account. Finally, future developments and scenarios have also been reported.

Coalitional game based resource allocation in D2D-enabled V2V communication

The joint resource block(RB)allocation and power optimization problem is studied to maximize the sum-rate of the vehicle-to-vehicle(V2V)links in the device-to-device(D2D)-enabled V2V communication system,where one feasible cellular user(FCU)can share its RB with multiple V2V pairs.The problem is first formulated as a nonconvex mixed-integer nonlinear programming(MINLP)problem with constraint of the maximum interference power in the FCU links.Using the game theory,two coalition formation algorithms are proposed to accomplish V2V link partitioning and FCU selection,where the transferable utility functions are introduced to minimize the interference among the V2V links and the FCU links for the optimal RB allocation.The successive convex approximation(SCA)is used to transform the original problem into a convex one and the Lagrangian dual method is further applied to obtain the optimal transmit power of the V2V links.Finally,numerical results demonstrate the efficiency of the proposed resource allocation algorithm in terms of the system sum-rate.

A Joint Power and Bandwidth Allocation Method Based on Deep Reinforcement Learning for V2V Communications in 5G

Vehicular communications have recently attracted great interest due to their potential to improve the intelligence of the transportation system.When maintaining the high reliability and low latency in the vehicle-to-vehicle(V2V)links as well as large capacity in the vehicle-to-infrastructure(V2I)links,it is essential to flexibility allocate the radio resource to satisfy the different requirements in the V2V communication.This paper proposes a new radio resources allocation system for V2V communications based on the proximal strategy optimization method.In this radio resources allocation framework,a vehicle or V2V link that is designed as an agent.And through interacting with the environment,it can learn the optimal policy based on the strategy gradient and make the decision to select the optimal sub-band and the transmitted power level.Because the proposed method can output continuous actions and multi-dimensional actions,it greatly reduces the implementation complexity of large-scale communication scenarios.The simulation results indicate that the allocation method proposed in this paper can meet the latency constraints and the requested capacity of V2V links under the premise of minimizing the interference to vehicle-to-infrastructure communications.

A Geometry-Based Stochastic Scattering Channel Model for V2V Communications in Dense Urban Street Environments

In this paper,we propose a stochastic channel model in three-dimensional(3D)space for multiple input multiple output(MIMO)vehicle-to-vehicle(V2V)communications in dense urban environments.The movement of the mobile transmitter and mobile receiver results in the V2V channel model behave temporal non-stationarity.Therefore,the time-varying parameters of the propagation paths and angles are derived to characterize such property.Using this channel model,we investigate the propagation characteristics of V2V channels in terms of the road section and moving time/directions/speeds of the transmitter and receiver.Numerical results show that the theoretical results of the propagation characteristics of the V2V channel model are very close to those of the simulation ones,which show that the proposed channel model is suitable for depicting the V2V communications in dense urban scenarios.

800 V充电平台中SiC材料的应用及发展趋势

SiC功率器件具有优异的性能,已经成为高端新能源汽车的核心部件,并随着应用成本的降低在逐步取代传统的Si基器件。然而,SiC单晶生长的参数可控性差、成本高、扩径难度大,它的市场渗透受到制约。当前对于SiC材料的投资非常火热,国内也有大量产业项目开展,但是实际投产却相对较少,半导体材料行业准入门槛较高,也需警惕重复建设的风险。山西烁科晶体有限公司实现了6英寸(1英寸=25.4 mm)SiC衬底产业化,并推出了8英寸产品,计划在十四五期间内将年产能扩充至150万片以满足市场巨大的需求,同时不断提升产品的良率及性能,助力第三代半导体行业的发展,在实现“碳达峰碳中和”的目标道路上贡献力量。

DQN-based decentralized multi-agent JSAP resource allocation for UAV swarm communication

It is essential to maximize capacity while satisfying the transmission time delay of unmanned aerial vehicle(UAV)swarm communication system.In order to address this challenge,a dynamic decentralized optimization mechanism is presented for the realization of joint spectrum and power(JSAP)resource allocation based on deep Q-learning networks(DQNs).Each UAV to UAV(U2U)link is regarded as an agent that is capable of identifying the optimal spectrum and power to communicate with one another.The convolutional neural network,target network,and experience replay are adopted while training.The findings of the simulation indicate that the proposed method has the potential to improve both communication capacity and probability of successful data transmission when compared with random centralized assignment and multichannel access methods.