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.

FSD与V2X的优劣对比

特斯拉将准备FSD引入中国,距离自动驾驶又近了一步。自动驾驶的FSD与车联网的V2X自动驾驶相比,谁更有优势?该文从原理、人工驾驶、系统的角度,对FSD与V2X的优劣做了对比。从实现的角度看,FSD更容易实现;从成本的角度看,FSD成本更低;从人工驾驶角度看,FSD缺少了声音传感器;从定位角度看,FSD无法在整车偏移或偏转时准确定位;从系统角度看,FSD是单机操作,容易实现,但效能无法与车联网的V2X自动驾驶匹敌;V2X涉及基站系统、需要全网元统一接口,投资巨大,互联互通困难,建设周期长,尚无商业网实践经验。PSD与V2X各有所长,PSD适用于智能网联的初级阶段,V2X适用于智能网联的中、后期阶段。

V2X-Communication Assisted Interference Minimization for Automotive Radars

With the development of automated driving vehicles, more and more vehicles will be fitted with more than one automotive radars, and the radar mutual interference will become very significant. Vehicle to everything (V2X) communication is a potential way for coordinating automotive radars and reduce the mutual interference. In this paper, we analyze the positional relation of the two radars that interfere with each other, and evaluate the mutual interference for different types of automotive radars based on Poisson point process (PPP). We also propose a centralized framework and the corresponding algorithm, which relies on V2X communication systems to allocate the spectrum resources for automotive radars to minimize the interference. The minimum spectrum resources required for zero-interference are analyzed for different cases. Simulation results validate the analysis and show that the proposed framework can achieve near-zero-interference with the minimum spectrum resources.

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.

Integrated Sensing and Communication:Who Benefits More?

This paper compares the benefits of communication-assisted sensing and sensing-assisted communication in the context of integrated sensing and communication(ISAC).Communication-assisted sensing leverages the extensive cellular infrastructure to create a vast and cooperative sensor network,enhancing environmental perception accuracy and coverage.On the other hand,sensing-assisted communication utilizes advanced sensing technologies to improve predictive beamforming and channel estimation performance in high-frequency and highmobility scenarios,thereby increasing communication efficiency and reliability.To validate our analysis,we present an example of channel knowledge map(CKM)-assisted beam tracking.This example demonstrates the practical advantages of incorporating CKM in enhancing beam tracking accuracy.Our analysis confirms that communication-assisted sensing may offer greater development potential due to its wide coverage and cost-effectiveness in large-scale applications.

Design and evaluation of V2X communication system for vehicle and pedestrian safety

As the vehicles gain the extensive popularity and increasing demand, traffic accident is one of the most serious problems faced by modem transportation system. Hereinto, crashes between cars and pedestrians cause plenty of injuries and even death. Diverting attention from walking to smartphones is one of the main reasons for pedestrians getting injured by vehicles. However, the traditional measures protecting pedestrians from the vehicles heavily rely on the sound warning method, which do not capable for pedestrians focusing on the smartphones. As the smartphones become ubiquitous and intelligent, they have the capacity to provide alert for the pedestrians with the help of vehicle-to-pedestrian （V2P） communication. In this paper, an efficient vehicle-to-X （V2X） communication system is designed for the vehicle and pedestrian communication to guarantee the safety of people. It achieves the IEEE 802.11p and the WiFi protocols meanwhile on the on-board unit （OBU） designed for vehicles. Extensive evaluation shows that the OBU can provide the reliable communication for vehicle-to-vehicle （V2V） and V2P in terms of packet delivery rate and average delay. Furthermore, two safety applications have been developed to protect the safety of vehicles and pedestrians based on the data transferred from the OBU. The first application is designed to show the driving information and provide the collision forewaming alert on the tablet within the vehicle. The second application is developed for the smartphone to provide forewarning alert information to the smartphone-distracted vulnerable pedestrians. Smartphone states are appreciable to provide the adaptive alert modes. Experimental results show that these applications are capable of alerting the intersection accidents, and the pedestrians can get the adaptive alerts according to smartphone usage contexts.

A polarisation coding scheme based on an integrated sensing and communication system

Integrated sensing and communication(ISAC)technology enhances the spectrum utilization of the system by interchanging the spectrum between communication and sensing,which has gained popularity in scenarios such as vehicle-to-everything(V2X).With the aim of providing more dependable services for vehicles in high-speed mobile scenarios,we propose a scheme based on sense-assisted polarisation coding.Specifically,the base station acquires the vehicle's positional information and channel strength parameters through the forward time slot echo information.This information informs the creation of the coding architecture for the following time slot.This approach not only optimizes resource consumption but also enhances system dependability.Our simulation results confirm that the introduced scheme displays a notable improvement in the bit error rate(BER)when compared to traditional communication frameworks,maintaining this advantage across both unimpeded and compromised channel conditions.

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.

Machine learning in vehicular networking:An overview

As vehicle complexity and road congestion increase,combined with the emergence of electric vehicles,the need for intelligent transportation systems to improve on-road safety and transportation efficiency using vehicular networks has become essential.The evolution of high mobility wireless networks will provide improved support for connected vehicles through highly dynamic heterogeneous networks.Particularly,5G deployment introduces new features and technologies that enable operators to capitalize on emerging infrastructure capabilities.Machine Learning(ML),a powerful methodology for adaptive and predictive system development,has emerged in both vehicular and conventional wireless networks.Adopting data-centric methods enables ML to address highly dynamic vehicular network issues faced by conventional solutions,such as traditional control loop design and optimization techniques.This article provides a short survey of ML applications in vehicular networks from the networking aspect.Research topics covered in this article include network control containing handover management and routing decision making,resource management,and energy efficiency in vehicular networks.The findings of this paper suggest more attention should be paid to network forming/deforming decision making.ML applications in vehicular networks should focus on researching multi-agent cooperated oriented methods and overall complexity reduction while utilizing enabling technologies,such as mobile edge computing for real-world deployment.Research datasets,simulation environment standardization,and method interpretability also require more research attention.

A Multi-Mode Public Transportation System Using Vehicular to Network Architecture

The number of accidents in the campus of Suranaree University of Technology(SUT)has increased due to increasing number of personal vehicles.In this paper,we focus on the development of public transportation system using Intelligent Transportation System(ITS)along with the limitation of personal vehicles using sharing economy model.The SUT Smart Transit is utilized as a major public transportation system,while MoreSai@SUT(electric motorcycle services)is a minor public transportation system in this work.They are called Multi-Mode Transportation system as a combination.Moreover,a Vehicle toNetwork(V2N)is used for developing theMulti-Mode Transportation system in the campus.Due to equipping vehicles with On Board Unit(OBU)and 4G LTE modules,the real time speed and locations are transmitted to the cloud.The data is then applied in the proposed mathematical model for the estimation of Estimated Time of Arrival(ETA).In terms of vehicle classifications and counts,we deployed CCTV cameras,and the recorded videos are analyzed by using You Only Look Once(YOLO)algorithm.The simulation and measurement results of SUT Smart Transit and MoreSai@SUT before the covid-19 pandemic are discussed.Contrary to the existing researches,the proposed system is implemented in the real environment.The final results unveil the attractiveness and satisfaction of users.Also,due to the proposed system,the CO_(2) gas gets reduced when Multi-Mode Transportation is implemented practically in the campus.

Modeling and Simulation of Packet Delivery Rate in LTE-V Network Based on Markov Chain

As one of the most promising communication technologies for vehicular networks, LTE-V has the advantages of wide coverage and a high transmission rate. 3 GPP released the technical specification of LTE-V in March 2017, launching a spate of related research and industrialization. In this paper, we propose a communication model based on Markov process to evaluate the reliability of LTE-V. We derived the Packet Delivery Rate(PDR) of LTE-V based on the model. Moreover, we use Poisson process to model the distribution of vehicles on a highway,then combine the communication model with the vehicles’ distribution to derive the PDR under this scenario. To verify the correctness of the proposed model, we established a simulation program on the MATLAB platform. By comparing the simulation results and the mathematical results, we found that simulation results are a very good fit for the model.