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.

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 Transmission Design in Dynamic Heterogeneous V2V Networks Through Multi-Agent Deep Reinforcement Learning

In highly dynamic and heterogeneous vehicular communication networks,it is challenging to efficiently utilize network resources and ensure demanding performance requirements of safetyrelated applications.This paper investigates machinelearning-assisted transmission design in a typical multi-user vehicle-to-vehicle(V2V)communication scenario.The transmission process proceeds sequentially along the discrete time steps,where several source nodes intend to deliver multiple different types of messages to their respective destinations within the same spectrum.Due to rapid movement of vehicles,real-time acquirement of channel knowledge and central coordination of all transmission actions are in general hard to realize.We consider applying multi-agent deep reinforcement learning(MADRL)to handle this issue.By transforming the transmission design problem into a stochastic game,a multi-agent proximal policy optimization(MAPPO)algorithm under a centralized training and decentralized execution framework is proposed such that each source decides its own transmission message type,power level,and data rate,based on local observations of the environment and feedback,to maximize its energy efficiency.Via simulations we show that our method achieves better performance over conventional methods.

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.

Fairness optimization and power allocation in cognitive NOMA/OMA V2V network with imperfect SIC

In order to improve the reliability and resource utilization efficiency of vehicle-to-vehicle(V2V)communication system,in this paper,the fairness optimization and power allocation for the cognitive V2V network that takes into account the realistic three-dimensional(3D)channel are investigated.Large-scale and small-scale fading are considered in the proposed channel model.An adaptive non-orthogonal multiple access(NOMA)/orthogonal multiple access(OMA)scheme is proposed to reduce the complexity of successive-interference-cancellation(SIC)in decoding and improve spectrum utilization.Also,a fairness index that takes into account each user's requirements is proposed to indicate the optimal point clearly.In the imperfect SIC,the optimization problem of maximizing user fairness is formulated.Then,a subgradient descent method is proposed to solve the optimization problem with customizable precision.And the computational complexity of the proposed method is analyzed.The achievable rate,outage probability and user fairness are analyzed.The results show that the proposed adaptive NOMA/OMA(A-NOMA/OMA)outperforms both NOMA and OMA.The simulation results are compared with validated analysis to confirm the theoretical analysis.

Interacting multiple model-based ETUKF for efficient state estimation of connected vehicles with V2V communication

Accurate prediction of the motion state of the connected vehicles,especially the preceding vehicle(PV),would effectively improve the decision-making and path planning of intelligent vehicles.The evolution of vehicle-tovehicle(V2V)communication technology makes it possible to exchange data between vehicles.However,since V2V communication has a transmission interval,which will result in the host vehicle not receiving information from the PV within the time interval.Furthermore,V2V communication is a time-triggered system that may occupy more communication bandwidth than required.On the other hand,traditional estimation methods of the PV state based on individual models are usually not applicable to a wide range of driving conditions.To address these issues,an event-triggered unscented Kalman filter(ETUKF)is first employed to estimate the PV state to strike a balance between estimation accuracy and communication cost.Then,an interactive multi-model(IMM)approach is combined with ETUKF to form IMMETUKF to further improve the estimation accuracy and applicability.Finally,simulation experiments under different driving conditions are implemented to verify the effectiveness of IMMETUKF.The test results indicated that the IMMETUKF has high estimation accuracy even when the communication rate is reduced to 14.84%and the proposed algorithm is highly adaptable to different driving conditions.

Application-Oriented Performance Comparison of 802.11p and LTE-V in a V2V Communication System

In recent years, the Vehicle-to-Vehicle(V2V) communication system has been considered one of the most promising technologies to build a much safer and more efficient transportation system. Both simulation and field test have been extensively performed to evaluate the performance of the V2V communication system. However,most of the evaluation methods are communication-based, and although in a transportation environment, lack a V2V application-oriented analysis. In this study, we conducted real-world tests and built an application-oriented evaluation model. The experiments were classified into four scenarios: static, following, face 2 face, and crossing vertically, which almost covered all the V2V communication patterns on the road. Under these scenarios, we conducted experiments and built a probability model to evaluate the performance of 802.11p and LTE-V in safetyrelated applications. Consequently, we found out that improvements are still needed in Non-Line-of-Sight scenarios.

Performance analysis of different coding schemes for wideband vehicle-to-vehicle MIMO systems

The signal is subjected to lots of interferences in vehicle-to-vehicle(V2V)channel propagation,resulting in receiving error codes.Two-dimensional(2D)and three-dimensional(3D)geometrical channel models are used to depict the wideband V2V multiple-input multiple-output(MIMO)channels.Using the channel model,Turbo code and low-density parity-check(LDPC)code are investigated for wideband V2V MIMO system,and the encoding and the decoding schemes are investigated.The bit error rate(BER),channel capacity and outage probability of wideband V2V MIMO system using Turbo code and LDPC code are analyzed at different typical speeds.The results show that the performance of wideband V2V MIMO system using Turbo code outperform that using LDPC code.The performance is affected by transmitting and receiving speeds with the same coding scheme.And the channel capacity of the 3D channel is larger than that of 2D channel.

Reliability Evaluation of IEEE 802.11p-Based Vehicle-to-Vehicle Communication in an Urban Expressway

IEEE 802.11p/DSRC （Dedicated Short Range Communication） is considered to be a promising wireless communication standard for enhancing transportation safety and efficiency. However, IEEE 802.11p-based Vehicle- to-Vehicle （V2V） communication is still unreliable because of the complicating factors of high vehicle speed and complex radio environments. In this paper, we performed a data-based evaluation of V2V communication reliability, using real-world measurements in a typical urban expressway in Beijing. With respect to the characteristics of the urban expressway and our experimental data, we found road slope and traffic density to be the major environmental factors having a significant impact on the V2V communication＇s Line-Of-Sight （LOS） conditions. On the basis of these two factors, we propose a fuzzy classification method for the LOS conditions, and separate the real- time communication environments into different LOS cases. For each LOS case, we quantify the metrics as received signal strength indication, packet delivery rate, and communication latency. The results reveal that the communication reliability in urban expressways is very unstable because of the changing LOS conditions. This study provides a useful reference for the IEEE 802.11 p-based cooperative systems in urban expressways.

Simulation and Analysis on Overtaking Safety Assistance System Based on Vehicle-to-Vehicle Communication

Because of the complexity and variability of an intelligent vehicle’s driving environment,it is difficult for the application of the vehicular sensors to meet the needs of the surrounding environment information entirely.Vehicle-to-vehicle(V2V)communication technology is used by target vehicles to exchange information,and obtain the driving condition and driving intention of the front driver.To obtain environmental information outside the range of vehicular sensors in advance,in this paper,a vehicle overtaking assistance system is proposed based on V2V communication.The data,including the speed,position,direction angle and steering angle obtained using V2V communication,were preliminarily processed.Then,combined with an overtaking safety distance model,the vehicle parameters,driver’s driving intention and vehicle status information were entered into an overtaking security assistance system to determine the overtaking conditions.Fuzzy theory was used to control the parameters of the overtaking safety distance model.Finally,the overtaking safety assistance system was established and the proposed algorithm was tested using PreScan/MATLAB cooperative simulation software.The results showed that the proposed overtaking safety algorithm effectively provided a warning according to environmental change and the driver’s intention,which assisted the driver to overtake and avoid the occurrence of accidents,which improved the safety performance of the vehicle.

Visible light communication for intelligent transportation systems:A review of the latest technologies

In seeking to improve traffic congestion and safety on roads and highways,there has been an increased interest in intelligent transportation systems(ITS).The emerging visible light communication(VLC)technology is a new candidate to enable wireless access in ITS.The purpose of this study is to present a comprehensive review of the current studies related to VLC.Since VLC facilitates illumination and data communication simultaneously,it reduces energy consumption significantly.Additionally,VLC is immune to electromagnetic interference,provides high data security,and utilizes unregulated visible light spectrum,showing promise as a potentially cheaper alternative to existing radio frequency(RF)based technology.Moreover,recent advances in semiconductor materials and solid-state technologies have enabled the development of efficient light-emitting diodes(LEDs)and laser diodes(LDs)which are used as transmitters in a VLC system.Although 10 s of Gbits/s data rate has been demonstrated in indoor VLC links,successful implementation of it in outdoor environments requires further research to overcome the challenges presented by environmental factors,unwanted lights,non-line of sight communication,directional radiation pattern,frequent fragmentation,and so on.Besides,in recent years,semiconductor LDs have been garnering more attention since they can transmit more data over longer distances due to their high quantum efficiency and modulation bandwidth compared to LEDs.As a result,urban planners,policy-makers,transportation engineers,and vehicle manufacturers are considering LD-based VLC to facilitate vehicle-to-vehicle and vehicle-to-infrastructure communication.Thus,this paper reviews and compares the most recent developments in VLC technologies,identifies their benefits and potential use in ITS applications,discusses the probable barriers for their implementation in our existing transportation infrastructure,and suggests future research directions and recommendations to overcome these challenges.

Advances in Vehicular Ad-hoc Networks(VANETs):Challenges and Road-map for Future Development

Recent advances in wireless communication technologies and auto-mobile industry have triggered a significant research interest in the field of vehicular ad-hoc networks （VANETs） over the past few years. A vehicular network consists of vehicle-to-vehicle （V2V） and vehicle-to-infrastructure （V2I） communications supported by wireless access technologies such as IEEE 802.11p. This innovation in wireless communication has been envisaged to improve road safety and motor traffic efficiency in near future through the development of intelligent transportation system （ITS）. Hence, governments, auto-mobile industries and academia are heavily partnering through several ongoing research projects to establish standards for VANETs. The typical set of VANET application areas, such as vehicle collision warning and traffic information dissemination have made VANET an interesting field of mobile wireless communication. This paper provides an overview on current research state, challenges, potentials of VANETs as well as the ways forward to achieving the long awaited ITS.

Design of hexagon microstrip antenna for vehicle-to-vehicle communication

Considering the shortcomings of the existing vehicle-to-vehicle（V2V） communication antennas, this paper proposes a regular hexagon broadband microstrip antenna. By loading shorting pins and etching V-shape slots with different size at each angle of the regular hexagon patch, it realizes impedance matching and obtains better impedance bandwidth. The simulated results show that the relative bandwidth of this antenna reaches 35.55%, covers the frequency band of 4.74 GHz to 6.79 GHz. The antenna acquires an omni-directional radiation pattern in the horizontal plane whose out of roundness is less than 0.5 d B. In addition, the antenna is manufactured and tested, whose tested results are basically consistent with simulated results. Because the height of antenna is 3 mm, it is easy to be hidden on roof of a vehicle for V2 V communication.

Optimal control of automated left-turn platoon at contraflow left-turn lane intersections

Purpose–This study aims to propose a centralized optimal control model for automated left-turn platoon at contraflow left-turn lane(CLL)intersections.Design/methodology/approach–The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness.The proposed model is cast into a mixed-integer linear programming problem and then solved by the branch-and-bound technique.Findings–The proposed model has a promising control effect under different geometric controlled conditions.Moreover,the proposed model performs robustly under various safety time headways,lengths of the CLL and green times of the main signal.Originality/value–This study proposed a centralized optimal control model for automated left-turn platoon at CLL intersections.The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness。