V2X Services Research Articles

Slice Sandwich: Jagged Slicing Multi-Tier Dynamic Resources for Diversified V2X Services

Slice Sandwich: Jagged Slicing Multi-Tier Dynamic Resources for Diversified V2X Services

A Multi-Agent Framework for P2P Energy Trading with EV Aggregators Supporting V2X Services

A Multi-Agent Framework for P2P Energy Trading with EV Aggregators Supporting V2X Services

Dynamic Resource Allocation Approach for Interference Mitigation based on NOMA in Network Operating in Both Uplink and Downlink

The new notion of Internet of Vehicles (IoV) supports Vehicle-to-Everything (V2X) communications, which play a very important role in 5G systems. Ultra-Dense-Network (UDN) and the new scheme Non-orthogonal multiple access (NOMA) are two important concepts to meet the requirements of V2X services with their remarkable capacity. However, the concept of NOMA technology, which allows multiple vehicles to be served by the same resource, can lead to interference between different active users. In addition, the extensive placement of small base stations (SBS) in UDN causes severe interference and degrades the network performance. To solve these problems, interference mitigation is widely used to avoid interference in NOMA-based UDN. In this document, we suggested a dynamic resource allocation method named Intra-cell-Inter-cell Interference Mitigation for V2X communication for UDN in uplink and downlink sense (Intra-Inter IMVN). Our algorithm aims to achieve five principals objectives, namely applying the same algorithm for both downlink and uplink modes, reducing the degree of interference, improving network performance in aspects like error rates and throughput, minimizing cost and delay when using this alternative, combining dynamic metrics to support many V2X scenarios and requirements, and dealing with two categories of interference such as inter-cell interference and intra-cell interference. Numerical results demonstrate that our suggested Intra-Inter IMVN approach offers higher performance compared to other existing algorithms as a function of various parameters.

Edge computing for Vehicle to Everything: a short review.

Vehicle to Everything (V2X) communications and services have sparked considerable interest as a potential component of future Intelligent Transportation Systems. V2X serves to organise communication and interaction between vehicle to vehicle (V2V), vehicle to infrastructure (V2I), vehicle to pedestrians (V2P), and vehicle to networks (V2N). However, having multiple communication channels can generate a vast amount of data for processing and distribution. In addition, V2X services may be subject to performance requirements relating to dynamic handover and low latency communication channels. Good throughput, lower delay, and reliable packet delivery are the core requirements for V2X services. Edge Computing (EC) may be a feasible option to address the challenge of dynamic handover and low latency to allow V2X information to be transmitted across vehicles. Currently, existing comparative studies do not cover the applicability of EC for V2X. This review explores EC approaches to determine the relevance for V2X communication and services. EC allows devices to carry out part or all of the data processing at the point where data is collected. The emphasis of this review is on several methods identified in the literature for implementing effective EC. We describe each method individually and compare them according to their applicability. The findings of this work indicate that most methods can simulate the EC positioning under predefined scenarios. These include the use of Mobile Edge Computing, Cloudlet, and Fog Computing. However, since most studies are carried out using simulation tools, there is a potential limitation in that crucial data in the search for EC positioning may be overlooked and ignored for bandwidth reduction. The EC approaches considered in this work are limited to the literature on the successful implementation of V2X communication and services. The outcome of this work could considerably help other researchers better characterise EC applicability for V2X communications and services.

Real-time RL-based 5G Network Slicing Design and Traffic Model Distribution: Implementation for V2X and eMBB Services

Real-time RL-based 5G Network Slicing Design and Traffic Model Distribution: Implementation for V2X and eMBB Services

Implementation of dynamic selective location in new radio communication services of the 5th generation based on the «vehicle connected to everything» technology

Problem statement. The principle of operation of dynamic selective positioning in fifth generation (5G) networks is especially relevant in the “vehicle connected to everything” (V2X) technology used in the automotive communication system, which includes types of communication that occur between one “vehicle” object and objects such as "infrastructure", "network", "pedestrian" or "device". To achieve high accuracy in V2X services, it is necessary to provide stable and uninterrupted connection, coverage with a minimum number of available communication points and wide bandwidth. Lack of line of sight is one of the major challenges in achieving accurate positioning in many locations, such as urban environments, tunnels, and underground parking lots. Today, the development of potential solutions to provide new users of the V2X service with high positioning accuracy is an urgent task for promising versions of the 5th generation mobile communication technology, which is being formed by the 3rd Generation Partnership Project (3GPP) consortium. Target. Introduce a new selective positioning method based on the dispersion of adjacent signal arrival times for dynamic switching between RAT-dependent methods and GNSS positioning methods. Results. Promising solutions have been explored to provide NR V2X users with long-term and highly accurate positioning. A selective positioning method is shown to dynamically switch between GNSS and DL-TDOA measurements based on the location of V2X users and improve the accuracy of the collected measurements using a MAP-based criterion to evaluate performance gains by combining measurements from different technologies in services. NR V2X. The proposed hybrid methods were evaluated using system-level simulations, the results of which demonstrated that the proposed algorithms can achieve position errors ≤ 3 m with an availability of approximately 76% compared to the 51 and 58% availability obtained using only GNSS measurements. or DL-TDOA, respectively. It is shown that in order to improve the tail of the distribution of user positioning errors by more than 56%, it is necessary to apply the deployment of roadside communication units. Practical significance. The implementation of the selective positioning method based on the dispersion of adjacent times of signal arrivals makes it possible to improve the accuracy of determining the location of a moving object in networks built on the basis of V2X technology. Thus, the developed solution helps to ensure stable data transmission with minimal interference due to dynamic switching between different detection methods.

3GPP 5G V2X Error Correction Coding for Various Propagation Environments: A QoS Approach

Vehicle-to-everything (V2X) communications is an emerging branch of wireless communications and has recently gained a lot of interest not only from academia but also from the automotive and telecommunications industry. An important feature of V2X telecommunication systems is that the communication quality varies quickly in time due to the high mobility of the transceivers and due to the rapid change in the fading characteristics of the communication medium. For this reason, it is vital to maintain tolerable quality of service (QoS) in a V2X communication environment, in terms of communication reliability, power, end-to-end latency, data rate, communication range, throughput and vehicle density. A significant impact on the quality parameters of the system has been the coding scheme used by the V2X telecommunication system. For this purpose, we examine the effect that popular coding schemes have on the QoS of a V2X communication system. More specifically, the impact of fourth-generation long-term evolution (4G-LTE) turbo codes, fifth-generation new radio (5G-NR) polar codes and 5G-NR low-density parity-check codes (LDPC) on the QoS parameters of a V2X communication system is researched. Το this end, we employ stochastic V2X propagation models that simulate every possible V2X channel state and traffic environment, based on the third-generation partnership project (3GPP) Release 16 specifications. These propagation models form the basis of our study, since through them, at a first level, we analyze the frame error rate (FER) performance for different levels of signal-to-noise ratios (SNRs) for all the aforementioned coding schemes and 128-bit V2X-compatible data frames, and, at a second level, we investigate the impact of these propagation models and coding schemes on the V2X QoS parameters. Our analysis shows that turbo-based coding schemes satisfy all the QoS parameters and achieve overall communication quality comparable to polar and better than LDPC, making them suitable for small-frame 5G V2X services.

Modeling and Evaluation of a Dynamic Channel Selection Framework for Multi-Channel Operation in ITS-G5

Many years ago, it seemed inconceivable that our cars could drive autonomously or communicate with each other to form a self-organizing convoy or platoon. By 2023, however, technological advances have taken us to the point where most of these goals will be achieved. In the time of what was initially known as Day 1, single-channel Intelligent Transport System (ITS) devices fully met the requirements for safe communication. The trends show that with the rapid development and the emergence of new, more robust Vehicle-to-Everything (V2X) applications, which require higher bandwidth (collectively called Day 2), the current single-channel medium access method in the available ITS bands will no longer achieve the desired capacities. The main reason is that Day 2 and beyond V2X information dissemination protocols introduce increasing packet sizes and sending frequencies. To complete a resource-friendly and more efficient operation with Day 2 or other advanced V2X services, ITS standards present the Multi-Channel Operation (MCO) constellation as a potential solution. In the case of MCO, we use two or more channels simultaneously, thus preventing the radio medium from saturating its capacity. However, there are still several pending questions about MCO applicability, practical usage, configuration, and deployment, to name a few. The primary purpose of this article is to present a dynamic channel selection framework design and implementation capable of modeling and simulating advanced multi-channel communication use cases. We used this framework to investigate Channel Busy Ratio (CBR) based dynamic channel switching within the Artery/OMNeT++ simulation environment.

Edge computing for Vehicle to Everything: a short review

Vehicle to Everything (V2X) communications and services have sparked considerable interest as a potential component of future Intelligent Transportation Systems. V2X serves to organise communication and interaction between vehicle to vehicle (V2V), vehicle to infrastructure (V2I), vehicle to pedestrians (V2P), and vehicle to networks (V2N). However, having multiple communication channels can generate a vast amount of data for processing and distribution. In addition, V2X services may be subject to performance requirements relating to dynamic handover and low latency communication channels. Good throughput, lower delay, and reliable packet delivery are the core requirements for V2X services. Edge Computing (EC) may be a feasible option to address the challenge of dynamic handover and low latency to allow V2X information to be transmitted across vehicles. Currently, existing comparative studies do not cover the applicability of EC for V2X. This review explores EC approaches to determine the relevance for V2X communication and services. EC allows devices to carry out part or all of the data processing at the point where data is collected. The emphasis of this review is on several methods identified in the literature for implementing effective EC. We describe each method individually and compare them according to their applicability. The findings of this work indicate that most methods can simulate the EC positioning under predefined scenarios. These include the use of Mobile Edge Computing, Cloudlet, and Fog Computing. However, since most studies are carried out using simulation tools, there is a potential limitation in that crucial data in the search for EC positioning may be overlooked and ignored for bandwidth reduction. The EC approaches considered in this work are limited to the literature on the successful implementation of V2X communication and services. The outcome of this work could considerably help other researchers better characterise EC applicability for V2X communications and services.

Heterogeneous Architecture for DSRC/LTE Vehicular Communication Networks Based on the ITS Reference Architecture with Fuzzy Logic for Decision-Making

Methods to integrate different access technologies such as heterogeneous communication architecture remains a challenge. Among a variety of V2X-supporting access technologies, Dedicated Short Range Communication (DSRC) and cellular communications, e.g., Long Term Evolution (LTE) is promising reliable and efficient vehicular communications. DSRC has been designed to allow for direct low-latency communications among different vehicles (i.e., V2V) and between vehicles and roadside units (RSU). On the other hand, DSRC suffers from link quality degradation with the presence of buildings and vehicles, especially in urban areas, where channel collisions become serious when vehicle density is high. LTE networks can provide wide area coverage and are favorable to bandwidth-greedy applications, which require high data rates and reliability. Considering the relatively high end-to-end delay for message transmission due to the long transmission time interval (TTI) current LTE networks have drawbacks regarding latency to support highfrequency safety-related information exchange among vehicles in local areas. Combining LTE and DSRC approaches as a heterogeneous solution is essential to fast introduce V2X services for future automated driving. By this intelligent Vertical Handover (VHO) algorithms are needed to ensure seamless connectivity of vehicles to the best network at a particular point in time. For this paper, we propose a 3- input fuzzy-logic-based VHO scheme for Heterogeneous DSRC/LTE Vehicular Communication Networks. The simulation results in this paper show that the proposed 3- input fuzzy-logic model can be able to make decisions and select the best network to connect to base on the network with the highest HF value. The 3-input fuzzy-logic model was also tested in a vehicular highway scenario simulation. The proposed model shows optimized communication results in terms of the mean end-to-end delay against that of the literature.

End-to-End V2X Latency Modeling and Analysis in 5G Networks

5G networks provide higher flexibility and improved performance compared to previous cellular technologies. This has raised expectations on the possibility to support advanced Vehicle to Everything (V2X) services using the cellular network via Vehicle-to-Network (V2N) and Vehicle-to-Network-to-Vehicle (V2N2V) connections. The possibility to support critical V2X services using 5G V2N2V or V2N connections depends on their end-to-end (E2E) latency. The E2E latency of V2N2V or V2N connections depends on the particular 5G network deployment, dimensioning and configuration, in addition to the network load. To date, few studies have analyzed the capabilities of V2N2V or V2N connections to support critical V2X services, and most of them focus on the 5G radio access network or consider dedicated 5G pilot deployments under controlled conditions. This paper progresses the state-of-the-art by introducing a novel E2E latency model to quantify the latency of 5G V2N and V2N2V communications. The model includes the latency introduced at the radio, transport, core, Internet, peering points and application server (AS) when vehicles are supported by a single mobile network operator (MNO) and when they are supported by multiple MNOs. The model can quantify the latency experienced when the V2X AS is deployed from the edge of the network (using MEC platforms) to the cloud. Using this model, this study estimates the E2E latency of 5G V2N2V connections for a large variety of possible 5G network deployments and configurations. The analysis helps identify which 5G network deployments and configurations are more suitable to meet V2X latency requirements. To this aim, we consider as case study the cooperative lane change service. The conducted analysis highlights the challenge for centralized network deployments that locate the V2X AS at the cloud to meet the latency requirements of advanced V2X services. Locating the V2X AS closer to the cell edge reduces the latency. However, it requires a higher number of ASs and also a careful dimensioning of the network and its configuration to ensure sufficient network and AS resources are dedicated to serve the V2X traffic.

5G Advanced: Sidelink Evolution

Third Generation Partnership Project (3GPP) standardization studied sidelink operation for 5G New Radio (NR), targeting advanced vehicle-to-everything (V2X) services in Release 16/17. 3GPP recently approved 5G Advanced study item, which includes NR sidelink for unlicensed operation, NR sidelink positioning for commercial devices, public safety, and V2X services. This article presents an overview of NR sidelink use case, requirements to be studied in 5G advanced, and discusses potential improvements needed in the physical layer. Furthermore, this article outlines design improvements needed in the NR sidelink physical layer, addressing it to meet regulatory requirements to operate in the unlicensed band, relative positioning calculation between peer sidelink devices, using sidelink relative positioning methods, and, finally, to meet ultra-low latency. Very high reliability enhancement is required for Industrial Internet of Things (IIoT) use case, such as end-to-end latency of 1msec, hi gh reliability up-to 99.9999 percen, t and tight requirement for clock synchronicity at <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$1\ \mu\mathrm{s}$</tex> .

5G V2X Performance Comparison for Different Channel Coding Schemes and Propagation Models

Channel coding is a fundamental procedure in wireless telecommunication systems and has a strong impact on the data transmission quality. This effect becomes more important when the transmission must be characterised by low latency and low bit error rate, as in the case of vehicle-to-everything (V2X) services. Thus, V2X services must use powerful and efficient coding schemes. In this paper, we thoroughly examine the performance of the most important channel coding schemes in V2X services. More specifically, the impact of use of 4th-Generation Long-Term Evolution (4G-LTE) turbo codes, 5th-Generation New Radio (5G-NR) polar codes and low-density parity-check codes (LDPC) in V2X communication systems is researched. For this purpose, we employ stochastic propagation models that simulate the cases of line of sight (LOS), non-line of sight (NLOS) and line of sight with vehicle blockage (NLOSv) communication. Different communication scenarios are investigated in urban and highway environments using the 3rd-Generation Partnership Project (3GPP) parameters for the stochastic models. Based on these propagation models, we investigate the performance of the communication channels in terms of bit error rate (BER) and frame error rate (FER) performance for different levels of signal to noise ratio (SNR) for all the aforementioned coding schemes and three small V2X-compatible data frames. Our analysis shows that turbo-based coding schemes have superior BER and FER performance than 5G coding schemes for the vast majority of the considered simulation scenarios. This fact, combined with the low-complexity requirements of turbo schemes for small data frames, makes them more suitable for small-frame 5G V2X services.

Advancing C-V2X for Level 5 Autonomous Driving from the Perspective of 3GPP Standards.

Cellular vehicle-to-everything (C-V2X) is one of the enabling vehicular communication technologies gaining momentum from the standardization bodies, industry, and researchers aiming to realize fully autonomous driving and intelligent transportation systems. The 3rd Generation Partnership Project (3GPP) standardization body has actively been developing the standards evolving from 4G-V2X to 5G-V2X providing ultra-reliable low-latency communications and higher throughput to deliver the solutions for advanced C-V2X services. In this survey, we analyze the 3GPP standard documents relevant to V2X communication to present the complete vision of 3GPP-enabled C-V2X. To better equip the readers with knowledge of the topic, we describe the underlying concepts and an overview of the evolution of 3GPP C-V2X standardization. Furthermore, we provide the details of the enabling concepts for V2X support by 3GPP. In this connection, we carry out an exhaustive study of the 3GPP standard documents and provide a logical taxonomy of C-V2X related 3GPP standard documents divided into three categories: 4G, 4G & 5G, and 5G based V2X services. We provide a detailed analysis of these categories discussing the system architecture, network support, key issues, and potential solution approaches supported by the 3GPP. We also highlight the gap and the need for intelligence in the execution of different operations to enable the use-case scenarios of Level-5 autonomous driving. We believe, the paper will equip readers to comprehend the technological standards for the delivery of different ITS services of the higher level of autonomous driving.

An Analytical Latency Model and Evaluation of the Capacity of 5G NR to Support V2X Services Using V2N2V Communications

5G has been designed to support applications such as connected and automated driving. To this aim, 5G includes a highly flexible New Radio (NR) interface that can be configured to utilize different subcarrier spacings (SCS), slot durations, scheduling, and retransmissions mechanisms. This flexibility can be exploited to support advanced V2X services with strict latency and reliability requirements using V2N2V (Vehicle-to-Network-to-Vehicles) communications instead of direct or sidelink V2V (Vehicle-to-Vehicle). To analyze this possibility, this paper presents a novel analytical model that estimates the latency of 5G at the radio network level. The model accounts for the use of different numerologies (SCS, slot durations and Cyclic Prefixes), modulation and coding schemes, full-slots or mini-slots, semi-static and dynamic scheduling, different retransmission mechanisms, and broadcast/multicast or unicast transmissions. The model has been used to first analyze the impact of different 5G NR radio configurations on the latency. We then identify which radio configurations and scenarios can 5G NR satisfy the latency and reliability requirements of V2X services using V2N2V communications. This paper considers cooperative lane changes as a case study. The results show that 5G can support advanced V2X services at the radio network level using V2N2V communications under certain conditions that depend on the radio configuration, bandwidth, service requirements and cell traffic load.

Vehicle-to-Everything (V2X) Evolution From 4G to 5G in 3GPP: Focusing on Resource Allocation Aspects

Cellular Vehicle-to-everything (V2X) is evolving from a communication technology for safety messages towards a platform for advanced V2X services such as platooning and autonomous driving. The development of technical specifications for V2X communications is done across several task specification groups (TSGs) and working groups (WGs) within 3rd Generation Partnership Project (3GPP). In this paper, we focus on radio access network (RAN) aspects for direct communication between user equipments (UEs), which is known as sidelink (SL) communication. Resource allocation for SL communication can be performed in one of two modes. In the first mode, resource allocation is centralized in the network. In the second mode, resource allocation is performed in a distributed manner among UEs, where resource selection is performed at a transmitting UE, i.e., the transmitting UE determines time and frequency resources for a SL transmission without the assistance of a base station. In this paper, we review V2X evolution from 4G to 5G in 3GPP focusing on resource allocation aspects defined in Long-Term Evolution (LTE) and New Radio (NR) specifications, with particular attention given to the difference in design and performance of each. We highlight the key 3GPP standard developments on V2X resource allocation which includes enhanced resource reselection mechanisms and partial sensing schemes. It is observed that NR V2X resource reselection mechanism can provide up to 20% of reliability improvement over LTE V2X and NR V2X partial sensing scheme can provide up to 95% of reduced power consumption over full sensing scheme.

Secure Privacy-Preserving V2V Communication in 5G-V2X Supporting Network Slicing

As autonomous driving technology continues to develop, communication for vehicles is becoming more important to provide an efficient and secure driving environment. Currently, vehicle-to-everything (V2X) based on fifth-generation (5G) is the only solution to meet the demanding requirements of self-driving cars in terms of ultra-low latency and ultra-high reliable connectivity under high mobility conditions, earning this technology more attention. Secure communication for vehicle-to-vehicle based on 5G (5G-V2V) is essential because vehicles decide how to maneuver and perceive situations based on the data exchanged. In this paper, we not only propose a new architecture for V2X based on 5G (5G-V2X) by utilizing network slicing (NS) to guarantee different features of V2X services but also analyze security requirements according to V2X service type. We also propose a secure V2V communication scheme based on 5G that satisfies these requirements. The security evaluation demonstrates that our scheme is secure against attacks on a V2V environment via both security proof and verification tool ProVerif. Through the performance evaluation, we prove that our scheme is more effective than the existing schemes while meeting end-to-end delay requirements for autonomous driving.

Edge computing for Vehicle to Everything: a short review

Vehicle to Everything (V2X) communications and services have sparked considerable interest as a potential component of future Intelligent Transportation Systems. V2X serves to organise communication and interaction between vehicle to vehicle (V2V), vehicle to infrastructure (V2I), vehicle to pedestrians (V2P), and vehicle to networks (V2N). However, having multiple communication channels can generate a vast amount of data for processing and distribution. In addition, V2X services may be subject to performance requirements relating to dynamic handover and low latency communication channels. Good throughput, lower delay, and reliable packet delivery are the core requirements for V2X services. Edge Computing (EC) may be a feasible option to address the challenge of dynamic handover and low latency to allow V2X information to be transmitted across vehicles. Currently, existing comparative studies do not cover the applicability of EC for V2X. This review explores EC approaches to determine the relevance for V2X communication and services. EC allows devices to carry out part or all of the data processing at the point where data is collected. The emphasis of this review is on several methods identified in the literature for implementing effective EC. We describe each method individually and compare them according to their applicability. The findings of this work indicate that most methods can simulate the EC positioning under predefined scenarios. These include the use of Mobile Edge Computing, Cloudlet, and Fog Computing. However, since most studies are carried out using simulation tools, there is a potential limitation in that crucial data in the search for EC positioning may be overlooked and ignored for bandwidth reduction. The EC approaches considered in this work are limited to the literature on the successful implementation of V2X communication and services. The outcome of this work could considerably help other researchers better characterise EC applicability for V2X communications and services.

Electromobility in Australia: Tariff Design Structure and Consumer Preferences for Mobile Distributed Energy Storage

The adoption of electric vehicles (EVs) may contribute to decarbonisation of the transport sector and has the potential to offer value to consumers and electricity grid operators through its energy storage capabilities. While electricity tariffs can play an important role in consumer uptake of EVs, little is known about how EV charging tariff design affects EV users’ behaviour in participating in applications that can support the electricity grid, such as those applications classed under Vehicle-to-Everything (V2X). Examining the case of Australia, this study reviews the literature on electromobility with a focus on EV charging tariffs and its impact on consumer behaviour within the V2X context. The main findings drawn from up-to-date publications show that a well-designed EV tariff structure, available parking, and EV charging facilities can increase consumer participation in V2X. However, cooperation between EV users and grid operators is needed to establish a form of controlled charging agreement to harness the full potential of the EV electricity storage system for grid stability and battery support operations. To achieve this, the right tariff structure will have to be established to incentivise EV consumers to subscribe to V2X services. We also present recommendations for EV tariff design to support Australian consumer participation in V2G. Finally, we identify research gaps for further research.

Deep Reinforcement Learning-Based RAN Slicing for UL/DL Decoupled Cellular V2X

The emerging uplink (UL) and downlink (DL) decoupled radio access networks (RAN) has attracted a lot of attention due to the significant gains in network throughput, load balancing and energy consumption, etc. However, due to the diverse vehicular service requirements in different vehicle-to-everything (V2X) applications, how to provide customized cellular V2X services with diversified requirements in the UL/DL decoupled 5G and beyond cellular V2X networks is challenging. To this end, we investigate the feasibility of UL/DL decoupled RAN framework for cellular V2X communications, including the vehicle-to-infrastructure (V2I) communications and relay-assisted cellular vehicle-to-vehicle (RAC-V2V) communications. We propose a two-tier UL/DL decoupled RAN slicing approach. On the first tier, the deep reinforcement learning (DRL) soft actor-critic (SAC) algorithm is leveraged to allocate bandwidth to different base stations. On the second tier, we model the QoS metric of RAC-V2V communications as an absolute-value optimization problem and solve it by the alternative slicing ratio search (ASRS) algorithm with global convergence. The extensive numerical simulations demonstrate that the UL/DL decoupled access can significantly promote load balancing and reduce C-V2X transmit power. Meanwhile, the simulation results show that the proposed solution can significantly improve the network throughput while ensuring the different QoS requirements of cellular V2X.