Vehicular Communication Networks Research Articles

Effective Capacity Maximization in beyond 5G Vehicular Networks: A Hybrid Deep Transfer Learning Method

How to improve delay‐sensitive traffic throughput is an open issue in vehicular communication networks, where a great number of vehicle to infrastructure (V2I) and vehicle to vehicle (V2V) links coexist. To address this issue, this paper proposes to employ a hybrid deep transfer learning scheme to allocate radio resources. Specifically, the traffic throughput maximization problem is first formulated by considering interchannel interference and statistical delay guarantee. The effective capacity theory is then applied to develop a power allocation scheme on each channel reused by a V2I and a V2V link. Thereafter, a deep transfer learning scheme is proposed to obtain the optimal channel assignment for each V2I and V2V link. Simulation results validate that the proposed scheme provides a close performance guarantee compared to a globally optimal scheme. Besides, the proposed scheme can guarantee lower delay violation probability than the schemes aiming to maximize the channel capacity.

Real-time separation optimisation algorithm for hybrid blind speech signal in vehicular communication networks in beyond the 5G era

Real-time separation optimisation algorithm for hybrid blind speech signal in vehicular communication networks in beyond the 5G era

Comprehensive Survey on Machine Learning in Vehicular Network: Technology, Applications and Challenges

Towards future intelligent vehicular network, the machine learning as the promising artificial intelligence tool is widely researched to intelligentize communication and networking functions. In this paper, we provide a comprehensive survey on various machine learning techniques applied to both communication and network parts in vehicular network. To benefit reading, we first give a preliminary on communication technologies and machine learning technologies in vehicular network. Then, we detailedly describe the challenges of conventional techniques in vehicular network and corresponding machine learning based solutions. Finally, we present several open issues and emphasize potential directions that are worthy of research for the future intelligent vehicular network.

Mutual Informative Brown Clustering based Multiattribute Cockroach Swarm Optimization for Reliable Data Dissemination in VANET

A vehicular ad hoc network (VANETs) intends to obtain communication for vehicular networks and enhances road safety and effectiveness with help of wireless technology. Data dissemination is an important process in communication. In VANETs system, Data dissemination plays a significant role. A novel Mutual informative brown clustering-based multi attribute cockroach swarm optimization (MIBCMCSO) technique is introduced for improving data dissemination. In reliable data dissemination, clustering and optimization are the two major process of proposed MIBCMCSO technique. Initially, clustering procedure is performed for separating entire network towards different groups of vehicle nodes namely distance, direction, density and velocity of node. For each group, cluster head was chosen among the members to efficient data with minimum delay. Secondly, multi attribute cockroach swarm optimization technique is applied for finding optimal cluster head through multi attribute functions such as residual energy, bandwidth availability, and distance. Then source node performs data dissemination destination via optimal cluster head. Simulation of MIBCMCSO as well as existing technique is performed by various performance parameters like packet delivery ratio, end to end delay and throughput. MIBCMCSO achieves higher consistency of data dissemination as well as lesser delay than conventional methods.

Weighted-Sum-Rate Maximization for an Reconfigurable Intelligent Surface Aided Vehicular Network

Recently, reconfigurable intelligent surfaces (RISs) have been identified as one potential solution to avoid performance degradation of using millimeter wave (mmWave) frequencies in vehicular communications. In this paper, we investigate the use of an RIS in a mmWave vehicular communication network. The problem of weighted sum-rate maximization in the uplink is considered, where an RIS is used to assist the communication. We focus on both single-user and multi-user cases. Single user case is solved using successive refinement algorithm, where two phase-optimization schemes that help reducing the channel estimation overhead are considered. In multi-user case, fractional programming technique is used to reformulate the original problem into a more convenient form, and an algorithm based on alternating optimization is proposed. The validity of the proposed methods is confirmed by numerical simulations. A significant performance increase is seen when utilizing an RIS in both cases. Considered phase optimization schemes are shown to result in a significant reduction in channel estimation at a cost of small performance degradation compared to the full channel state information beamforming scenario. We perform simulations to investigate the effects of mobility, and the results demonstrate the ability of an RIS to mitigate the effects of mobility to some extent. Furthermore, to get practical insights into vehicular communications aided by an RIS, we use a commercial ray-tracing tool to evaluate the performance.

Joint use of DSRC and C‐V2X for V2X communications in the 5.9 GHz ITS band

Vehicular communications networks form the backbone of cooperative intelligent transport systems to support road safety and infotainment applications amongst users. IEEE 802.11p of the Dedicated Short-Range Communications protocol stack has been the technology of choice for Vehicle-to-Everything communications within the United States and Japan and has been extensively trailed in other countries such as Australia. With the advent of cellular technologies, a new, competing cellular-based Device-to-Device technology, known as Cellular Vehicle-to-Everything Sidelink, has emerged. Considering both technologies suffer from performance limitations, there is a current debate as to which of these technologies will eventually dominate the cooperative intelligent transport systems landscape if they cannot coexist. To investigate mechanisms of spectrum sharing between Dedicated Short-Range Communications and Cellular Vehicle-to-Everything for deployment in a common region, this paper initially reviews the background and technicalities of both technologies. The paper subsequently sets forth Vehicle-to-Everything platform models that allow not only spectrum sharing at the ITS band but also concurrent and simultaneous propagations of Dedicated Short-Range Communications and Cellular Vehicle-to-Everything messages. The transmission and reception mechanisms of hybrid Vehicle-to-Everything platforms are verified through a describing function model.

A Beacon-less Multi-channel Packet Forwarding Scheme in Vehicular Networks

The ad-hoc vehicular network is a sub stream of an ad-hoc mobile network where the nodes can converse and know each other by their periodic control packet dissemination. In vehicular network communication, the available bandwidth is limited. The parallel and multi-vehicle channel access will create an unwanted delay during the packet dissemination. The node may compete with each other to access the channel during parallel communication. The simultaneous channel access will increase network overload. The proposed approach will minimize the channel access collision through the variable time slots. Before any data dissemination, the node will send a Channel Booking Request (CBR) message to a correspondent node. The spectrum allocation is based on the type of vehicle and message_code. The concept has experimented with traditional routing protocols for overtaking assistance. The proposed approach is compared with the packet delivery rate, jitter, and packet loss rate.

DOLPHIN: Dynamically Optimized and Load Balanced Path for Inter-Domain SDN Communication

Software-Defined Networking has become an integral technology for large scale networks that require dynamic flow management. It separates the control function from data plane devices and centralizes it in a domain controller. However, only a limited number of switches can be managed by a single and centralized controller which introduces challenges such as scalability, reliability, and availability. Distributed controller architecture resolves these issues but also introduces new challenges of uneven load and traffic management across domains. As real-world networks have redundant links, hence a significant challenge is to distribute traffic flows on multiple paths, within a domain, and across multiple independent domains. The selection of ingress and egress switches becomes even more problematic if the intermediate domain is non-cooperative. In this work, we propose a Dynamically Optimized and Load-balanced Path for Inter-domain (DOLPHIN) communication system, a customized solution for different SDN controllers. It provides control beyond the virtual switch elements in intra and inter-domain communication and extends the range of programmability to wireless devices, such as the Internet of Things or vehicular networks. Extensive simulation results show that the traffic load is distributed evenly on multiple links connecting different domains. We model data center communication and 5G vehicular network communication to show that, by load balancing the flow completion times of the different types of network traffic can be significantly improved.

The feasibility of obstacle awareness forwarding scheme in a visible light communication vehicular network

A vehicular-to-vehicular (V2V) communication is a part of a vehicular ad-hoc network (VANET) that emerges recently due to the heavy traffic environment. V2V is a frequently changing network since it implements vehicles as mobile nodes. The challenges in implementing V2V are the relatively short duration of possible communication and the uneven city environment caused by high rise buildings or other objects that distract 
 the signal transmission. The limited transmitting duration between vehicles requires efficient coordination and communication. This work focuses on the utility of visible light communication in vehicular network (VLC-VN) in data transmitting and the obstacle awareness in the forwarding scheme based on our knowledge in previous researches. The result of evaluating the feasibility of VLC-VN forwarding in a freeway environment the transmission delay is lower than 1 second in 500 byte data transmission, however it reaches to only about 4% in throughput as a drawback.

Certificateless and Lightweight Authentication Scheme for Vehicular Communication Networks

Reducing the number of road accidents is a key agenda item for governments across the world. This has led to an increase in the amount of attention given to Vehicular Communication Systems (VCS), which are seen as an important technology that can offer significant improvements in road safety. Using VCS, vehicles can form a dynamic self-configuring network that enables a vehicle to communicate with other vehicles (V2V) and roadside infrastructure (V2I). However, such wireless communication channels are vulnerable to attacks, and therefore an authentication scheme for communications should be designed before the deployment. Prior work has focused on utilising digital signature approaches to achieve the security requirements, but due to the special characteristics of VCS, such approaches are not well suited for safety related applications of VCS, since they incur high communication and computation overheads. To combat this issue, we propose a certificateless and lightweight authentication scheme to provide means of secure communications for VCS. In this work we introduce authentication tokens, which replace digital certificates to reduce the burden of certificate management on a Trusted Authority (TA). In addition, the utilisation of tokens ensures that mutual authentication is achieved for V2I communication. Moreover, we employ TESLA as the underlying broadcast authentication protocol to achieve the required security goals for safety message broadcasting. According to the security analysis and extensive simulation of our scheme, the results show that it can withstands various types of attacks. Also it has better performance in term of verification delay, scalability and communication overhead compared to lightweight authentication schemes that are based on similar techniques. Therefore, the scheme is well suited for VCS

Performance of Downlink NOMA in Vehicular Communication Networks: An Analysis Based on Poisson Line Cox Point Process

In this paper we investigate downlink performance in a non-orthogonal multiple access (NOMA) based vehicular communication network. In contrast to the previous works wherein the vehicles are simply assumed to be located anywhere in the coverage area, we consider practical cases where vehicles are located on a system of roads. We then adopt a system model based on Poisson Line Cox Point (PLC) processes, where the road system is represented through a Poisson Line (PL) Process. Vehicles ordered according to their distances to their corresponding roadside units (RSUs) are then served by using power domain NOMA. Adopting analytical tools from the stochastic geometry, we then analyse the outage performance of the system. Numerical results corroborate our analysis and demonstrate how the system settings influence the considered NOMA based V2X network.

Mobility and Blockage-Aware Communications in Millimeter-Wave Vehicular Networks

Mobility may degrade the performance of next-generation vehicular networks operating at the millimeter-wave spectrum: frequent mis-alignment and blockages require repeated beam training and handover, and incur enormous overhead. Nevertheless, mobility induces temporal correlations in the communication beams and in blockage events. In this paper, an adaptive design of beam training, data transmission and handover is proposed, that learns and exploits these temporal correlations to reduce the beam training overhead and optimally trade-off throughput and power consumption. At each time-slot, the serving base station (BS) decides to perform either beam training, data communication, or handover when blockage is detected, under uncertainty in the system state. The decision problem is cast as a partially observable Markov decision process, and the goal is to maximize the throughput delivered to the UE, under an average power constraint. To address the high dimensional optimization, an approximate constrained point-based value iteration (C-PBVI) method is developed, which simultaneously optimizes the primal and dual functions to meet the power constraint. Numerical results demonstrate a good match between the analysis and a simulation based on 2D mobility and 3D analog beamforming via uniform planar arrays at both BSs and UE, and reveal that C-PBVI performs near-optimally, and outperforms a baseline scheme with periodic beam training by 38% in spectral efficiency. Motivated by the structure of the C-PBVI policy, two heuristics are proposed, that trade complexity with sub-optimality, and achieve only 4% and 15% loss in spectral efficiency.

Distributed Utility Optimization in Vehicular Communication Systems

In this paper, we study the problem of utility maximization in the uplink of vehicle-to-infrastructure communication systems. The studied scenarios consider four practical aspects of mobile radio communication links: i) Interference between adjacent channels, ii) interference between roadside units along the way, iii) fast and slow channel fadings, and iv) Doppler shift effects. We present first the system model for the IEEE 802.11p standard, which considers a communication network between vehicles and roadside infrastructure. Next, we formulate the problem of utility maximization in the network, and propose a distributed optimization scheme. This distributed scheme is based on a two-loop feedback configuration, where an outer-loop establishes the optimal signal to interference-noise ratio (SINR) that maximizes the utility function per vehicle and defines a quality-of-service objective. Meanwhile, inner-control loops adjust the transmission power to achieve this optimal SINR reference in each vehicle node regardless of interference, time-varying channel profiles and network latency. The computation complexity of the distributed utility maximization scheme is analyzed for each feedback loop. Simulation results indicate that the proposed scheme reaches the objective SINRs that maximize utility and improve energy efficiency in the network with a low time cost. The results also show that the maximum utility is consistently achieved for different propagation scenarios inside the vehicular communication network.

Green Communications for Future Vehicular Networks: Data Compression Approaches, Opportunities, and Challenges

Cellular vehicular networks constitute an important part of future vehicular communication systems. However, they pose challenges to fulfill vehicles with demands for the transmission rates of various network services while achieving satisfactory costs and energy consumption. The cloud radio access network architecture is considered as a green wireless access network framework that reduces the deployment costs of base stations while achieving resource sharing and dynamic scheduling to lower energy consumption, and thus will greatly improve spectrum efficiency. in this article, we first propose a cloud vehicular radio access network (C-VRAN) architecture to enable rapid network innovation for green vehicular communications. Specifically, we propose a vehicular network framework consisting of centralized processing, collaborative radio, real-time cloud computing, and data compression functions. Then, the design and the potential benefits of C-VRAN are presented in detail. Moreover, an effective data compression approach for the proposed architecture is proposed to meet low-distortion compression for cellular vehicular network data, thereby improving fiber resource utilization. Finally, we briefly discuss key challenges and solutions for future green vehicular communications.

Empowering Communications in Vehicular Networks with an Intelligent Blockchain-Based Solution

Blockchains have emerged over time as a reliable and secure way to record transactions in an immutable manner in a wide range of application domains. However, current related solutions are not yet capable of appropriately checking the authenticity of data when their volumes are huge. They are not also capable of updating Blockchain data blocks and synchronizing them within reasonable timeframes. This is the case within the specific context of Blockchain vehicular networks, where these solutions are commonly cumbersome when attempting to add new vehicles to the network. In order to address these problems, we propose in this paper a new Blockchain-based solution that intelligently implement selective communication and collaborative endorsement approaches to reduce communications between vehicles. Our solution represents the vehicles of the Blockchain as intelligent software agents with a Belief–Desire–Intention (BDI) architecture. Furthermore, we propose an approach based on multi-endorsement levels to exchange data of varying sensitive categories. This approach, which is based on endorsing scores, is also used to shorten the admission of new vehicles into the Blockchain. We run simulations using the Hyperledger Fabric Blockchain tool. Results show the efficiency of our solution in reducing the processing times of transactions within two different scenarios.

Research on Data Transmission Optimization Of Communication Network Based on Reliability Analysis

This paper briefly introduced the vehicular communication network, vehicular ad-hoc network (VANET), and the ant colony algorithm for path search in the network, improved the ant colony algorithm, carried out a simulation experiment on the improved ant colony algorithm on the simulation platform, and compared it with the traditional ant colony algorithm and the geographical location-based routing algorithm. The results showed that the network packet loss rate and time delay showed a tendency of increasing first and then decreasing under the three algorithms with the increase of vehicle nodes in VANET; with the increase of nodes, the network reliability under the improved ant colony algorithm showed a tendency of increasing first and then being stable, and the network reliability under the other two algorithms showed a tendency of increasing first and then decreasing; under the same number of nodes, the packet loss rate and average delay were lower, and the reliability was higher under the improved ant colony algorithm.

Geographic information-based Data Transmission and Cooperative Communication for Vehicular Networks

With the advancements in Vehicular communication technologies in automobile engineering leads to enhancement of modern societies by utilizing Internet based data communication in a vehicular network to effectively avoid accidents and traffic congestions using Multi Input Multi Output (MIMO) cooperative relay technique for enhancing the aspects of performance by reduction of transmission energy consumption by taking the advantage of spatial and temporal diversity gain in a vehicular network as the conventional routing based on topology is merely not suitable over a dynamic vehicular network environment as GPS is used to identify effective route [4].In this paper we propose applications of cooperative communication techniques and their survey for identifying close relationship between forwarding and addressing techniques in a vehicular network and further we compare performance and energy consumption of cooperative techniques with the traditional multi-hop technique over Rayleigh channel using MQAM for optimization.

Geographic information-based Data Transmission and Cooperative Communication for Vehicular Networks

With the advancements in Vehicular communication technologies in automobile engineering leads to enhancement of modern societies by utilizing Internet based data communication in a vehicular network to effectively avoid accidents and traffic congestions using Multi Input Multi Output (MIMO) cooperative relay technique for enhancing the aspects of performance by reduction of transmission energy consumption by taking the advantage of spatial and temporal diversity gain in a vehicular network as the conventional routing based on topology is merely not suitable over a dynamic vehicular network environment as GPS is used to identify effective route [4].In this paper we propose applications of cooperative communication techniques and their survey for identifying close relationship between forwarding and addressing techniques in a vehicular network and further we compare performance and energy consumption of cooperative techniques with the traditional multi-hop technique over Rayleigh channel using MQAM for optimization.

Energy-efficiency maximization in D2D-enabled vehicular communications with consideration of dynamic channel information and fairness

Device-to-device (D2D) communications in a cellular network can be implemented on vehicular communications. However, high mobilities of vehicles generate fast channel variations in the communications. Channel description has to be specified in the D2D-enable vehicular communications network. In this paper, the vehicle speed and the sampling time are involved to the channel description such that the dynamic information of vehicle is integrated with the channel gain. By doing so, the channel description is more practical. The power control and spectrum sharing problem is formulated in order to maximize the energy-efficiency (EE) of total vehicle-to-infrastructure (V2I) links. It also attempts to ensure reliable communications in a multi-cellular users multi-D2D users frequency division multiple access (FDMA) cellular environment. The reformulated objective function in the fractional form is proved to be quasi-concave, and it can be solved by the Dinkelbach method which requires low computational complexity. In addition, the Hungarian algorithm is used to determine the optimal match of cellular user equipments (CUEs) and V2V pairs. User fairness is further considered under the goal of maximizing overall energy efficiency. Then, the approach of minimum EE maximization is implemented on all V2I links in order to improve system fairness. Finally, the system performance of the proposed scheme is validated by numerical simulations. The results show that the algorithm is effective to improve the energy efficiency and robustness in the dynamic communications environment.

Machine Learning and Reputation Based Misbehavior Detection in Vehicular Communication Networks

Vehicular networks are vulnerable to various attacks such as Sybil, denial-of-service (DoS) and false alert generation attacks. Cryptographic methods can provide some protection to vehicular networks from external attacks but are found to be vulnerable to internal attacks. A misbehavior detection system (MDS) can be deployed to detect and prevent internal attacks. In this paper, we propose a machine learning and reputation based MDS to enhance the detection accuracy as well as to ensure the reliability of both vehicles and messages. Proposed MDS is trained using datasets generated through extensive simulation based on the realistic vehicular network environment. To improve the accuracy of the detection, we have employed the Dempster-Shafer (DS) theory-based collaborative misbehavior detection system. In the proposed scheme, the reputation score of each vehicle is used as a belief value for Dempster-Shafer based feedback combination. In addition, we propose a beta distribution based reputation update and revocation scheme. Moreover, we show that our proposed scheme is better compared to previous methods in terms of accurately identifying various misbehaviors.