Intelligent Vehicle Network Routing With Adaptive 3D Beam Alignment for mmWave 5G-Based V2X Communications

Rasheed, Iftikhar; Hu, Fei; Hong, Yang‐Ki; Balasubramanian, Bharat

doi:10.1109/tits.2020.2973859

Cited by 58 publications

(42 citation statements)

References 41 publications

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“…In addition to taking into account the problem of transmission interruption due to blockage, the authors propose an energy-angle domain initial access and beam tracking scheme for a V2X scenario, through which the signals are labeled by different directions with multi-power level. [129] also deals with the topic of beam alignment and the routing stability problems because of vehicles' rapid mobility. The authors introduce a 3D-based position detection method and a group-based routing algorithm to select beam alignment, in addition to define a secure path to achieve reliable data transfers.…”

Section: ) Mmwavementioning

confidence: 99%

On 5G-V2X Use Cases and Enabling Technologies: A Comprehensive Survey

2021

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5G technologies promise faster connections, lower latency, higher reliability, more capacity and wider coverage. We are looking to rely on these technologies to achieve Vehicle-to-Everything (V2X) communications, which increase the safety and autonomy of vehicles in addition to road safety, saving energy and costs. The integration of vehicular communication systems and 5G is the subject of many research. Nowadays, researchers address challenges such as automated and intelligent networks, cloud and edge data processing, network management, virtualization, security, privacy and finally interoperability. This paper provides a survey of the latest V2X use cases including requirements, and various 5G enabling technologies under consideration for vehicular communications. Subsequently, we first provide an interesting mapping between the three 5G pillars and V2X use case groups. Then, we present a summary of potential applications of enabling technologies for V2X use case groups. Finally, the open directions of research are discussed, and the challenges that await to be met are pointed out.

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Section: ) Mmwavementioning

confidence: 99%

On 5G-V2X Use Cases and Enabling Technologies: A Comprehensive Survey

2021

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“…Contributions [47] The proposed routing protocol has the ability to learn the best suited transmission parameters from interactions with the environment [45] Uses knowledge of predictable and periodic movement of buses to learn the temporal distance to transmit every data to RSUs [140] Proposes a better form of BRT which results in overall performance improvement of bus-based routing [51] A group-based routing approach is proposed for detecting the position in 3D for beam selection in mmWave-based V2X transmissions mobility models to learn about vehicle mobility and analyze the impact of mobility on VANET performance. The performance of these models is recorded and correlated using suitable mobility metrics, as they play a very important role in network design.…”

Section: Itemmentioning

confidence: 99%

“…Furthermore, reinforcement learning is used to meet the requirements of VANETs. The authors of [51] consider beam alignment difficulties and routing stability issues in millimeter Wave (mmWave)-based V2X transmissions, and accordingly propose a scheme for detecting the position of vehicles in 3D for beam selection or alignment purposes. A group-based routing approach is followed to choose a secure path that can achieve trustworthy data transmissions.…”

Section: Itemmentioning

confidence: 99%

A Survey of VANET/V2X Routing From the Perspective of Non-Learning- and Learning-Based Approaches

Chatterjee¹,

Karmakar

Kaddoum

et al. 2022

IEEE Access

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Intelligent transportation systems (ITSs) have become increasingly popular because they support effective coordination in connected vehicles. ITSs present an integrated approach for exchanging relevant information in order to improve the safety, efficiency, and reliability of road transportation systems. A variant of mobile ad-hoc networks (MANETs) called vehicular ad-hoc networks (VANETs) are an integral component of ITSs. VANETs consist of interconnected vehicles with sensing abilities that exchange information related to traffic, positioning, weather, and emergency services. In general, vehicle-to-everything (V2X) refers to communications between any entity and a vehicle, where the entity may be a vehicle, a cloud-based network, a pedestrian, or equipment installed along a road. One of the crucial challenges in V2X is the reliable and timely circulation of information among vehicular nodes to allow drivers to make decisions that increase road safety. In this context, efficient V2X routing protocols play a key role in supporting reliability and safety, and enhancing the overall quality of service (QoS) in VANETs. However, VANETs have distinct characteristics, such as high vehicular node mobility, unsteady connectivity, rapid changes in network topology, and unbounded network size, that can significantly affect routing in the network. Various routing protocols for V2X communication exist in the open technical literature. In this survey, we categorize the routing mechanisms as non-learning-and learning-based approaches, and discuss existing V2X routing protocols and their contributions to and impacts on VANET performance. Here, the learning-based approach implies the use of machine learning algorithms. This survey also summarizes open challenges in designing effective V2X routing protocols and future research directions to consider when developing smart routing mechanisms for next-generation intelligent VANET technologies.INDEX TERMS VANET, V2X, routing protocol, non-learning-based routing, learning-based routing.

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“…Compared to LTE, the carrier frequency of the 5G mmWave allows for increased data rates while reducing the communication latency [8]. This inherent capacity offered by the 5G mmWave for both backhaul links (within multiple base stations) and access links (within the base station and end-users) can support the CV environment [9]- [12]. The coverage area of mmWave communication is limited; however, extending the coverage area through multihop cooperative relay networks can significantly enhance communication network performance [13].…”

Section: A Backgroundmentioning

confidence: 99%

Performance Evaluation of 5G Millimeter-Wave based Vehicular Communication for Connected Vehicles

Khan¹,

Khan²,

Chowdhury³

et al. 2021

Preprint

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Due to the gradual increase in the volume of data generated by connected vehicles (CV), future vehicle-to-infrastructure (V2I) applications will require a communication medium that offers high-speed (high bandwidth) while maintaining reliability in high-mobility traffic scenarios. The 5G millimeter-wave (mmWave) can solve the communication issues related to V2I applications. However, the performance of the 5G mmWave for vehicular communication in high-mobility urban traffic scenarios is yet to be evaluated. This study presents a case study on assessing the performance of the 5G mmWave based vehicular communication in such traffic scenarios. We have designed three realistic use cases for performance evaluation based on three challenges: increased CV penetration level, dynamic mobility, and V2I application specifications, such as data rate and packet size. Then, we have created a simulation-based experimental setup using a microscopic traffic simulator (SUMO) and a communication network simulator (ns-3) to simulate the use cases. We have used delay, packet loss, throughput, and signal-to-interference-plus-noise ratio (SINR) as the communication performance evaluation metrics. Our analyses found that the CV penetration level is the primary determinant of the performance of the 5G mmWave. Moreover, once the data rate is increased by a factor of 40, delay and packet loss increase by factors of 6.8 and 2.8, respectively.

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Intelligent Vehicle Network Routing With Adaptive 3D Beam Alignment for mmWave 5G-Based V2X Communications

Cited by 58 publications

References 41 publications

On 5G-V2X Use Cases and Enabling Technologies: A Comprehensive Survey

On 5G-V2X Use Cases and Enabling Technologies: A Comprehensive Survey

A Survey of VANET/V2X Routing From the Perspective of Non-Learning- and Learning-Based Approaches

Performance Evaluation of 5G Millimeter-Wave based Vehicular Communication for Connected Vehicles

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