5G New Radio for Automotive, Rail, and Air Transport

Fodor, Gábor; Vinogradova, Julia; Hammarberg, Peter; Nagalapur, Keerthi Kumar; Qi, Zhiqiang Tyler; Do, Hieu; Blasco, Ricardo; Baig, Mirza Uzair

doi:10.1109/mcom.001.2001106

Cited by 24 publications

(10 citation statements)

References 17 publications

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“…For example, in [10], the authors present three novel Cooperated, Connected, and Automated Mobility (CCAM) use cases in a cross-border setting, running on top of the 5G communication infrastructures connecting three neighbouring cities. Apart from illustrative examples of the envisaged applications, a suitable set of metrics, target requirements, and KPIs has also been investigated, along with the enabling technologies needed for meeting these more stringent conditions [8][9][10][11][12]. As a representative example, an Artificial Intelligence (AI)-driven automated 5G end-to-end slicing solution for supporting multiple vertical services is introduced in [13].…”

Section: Related Workmentioning

confidence: 99%

Design, Development, and Evaluation of 5G-Enabled Vehicular Services: The 5G-HEART Perspective

Kakkavas

Diamanti

Stamou

et al. 2022

Sensors

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The ongoing transition towards 5G technology expedites the emergence of a variety of mobile applications that pertain to different vertical industries. Delivering on the key commitment of 5G, these diverse service streams, along with their distinct requirements, should be facilitated under the same unified network infrastructure. Consequently, in order to unleash the benefits brought by 5G technology, a holistic approach towards the requirement analysis and the design, development, and evaluation of multiple concurrent vertical services should be followed. In this paper, we focus on the Transport vertical industry, and we study four novel vehicular service categories, each one consisting of one or more related specific scenarios, within the framework of the “5G Health, Aquaculture and Transport (5G-HEART)” 5G PPP ICT-19 (Phase 3) project. In contrast to the majority of the literature, we provide a holistic overview of the overall life-cycle management required for the realization of the examined vehicular use cases. This comprises the definition and analysis of the network Key Performance Indicators (KPIs) resulting from high-level user requirements and their interpretation in terms of the underlying network infrastructure tasked with meeting their conflicting or converging needs. Our approach is complemented by the experimental investigation of the real unified 5G pilot’s characteristics that enable the delivery of the considered vehicular services and the initial trialling results that verify the effectiveness and feasibility of the presented theoretical analysis.

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Section: Related Workmentioning

confidence: 99%

Design, Development, and Evaluation of 5G-Enabled Vehicular Services: The 5G-HEART Perspective

Kakkavas

Diamanti

Stamou

et al. 2022

Sensors

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“…In release 17, different QCL enhancements were studied to better support advanced channel estimation schemes that can be implemented at the train. QCL enhancements were investigated to evaluate the need for TRP-side pre-compensation algorithms [44].…”

Section: ) Cjt-compmentioning

confidence: 99%

Physical Layer Enhancement for Next-Generation Railway Communication Systems

Sibel

Berbineau

et al. 2022

IEEE Access

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This paper presents an overview of the challenges and state-of-the-art physical layer enhancement designs for next-generation railway communication, also known as high-speed train (HST) communication. The physical layer design for the HST should adapt from its counterpart in the generalpurpose network because of the harsh propagation environment and extreme conditions, stringent latency and reliability requirements of dedicated railway applications, and frequency band scarcity caused by regulation. In this survey, we examine how conventional multiple-input-multiple-output (MIMO) family techniques such as beamforming, multi-cell MIMO, and relays can enhance the physical layer performance for HST. Physical layer enhancement assisted by novel reconfigurable intelligent surface (RIS) technology was also analyzed from different perspectives. Dedicated control channels, reference signals, waveforms, and numerology designs for train-to-infrastructure (T2I) and train-to-train (T2T) communication in sidelinks are also reviewed. Finally, a brief introduction to artificial intelligence (AI)/machine learning (ML)-aided HST physical layer design is provided. Several promising research avenues have also been suggested.

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“…Experimental results show that the algorithm can significantly reduce the average task execution delay. An efficient lightweight offloading scheme is proposed for the multi-user edge system [10].…”

Section: Related Workmentioning

confidence: 99%

Telematics Collaborative Resource Allocation Algorithm Based on Cloud Sidecar

Zhang

Shao

Liu

et al. 2022

Security and Communication Networks

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This paper provides an in-depth study and analysis of a distributed allocation algorithm for collaborative resources for cloud-edge-vehicle-based Telematics. The approach starts from the emerging application of urban environmental monitoring based on vehicular networking, with an integrated design of data sensing detection and transmission, and collaborative monitoring of vehicle swarm intelligence based on urban air quality collection to avoid redundancy of information and communication overload. A hybrid routing method with minimal delay for reliable data transmission is proposed. The power adjustment algorithm divides the channel into 3 states. When the CBR is less than 0.5, the channel is in an idle state, and when the CBR is greater than 0.5 and less than 0.8, the channel is in an active state. The algorithm designs redundancy strategies based on coding mechanisms to improve the reliability of data transmission, combines coding mechanisms with routing design, incorporates routing switching ideas, and performs probability-based routing decisions to minimize the delay. In straight-line road sections, a fuzzy logic prediction-based vehicle adaptive connectivity clustering routing algorithm is proposed to reduce the communication overhead during vehicle collaboration and ensure high network connectivity; at intersections, a probability-based minimum delay routing decision algorithm is proposed to reduce the information transmission delay. Experiments show that the proposed method effectively improves the efficiency of data-aware collection and transmission, and increases the reliability of transmission. With the explosive growth of video services, the problem of intelligent transmission of DASH-based video streams has become another research hotspot in mobile edge networks. Based on the edge container cloud architecture of vehicular networking, the resource constraints of microservices when deployed in the edge cloud platform were analyzed, and a multi-objective optimization model for microservice resource scheduling was established with the comprehensive performance objectives of shortest microservice invocation distance, highest resource utilization of physical machine clusters, and ensuring load balancing as much as possible.

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5G New Radio for Automotive, Rail, and Air Transport

Cited by 24 publications

References 17 publications

Design, Development, and Evaluation of 5G-Enabled Vehicular Services: The 5G-HEART Perspective

Design, Development, and Evaluation of 5G-Enabled Vehicular Services: The 5G-HEART Perspective

Physical Layer Enhancement for Next-Generation Railway Communication Systems

Telematics Collaborative Resource Allocation Algorithm Based on Cloud Sidecar

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