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6G Cellular Networks and Connected Autonomous Vehicles
Jianhua He, Kun Yang, Hsiao-Hwa Chen
TL;DR
The paper considers how the evolution of 6G and connected autonomous vehicles intersects, given CAVs’ demanding connectivity needs. It surveys V2X-to-CAV and 6G technologies, then discusses 6G support for CAVs and CAV support for 6G. It concludes that joint design may be an effective way forward.
Problem
CAV connectivity demands such as 99.999% reliability, 0.1 ms radio latency, and high throughput challenge current LTE C-V2X and 5G NR V2X technologies.
Source: §I · p. 2Method
The paper reviews V2X-to-CAV and 6G technology evolution, then discusses reciprocal research directions for applying 6G to CAVs and CAVs to 6G.
Source: §V · p. 7Results
The discussion describes how 6G enablers could support CAV mission-critical services and how CAVs could contribute to more effective 6G deployment and operation.
Source: §V · p. 7Takeaways & Limitations
The paper suggests joint design of CAV and 6G systems may be an effective way forward.
Source: §V · p. 7
Abstract
from arXiv · showhide
With 5G mobile communication systems been commercially rolled out, research discussions on next generation mobile systems, i.e., 6G, have started. On the other hand, vehicular technologies are also evolving rapidly, from connected vehicles as coined by V2X (vehicle to everything) to autonomous vehicles to the combination of the two, i.e., the networks of connected autonomous vehicles (CAV). How fast the evolution of these two areas will go head-in-head is of great importance, which is the focus of this paper. Based on a brief overview on the technological evolution of V2X to CAV and 6G key technologies, this paper explores two complementary research directions, namely, 6G for CAVs versus CAVs for 6G. The former investigates how various 6G key enablers, such as THz, cell free communication and artificial intelligence (AI), can be utilized to provide CAV mission-critical services. The latter discusses how CAVs can facilitate effective deployment and operation of 6G systems. This paper attempts to investigate the interactions between the two technologies to spark more research efforts in these areas.
I. INTRODUCTION
The introduction frames 6G and connected autonomous vehicles (CAVs) as evolving together: 6G could support CAV mission-critical services, while CAV infrastructure could aid 6G deployment and operation. It presents these reciprocal directions as a research agenda.
I. INTRODUCTION
- CAVs combine connected and autonomous vehicles and can extend toward cooperative applications such as platooning, smart intersections, and cooperative perception.The paper identifies road safety, efficiency, fuel consumption, and congestion as potential application benefits.Source: §I · p. 1
- CAV connectivity must meet 99.999% reliability, 0.1 ms radio latency, massive instant access, and high throughput, exceeding current LTE C-V2X and 5G NR V2X capabilities.The paper says these demands call for new communication technologies.Source: §I · p. 2
- 6G’s THz bands, sensing and positioning, and embedded intelligence could combine communications, computation, positioning, and sensing (CCPS) for CAV missions.The paper argues that jointly designing these functions may benefit all four CCPS functions, which are also essential to CAVs.Source: §I · pp. 1–2
- CAVs could support 6G service provisioning and operation through smart roads, roadside units, and vehicles offering resources, physical space, and services.The paper points to controlled mobility and ease of deployment as useful CAV features.Source: §I · p. 2
- The paper brings 6G and CAVs together for discussion, aiming to identify potential research directions for applying 6G to CAVs and vice versa, beyond ongoing 5G NR V2X and IEEE 802.11bd research.With expected tremendous investments in both infrastructures, they could be jointly designed, planned, and operated to achieve much better reuse of system resources and services.Source: §I · p. 2
A. Evolution of V2X
V2X developed from vehicular wireless communication technologies into cellular-based options, while standards work continued across 3GPP and IEEE. The paper describes differing scheduling and backward-compatibility choices along that evolution.
A. Evolution of V2X
- V2X encompasses vehicle-to-vehicle, infrastructure, pedestrian, and network communication, with DSRC in the 5.9 GHz band and IEEE 802.11p among its early technologies.The passage identifies DSRC as supporting intelligent transportation applications such as toll collection and vehicle safety.Source: A. Evolution of V2X · p. 2
- The V2X roadmap depicts Release 17 as planned, with completion expected in 2021–2022.The text describes further sidelink-efficiency, URLLC, positioning, relay, and FR2 enhancements as planned.Source: Figure 2 · p. 3, A. Evolution of V2X · p. 3
- IEEE 802.11p’s random channel access is associated with no QoS guarantee, unbounded physical-channel delay, short-lived vehicle-infrastructure connectivity, and large infrastructure deployment needs.3GPP proposed cellular-based C-V2X using existing cellular infrastructure to overcome these limitations.Source: A. Evolution of V2X · p. 3
- Release 14 specified V2X over the PC5 sidelink; centralized scheduling offers high broadcast reliability but high signaling overhead, while distributed scheduling offers greater scalability.Release 15 added transmission diversity, carrier aggregation, and higher-order modulation; Release 16 added unicast, multicast, sensing, resource-selection, QoS, and congestion-control functions,.Source: A. Evolution of V2X · p. 3
- IEEE 802.11bd and 5G NR-V2X both target lower latency, higher throughput, and higher reliability, but differ in backward-compatibility design.802.11bd requires compatibility on the same physical channel; NR-V2X can communicate with LTE-V2X on a different channel.Source: A. Evolution of V2X · p. 3
B. Evolution to CAV
Autonomous-driving development spans basic assistance systems and conditional Level 4 robotic taxi services, while full Level 5 automation remains a goal. The paper presents connected vehicles as complementary to onboard autonomy’s limitations.
B. Evolution to CAV
- Robotic taxis offered in the United States and China can drive autonomously under certain conditions at SAE Level 4, while manufacturers and IT companies pursue Level 5 automation.The passage describes this progress as a development from basic advanced driving systems such as collision warning and automatic braking.Source: B. Evolution to CAV · p. 3
- Autonomous vehicles combine sensors with different strengths and weaknesses, including cameras’ poor-light and weather limitations and radar’s lower resolution and inability to identify object shape and height.Lidar is described as providing wide vision and accurate distance estimates, but having poor resolution and weather sensitivity.Source: B. Evolution to CAV · pp. 3–4
- Sensor fusion can improve sensing and safety, but remains limited by line of sight and declining detection with distance; connected vehicles complement these limits through cooperation.The paper identifies cooperative perception, cooperative driving, platooning, and remote driving as CAV applications.Source: B. Evolution to CAV · p. 4
III. 6G SUPPORT FOR CAV
A typical CAV system combines on-road vehicles, roadside units, smart roads, and a transport control center. The described roadside units and 6G-enabled functions support collaboration, mobility, and computing.
III. 6G SUPPORT FOR CAV
- A typical CAV system includes vehicles on roads, roadside units, smart roads, and a transport control center.Roadside units may be equipped with communication, computing, and traffic-control devices.Source: §III · p. 4
- Roadside units play a critical role in collaborative mobility and computing, while connected unmanned aerial vehicles may supplement on-road vehicles.The paper also regards connected UAVs as part of a CAV system.Source: §III · p. 4
- 6G functions such as communications, computation, positioning, and sensing can benefit CAV connectivity and computing, alongside existing 5G technologies.The cited existing technologies include mmWave, massive MIMO, network virtualization, and software-defined networks.Source: §III · p. 4
A. Key 6G Enabling Technologies
The section surveys candidate 6G enablers for CAVs, then explains how THz could support data-intensive applications and more precise positioning and sensing.
A. Key 6G Enabling Technologies
- THz, RIS, ISTN, AI, and distributed computing are identified as promising 6G technologies, with THz and cell-free networks among proposed roadmaps.The section positions these technologies as candidates for integration into CAV architecture.Source: A. Key 6G Enabling Technologies · pp. 4–5
B. THz for CAVs
- THz offers bandwidth up to 10s GHz for CAV links and supports applications including cooperative perception, mobile edge intelligence, and remote driving.Its short wavelengths also permit large antenna arrays and narrow beams for precision positioning and radio-frequency sensing.Source: B. THz for CAVs · p. 5
- THz positioning and sensing could address limitations of GPS in urban environments and high-definition maps that do not respond quickly to road changes.The passage describes THz localization as a low-cost, precise, and reliable alternative, while noting challenges in transceiver design, range, and high mobility.Source: B. THz for CAVs · p. 5
C. Grant Free and Non-orthogonal Multiple Access (NOMA)
NOMA is presented as a candidate for the dense, high-mobility conditions of CAV networks, with grant-free access and multiplexing as relevant applications.
C. Grant Free and Non-orthogonal Multiple Access (NOMA)
- NOMA lets multiple users share non-orthogonal resources for random access and multiplexing, and offers higher spectrum efficiency than orthogonal access.The passage describes power-, code-, and pattern-domain approaches and reports grant-free methods supporting massive connectivity with performance close to scheduled access.Source: C. Grant Free and Non-orthogonal… · p. 5
- NOMA could support CAVs under high vehicle density, mobility, long communication range, and heavy traffic through massive connectivity and spectrum efficiency.SCMA is described for resource reservation and packet transmission in 3GPP V2V protocols; practical grant-free schemes, especially for distributed V2V, remain challenging.Source: C. Grant Free and Non-orthogonal… · p. 5
D. Cell Free Communications
The section discusses cell-free communication for CAV mobility challenges and AI and edge intelligence for computing-intensive CAV applications.
D. Cell Free Communications
- Cell-free networks use cooperating access points and central processing without cell boundaries, allowing users to move seamlessly across heterogeneous networks.For CAVs, cooperative communication may avoid handover problems; coordinating transmissions under high vehicle mobility and managing radio resources remain challenges.Source: D. Cell Free Communications · p. 6
- Cell-free communication can integrate localization and sensing with cooperative communication to support CAV cooperative perception and positioning.The passage identifies high-mobility transmission coordination and central radio-resource management as technical challenges.Source: D. Cell Free Communications · p. 6
E. Artificial Intelligence (AI) and Edge Intelligence (EI)
- AI and mobile edge computing can process CAV sensor data, aggregate sensing outcomes, and return real-time driving decisions or hazard information.The passage also describes distributed AI and federated learning over 6G MEC for cooperative learning and model training while preserving user privacy.Source: E. Artificial Intelligence (AI) and… · p. 6
- 6G-supported remote driving, edge driving, and digital twins are described as advanced CAV use cases with diverse QoS needs.Remote driving uses human or machine drivers; edge driving uses machine drivers from nearby CAVs or edge stations, while digital twins collect sensor data and build predictive models.Source: E. Artificial Intelligence (AI) and… · p. 6, Figure 4 · p. 6
IV. CAV ENHANCEMENTS IN 6G NETWORKS
The envisioned 6G architecture combines core, space-access, edge-cloud, and edge-access components, with CAVs supporting network functions from edge and space access.
IV. CAV ENHANCEMENTS IN 6G NETWORKS
- The envisioned architecture includes a mobile core, satellite- and UAV-based space access, central and edge servers, and edge access connecting users and devices.CAV sensing is described as supporting mmWave and THz beam alignment and connection management.Source: §IV · p. 6
- CAV systems can enhance 6G networks from the edge and space-access aspects.The passage frames CAVs as supporting 6G communication, networking, computing, and management services.Source: §IV · pp. 6–7
A. Extension of 6G Communication Infrastructure
CAVs can extend 6G infrastructure through flexible, mostly stationary mobile base stations and vehicle edge computing. Their deployment can respond to network demand while supporting mobile users’ computing needs.
A. Extension of 6G Communication Infrastructure
- CAV mobile base stations can flexibly augment fixed 6G infrastructure, mainly while stationary and offloading only a small share of base-station traffic.They connect to base stations for wireless backhaul and can self-organize to adapt service locations and timing to changing demand.Source: A. Extension of 6G Communication… · p. 7
- Reusing CAVs as base stations can match vehicle availability to wireless demand, potentially improving utilization and reducing 6G operating costs.The paper gives nighttime as an example: road traffic is lower while wireless network traffic is higher.Source: A. Extension of 6G Communication… · p. 7
B. Mobile Vehicle Edge Computing
- Vehicle edge computing lets CAVs provide mobile computing services to other CAVs and mobile users as demand requires.CAV mobility and deployability make VEC a flexible enhancement to 6G mobile edge computing.Source: B. Mobile Vehicle Edge Computing · p. 7
C. Network Performance Monitoring and Sensing for 6G
CAVs and smart roads can support 6G network monitoring, automation, and sensing. The paper concludes that joint design of CAV systems and 6G networks may benefit both sectors.
C. Network Performance Monitoring and Sensing for 6G
- CAVs and smart-road sensors can provide real-time service-quality updates and infrastructure surveillance for 6G network automation.On demand, they can measure service quality, act as temporary base stations, and detect or repair problematic outdoor components.Source: C. Network Performance Monitoring and… · p. 7
V. CONCLUSIONS
- The paper proposes using 6G enablers, including THz, cell-free communications, and edge intelligence, for CAV mission-critical services, and CAVs for more effective 6G deployment and operation..Source: §V · p. 7
- Joint design from the early stages aims at an optimized integral system that benefits both sectors.Source: §V · pp. 7–8