Advancing C-V2X for Level 5 Autonomous Driving from the Perspective of 3GPP Standards
Abstract
:1. Introduction
Case of Interest of This Paper
- 3GPP standardizes for a large set of use-case scenarios when it comes to supporting vehicular communication (in general) and C-V2X in particular. One major contribution of this work is to conduct extensive analyses of the 3GPP C-V2X standards, which are compiled in a way to guide better the readers, research community, and industry.
- The 3GPP standard documents provide various key issues and their potential solutions, which will help in realizing the true potential of a higher level of C-V2X communication. A literature survey shows that there is a clear lack of resources that present most (if not all) key issues, assumptions, and solutions. Hence, in this article, we elaborate on all of these and present easy-to-comprehend content by discussing these together and their roles in achieving the L-5 AD. We believe this will equip the readers and researchers in a way allowing them to study the right potential solutions for the challenges of their interest. This will assist in evolving the research work leading towards achieving the solutions of higher autonomy levels.
- 3GPP is a large body of various strong partners and there exists a large amount of support for different categories of V2X communication. Therefore, we performed an exhaustive study of 3GPP standard documents and presented a categorization of the documentation about V2X services.
- The available standard documents tend to introduce ignorance of the readers. Therefore, we provide an easy-to-follow discussion for the readers about use cases, challenges, communication requirements, and potential solutions. This simplified version of the discussion aims to build readers’ involvement by making their interest in 3GPP standardization.
- The work provided by 3GPP for standardized V2X communication is complex to understand and therefore, we provide a simplified structure of 3GPP documentation and technological standards of intelligent transportation systems (ITS) services to achieve L-5 AD.
- The current standpoint of 3GPP standardization for V2X services places little or no emphasis on the intelligence part in vehicular communication. In this regard, we highlighted the missing gaps for introducing intelligence in the execution of different network operations for enabling the use-case scenarios.
2. Background
2.1. Cellular-V2X for Autonomous Driving
2.2. Modes of C-V2X Communications
- Device-to-Device Mode: This mode of C-V2X communication deals with enabling the communication bit-pipes between vehicles (V2V), pedestrians (V2P), and infrastructures (V2I). Hence, the vehicular communication types i.e., V2V, V2P, and V2I are realized by device-to-device mode furthering the direct communication between devices (vehicles, pedestrians, and infrastructures are considered as devices) [9].
- Device-to-Network Mode: This mode of C-V2X communication enables the communication of bit-pipes between devices and network elements/entities. V2N is realized by this mode of C-V2X implementation. Hence, the end-user (driver) is able to achieve the advantages of network and cloud services. The V2N plays an essential role in completing the picture of an end-to-end solution for various verticals based on C-V2X communications.
2.3. An Overview of 3GPP Releases
3. Taxonomy of C-V2X Related 3GPP Standard Documents
- Categorize the standard documents following the natural evolution path of communication technologies,
- Evolution of technical specifications showcasing the dependency among specification documents,
- Decompose the services on the system and network segments including core and access network,
- Map the standard documents to the aforementioned system and network segments.
4. 4G and NSA-Based 5G V2X Services
4.1. System Support
4.1.1. Enhancements Support
4.1.2. Architectural Enhancements Support
4.1.3. Application Layer Support
4.1.4. Security Aspects Support
4.1.5. Media Handling and Interaction Support
4.2. Network Support
4.2.1. Core Network
V2X Control Function Support
V2X Application Enabler (VAE) Support
4.2.2. Access Network
Band Combinations Support for 4G & 5G Band
RAN Aspects Support for the 4G & 5G V2X
5. SA-Based 5G V2X Services
5.1. System Support
5.1.1. Enhancements Support
5.1.2. Architectural Enhancements Support
5.1.3. Application Layer Support
5.2. Network Support
5.2.1. Core Network
5G System Support
UE Policies in 5GS
5.2.2. Access Network
New Radio Support
UE Radio Transmission and Reception Support
6. Network Data Analytics Function (NWDAF)
- Support data collection from network functions (NFs) and analytical functions (AFs),
- Support analytics information provisioning to NFs and AFs,
- Support machine learning (ML) model training and provisioning to NWDAFs (containing analytics logical function).
- Slice load level information,
- Network slice instance load level information,
- Service experience,
- Network Function (NF) load,
- Network performance,
- Abnormal behavior,
- UE mobility and UE communication,
- User data congestion, and
- QoS sustainability.
6.1. NWDAF and Federated Learning
6.2. Challenges of Federated Learning
6.2.1. Heterogeneous Characteristics of Clients
6.2.2. Achieving Reliable and Dynamically Configurable Communication Bit-Pipes
- The term is the function of network state and the offered bandwidth . The collection n is the vector that represents the total number of users who request the service of a specific class.
- is the weighted multiplicative approach for bandwidth-dependent associated QoE attributes, i.e. delay, packet loss, etc.
- is the weighted sum of different independent QoE attributes.
6.2.3. Varying Client Sets
6.2.4. Statistical Heterogeneity
6.2.5. Privacy Concerns and Data Labeling
6.2.6. Model Convergence Time
6.2.7. Personalization
6.2.8. Incentivization
7. Future Directions
8. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
AD | Autonomous Driving |
AV | Autonomous Vehicles |
3GPP | 3rd Generation Partnership Project |
OEM | Original Equipment Manufacturers |
4G | 4th-generation |
5G | 5th-generation |
V2X | Vehicle to Everything |
C-V2X | Cellular-V2X |
LTE-V2X | long-term-evolution-V2X |
V2V | Vehicle to Vehicle |
V2P | Vehicle to Pedestrian |
V2N | Vehicle to Network |
V2I | Vehicle to Infrastructure |
ITS | Intelligent Transportation Systems |
CAV | Connected and Automated Vehicles |
DSRC | Dedicated Short Range Communication |
Rel-14 | Release 14 |
eV2X | Enhanced-V2X |
aV2X | advanced V2X |
5GS | 5G System |
5GC | 5G Core |
NR | New Radio |
TR | Technical Report |
TS | Technical Specification |
NWDAF | Network Data Analytics Function |
NF | Network Function |
FL | Federated Learning |
MLOps | Machine Learning Operations |
References
- Harounabadi, M.; Soleymani, D.M.; Bhadauria, S.; Leyh, M.; Roth-Mandutz, E. V2X in 3GPP Standardization: NR Sidelink in Release-16 and Beyond. IEEE Commun. Stand. Mag. 2021, 5, 12–21. [Google Scholar] [CrossRef]
- Liu, Z.; Liang, T.; Guo, J.; Zhang, L. Priority-based access for dsrc and 802.11 p vehicular safety communication. In Proceedings of the 2012 International Conference on Connected Vehicles and Expo (ICCVE), IEEE, Beijing, China, 12–16 December 2012; pp. 103–107. [Google Scholar]
- Petrov, T.; Sevcik, L.; Pocta, P.; Dado, M. A performance benchmark for dedicated short-range communications and lte-based cellular-v2x in the context of vehicle-to-infrastructure communication and urban scenarios. Sensors 2021, 21, 5095. [Google Scholar] [CrossRef] [PubMed]
- Malik, S.; Khan, M.A.; El-Sayed, H. Collaborative Autonomous Driving—A Survey of Solution Approaches and Future Challenges. Sensors 2021, 21, 3783. [Google Scholar] [CrossRef] [PubMed]
- Khan, M.A.; Sayed, H.E.; Malik, S.; Zia, T.; Khan, J.; Alkaabi, N.; Ignatious, H. Level-5 Autonomous Driving—Are We There Yet? A Review of Research Literature. ACM Comput. Surv. (CSUR) 2022, 55, 1–38. [Google Scholar] [CrossRef]
- Kim, H.; Kim, T. Vehicle-to-vehicle (V2V) message content plausibility check for platoons through low-power beaconing. Sensors 2019, 19, 5493. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Khan, M.A.; El Sayed, H.; Malik, S.; Zia, M.T.; Alkaabi, N.; Khan, J. A Journey towards Fully Autonomous Driving-Fueled by a Smart Communication System. Veh. Commun. 2022, 36, 100476. [Google Scholar] [CrossRef]
- C-V2X Enabling Intelligent Transport. Available online: https://www.gsma.com/iot/wp-content/uploads/2017/12/C-2VX-Enabling-Intelligent-Transport_2.pdf (accessed on 27 November 2022).
- Ali, Z.; Lagén, S.; Giupponi, L.; Rouil, R. 3GPP NR V2X mode 2: Overview, models and system-level evaluation. IEEE Access 2021, 9, 89554–89579. [Google Scholar] [CrossRef]
- Intelligent Transport Systems. Available online: https://www.3gpp.org/news-events/partner-news/intelligent-transport-systems (accessed on 27 November 2022).
- 3GPP—Specifications & Technologies—Release 14. Available online: https://www.3gpp.org/specifications-technologies/releases/release-14 (accessed on 27 November 2022).
- The start of 5G standardization—Ericsson. Available online: https://www.ericsson.com/en/blog/2015/6/release-14–the-start-of-5g-standardization (accessed on 27 November 2022).
- Garcia-Roger, D.; González, E.E.; Martín-Sacristán, D.; Monserrat, J.F. V2X support in 3GPP specifications: From 4G to 5G and beyond. IEEE Access 2020, 8, 190946–190963. [Google Scholar] [CrossRef]
- 3GPP—Specifications & Technologies—Release 16. Available online: https://www.3gpp.org/specifications-technologies/releases/release-16 (accessed on 27 November 2022).
- 3GPP—Specifications & Technologies—Release 17. Available online: https://www.3gpp.org/specifications-technologies/releases/release-17 (accessed on 27 November 2022).
- 3GPP—Specifications & Technologies—Release 18. Available online: https://www.3gpp.org/specifications-technologies/releases/release-18 (accessed on 27 November 2022).
- Khan, M.J.; Khan, M.A.; Beg, A.; Malik, S.; El-Sayed, H. An overview of the 3GPP identified Use Cases for V2X Services. Procedia Comput. Sci. 2022, 198, 750–756. [Google Scholar] [CrossRef]
- TSG Radio Access Network (RAN); 3GPP. Available online: https://www.3gpp.org/3gpp-groups/radio-access-networks-ran (accessed on 27 November 2022).
- TSG Core Network and Terminals (CT); 3GGP. Available online: https://www.3gpp.org/3gpp-groups/core-network-terminals-ct (accessed on 27 November 2022).
- Hakeem, S.A.A.; Kim, H. Multi-zone authentication and privacy-preserving protocol (MAPP) based on the bilinear pairing cryptography for 5G-V2X. Sensors 2021, 21, 665. [Google Scholar] [CrossRef] [PubMed]
- Study on NR Vehicle-to-Everything (V2X)—Technical Specification # 38.885. Available online: https://portal.3gpp.org/desktopmodules/Specifications/SpecificationDetails.aspx?specificationId=3497 (accessed on 27 November 2022).
- 3GPP—Specifications & Technologie—Release 15. Available online: https://www.3gpp.org/specifications-technologies/releases/release-15 (accessed on 27 November 2022).
- Architecture Enhancements for 5G System (5GS) to Support Network Data Analytics Services—Technical Specification # 23.288. Available online: https://portal.3gpp.org/desktopmodules/Specifications/SpecificationDetails.aspx?specificationId=3579 (accessed on 27 November 2022).
- 5G System; Network Data Analytics Services; Stage 3—Technical Specification # 29.520. Available online: https://portal.3gpp.org/desktopmodules/Specifications/SpecificationDetails.aspx?specificationId=3355 (accessed on 27 November 2022).
- Study of Enablers for Network Automation for 5G—Technical Specification # 23.791. Available online: https://portal.3gpp.org/desktopmodules/Specifications/SpecificationDetails.aspx?specificationId=3252 (accessed on 27 November 2022).
- Tran, N.H.; Bao, W.; Zomaya, A.; Nguyen, M.N.; Hong, C.S. CFederated learning over wireless networks: Optimization model design and analysis. In Proceedings of the IEEE INFOCOM 2019-IEEE Conference on Computer Communications, Paris, France, 28 April–2 May 2019. [Google Scholar]
- Smith, V.; Forte, S.; Chenxin, M.; Takáč, M.; Jordan, M.I.; Jaggi, M. Cocoa: A general framework for communication-efficient distributed optimization. J. Mach. Learn. Res. 2018, 18, 230. [Google Scholar]
- Smith, V.; Chiang, C.K.; Sanjabi, M.; Talwalkar, A. Federated Multi-Task Learning. In Advances in Neural Information Processing Systems; Guyon, I., Luxburg, U.V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S., Garnett, R., Eds.; Curran Associates, Inc.: Red Hook, NY, USA, 2017. [Google Scholar]
- Kim, T.; Kim, J.; Ko, H.; Seo, S.; Jcon, Y.; Jeong, H.; Lee, S.; Pack, S. An Implementation Study of Network Data Analytic Function in 5G. In Proceedings of the 2022 IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, US, 7–9 January 2022; pp. 1–3. [Google Scholar] [CrossRef]
- Jeon, Y.; Jeong, H.; Seo, S.; Kim, T.; Ko, H.; Pack, S. A Distributed NWDAF Architecture for Federated Learning in 5G. In Proceedings of the 2022 IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, US, 7–9 January 2022; pp. 1–2. [Google Scholar] [CrossRef]
- Abbas, K.; Khan, T.A.; Afaq, M.; Diaz Rivera, J.J.; Song, W.C. Network Data Analytics Function for IBN-based Network Slice Lifecycle Management. In Proceedings of the 2021 22nd Asia-Pacific Network Operations and Management Symposium (APNOMS), Tainan, Taiwan, 8–10 September 2021; pp. 148–153. [Google Scholar]
- Sevgican, S.; Turan, M.; Gökarslan, K.; Yilmaz, H.B.; Tugcu, T. Intelligent network data analytics function in 5G cellular networks using machine learning. J. Commun. Netw. 2020, 22, 269–280. [Google Scholar] [CrossRef]
- Kweon, K.; Gutierrez-Estevez, D.; Pujol-Roig, J.; Jeong, S. Automated Multi-service 5G Session Timer via AI-based Network Data Analytics Function. In Proceedings of the 2020 IEEE Globecom Workshops (GC Wkshps, Taipei, Taiwan, 7–11 December 2020; pp. 1–6. [Google Scholar] [CrossRef]
- Khan, M.A.; Alkaabi, N. Rebirth of Distributed AI—A Review of eHealth Research. Sensors 2021, 21, 4999. [Google Scholar] [CrossRef] [PubMed]
- Khan, M.A.; Tembine, H.; Sivrikaya, F.; Albayrak, S.; Konz, B.U. User QoE influenced spectrum trade, resource allocation, and network selection. Int. J. Wirel. Inf. Netw. 2011, 18, 193–209. [Google Scholar] [CrossRef]
- Khan, M.A.; Toseef, U. User utility function as quality of experience (QoE). In Proceedings of the ICN 2011: The Tenth International Conference on Networks, St. Maarten, The Netherlands, 23–28 January 2011; Citeseer, 2011; Volume 11, pp. 99–104. [Google Scholar]
- Khan, M.A. A Technical and Economic Framework for End-to-End Realization of the User-Centric Telecommunication Paradigm. Ph.D. Thesis, Berlin Institute of Technology, Berling, Germany, 2011. [Google Scholar]
- Khan, M.A.; Tembine, H.; Vasilakos, A.V. Game Dynamics and Cost of Learning in Heterogeneous 4G Networks. IEEE J. Sel. Areas Commun. 2012, 30, 198–213. [Google Scholar] [CrossRef]
Technology Categorization | Document ID | Topic | Release-14 | Release-15 | Release-16 | Release-17 | ||||
---|---|---|---|---|---|---|---|---|---|---|
Version | Year | Version | Year | Version | Year | Version | Year | |||
4G V2XServices | TS 22.185 | Requirements for V2X Services | 14.4.0 | 2018-06 | 15.0.0 | 2018-06 | 16.0.0 | 2020-07 | ||
TR 22.885 | LTE support for V2X Services | 14.0.0 | 2015-12 | |||||||
TS 23.285 | Architecture enhancements for V2X Services | 14.9.0 | 2019-12 | 15.4.0 | 2019-12 | 16.4.0 | 2020-09 | |||
TR 23.785 | Architecture enhancements for V2X Services | 14.0.0 | 2016-09 | |||||||
TR 23.795 | Application Layer for V2X Services | 16.1.0 | 2018-12 | |||||||
TS 24.385 | Management Object (MO) for V2X Services | 14.4.0 | 2018-09 | 15.1.0 | 2018-09 | 16.2.0 | 2020-09 | |||
TS 24.386 | Protocol Aspects for UE to V2X Control Function | 14.5.0 | 2020-06 | 15.3.0 | 2020-06 | 16.2.0 | 2020-12 | |||
TS 24.486 | Protocol Aspects for V2X Application Enabler (VAE) Layer | 16.3.0 | 2021-03 | |||||||
TS 29.387 | V2X Control Function to V2X AS Aspects | 0.1.0 | 2016-11 | |||||||
TS 29.388 | V2X Control Function to HSS Aspects | 14.2.0 | 2019-09 | 15.1.0 | 2019-09 | 16.0.0 | 2020-06 | |||
TS 29.389 | Inter-V2X Control Function Signalling Aspects | 14.2.0 | 2019-09 | 15.1.0 | 2019-09 | 16.0.0 | 2020-06 | |||
TR 33.885 | Security Aspects V2X Services | 14.1.0 | 2017-09 | |||||||
TR 36.786 | UE Radio Transmission and Reception for V2X | 14.0.0 | 2017-03 | |||||||
TR 36.787 | New Band Combinations for V2X | 15.0.0 | 2018-07 | |||||||
TR 36.788 | UE Radio Transmission and Reception for V2X | 15.0.0 | 2018-07 | |||||||
TR 36.885 | LTE-based V2X Services | 14.0.0 | 2016-07 | |||||||
4G & NSA-based 5G V2X Services | TR 22.886 | Enhancement of V2X Services for 5G | 15.3.0 | 2018-09 | 16.2.0 | 2018-12 | ||||
TS 23.286 | Functional Architecture and Information Flows for V2X Services | 16.5.0 | 2020-12 | 17.1.0 | 2021-04 | |||||
TR 23.764 | Enhancements to Application Layer for V2X Services | 17.1.0 | 2020-12 | |||||||
TR 23.776 | Architecture Enhancements for aV2X Services | 17.0.0 | 2021-03 | |||||||
TR 23.786 | Architecture Enhancements of aV2X Services for the EPS and 5GS | 16.1.0 | 2019-06 | |||||||
TR 26.985 | Media Handling and Interaction for V2X | 0.2.1 | 2018-01 | 16.0.0 | 2019-12 | |||||
TS 29.486 | V2X Application Enabler (VAE) Services | 16.3.0 | 2021-03 | 17.0.0 | 2021-03 | |||||
TS 33.185 | Security Aspect for V2X Services | 14.1.0 | 2017-09 | 15.0.0 | 2018-06 | 16.0.0 | 2020-07 | |||
TS 33.536 | Security Aspects aV2X Services | 16.3.0 | 2021-03 | |||||||
TS 33.836 | Security Aspects aV2X Services | 16.1.0 | 2020-09 | |||||||
TR 37.875 | Band Combinations for Uu and V2X con-current Operation | 0.4.0 | 2021-06 | |||||||
TR 37.985 | RAN Aspects for V2X based on LTE and NR | 16.0.0 | 2020-07 | |||||||
SA-based 5GV2X Services | TS 23.287 | Architecture Enhancements of V2X Services for 5GS | 16.5.0 | 2020-12 | ||||||
TS 24.587 | V2X Services in 5GS | 16.4.0 | 2021-03 | 17.1.0 | 2021-03 | |||||
TS 24.588 | UE Policies for V2X Services in 5GS | 16.4.0 | 2021-03 | |||||||
TR 38.885 | NR-based V2X | 16.0.0 | 2019-03 | |||||||
TR 38.886 | UE Radio Transmission and Reception for NR-based V2X | 16.3.0 | 2021-04 | |||||||
V2X Scenarios and Use Cases | TS 22.186 | Enhancement for V2X Scenarios | 15.4.0 | 2018-09 | 16.2.0 | 2019-06 | ||||
TR 37.885 | Evaluation Methodology of new V2X Use Cases for LTE and NR | 15.3.0 | 2019-06 |
5G Use Cases | Performance Requirements | ||||||||
---|---|---|---|---|---|---|---|---|---|
Degree of Automation | Payload (Bytes) | Tx Rate (message/sec) | E2E Latency (ms) | Reliability | Data Rate (Mbps) | Comm. Range (m) | |||
General Requirements | 50–6000 | 30 | 10–500 | 90–99.99 | 50–65 | 80–350 | |||
Platooning | Scenario Specific | Vehicular Platoon drives cooperatively and exchanges information between groups of UEs supporting V2X services. | Lowest | 300–400 | 30 | 25 | 90 | - | - |
Low | 6500 | 50 | 20 | - | - | 350 | |||
High | - | - | 20 | - | 65 | 180 | |||
Highest | 50–1200 | 30 | 10 | 99.99 | - | 80 | |||
Reporting needed for platooning between UEs supporting V2X application and between a UE supporting V2X application and RSU. | - | 50–1200 | 2 | 500 | - | - | - | ||
To share information for platooning between a UE supporting V2X application and RSU. | Lower | 600 | 50 | 20 | - | - | 350 | ||
Higher | - | - | 20 | - | 50 | 180 | |||
General Requirements | 1600 | - | 3–100 | 90–99.999 | 10–1000 | 50–1000 | |||
Extended Sensors | Scenario Specific | Sensor information sharing between UEs supporting V2X application | Lower | 1600 | 10 | 100 | 99 | - | 1000 |
Higher | - | - | 10 | 99.99 | 25 | 500 | |||
Video sharing between UEs supporting V2X application | Lower | - | - | 50 | 90 | 10 | 100 | ||
Higher | - | - | 10 | 99.99 | 90 | 400 | |||
General Requirements | - | - | 5 | 99.99 | UL: 25 DL: 1 | - | |||
Remote Driving | Scenario Specific | To exchnage information between a UE supporting V2X application and a V2X Application Server | - | - | 5 | 99.99 | UL: 25 DL: 1 | - | |
Advanced Driving | General Requirements | 2000–12,000 | 100 | 3–10 | 99.99 | 30–53 | 500 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Khan, M.J.; Khan, M.A.; Malik, S.; Kulkarni, P.; Alkaabi, N.; Ullah, O.; El-Sayed, H.; Ahmed, A.; Turaev, S. Advancing C-V2X for Level 5 Autonomous Driving from the Perspective of 3GPP Standards. Sensors 2023, 23, 2261. https://doi.org/10.3390/s23042261
Khan MJ, Khan MA, Malik S, Kulkarni P, Alkaabi N, Ullah O, El-Sayed H, Ahmed A, Turaev S. Advancing C-V2X for Level 5 Autonomous Driving from the Perspective of 3GPP Standards. Sensors. 2023; 23(4):2261. https://doi.org/10.3390/s23042261
Chicago/Turabian StyleKhan, Muhammad Jalal, Manzoor Ahmed Khan, Sumbal Malik, Parag Kulkarni, Najla Alkaabi, Obaid Ullah, Hesham El-Sayed, Amir Ahmed, and Sherzod Turaev. 2023. "Advancing C-V2X for Level 5 Autonomous Driving from the Perspective of 3GPP Standards" Sensors 23, no. 4: 2261. https://doi.org/10.3390/s23042261
APA StyleKhan, M. J., Khan, M. A., Malik, S., Kulkarni, P., Alkaabi, N., Ullah, O., El-Sayed, H., Ahmed, A., & Turaev, S. (2023). Advancing C-V2X for Level 5 Autonomous Driving from the Perspective of 3GPP Standards. Sensors, 23(4), 2261. https://doi.org/10.3390/s23042261