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Socially Aware V2X Localized QoS (2401.17457v1)

Published 30 Jan 2024 in cs.NI and cs.SI

Abstract: Vehicle-to-everything (V2X) is a core 5G technology. V2X and its enabler, Device-to-Device (D2D), are essential for the Internet of Things (IoT) and the Internet of Vehicles (IoV). V2X enables vehicles to communicate with other vehicles (V2V), networks (V2N), and infrastructure (V2I). While V2X enables ubiquitous vehicular connectivity, the impact of bursty data on the network's overall Quality of Service (QoS), such as when a vehicle accident occurs, is often ignored. In this work, we study both 4G and 5G V2X utilizing Evolved Universal Terrestrial Radio Access New Radio (E-UTRA-NR) and propose the use of socially aware 5G NR Dual Connectivity (en-DC) for traffic differentiation. We also propose localized QoS, wherein high-priority QoS flows traverse 5G road side units (RSUs) and normal-priority QoS flows traverse 4G Base Station (BS). We formulate a max-min fair QoS-aware Non-Orthogonal Multiple Access (NOMA) resource allocation scheme, QoS reclassify. QoS reclassify enables localized QoS and traffic steering to mitigate bursty network traffic's impact on the network's overall QoS. We then solve QoS reclassify via Integer Linear Programming (ILP) and derive its approximation. We demonstrate that both optimal and approximation QoS reclassify resource allocation schemes in our socially aware QoS management methodology outperform socially unaware legacy 4G V2X algorithms (no localized QoS support, no traffic steering) and socially aware 5G V2X (no localized QoS support, yet utilizes traffic steering). Our proposed QoS reclassify scheme's QoS flow end-to-end latency requires only $\approx~15\%$ of the time legacy 4G V2X requires.

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References (40)
  1. 3rd Generation Partnership Project (3GPP), “TS 37.340: NR; Multi-connectivity; Overall description; Stage-2,” Tech. Rep., 07 2020. [Online]. Available: https://www.3gpp.org
  2. 5GAA Automotive Association, “White Paper: C-V2X Use Cases Methodology, Examples and Service Level Requirements,” Tech. Rep., 06 2019. [Online]. Available: https://5gaa.org/
  3. 3rd Generation Partnership Project (3GPP), “TS 22.186: Service Requirements for Enhanced V2X Scenarios,” Tech. Rep., July 2018.
  4. J. Jeong et al., “A comprehensive survey on vehicular networks for smart roads: A focus on IP-based approaches,” Vehicular Communications, vol. 29, p. 100334, 2021. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2214209621000036
  5. J. Choi, “Power allocation for max-sum rate and max-min rate proportional fairness in NOMA,” IEEE Commun. Lett., vol. 20, no. 10, pp. 2055–2058, 2016.
  6. 3rd Generation Partnership Project (3GPP), “TR 38.886: V2X Services based on NR; User Equipment (UE) radio transmission and reception,” Tech. Rep., 06 2020. [Online]. Available: https://www.3gpp.org
  7. A. M. Vegni and V. Loscri, “A survey on vehicular social networks,” IEEE Commun. Surveys Tuts., vol. 17, no. 4, pp. 2397–2419, 2015.
  8. R. Kaliski and Y.-H. Han, “Socially-Aware V2X QoS for NOMA Dual-Connectivity,” in IEEE VTC2021-Fall, 2021, pp. 1–5.
  9. A. Masmoudi, K. Mnif, and F. Zarai, “A survey on radio resource allocation for V2X communication,” Wireless Communications and Mobile Computing, vol. 2019, 2019.
  10. Q. Wei et al., “Resource allocation for V2X communications: A local search based 3D matching approach,” in IEEE ICC, 2017, pp. 1–6.
  11. S.-Y. Lien et al., “Enhanced LTE Device-to-Device Proximity Services,” IEEE Commun. Mag., vol. 54, no. 12, pp. 174–182, 2016.
  12. B. Hu and X. Chu, “Social-Aware Resource Allocation for Vehicle-to-Everything Communications Underlaying Cellular Networks,” in IEEE VTC2021-Spring, 2021, pp. 1–6.
  13. H. Malik et al., “Interference-Aware Radio Resource Allocation for 5G Ultra-Reliable Low-Latency Communication,” in IEEE Globecom Workshops, 2018, pp. 1–6.
  14. K.-C. Chen et al., “Ultra-low latency mobile networking,” IEEE Netw., vol. 33, no. 2, pp. 181–187, 2019.
  15. F. Zhang et al., “Applying noma to nr v2x: A graph-based matching and cooperative game approach,” in IEEE VTC2021-Spring, 2021, pp. 1–5.
  16. G. Liu et al., “Cooperative NOMA Broadcasting/Multicasting for Low-Latency and High-Reliability 5G Cellular V2X Communications,” IEEE Internet Things J., vol. 6, no. 5, pp. 7828–7838, 2019.
  17. M. Aldababsa et al., “A Tutorial on Nonorthogonal Multiple Access for 5G and Beyond,” Wireless Communications and Mobile Computing, vol. 2018, p. 9713450, Jun 2018. [Online]. Available: https://doi.org/10.1155/2018/9713450
  18. B. Wang et al., “Interference Hypergraph-Based 3D Matching Resource Allocation Protocol for NOMA-V2X Networks,” IEEE Access, vol. 7, pp. 90 789–90 800, 2019.
  19. W. Qi et al., “Traffic Differentiated Clustering Routing in DSRC and C-V2X Hybrid Vehicular Networks,” IEEE Trans. Veh. Technol., vol. 69, no. 7, pp. 7723–7734, 2020.
  20. D. Djenouri and I. Balasingham, “Traffic-Differentiation-Based Modular QoS Localized Routing for Wireless Sensor Networks,” IEEE Trans. Mobile Comput., vol. 10, no. 6, pp. 797–809, 2011.
  21. M. Zhang et al., “Fuzzy Logic-Based Resource Allocation Algorithm for V2X Communications in 5G Cellular Networks,” IEEE J. Sel. Areas Commun., vol. 39, no. 8, pp. 2501–2513, 2021.
  22. Z. Zhao et al., “Topology and Link quality-aware Geographical opportunistic routing in wireless ad-hoc networks,” in IEEE IWCMC, 2013, pp. 1522–1527.
  23. A. Brogi and S. Forti, “QoS-Aware Deployment of IoT Applications Through the Fog,” IEEE Internet Things J., vol. 4, no. 5, pp. 1185–1192, 2017.
  24. M. S. Bute et al., “QoS-Aware Content Dissemination Based on Integrated Social and Physical Attributes Among Cellular and V2V Users,” IEEE Trans. Veh. Technol., vol. 72, no. 9, pp. 12 181–12 194, 2023.
  25. M. Hashem Eiza, T. Owens, and Q. Ni, “Secure and Robust Multi-Constrained QoS Aware Routing Algorithm for VANETs,” IEEE Trans. Depend. Sec. Comput., vol. 13, no. 1, pp. 32–45, 2016.
  26. M. Noor-A-Rahim et al., “6g for vehicle-to-everything (v2x) communications: Enabling technologies, challenges, and opportunities,” Proc. IEEE, vol. 110, no. 6, pp. 712–734, 2022.
  27. Q. Pan et al., “Artificial intelligence-based energy efficient communication system for intelligent reflecting surface-driven vanets,” IEEE Trans. Intell. Transp. Syst., vol. 23, no. 10, pp. 19 714–19 726, 2022.
  28. H. Xie et al., “User Grouping and Reflective Beamforming for IRS-Aided URLLC,” IEEE Wireless Commun. Lett., vol. 10, no. 11, pp. 2533–2537, 2021.
  29. 3rd Generation Partnership Project (3GPP), “TS 37.324: Evolved Universal Terrestrial Radio Access (E-UTRA) and NR; Service Data Adaptation Protocol (SDAP) specification,” Tech. Rep., 07 2020. [Online]. Available: https://www.3gpp.org
  30. Fabio Giust and others, “MEC Deployments in 4G and Evolution Towards 5G,” European Telecommunications Standards Institute (ETSI), Tech. Rep., Feb 2018. [Online]. Available: https://www.etsi.org/
  31. 3rd Generation Partnership Project (3GPP), “TS 23.501: System architecture for the 5G System (5GS),” Tech. Rep., Apr 2019.
  32. D. Li et al., “Statistical inference for Mt/G/Infinity queueing systems under incomplete observations,” European Journal of Operational Research, vol. 279, no. 3, pp. 882–901, 2019.
  33. Z. Ding, R. Schober, and H. V. Poor, “Unveiling the Importance of SIC in NOMA Systems: Part I–State of the Art and Recent Findings,” arXiv preprint arXiv:2005.10215, 2020.
  34. 3rd Generation Partnership Project (3GPP), “TS 36.300: Radio Access Network (E-UTRAN); overall description; stage 2,” Tech. Rep., 06 2019. [Online]. Available: https://www.3gpp.org
  35. ——, “TR 38.901: 5G; Study on channel model for frequencies from 0.5 to 100 GHz,” Tech. Rep., 01 2018. [Online]. Available: https://www.3gpp.org
  36. ——, “TS 36.213: Evolved Universal Terrestrial Radio Access (E-UTRAN); physical layer procedures,” Tech. Rep., 06 2019. [Online]. Available: https://www.3gpp.org
  37. ——, “TS 38.214: NR; Physical layer procedures for data,” Tech. Rep., 06 2019. [Online]. Available: https://www.3gpp.org
  38. P. Tseng, “Convergence of a Block Coordinate Descent Method for Nondifferentiable Minimization,” Journal of Optimization Theory and Applications, vol. 109, no. 3, pp. 475–494, Jun 2001. [Online]. Available: https://doi.org/10.1023/A:1017501703105
  39. A. B. Kihero et al., “Inter-Numerology Interference Analysis for 5G and Beyond,” in IEEE Globecom Workshops.   IEEE, 2018, pp. 1–6.
  40. P. A. Lopez et al., “Microscopic Traffic Simulation using SUMO,” in The 21st IEEE International Conference on Intelligent Transportation Systems.   IEEE, 2018. [Online]. Available: https://elib.dlr.de/124092/

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