Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
research-article

Resource Allocation and Slicing Strategy for Multiple Services Co-Existence in Wireless Train Communication Network

Published: 01 January 2025 Publication History

Abstract

Wireless train communication network (WLTCN) is an emerging technology for enabling intelligent rail vehicles. It is responsible for providing train control services (TCS), passenger information services (PIS), and train sensing services (TSS). These services within WLTCN have notably different quality of service (QoS) requirements from traditional telecommunication services. In this paper, to incorporate multiple services in a single WLTCN, we propose a radio access network (RAN) slicing architecture empowered WLTCN to satisfy the demands of services and save bandwidth resource. In particular, the service and slicing models of TCS, PIS, and TSS are investigated. By analyzing the heterogeneous characteristics and QoS requirements of the above services within WLTCN, we exploit the orthogonal multiple access scheme for TCS and PIS and the non-orthogonal multiple access scheme for TSS, respectively. The system bandwidth minimization problem is formulated with slicing resource allocation for TCS, PIS, and TSS and non-orthogonal access grouping for TSS terminals as a mixed-integer nonlinear programming (MINLP). To solve the intractable MINLP, the original problem is transformed and decoupled into the two subproblems. Then, we propose a joint bandwidth optimization and terminal clustering (JBOTC) algorithm to tackle the bandwidth allocation problem with optimal terminal grouping strategy for TSS effectively. The closed-form expressions of the optimal bandwidth allocation strategy for three services are derived. The simulation results illustrate the performance superiority for saving bandwidth of the JBOTC algorithm to the benchmark schemes. Our proposed slicing strategy enables WLTCN to support heterogeneous services co-existence with minimal bandwidth consumption.

References

[1]
Q. Ren et al., “Resource slicing strategy for services co-existence in wireless train communication network,” in Proc. IEEE Global Commun. Conf., Dec. 2023, pp. 5397–5402.
[2]
J. Moreno Garcia-Loygorri et al., “The wireless train communication network: Roll2Rail vision,” IEEE Veh. Technol. Mag., vol. 13, no. 3, pp. 135–143, Sep. 2018.
[3]
D. Ludicke and A. Lehner, “Train communication networks and prospects,” IEEE Commun. Mag., vol. 57, no. 9, pp. 39–43, Sep. 2019.
[4]
S. Li et al., “Joint admission control and resource allocation in edge computing for of Things,” IEEE Netw., vol. 32, no. 1, pp. 72–79, Feb. 2018.
[5]
(2017). D2.5-Architecture for the Train and Consist Wireless Networks. [Online]. Available: https://www.roll2rail.eu
[6]
S. Li, S. Lin, L. Cai, W. Li, and G. Zhu, “Joint resource allocation and computation offloading with time-varying fading channel in vehicular edge computing,” IEEE Trans. Veh. Technol., vol. 69, no. 3, pp. 3384–3398, Mar. 2020.
[7]
B. Ai, A. F. Molisch, M. Rupp, and Z.-D. Zhong, “5G key technologies for smart railways,” Proc. IEEE, vol. 108, no. 6, pp. 856–893, Jun. 2020.
[8]
S. Verma, Y. Kawamoto, and N. Kato, “Energy-efficient group paging mechanism for QoS constrained mobile IoT devices over LTE-A pro networks under 5G,” IEEE Internet Things J., vol. 6, no. 5, pp. 9187–9199, Oct. 2019.
[9]
X. Li, Z. Xie, Z. Chu, V. G. Menon, S. Mumtaz, and J. Zhang, “Exploiting benefits of IRS in wireless powered NOMA networks,” IEEE Trans. Green Commun. Netw., vol. 6, no. 1, pp. 175–186, Mar. 2022.
[10]
(2015). D2.3-State of the Art in Radio Technologies and Recommendation of Suitable Technologies. [Online]. Available: https://www.roll2rail.eu
[11]
L. Zhao, H. Chai, Y. Han, K. Yu, and S. Mumtaz, “A collaborative V2X data correction method for road safety,” IEEE Trans. Rel., vol. 71, no. 2, pp. 951–962, Jun. 2022. 10.1109/TR.2022.3159664.
[12]
C. Zhixiong, Z. Zhikun, C. Tianshu, and Z. Zhenyu, “PLC for in-vehicle network: A DRL-based algorithm of diversity combination of OFDM subcarriers,” Chin. J. Electron., vol. 32, no. 6, pp. 1245–1257, Nov. 2023.
[13]
H. Du et al., “Attention-aware resource allocation and QoE analysis for metaverse xURLLC services,” IEEE J. Sel. Areas Commun., vol. 41, no. 7, pp. 2158–2175, Jul. 2023.
[14]
Z. Wang, Y. Wei, F. R. Yu, and Z. Han, “Utility optimization for resource allocation in multi-access edge network slicing: A twin-actor deep deterministic policy gradient approach,” IEEE Trans. Wireless Commun., vol. 21, no. 8, pp. 5842–5856, Aug. 2022.
[15]
F. Ye, J. Li, P. Zhu, D. Wang, and X. You, “Intelligent hierarchical NOMA-based network slicing in cell-free RAN for 6G systems,” IEEE Trans. Wireless Commun., vol. 23, no. 5, pp. 4724–4737, May 2024.
[16]
A. De Domenico, Y. Liu, and W. Yu, “Optimal virtual network function deployment for 5G network slicing in a hybrid cloud infrastructure,” IEEE Trans. Wireless Commun., vol. 19, no. 12, pp. 7942–7956, Dec. 2020.
[17]
Technical Specification Group Services and Systems Aspects, Standard TS, 2019.
[18]
Y. Zhao, X. Chi, L. Qian, Y. Zhu, and F. Hou, “Resource allocation and slicing puncture in cellular networks with eMBB and URLLC terminals coexistence,” IEEE Internet Things J., vol. 9, no. 19, pp. 18431–18444, Oct. 2022.
[19]
J. Tang, B. Shim, and T. Q. Quek, “Service multiplexing and revenue maximization in sliced C-RAN incorporated with URLLC and multicast eMBB,” IEEE J. Sel. Areas Commun., vol. 37, no. 4, pp. 881–895, Apr. 2019.
[20]
P. Popovski, K. F. Trillingsgaard, O. Simeone, and G. Durisi, “5G wireless network slicing for eMBB, URLLC, and mMTC: A communication-theoretic view,” IEEE Access, vol. 6, pp. 55765–55779, 2018.
[21]
Y. Liu, B. Clerckx, and P. Popovski, “Network slicing for eMBB, URLLC, and mMTC: An uplink rate-splitting multiple access approach,” IEEE Trans. Wireless Commun., vol. 23, no. 3, pp. 2140–2152, Mar. 2024.
[22]
L. Tang, Y. Du, Q. Liu, J. Li, S. Li, and Q. Chen, “Digital-twin-assisted resource allocation for network slicing in industry 4.0 and beyond using distributed deep reinforcement learning,” IEEE Internet Things J., vol. 10, no. 19, pp. 16989–17006, Oct. 2023.
[23]
S. Chatterjee, M. J. Abdel-Rahman, and A. B. MacKenzie, “On optimal orchestration of virtualized cellular networks with statistical multiplexing,” IEEE Trans. Wireless Commun., vol. 21, no. 1, pp. 310–325, Jan. 2022.
[24]
Y.-J. Liu, H. Du, D. Niyato, G. Feng, J. Kang, and Z. Xiong, “Slicing4Meta: An intelligent integration architecture with multi-dimensional network resources for metaverse-as-a-service in web 3.0,” IEEE Commun. Mag., vol. 61, no. 8, pp. 20–26, Aug. 2023.
[25]
(2023). ZTE and China Telecom Unveil the Smart Giga 5G Powered Metro in Shanghai. [Online]. Available: https://www.zte.com.cn
[26]
A. Manzoor, S. M. A. Kazmi, S. R. Pandey, and C. S. Hong, “Contract-based scheduling of URLLC packets in incumbent EMBB traffic,” IEEE Access, vol. 8, pp. 167516–167526, 2020.
[27]
B. Yin, J. Tang, and M. Wen, “Connectivity maximization in non-orthogonal network slicing enabled industrial Internet-of-Things with multiple services,” IEEE Trans. Wireless Commun., vol. 22, no. 8, pp. 5642–5656, Aug. 2023.
[28]
P. Yang, X. Xi, Y. Fu, T. Q. Quek, X. Cao, and D. Wu, “Multicast eMBB and bursty URLLC service multiplexing in a CoMP-enabled RAN,” IEEE Trans. Wireless Commun., vol. 20, no. 5, pp. 3061–3077, May 2021.
[29]
H. Yin, L. Zhang, and S. Roy, “Multiplexing URLLC traffic within eMBB services in 5G NR: Fair scheduling,” IEEE Trans. Commun., vol. 69, no. 2, pp. 1080–1093, Feb. 2021.
[30]
P. Yang, X. Xi, T. Q. S. Quek, J. Chen, X. Cao, and D. Wu, “RAN slicing for massive IoT and bursty URLLC service multiplexing: Analysis and optimization,” IEEE Internet Things J., vol. 8, no. 18, pp. 14258–14275, Sep. 2021.
[31]
M. Alsenwi, N. H. Tran, M. Bennis, S. R. Pandey, A. K. Bairagi, and C. S. Hong, “Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond: A deep reinforcement learning based approach,” IEEE Trans. Wireless Commun., vol. 20, no. 7, pp. 4585–4600, Jul. 2021.
[32]
M. Setayesh, S. Bahrami, and V. W. S. Wong, “Resource slicing for eMBB and URLLC services in radio access network using hierarchical deep learning,” IEEE Trans. Wireless Commun., vol. 21, no. 11, pp. 8950–8966, Nov. 2022.
[33]
L. Xingwang, G. Xuesong, L. Yingting, H. Gaojian, Z. Ming, and Q. Dawei, “Overlay CR-NOMA assisted intelligent transportation system networks with imperfect SIC and CEEs,” Chin. J. Electron., vol. 32, no. 6, pp. 1258–1270, Nov. 2023.
[34]
W. Feng et al., “Latency minimization of reverse offloading in vehicular edge computing,” IEEE Trans. Veh. Technol., vol. 71, no. 5, pp. 5343–5357, May 2022.
[35]
B. Zhu, K. Chi, J. Liu, K. Yu, and S. Mumtaz, “Efficient offloading for minimizing task computation delay of NOMA-based multiaccess edge computing,” IEEE Trans. Commun., vol. 70, no. 5, pp. 3186–3203, May 2022.
[36]
Y. Polyanskiy, H. V. Poor, and S. Verdu, “Channel coding rate in the finite blocklength regime,” IEEE Trans. Inf. Theory, vol. 56, no. 5, pp. 2307–2359, May 2010.
[37]
H. Yu, T. Taleb, and J. Zhang, “Deterministic latency/jitter-aware service function chaining over beyond 5G edge fabric,” IEEE Trans. Netw. Service Manag., vol. 19, no. 3, pp. 2148–2162, Sep. 2022.
[38]
S. Verma, Y. Kawamoto, Z. M. Fadlullah, H. Nishiyama, and N. Kato, “A survey on network methodologies for real-time analytics of massive IoT data and open research issues,” IEEE Commun. Surveys Tuts., vol. 19, no. 3, pp. 1457–1477, 3rd Quart., 2017.
[39]
Study RAN Improvements for Machine-Type Communications, Standard TR, V11.0.0, 3GPP, 2011.
[40]
N. Jiang, Y. Deng, X. Kang, and A. Nallanathan, “Random access analysis for massive IoT networks under a new spatio-temporal model: A stochastic geometry approach,” IEEE Trans. Commun., vol. 66, no. 11, pp. 5788–5803, Nov. 2018.
[41]
M. K. Simon and M.-S. Alouini, Digital Communication Over Fading Channels. Hoboken, NJ, USA: Wiley, 2001.
[42]
S. Boyd, S. P. Boyd, and L. Vandenberghe, Convex Optimization. Cambridge, U.K.: Cambridge Univ. Press, 2004.
[43]
W. Feng, S. Lin, N. Zhang, G. Wang, B. Ai, and L. Cai, “Joint C-V2X based offloading and resource allocation in multi-tier vehicular edge computing system,” IEEE J. Sel. Areas Commun., vol. 41, no. 2, pp. 432–445, Feb. 2023. 10.1109/JSAC.2022.3227081.
[44]
Z. Ding, P. Fan, and H. V. Poor, “Impact of user pairing on 5G nonorthogonal multiple-access downlink transmissions,” IEEE Trans. Veh. Technol., vol. 65, no. 8, pp. 6010–6023, Aug. 2016. 10.1109/TVT.2015.2480766.
[45]
Z. Yang, M. Chen, W. Saad, W. Xu, and M. Shikh-Bahaei, “Sum-rate maximization of uplink rate splitting multiple access (RSMA) communication,” IEEE Trans. Mobile Comput., vol. 21, no. 7, pp. 2596–2609, Jul. 2022.
[46]
W. Feng et al., “Energy-efficient collaborative offloading in NOMA-enabled fog computing for Internet of Things,” IEEE Internet Things J., vol. 9, no. 15, pp. 13794–13807, Aug. 2022.

Index Terms

  1. Resource Allocation and Slicing Strategy for Multiple Services Co-Existence in Wireless Train Communication Network
              Index terms have been assigned to the content through auto-classification.

              Recommendations

              Comments

              Information & Contributors

              Information

              Published In

              cover image IEEE Transactions on Wireless Communications
              IEEE Transactions on Wireless Communications  Volume 24, Issue 1
              Jan. 2025
              872 pages

              Publisher

              IEEE Press

              Publication History

              Published: 01 January 2025

              Qualifiers

              • Research-article

              Contributors

              Other Metrics

              Bibliometrics & Citations

              Bibliometrics

              Article Metrics

              • 0
                Total Citations
              • 0
                Total Downloads
              • Downloads (Last 12 months)0
              • Downloads (Last 6 weeks)0
              Reflects downloads up to 02 Feb 2025

              Other Metrics

              Citations

              View Options

              View options

              Figures

              Tables

              Media

              Share

              Share

              Share this Publication link

              Share on social media