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Engineering >> 2022, Volume 8, Issue 1 doi: 10.1016/j.eng.2021.11.002

MEC-Empowered Non-Terrestrial Network for 6G Wide-Area Time-Sensitive Internet of Things

a Department of Electronic Engineering, Tsinghua University, Beijing 100084, China

b Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing 100084, China

Received:2020-12-31 Revised:2021-06-11 Accepted: 2021-08-29 Available online:2021-11-15

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In the upcoming sixth-generation (6G) era, the demand for constructing a wide-area time-sensitive Internet of Things (IoT) continues to increase. As conventional cellular technologies are difficult to directly use for wide-area time-sensitive IoT, it is beneficial to use non-terrestrial infrastructures, including satellites and unmanned aerial vehicles (UAVs). Thus, we can build a non-terrestrial network (NTN) using a cell-free architecture. Driven by the time-sensitive requirements and uneven distribution of IoT devices, the NTN must be empowered using mobile edge computing (MEC) while providing oasisoriented on-demand coverage for devices. Nevertheless, communication and MEC systems are coupled with each other under the influence of a complex propagation environment in the MEC-empowered NTN, which makes it difficult to coordinate the resources. In this study, we propose a process-oriented framework to design communication and MEC systems in a time-division manner. In this framework, large-scale channel state information (CSI) is used to characterize the complex propagation environment at an affordable cost, where a nonconvex latency minimization problem is formulated. Subsequently, the approximated problem is provided, and it can be decomposed into sub-problems. These sub-problems are then solved iteratively. The simulation results demonstrated the superiority of the proposed process-oriented scheme over other algorithms, implied that the payload deployments of UAVs should be appropriately predesigned to improve the efficiency of using resources, and confirmed that it is advantageous to integrate NTN with MEC for wide-area time-sensitive IoT.



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[1]  Saarnisaari H, Dixit S, Alouini MS, Chaoub A, Giordani M, Kliks A, et al. A 6G white paper on connectivity for remote areas. 2020. arXiv: 2004.14699.

[2]  Huang C, Huang G, Liu W, Wang R, Xie M. A parallel joint optimized relay selection protocol for wake-up radio enabled WSNs. Phys Commun 2021;47:101320. link1

[3]  FG-NET-2030. Network 2030: a blueprint of technology, applications and market drivers towards the year 2030 and beyond. Geneva: ITU; 2019.

[4]  Wei T, Feng W, Chen Y, Wang CX, Ge N, Lu J. Hybrid satellite–terrestrial communication networks for the maritime Internet of Things: key technologies, opportunities, and challenges. IEEE Internet Things J 2021;8(11): 8910–34. link1

[5]  Li X, Feng W, Wang J, Chen Y, Ge N, Wang CX. Enabling 5G on the ocean: a hybrid satellite–UAV–terrestrial network solution. IEEE Wirel Commun 2020;27(6):116–21. link1

[6]  Wang Y, Feng W, Wang J, Quek TQS. Hybrid satellite–UAV–terrestrial networks for 6G ubiquitous coverage: a maritime communications perspective. IEEE J Sel Areas Commun 2021;39(11):3475–90. link1

[7]  Onireti O, Qadir J, Imran MA, Sathiaseelan A. Will 5G see its blind side? Evolving 5G for universal Internet access. In: Proceedings of the 2016 workshop on Global Access to the Internet for All; 2016 Aug; Florianopolis, Brazil. New York: Association for Computing Machinery; 2016. p. 1–6.

[8]  Liu C, Feng W, Chen Y, Wang CX, Ge N. Cell-free satellite–UAV networks for 6G wide-area Internet of Things. IEEE J Sel Areas Commun 2021;39(4):1116–31. link1

[9]  Zhao J, Gao F, Wu Q, Jin S, Wu Y, Jia W. Beam tracking for UAV mounted SatCom on-the-move with massive antenna array. IEEE J Sel Areas Commun 2018;36(2): 363–75. link1

[10]  Cheng X, Lyu F, Quan W, Zhou C, He H, Shi W, et al. Space/aerial-assisted computing offloading for IoT applications: a learning-based approach. IEEE J Sel Areas Commun 2019;37(5):1117–29. link1

[11]  Raza U, Kulkarni P, Sooriyabandara M. Low power wide area networks: an overview. IEEE Commun Surv Tutor 2017;19(2):855–73. link1

[12]  Centenaro M, Vangelista L, Zanella A, Zorzi M. Long-range communications in unlicensed bands: the rising stars in the IoT and smart city scenarios. IEEE Wirel Commun 2016;23(5):60–7. link1

[13]  Lo Bello L, Steiner W. A perspective on IEEE time-sensitive networking for industrial communication and automation systems. Proc IEEE 2019;107(6): 1094–120. link1

[14]  Liang W, Zheng M, Zhang J, Shi H, Yu H, Yang Y, et al. WIA-FA and its applications to digital factory: a wireless network solution for factory automation. Proc IEEE 2019;107(6):1053–73. link1

[15]  Luvisotto M, Pang Z, Dzung D. High-performance wireless networks for industrial control applications: new targets and feasibility. Proc IEEE 2019;107(6): 1074–93. link1

[16]  TR 38.824: Study on physical layer enhancements for NR ultra-reliable and low latency case (URLLC). 3GPP standard. France: 3GPP; 2019.

[17]  TR 38.825: Study on NR industrial Internet of Things (IoT). 3GPP standard. France: 3GPP; 2019.

[18]  TR 38.821: Solutions for NR to support non-terrestrial networks (NTN). 3GPP standard. France: 3GPP; 2020.

[19]  Ghosh A, Maeder A, Baker M, Chandramouli D. 5G evolution: a view on 5G cellular technology beyond 3GPP Release 15. IEEE Access 2019;7:127639–51. link1

[20]  De Sanctis M, Cianca E, Araniti G, Bisio I, Prasad R. Satellite communications supporting Internet of Remote Things. IEEE Internet Things J 2016;3(1): 113–23. link1

[21]  Cioni S, De Gaudenzi R, Del Rio Herrero O, Girault N. On the satellite role in the era of 5G massive machine type communications. IEEE Netw 2018;32(5): 54–61. link1

[22]  Zhen L, Qin H, Zhang Q, Chu Z, Lu G, Jiang J, et al. Optimal preamble design in spatial group-based random access for satellite-M2M communications. IEEE Wirel Commun Lett 2019;8(3):953–6. link1

[23]  Zhang Q, Jiang M, Feng Z, Li W, Zhang W, Pan M. IoT enabled UAV: network architecture and routing algorithm. IEEE Internet Things J 2019;6(2):3727–42. link1

[24]  Chakareski J. UAV-IoT for next generation virtual reality. IEEE Trans Image Process 2019;28(12):5977–90. link1

[25]  Ranjha A, Kaddoum G. Quasi-optimization of uplink power for enabling green URLLC in mobile UAV-assisted IoT networks: a perturbation-based approach. IEEE Internet Things J 2021;8(3):1674–86. link1

[26]  Huang M, Liu A, Xiong NN, Wu J. A UAV-assisted ubiquitous trust communication system in 5G and beyond networks. IEEE J Sel Areas Commun 2021;39(11):3444–58. link1

[27]  Islambouli R, Sharafeddine S. Optimized 3D deployment of UAV-mounted cloudlets to support latency-sensitive services in IoT networks. IEEE Access 2019;7:172860–70. link1

[28]  Zhang L, Ansari N. Latency-aware IoT service provisioning in UAV-aided mobile-edge computing networks. IEEE Internet Things J 2020;7(10): 10573–80. link1

[29]  Tan Z, Qu H, Zhao J, Zhou S, Wang W. UAV-aided edge/fog computing in smart IoT community for social augmented reality. IEEE Internet Things J 2020;7(6): 4872–84. link1

[30]  Tun YK, Park YM, Tran NH, Saad W, Pandey SR, Hong CS. Energy-efficient resource management in UAV-assisted mobile edge computing. IEEE Commun Lett 2021;25(1):249–53. link1

[31]  Wang J, Liu K, Pan J. Online UAV-mounted edge server dispatching for mobileto-mobile edge computing. IEEE Internet Things J 2020;7(2):1375–86. link1

[32]  Guo J, Huang G, Li Q, Xiong NN, Zhang S, Wang T. STMTO: a smart and trust multi-UAV task offloading system. Inf Sci 2021;573:519–40. link1

[33]  Zeng Y, Wu Q, Zhang R. Accessing from the sky: a tutorial on UAV communications for 5G and beyond. Proc IEEE 2019;107(12):2327–75. link1

[34]  Liu J, Du X, Cui J, Pan M, Wei D. Task-oriented intelligent networking architecture for the space–air–ground–aqua integrated network. IEEE Internet Things J 2020;7(6):5345–58. link1

[35]  Cao P, Liu Y, Yang C, Xie S, Xie K. MEC-driven UAV-enabled routine inspection scheme in wind farm under wind influence. IEEE Access 2019;7:179252–65. link1

[36]  Chen Y, Feng W, Zheng G. Optimum placement of UAV as relays. IEEE Commun Lett 2018;22(2):248–51. link1

[37]  Pan Y, Jiang H, Zhu H, Wang J. Latency minimization for task offloading in hierarchical fog-computing C-RAN networks. In: Proceedings of 2020 IEEE International Conference on Communications; 2020 Jun 7–11; Dublin, Ireland; 2020. p. 1–6.

[38]  Wang JB, Yang H, Cheng M, Wang JY, Lin M, Wang J. Joint optimization of offloading and resources allocation in secure mobile edge computing systems. IEEE Trans Vehicular Technol 2020;69(8):8843–54. link1

[39]  Wang P, Yao C, Zheng Z, Sun G, Song L. Joint task assignment, transmission, and computing resource allocation in multilayer mobile edge computing systems. IEEE Internet Things J 2019;6(2):2872–84. link1

[40]  Sharma J, Choudhury T, Satapathy SC, Sabitha AS. Study on H.265/HEVC against VP9 and H.264: on space and time complexity for codecs. In: Proceedings of 2018 International Conference on Communication, Computing and Internet of Things; 2018 Feb 17–19; Chennai, India; 2018. p. 106–10.

[41]  Dymond A, Billowes C, Lopianowski M. Trends and potential for the use of satellites for rural telecommunications in developing countries. In: Proceedings of International Conference on Rural Telecommunications; 1988 May 23–25; London, UK; 1988. p. 126–9.

[42]  Khuwaja AA, Chen Y, Zhao N, Alouini MS, Dobbins P. A survey of channel modeling for UAV communications. IEEE Commun Surv Tutor 2018;20(4): 2804–21. link1

[43]  Du J, Xu W, Deng Y, Nallanathan A, Vandendorpe L. Energy-saving UAVassisted multi-user communications with massive MIMO hybrid beamforming. IEEE Commun Lett 2020;24(5):1100–4. link1

[44]  Ammari ML, Fortier P. Low complexity ZF and MMSE detectors for the uplink MU-MIMO systems with a time-varying number of active users. IEEE Trans Vehicular Technol 2017;66(7):6586–90. link1

[45]  Cao P, Liu W, Thompson JS, Yang C, Jorswieck EA. Semidynamic green resource management in downlink heterogeneous networks by group sparse power control. IEEE J Sel Areas Commun 2016;34(5):1250–66. link1

[46]  Rost P. Achievable net-rates in multi-user OFDMA with partial CSI and finite channel coherence. In: Proceedings of 2012 IEEE Vehicular Technology Conference (VTC Fall); 2012 Sep 3–6; Quebec, QC, Canada; 2012. p. 1–5.

[47]  Khoshnevis B, Yu W, Lostanlen Y. Two-stage channel quantization for scheduling and beamforming in network MIMO systems: feedback design and scaling laws. IEEE J Sel Areas Comm 2013;31(10):2028–42. link1

[48]  Liu C, Feng W, Tao X, Ge N. MEC-empowered non-terrestrial networks for 6G wide-area time-sensitive Internet of Things. 2021. arXiv: 1103.21907.

[49]  Sun Y, Babu P, Palomar DP. Majorization–minimization algorithms in signal processing, communications, and machine learning. IEEE Trans Signal Process 2017;65(3):794–816. link1

[50]  Boyd S, Vandenberghe L, editors. Convex optimization. Cambridge: Cambridge University Press; 2004. link1

[51]  Mirahsan M, Schoenen R, Yanikomeroglu H. Hethetnets: heterogeneous traffic distribution in heterogeneous wireless cellular networks. IEEE J Sel Areas Comm 2015;33(10):2252–65. link1

[52]  Zhao B, Ren G, Dong X, Zhang H. Spatial group based optimal uplink power control for random access in satellite networks. IEEE Trans Vehicular Technol 2020;69(7):7354–65. link1

[53]  Peng F, Cardona ÁS, Shafiee K, Leung VCM. TCP performance evaluation over GEO and LEO satellite links between performance enhancement proxies. In: Proceedings of 2012 IEEE Vehicular Technology Conference (VTC Fall); 2012 Sept 3–6; Quebec, QC, Canada; 2012. p. 1–5.

[54]  Luglio M, Roseti C, Zampognaro F. Transport layer optimization for cloud computing applications via satellite: TCP Noordwijk+. China Commun 2014;11 (12):105–19. link1

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