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6G-BRICKS: Developing a Modern Experimentation Facility for Validation, Testing and Showcasing of 6G Breakthrough Technologies and Devices

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Artificial Intelligence Applications and Innovations. AIAI 2023 IFIP WG 12.5 International Workshops (AIAI 2023)

Abstract

Shifting towards B5G/6G implicates for a great diversity of challenges for the involved markets, especially via the creation of vast amounts of generated data and of related novel applications serving a great multiplicity of verticals. Such innovative services exceed the capabilities of existing 5G infrastructures for potential support of their corresponding KPIs and computational offloading, thus creating a new generation of Smart Networks. Towards fulfilling this target, the 6G-BRICKS project aims to deliver a new 6G experimentation facility building on the baseline of mature platforms coming from ongoing EU-funded activities and bringing breakthrough cell-free (CF) and RIS technologies. We have presented the essential architectural structure of the above facility and assessed in detail the core objectives of the project, as these “identify” diverse technical challenges and dedicated areas for future research. In addition, we have discussed and evaluated the fundamental use cases together with their intended PoCs that are expected to demonstrate strong market impact.

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Notes

  1. 1.

    An xApp is a software tool used by a RAN Intelligent Controller (RIC) to manage network functions in near-real time. The xApps are part of a RIC which is a central software component of the Open RAN architecture, being responsible for controlling and optimizing RAN functions and resources. These applications – or services –include functions like radio resource management, mobility management and security.

  2. 2.

    Composable infrastructure is a framework that decouples device resources in order to treat them as services. Physical compute, storage and network fabrics are examples of device resources that can be treated as services.

References

  1. Shah, S.D.A., Gregory, M.A., Li, S.: Cloud-Native Network Slicing Using Software Defined Networking Based Multi-Access Edge Computing: A Survey. IEEE Access 9, 10903–10924 (2021)

    Article  Google Scholar 

  2. Saad, W., Bennis, M., Chen, M.: A Vision of 6G Wireless Systems: Applications, Trends, Technologies, and Open Research Problems. IEEE Network 34(3), 134–142 (2020)

    Article  Google Scholar 

  3. Ericsson: “XR and 5G: Extended reality at scale with time-critical communication”, https://www.ericsson.com/en/reports-and-papers/ericsson-technology-review/articles/xr-and-5g-extended-reality-at-scale-with-time-critical-communication

  4. Bhat, J.R., Alqahtani, S.A.: 6G Ecosystem: Current Status and Future Perspective. IEEE Access 9, 43134–43167 (2021)

    Article  Google Scholar 

  5. Akyildiz, I.F., Kak, A., Nie, S.: 6G and Beyond: The Future of Wireless Communications Systems. IEEE Access 8, 133995–134030 (2020)

    Article  Google Scholar 

  6. Seppo Yrjölä, S., Ahokangas, P., Matinmikko-Blue, M.: Value Creation and Capture From Technology Innovation in the 6G Era. IEEE Access 10, 16299–16319 (2022)

    Article  Google Scholar 

  7. O-RAN Alliance eV, https://www.o-ran.org/

  8. Open Source, https://opensource.com/resources/what-open-source

  9. 6G-BRICKS (Building Reusable testbed Infrastructures for validating Cloud-to-device breakthrough technologieS) Horizon-JU-SNS project, Grant Agreement No.101096954, https://6g-bricks.eu/

  10. Chen, S., Zhang, J., Zhang, J., Björnson, E., and Ai, B: A Survey on User-centric Massive MIMO Systems. Digital Communications and Networks 8(5), 695--719 (2022)

    Google Scholar 

  11. Ngo, H.Q., Ashikhmin, A., Yang, H., Larsson, E.G., Marzetta, T.L.: Cell-Free Massive MIMO Versus Small Cells. IEEE Trans. Wireless Commun. 16(3), 1834–1850 (2017)

    Article  Google Scholar 

  12. Ngo, H.Q., Ashikhmin, A., Yang, X., Larsson, E.G., and Marzetta, T.L.: Cell-Free Massive MIMO: Uniformly Great Service for Everyone. In: Proceedings of the 16th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC’15), pp.201–205. IEEE (2015)

    Google Scholar 

  13. European Telecommunications Standards Institute (ETSI): Reconfigurable Intelligent Interfaces, https://www.etsi.org/technologies/reconfigurable-intelligent-surfaces

  14. OpenAirInterface (OAI), https://openairinterface.org/

  15. 5G Public Private Infrastructure (5G-PPP), https://5g-ppp.eu/

  16. NI, https://www.ni.com/en-us/shop/wireless-design-test/what-is-a-usrp-software-defined-radio.html

  17. Girardon, G., Costa V., Machado, R., Bernardino, M., Legramante, M., Basso, F.P., et al.: Testing as a Service (TaaS): A Systematic Literature Map. In: Proceedings of the 35th Annual ACM Symposium on Applied Computing (SAC’20), pp.1989–1996. ACM (2020)

    Google Scholar 

  18. 5G Public Private Infrastructure (5G-PPP): H2020-ICT52–2020: “5G-PPP Smart connectivity beyond 5G”, https://5g-ppp.eu/5g-ppp-phase-3-6-projects/

  19. Toumi, N., Bernier, O., Meddour, D.-E., Ksentini, A.: On cross-domain service function chain orchestration: an architectural framework. Comput. Netw. 187, 107806–107823 (2021)

    Google Scholar 

  20. 5GMediaHUB (“5G Experimentation Environment for 3rd Party Media Services”) 5G-PPP/H2020 Project, Grant Agreement No.101016714, https://www.5gmediahub.eu/

  21. Chochliouros, I.P., Spiliopoulou, A.S., Lazaridis, P., Dardamanis, A., Zaharis, Z., Kostopoulos, A.: Dynamic Network Slicing: Challenges and Opportunities. In: Maglogiannis, I., Iliadis, L., Pimenidis, E. (eds.) AIAI 2020. AICT, vol. 585, pp. 47–60. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-49190-1_5

    Chapter  Google Scholar 

  22. European Telecommunications Standards Institute (ETSI) ETSI GR ENI 008 (V2.1.1) (2021–03) Experiential Networked Intelligence (ENI); InTent Aware Network Autonomicity (ITANA). https://www.etsi.org/deliver/etsi_gr/ENI/001_099/008/02.01.01_60/gr_ENI008v020101p.pdf

  23. Jonathon Phillips, P., Hahn, C.A., Fontana, P.C., Yates, A.N., Greene, K., Broniatowski, D.A., Przybocki, M.A.: Four Principles of Explanable Artificial Intelligence (NISTIR 8312). National Institute of Standards and Technology (2021). https://nvlpubs.nist.gov/nistpubs/ir/2021/NIST.IR.8312.pdf

  24. MARSAL (“Machine Learning-based Networking and Computing Infrastructure Resource Management of 5G and Beyond Intelligent Networks”) 5G-PPP/H2020 project, Grant Agreement No.101017171, https://www.marsalproject.eu/

  25. 5G-EVE (“5G European Validation platform for extensive trials”) 5G-PPP/H2020 project, Grant Agreement No.815074, https://www.5g-eve.eu/

  26. RISE-6G (“Reconfigurable Intelligent Sustainable Environments for 6G Wireless Networks”) 5G-PPP/H2020 project Grant Agreement No.10101701, https://rise-6g.eu/

  27. Yamansavascilar, B., Baktir, A.C., Sonmez, C., Ozgovde, A., and Ersoy, C.: DeepEdge: A Deep Reinforcement Learning based Task Orchestrator for Edge Computing (2021), https://arxiv.org/abs/2110.01863

  28. European Telecommunications Standards Institute (ETSI): Zero-touch network and Service Management (ZSM). ETSI (2023), https://www.etsi.org/technologies/zero-touch-network-service-management

  29. Rosendo, D., Costan, A., Valduriez, P., Antoniu, G.: Distributed intelligence on the Edge-to-Cloud Continuum: A systematic literature review. Journal of Parallel and Distributed Computing 166, 71–94 (2022)

    Article  Google Scholar 

  30. 5G Public Private Infrastructure (5G-PPP): 5G-PPP White Paper: “Beyond 5G/6G KPIs and Target Values” (2022), https://5g-ppp.eu/5g-ppp-white-paper-beyond-5g-6g-kpis-and-target-values/

  31. 6G Infrastructure Association (6G-IA), Vision and Societal Challenges Working Group: White Paper: “What societal values will 6G address? Societal Key Values and Key Value Indicators analysed through 6G use cases” (2022), https://doi.org/10.5281/zenodo.6557534

  32. REINDEER (“REsilient INteractive applications through hyper Diversity in Energy Efficient RadioWeaves technology”) 5G-PPP/H2020 Project, Grant Agreement No.101013425, https://reindeer-project.eu/

  33. HEXA-X (“A flagship for B5G/6G vision and intelligent fabric of technology enablers connecting human, physical, and digital worlds”) 5G-PPP/H2020 Project, Grant Agreement No.101015956, https://hexa-x.eu/

  34. Kandiraju, G., Franke, H., Williams, M.D., Steinder, M., and Black, S.M.: Software defined infrastructures. IBM Journal of Research and Development 58(2/3), 2:1--2:13 (2014)

    Google Scholar 

  35. Čyras, K., Badrinath, R., Mohalik, S.K., Mujumdar, A., Nikou, A., Previti, A., Sundararajan, V., and Vulgarakis-Feljan, A.: Machine Reasoning Explainability (2020), https://arxiv.org/pdf/2009.00418.pdf,

  36. Balouek-Thomert, D., Renart, E.G., Zamani, A.R., et al.: Towards a computing continuum: Enabling edge-to-cloud integration for data-driven workflows. The International Journal of High Performance Computing Applications 33(6), 1159–1174 (2019)

    Article  Google Scholar 

  37. La Oliva, A.D., Costa-Pérez, X., Azcorra, A., Di Gigglio, A.: Xhaul: toward an integrated fronthaul/backhaul architecture in 5G networks. IEEE Wirel. Commun. 22(5), 32–40 (2015)

    Article  Google Scholar 

  38. Arulkumaran, K., Deisenroth, M.P., Brundage, M., Bharath, A.A.: A Brief Survey of Deep Reinforcement Learning. IEEE Signal Process. Mag. 34(6), 26–38 (2017)

    Article  Google Scholar 

  39. Xie, Z., and Xu, Y.: Research on OTA Optimization of Wireless Sensor Networks Based on CSMA/CA Improved Algorithm. In: Proceedings of the 2018 10th International Conference on Communications, Circuits and Systems (ICCCAS’18), pp.331–335. IEEE (2018)

    Google Scholar 

  40. Interdonato, G., Björnson, E., Ngo, H.Q., Frenger, P., Larsson, E.G.: Ubiquitous Cell-Free Massive MIMO Communications. EURASIP J. Wirel. Commun. Netw. 197, 1–13 (2019)

    Google Scholar 

  41. Lefebvre, M., Engels, D.W., and Nair, S.: On SDPN: Integrating the Software-Defined Perimeter (SDP) and the Software-Defined Network (SDN) Paradigms. In: Proceedings of the 2022 IEEE Conference on Communications and Network Security (CNS’22), pp.353–358. IEEE (2022)

    Google Scholar 

  42. Bhat, A.Z., Shuaibi, D.K.A., and Singh, A.V.: Virtual private network as a service - A need for discrete cloud architecture. In: Proceedings of the 2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO’16), pp.526–532. IEEE (2016)

    Google Scholar 

  43. J. Lee, J., Yeo, I., et al.: Metaverse Current Status and Prospects: Focusing on Metaverse Field Cases. In: Proceedings of the 2022 IEEE/ACIS 7th International Conference on Big Data, Cloud Computing, and Data Science (BCD’22), pp. 332–336. IEEE (2022)

    Google Scholar 

  44. Go, S.Y., Jeong, H.G., Kim, J.I., Sin, Y.Y.: Concept and Development of Metaverse. Korea Information Processing Society Review 28(1), 7–16 (2021)

    Google Scholar 

  45. Peng, H., Chen, P.-C., Chen, P.-H., Yang, Y.-S., Hsia, C.-C., et al.: 6G toward Metaverse: Technologies, Applications, and Challenges. In: Proceedings of the 2022 IEEE VTS Asia Pacific Wireless Communications Symposium (APWCS’22), pp.6–10. IEEE (2022)

    Google Scholar 

  46. Aslam, A.M., Chaudhary, R., Bhardwaj, A., Budhiraja, I., Kumar, N., Zeadally, S.: Metaverse for 6G and Beyond: The Next Revolution and Deployment Challenges. IEEE Internet of Things Magazine 6(1), 32–39 (2023)

    Article  Google Scholar 

  47. Abari, O.: Enabling High-Quality Untethered Virtual Reality. In: Proceedings of the 1st ACM Workshop on Millimeter-Wave Networks and Sebsning Systems (mmNets’17), pp.1–49. ACM (2017)

    Google Scholar 

  48. Zucchi, S., Füchter, S.K., Salazar, G., and Alexander, K.: Combining immersion and interaction in XR training with 360-degree video and 3D virtual objects. In: Proceedings of the 2020 23rd International Symposium on Measurement and Control in Robotics (ISMCR’20), pp.1–5. IEEE (2020)

    Google Scholar 

  49. Cernigliaro, G., Martos, M., Montagud, M., Ansari, A., and Fernandez, S.: PC-MCU: point cloud multipoint control unit for multi-user holoconferencing systems. In: Proceedings of the 30th ACM Workshop on Network and Operating Systems Support for digital Audio and Video (NOSSDAV’20), pp.47–53. ACM (2020)

    Google Scholar 

  50. Bennis, M., Debbah, M., et al.: Ultrareliable and Low-Latency Wireless Communication: Tail, Risk, and Scale. Proc. IEEE 106(10), 1834–1853 (2018)

    Article  Google Scholar 

  51. Langa, S.F., Montagud, M., Cernigliaro, G., Rivera, D.R.: Multi-party Holomeetings: Toward a New Era of Low-Cost Volumetric Holographic Meetings in Virtual Reality. IEEE Access 10, 81856–81876 (2022)

    Article  Google Scholar 

  52. Alraih, S., Shayea, I., et al.: Revolution or Evolution? Technical Requirements and Considerations towards 6G Mobile Communications. Sensors (MDPI) 22(3), 762 (2022)

    Article  Google Scholar 

  53. Numan, N., Haar, F.T., and Cesar, P.: Generative RGB-D face completion for head-mounted display removal. In: Proceedings of the IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW’21), pp.109–116. IEEE (2021)

    Google Scholar 

  54. Standardization Council Industrie 4.0: The German Standardization Roadmap Industrie 4.0- Edition 4. Din & DKE (2020), https://www.sci40.com/english/publications/

  55. Maier, M.: 6G as if People Mattered: From Industry 4.0 toward Society 5.0 (Invited Paper), In: Proceedings of the 2021 International Conference on Computer Communications and Networks (ICCCN), pp.1–10. IEEE (2021)

    Google Scholar 

  56. Xu, L.D., Xu, E.L., & Li, L.: Industry 4.0: state of the art and future trends. International Journal of Production Research 56(8), 2941--2962 (2018)

    Google Scholar 

  57. Sigov, A., Ratkin, L., Ivanov, L.A., Xu, L.D.: Emerging Enabling Technologies for Industry 4.0 and Beyond. Inf. Syst. Front. (2022). https://doi.org/10.1007/s10796-021-10213-w

    Article  Google Scholar 

  58. Liu, G., et al.: Vision, requirements and network architecture of 6G mobile network beyond 2030. China Communications 17(9), 92–104 (2020)

    Article  Google Scholar 

  59. Yurtsever, E., Lambert, J., Carballo, A., Takeda, K.: A Survey of Autonomous Driving: Common Practices and Emerging Technologies. IEEE Access 8, 58443–58469 (2020)

    Article  Google Scholar 

  60. Liu, M., Fang, S., Dong, H., Xu, C.: Review of digital twin about concepts, technologies, and industrial applications. J. Manuf. Syst. 58(part B), 346–361 (2021)

    Google Scholar 

  61. Grand View Research, Inc.: Digital Twin Market Size Worth $26.07 Billion By 2025 with CAGR 38.2% - Digital Twin Market Growth & Trends (2022), https://www.grandviewresearch.com/press-release/global-digital-twin-market

  62. Tao, F., Zhang, H., Liu, A., Nee, A.Y.: Digital Twin in Industry: State-of-the-Art. IEEE Trans. Industr. Inf. 15(4), 2405–2415 (2019)

    Article  Google Scholar 

  63. Han, B., Habibi, M.A., Richerzhagen, B., Schindhelm, K., Zeiger, F., Lamberti, F., Pratticò, F.G., Upadhya, K., Korovesis, C., Belikaidis, I.-P., Demestichas, P., Yuan, S., and Schotten, H.D.: Digital Twins for Industry 4.0 in the 6G Era (2022), https://arxiv.org/ftp/arxiv/papers/2210/2210.08970.pdf

  64. Wang, T., Li, J., Deng, Y., Wang, C., Snoussi, H., Tao, F.: Digital twin for human-machine interaction with convolutional neural network. Int. J. Comput. Integr. Manuf. 34(7–8), 888–897 (2021)

    Article  Google Scholar 

  65. Fuller, A., Fan, Z., Day, C., Barlow, C.: Digital twin: Enabling technologies, challenges and open research. IEEE Access 8, 108952–108971 (2020)

    Article  Google Scholar 

  66. Huang, Z., Shen, Y., Li, J., Fey, M., and Brecher, C.: A survey on AI-driven digital twins in Industry 4.0: Smart manufacturing and advanced robotics. Sensors (MDPI) 21(19), 6340 (2021)

    Google Scholar 

  67. Dang, S., Amin, O., Shihada, B., Alouini, M.-S.: What should 6G be? Nature Electronics 3, 20–29 (2020)

    Article  Google Scholar 

  68. Next Generation of Mobile Networks Alliance (NGMN): 6G Use Cases and Analysis – Version 1.0. NGMN (2022), https://www.ngmn.org/publications/6g-use-cases-and-analysis.html

  69. Sakai, T., Nagai, T.: Explainable autonomous robots: a survey and perspective. Adv. Robot. 36(5–6), 219–238 (2021)

    Google Scholar 

  70. Goel, R., and Gupta, P.: Robotics and Industry 4.0. In: Nayyar, A., Kumar, A. (eds) A Roadmap to Industry 4.0: Smart Production, Sharp Business and Sustainable Development. Advances in Science, Technology & Innovation, pp.157–169. Springer, Cham (2020), https://doi.org/10.1007/978-3-030-14544-6_9

  71. Gonzalez-Aguirre, J.A., Osorio-Oliveros, R., Rodríguez-Hernández, K.L., Lizárraga-Iturralde, J., Morales Menendez, R., Ramírez-Mendoza, R.A., et al.: Service robots: trends and technology. Appl. Sci. (MDPI) 11(22), 1070 (2021)

    Google Scholar 

  72. Bayram, B., İnce, G.: Advances in Robotics in the Era of Industry 4.0. In: Industry 4.0: Managing The Digital Transformation. SSAM, pp. 187–200. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-57870-5_11

    Chapter  Google Scholar 

  73. Javaid, M., Haleem, A., Singh, R.P., and Suman, R.: Substantial capabilities of robotics in enhancing industry 4.0 implementation. Cognitive Robotics 1, 58--75 (2021)

    Google Scholar 

  74. Hu, L., Miao, Y., Wu, G., Hassan, M.M., Humar, I.: iRobot-Factory: An intelligent robot factory based on cognitive manufacturing and edge computing. Futur. Gener. Comput. Syst. 90, 569–577 (2019)

    Article  Google Scholar 

  75. Gualtieri, L., Rauch, E., Vidoni, R.: Emerging research fields in safety and ergonomics in industrial collaborative robotics: A systematic literature review. Robotics and Computer-Integrated Manufacturing 67, 101998–102001 (2021)

    Article  Google Scholar 

  76. Parmar, H., Khan, T., Tucci, F., Umer, R., and Carlone, P.: Advanced robotics and additive manufacturing of composites: towards a new era in Industry 4.0. Materials and Manufacturing Processes 37(5), 1--35 (2021)

    Google Scholar 

  77. Schroeder, G.N., Steinmetz, C., Pereira, C.E., Muller, I., Garcia, N., Espindola, D., and Rodrigues, R.: Visualising the digital twin using web services and augmented reality. In: Proceedings of the 2016 IEEE 14th International Conference on Industrial Informatics (INDIN’16), pp.522–527. IEEE (2016)

    Google Scholar 

  78. Künz, A., Rosmann, S., Loria, E., Pirker, J.: The potential of augmented reality for digital twins: a literature review. In: Proceedings of the 2022 IEEE Conference on Virtual Reality and 3D User Interfaces (VR 2022), pp. 389–398. IEEE (2022)

    Google Scholar 

  79. Böhm, F., Dietz, M., Preindl, T., Pernul, G.: Augmented Reality and the Digital Twin: State-of-the-Art and Perspectives for Cybersecurity. Journal of Cybersecurity and Privacy (MDPI) 1, 519–538 (2021)

    Article  Google Scholar 

  80. Yu, L., Yang, E., Ren, P., Luo, C., Dobie, G., Gu, D., and Yan, X.: Inspection Robots in Oil and Gas Industry: a Review of Current Solutions and Future Trends. In: Proceedings of the 2019 25th International Conference on Automation and Computing (ICAC’19), pp.1–6. IEEE (2019)

    Google Scholar 

  81. MarketWatch: Inspection Robotics in Oil and Gas Market Share by 2031 (2023) https://www.marketwatch.com/press-release/inspection-robotics-in-oil-and-gas-market-share-by-2031-2023-03-24

  82. Hajjaj, S.S.H., Khalid, I.B.: Design and Development of an Inspection Robot for Oil and Gas Applications. International Journal of Engineering & Technology 7(435), 5–10 (2018)

    Article  Google Scholar 

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Acknowledgments

This work has been performed in the scope of the 6G-BRICKS European Research Project and has been supported by the Commission of the European Communities /HORIZON, Grant Agreement No.101096954.

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Correspondence to Ioannis P. Chochliouros .

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Chochliouros, I.P. et al. (2023). 6G-BRICKS: Developing a Modern Experimentation Facility for Validation, Testing and Showcasing of 6G Breakthrough Technologies and Devices. In: Maglogiannis, I., Iliadis, L., Papaleonidas, A., Chochliouros, I. (eds) Artificial Intelligence Applications and Innovations. AIAI 2023 IFIP WG 12.5 International Workshops. AIAI 2023. IFIP Advances in Information and Communication Technology, vol 677. Springer, Cham. https://doi.org/10.1007/978-3-031-34171-7_1

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