True-data Testbed for 5G/B5G Intelligent Network
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Abstract (arXiv)
Future beyond fifth-generation (B5G) and sixth-generation (6G) mobile communications will shift from facilitating interpersonal communications to supporting Internet of Everything (IoE), where intelligent communications with full integration of big data and artificial intelligence (AI) will play an important role in improving network efficiency and providing high-quality service. As a rapid evolving paradigm, the AI-empowered mobile communications demand large amounts of data acquired from real network environment for systematic test and verification. Hence, we build the world's first true-data testbed for 5G/B5G intelligent network (TTIN), which comprises 5G/B5G on-site experimental networks, data acquisition & data warehouse, and AI engine & network optimization. In the TTIN, true network data acquisition, storage, standardization, and analysis are available, which enable system-level online verification of B5G/6G-orientated key technologies and support data-driven network optimization through the closed-loop control mechanism. This paper elaborates on the system architecture and module design of TTIN. Detailed technical specifications and some of the established use cases are also showcased.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Nov 2020.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 2; 2025: 1.
5 papers.
- 2021Hybrid Policy Learning for Energy-Latency Tradeoff in MEC-Assisted VR Video Servicecited by 5
- 2024Learning Wireless Data Knowledge Graph for Green Intelligent Communications: Methodology and Experimentscited by 2
- 2022Representation Learning of Knowledge Graph for Wireless Communication Networkscited by 0
- 2024Random Aggregate Beamforming for Over-the-Air Federated Learning in Large-Scale Networkscited by 0
- 2025A Theoretical Analysis of State Similarity Between Markov Decision Processescited by 0
- 2025A Theoretical Analysis of State Similarity Between Markov Decision Processes19 Dec 2025
- 2024Learning Wireless Data Knowledge Graph for Green Intelligent Communications: Methodology and Experiments16 Apr 2024
- 2024Random Aggregate Beamforming for Over-the-Air Federated Learning in Large-Scale Networks20 Feb 2024
- 2022Representation Learning of Knowledge Graph for Wireless Communication Networks22 Aug 2022
- 2021Hybrid Policy Learning for Energy-Latency Tradeoff in MEC-Assisted VR Video Service2 Apr 2021