Internet of radio and light: 5G building network radio and edge architecture

Zhang, Yue; Zhang, Hequn; Cosmas, John; Jawad, Nawar; Ali, Kareem; Meunier, Ben; Kapovits, Adam; Huang, Li-Ke; Li, Wei; Shi, Lina; Zhang, Xun; Wang, Jintao; Koffman, Israel; Robert, Muller; Zarakovitis, Charilaos C.

doi:10.23919/icn.2020.0002

Cited by 24 publications

(11 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The 5G multicomponent carrier indoor system contains six main components for both VLC and mmWave measurement campaign [1]. 1) A 5G base station including PHY Layer Central Unit, named DRAN (Distributed Radio Access Network) and RRLH Control Units.…”

Section: Methodsmentioning

confidence: 99%

Measurement Campaign on 5G Indoor Millimeter Wave and Visible Light Communications Multi Component Carrier System

Ali

Cosmas

Zhang

et al. 2022

IEEE Trans. on Broadcast.

Self Cite

View full text Add to dashboard Cite

This paper presents the technical performance results of a measurement campaign from a 5G indoor millimeter Wave (mmWave) and Visible Light Communications (VLC) multi component carrier system, which was developed in a Horizon 2020 research project called Internet of Radio-Light (IoRL). The measurement campaign was performed in the famous Integer House laboratory at the Innovation Park in Building Research Establishment in Watford, UK, which represents a typical European home environment. It includes four field test results: 1)VLC received signal quality measured as Error Vector Magnitude (EVM) against coverage, 2) mmWave received signal quality measured as EVM against coverage, 3) VLC location accuracy against a prescribed grid using received signal strength, 4) Comparison of measured and simulated Electromagnetic Field (EMF) strength against coverage. This measurement campaign not only tests the system concept in a realistic indoor home environment but also provides analysis of the results with practical recommendations on further technical enhancements required to improve the system performance and insights into viable commercial solutions and applications.Other environments in which this technology could be deployed were envisaged as: underground train platforms and tunnels, museums and supermarkets.

show abstract

Section: Methodsmentioning

confidence: 99%

Measurement Campaign on 5G Indoor Millimeter Wave and Visible Light Communications Multi Component Carrier System

Ali

Cosmas

Zhang

et al. 2022

IEEE Trans. on Broadcast.

Self Cite

View full text Add to dashboard Cite

show abstract

“…It can use the collected data for pattern recognition, dimensionality reduction, intelligent processing, and other functions and directly face computer room users. At present, large data processing has stepped from the era of centralized processing centered on cloud computing into the era of edge computing centered on the interconnection of all things [ 21 ]. In the large centralized data processing era, more is centralized storage and processing of large data.…”

Section: Iot Architecture and Edge Computing Model For Energy Consump...mentioning

confidence: 99%

Research on energy saving of computer rooms in Chinese colleges and universities based on IoT and edge computing technology

2022

Heliyon

View full text Add to dashboard Cite

“…AI technology has been applied in many fields [12][13][14][15]. Enterprises usually utilize the maturity model related to technologies to appreciate the capabilities of technologies and improve enterprises' capability to apply technologies [16].…”

Section: Related Workmentioning

confidence: 99%

A maturity model for AI-empowered cloud-native databases: from the perspective of resource management

et al. 2022

View full text Add to dashboard Cite

Cloud-native database systems have started to gain broad support and popularity due to more and more applications and systems moving to the cloud. Various cloud-native databases have been emerging in recent years, but their developments are still in the primary stage. At this stage, database developers are generally confused about improving the performance of the database by applying AI technologies. The maturity model can help database developers formulate the measures and clarify the improvement path during development. However, the current maturity models are unsuitable for cloud-native databases since their architecture and resource management differ from traditional databases. Hence, we propose a maturity model for AI-empowered cloud-native databases from the perspective of resource management. We employ a systematic literature review and expert interviews to conduct the maturity model. Also, we develop an assessment tool based on the maturity model to help developers assess cloud-native databases. And we provide an assessment case to prove our maturity model. The assessment case results show that the database’s development direction conforms to the maturity model. It proves the effectiveness of the maturity model.

show abstract

Internet of radio and light: 5G building network radio and edge architecture

Cited by 24 publications

References 10 publications

Measurement Campaign on 5G Indoor Millimeter Wave and Visible Light Communications Multi Component Carrier System

Measurement Campaign on 5G Indoor Millimeter Wave and Visible Light Communications Multi Component Carrier System

Research on energy saving of computer rooms in Chinese colleges and universities based on IoT and edge computing technology

A maturity model for AI-empowered cloud-native databases: from the perspective of resource management

Contact Info

Product

Resources

About