- Next-generation Private Network Technology
Research in this area focuses on the R&D and innovations of the 5G/6G mobile communications system in the industrial private network field. In line with the needs of industrial customers, the XG Lab has developed technologies in fields such as communications protocols, AI, and the integration of networks and cloud services. The XG Lab works closely with ecosystem partners and delivers key technological innovations for clouds, networks, edges, and devices. The research aims to build maintenance-free, low-cost, and easily iterated industrial private networks and develop digital intelligence technologies that are fundamental to digital transformations in all industries.
- Mobile Network Transmission Technology
Research in this area focuses on the optimization of high-performance streaming media transmission protocols for 5G and next-generation mobile networks. The research aims to resolve packet loss and transmission latency issues and improve the user experience of streaming data transmission over mobile networks. The research covers fields such as mobile network visualization, multipath scheduling, lightweight network encoding, and QoE-driven network congestion control.
- Video Encoding and Decoding Technology
Research in this area focuses on the development of cutting-edge video encoding and decoding technologies for 5G and next-generation networks. The research aims to achieve narrowband HD and broadband UHD, which will significantly boost the development of video applications. The XG Lab develops technologies and products related to UHD videos, immersive videos, and real-time rendering on the cloud, and empowers new applications. It also develops the video encoding and decoding technology based on deep learning, and plays a leading role in the formulation of international and Chinese video-specific standards.
- 5G Application Technology
Research in this area focuses on developing innovative application technologies for 5G. 5G delivers high-bandwidth, low-latency connectivity and promises the collaboration of clouds, networks, edges, and devices. The research aims to make innovations in application and network systems and develop real-time rendering on the cloud, real-time 3D modeling, AR/VR, and UHD immersive video products and services. The research contributes to better user experiences of devices and gives birth to new applications and values for 5G.
Ming Zhang holds a PhD in computer science from Princeton University, USA. His research interests include 5G, edge networks, cloud data center networks, and backbone networks. Before joining Alibaba, he was a senior researcher of Microsoft Research Asia and responsible for research on key cloud networking technologies of Microsoft Azure. He published many forward-looking and influential papers in world-class academic conferences and journals, and was invited to serve as a reviewer at world-class academic conferences (such as ACM SIGCOMM).
- Y. Ye, J. Boyce, P. Hanhart, Omnidirectional 360° Video Coding Technology in Responses to the Joint Call for Proposals on Video Compression With Capability Beyond HEVC, IEEE Transactions on Circuit and Systems for Video Technology, special section on the joint Call for Proposals on video compression with capability beyond HEVC, Volume: 30, Issue: 5, pp. 1241-1252, May 2020.
- H. Gao, R.-L. Liao, K. Reuz, S. Esenlik, E. Alshina, Y. Ye, J. Chen, J. Luo, C.-C. Chen, H. Huang, W.-J. Chien, V. Seregin, M. Karczewicz, Advanced Geometric-based Inter Prediction for Versatile Video Coding, IEEE Data Compression Conference (DCC), 2020.
- T. Lu, F. Pu, P. Yin, S. McCarthy, W. Husak, T. Chen, E. Francois, C. Chevance, F. Hiron, J. Chen, R.-L. Liao, Y. Ye, J. Luo, Luma Mapping with Chroma Scaling in Versatile Video Coding, IEEE Data Compression Conference (DCC), 2020.
