Dynamic Network Slicing
- A network slicing management framework of 5G ultra-dense networks. A multilayer network model is used to represent the topology of multi-slices and infrastructure network from a global perspective. With this model, the physical resources can be allocated to massive slices efficiently.
- A service-oriented deployment policy of end-to-end network slicing. Three different deployment algorithms are investigated to deploy end-to-end slices. Complex network theory is adopted to improve the resource efficiency and acceptance ratio of slices.
- On-demand cooperation among multiple infrastructure networks for multi-tenant slicing. The impact of topology properties on the cooperation among multiple infrastructure networks is analyzed. An on-demand cooperation strategy is proposed for improving the delay performance of slices.
Service Based 6G networking
Our team has already done some related work on the service based network. We have researched on the service based architecture for 5G network and proposed some proposals to ITU and 3GPP in cooperation with China Mobile. We have developed the world’s first service-oriented network slice management and orchestration prototype system in 2017. It can realize flexible network slicing management, dynamic service orchestration and flexible scaling, also it can support the typical application scenarios of eMBB, mIoT network slice creation and management in 5G networks, and the implementation of end-to-end services.
Beam Management in MmWave Massive MIMO Systems
The mmWave Massive MIMO systems are envisioned to provide gigabit wireless access in the near future. However, due to the unfavorable propagation characteristics of the mmWave, beam management is crucial for the reliable communications in mmWave Massive MIMO systems. Specially, we focus on the following beam management problems:
- Beam handover in V2I: How to efficiently choose the optimal beam for the high-speed vehicles so as to provide seamless handover.
- The performance analysis of hybrid beamforming with channel non-reciprocity and imperfect CSI: How does the hybrid beamforming perform in the case where there exists channel non-reciprocity and CSI uncertainty.
- Robust hybrid beamforming design under channel non-reciprocity and imperfect CSI: How to design robust hybrid beamforming that can still achieve outstanding performance under the channel non-reciprocity and imperfect CSI.
Spectrum and Interference Management for Heterogeneous Networks
Due to the scarcity of the spectrum resources and severe interference problems in the heterogeneous networks, we research the spectrum and interference management for heterogeneous networks, to achieve the efficient utilization and management of spectrum resources in wireless communication systems.
Firstly, we research spectrum sharing strategies and novel spectrum management mechanisms in the heterogeneous networks. Aim to achieve the synchronous transmission at the same frequency in the heterogeneous networks.
Secondly, as for the problem of interference management in a network of heterogeneous networks. We study how to cancel interference by using an interference cancellation scheme, include parallel interference cancellation (PIC) and successive interference cancellation (SIC).