Large-Scale and Hierachical Bayesian Inference for Future Mobile Communication Networks

• Applicant: Professor Dr.-Ing. Gerhard P. Fettweis, since 2/2019
• Subject Area: Electronic Semiconductors, Components and Circuits, Integrated Systems, Sensor Technology, Theoretical Electrical Engineering
• Term: from 2018 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 392016367

A significant increase of the network capacity, which is required to cope with the explosive growth of mobile data traffic, will be enabled by the use of massive multiple-input multiple-output (MIMO) and millimeter wave communication technologies. Non-orthogonal multiple access and network densification can further improve the efficiency of resource utilization. Overall, they will create a communication environment with rich inter-user interference and yield a variety of large-scale signal processing problems. In this environment, cloud technologies enable joint signal processing across the network, leading to a hierarchical network structure. In order to harness the benefits of new radio access techniques and hierarchical network structures, advanced signal processing techniques play a vital role. By exploiting the statistical input-output relations in the communication system, Bayesian inference permits to systematically solve the involved signal processing problems. On the other hand, the new radio access techniques and the hierarchical network structures foreseen for future communication systems will considerably change the statistical system models that we are familiar with today. This project contributes to the investigation of Bayesian inference techniques, particularly for addressing large-scale and hierarchical signal processing problems in future communication systems.The research topics in this project proposal include: 1) the development of mathematical tools for large-scale and hierarchical Bayesian inference, and 2) their application for solving practical large-scale and hierarchical signal processing problems. The developed approaches will be validated by assessing their performance with respect to 1) the theoretical limits and 2) state-of-the-art approaches in realistic scenarios. The results of this project will be an enabler of advances in signal processing for next generation communications systems.

• DFG Programme: Research Grants
• International Connection: China
• Partner Organisation: National Natural Science Foundation of China
• Cooperation Partner: Dr. Wenjin Wang
• Ehemalige Antragstellerin: Dr.-Ing. Dan Zhang, until 1/2019