Reduced Complexity Techniques and Performance Analysis towards 6G Cell-Free Massive MIMO

• Applicant: Professorin Laura Cottatellucci, Ph.D.
• Subject Area: Communication Technology and Networks, High-Frequency Technology and Photonic Systems, Signal Processing and Machine Learning for Information Technology
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 491320625

Distributed antenna systems (DAS) are expected to play a fundamental role in next generation wireless systems. In DASs, access points (AP) are distributed over a wide area and connected to a centralized processing unit. They present great potential to enhancespectral and power efficiency compared to traditional cellular systems with centralized base stations (BS). We have analyzed the capacity of DASs, leveraging on a mathematical framework based on Euclidean random matrices. To reap the benefits promised bythis analysis, the use of a centralized optimal joint processing is crucial. However, an optimal maximum likelihood detector has an unaffordable complexity for large systems. Interestingly, in centralized massive MIMO systems, the channels between users and BStend to become jointly orthogonal, allowing low complexity matched filters to attain the same performance as maximum likelihood detectors, asymptotically. In Cell-Free DAS however, more sophisticated receivers are needed.

• DFG Programme: Research Grants
• International Connection: France
• Cooperation Partner: Professor Dr. Dirk Slock