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A New Look at Cell-Free Massive MIMO : Making It Practical With Dynamic Cooperation
Abstract
This paper takes a new look at Cell-free Massive MIMO (multiple-input multiple-output) through the lens of the dynamic cooperation cluster framework from the Network MIMO literature. The purpose is to identify and address scalability issues that appear in prior work. We provide distributed algorithms for initial access, pilot assignment, cluster formation, precoding, and combining that are scalable in the sense of being implementable with arbitrarily many users. Interestingly, the suggested precoding and combining outperform conjugate beamforming and matched filtering, respectively, while also being fully distributed.Funding agencies: ELLIIT; Wallenberg AI, Autonomous Systems and Software Program (WASP); University of Pisa under the PRA 2018-2019 Research Project CONCEPT</p- Conference paper
- info:eu-repo/semantics/conferenceObject
- text
- array signal processing;matched filters;MIMO communication;precoding;cell-free massive MIMO;dynamic cooperation cluster framework;combining outperform conjugate beamforming;network MIMO literature;precoding;matched filtering;Cell-free Massive MIMO;dynamic cooperation clustering;scalability;combining and precoding
- Communication Systems
- Kommunikationssystem
- Telecommunications
- Telekommunikation
- Signal Processing
- Signalbehandling