Sparse Bayesian learning, beamforming techniques and asymptotic analysis for massive MIMO (2020)
Abstract / truncated to 115 words
Multiple antennas at the base station side can be used to enhance the spectral efficiency and energy efficiency of the next generation wireless technologies. Indeed, massive multi-input multi-output (MIMO) is seen as one promising technology to bring the aforementioned benefits for fifth generation wireless standard, commonly known as 5G New Radio (5G NR). In this monograph, we will explore a wide range of potential topics in multi-user MIMO (MU-MIMO) relevant to 5G NR, • Sum rate maximizing beamforming (BF) design and robustness to partial channel state information at the transmitter (CSIT) • Asymptotic analysis of the various BF techniques in massiveMIMO and • Bayesian channel estimationmethods using sparse Bayesian learning. While massive MIMO has the ...
sparse bayesian learning – massive mimo beamforming – large system analysis – random matrix theory – message passing.
Information
- Author
- Christo Kurisummoottil Thomas
- Institution
- EURECOM ( SORBONNE UNIVERSITY, FRANCE)
- Supervisor
- Publication Year
- 2020
- Upload Date
- Sept. 30, 2021
First few pages / click to enlarge
The current layout is optimized for mobile phones. Page previews, thumbnails, and full abstracts will remain hidden until the browser window grows in width.
The current layout is optimized for tablet devices. Page previews and some thumbnails will remain hidden until the browser window grows in width.