Web: http://arxiv.org/abs/2206.04967

June 16, 2022, 1:11 a.m. | Xin Wang, Xiaolin Hou, Lan Chen, Yoshihisa Kishiyama, Takahiro Asai

cs.LG updates on arXiv.org arxiv.org

Recently, inspired by successful applications in many fields, deep learning
(DL) technologies for CSI acquisition have received considerable research
interest from both academia and industry. Considering the practical feedback
mechanism of 5th generation (5G) New radio (NR) networks, we propose two
implementation schemes for artificial intelligence for CSI (AI4CSI), the
DL-based receiver and end-to-end design, respectively. The proposed AI4CSI
schemes were evaluated in 5G NR networks in terms of spectrum efficiency (SE),
feedback overhead, and computational complexity, and compared with …

5g acquisition arxiv deep deep learning evolution learning massive

More from arxiv.org / cs.LG updates on arXiv.org

Machine Learning Researcher - Saalfeld Lab

@ Howard Hughes Medical Institute - Chevy Chase, MD | Ashburn, Virginia

Project Director, Machine Learning in US Health

@ ideas42.org | Remote, US

Data Science Intern

@ NannyML | Remote

Machine Learning Engineer NLP/Speech

@ Play.ht | Remote

Research Scientist, 3D Reconstruction

@ Yembo | Remote, US

Clinical Assistant or Associate Professor of Management Science and Systems

@ University at Buffalo | Buffalo, NY