March 4, 2024, 5:42 a.m. | Jinhyun So, Hyukjoon Kwon

cs.LG updates on arXiv.org arxiv.org

arXiv:2403.00299v1 Announce Type: cross
Abstract: Existing auto-encoder (AE)-based channel state information (CSI) frameworks have focused on a specific configuration of user equipment (UE) and base station (BS), and thus the input and output sizes of the AE are fixed. However, in the real-world scenario, the input and output sizes may vary depending on the number of antennas of the BS and UE and the allocated resource block in the frequency dimension. A naive approach to support the different input and …

abstract arxiv auto cs.ai cs.it cs.lg eess.sp encoder equipment feedback framework frameworks information math.it state type universal world

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US

Research Engineer

@ Allora Labs | Remote

Ecosystem Manager

@ Allora Labs | Remote

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US