LOW COMPLEXITY MACHINE LEARNING-BASED CHANNEL STATE INFORMATION COMPRESSION

Title:

LOW COMPLEXITY MACHINE LEARNING-BASED CHANNEL STATE INFORMATION COMPRESSION

Document Type and Number:

WIPO Patent Application WO/2024/032089

Kind Code:

A1

Abstract:

This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for low-complexity ML-based CSI compression (270a). A UE (102) receives (240), from a network entity (104), a CSI-RS for a channel estimation (250). The UE (102) sends (285), to the network entity (104), a CSI report including a first PMI and a second PMI. The first PMI indicates a wideband preceder (355) associated with the channel estimation (250) and the second PMI indicates a compressed subband eigenvecter associated with the wideband preceder (355).

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Inventors:

ZHANG YUSHU (CN)
WU CHIH-HSIANG (CN)

Application Number:

PCT/CN2023/096258

Publication Date:

February 15, 2024

Filing Date:

May 25, 2023

Export Citation:

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Assignee:

GOOGLE LLC (US)
ZHANG YUSHU (CN)

International Classes:

H04B7/06

Foreign References:

US20140177744A1

2014-06-26

Other References:

QUALCOMM INCORPORATED: "Other aspects on AI/ML for CSI feedback enhancement", vol. RAN WG1, no. e-Meeting; 20220509 - 20220520, 29 April 2022 (2022-04-29), XP052144134, Retrieved from the Internet [retrieved on 20220429]

Attorney, Agent or Firm:

CHINA SINDA INTELLECTUAL PROPERTY LIMITED (CN)

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