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Google patents method to compress wireless channel data using machine learning

Google describes a way for mobile devices to send less data to cell towers by using machine learning to compress information about the wireless signal. The device can also skip parts of the report if the data size gets too large, and it can process these compressed reports alongside standard ones at the same time.

Why it mattersThis is a technical improvement that could help make 5G and future networks more efficient by reducing the amount of data phones need to send to towers.

In the filing’s own words

This disclosure describes CSI reports based on ML techniques. A UE receives one or more CSI-RSs from a network entity for generating one or more CSI reports. When at least one CSI report is based on an ML model, the UE may compress the at least one CSI report with a selected wideband precoder using one or more subband eigenvectors for one or more precoded estimated subband channels. The UE may also omit at least a portion of the at least one CSI report when a total payload size of the one or more CSI reports exceeds a threshold. The UE may be configured for parallel processing of a plurality of CSI reports that are based on the ML model and/or parallel processing of a first CSI report based on the ML model and a second CSI report that is not based on the ML model.

What exactly they claim (claim 1)

1 - 19. (canceled)

Facts

Company
Google (Google LLC)
Official title
CSI REPORTS BASED ON ML TECHNIQUES
Publication number
US20260261306A1
Application number
18994557
Filed
Aug 12, 2022
Published
Sep 3, 2026
Inventors
2
Claims
21

Classified under

H04B 7/0626 Electricity & electronicsH04L 41/16 Electricity & electronics
Read the full filing (official PDF) ↗ Open in the Patent Tracker

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Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.