公开(公告)号：US12273167B2

公开(公告)日：2025-04-08

申请号：US17636887

申请日：2020-08-31

Applicant: Google LLC

Inventor： Erik Richard Stauffer ,  Jibing Wang ,  Aamir Akram ,  Vijay L. Asrani

IPC: H04B7/06 ,  H04B1/036

Abstract: A user equipment (UE) manages thermal levels of antenna modules with reference to a temperature threshold. The UE includes multiple antenna modules having a first antenna module and a second antenna module and at least one wireless transceiver coupled to the multiple antenna modules. The UE also includes a processor and memory system implementing an antenna module thermal manager. The manager is configured to obtain a first temperature indication corresponding to the first antenna module of the multiple antenna modules. The manager is also configured to perform a comparison of the first temperature indication to at least one temperature threshold. The manager is further configured to switch, based on the comparison, from using the first antenna module to using the second antenna module for wireless communication with the at least one wireless transceiver.

公开(公告)号：US20240419953A1

公开(公告)日：2024-12-19

申请号：US18701168

申请日：2022-10-12

Applicant: Google LLC

Inventor： Jibing Wang ,  Erik Stauffer

IPC: G06N3/0495 ,  H04W72/04

Abstract: Aspects describe communicating quantized machine-learning, ML, configuration information over a wireless network. A base station selects (605) a quantization configuration for quantizing ML configuration information for a deep neural network, DNN, where the quantization configuration indicates one or more quantization formats associated with quantizing the ML configuration information. The base station transmits (610) an indication of the quantization configuration to a user equipment, UE and transfers (615), over the wireless network and with the UE, quantized ML configuration information using the quantization configuration.

公开(公告)号：US12170940B2

公开(公告)日：2024-12-17

申请号：US18127893

申请日：2023-03-29

Applicant: Google LLC

Inventor： Jibing Wang ,  Erik Richard Stauffer ,  Qin Zhang

IPC: H04W4/80 ,  H04L5/14 ,  H04L41/0806 ,  H04W76/11 ,  H04W76/15

Abstract: The subject matter described herein provides systems and techniques to automatically configure a proximal device, such as a smart watch, a tablet, or any other smart device, based on configuration information sent from the user equipment (UE) to the proximal device when the local communications connection, such as a wireless connection, between the devices is weak. If it is determined that there is a weak local communications connection between the UE and the proximal device the UE may automatically send network configuration information to the proximal device. If it is determined that there is a weak local communications connection between the UE and the proximal device the UE may automatically turn on its mobile hotspot, and automatically send the mobile hotspot configuration information to the proximal device.

公开(公告)号：US20240373336A1

公开(公告)日：2024-11-07

申请号：US18774080

申请日：2024-07-16

Applicant: Google LLC

Inventor： Jibing Wang ,  Erik Richard Stauffer

IPC: H04W48/18 ,  G06F18/20 ,  H04L41/16 ,  H04W8/08 ,  H04W24/10 ,  H04W64/00

Abstract: This document describes techniques and devices for determining a machine-learning architecture. A user equipment (UE) transmits, to a network-slice manager of a wireless network, a first machine-learning architecture request message to request permission to use a first machine-learning architecture. The UE receives a first machine-learning architecture response message that grants permission to use the first machine-learning architecture based on a first network slice, the first machine-learning architecture forming a portion of at least one first end-to-end machine-learning architecture associated with the first network slice, the at least one first end-to-end machine-learning architecture being a distributed machine-learning architecture that is configured to process wireless communication signals and is formed by the first machine-learning architecture implemented by the user equipment, a machine-learning architecture implemented by a base station, and a machine-learning architecture implemented by an entity of a core network. The UE wirelessly communicates data using the first machine-learning architecture.

公开(公告)号：US12127179B2

公开(公告)日：2024-10-22

申请号：US17413494

申请日：2020-01-10

Applicant: GOOGLE LLC

Inventor： Erik Stauffer ,  Jibing Wang

IPC: H04W72/044 ,  H04W16/14

CPC classification number: H04W72/046 ,  H04W16/14

Abstract: The systems, methods, and techniques described in this disclosure allow different wireless systems that operate in accordance with different Radio Access Technologies (RATs) to coexist within a same frequency domain with minimal (if any) inter-RAT interference. Specifically, the described techniques allocate a respective, mutually-exclusive portion of a plurality of Space-Time-Frequency (STF) resources for use in communicating in accordance with each different RAT. For example, mutually-exclusive portions of spatial domain resources, time domain resources, and/or frequency domain resources may be respectively allocated for exclusive use by different RATs. A centralized, third-party controller (120) may perform the allocations, or the allocations may be cooperatively arrived at between systems supporting different RATs, e.g., in a peer-to-peer manner. STF resource allocations may be static and/or dynamic over time, and STF resources may be uniquely identified by respective resource identifiers.

公开(公告)号：US20240241222A1

公开(公告)日：2024-07-18

申请号：US18557849

申请日：2022-05-02

Applicant: Google LLC

Inventor： Jibing Wang ,  Erik Richard Stauffer

IPC: G01S7/41 ,  G01S13/00

CPC classification number: G01S7/417 ,  G01S7/411 ,  G01S13/003

Abstract: Techniques and apparatuses are described that implement cooperative bistatic radar sensing using deep neural networks. In particular, a base station (120) operates as a transmitter of the bistatic radar, and the user equipment (110) operates as a receiver of the bistatic radar. During radar sensing, the base station (120) and the user equipment (110) use their respective deep neural networks (460 and 420) for signal generation and signal processing. The deep neural networks (460 and 420) also enable the base station (120) and the user equipment (110) to utilize the same hardware for both radar sensing and wireless communication. With cooperative bistatic radar sensing, the base station (120) and the user equipment (110) can compile explicit information about objects within an operating environment and use this information to improve wireless communication performance.

公开(公告)号：US20240236862A1

公开(公告)日：2024-07-11

申请号：US18554428

申请日：2022-03-23

Applicant: Google LLC

Inventor： Jibing Wang ,  Erik Stauffer

IPC: H04W52/02

CPC classification number: H04W52/0261

Abstract: Techniques for improving, for a set of conditions at a UE, the usage of energy stored at a UE include determining a preferred or requested partitioning of the UE's stored energy usage during wireless data transfer between the UE and the base station (e.g., an amount or percentage of stored energy utilized by the UE for baseband signal processing with respect to the amount or percentage of energy utilized by the UE for radio interface signal processing tasks), and indicating the preferred partitioning to the base station or network. Based on the indication, the base station/network may modify the baseband communication scheme, parameters, and/or values, and/or the radio interface communication scheme, parameters, and/or values utilized for the wireless transfers of data between the base station and the UE, thereby better managing (and in some cases, optimizing) the UE's stored energy usage and increasing battery life at the UE.

公开(公告)号：US12020158B2

公开(公告)日：2024-06-25

申请号：US18306010

申请日：2023-04-24

Applicant: Google LLC

Inventor： Jibing Wang ,  Erik Richard Stauffer

IPC: G06N3/08 ,  G06N3/04 ,  H04B7/026

CPC classification number: G06N3/08 ,  G06N3/04 ,  H04B7/026

Abstract: Techniques and apparatuses are described for deep neural network (DNN) processing for a user equipment-coordination set (UECS). A network entity selects (910) an end-to-end (E2E) machine-learning (ML) configuration that forms an E2E DNN for processing UECS communications. The network entity directs (915) each device of multiple devices participating in an UECS to form, using at least a portion of the E2E ML configuration, a respective sub-DNN of the E2E DNN that transfers the UECS communications through the E2E communication, where the multiple devices include at least one base station, a coordinating user equipment (UE), and at least one additional UE. The network entity receives (940) feedback associated with the UECS communications and identifies (945) an adjustment to the E2E ML configuration. The network entity then directs at least some of the multiple devices participating in an UECS to update the respective sub-DNN of the E2E DNN based on the adjustment.

公开(公告)号：US12015459B2

公开(公告)日：2024-06-18

申请号：US17997587

申请日：2021-05-17

Applicant: Google LLC

Inventor： Jibing Wang ,  Erik Richard Stauffer

IPC: H04B7/0456 ,  H04B7/026 ,  H04B7/06

CPC classification number: H04B7/0456 ,  H04B7/026 ,  H04B7/0617

Abstract: Techniques and apparatuses are described for modifying a position of an adaptive phase-changing device, APD. In aspects, a base station receives, from a user equipment, UE, at least one link quality parameter that is indicative of a channel impairment. The base station then identifies, using the at least one link quality parameter, a surface configuration for a reconfigurable intelligent surface (RIS) of an adaptive phase-changing device (APD) and transmits a first indication of the surface configuration using an adaptive phase-changing device control channel, APD control channel. In aspects, the base station determines using the at least one link quality parameter, a position configuration for the APD and transmits a second indication of the position configuration to the APD. The base station then communicates with the UE using the APD.

公开(公告)号：US20240188031A1

公开(公告)日：2024-06-06

申请号：US18281873

申请日：2022-03-09

Applicant: GOOGLE LLC

Inventor： Jibing Wang ,  Aamir Akram ,  Erik Richard Stauffer ,  Sharath Ananth

IPC: H04W64/00 ,  H04W76/15 ,  H04W84/06

CPC classification number: H04W64/006 ,  H04W76/15 ,  H04W84/06

Abstract: A UE receives satellite ephemeris information from a server server and calculates one or more satellite parameters for at least one satellite based on the satellite ephemeris information. The UE controls, based on the one or more satellite parameters, operation of a software application that utilizes a data service provided via the at least one satellite. Calculating satellite parameters can include calculating one or more satellite parameters at an API of the UE, and controlling operation of a software application can include receiving, at the API, a request for satellite ephemeris information from the software application, providing, by the API, a representation of the one or more satellite parameters to the software application in response to the request, and adjusting, at the software application, an operation of the software application based on the received representation of the one or more satellite parameters.