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    Learning and deploying compression of radio signals
    12.
    发明授权
    Learning and deploying compression of radio signals 有权

    公开(公告)号：US11632181B2

    公开(公告)日：2023-04-18

    申请号：US16798490

    申请日：2020-02-24

    Applicant: Virginia Tech Intellectual Properties, Inc.

    Inventor： Timothy James O'Shea

    IPC: G06N3/04 ,  H04B17/30 ,  H04W24/08 ,  G06N20/00 ,  G06N3/045 ,  G06N3/08

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and deploying machine-learned compact representations of radio frequency (RF) signals. One of the methods includes: determining a first RF signal to be compressed; using an encoder machine-learning network to process the first RF signal and generate a compressed signal; calculating a measure of compression in the compressed signal; using a decoder machine-learning network to process the compressed signal and generate a second RF signal that represents a reconstruction of the first RF signal; calculating a measure of distance between the second RF signal and the first RF signal; and updating at least one of the encoder machine-learning network or the decoder machine-learning network based on (i) the measure of distance between the second RF signal and the first RF signal, and (ii) the measure of compression in the compressed signal.

    Learning and deployment of adaptive wireless communications
    13.
    发明授权
    Learning and deployment of adaptive wireless communications 有权

    公开(公告)号：US11423301B2

    公开(公告)日：2022-08-23

    申请号：US16281246

    申请日：2019-02-21

    Applicant: Virginia Tech Intellectual Properties, Inc.

    Inventor： Timothy James O'Shea

    IPC: G06N3/08 ,  G06N3/04

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and deploying machine-learned communication over radio frequency (RF) channels. One method includes: determining an encoder and a decoder, at least one of which is configured to implement an encoding or decoding that is based on at least one of an encoder machine-learning network or a decoder machine-learning network that has been trained to encode or decode information over a communication channel; determining first information; using the encoder to process the first information and generate a first RF signal; transmitting, by at least one transmitter, the first RF signal through the communication channel; receiving, by at least one receiver, a second RF signal that represents the first RF signal altered by transmission through the communication channel; and using the decoder to process the second RF signal and generate second information as a reconstruction of the first information.

    Encoding and decoding of information for wireless transmission using multi-antenna transceivers
    14.
    发明授权
    Encoding and decoding of information for wireless transmission using multi-antenna transceivers 有权

    公开(公告)号：US11381286B2

    公开(公告)日：2022-07-05

    申请号：US17145501

    申请日：2021-01-11

    Applicant: Virginia Tech Intellectual Properties, Inc.

    Inventor： Timothy James O'Shea ,  Tugba Erpek

    IPC: H04B7/02 ,  H04B7/0452 ,  G06N3/08 ,  H04B7/0413 ,  G06N3/04 ,  H04B7/06 ,  G06N3/00

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and deploying machine-learned communication over multi-input-multi-output (MIMO) channels. One of the methods includes: determining a transmitter and a receiver, at least one of which implements a machine-learning network; determining a MIMO channel model; determining first information; using the transmitter to process the first information and generate first RF signals representing inputs to the MIMO channel model; determining second RF signals representing outputs of the MIMO channel model, each second RF signal representing aggregated reception of the first RF signals altered by transmission through the MIMO channel model; using the receiver to process the second RF signals and generate second information as a reconstruction of the first information; calculating a measure of distance between the second and first information; and updating the machine-learning network based on the measure of distance between the second and first information.

    Encoding and decoding of information for wireless transmission using multi-antenna transceivers
    15.
    发明授权
    Encoding and decoding of information for wireless transmission using multi-antenna transceivers 有权

    公开(公告)号：US10892806B2

    公开(公告)日：2021-01-12

    申请号：US16421694

    申请日：2019-05-24

    Applicant: Virginia Tech Intellectual Properties, Inc.

    Inventor： Timothy James O'Shea ,  Tugba Erpek

    IPC: H04B7/04 ,  H04B7/0452 ,  G06N3/08 ,  H04B7/0413 ,  G06N3/04 ,  H04B7/06 ,  G06N3/00

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and deploying machine-learned communication over multi-input-multi-output (MIMO) channels. One of the methods includes: determining a transmitter and a receiver, at least one of which implements a machine-learning network; determining a MIMO channel model; determining first information; using the transmitter to process the first information and generate first RF signals representing inputs to the MIMO channel model; determining second RF signals representing outputs of the MIMO channel model, each second RF signal representing aggregated reception of the first RF signals altered by transmission through the MIMO channel model; using the receiver to process the second RF signals and generate second information as a reconstruction of the first information; calculating a measure of distance between the second and first information; and updating the machine-learning network based on the measure of distance between the second and first information.

    Learning and deploying compression of radio signals
    16.
    发明授权
    Learning and deploying compression of radio signals 有权

    公开(公告)号：US10572830B2

    公开(公告)日：2020-02-25

    申请号：US15961454

    申请日：2018-04-24

    Applicant: Virginia Tech Intellectual Properties, Inc.

    Inventor： Timothy James O'Shea

    IPC: G06N99/00 ,  G06N3/08 ,  G06N20/00 ,  H04W24/08

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and deploying machine-learned compact representations of radio frequency (RF) signals. One of the methods includes: determining a first RF signal to be compressed; using an encoder machine-learning network to process the first RF signal and generate a compressed signal; calculating a measure of compression in the compressed signal; using a decoder machine-learning network to process the compressed signal and generate a second RF signal that represents a reconstruction of the first RF signal; calculating a measure of distance between the second RF signal and the first RF signal; and updating at least one of the encoder machine-learning network or the decoder machine-learning network based on (i) the measure of distance between the second RF signal and the first RF signal, and (ii) the measure of compression in the compressed signal.

    Learning and deploying compression of radio signals
    17.
    发明授权
    Learning and deploying compression of radio signals 有权

    公开(公告)号：US12293297B2

    公开(公告)日：2025-05-06

    申请号：US18135259

    申请日：2023-04-17

    Applicant: Virginia Tech Intellectual Properties, Inc.

    Inventor： Timothy James O'Shea

    IPC: G06N3/086 ,  G06N3/045 ,  G06N3/08 ,  G06N20/00 ,  H04B17/30 ,  H04W24/08

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and deploying machine-learned compact representations of radio frequency (RF) signals. One of the methods includes: determining a first RF signal to be compressed; using an encoder machine-learning network to process the first RF signal and generate a compressed signal; calculating a measure of compression in the compressed signal; using a decoder machine-learning network to process the compressed signal and generate a second RF signal that represents a reconstruction of the first RF signal; calculating a measure of distance between the second RF signal and the first RF signal; and updating at least one of the encoder machine-learning network or the decoder machine-learning network based on (i) the measure of distance between the second RF signal and the first RF signal, and (ii) the measure of compression in the compressed signal.

    Learning approximate estimation networks for communication channel state information
    18.
    发明授权
    Learning approximate estimation networks for communication channel state information 有权

    公开(公告)号：US12223443B1

    公开(公告)日：2025-02-11

    申请号：US18218855

    申请日：2023-07-06

    Applicant: Virginia Tech Intellectual Properties, Inc.

    Inventor： Timothy James O'Shea ,  Kiran Karra ,  T. Charles Clancy

    IPC: H04B17/309 ,  G06N3/02 ,  G06N5/046 ,  G06N20/00 ,  H04B17/391

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and deploying machine-learning estimation networks in a communications system. One of the methods includes: processing first information with ground truth information to generate a first RF signal by altering the first information by channel impairment having at least one channel effect, using a receiver to process the first RF signal to generate second information, training a machine-learning estimation network based on a network architecture, the second information, and the ground truth information, receiving by the receiver a second RF signal transmitted through a communication channel including the at least one channel effect, inferring by the trained estimation network the receiver to estimate an offset of the second RF signal caused by the at least one channel effect, and correcting the offset of the RF signal with the estimated offset to obtain a recovered RF signal.

    Learning radio signals using radio signal transformers
    19.
    发明授权
    Learning radio signals using radio signal transformers 有权

    公开(公告)号：US12061982B2

    公开(公告)日：2024-08-13

    申请号：US17962007

    申请日：2022-10-07

    Applicant: Virginia Tech Intellectual Properties, Inc.

    Inventor： Timothy James O'Shea

    IPC: G06N3/08 ,  G06N3/04 ,  G06N3/045 ,  H04B1/00 ,  H04B17/309

    CPC classification number: G06N3/08 ,  G06N3/045 ,  H04B1/0003 ,  H04B17/309

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a storage medium, for processing radio signals. In once aspect, a system is disclosed that includes a processor and a storage device storing computer code that includes operations. The operations may include obtaining first output data generated by a first neural network based on the first neural network processing a received radio signal, receiving, by a signal transformer, a second set of input data that includes (i) the received radio signal and (ii) the first output data, generating, by the signal transformer, data representing a transformed radio signal by applying one or more transforms to the received radio signal, providing the data representing the transformed radio signal to a second neural network, obtaining second output data generated by the second neural network, and determining based on the second output data a set of information describing the received radio signal.

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