公开(公告)号：US20180314985A1

公开(公告)日：2018-11-01

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

CPC classification number: G06N20/00 ,  G06N3/0454 ,  G06N3/08 ,  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.

公开(公告)号：US20180308013A1

公开(公告)日：2018-10-25

申请号：US15961465

申请日：2018-04-24

Applicant: Virginia Tech Intellectual Properties, Inc.

Inventor： Timothy James O`Shea

IPC: G06N99/00 ,  H04W24/08

CPC classification number: G06N99/005 ,  H04W24/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and deploying machine-learned identification of radio frequency (RF) signals. One of the methods includes: determining an RF signal configured to be transmitted through an RF band of a communication medium; determining first classification information that is associated with the RF signal, and that includes a representation of a characteristic of the RF signal or a characteristic of an environment in which the RF signal is communicated; using at least one machine-learning network to process the RF signal and generate second classification information as a prediction of the first classification information; calculating a measure of distance between (i) the second classification information that was generated by the at least one machine-learning network, and (ii) the first classification information associated with the RF signal; and updating the at least one machine-learning network based on the measure of distance.

公开(公告)号：US20250045581A1

公开(公告)日：2025-02-06

申请号：US18799049

申请日：2024-08-09

Applicant: Virginia Tech Intellectual Properties, Inc.

Inventor： Timothy James O`Shea

IPC: G06N3/08 ,  G06N3/045 ,  H04B1/00 ,  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.

公开(公告)号：US20240104386A1

公开(公告)日：2024-03-28

申请号：US18376480

申请日：2023-10-04

Applicant: Virginia Tech Intellectual Properties, Inc.

Inventor： Timothy James O`Shea

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

CPC classification number: 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 identification of radio frequency (RF) signals. One of the methods includes: determining an RF signal configured to be transmitted through an RF band of a communication medium; determining first classification information that is associated with the RF signal, and that includes a representation of a characteristic of the RF signal or a characteristic of an environment in which the RF signal is communicated; using at least one machine-learning network to process the RF signal and generate second classification information as a prediction of the first classification information; calculating a measure of distance between (i) the second classification information that was generated by the at least one machine-learning network, and (ii) the first classification information associated with the RF signal; and updating the at least one machine-learning network based on the measure of distance.

公开(公告)号：US20240080120A1

公开(公告)日：2024-03-07

申请号：US18140018

申请日：2023-04-27

Applicant: Virginia Tech Intellectual Properties, Inc.

Inventor： Timothy James O`Shea ,  Thomas Charles Clancy, III

IPC: H04B17/391 ,  G06N3/045 ,  G06N5/046 ,  G06N20/00 ,  H04B17/10 ,  H04B17/373 ,  H04L25/02 ,  H04L25/03

CPC classification number: H04B17/3912 ,  G06N3/045 ,  G06N5/046 ,  G06N20/00 ,  H04B17/101 ,  H04B17/373 ,  H04B17/3913 ,  H04L25/0252 ,  H04L25/03165 ,  H04B17/24 ,  H04L2025/03464

Abstract: One or more processors control processing of radio frequency (RF) signals using a machine-learning network. The one or more processors receive as input, to a radio communications apparatus, a first representation of an RF signal, which is processed using one or more radio stages, providing a second representation of the RF signal. Observations about, and metrics of, the second representation of the RF signal are obtained. Past observations and metrics are accessed from storage. Using the observations, metrics and past observations and metrics, parameters of a machine-learning network, which implements policies to process RF signals, are adjusted by controlling the radio stages. In response to the adjustments, actions performed by one or more controllers of the radio stages are updated. A representation of a subsequent input RF signal is processed using the radio stages that are controlled based on actions including the updated one or more actions.

公开(公告)号：US20200265338A1

公开(公告)日：2020-08-20

申请号：US16798490

申请日：2020-02-24

Applicant: Virginia Tech Intellectual Properties, Inc.

Inventor： Timothy James O`Shea

IPC: G06N20/00 ,  G06N3/08 ,  G06N3/04 ,  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.

公开(公告)号：US20190340506A1

公开(公告)日：2019-11-07

申请号：US16416921

申请日：2019-05-20

Applicant: Virginia Tech Intellectual Properties, Inc.

Inventor： Timothy James O`Shea

IPC: G06N3/08 ,  G06N3/04 ,  H04B1/00

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.

公开(公告)号：US20180322389A1

公开(公告)日：2018-11-08

申请号：US15970510

申请日：2018-05-03

Applicant: Virginia Tech Intellectual Properties, Inc.

Inventor： Timothy James O`Shea

IPC: G06N3/08 ,  G06N3/04

CPC classification number: G06N3/08 ,  G06N3/0454 ,  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.

公开(公告)号：US20180322388A1

公开(公告)日：2018-11-08

申请号：US15970324

申请日：2018-05-03

Applicant: Virginia Tech Intellectual Properties, Inc.

Inventor： Timothy James O`Shea

IPC: G06N3/08

CPC classification number: G06N3/08 ,  G06N3/04 ,  G06N3/0445

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 of the methods includes: determining first information; using an encoder machine-learning network to process the first information and generate a first RF signal for transmission through a communication channel; determining a second RF signal that represents the first RF signal having been altered by transmission through the communication channel; using a decoder machine-learning network to process the second RF signal and generate second information as a reconstruction of the first information; calculating a measure of distance between the second information and the first information; and updating at least one of the encoder machine-learning network or the decoder machine-learning network based on the measure of distance between the second information and the first information.