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1. 发明授权

US10284269B2 Soft codebook subset restriction for elevation beamforming 有权
公开(公告)号：US10284269B2
公开(公告)日：2019-05-07
申请号：US15005650
申请日：2016-01-25
申请人： Nvidia Corporation
发明人： Pekka Janis , Tommi Koivisto , Kari Hamalainen
IPC分类号： H04B7/0456 , H04W16/28 , H04B7/06
摘要： A communications system has a cellular structure including a base station that is located within a cell of the cellular structure and provides an elevation beamforming transmission based on a set of elevation precoding matrix indicator offsets in an elevation codebook. The communications system also includes user equipment that is located within the cell and coupled to the base station to receive the set of elevation precoding matrix indicator offsets and a set of reference signals to provide channel quality and inter-cell interference measurements, wherein a selected channel quality indicator is based on an increase in channel quality with respect to inter-cell interference at the user equipment and corresponds to one of the set of elevation precoding matrix indicator offsets. A method of operating a communications system having a cellular structure is also provided.

2. 发明授权

US09887751B2 Channel quality indication compensation for kronecker precoding 有权
公开(公告)号：US09887751B2
公开(公告)日：2018-02-06
申请号：US15005602
申请日：2016-01-25
申请人： Nvidia Corporation
发明人： Pekka Janis , Tommi Koivisto , Kari Hamalainen
IPC分类号： H04B7/02 , H04B7/04 , H04W16/28 , H04B7/06
CPC分类号： H04B7/0469 , H04B7/0478 , H04B7/0639 , H04B7/065 , H04W16/28
摘要： A communications system has a cellular structure and the communications system includes a base station that is located within a cell of the cellular structure and employs a Kronecker product of azimuth and elevation precoding vectors for beamforming. Additionally, the communications system includes user equipment that is located within the cell and coupled to the base station to receive a reference channel state information process employing a reference precoding vector for use in a non-reference channel state information process to derive a compensated channel quality indication. A method of operating a communications system is also included.

3. 发明授权

US09602230B2 Estimating channel information 有权
公开(公告)号：US09602230B2
公开(公告)日：2017-03-21
申请号：US14656810
申请日：2015-03-13
申请人： Nvidia Corporation
发明人： Timo Roman , Tommi Koivisto , Tero Kuosmanen , Pekka Janis
IPC分类号： G01R31/08 , H04J11/00 , H04B7/06 , H04W24/08 , H04B7/04
CPC分类号： H04J11/005 , H04B7/0417 , H04B7/0626 , H04W24/08
摘要： Disclosed is a method of providing channel state information for a desired downlink channel of a wireless communication system. In a configuration phase, the method comprises receiving on a signaling channel configuration information comprising an identifier of an interference source and an association which associates the identifier with at least one resource element not used for transmission on the desired downlink channel. In an estimation phase, the method comprises estimating channel state information for an expected transmission on the desired downlink channel accounting for an incoming interference transmission from the identified interference source as observed from the at least one resource element. In a reporting phase, the method comprises reporting the channel state information.

4. 发明申请

US20150270917A1 ESTIMATING CHANNEL INFORMATION 有权
标题翻译：估计渠道信息
公开(公告)号：US20150270917A1
公开(公告)日：2015-09-24
申请号：US14656810
申请日：2015-03-13
申请人： Nvidia Corporation
发明人： Timo Roman , Tommi Koivisto , Tero Kuosmanen , Pekka Janis
IPC分类号： H04J11/00 , H04B7/06 , H04W24/08 , H04W72/04
CPC分类号： H04J11/005 , H04B7/0417 , H04B7/0626 , H04W24/08
摘要： Disclosed is a method of providing channel state information for a desired downlink channel of a wireless communication system. In a configuration phase, the method comprises receiving on a signaling channel configuration information comprising an identifier of an interference source and an association which associates the identifier with at least one resource element not used for transmission on the desired downlink channel. In an estimation phase, the method comprises estimating channel state information for an expected transmission on the desired downlink channel accounting for an incoming interference transmission from the identified interference source as observed from the at least one resource element. In a reporting phase, the method comprises reporting the channel state information.
摘要翻译：公开了一种为无线通信系统的期望的下行链路信道提供信道状态信息的方法。在配置阶段，该方法包括在信令信道配置信息上接收包括干扰源的标识符和将该标识符与至少一个不用于在期望的下行链路信道上进行传输的资源元素相关联的信息。在估计阶段中，所述方法包括：从所述至少一个资源元素观察到，估计所述期望下行链路信道上的期望传输的信道状态信息，以对来自所识别的干扰源的进入干扰传输进行核算。在报告阶段，该方法包括报告信道状态信息。

5. 发明申请

US20200210726A1 DISTANCE TO OBSTACLE DETECTION IN AUTONOMOUS MACHINE APPLICATIONS 审中-公开
公开(公告)号：US20200210726A1
公开(公告)日：2020-07-02
申请号：US16728595
申请日：2019-12-27
申请人： NVIDIA Corporation
发明人： Yilin Yang , Bala Siva Sashank Jujjavarapu , Pekka Janis , Zhaoting Ye , Sangmin Oh , Minwoo Park , Daniel Herrera Castro , Tommi Koivisto , David Nister
IPC分类号： G06K9/00 , G06N3/08 , G06N3/04 , G06K9/62 , G06K9/52 , G06K9/20
摘要： In various examples, a deep neural network (DNN) is trained to accurately predict, in deployment, distances to objects and obstacles using image data alone. The DNN may be trained with ground truth data that is generated and encoded using sensor data from any number of depth predicting sensors, such as, without limitation, RADAR sensors, LIDAR sensors, and/or SONAR sensors. Camera adaptation algorithms may be used in various embodiments to adapt the DNN for use with image data generated by cameras with varying parameters—such as varying fields of view. In some examples, a post-processing safety bounds operation may be executed on the predictions of the DNN to ensure that the predictions fall within a safety-permissible range.

6. 发明授权

US09831999B2 Enhanced discontinued transmission and reception methods 有权
公开(公告)号：US09831999B2
公开(公告)日：2017-11-28
申请号：US14707203
申请日：2015-05-08
申请人： Nvidia Corporation
发明人： Tommi Koivisto , Tero Kuosmanen , Timo Roman
IPC分类号： H04W56/00 , H04L5/00 , H04W76/04 , H04W74/00 , H04W84/04
CPC分类号： H04L5/0073 , H04L5/00 , H04L5/005 , H04L5/0082 , H04L5/0092 , H04W74/006 , H04W76/27 , H04W76/28 , H04W84/045
摘要： Methods for operating a small cell in a discontinued reception (DRX) mode include maintaining the small cell in a discontinuous transmission (DTX) mode during a first time period having a plurality of first time slots. The methods include transmitting common reference signals in a predetermined number of second time slots prior to the first time slots and in a predetermined number of third time slots following commencement of the first time slots. The methods include discontinuing transmission of the common reference signals and common channel signals if mobile devices are in a discontinuous reception mode during the first time period. The methods include discontinuing transmission of the common reference signals during a predetermined number of fourth time slots following commencement of the first time period if there is no dedicated common transmission to the mobile devices.

7. 发明授权

US11308338B2 Distance to obstacle detection in autonomous machine applications 有权
公开(公告)号：US11308338B2
公开(公告)日：2022-04-19
申请号：US16728595
申请日：2019-12-27
申请人： NVIDIA Corporation
发明人： Yilin Yang , Bala Siva Sashank Jujjavarapu , Pekka Janis , Zhaoting Ye , Sangmin Oh , Minwoo Park , Daniel Herrera Castro , Tommi Koivisto , David Nister
IPC分类号： G06K9/00 , G06N3/08 , G06N3/04 , G06K9/52 , G06K9/20 , G06K9/62
摘要： In various examples, a deep neural network (DNN) is trained to accurately predict, in deployment, distances to objects and obstacles using image data alone. The DNN may be trained with ground truth data that is generated and encoded using sensor data from any number of depth predicting sensors, such as, without limitation, RADAR sensors, LIDAR sensors, and/or SONAR sensors. Camera adaptation algorithms may be used in various embodiments to adapt the DNN for use with image data generated by cameras with varying parameters—such as varying fields of view. In some examples, a post-processing safety bounds operation may be executed on the predictions of the DNN to ensure that the predictions fall within a safety-permissible range.

8. 发明申请

US20220101635A1 OBJECT DETECTION AND DETECTION CONFIDENCE SUITABLE FOR AUTONOMOUS DRIVING 有权
公开(公告)号：US20220101635A1
公开(公告)日：2022-03-31
申请号：US17456045
申请日：2021-11-22
申请人： NVIDIA Corporation
发明人： Tommi Koivisto , Pekka Janis , Tero Kuosmanen , Timo Roman , Sriya Sarathy , William Zhang , Nizar Assaf , Colin Tracey
IPC分类号： G06V20/58 , G06V10/25 , G06V10/774 , G06V10/77 , G06N20/00
摘要： In various examples, detected object data representative of locations of detected objects in a field of view may be determined. One or more clusters of the detected objects may be generated based at least in part on the locations and features of the cluster may be determined for use as inputs to a machine learning model(s). A confidence score, computed by the machine learning model(s) based at least in part on the inputs, may be received, where the confidence score may be representative of a probability that the cluster corresponds to an object depicted at least partially in the field of view. Further examples provide approaches for determining ground truth data for training object detectors, such as for determining coverage values for ground truth objects using associated shapes, and for determining soft coverage values for ground truth objects.

9. 发明授权

US11210537B2 Object detection and detection confidence suitable for autonomous driving 有权
公开(公告)号：US11210537B2
公开(公告)日：2021-12-28
申请号：US16277895
申请日：2019-02-15
申请人： NVIDIA Corporation
发明人： Tommi Koivisto , Pekka Janis , Tero Kuosmanen , Timo Roman , Sriya Sarathy , William Zhang , Nizar Assaf , Colin Tracey
IPC分类号： G06K9/00 , G06K9/46 , G06K9/62 , B60W50/00 , G06N3/04 , G01S7/41 , G05D1/02 , G06N3/08 , G06K9/32 , G06K9/48 , G01S13/86 , G01S7/48 , G01S17/931 , G01S13/931
摘要： In various examples, detected object data representative of locations of detected objects in a field of view may be determined. One or more clusters of the detected objects may be generated based at least in part on the locations and features of the cluster may be determined for use as inputs to a machine learning model(s). A confidence score, computed by the machine learning model(s) based at least in part on the inputs, may be received, where the confidence score may be representative of a probability that the cluster corresponds to an object depicted at least partially in the field of view. Further examples provide approaches for determining ground truth data for training object detectors, such as for determining coverage values for ground truth objects using associated shapes, and for determining soft coverage values for ground truth objects.

10. 发明申请

US20220253706A1 DISTANCE TO OBSTACLE DETECTION IN AUTONOMOUS MACHINE APPLICATIONS 有权
公开(公告)号：US20220253706A1
公开(公告)日：2022-08-11
申请号：US17723195
申请日：2022-04-18
申请人： NVIDIA Corporation
发明人： Yilin Yang , Bala Siva Sashank Jujjavarapu , Pekka Janis , Zhaoting Ye , Sangmin Oh , Minwoo Park , Daniel Herrera Castro , Tommi Koivisto , David Nister
IPC分类号： G06N3/08 , B60W30/14 , B60W60/00 , G06K9/62 , G06V20/56
摘要： In various examples, a deep neural network (DNN) is trained to accurately predict, in deployment, distances to objects and obstacles using image data alone. The DNN may be trained with ground truth data that is generated and encoded using sensor data from any number of depth predicting sensors, such as, without limitation, RADAR sensors, LIDAR sensors, and/or SONAR sensors. Camera adaptation algorithms may be used in various embodiments to adapt the DNN for use with image data generated by cameras with varying parameters—such as varying fields of view. In some examples, a post-processing safety bounds operation may be executed on the predictions of the DNN to ensure that the predictions fall within a safety-permissible range.

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