Qualcomm Incorporated

Ravi Teja Sukhavasi

Tao Luo

Peter S Gaal

Aleksandar Damnjanovic

Yongbin Wei

Durga Prasad Malladi

Srinivas Yerramalli

Wanshi Chen

Naga Bhushan

Kiran Kumar Somasundaram

Onkar Jayant Dabeer

Radhika Dilip Gowaikar

Hao Xu

Xiaoxia Zhang

Tingfang Ji

Xinzhou Wu

Amin Ansari

Bence Major

Daniel Hendricus Franciscus Fontijne

Sundar Subramanian

Makesh Pravin John Wilson

Jing X Sun

Alexei Yurievitch Gorokhov

Brian Clarke Banister

Michael Lee McCloud

Supratik Bhattacharjee

Gerhard Reitmayr

Jayakrishnan Unnikrishnan

Duck Hoon Kim

Young-Ki Baik

Chengjin Zhang

Hyun-Mook Cho

Avdhut Joshi

Michael John Hamilton

Yoga Y Nadaraajan

Amir Salimi

Gautam Sachdeva

Shivam Agarwal

Sree Sesha Aravind Vadrevu

Teck Yian Lim

Peter Gaal

Disclosed are techniques for employing deep learning to analyze radar signals. In an aspect, an on-board computer of a host vehicle receives, from a radar sensor of the vehicle, a plurality of radar frames, executes a neural network on a subset of the plurality of radar frames, and detects one or more objects in the subset of the plurality of radar frames based on execution of the neural network on the subset of the plurality of radar frames. Further, techniques for transforming polar coordinates to Cartesian coordinates in a neural network are disclosed. In an aspect, a neural network receives a plurality of radar frames in polar coordinate space, a polar-to-Cartesian transformation layer of the neural network transforms the plurality of radar frames to Cartesian coordinate space, and the neural network outputs the plurality of radar frames in the Cartesian coordinate space.

Radar deep learning

Disclosed are techniques for fusing camera and radar frames to perform object detection in one or more spatial domains. In an aspect, an on-board computer of a host vehicle receives, from a camera sensor of the host vehicle, a plurality of camera frames, receives, from a radar sensor of the host vehicle, a plurality of radar frames, performs a camera feature extraction process on a first camera frame of the plurality of camera frames to generate a first camera feature map, performs a radar feature extraction process on a first radar frame of the plurality of radar frames to generate a first radar feature map, converts the first camera feature map and/or the first radar feature map to a common spatial domain, and concatenates the first radar feature map and the first camera feature map to generate a first concatenated feature map in the common spatial domain.

Early fusion of camera and radar frames

A method performed by an apparatus is described. The method includes receiving map data that is based on first image data, second image data, and a similarity metric. The first image data can be received from a first vehicle and represent an object. The second image data can be received from a second vehicle and represent the object. The similarity metric can be associated with the object represented in the first image data and the object represented in the second image data. The method can also include storing, by a vehicle, the received map data and localizing the vehicle based on the stored map data.

Systems and methods for mapping based on multi-journey data

Disclosed are techniques for determining a motion state of a target object. In an aspect, an on-board computer of an ego vehicle detects the target object in one or more images, determines one or more first attributes of the target object based on measurements of the one or more images, determines one or more second attributes of the target object based on measurements of a map of a roadway on which the target object is travelling, and determines the motion state of the target object based on the one or more first attributes and the one or more second attributes of the target object.

Determining a motion state of a target object

Methods of processing vehicle sensor information for object detection may include capturing generating a feature map based on captured sensor information, associating with each pixel of the feature map a prior box having a set of two or more width priors and a set of two or more height priors, determining a confidence value of each height prior and each width prior, outputting an indication of a detected object based on a highest confidence height prior and a highest confidence width prior, and performing a vehicle operation based on the output indication of a detected object. Embodiments may include determining for each pixel of the feature map one or more prior boxes having a center value, a size value, and a set of orientation priors, determining a confidence value for each orientation prior, and outputting an indication of the orientation of a detected object based on the highest confidence orientation.

Processing sensor information for object detection

A method performed by an apparatus is described. The method includes receiving a first set of object data corresponding to a first journey. The method also includes receiving a second set of object data corresponding to a second journey. The method further includes determining a similarity metric between the first set of object data and the second set of object data. The similarity metric indicates a distance between the first set of object data and the second set of object data for at least one object. The method additionally includes clustering the first set of object data and the second set of object data for the at least one object based on the similarity metric to produce at least one object cluster. The method also includes producing map data based on the at least one object cluster.

Techniques and devices are described for wireless communication. A base station may determine a parameter associated with a transmission such as hybrid automatic repeat request (HARQ) feedback, a signal-to-noise ratio, or a determination regarding whether the transmission was successfully decoded. The base station may then determine a contention window adjustment value based on the parameter. The base station may then apply weighting factor (e.g., based on the time of the transmission, a number of devices being served, aspects of the transmission parameter, etc.) to the contention window adjustment value may adjust a contention window size for a second transmission based on the weighted contention window adjustment value (and, in some cases, other weighted adjustments based on other transmissions). The base station may then perform a clear channel assessment (CCA) based on the contention window size.

Techniques for adjusting clear channel assessment (CCA) window for transmissions in a shared radio frequency spectrum band

Various aspects related to techniques for harmonization between common reference signal (CRS) and demodulation reference signal (DM-RS) based transmission modes (TMs) in unlicensed spectrum are described. In one aspect, a downlink/uplink (DL/UL) subframe configuration may be signaled for each subframe. Information provided by the DL/UL subframe configuration may indicate whether the respective downlink subframe is a single-frequency network (MBSFN) subframe (associated with DM-RS-based TM) or a non-MBSFN subframe (associated with CRS-based TM). In another aspect, periodic as well as aperiodic channel state information (CSI) reporting requests may be supported. In yet another aspect, discontinued reception (DRX) wake ups for unlicensed carriers may be explicitly or implicitly indicated to a user equipment (UE) via a carrier in a licensed spectrum.

Techniques for harmonization between CRS and DM-RS based transmission modes in unlicensed spectrum

Methods and apparatus for wireless communication are described. A method may include receiving at a user equipment (UE) a number of allocated interlaces for an uplink transmission over a shared spectrum, each of which may include a plurality of non-contiguous resource blocks (RB) of the shared spectrum. In some cases, the number of allocated interlaces is unsupported by joint interlace precoding hardware of the UE and the allocated interlaces may be partitioned into subsets of interlaces which may be a size supported by the joint interlace precoding hardware. Reference signals may be generated for the RBs of the allocated interlaces according to a reference signal sequence based on an ordering of the RBs for the allocated interlaces within the shared spectrum.

Power metric optimization and uplink DM-RS design for LTE/LTE-A uplink transmissions in unlicensed spectrum

A method performed by an apparatus is described. The method includes receiving a set of image frames including at least one object. The method also includes receiving a camera position for each image frame. The method further includes associating the at least one object between image frames based on one or more object points and the received camera position for each image frame to produce two-dimensional (2D) object location data. The method additionally includes estimating three-dimensional (3D) pose data of the at least one object based on the 2D object location data. The method also includes refining the 3D pose data based on a shape constraint.

Systems and methods for object location

Methods, apparatuses, systems, and devices are described for wireless communication. In one method, a control format indicator value for a frame may be received over a physical carrier in a shared spectrum. Based on the control format indicator value, a number of subframes of the frame to be used by a base station for downlink transmissions over the physical carrier may be determined. The control format indicator value may indicate an end of transmission, if data is to be transmitted during the frame, a number of subframes to be used for transmission, or whether the current subframe is the final subframe used for transmission. In some cases, a user equipment (UE) may use the control format indicator value to determine a sleep schedule. Further, ACK/NACK transmissions by a UE may be scheduled based on the control format indicator value.

Downlink control format indicator

The present disclosure, for example, relates to one or more techniques for scaling the bandwidth of a carrier. Available sub-channels of an unlicensed radio frequency spectrum band may be determined, and the available sub-channels may be included in the carrier. The available sub-channels may be adjacent or non-adjacent sub-channels. The bandwidth of the carrier may be determined according to which sub-channels are included in the carrier. In this way, the bandwidth of the carrier may be scaled according to the available sub-channels in the unlicensed radio frequency spectrum band.

Techniques for scaling bandwidth of an unlicensed radio frequency spectrum band

Apparatuses and methods for special subframe configuration in unlicensed spectrum are disclosed. For example, the disclosure presents an example method including identifying a time period for an extended clear channel assessment (ECCA) operation. Further, the example method may include determining a guard period portion included in a special subframe of a frame structure based on the identified time period. An apparatus may include means for identifying a time period for an extended clear channel assessment (ECCA) operation. Further, the example apparatus may include means for determining a guard period portion included in a special subframe of a frame structure based on the identified time period.

Special subframe configuration in unlicensed spectrum

Growing community of inventors

San Diego, CA, United States of America

Ravi Teja Sukhavasi