Abstract: Methods, systems, and devices for wireless communications at a user equipment (UE) are described. A UE may identify one or more measurement parameters to use for input in a machine learning (ML) model. In some cases, the measurement parameters may include reference signal received power measurements or a past set of timing advance (TA) values for a specific node. The UE may predict the TA based on inputting the measurement parameters into the ML model. The UE may transmit an uplink communication from the UE to a network entity using the TA predicted from the ML model. In some examples, the UE may transmit a capability report to indicate that the UE may support autonomous update of the TA based on the predictions of the TA values produced from the ML model.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may transmit, to a network node, an event trigger request based at least in part on an occurrence of a triggering event, the event trigger request activating a beam report configuration at the UE in lieu of a machine learning (ML) model for beam prediction at the UE. The UE may transmit, to the network node, a beam measurement report based at least in part on the beam report configuration. Numerous other aspects are described.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, from a network node, a configuration for applying weighted averaging to layer 1 (L1) reference signal received power (RSRP) measurements. The UE may receive, from the network node, a plurality of reference signals during a period of time, the plurality of reference signals being quasi-co-located with each other. The UE may obtain weighted averaged L1 RSRP measurements associated with the plurality of reference signals based at least in part on the configuration, the weighted averaged L1 RSRP measurements being available as input to a machine learning (ML) model for beam prediction. Numerous other aspects are described.

Abstract: A method of wireless communication is performed by a user equipment (UE). The method receives, from a network, a configuration for a decision making module. The method also executes the decision making module to determine a selection parameter for a configuration of at least one machine learning module. The method selects the configuration of the at least one machine learning module based on the selection parameter. Further, the method reports, to the network, a decision resulting from executing the decision making module.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, from a network node, a configuration of a beam prediction model that is trained to predict beam measurements for a set of beams. The UE may receive, from the network node, an indication of a subset of beams, from the set of beams, that are to be associated with a measurement report. The UE may transmit, to the network node, the measurement report indicating one or more predicted beam measurements that are based at least in part on an output of the beam prediction model, the output of the beam prediction model including beam predictions associated with the set of beams, and the one or more predicted beam measurements including information associated with the subset of beams. Numerous other aspects are provided.

Abstract: Disclosed is a high-precision dynamic real-time 360-degree omnidirectional point cloud acquisition method based on fringe projection. The method comprises: firstly, by means of the fringe projection technology based on a stereoscopic phase unwrapping method, and with the assistance of an adaptive dynamic depth constraint mechanism, acquiring high-precision three-dimensional (3D) data of an object in real time without any additional auxiliary fringe pattern; and then, after a two-dimensional (2D) matching points optimized by the means of corresponding 3D information is rapidly acquired, by means of a two-thread parallel mechanism, carrying out coarse registration based on Simultaneous Localization and Mapping (SLAM) technology and fine registration based on Iterative Closest Point (ICP) technology.

Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may transmit, to a network entity, a first message indicating data collected at the first UE and geo-location information of the first UE. The first UE may receive, from the network entity, a second message indicating a sidelink grant for transmitting a sidelink message on a set of resources and a source identifier and destination identifier associated with the sidelink message. The first UE may transmit the sidelink message on the set of resources to at least a second UE, the sidelink message including the source identifier and the destination identifier. The second UE may transmit, to the network entity, an indication of calculated geo-location information for the first UE and a received power measurement of the sidelink message based on the sidelink message.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a first user equipment (UE) may transmit, to a second UE, an indication of at least one sidelink unified transmission configuration indicator (TCI) state, wherein the at least one sidelink unified TCI state includes at least one of: a joint forward link and reverse link TCI state, a separate forward link TCI state, or a separate reverse link TCI state. The first UE may communicate with the second UE on at least one of the forward link or the reverse link based at least in part on the indication of the sidelink unified TCI state. Numerous other aspects are described.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive multiple reference signals (RSs). The UE may measure the multiple RSs to generate measurements for the multiple RSs. The UE may encode the measurements using a machine learning model to generate codewords representing a quantized version of the measurements. The UE may transmit the codewords. Numerous other aspects are described.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a transmitter user equipment (UE) may identify a plurality of beams that are configured for transmitting one or more sidelink communications via one or more sidelink resources. The UE may transmit sidelink control information that indicates to reserve the one or more sidelink resources and that includes an explicit beam indication or a beam hopping indication associated with the plurality of beams. Numerous other aspects are described.

Abstract: A fingerprint identification apparatus, comprising: a nonopaque nonopaque glass cover plate, a display unit, an optical film, an imaging unit, and a photoelectric sensing unit, wherein the nonopaque glass cover plate has a touch interface for contacting a to-be-identified fingerprint; the display unit is provided with a plurality of pixels, a part of the plurality of pixels form one or more point light source regions; the optical film is provided with a light-transmitting region allowing light to pass through the optical film and a light-blocking region configured for preventing light from passing through the optical film; light emitted from one or more point light source region is reflected by an upper surface of the nonopaque cover glass, the reflected light passes through the nonopaque cover glass, the display unit, and the light-transmitting region of the optical film, and is imaged by the imaging unit onto the photoelectric sensing unit.

Abstract: Fingerprint encryption method and device, fingerprint decryption method and device, storage medium and terminal are provided. The fingerprint encryption method includes: acquiring a fingerprint image; dividing the fingerprint image into a plurality of block images according to a preset window, wherein a size of the block image is the same with a size of the preset window; determining identifiers of the plurality of block images, wherein the identifiers of the plurality of block images have a first preset order; and determining, according to the identifiers of the plurality of block images and a received encryption order, a plurality of encrypted block images to obtain an encrypted fingerprint image. Security of fingerprint storage or fingerprint transmission is enhanced.

Abstract: The present disclosure provides a fingerprint identification method and apparatus, a storage medium, and a terminal. The fingerprint identification method includes: collecting a to-be-identified fingerprint image of a to-be-identified fingerprint; identifying whether the to-be-identified fingerprint belongs to a first type of fingerprint; calculating an image correlation between the to-be-identified fingerprint image and a standard fingerprint image, when it's determined that the to-be-identified fingerprint belongs to the first type of fingerprint; calculating a feature point matching result between the to-be-identified fingerprint image and the standard fingerprint image when it's determined that the to-be-identified fingerprint does not belong to the first type of fingerprint; and determining whether the to-be-identified fingerprint is consistent with the standard fingerprint; wherein the standard fingerprint image is a fingerprint image collected from a standard fingerprint.

Abstract: The present disclosure provides a light detection apparatus and application thereof. The apparatus includes: a nonopaque cover plate, a display, and a photosensor, and further including a processor configured to transmit a display driving signal to the display when the apparatus detects a touch signal on the apparatus; wherein the display includes a plurality of display pixels configured to emit an optical signal when receiving the display driving signal transmitted by the processor, and the optical signal is reflected on an upper surface of the nonopaque cover plate to form a reflected optical signal; and wherein the reflected optical signal is received by the photosensor. By some embodiments of the present disclosure, obtained physiological feature information can be more accurate and identification precision can be effectively improved.

Abstract: Method for determining imaging ratio of flexible panel, electronic device and storage medium are provided. A first surface of the flexible panel is adapted to be placed with an object to be imaged, an image capturing device is disposed on the second surface, and a curvature radius of the first surface is adjustable. The method includes: for a light source in the image capturing device, acquiring a real-time image formed on the image capturing device after a light signal emitted from the light source is reflected by the first surface; determining a real-time curvature radius of the first surface based on the real-time image; and calculating the imaging ratio based on the real-time curvature radius and thickness of the flexible panel. The imaging ratio is determined based on bending degree of the flexible panel in real time to acquire an image with size approximate to actual size of the object.

Abstract: An image capturing apparatus and an electronic device are provided. The image capturing apparatus includes: a light-transmitting cover plate, a light source component, a sensor component, and a lens disposed between the light source component and the sensor component. A preset angle is formed between a central axis of the lens and a normal of the light source component. A light generated by the light source component is transmitted through the light-transmitting cover plate, and then is scattered by the object to be captured, and the scattered light is focused by the lens to the sensor component. The light source component is disposed outside of a depth of field of the lens, and the object to be captured is disposed within the depth of field of the lens.

Abstract: The present invention discloses a topological structure light source driving method, a storage medium and an electronic device applied to off screen imaging. The method includes the following steps of: lighting up pixel points of one or more separate light source regions of a display panel, the light source regions being arranged in a topological structure and spaced by nonluminous pixel points, the light source regions including one or more pixel points; obtaining, through a light sensor, light of pixel points that is totally reflected by a light-permeable cover plate; the display panel and the light sensor are placed under the light-permeable cover plate. Distinguishing from the prior art, the above technical scheme, by one or more pixel points forming one light source, improves the brightness of the light source and enhances the quality of lens-free off-screen optical imaging, while having multiple light sources for image imaging also improves the imaging efficiency.

Abstract: The present disclosure provides a fingerprint identification method and apparatus, a storage medium, and a terminal. The fingerprint identification method includes: collecting a to-be-identified fingerprint image of a to-be-identified fingerprint; identifying whether the to-be-identified fingerprint belongs to a first type of fingerprint; calculating an image correlation between the to-be-identified fingerprint image and a standard fingerprint image, when it's determined that the to-be-identified fingerprint belongs to the first type of fingerprint; calculating a feature point matching result between the to-be-identified fingerprint image and the standard fingerprint image when it's determined that the to-be-identified fingerprint does not belong to the first type of fingerprint; and determining whether the to-be-identified fingerprint is consistent with the standard fingerprint; wherein the standard fingerprint image is a fingerprint image collected from a standard fingerprint.

Abstract: The present disclosure provides a fingerprint identification method and apparatus, a storage medium, and a terminal. The fingerprint identification method includes: collecting a to-be-identified fingerprint image of a to-be-identified fingerprint; calculating an image correlation between the to-be-identified fingerprint image and a standard fingerprint image, wherein the standard fingerprint image is a fingerprint image collected from a standard fingerprint; and determining whether the to-be-identified fingerprint is consistent with the standard fingerprint according to the image correlation. The solution provided by the present disclosure can effectively improve the accuracy of fingerprint identification.

Abstract: A fingerprint identification apparatus, comprising: a nonopaque nonopaque glass cover plate, a display unit, an optical film, an imaging unit, and a photoelectric sensing unit, wherein the nonopaque glass cover plate has a touch interface for contacting a to-be-identified fingerprint; the display unit is provided with a plurality of pixels, a part of the plurality of pixels form one or more point light source regions; the optical film is provided with a light-transmitting region allowing light to pass through the optical film and a light-blocking region configured for preventing light from passing through the optical film; light emitted from one or more point light source region is reflected by an upper surface of the nonopaque cover glass, the reflected light passes through the nonopaque cover glass, the display unit, and the light-transmitting region of the optical film, and is imaged by the imaging unit onto the photoelectric sensing unit.