Abstract: Aspects presented herein may enable a first UE to utilize inference results provided by at least a second UE to improve its inference accuracy. In one aspect, a first UE establishes an ML inference result sharing session with one or more second UEs for at least one ML inference task. The first UE receives a first set of ML inference results associated with the at least one ML inference task, where the first set of ML inference results is received from the one or more second UEs during the ML inference result sharing session. The first UE estimates an aggregated ML inference result based on at least one of the first set of ML inference results or a second set of ML inference results, where the second set of ML inference results is configured by the first UE for the at least one ML inference task.

Abstract: Aspects are provided which allow a UE to achieve sidelink parameter coordination through various signaling in clustered FL or peer-to-peer FL. The UE provides a first ML model information update and a measurement associated with the update. The UE obtains an aggregated ML model information update aggregating the first update with a second ML model information update of either a first network node in a FL cluster including the UE or a second network node in a second FL cluster. The UE provides a sidelink communication parameter in SCI to a network node, which parameter is an output of an ML model associated with the aggregated ML model information update. As a result, UEs may derive common SCI parameters from their updated ML models to apply in sidelink communications, thereby leading to maximized packet reception rate, maximized throughput, or minimized latency in communication.

Abstract: Methods, systems, and devices for wireless communications are described. The described techniques provide for using situational information to aid in beam-based communications between a first user equipment (UE) and a network entity. The first UE may collect data at one or more sensors and may generate the situational information using the collected data. The first UE may then use the situational information in a beam selection procedure to identify suitable candidate beams for communicating with the network entity. The first UE may also transmit the situational information to the network entity in a beam management report, and the network entity may use the situational information to identify suitable candidate beams for communicating with the first UE. In some cases, the network entity may also use the situational information to identify suitable candidate beams for communicating with a second UE associated with the first UE.

Abstract: Methods, systems, and devices for wireless communications are described. The described techniques support communication between one or more network entities and user equipment (UEs) via configurable intelligent surfaces. A first UE may transmit, to a second UE associated with a set of configurable intelligent surfaces, first information that indicates a tracking period and a data period that the second UE is to use to manage the configurable intelligent surfaces. The second UE may adjust the configurable intelligent surfaces for the communications between the first UE and network entities during the tracking period and the data period. The second UE may adjust the configurable intelligent surfaces based on measurement reports generated by the first UE based on communication during the tracking and data periods.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may transmit, to first network node for use by a first inference host associated with a first network node, first machine learning data associated with a machine learning service. The UE may receive, from the first network node, a handover command communication indicating that the UE is to perform a handover from the first network node to a second network node, wherein the handover command communication indicates machine learning inference information associated with a second inference host that is associated with the second network node. The UE may transmit, to the second network node for use by the second inference host associated with the second network node, second machine learning data for the machine learning service based at least in part on receiving the handover command communication. Numerous other aspects are described.

Abstract: Methods, systems, and devices for wireless communications are described. A base station may transmit a request for a first user equipment (UE) to provide sensing capability information associated with UEs other than the first UE (e.g., an indication of one or more sensors associated with the corresponding UE, an orientation of the corresponding UE, a field of view associated with the corresponding UE). Additionally, the first UE may receive, from each of a set of second UEs, indications of the sensing capability information associated with the corresponding second UEs. Based on the sensing capability information indicated for each of the set of second UEs, the first UE select a subset of second UEs and transmit an indication of the sensing capability information associated with the subset of second UEs to the base station.

Abstract: Aspects are provided which allow a UE to switch between feature data extraction models in order to provide adaptive feature data of dynamic, potential LOS obstacles for improved beam blockage prediction performance (or other functions) at the network node. Initially, the network node receives first feature data from a UE based on a first data extraction model of the UE. The network node transmits a message instructing the UE to switch from the first data extraction model to a second data extraction model of the UE based on a state of the UE. In response to the message, the UE determines to switch from the first data extraction model to the second data extraction model and transmits, to the network node, second feature data based on the second data extraction model. The network node may then determine a beam blockage prediction in response to the second feature data.

Abstract: Aspects of dynamic and interactive machine learning and feature extraction techniques for performing beam interference management are disclosed. In one aspect, upon entering a coverage area, a UE may transmit a discovery message including one or more machine learning (ML) services for ML service discovery. Based on the ML service discovery, the UE may transmit a session request to establish a data service session between the UE and a network node based on the ML service discovery and other criteria such as extracted features. The network node may receive the ML discovery data and extracted features and aggregate this information with other intelligent network devices to enable the network node to predict a beam blockage during the ML inference data service session. The network node can adapt beam blockage predictions by changing the timing and direction of communications between network entities.

Abstract: Aspects presented herein may enable wireless communications to be adaptive to a dynamic environment, where wireless devices may manage wireless communications, such as performing beam managements, based at least in part on environmental conditions. In one aspect, a network entity receives, from a sensor device or a UE, a request for an ML data service. The network entity establishes, with the sensor device or the UE, the ML data service based on the request. The network entity receives, from the sensor device, ML data including a set of features extracted from at least one sensor of the sensor device or information indicative of at least one beam for the ML data service. The network entity transmits, to the UE, a beam indication to modify the at least one beam based at least in part on the ML data received from the sensor device during the ML data service.

Abstract: A first UE and a second UE may exchange information relating to one or more machine learning data services. The one or more machine learning data services may be provided by the second UE. The first UE and the second UE may pair with each other for the one or more machine learning data services. The second UE may perform machine learning inference using at least one machine learning inference model, and may transmit the inference result (e.g., a link quality prediction) associated with a link between a network node and the first UE to the network node. The network node may switch (the direction of) the network node beam if the inference result predicts that the degree of link quality degradation associated with a current network node beam is going to be greater than a prespecified threshold.

Abstract: Methods, systems, and devices for wireless communications are described. A base station may transmit a request for a first user equipment (UE) to provide sensing capability information associated with UEs other than the first UE (e.g., an indication of one or more sensors associated with the corresponding UE, an orientation of the corresponding UE, a field of view associated with the corresponding UE). Additionally, the first UE may receive, from each of a set of second UEs, indications of the sensing capability information associated with the corresponding second UEs. Based on the sensing capability information indicated for each of the set of second UEs, the first UE select a subset of second UEs and transmit an indication of the sensing capability information associated with the subset of second UEs to the base station.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a transmitter node may predict a future state associated with a wireless channel at a future time instance using a machine learning model, wherein the future state is predicted based at least in part on one or more of weights associated with the machine learning model, a current state associated with the wireless channel, or one or more previous states associated with the wireless channel. The transmitter node may select one or more parameters for a transmission to occur at the future time instance based at least in part on the future state associated with the wireless channel. The transmitter node may perform the transmission using the one or more parameters. Numerous other aspects are described.

Abstract: A split-screen display method and an electronic device are provided. The method may be applied to the field of human-machine interaction. The method includes: A user enters an operation for a split-screen display area, for example, taps a lock control in a split-screen display area; and the electronic device locks display content in the split-screen display area in response to the operation.

Abstract: A non-intrusive interaction method includes an electronic device that obtains a description file of an application, where the description file indicates a function to be implemented by the application, and is defined using a non-intrusive protocol description; determines a first component based on the description file, where the first component is a component that is in components of the electronic device and that can implement the function that needs to be implemented by the application, and the component is configured based on a non-intrusive protocol to provide a device capability service and can implement an independent function; and runs, based on the description file to provide the device capability service for the application, the first component to implement the function.

Abstract: The present solution provides a network communication method, peers and a network communication system, the method includes establishing communication with a communication room peer, and obtaining a capacity of the communication room peer, and an IP address and a port of communication room; establishing communication with a pilot peer, obtaining an IP address and a port of the pilot peer, sending a capacity of the communication room and a total number of user peers to the pilot peer, so that the pilot peer creates a required number of communication room peers based on the capacity of the communication room and the total number of user peers; and establishing communication with the user peers, sending the IP address and the port of the communication room peer to the user peers, so that the user peers join in the corresponding communication room peer to perform communication.

Abstract: The present solution provides a network communication method, peers and a network communication system, the method includes establishing communication with a communication room peer, and obtaining a capacity of the communication room peer, and an IP address and a port of communication room; establishing communication with a pilot peer, obtaining an IP address and a port of the pilot peer, sending a capacity of the communication room and a total number of user peers to the pilot peer, so that the pilot peer creates a required number of communication room peers based on the capacity of the communication room and the total number of user peers; and establishing communication with the user peers, sending the IP address and the port of the communication room peer to the user peers, so that the user peers join in the corresponding communication room peer to perform communication.

Abstract: Collimating microlenses are “printed” from optical polymeric materials on the ends of optical fibers using ink-jet technology. In one embodiment the optical fibers are inserted into a collet, a stand-off distance from the open upper end of the collet. The open upper end is filled with optical fluid and a microlens is formed thereon to collimate light exiting the fiber through the microlens. In another embodiment optical fibers from a “ribbon” are separated and installed into a ferrule having multiple openings therethrough. In the same manner as in the collet embodiment, the ferrule openings serve as a mold for the lens formation with the end of the fiber being located at the focal distance of the lenslet formed in an on the ferrule. A non-wetting coating can serve to control spreading of the fluid optical material and allow lens radius control as well. The microlenses are hardened after formation.

Abstract: A process is disclosed which utilizes ink-jet printing of optical polymeric fluids to produce microlenses on a substrate having an axial gradient index of refraction. Two optical polymeric fluids are used, one having an index of refraction higher than the other. A base portion of the microlens is printed using the lower index of refraction material and a cap portion of the microlens is printed over the base portion to produce a radiused formed microlens. Inter-diffusion of the base portion and top or cap portion creates a generally uniform gradient diffusion zone in the axial (vertical) direction wherein the lower boundary of the zone has the index of the base portion and the upper boundary of the zone has the index of the top portion. After a sufficient gradient diffusion zone is formed, the formed microlens is solidified by curing or other means to stop any further diffusion. The microlenses may be formed as individual lenses on a optical substrate or as an array of microlenses.

Abstract: Collimating microlenses are “printed” from optical polymeric materials on the ends of optical fibers using ink-jet technology. In one embodiment the optical fibers are inserted into a collet, a stand-off distance from the open upper end of the collet. The open upper end is filled with optical fluid and a microlens is formed thereon to collimate light exiting the fiber through the microlens. In another embodiment optical fibers from a “ribbon” are separated and installed into a ferrule having multiple openings therethrough. In the same manner as in the collet embodiment, the ferrule openings serve as a mold for the lens formation with the end of the fiber being located at the focal distance of the lenslet formed in an on the ferrule. A non-wetting coating can serve to control spreading of the fluid optical material and allow lens radius control as well. The microlenses are hardened after formation.