Abstract: Users access content using a variety of formats, where some formats provide stronger encryption or protections than others. Content transmitted over open protocols may expose content to unauthorized third parties or enable unauthorized use of the content. The content may be protected by converting the content to a set of instructions on a user device, where the instructions correlate characters to identifications and outlines of the characters with instructions for rendering the characters. Different segments of content may have different mappings between characters, identifications, and outlines to add time or resource use to attempts to reverse engineer the instructions.

Abstract: A user equipment (UE) is configured to establish network connections for long-term evolution (LTE) and new radio (NR) radio access technologies (RATS) in non-standalone (NSA) E-UTRA-NR dual connectivity (ENDC) operation. The UE includes a multi-antenna array for data and signaling transmissions and receptions over the LTE and NR connections. The UE determines a most efficient antenna of the multi-antenna array for an operating frequency band of the LTE and NR connections, wherein the most efficient antenna is determined based on at least one performance factor for the UE when using the antenna compared to other antennas of the multi-antenna array, evaluates one or more factors for determining whether the LTE RAT or the NR RAT is to use the most efficient antenna and transmits uplink data on the most efficient antenna via either the LTE RAT or the NR RAT based on the evaluated factors.

Abstract: Apparatuses, systems, program products, and method are disclosed for machine learning abstraction. An apparatus includes an objective module configured to receive an objective to be analyzed using machine learning. An apparatus includes a grouping module configured to select a logical grouping of one or more machine learning pipelines to analyze a received objective. An apparatus includes an adjustment module configured to dynamically adjust one or more machine learning settings for a logical grouping of one or more machine learning pipelines based on feedback generated in response to analyzing a received objective.

Abstract: The present invention concerns a method and apparatus for the modulation of an acoustic field for providing tactile sensations. A method of creating haptic feedback using ultrasound is provided. The method comprises the steps of generating a plurality of ultrasound waves with a common focal point using a phased array of ultrasound transducers, the common focal point being a haptic feedback point, and modulating the generation of the ultrasound waves using a waveform selected to produce little or no audible sound at the haptic feedback point.

Abstract: Systems and methods are provided for a user equipment (UE) connected to a network using FR1 and configured for mmWave beam measurement to communicate using FR2. The UE receives, from a base station, measurement configuration information including an indication of measurement opportunities. The UE determines that a current data traffic type is associated with mmWave communication. In response to the current data traffic type being associated with the mmWave communication, the UE performs an FR2 cell addition measurement decision. The FR2 cell addition measurement decision may be based on one or more of signal quality feedback, sensor input, UE motion state, and geographic (geo) location information associated with FR2 cell information. Based on the FR2 cell addition measurement decision, the UE suppresses or selects a next measurement opportunity of the measurement opportunities for measuring one or more mmWave signals.

Abstract: The present invention concerns a method and apparatus for the modulation of an acoustic field for providing tactile sensations. A method of creating haptic feedback using ultrasound is provided. The method comprises the steps of generating a plurality of ultrasound waves with a common focal point using a phased array of ultrasound transducers, the common focal point being a haptic feedback point, and modulating the generation of the ultrasound waves using a waveform selected to produce little or no audible sound at the haptic feedback point.

Abstract: An automated machine learning (“ML”) method may include training a first machine learning model using a first machine learning algorithm and a training data set; validating the first machine learning model using a validation data set, wherein validating the first machine learning model comprises generating an error data set; training a second machine learning model to predict a suitability of the first machine learning model for analyzing an inference data set, wherein the second machine learning model is trained using a second machine learning algorithm and the error data set; and triggering a remedial action associated with the first or second machine learning model in response to a predicted suitability of the first machine learning model for analyzing the inference data set not satisfying a suitability threshold.

Abstract: A method performed by a user equipment (UE) configured with a plurality of antenna panels. Each antenna panel is configured to beamform over a millimeter wave (mmWave) frequency band. The method includes identifying a predetermined condition corresponding to a first antenna panel of the plurality of antenna panels, selecting a second antenna panel of the plurality of antenna panels based on identifying the predetermined condition corresponding to the first antenna panel and transmitting a beam via the second antenna panel based on the selection.

Abstract: Disclosed are systems, methods, integrated circuits and computer readable storage media for configuring time sensitive communications (TSC). The configuring of the TSC includes monitoring, by a user plane function (UPF), a source and destination of packets in a first protocol data unit (PDU) session of a first user equipment (UE) and in a second PDU session of a second UE, pairing a first device side TSN translator (DS-TT) port of the first UE with a second DS-TT port of the second UE when the first PDU session and the second PDU session are served by the same UPF, wherein the pairing is based on the monitoring of the first and second PDU sessions and when the first DS-TT and second DS-TT ports are paired, communicating the packets between the first UE and the second UE in a UE-UE communication without traversing the TSN.

Abstract: The present invention concerns a method and apparatus for the modulation of an acoustic field for providing tactile sensations. A method of creating haptic feedback using ultrasound is provided. The method comprises the steps of generating a plurality of ultrasound waves with a common focal point using a phased array of ultrasound transducers, the common focal point being a haptic feedback point, and modulating the generation of the ultrasound waves using a waveform selected to produce little or no audible sound at the haptic feedback point.

Abstract: Embodiments include a user equipment (UE) and methods performed by the UE. The methods include receiving a measurement configuration request from a network, in response to the measurement configuration request, measuring a quality of one or more uplink (UL) carrier aggregation (CA) combinations, wherein each UL CA combination comprises a plurality of component carriers, generating a message that includes the quality of the one or more UL CA combinations and transmitting the message to the network. Further embodiments include the above operations being performed as a set of instructions executed by a processor or an integrated circuit that includes circuitry to perform the operations.

Abstract: User equipment in close proximity may transfer data and control information. For example, the user equipment may exchange data or data sets between each other. Each user equipment can receive and transmit data using radio access technologies. A group of user equipments may include active user equipment and passive user equipment. Active user equipment connects with one or more base stations and transfers data on a wireless communication network via the base station. The active user equipment may communicate with other active user equipment and passive user equipment. Passive user equipment may not connect to any base station and/or the wireless communication network and may communicate with other passive user equipment and active user equipment (e.g., via a sidelink, peer-to-peer, or device-to-device channel).

Abstract: User equipment in close proximity may transfer data and control information. For example, the user equipment may exchange data or data sets between each other. Each user equipment can receive and transmit data using radio access technologies. A group of user equipments may include active user equipment and passive user equipment. Active user equipment connects with one or more base stations and transfers data on a wireless communication network via the base station. The active user equipment may communicate with other active user equipment and passive user equipment. Passive user equipment may not connect to any base station and/or the wireless communication network and may communicate with other passive user equipment and active user equipment (e.g., via a sidelink, peer-to-peer, or device-to-device channel).

Abstract: User equipment in close proximity may transfer data and control information. For example, the user equipment may exchange data or data sets between each other. Each user equipment can receive and transmit data using radio access technologies. A group of user equipments may include active user equipment and passive user equipment. Active user equipment connects with one or more base stations and transfers data on a wireless communication network via the base station. The active user equipment may communicate with other active user equipment and passive user equipment. Passive user equipment may not connect to any base station and/or the wireless communication network and may communicate with other passive user equipment and active user equipment (e.g., via a sidelink, peer-to-peer, or device-to-device channel).

Abstract: User equipment in close proximity may transfer data and control information. For example, the user equipment may exchange data or data sets between each other. Each user equipment can receive and transmit data using radio access technologies. A group of user equipments may include active user equipment and passive user equipment. Active user equipment connects with one or more base stations and transfers data on a wireless communication network via the base station. The active user equipment may communicate with other active user equipment and passive user equipment. Passive user equipment may not connect to any base station and/or the wireless communication network and may communicate with other passive user equipment and active user equipment (e.g., via a sidelink, peer-to-peer, or device-to-device channel).

Abstract: User equipment in close proximity may transfer data and control information. For example, the user equipment may exchange data or data sets between each other. Each user equipment can receive and transmit data using radio access technologies. A group of user equipments may include active user equipment and passive user equipment. Active user equipment connects with one or more base stations and transfers data on a wireless communication network via the base station. The active user equipment may communicate with other active user equipment and passive user equipment. Passive user equipment may not connect to any base station and/or the wireless communication network and may communicate with other passive user equipment and active user equipment (e.g., via a sidelink, peer-to-peer, or device-to-device channel).

Abstract: User equipment in close proximity may transfer data and control information. For example, the user equipment may exchange data or data sets between each other. Each user equipment can receive and transmit data using radio access technologies. A group of user equipments may include active user equipment and passive user equipment. Active user equipment connects with one or more base stations and transfers data on a wireless communication network via the base station. The active user equipment may communicate with other active user equipment and passive user equipment. Passive user equipment may not connect to any base station and/or the wireless communication network and may communicate with other passive user equipment and active user equipment (e.g., via a sidelink, peer-to-peer, or device-to-device channel).

Abstract: User equipment in close proximity may transfer data and control information. For example, the user equipment may exchange data or data sets between each other. Each user equipment can receive and transmit data using radio access technologies. A group of user equipments may include active user equipment and passive user equipment. Active user equipment connects with one or more base stations and transfers data on a wireless communication network via the base station. The active user equipment may communicate with other active user equipment and passive user equipment. Passive user equipment may not connect to any base station and/or the wireless communication network and may communicate with other passive user equipment and active user equipment (e.g., via a sidelink, peer-to-peer, or device-to-device channel).

Abstract: User equipment in close proximity may transfer data and control information. For example, the user equipment may exchange data or data sets between each other. Each user equipment can receive and transmit data using radio access technologies. A group of user equipments may include active user equipment and passive user equipment. Active user equipment connects with one or more base stations and transfers data on a wireless communication network via the base station. The active user equipment may communicate with other active user equipment and passive user equipment. Passive user equipment may not connect to any base station and/or the wireless communication network and may communicate with other passive user equipment and active user equipment (e.g., via a sidelink, peer-to-peer, or device-to-device channel).

Abstract: Apparatuses, systems, and methods for a wireless device to perform negotiation of bearer type configuration and/or related parameters. A user equipment device (UE) and/or network may determine a bearer configuration and/or other parameters based on information or measurements of the UE. The UE and the BS may exchange data using a negotiated configuration.