Abstract: Certain aspects of the present disclosure provide techniques for method for wireless communications by a user equipment (UE). The method generally includes receiving a group-common downlink control information (GC-DCI) of a format that has multiple blocks that allow for triggering sounding reference signal (SRS) transmissions on one or more component carriers (CCs) with transmit power control (TPC) independent of TPC commands for SRS, determining, based on one of the blocks, one or more SRS parameters for transmitting SRS on at least a first CC, and transmitting SRS on at least the first CC in accordance with SRS parameters.

Abstract: Methods, systems, and devices for wireless communication are described in which a user equipment (UE) may transmit one or more uplink communications to multiple transmission-reception points (TRPs). Transmission parameters for each repetition may be based on parameters (e.g., a number of antenna ports, a spatial domain filter or beam, a rank or number of layers, or any combinations thereof) that are determined from an indication of whether the repetitions are to use different sounding reference signal (SRS) resource sets, and indicated SRS resource of each SRS resource set. The indication may include a same number of bits regardless of whether one SRS resource set is used or multiple SRS resource sets are used, and may be based on a prior configuration of the UE.

Abstract: This disclosure provides methods for transmissions and retransmissions over a configured grant (CG) physical uplink shared channel (PUSCH) and for transmissions over physical uplink control channel (PUCCH) resources in multi-transmission and reception point (TRP) deployments. A user equipment (UE) may receive signaling configuring a first set of power control parameters and a second set of power control parameters for a CG-PUSCH resource. Additionally or alternatively, the UE may receive signaling activating a first closed-loop power control operation and a second closed-loop power control operation for a PUCCH resource. In some scenarios, the UE may receive a fallback downlink control information (DCI) format activating or scheduling the CG-PUSCH resource or indicating the PUCCH resource. In such scenarios, the UE may employ one or both of a power control selection rule or a transmit power control (TPC) command application rule for a transmission over the CG-PUSCH resource or the PUCCH resource.

Abstract: Methods, systems, and devices for wireless communications are described. In some wireless communications systems, a user equipment (UE) may receive signaling scheduling a first set repetitions of a first uplink shared channel transmission associated with a first sounding reference signal (SRS) resource set and a second set of repetitions of a second uplink shared channel transmission associated with a second SRS resource set. The UE may receive a request to transmit one or more channel state information (CSI) reports and an indication that the CSI reports are to be multiplexed with one of the first set of repetitions or the second set of repetitions or with both of the first and second set of repetitions. The UE may then transmit the CSI reports in accordance with the indication by multiplexing the CSI reports with one or both of the first set of repetitions and the second set of repetitions.

Abstract: This disclosure provides systems, methods and apparatus, including computer programs encoded on computer storage media, for maintaining, between a user equipment (UE) and a component of a base station (BS), a mutual understanding of a set of linked physical downlink control channel (PDCCH) candidates if the UE selects to monitor a subset of the linked PDCCH candidates. In one aspect, the UE may monitor the subset of the linked PDCCH candidates, and the UE and the component of the BS may select a reference PDCCH candidate from which to define scheduling information in accordance with the UE monitoring the subset of the linked PDCCH candidates. In some examples, the UE and the component of the BS may select the reference PDCCH candidate in accordance with one or more mutually understood rules or procedures such that the UE and the component of the BS may select a same reference PDCCH candidate.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive first downlink control information (DCI) having a first transmission configuration indicator (TCI) field that indicates a pair of TCI states to be used after a first time. The UE may receive second DCI having a second TCI field that indicates a selected one or more TCI states, of the pair of TCI states, to be used for a physical downlink shared channel (PDSCH). 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 configuration information associated with a first sounding reference signal (SRS) resource set, including a first quantity of SRS resources, and a second SRS resource set, including a second quantity of SRS resources. The UE may receive downlink control information (DCI) scheduling a spatial division multiplexing communication, the DCI indicating a first one or more SRS resources, associated with a first set of layers, and a second one or more SRS resources, associated with a second set of layers, from the first SRS resource set and/or the second SRS resource set based on: a dynamic switching indicator, a first SRS resource indicator (SRI), a second SRI, the first quantity of SRS resources, the second quantity of SRS resources, and/or a maximum rank. Numerous other aspects are described.

Abstract: Aspects of the disclosure relate to power control for reference signals, such as a sounding reference signal (SRS) in an uplink (UL) dense deployment. A user equipment (UE) may receive, via a transceiver, an indication of a power spectral density for a sounding reference signal (SRS) from a base station. The UE may then transmit, via the transceiver, the SRS at a power level that is based on the power spectral density. The base station may then receive, from an uplink (UL) receive point via the communication interface, an indication of a measured power of the SRS received by the UL receive point from the UE. The base station may then transmit, to the UE, an UL transmitter configuration based on the indication of the measured power of the SRS. Other aspects, embodiments, and features are also claimed and described.

Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may be configured to indicate to a base station a distribution of transmit antennas and receive antennas across a set of antenna panels, and the base station may configure resource sets for reference signal transmissions from the antenna panels based on the indicated distribution. In a first example, the UE may be configured to indicate a respective number of transmit antennas and receive antennas at each antenna panel. In a second example, the UE may be configured to indicate a sum of transmit antennas and a sum of receive antennas across all antenna panels, along with information on how the transmit antennas and receive antennas are distributed. Based on the indication, the base station may configure resource sets for reference signal transmission on sets of ports in resources of the resource sets.

Abstract: Disclosed are systems and methods including software processes executed by a server that detect audio-based synthetic speech (“deepfakes”) in a call conversation. The server applies an NLP engine to transcribe call audio and analyze the text for anomalous patterns to detect synthetic speech. Additionally or alternatively, the server executes a voice “liveness” detection system for detecting machine speech, such as synthetic speech or replayed speech. The system performs phrase repetition detection, background change detection, and passive voice liveness detection in call audio signals to detect liveness of a speech utterance. An automated model update module allows the liveness detection model to adapt to new types of presentation attacks, based on the human provided feedback.

Abstract: Disclosed are systems and methods including software processes executed by a server that detect audio-based synthetic speech (“deepfakes”) in a call conversation. The server applies an NLP engine to transcribe call audio and analyze the text for anomalous patterns to detect synthetic speech. Additionally or alternatively, the server executes a voice “liveness” detection system for detecting machine speech, such as synthetic speech or replayed speech. The system performs phrase repetition detection, background change detection, and passive voice liveness detection in call audio signals to detect liveness of a speech utterance. An automated model update module allows the liveness detection model to adapt to new types of presentation attacks, based on the human provided feedback.

Abstract: Disclosed are systems and methods including software processes executed by a server that detect audio-based synthetic speech (“deepfakes”) in a call conversation. The server applies an NLP engine to transcribe call audio and analyze the text for anomalous patterns to detect synthetic speech. Additionally or alternatively, the server executes a voice “liveness” detection system for detecting machine speech, such as synthetic speech or replayed speech. The system performs phrase repetition detection, background change detection, and passive voice liveness detection in call audio signals to detect liveness of a speech utterance. An automated model update module allows the liveness detection model to adapt to new types of presentation attacks, based on the human provided feedback.

Abstract: Disclosed are systems and methods including software processes executed by a server that detect audio-based synthetic speech (“deepfakes”) in a call conversation. The server applies an NLP engine to transcribe call audio and analyze the text for anomalous patterns to detect synthetic speech. Additionally or alternatively, the server executes a voice “liveness” detection system for detecting machine speech, such as synthetic speech or replayed speech. The system performs phrase repetition detection, background change detection, and passive voice liveness detection in call audio signals to detect liveness of a speech utterance. An automated model update module allows the liveness detection model to adapt to new types of presentation attacks, based on the human provided feedback.

Abstract: Disclosed are systems and methods including software processes executed by a server that detect audio-based synthetic speech (“deepfakes”) in a call conversation. The server applies an NLP engine to transcribe call audio and analyze the text for anomalous patterns to detect synthetic speech. Additionally or alternatively, the server executes a voice “liveness” detection system for detecting machine speech, such as synthetic speech or replayed speech. The system performs phrase repetition detection, background change detection, and passive voice liveness detection in call audio signals to detect liveness of a speech utterance. An automated model update module allows the liveness detection model to adapt to new types of presentation attacks, based on the human provided feedback.

Abstract: Disclosed are systems and methods including software processes executed by a server that detect audio-based synthetic speech (“deepfakes”) in a call conversation. The server applies an NLP engine to transcribe call audio and analyze the text for anomalous patterns to detect synthetic speech. Additionally or alternatively, the server executes a voice “liveness” detection system for detecting machine speech, such as synthetic speech or replayed speech. The system performs phrase repetition detection, background change detection, and passive voice liveness detection in call audio signals to detect liveness of a speech utterance. An automated model update module allows the liveness detection model to adapt to new types of presentation attacks, based on the human provided feedback.

Abstract: Disclosed are systems and methods including software processes executed by a server that detect audio-based synthetic speech (“deepfakes”) in a call conversation. The server applies an NLP engine to transcribe call audio and analyze the text for anomalous patterns to detect synthetic speech. Additionally or alternatively, the server executes a voice “liveness” detection system for detecting machine speech, such as synthetic speech or replayed speech. The system performs phrase repetition detection, background change detection, and passive voice liveness detection in call audio signals to detect liveness of a speech utterance. An automated model update module allows the liveness detection model to adapt to new types of presentation attacks, based on the human provided feedback.

Abstract: Disclosed are systems and methods including software processes executed by a server that detect audio-based synthetic speech (“deepfakes”) in a call conversation. The server applies an NLP engine to transcribe call audio and analyze the text for anomalous patterns to detect synthetic speech. Additionally or alternatively, the server executes a voice “liveness” detection system for detecting machine speech, such as synthetic speech or replayed speech. The system performs phrase repetition detection, background change detection, and passive voice liveness detection in call audio signals to detect liveness of a speech utterance. An automated model update module allows the liveness detection model to adapt to new types of presentation attacks, based on the human provided feedback.

Abstract: Apparatus, methods, and computer-readable media for facilitating multi-cluster control resource sets for downlink control channel repetition are disclosed herein. An example method for wireless communication at a UE includes receiving a configuration for a CORESET having a first RB set associated with a first TCI state and a second RB set associated with a second TCI state. The example method also includes monitoring for a control signal in the first RB set and the second RB set. Another example method includes receiving a configuration for an SSS associated with a first CORESET having a first TCI state and a second CORESET having a second TCI state. The example method also includes monitoring for a control signal based on the configuration for the SSS.

Abstract: A method of wireless communication performed by a user equipment (UE) includes: receiving, from a base station (BS), a multi-transport block (TB) repetition configuration indicating a first number of repetitions and a second number of repetitions; receiving, from the BS, downlink control information (DCI) indicating a beam pattern including a plurality of beam directions; communicating, with the BS based on the multi-TB repetition configuration and the beam pattern, a first TB and a second TB associated with a same scheduling grant, wherein the communicating the first TB and the second TB includes: communicating the first number of repetitions for the first TB; and communicating the second number of repetitions for the second TB.

Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may be configured to indicate to a base station a distribution of transmit antennas and receive antennas across a set of antenna panels, and the base station may configure resource sets for reference signal transmissions from the antenna panels based on the indicated distribution. In a first example, the UE may be configured to indicate a respective number of transmit antennas and receive antennas at each antenna panel. In a second example, the UE may be configured to indicate a sum of transmit antennas and a sum of receive antennas across all antenna panels, along with information on how the transmit antennas and receive antennas are distributed. Based on the indication, the base station may configure resource sets for reference signal transmission on sets of ports in resources of the resource sets.