Abstract: A first user equipment (UE) receives, from a scheduling entity, one or more indications of one or more parameters associated with an uplink (UL) transmission from a second UE. The UL transmission includes one or more cross link interference (CLI) measurement resources. The first UE configures one or more dedicated tracking loops for receiving the one or more CLI measurement resources of the UL transmission based on the one or more indications of the one or more parameters. The first UE receives, from the second UE, the one or more CLI measurement resources of the UL transmission using the one or more dedicated tracking loops according to the one or more parameters, while also receiving a downlink (DL) transmission from the scheduling entity. The first UE determines one or more CLI measurements using the one or more CLI measurement resources of the UL transmission.

Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may receive a control message identifying a backbone model that is combinable with at least one task-specific model to generate a multi-model machine learning application. The UE may receive the backbone model and a first task-specific model identified by the control message. The UE use a multi-model machine learning application that is a combination of the backbone model and the first task-specific model to process one or more received signals to generate one or more outputs. The UE may communicate with a wireless device based on the one or more outputs.

Abstract: Embodiments described herein provide for an RIS-aided determination of the location of mobile device that enables the signal reflected by the RIS to be identified through channel estimation. More specifically, an Orthogonal Cover Code (OCC)-based approach may be taken where the RIS is configured to use different weights to reflect different reference signals, enabling a receiving device to identify the reflected signal. This can be utilized on signals used for positioning of the mobile device. Additionally or alternatively, this can be used for positioning of the RIS.

Abstract: Methods, systems, and devices for wireless communications are described. A first user equipment (UE) may transmit, to a base station, capability signaling including an indication of a capability of the first UE to prioritize reception of downlink messages scheduled via a first type of scheduling which at least partially overlap with resources used to perform cross-link interference (CLI) measurements. The first UE may receive control signaling indicating a first set of resources for a downlink message, and additional control signaling indicating a second set of resources usable by the first UE to perform CLI measurements on signals transmitted by a second UE, where the second set of resources at least partially overlap with the first set of resources in a time domain. The first UE may then receive the downlink message from the base station within the first set of resources based on the indication of the capability.

Abstract: A method of wireless communications by a user equipment (UE) includes communicating with a network based on a machine learning model for wireless communication. The method also includes monitoring a status of the machine learning model for wireless communication. The method further includes reporting the status of the machine learning model for wireless communication using a predetermined resource according to a predetermined format. The method also includes falling back to communicating with a fallback procedure, instead of the machine learning model for wireless communication, to maintain wireless communication with the network in response to the status of the machine learning model indicating a model failure.

Abstract: Methods, systems, and devices for wireless communications are described. In some systems, devices use machine learning (ML) models to support wireless communications. For example, a user equipment (UE) may download ML model information from a network to determine an ML model. The network may additionally configure a status reporting procedure, a fallback procedure, or both for the ML model. In some examples, based on a configuration, the UE may transmit a status report to a base station according to a reporting periodicity, a UE-based trigger, a network-based trigger, or some combination thereof. Additionally or alternatively, the UE may determine to fallback from operating using the ML model to operating in a second mode based on a fallback trigger. In some examples, to restore operating using a downloaded ML model, the UE may download an updated ML model or receive iterative updates to a previously downloaded ML model.

Abstract: A configuration for reporting OOD samples for neural network optimization. The apparatus receives, from a base station, a configuration to report an OOD dataset for a machine learning model. The apparatus detects an occurrence of one or more OOD events. The apparatus reports the OOD dataset comprising the one or more OOD events based on the configuration to report OOD dataset. The apparatus receives, from the base station, an update to the machine learning model. The OOD dataset may comprise raw data related to the one or more OOD events, or may comprise extracted latent data corresponding to features of raw data related to the one or more OOD events.

Abstract: Disclosed are techniques for wireless positioning. In an aspect, a first network node receives, from a second network node, a positioning reference signal having a first reception time at the first network node, receives, from a first user equipment (UE), a first uplink positioning reference signal having a second reception time at the first network node, receives, from a second UE, a second uplink positioning reference signal having a third reception time at the first network node, and enables a first reference signal time difference (RSTD) measurement to be calculated for the first UE and a second RSTD measurement to be calculated for the second UE based on the first reception time, the second reception time, the third reception time, and other measurements.

Abstract: Techniques to incorporate quality of experience (QoE) in mobility management are disclosed. A user equipment (UE) may provide a QoE report to network (e.g., cell) upon detection of a QoE report triggering event (e.g., mobility management, environmental trigger, etc.). The QoE report may comprise information related to QoE metrics such as uplink (UL) latency, UL throughput, UL error rate, downlink (DL) frequency, DL throughput, DL error rate, handover (HO) frequency, beam switch frequency, UE power consumption, etc. The network may take actions such as sending a mobility management command if it is decided that QoE should be restored to the UE.

Abstract: Certain aspects of the present disclosure provide techniques for remote interference mitigation between base stations using reference signals. Certain aspects provide a method for wireless communication by a first base station (BS). The method includes receiving a reference signal (RS) from a second BS. The method further includes performing interference measurement corresponding to interference from the second BS based on the RS being associated with the second BS.

Abstract: A determination of a position of a target mobile device in a wireless communication network employing time-division duplexing (TDD) can use a wireless reference signal from another mobile device with a known position. The other mobile device can be configured to transmit the wireless reference signal using cross-link interference (CLI), where the target mobile device receives the signal during a period in which the target mobile device is configured to receive downlink (DL) communication. The target mobile device then transmits another wireless reference signal, which is received by a base station, which also receives the wireless reference signal from the other mobile device. The timing of these various signals received at the target mobile device and base station can be used to determine the location of the mobile device.

Abstract: In some aspects, a base station may transmit, to a user equipment (UE), an instruction that triggers the UE to transmit an uplink random access channel (RACH) message, the instruction identifying a RACH preamble index corresponding to a RACH preamble to be used for the uplink RACH message; transmit, to a plurality of neighbor base stations, information that identifies the RACH preamble index; receive the uplink RACH message from the UE; receive, from the plurality of neighbor base stations, feedback that indicates respective timings with which the uplink RACH message was received by the plurality of neighbor base stations; and estimate a position of the UE based at least in part on a timing with which the uplink RACH message was received by the base station and at least two of the respective timings with which the uplink RACH message was received by the plurality of neighbor base stations.

Abstract: A user equipment (UE) may receive a resource configuration indicating cross link interference (CLI) measurement resources, measure receive strength signal indicator (RSSI) values on the CLI measurement resources, respectively, and determine whether one or more RSSI values of the multiple of RSSI values exceed an RSSI threshold, the one or more RSSI values being respectively associated with one or more CLI measurement resources of the CLI measurement resources. The UE may measure at least one reference signal received power (RSRP) value respectively on at least one CLI measurement resource of the one or more CLI measurement resources in response to determining that the one or more RSSI values exceed the RSSI threshold. The UE may transmit an RSRP measurement report, the RSRP measurement report including the at least one RSRP value and at least one resource index respectively indicating the at least one CLI measurement resource.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a base station may detect interference, in a remote interference management (RIM) scenario, in a set of sub-bands of a plurality of sub-bands of a bandwidth portion. The base station may transmit, to identify the set of sub-bands in which interference is detected, a set of reference signals configured to indicate the set of sub-bands in which the interference is detected. Numerous other aspects are provided.

Abstract: The described techniques relate to improved methods, systems, devices, and apparatuses that support interference mitigation for remote devices. A first wireless device (e.g., a base station) may detect remote interference with its communications caused by a second wireless device (e. g., a second, remote base station) based on, for example, a measured interference over thermal noise level exceeding a threshold. The first wireless device may identify a set of time-frequency resources for remote interference reference signals and a data transmission for a user equipment (UE) that is in communication with the first wireless device. The first wireless device may transmit a remote interference signal to a second wireless device (e. g., a second base station) via the set of time-frequency resources. The first wireless device may further signal a resource allocation to the UE for the UE to use for transmitting uplink transmissions to the first wireless device.

Abstract: Methods, systems, and devices for wireless communications are described. The method includes transmitting, to a base station, a capability parameter indicating one or more predictive retransmission feedback capabilities of the UE, receiving, from the base station, an activation indicator that indicates a predictive retransmission feedback procedure is enabled, receiving data from the base station, and transmitting a predictive retransmission feedback associated with the data to the base station, the predictive retransmission feedback being computed, in accordance with the activation indicator, prior to completing a decoding of the data.

Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may detect whether a data sample falls outside of a dataset used to train a machine learning model configured by a network device. For example, a base station may transmit control signaling to the UE to indicate an out-of-distribution (OOD) detection rule configuration that the UE uses to determine whether at least one data sample falls outside of the dataset. If the at least one data sample is determined to fall outside of the dataset using the OOD detection rule configuration, the UE may transmit an indication to the base station that indicates an OOD event has occurred for the at least one sample. Additionally, the base station may parameters for determining the OOD event, OOD detection patterns to indicate when to monitor for the OOD event, or a combination thereof.

Abstract: Disclosed are techniques for communication. In an aspect, a wireless node (e.g., UE or BS) measures a first TOA of a first SRS-P from a UE, a second TOA of a reflection of a second SRS-P from the UE off of a first RIS, and a third TOA of a reflection of a third SRS-P from the UE off of a second RIS. The UE transmits, to a position estimation entity, measurement information based on the first, second and third TOAs. The position estimation entity determines a positioning estimate of the UE based at least in part on the measurement information.

Abstract: A UE in one of an RRC idle mode or an RRC inactive mode may transmit a plurality of UL reference signals to the base station, receive a first L1 ACK message based on the transmission of the plurality of UL signals from the base station, and transmit UL data via at least one PUR based on the received first L1 ACK message. The plurality of UL signals may include SRS. The UE may receive a PUR configuration from the base station. The UE may determine to drop the transmission of one or more first UL signals, or the base station may determine to omit the transmission of the first L1 ACK message in response to one or more first UL signals, based on L1 ACK density or L1 ACK message in the L1 ACK monitoring window.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, from a New Radio (NR) base station, an indication that includes a configuration for at least one reference signal. The UE may measure, while in an idle mode or inactive state, the at least one reference signal based at least in part on the indication of the configuration. In some aspects, the UE may further receive, from the NR base station, an activation associated with the at least one reference signal. The at least one reference signal may be measured based at least in part on the activation. Numerous other aspects are described.