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: A method, a computer-readable medium, and an apparatus are provided for wireless communication at a network node having a split bearer configuration with a user equipment (UE). The network node measures, at a primary node (MN) or a secondary node (SN), a data burst statistic for the network node, the data burst statistic being based on at least one of a burst level throughput or a packet loss measurement for a data burst between the UE and the MN based on a first bearer in the split bearer configuration or between the UE and the SN based on a second bearer in the split bearer configuration. The network node provides the data burst statistic from the network node to at least one of the MN or a core network component.

Abstract: Aspects of the disclosure relate to systems and methods for configuring a voice domain preference and/or a radio access technology (RAT) preference for a user equipment (UE) in a radio access network (RAN) according to the capability and compatibility of the UE. The UE may send at least one of a requested voice domain preference or a requested RAT preference to a 5G core network (5GC). The UE may also receive, from the 5GC, at least one of a voice domain preference or a RAT preference based on, for example, the capability and compatibility of the UE. The 5GC may additionally generate a RAT/frequency selection priority (RFSP) index for the UE, giving priority to the voice domain preference and/or the RAT preference of the UE. The 5GC may communicate the RFSP index to the RAN. Other aspects, embodiments, and features are also claimed and described.

Abstract: Methods, systems, and devices for wireless communications are described. Some wireless communications system may utilize an inter-system information report message (e.g., a self-organizing network (SON) information report message) to support inter-system mobility load balancing (MLB). For example, a first node, operating in accordance with a first radio access technology (RAT), may receive an information report message from a second node operating in accordance with a second RAT. The information report message may include a periodic load reporting request information element (IE) or an event-triggered load reporting request IE. In response, the first node may determine a traffic load based on the load reporting request and transmit, to the second node, an information report message which includes one or more IEs for reporting the determined traffic load. The exchange of the load information via the IEs may enable for MLB between nodes of different RAT.

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: Methods, systems, and devices for wireless communications are described. An access and mobility management function (AMF) associated with a first radio access network (RAN) may identify a user equipment (UE) connected to a source base station of the first RAN. The AMF may receive a handover message including a voice call continuity handover trigger message indicating a handover of the UE to a target base station associated with a second RAN. In some examples, the AMF may transmit a bypass handover message to a second network device based a on the received handover message. In some cases, the bypass handover message may include the voice call continuity handover trigger message. In some examples, the second network device is a mobility management entity (MME) associated with an Evolved Universal Terrestrial Radio Access Network (E-UTRAN).

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, from a base station, supported slice information. The UE may perform, in connection with a determination that one or more intended slices for the UE include a high priority slice, at least one of cell selection or cell reselection based at least in part on the supported slice information. Numerous other aspects are described.

Abstract: Certain aspects of the present disclosure provide techniques for reporting an indication of a PHR when the UE's assigned of UL resources is insufficient to transmit both UL data and a PHR. Additionally, aspects described herein introduce a negative PHR used to indicate the UE requires additional UL resources.

Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may measure quality of experience (QoE) metrics and transmit a QoE report that is formatted to be readable by a base station, such that a base station may receive the QoE report and independently perform adjustments associated with the service being utilized by the UE. A UE may receive a configuration message that includes a first configuration for reporting QoE measurements to a base station and a second configuration for reporting QoE measurements to a QoE server. The UE may measure one or more QoE metrics in accordance with the configuration message, and generate a first report for the base station based on the QoE measurements and the first configuration. Upon generating the report, the UE may transmit the first report to the base station in accordance with the first configuration.

Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may receive from a base station a measurement configuration signal comprising a measurement resource configuration associated with a cross-link interference signal strength measurement. The UE may perform the cross-link interference signal strength measurement for one or more UEs associated with one or more intra-frequency neighboring cells according to the measurement resource configuration, wherein the cross-link interference signal strength measurement is performed during an intra-frequency measurement gap. The UE may transmit a report of the cross-link interference signal strength measurement to the base station.

Abstract: Methods, systems, and devices for wireless communications are described. A communication link between the UE and a serving base station may be established. The UE may measure, at an application layer of the UE, a set of quality of experience variables associated with different service types. The UE may measure, at an access stratum of the UE, a set of radio resource management variables associated with the communication link between the UE and the serving base station and a communication link between the UE and a corresponding set of one or more neighboring base stations associated with the communication links. The UE may transmit a measurement report to the serving base station indicating information associated with the quality of experience variables and the radio resource management variables in a multi-layer readable format.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, via a first cell, multicast radio bearer (MRB) configuration information indicating one or more MRB configurations for receiving multicast communications. The UE may receive, via a second cell, a multicast communication based at least in part on an MRB configuration of the one or more MRB configurations. Numerous other aspects are described.

Abstract: A method of wireless communication includes determining, based on a plurality of network measurements performed by a user equipment (UE), one or more measurement log files associated with the plurality of network measurements. The method further includes receiving, by the UE from a network device, a request associated with the one or more measurement log files. The request indicates at least one measurement filter. The method further includes transmitting, by the UE to the network device, a response to the request. The response includes first measurement results of the one or more measurement log files selected based on the at least one measurement filter and excludes second measurement results of the one or more measurement log files based on the at least one measurement filter.

Abstract: A delta configuration is signaled for handover of a wireless communication device (e.g., a user equipment, UE) from a first form of connectivity to a second form of connectivity. For example, a UE with master cell group (MCG) connectivity may be handed-over to multiple radio access technology-dual connectivity (MR-DC). In some examples, a UE with standalone (SA) connectivity may be handed-over to non-standalone (NSA) connectivity (e.g., dual connectivity). In conjunction with this handover the UE may be signaled as to whether the UE is to reuse a configuration from the first connectivity mode during the second connectivity mode.

Abstract: Certain aspects of the present disclosure provide techniques for capability based cell selection and cell reselection. A method for wireless communications by a user equipment (UE) includes receiving system information including information for cell selection, cell reselection, or a combination thereof. The system information comprises at least first system information associated with a first one or more capabilities and second system information associated with a second one or more capabilities. The method includes performing a measurement of one or more signals from one or more cells. The method includes performing cell selection, cell reselection, or both based at least in part on the system information, the measurement of the one or more signals, and one or more capabilities of the UE.

Abstract: Methods, systems, and devices for wireless communications are described. In some examples, a wireless communications system may support machine learning and may configure a user equipment (UE) for machine learning. The UE may transmit, to a base station, a request message that includes an indication of a machine learning model or a neural network function based at least in part on a trigger event. In response to the request message, the base station may transmit a machine learning model, a set of parameters corresponding to the machine learning model, or a configuration corresponding to a neural network function and may transmit an activation message to the UE to implement the machine learning model and the neural network function.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a central unit (CU) may receive one or more cross-link interference (CLI) measurement reports that are based at least in part on one or more CLI measurements performed by one or more downstream nodes. The CU may transmit, and a distributed unit (DU) may receive, CLI measurement information based at least in part on the one or more CLI measurement reports. In some aspects, the DU may perform one or more CLI mitigation actions based at least in part on the CLI measurement information received from the CU. Numerous other aspects are provided.

Abstract: Example implementations include a method, apparatus and computer-readable medium of wireless communication by a user equipment (UE), comprising receiving parameter set configuration information from a network entity, the parameter set configuration information corresponding to a model structure employed in a machine learning operation by the UE for the wireless communication. The implementations further include activating a parameter set in response to an activation condition, the parameter set identified within the parameter set configuration information as being associated with the activation condition.

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, UE capability information associated with at least one machine learning component. The UE may receive, from the network node and based on the UE capability information, configuration information corresponding to the at least one machine learning component. The UE may generate a first machine learning output based on the machine learning component. The UE may perform a communication task based on the first machine learning output. 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 start a timer for obtaining quality of experience (QoE) measurements. The UE may obtain the QoE measurements until the timer expires. The UE may transmit information indicating the QoE measurements. Numerous other aspects are described.