Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may be configured to receive first system information from a base station, the first system information being for reduced-capability UEs including UEs with a bandwidth capability below a threshold, the UE being a reduced-capability UE. The UE may evaluate the first system information for a dedicated field that includes an indicator that additional system information for reduced-capability UEs is to be received in response to on-demand requests. Subsequently, the UE may obtain the additional system information for reduced-capability UEs in accordance with information included in either the dedicated field when the dedicated field is included in the first system information or in a configuration information element of the first system information when the dedicated field is absent from the first system information.

Abstract: Certain aspects of the present disclosure provide techniques and apparatus for determining neural network functions (NNFs) and configuring and using corresponding machine learning (ML) models for performing one or more ML-based wireless communications management procedures. An example method performed by a user equipment includes transmitting, to a base station (BS), UE capability information indicating at least one radio capability of the UE and at least one machine learning (ML) capability of the UE and receiving, from the BS based on the UE capability information, ML configuration information indicating at least one neural network function (NNF) and at least one ML model corresponding to the at least one NNF.

Abstract: Aspects of the present disclosure provide apparatus, methods, processing systems, and computer readable mediums for a nested conditional mobility procedure. In some cases, a method for wireless communications by a UE generally includes receiving configuration information configuring the UE for conditional handover (CHO) from a source master node (S-MN) to a target master node (T-MN) and for conditional primary secondary cell (PSCell) addition or change (CPAC) and performing a nested procedure based on an evaluation of conditions for both CHO and CPAAC in accordance with the configuration information.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may transmit an indication of functionalities associated with artificial intelligence or machine learning (AI/ML) models supported by the UE. The UE may receive one or more AI/ML models associated with the functionalities. Numerous other aspects are described.

Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may receive, from a network entity, control signaling indicating a configuration for establishing a dual connectivity connection. The dual connectivity connection may include a wireless local area network (WLAN) link and a cellular network link. The UE may establish the WLAN link or the cellular network link as a primary link of the dual connectivity connection. The primary link may be reconfigurable between the WLAN link and the cellular network link. The dual connectivity connection may support a single radio resource control connection associated with the primary link between the UE and the network entity. The UE may communicate with the network entity using at least the primary link of the dual connectivity connection. The UE may support a single radio resource control state of the plurality of radio resource control states at a time.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a mobility management function (MMF) of a core network entity may obtain a trigger for transmitting meta information associated with a model. The MMF may transmit, to an access and mobility management function (AMF) of the core network entity, an AMF service invoke message. The AMF may obtain an indication of one or more central network entities within an area. The AMF may transmit, to the one or more central network entities, meta information associated with the model. Numerous other aspects are described.

Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may transmit an uplink data message to a base station while the UE is in an inactive mode with respect to the base station. The UE may transmit the uplink data message in accordance with a communications procedure, which may be an example of a random access channel (RACH)-based communications procedure or a configured grant (CG)-based communications procedure. The UE may generate a report that includes parameters related to transmission of the uplink data message, which may be used to improve subsequent uplink data message transmissions from the UE, subsequent RACH procedures performed by the UE, or both. The UE may determine which parameters to include in the report based on the communications procedure and whether transmission of the uplink data message was successful. Accordingly, the UE may transmit the report to the base station.

Abstract: A method for wireless communication by a user equipment (UE) includes collaborating with a network device in accordance with a selected network-UE collaboration level of a number of network-UE collaboration levels for machine learning operations. At least one of the network-UE collaboration levels comprises a number of sub-categories. The UE may transmit an indication of a level of support for the selected network-UE collaboration level. The sub-categories may correspond to a life cycle management type and a model transfer/delivery format. The UE may also receive a machine learning configuration based on the level of support.

Abstract: Certain aspects of the present disclosure provide techniques for exchanging information between user equipments (UEs) and network entities regarding which models the UEs and network entities support. A method that may be performed by a UE includes: obtaining an indication of one or more machine learning (ML) based network-side models applicable at a network entity; and transmitting signaling indicating one or more of the ML-based network-side models supported by the UE.

Abstract: A relay device receives, from the base station, a configuration for minimization of drive test (MDT) measurements associated with sidelink communication and transmits a report of the MDT measurements to the base station based on the configuration. The relay device may transmit, to a second UE, a configuration for logged MDT measurements associated with sidelink communication. The relay may receive an availability indication of logged MDT measurements from the second UE, transmit a request for the logged MDT measurements to the second UE, and receive the logged MDT measurements from the second UE over sidelink. A remote device receives, in a sidelink message from a relay device, a configuration for MDT measurements of sidelink communication and transmits the MDT measurements to the relay device.

Abstract: Methods, systems, and devices for wireless communications are described. A UE may receive outer coded downlink signaling via carrier aggregation, and may deactivate retransmission protocols and then selecting at least one of two different feedback modes. A first feedback mode may include a radio link control (RLC) status report mode (e.g., which may be referred to as mode 1, or RLC mode 1). A second feedback mode is a hybrid automatic repeat request (HARQ) feedback mode (e.g., which may be referred to as mode 2, or HARQ mode 2. The network may configure the UE with parameters for operating in mode 1, mode 2, or both, or the UE may select a feedback mode autonomously. The UE may refrain from transmitting additional feedback signaling, and retransmissions may be deactivated, resulting in improved power savings and more efficient use of system resources.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may determine an antenna switching capability for the UE that relates to a capability of the UE to switch an antenna for a plurality of bands that are included in a band combination of a set of band combinations supported by the UE, wherein at least two bands of the plurality of bands correspond to a first radio access technology (RAT) and a second RAT respectively. The UE may signal the set of band combinations and the antenna switching capability to a base station. Numerous other aspects are provided.

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: Methods, systems, and devices for wireless communication are described. A wireless communications system may establish radio bearers for certain data transmissions between a user equipment (UE) and a base station. A radio bearer may be associated with one or more quality of services (QoS) parameters, such as a bit rate. The base station may indicate to the UE a time window over which to average the bit rate. In some examples, a radio bearer may include multiple data flows. The base station may provide information regarding QoS parameters for each data flow in control signaling, such as a grant.

Abstract: Aspects of the present disclosure provide apparatus, methods, processing systems, and computer readable mediums for a nested conditional mobility procedure. In some cases, a method for wireless communications by a UE generally includes receiving configuration information configuring the UE for conditional handover (CHO) from a source master node (S-MN) to a target master node (T-MN) and for conditional primary secondary cell (PSCell) addition or change (CPAC) and performing a nested procedure based on an evaluation of conditions for both CHO and CPAAC in accordance with the configuration information.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may determine an antenna switching capability for the UE that relates to a capability of the UE to switch an antenna for a plurality of bands that are included in a band combination of a set of band combinations supported by the UE, wherein at least two bands of the plurality of bands correspond to a first radio access technology (RAT) and a second RAT respectively. The UE may signal the set of band combinations and the antenna switching capability to a base station. Numerous other aspects are provided.

Abstract: A method of wireless communication by a user equipment (UE) includes receiving an uplink grant from a network device. The method also includes determining, by a lower analog media access control (MAC-A) layer of an analog data communications stack, a quantity of analog neural network gradients to transmit in a data packet using resources allocated by the uplink grant. The determining is based on an analog physical (PHY-A) layer encoding scheme and the resources allocated by the uplink grant. The method further includes segmenting the analog neural network gradients into the data packet. The method still further includes transferring the data packet to the PHY-A layer for transmission to the network device across a wireless network.

Abstract: Disclosed are systems and techniques for wireless communications. For instance, a process may include transmitting a first radio resource control (RRC) message, the first RRC message including a first establishment cause value indicating that an apparatus does not have priority access. The process may also include determining that priority access may be used by the apparatus, transmitting a second RRC message, the second RRC message including a second establishment cause value indicating that the apparatus has priority access, and accessing a wireless network using the priority access.

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: Methods, systems, and devices for wireless communications are described. The method may include a user equipment (UE) may receive a control signal indicating an event trigger for reporting a performance parameter associated with a machine learning model. Further, the UE may receive one or more signals indicating input data for monitoring a performance of the machine learning model by the UE. Upon detecting the event trigger, the UE may transmit a report comprising the performance parameter.