Abstract: Access class barring can provide latency for accessing a barred service using a radio access technology (RAT) due to congestion of a local cell accessed via that RAT. A user equipment (UE) supports multiple RATs and the same service may be accessible via a separate cell accessed using a different RAT. Various aspects of the present disclosure describe techniques for configuring the UE to selectively switch between RATs to access a service based on a barring factor employed for a particular RAT, thereby reducing latency for accessing the service. The UEs may operate to monitor a current value of a barring factor for a service the UE seeks to access via a preferred, or default, RAT. In the event that the current value of the barring factor exceeds a specified threshold, the UE switches over to using a different RAT to access this service.

Abstract: Methods, devices, systems, and means for coordinating full-duplex communication are described in which a user equipment, UE, configured as a coordinating user equipment for a user equipment-coordination set, UECS, selects a first subset of UEs in the UECS to jointly receive downlink signals and selects a second subset of UEs in the UECS to jointly transmit uplink signals. The coordinating UE receives uplink data to transmit to the network entity and receives, from the first subset of UEs, demodulated and sampled downlink data that is received concurrently with joint-transmission of the uplink data. The coordinating UE combines the samples received from each UE in the first subset of UEs and jointly processes the combined samples to provide decoded data using the received uplink data to cancel crosstalk of uplink signals for the transmitted uplink data to downlink signals to the received downlink data.

Abstract: A user equipment (UE) is configured to request connection to a selected one of a plurality of available network slices of a network system. The UE implements a permission control framework that allows individual applications to request connection to the selected network slice, but establishes the connection only when the framework determines, based on any of a variety of permission criteria, that the application is permitted to access the requested network slice. The UE also supports user selection of the network slice via a graphical user interface that presents a selectable list of available network slices.

Abstract: The present disclosure describes systems and methods directed to a user equipment (UE) limited-service mode for wireless communications. For a user equipment (UE) that is wirelessly communicating with a base station, a service-mode manager determines that a thermal, power, or battery condition local to the UE violates a threshold and causes the UE to transmit a message that indicates a request by the UE to enter a UE limited-service mode. The base station allocates a set of resources of the air interface to be used for wireless communications upon the UE entering the UE limited-service mode. The base station then transmits a message to the UE, directing the UE to enter the UE limited-service mode and wirelessly communicate with the base station using the allocated set of resources of the air interface.

Abstract: This document describes network slicing for WLAN in cellular networks. The techniques described enable the use of WLAN network slices (216c) with cellular networks (202) and mobility management of user equipment (102) between cellular networks (202) and WLAN networks (206). An Access and Mobility Function-Aggregation Proxy (AMF-AP) (218) connects one or more WLAN networks (206) to the cellular core network (110) of a network operator via the Access and Mobility Function (AMF) (212) in the core network (110). The AMF-AP (218) acts as a proxy and a firewall to protect the AMF (212) and other entities in the cellular core network (110) from malicious actors.

Abstract: Aspects describe federated learning for deep neural networks, DNNs, in a wireless communication system. A network entity directs (610) each user equipment, UE, in a set of UEs to form, using an initial machine-learning (ML) configuration, a respective deep neural network, DNN, that processes wireless network communications. The network entity requests (620), from each UE in the set of UEs, respective updated ML information generated by the respective UE using a training procedure and local input data. The network entity then receives (640), from at least some UEs in the set of UEs, the respective updated ML information determined by the respective UE. The network entity identifies (645) a subset of UEs in the set of UEs and determines (650) a common ML configuration for the subset of UEs. The network entity then directs (655) each UE in the subset of UEs to form an updated DNN using the common ML configuration.

Abstract: Techniques and apparatuses are described for determining a position of user equipment by using adaptive phase-changing devices. In aspects, a base station transmits wireless signals for a UE toward respective reconfigurable intelligent surfaces (RISs) of adaptive phase-changing devices. The APDs may direct reflections of the wireless signals in a direction, such as toward the UE, based on a configuration of the RIS of the APD. The base station receives, from the UE via a wireless connection identifiers of the reflections of the wireless signals that are received by the UE. In some cases, the base station also receives a signal quality parameter associated with the reflection reaching the UE. The base station determines angular information based on the respective identifiers and/or signal quality parameters of the reflections. Based on the angular information and known positions of the APDs, the base station determines a position of the UE.

Abstract: Techniques and apparatuses are described for deep neural network (DNN) processing for a user equipment-coordination set (UECS). A network entity selects (910) an end-to-end (E2E) machine-learning (ML) configuration that forms an E2E DNN for processing UECS communications. The network entity directs (915) each device of multiple devices participating in an UECS to form, using at least a portion of the E2E ML configuration, a respective sub-DNN of the E2E DNN that transfers the UECS communications through the E2E communication, where the multiple devices include at least one base station, a coordinating user equipment (UE), and at least one additional UE. The network entity receives (940) feedback associated with the UECS communications and identifies (945) an adjustment to the E2E ML configuration. The network entity then directs at least some of the multiple devices participating in an UECS to update the respective sub-DNN of the E2E DNN based on the adjustment.

Abstract: Methods, devices, systems, and means for selection of a coordinating user equipment, UE, in a user equipment-coordination set, UECS, that facilitates selection of the coordinating UE by the UEs in the UECS are described herein. Sharing of the role of coordinating UE by UEs in the UECS can be scheduled in a round-robin manner. Selection criteria can be used to determine which one or more UEs in the UECS will offer better performance in the role of coordinating UE.

Abstract: The subject matter described herein provides systems and techniques to automatically configure a proximal device, such as a smart watch, a tablet, or any other smart device, based on configuration information sent from the user equipment (UE) to the proximal device when the local communications connection, such as a wireless connection, between the devices is weak. If it is determined that there is a weak local communications connection between the UE and the proximal device the UE may automatically send network configuration information to the proximal device. If it is determined that there is a weak local communications connection between the UE and the proximal device the UE may automatically turn on its mobile hotspot, and automatically send the mobile hotspot configuration information to the proximal device.

Abstract: Methods, devices, systems, and means for managing extended device pairing by a target device and a host device are described herein. The target device transmits a pairing intent message expressing an intent to pair with the host device (2002), receives a pairing response message in response to the transmitting the pairing intent message (2004), pairs with the host device (2006), and communicates data with the host device (2008).

Abstract: A user equipment (UE) reduces power consumption by selectively disconnecting from a radio access network (RAN) while in a non-standalone (NSA) mode in response to detecting a threshold number of communication failures associated with the RAN. The UE connects to a core network in the NSA mode via both a 4G RAN and a 5G RAN. The UE monitors the connection with the 5G RAN for communication failures, such as Random Access Channel (RACH) failures, radio link failures (RLFs), and the like. In response to the number of detected failures exceeding a threshold, the UE can determine that the quality of the connection with the 5G RAN is providing relatively little benefit and can terminate the connection with the 5G RAN.

Abstract: Techniques and apparatuses are described for modifying a position of an adaptive phase-changing device, APD. In aspects, a base station receives, from a user equipment, UE, at least one link quality parameter that is indicative of a channel impairment. The base station then identifies, using the at least one link quality parameter, a surface configuration for a reconfigurable intelligent surface (RIS) of an adaptive phase-changing device (APD) and transmits a first indication of the surface configuration using an adaptive phase-changing device control channel, APD control channel. In aspects, the base station determines using the at least one link quality parameter, a position configuration for the APD and transmits a second indication of the position configuration to the APD. The base station then communicates with the UE using the APD.

Abstract: The systems, methods, and techniques described in this disclosure allow different wireless systems that operate in accordance with different Radio Access Technologies (RATs) to coexist within a same frequency domain with minimal (if any) inter-RAT interference. Specifically, the described techniques allocate a respective, mutually-exclusive portion of a plurality of Space-Time-Frequency (STF) resources for use in communicating in accordance with each different RAT. For example, mutually-exclusive portions of spatial domain resources, time domain resources, and/or frequency domain resources may be respectively allocated for exclusive use by different RATs. A centralized, third-party controller (120) may perform the allocations, or the allocations may be cooperatively arrived at between systems supporting different RATs, e.g., in a peer-to-peer manner. STF resource allocations may be static and/or dynamic over time, and STF resources may be uniquely identified by respective resource identifiers.

Abstract: Techniques and apparatuses are described for machine-learning architectures for simultaneous connection to multiple carriers. In implementations, a network entity determines at least one deep neural network (DNN) configuration for processing information exchanged with a user equipment (UE) over a wireless communication system using carrier aggregation that includes at least a first component carrier and a second component carrier. At times, the at least one DNN configuration includes a first portion for forming a first DNN at the network entity, and a second portion for forming a second DNN at the UE. The network entity forms the first DNN based on the first portion and communicates an indication of the second portion to the UE. The network entity directs the UE to form the second DNN based on the second portion, and uses the first DNN to exchange, over the wireless communication system, the information with the UE using the carrier aggregation.

Abstract: This document describes improvements in management of data traffic of user equipment between cellular and non-cellular accesses in fifth generation new radio, 5G NR, wireless networks. An energy-aware traffic manager is introduced to manage data traffic communicated by the user equipment over the cellular access and the non-cellular access, such as a wireless local area network, WLAN. The energy-aware traffic manager enables reporting of energy-related information by user equipment, energy-aware traffic management modes for the user equipment, and access management in response to critical events related to user equipment energy, as well as reporting of changes in the user equipment access management or access management modality to core network entities.

Abstract: A user equipment (UE) employing different radio access technologies (RATs) concurrently or successively provides the UE the opportunity to select a particular RAT to support an access service used by one or more software applications of the UE. A RAT operational control scheme provides for opportunistic enablement and disablement of a RAT and/or intra-RAT configuration so as to provide sufficient uplink and downlink throughput for supported software applications while reducing unnecessary power consumption by the UE, which often is battery powered.

Abstract: The subject matter described herein provides systems and techniques to automatically configure a proximal device, such as a smart watch, a tablet, or any other smart device, based on configuration information sent from the user equipment (UE) to the proximal device when the local communications connection, such as a wireless connection, between the devices is weak. If it is determined that there is a weak local communications connection between the UE and the proximal device the UE may automatically send network configuration information to the proximal device. If it is determined that there is a weak local communications connection between the UE and the proximal device the UE may automatically turn on its mobile hotspot, and automatically send the mobile hotspot configuration information to the proximal device.

Abstract: Techniques and apparatuses are described for deep neural network (DNN) processing for a user equipment-coordination set (UECS). A network entity selects (910) an end-to-end (E2E) machine-learning (ML) configuration that forms an E2E DNN for processing UECS communications. The network entity directs (915) each device of multiple devices participating in an UECS to form, using at least a portion of the E2E ML configuration, a respective sub-DNN of the E2E DNN that transfers the UECS communications through the E2E communication, where the multiple devices include at least one base station, a coordinating user equipment (UE), and at least one additional UE. The network entity receives (940) feedback associated with the UECS communications and identifies (945) an adjustment to the E2E ML configuration. The network entity then directs at least some of the multiple devices participating in an UECS to update the respective sub-DNN of the E2E DNN based on the adjustment.

Abstract: This document describes methods, devices, systems, and means for performing a regrouping of a user equipment (UE) (113) between user equipment-coordination sets (UECS) by a base station (121) in which the base station (121) determines to regroup a user equipment (113) from a source UECS to a target UECS and transmits a release message to a coordinating UE (111) of the source UECS requesting the coordinating UE (111) of the source UECS to release the user equipment (113) from the source UECS (605). The base station (121) transmits a request message to a coordinating UE (114) of the target UECS requesting the coordinating UE (114) of the target UECS to add the user equipment (113) to the target UECS (610), and transmits a regrouping message to the user equipment (113) that is effective to direct the user equipment (113) is to perform a regrouping from the source UECS to the target UECS (615).