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: A wireless communication system employs DNNs or other neural networks to provide for RACH techniques. A TX DNN at user equipment (UE) generates and provides for wireless transmission of a Random Access (RA) signal to a base station (BS). A BS receives the RA signal as input, and from this input generates and provides for wireless transmission of an RA Response signal to the UE.

Abstract: A user equipment (UE) manages thermal levels of antenna modules with reference to a temperature threshold. The UE includes multiple antenna modules having a first antenna module and a second antenna module and at least one wireless transceiver coupled to the multiple antenna modules. The UE also includes a processor and memory system implementing an antenna module thermal manager. The manager is configured to obtain a first temperature indication corresponding to the first antenna module of the multiple antenna modules. The manager is also configured to perform a comparison of the first temperature indication to at least one temperature threshold. The manager is further configured to switch, based on the comparison, from using the first antenna module to using the second antenna module for wireless communication with the at least one wireless transceiver.

Abstract: Techniques and apparatuses are described for user equipment-coordination set, UECS, hybrid automatic repeat request, HARQ, that establish a HARQ timeline that is specific to the capabilities of a respective UECS. Compared to a single user equipment, UE, the HARQ timeline for a UECS depends on a number of factors, such as the joint processing capability in the UECS, latency of communication over a local wireless network between the UEs in the UECS, or the like. Based on its capabilities, the UECS can request uplink and/or downlink processing delay times or a UECS-specific HARQ timeline from a base station. The base station grants the uplink and/or downlink processing delay times or the UECS-specific HARQ timeline to the UECS in a layer-1, layer-2, or a layer-3 control message. The use of a UECS-specific HARQ timeline increases the reliability of HARQ signaling for uplink and downlink communication between the UECS and a base station.

Abstract: In aspects, a non-terrestrial communication system communicates with a user equipment, UE, using repetitive communications. The non-terrestrial communication system determines a repetition configuration for repetitive communications with the UE and indicates the repetition configuration to the UE. The non-terrestrial communication system communicates with the UE using the repetitive communications in accordance with the repetition configuration.

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: Techniques and apparatuses are described for adaptive phase-changing device power-saving operations. In aspects, a base station determines to transition an adaptive phase-changing device (APD) into an enabled APD-PS mode and determines an APD-PS configuration for the APD that specifies a framework for operating in the enabled APD-PS mode. The base station then directs the APD to operate in the enabled APD-PS mode by communicating the APD-PS configuration to the APD and transmits or receives wireless signals using a surface of the APD and based on the APD-PS configuration.

Abstract: Techniques and apparatuses are described for multiple-input multiple-output transmissions using adaptive phase-changing devices. In aspects, a base station selects one or more adaptive phase-changing devices, APDs, to use in at least one communication path for multiple-input, multiple-output, MIMO, transmissions. The base station can perform a channel characterization process for the at least one communication path using the at least one APD and at least one UE. Based on results of the channel characterization process, the base station configures the at least one APD by which to implement single user-MIMO communication with a UE or multiple user-MIMO communication with multiple UEs. By so doing, the base station may implement MIMO transmissions using APDs to communicate with the at least one UE using same time and frequency resources, which can improve spectral efficiency of a wireless network.

Abstract: A network entity transmits, to a first UE and a second UE, a plurality of reference signals via a plurality of beams corresponding to a plurality of subbands, receives, from the first UE, a first indicator of a first beam of the plurality of beams and a first subband of the plurality of subbands satisfying a first threshold, receives, from the second UE, a second indicator of the first beam and a second subband of the plurality of subbands satisfying a second threshold, the second subband being different from the first subband. The network entity further communicates, with the first UE in a slot, a first communication via the first beam and the first subband, and communicates, with the second UE in the slot, a second communication via the first beam and the second subband.

Abstract: This document describes techniques and apparatuses for a user equipment (UE)-coordination set for a wireless network. In aspects, a base station specifies a set of UEs to form a UE-coordination set for joint transmission and reception of data intended for a target UE within the UE-coordination set. The base station selects one of the UEs within the UE-coordination set to act as a coordinating UE for the UE-coordination set and transmits a request message that directs the coordinating UE to coordinate the joint transmission and reception of the data intended for the target UE. Then, the base station transmits a downlink signal to each UE within the UE-coordination set. Each UE within the UE-coordination set demodulates and samples the downlink signal and then forwards the samples to the coordinating UE, which combines the samples and processes the combined samples to provide decoded data.

Abstract: Techniques and apparatuses are described for adaptive phase-changing device power-saving operations. In aspects, a base station determines to transition an adaptive phase-changing device (APD) into an enabled APD-PS mode and determines an APD-PS configuration for the APD that specifies a framework for operating in the enabled APD-PS mode. The base station then directs the APD to operate in the enabled APD-PS mode by communicating the APD-PS configuration to the APD and transmits or receives wireless signals using a surface of the APD and based on the APD-PS configuration.

Abstract: This document describes methods, devices, systems, and means for dynamic carrier subband operation for active coordination sets. A master base station selects a first carrier subband associated with a first Active Coordination Set (ACS) for joint communication with a user equipment (UE), coordinates the joint communication for the UE with other base stations in the first ACS, and monitors the joint communication with the UE. Based on the monitoring of the joint communication, the master base station selects a second carrier subband that is associated with a second ACS for the joint communication with the UE and coordinates with base stations associated with the second ACS to jointly communicate with the UE using the second carrier subband.

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: A wireless communication system employs DNNs or other neural networks to provide for RAT-assisted positioning of UEs. A TX DNN at the BS generates and provides for wireless transmission of a reference signal to the UE. An RX DNN at the UE receives the reference signal and local UE sensor data as input, and from this input generates a UE measurement and sensor report. A TX DNN at the UE receives the report as an input, and from this input generates an RF signal representing the UE measurement and sensor report for transmission to the BS. An RX DNN at the BS receives the report from the RF signal as input, and from this input generates a position estimate of the UE.

Abstract: In aspects, a base station schedules air interface resources of a wireless communication system using one or more prediction metrics from a user equipment, UE. The base station receives (505), from the user equipment, user-equipment-prediction-metric capabilities. Based on the user-equipment-prediction-metric capabilities, the base station generates (510) a prediction-reporting request and communicates (515) the prediction-reporting request to the user equipment. The base station receives (520) one or more user-equipment-prediction-metric reports from the UE and schedules (525) the one or more air interface resources of the wireless communication system based on the one or more user-equipment-prediction-metric reports.

Abstract: Wireless networks may have thousands of configurable parameters, so manual tuning is infeasible. A self-organizing network (SON) can provide automation. However, automated algorithms are not designed to interact with a wireless network, and network experimentation can jeopardize reliability. To address the former, a SON facilitator of a wireless network management node exposes an API that can translate network configuration information for consumption by a SON enhancer, which may implement an AI algorithm for network tuning. The SON facilitator can also transform output from the SON enhancer into directions for controlling a test scenario, including generating a DL SON message describing the test to a UE. To further increase reliability during the test scenario, the UE can be provisioned with two wireless connections. A first connection is unchanged by the test scenario for stability, and a second connection is used for testing.

Abstract: This document describes techniques and apparatuses for optimizing a cellular network using machine learning. A network-optimization controller determines a performance metric to optimize for a cellular network. The network-optimization controller determines at least one network-configuration parameter that affects the performance metric. The network-optimization controller sends a gradient-request message to multiple base stations that directs multiple wireless transceivers to respectively evaluate gradients of the performance metric relative to the at least one network-configuration parameter. The network-optimization controller receives, from the multiple base stations, gradient-report messages generated by the multiple wireless transceivers, the gradient-report messages respectively including the gradients. The network-optimization controller analyzes the gradients using machine learning to determine at least one optimized network-configuration parameter.

Abstract: This document describes techniques and devices for determining a machine-learning architecture for network slicing. A user equipment (UE) executes a first application associated with a first requested quality-of-service level. The UE selects a first machine-learning architecture based on the first requested quality-of-service level. The UE transmits, to a network-slice manager of a wireless network, a first machine-learning architecture request message to request permission to use the first machine-learning architecture. The UE receives, from the network-slice manager, a first machine-learning architecture response message that grants permission to use the first machine-learning architecture based on a first network slice. The UE wirelessly communicates data for the first application using the first machine-learning architecture, the first machine-learning architecture being configured to compute an output based on an input using coefficients determined by the user equipment.

Abstract: In aspects, a high altitude platform station, HAPS, communicating with a user equipment, UE, using an adaptive phase-changing device, APD. The HAPS receives characteristics of the APD and selects the APD for inclusion in a wireless communication path with the UE based at least in part on the characteristics. The HAPS transmits a resource grant to the APD that includes an indication of air interface resources for an APD-Physical Downlink Control Channel, APD-PDCCH, between the HAPS and the APD, transmits, to the APD, an indication of phase vectors and timing information for a surface of the APD using the APD-PDCCH, and communicates with the UE using wireless transmissions that travel along the wireless communication path that includes the surface of the APD.

Abstract: This document describes techniques and devices for determining a machine-learning architecture. A user equipment (UE) transmits, to a network-slice manager of a wireless network, a first machine-learning architecture request message to request permission to use a first machine-learning architecture.