Abstract: Wireless communications systems and methods related to narrow beam-based channel access for communications in a wireless communication network operating over an unlicensed spectrum are provided. A first wireless communication device receives, from a second wireless communication device, one or more signals associated with a beam parameter. The first wireless communication device determines, at each of a plurality of locations, a signal measurement for at least one received signal of the one or more received signals. The first wireless communication device determines, based at least in part on an p-th percentile signal measurement and a q-th percentile signal measurement of the signal measurements at the plurality of locations, whether the second wireless communication device satisfies an interference condition.

Abstract: In an aspect, a first user equipment (UE) obtains one or more first radio frequency fingerprint (RFFP) measurements of one or more first downlink channels received at the first UE, one or more first sidelink channels received at the first UE, or both, and determines one or more locations of a target UE based on the one or more first RFFP measurements and a machine learning module, wherein the machine learning module is trained based on previously collected RFFP measurements of one or more downlink channels, RFFP measurements of one or more uplink channels, RFFP measurements of one or more sidelink channels, locations of one or more sidelink anchor UEs, locations of one or more base stations, or any combination thereof.

Abstract: In an aspect, a network node may obtain a plurality of radio frequency fingerprint positioning (RFFP) measurements associated with a transmission-reception point (TRP). The network node may obtain a position estimate of the TRP based on applying a positioning model to the plurality of RFFP measurements.

Abstract: Wireless communications systems and methods related to accessing a channel based on an interference condition in a wireless communication network are provided. For example, a method of wireless communication performed by a wireless communications device may include receiving, from a second wireless communication device, one or more signals associated with a beam parameter, determining, at each of a plurality of locations, a signal measurement for at least one received signal of the one or more received signals, and determining, based at least in part on a cumulative distribution of the signal measurements at the plurality of locations and a reference probability distribution, whether the second wireless communication device satisfies an interference condition. Other features are also claimed and described.

Abstract: Disclosed are techniques for wireless communication. In an aspect, a network device may obtain one or more uplink composite radio frequency fingerprint (RFFP) measurements, the one or more uplink composite RFFP measurements being based on multiple uplink reference signals observed at one or more Transmission/Reception Points (TRPs), the uplink reference signals being transmitted by multiple target devices over an uplink reference signal resource. The network device may determine estimated positions of the target devices based on applying a machine learning model to the one or more uplink composite RFFP measurements.

Abstract: Methods, systems, and devices for wireless communications are described. In some examples, a device (e.g., a user equipment (UE)) may obtain a configuration message indicating one or more neural network models from abase station. The UE may then obtain an indication of a sequence of operations for a signal processing procedure for a neural network model of the one or more neural network models. In some examples, the signal processing procedure includes an input pre-processing procedure or an output pre-processing procedure. Upon obtaining a signal from a base station, the UE may perform the signal processing procedure on the received signal for the neural network model according to the sequence of operations.

Abstract: Aspects presented herein may enable an LMF to configure AI/ML-based techniques/measurements for a set of base stations/TRPs to improve the performance of UL-based positioning. In one aspect, a network entity transmits a configuration to at least one network node to configure the at least one network node to perform an UL-based positioning measurement with at least one ML model, where each of the at least one ML model is associated with a corresponding ML model ID in which the at least one network node uses for the UL-based positioning measurement, where the UL-based positioning measurement is for a set of SRSs from a UE. The network entity receives the UL-based positioning measurement for the set of SRSs from the at least one network node. The network entity estimates a position of the UE based on the UL-based positioning measurement for the set of SRSs.

Abstract: Methods, systems, and devices for wireless communications are described that provide for mitigation of interference related to full-duplex communications for random access channel (RACH) initial access procedures in shared radio frequency spectrum. A user equipment (UE) may send different RACH preambles subsequent to a channel access procedure, based on whether full-duplex communications or half-duplex communications are being used at a corresponding network entity. The different RACH preambles may include a longer RACH preamble that is used when full-duplex is present, and a shorter RACH preamble that is used when full-duplex is not present. The shorter or longer RACH preamble may be used, for example, based at least in part on an open-loop transmit power for the RACH procedure, a RACH occasion configuration that provides different preamble lengths for different RACH occasions, a full-duplexing type that is being used, or any combinations thereof.

Abstract: A signal time delay estimation method includes: obtaining, at an apparatus, a plurality of RFFPs (radio frequency fingerprints) each based on a plurality of signal measurements of respective signals transferred between respective ones of a plurality of wireless signal transfer devices; obtaining, at the apparatus, a plurality of locations corresponding to the plurality of wireless signal transfer devices; and implementing, at the apparatus, a machine-learning algorithm to provide at least one first indication of at least one first signal time delay to convert between a first wireless signal at a target device, of the plurality of wireless signal transfer devices, and a first baseband signal at the target device based on the plurality of RFFPs and the plurality of locations.

Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may receive a discovery burst from a network entity during the transmission duration. The received discovery burst may indicate a duplex operation mode used at the network entity for transmission of the discovery burst and a type of channel access procedure associated with a random access occasion included in the transmission duration. The UE may transmit a random access message to the network entity during the random access occasion based on a success of a channel access procedure. The channel access procedure may correspond to the indicated type of channel access procedure.

Abstract: A method of wireless communication performed by a wireless communications device may include receiving, from a second wireless communication device, one or more signals associated with a beam parameter, determining, for each of a plurality of locations within a first zone, a first signal measurement for the one or more received signals, determining, at each of a plurality of locations within a second zone, a second signal measurement for the one or more received signals, wherein the second zone is different from the first zone, and determining whether the second wireless communication device satisfies an interference condition based at least in part on a cumulative distribution of at least one of the first signal measurements at the plurality of locations within the first zone or a cumulative distribution of at least one of the second signal measurements at the plurality of locations within the second zone.

Abstract: Aspects presented herein may improve the accuracy of uplink-based positioning when at least one network entity participating in the uplink-based positioning is operating under an energy saving mode. In one aspect, a network entity receives information indicative of a set of antenna panel configurations for a plurality of network nodes, where the set of antenna panel configurations is associated with a set of energy saving modes. The network entity transmits an indication of one or more UL-SRS transmission parameters for a UE based on the information indicative of the set of antenna panel configurations for the plurality of network nodes. In some examples, each antenna panel configuration in the set of antenna panel configurations may include a number of antennas to be used in an UL azimuth angle measurement and a number of antennas to be used in an UL elevation angle measurement under one energy saving mode.

Abstract: In an aspect, a method performed by a network node includes obtaining a first plurality of radio frequency fingerprint positioning (RFFP) measurements corresponding to a plurality of known displacements between positions of a user equipment (UE); and training a positioning model to provide a position estimate of the UE, wherein the training of the positioning model is at least based on the first plurality of RFFP measurements and the known displacements between the positions of the UE corresponding to the first plurality of RFFP measurements.

Abstract: Disclosed are techniques for identifying virtual anchors. In an aspect, a network entity obtains a set of data samples associated with a user equipment (UE), each data sample comprising a location of the UE and a set of multipath components (MPCs) obtained by the UE, and determines whether any MPCs in a subset of non-line-of-sight (NLOS) MPCs selected from at least one set of MPCs are associated with any previously identified virtual anchors in a database of found virtual anchors, wherein one or more first NLOS MPCs are removed from the set of data samples based on the one or more first NLOS MPCs being associated with a previously identified virtual anchor, and wherein one or more second NLOS MPCs are added to the database of found virtual anchors based on the one or more second NLOS MPCs not being associated with any previously identified virtual anchor.

Abstract: In an aspect, a method of wireless communication performed by a user equipment (UE) includes measuring a plurality of different bandwidth segments of a reference signal (RS) over a corresponding plurality of different RS occasions during a positioning session to obtain a plurality of radio frequency fingerprint positioning (RFFP) measurements corresponding to the plurality of different bandwidth segments; aggregating the plurality of RFFP measurements to provide at least one aggregated RFFP measurement; and applying a positioning model to the at least one aggregated RFFP measurement to obtain an estimate of one or more positioning parameters associated with a location of the UE.

Abstract: Methods, systems, and devices for wireless communications are described. In some wireless communications systems, a base station may transmit a set of reference signals spanning a channel to a user equipment (UE), where each of the reference signals is associated with one of a set of transmit beams. The UE may measure a signal quality of each of the set of reference signals. In some cases, each measured signal quality may correspond to one of a set of subbands of the channel and one of the set of transmit beams. The UE may then transmit an indication of at least one signal quality associated with one of the set of subbands and one of the set of transmit beams. In some cases, the UE may indicate the at least one signal quality according to a configuration that may be indicated by the base station or selected by the UE.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, an apparatus may obtain a set of training measurement information associated with a user equipment (UE). The apparatus may obtain a training position value associated with the UE. The apparatus may provide the training position value and the set of training measurement information for training of a model using a machine learning (ML) technique, the model being trained to output location information based at least in part on measurement information. Numerous other aspects are described.

Abstract: Disclosed are techniques for communication. In an aspect, a wireless node receives a configuration associated with one or more reference signal for positioning (RS-P) resources from a position estimation entity. The wireless node performs measurement(s) of a set of RS-P resources, and derives measurement information associated with a first virtual instance of the one or more RS-P resources based on the measurement(s). The wireless node transmits a measurement report comprising the measurement information to the position estimation entity.

Abstract: Aspects described herein relate to configuring a beam for communicating over a wireless channel, where the beam is associated with a channel access class based on a threshold for channel access and having at least one of a defined channel occupancy time (COT) or a defined minimum gap between communications, and communicating over the wireless channel using the beam and based on at least one of the defined COT or the defined minimum gap.

Abstract: In an aspect, a method performed by a network node includes obtaining a plurality of radio frequency fingerprint positioning (RFFP) measurements associated with known positioning parameters associated with a known location of a user equipment (UE), wherein each RFFP measurement of the plurality of RFFP measurements is further associated with a transmission point configuration of a plurality of transmission point configurations; and training a positioning model to provide an estimate of one or more positioning parameters associated with a location of the UE, wherein the training of the positioning model is based on the plurality of RFFP measurements, known positioning parameters associated with the known location, and the plurality of transmission point configurations.