Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive a configuration that indicates a sounding reference signal (SRS) resource set to be used for analog channel state feedback (CSF) and an association between the SRS resource set and a set of downlink channel state information reference signals (CSI-RSs). The UE may measure the set of downlink CSI-RSs associated with the SRS resource set. The UE may transmit one or more SRSs for analog CSF using the SRS resource set and based at least in part on measuring the set of downlink CSI-RSs. Numerous other aspects are provided.

Abstract: Systems and techniques are disclosed to enhance the efficiency of available bandwidth between UEs and base stations. A UE transmits a sounding reference signal (SRS) to the base station. The base station characterizes the uplink channel based on the SRS received and, using reciprocity, applies the channel characterization for the downlink channel. As part of applying the channel information, the base station forms the beam to the UE based on the uplink channel information obtained from the SRS. The UE may include an array of antennas, each UE transmitting a different SRS that the base station receives and uses to characterize the downlink. Multiple UEs (or a single UE with multiple antennas) transmit SRS at the same time and frequency allocation (non-orthogonal), but with each sending its own unique SRS. Further, multiple UEs (or a single UE with multiple antennas) may send their SRS at unique time/frequency allocations (orthogonal).

Abstract: Various embodiments may employ neural networks at transmitting devices to compress transmit (TX) waveform distortion. In various embodiments, compressed TX waveform distortion information may be conveyed to a receiving device. In various embodiments, the signaling of TX waveform distortion information from a transmitting device to a receiving device may enable a receiving device to mitigate waveform distortion in a transmit waveform received from the transmitting device. Various embodiments include systems and methods of wireless communication by transmitting a waveform to a receiving device performed by a processor of a transmitting device. Various embodiments include systems and methods of wireless communication by receiving a waveform from a transmitting device performed by a processor of a receiving device.

Abstract: Methods, systems, and devices for wireless communications are described. The described techniques provide for the establishment of a communication link between a base station and a user equipment (UE). The UE may have a spatial partial reciprocity capability. The UE may be configured to determine antenna cross-correlation information for at least a first subset of antenna elements in the UE. The cross-correlation information may include one or more correlation parameters (e.g., correlation coefficients), a correlation model, or both. The UE may transmit sounding reference signals for a second set of antenna elements in accordance with the spatial partial reciprocity capability. The UE may also transmit an indication of the cross-correlation information for at least the first subset of antenna elements of the UE. The base station may use such information to derive correlation parameters for the unsounded antennas and determine precoders for downlink communications.

Abstract: Aspects of the present disclosure disclose techniques for the indication of the allocation of the downlink (DL) demodulation reference signal (DM-RS) ports for the data channel in NR communications. In some examples, the channel state information (CSI) reference signal (CSI-RS) may be associated with a corresponding DM-RS for a DL data channel. The transmitting device, in some examples, may further transmit a notification that provides resource allocations (e.g., port allocations) that minimize the redundant information that is required to be transmitted from the base station to the user equipment (UE) when the DM-RS port allocation is the same as the CSI-RS port allocation received by the UE in an earlier time slot.

Abstract: Certain aspects of the present disclosure generally relate to methods and apparatus for providing channel state feedback. One example method generally includes receiving at least one first pilot signal, and generating a first channel state information (CSI) report based on the at least one first pilot signal. The first CSI report may include a differential phase feedback for each subband (SB) of one or more SBs associated with the at least one first pilot signal. The method may also include transmitting the first CSI report having the differential phase feedback.

Abstract: In an embodiment, a network entity (e.g., a base station, a location server, etc.) transmits, to a user equipment (UE), at least one base station almanac (BSA) message that indicates (i) a set of transmission point locations associated with at least one base station, the set of transmission point locations including at least one transmission point location of a base station that is based upon a plurality of different transmission point locations associated with the base station, and (ii) a mapping of each of a plurality of beams to the at least one transmission point location. The UE receives the transmitted at least one BSA message.

Abstract: Methods, systems, and devices for wireless communications are described. In some systems, a user equipment (UE) may transmit feedback to a base station indicating phase values for sub-bands in a bandwidth part (BWP). The base station may use the phase feedback to perform precoding on a set of beams. To support a reduced payload overhead for the feedback, the UE may implement differential phase feedback. For example, the UE may divide the BWP into a number of sub-band groups and may generate, for each sub-band group of each beam, a first set of bits indicating an absolute phase value for a first sub-band of the sub-band group. The UE may additionally generate a second set of bits indicating differential phase values for the other sub-bands of each sub-band group. The UE may report the first and second sets of bits for the beams to the base station for precoding.

Abstract: Methods, systems, and devices for wireless communications are described. Techniques described herein provide for a user equipment (UE) receiving a set of downlink reference signals associated with a downlink channel. In some cases, the set of downlink reference signals may include a channel state information reference signals (CSI-RS). The UE may calculate a transmission rank and a channel quality based on the received set of downlink reference signals. In some cases, the indication of the transmission rank may include a rank indication (RI), and the indication of the channel quality includes a channel quality indicator (CQI). The UE may then transmit the indications of the transmission rank and the channel quality using an uplink control channel, and may transmit an indication of a remaining channel state feedback using a precoded uplink reference signal.

Abstract: A base station may precode a first reference signal using a first precoder (P1) and at least one second reference signal using at least one second precoder (P2). At least two UEs may measure the first reference signal and the at least one second reference signal, and transmit channel state feedback based on the measuring (m11 and m12 for a first UE, and m21 and m22 for a second UE). The channel state feedback may comprise channel state information compressed by at least one neural network. The base station may derive a higher-level precoder (W) for multiple-input multiple-output (MIMO) downlink transmission to the at least two UEs.

Abstract: Methods, systems, and devices for wireless communications are described. A configuration for a reference signal used to determine a non-linear behavior of transmission components at a transmitting device may be determined. The configuration for the reference signal may be determined based on signaling transmitted by the transmitting device, signaling transmitted by a device that receives the reference signal, or both. Additionally, or alternatively, the configuration for the reference signal may be determined based on a configuration of other signals transmitted by the transmitting device prior to or concurrently with the transmission of the reference signal. The determined configuration may be used to generate and transmit the reference signal or to determine a configuration of a received reference signal. In both cases, a non-linear response of transmission components at the transmitting device may be determined based on the reference signal.

Abstract: Certain aspects of the present disclosure generally relate to methods and apparatus for sounding reference signal (SRS) guided downlink channel state information-reference signal (CSI-RS) scan.

Abstract: Various embodiments include methods for reducing peak to average power ratio of wireless transmission waveforms, performed in transmitter circuitry of a wireless communication. Various embodiments may include receiving frequency domain data tones, transforming the frequency domain data tones to time domain data signals, generating, using a set of peak reduction tone (PRT) neural networks, time domain PRTs using the time domain data signals in which the set of PRT neural networks have been trained in conjunction with an augmentation neural network, and a receiver neural network, generating an output of the augmentation neural network based on an input of final combined time domain signals including the time domain PRTs combined with previous combined time domain signals, and generating time domain wireless transmission waveforms that include the output of the augmentation neural network combined with the final combined time domain signals.

Abstract: Various embodiments include methods for demodulating wireless transmission waveforms to reconstruct data tones, performed in receiver circuitry of a wireless communication device. The methods may include receiving time domain wireless transmission waveforms that include time domain peak reduction tones (PRTs) that were generated by a set of PRT neural networks using time domain data signals derived from frequency domain data tones in another wireless communication device, reconstructing the time domain data signals from the time domain wireless transmission waveforms using a receiver neural network that has been trained in conjunction with the set of PRT neural networks to generate a time domain reconstruction of data signals, and transforming the time domain reconstruction of data signals to a frequency domain reconstruction of data tones.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a client may determine, using a conditioning network and based at least in part on an observed environmental vector, a set of client-specific parameters. The client may determine a latent vector using a client autoencoder and based at least in part on the set of client-specific parameters and the set of shared parameters. The client may transmit the observed environmental vector and the latent vector to a server. Numerous other aspects are provided.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a first device may encode a data set using one or more extraction operations and compression operations associated with a neural network, the one or more extraction operations and compression operations being based at least in part on a set of features of the data set to produce a compressed data set. The first device may transmit the compressed data set to a second device. Numerous other aspects are provided.

Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may transmit a request for sets of neural network weights, each set corresponding to a neural network, to one or more network entities. The one or more network entities may transmit multiple sets of neural network weights to the UE in response to the request. The UE may run a classifier neural network on the sets of neural network weights to select a set of neural network weights corresponding to a neural network. The UE may transmit a neural network identifier to the one or more network entities that transmitted neural network weights.

Abstract: A user equipment (UE) receives, from a network entity, a message indicating a change in a set of downlink beams for channel state information reference signals (CSI-RSs), and a context associated with the change. The UE saves state values in an auto-encoder neural network in response to receiving the message and associates the saved state values in the auto-encoder neural network to the context in the received message. The UE also resets the state values in the auto-encoder neural network in response to receiving the message and estimates a channel state based on the CSI-RSs received on the changed set of downlink beams. The UE compresses the channel state with the auto-encoder neural network based on the reset state values and further sends to the network entity, the compressed channel state.

Abstract: In an aspect, a BS obtains at least one neural network function configured to facilitate a UE to derive a likelihood of at least one set of positioning measurement features being present at a candidate set of positioning estimates for the UE, the at least one neural network function being generated dynamically based on machine-learning associated with one or more historical measurement procedures. The BS transmits the at least one neural network function to the UE. In another aspect, the UE obtains positioning measurement data associated with a location of the UE (e.g., locally the UE, or remotely from the BS). The UE determines a positioning estimate for the UE based at least in part upon the positioning measurement data and the at least one neural network function.

Abstract: In an aspect, a UE obtains information (e.g., UE-specific information, etc.) associated with a set of triggering criteria for a set of neural network functions, the set of neural network functions configured to facilitate positioning measurement feature processing at the UE, the set of neural network functions being generated dynamically based on machine-learning associated with one or more historical measurement procedure, obtains positioning measurement data associated with a location of the UE, and determines a positioning estimate for the UE based at least in part upon the positioning measurement data and at least one neural network function from the set of neural network functions that is triggered by at least one triggering criterion from the set of triggering criteria.