Abstract: Disclosed are techniques for positioning. In an aspect, a network node receives, from a network entity, one or more parameters for a neural network, performs one or more measurements of at least one reference signal from a target user equipment (UE) based on a measurement configuration for the at least one reference signal, generates one or more statistics of one or more features of the at least one reference signal based on the neural network and the one or more measurements, and reports the one or more statistics to the network entity to enable the network entity to estimate a location of the target UE based on the one or more statistics and a location of the network node.

Abstract: Aspects presented herein may enhance the accuracy and/or latency of UE positioning based on crowd-sourcing, where a network entity may compute a position estimate of a UE based on neighbor-cell scan data from the UE and one or more reference UEs. In one aspect, a network entity receives a first set of measurements associated with at least one cell from a UE. The network entity performs a position estimation of the UE based on at least one of the first set of measurements associated with the at least one cell, a second set of measurements for each of a set of reference UEs, or a location of each of the set of reference UEs via an ML model, where the UE and the set of reference UEs include at least one common cell.

Abstract: A method of wireless communication by a base station, jointly processes channel information associated with a user equipment, UE, in order to generate a jointly processed report. The channel information is collected from collocated transmit and receive points, TRPs (604, t1, t2, t3), of the base station. The base station transmits (t5) the jointly processed (t4) report to a location server (112).

Abstract: Disclosed are techniques for wireless communication. In an aspect, a first network node determines at least one positioning measurement based on a channel estimate of a positioning reference signal (PRS) transmitted by a second network node, and obtains measurement error feedback for at least the at least one positioning measurement, wherein the measurement error feedback is based on an expected positioning measurement corresponding to the at least one positioning measurement, and wherein the expected positioning measurement is based on a location of the first network node and a location of the second network node.

Abstract: Disclosed are techniques for wireless positioning. In an aspect, a base station determines a channel profile for a multipath channel between the base station and a user equipment (UE) based on at least one positioning reference signal transmitted to the UE or received from the UE by the base station on one or more radio beams, compresses the channel profile into a compressed representation of the channel profile, and transmits the compressed representation of the channel profile to a network entity. The network entity receives the compressed representation of the time-angle channel profile and determines a location of the UE based on the compressed representation of the channel profile.

Abstract: Disclosed are various techniques for wireless positioning. In an aspect, a base station calculates statistics of one or more time-angle metrics based on a signal received from a user equipment, and reports the statistics to a network entity, such as a location server, which uses the statistics to estimate a position of the UE. In some aspects, the network entity receives statistics from multiple base stations, which allows the network entity to more accurately determine the position of the UE. In some aspects, the base station reports the statistics to a network entity according to a statistics reporting configuration, which the network entity may provide to the base station.

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: Techniques are provided for determining a position of a mobile device. An example method of reporting a probability distribution for positioning a mobile device includes obtaining positioning measurements, determining one or more probability distributions of one or more positioning metrics based on the positioning measurements, determining a parametric representation of the one or more probability distributions, and reporting the parametric representation.