Geolocating Minimization of Drive Test (MDT) measurement reports (MRs) with missing satellite navigation system coordinates is disclosed. In some embodiments, a computing node receives a plurality of complete MRs corresponding to a plurality of user equipments (UEs), wherein each complete MR comprises satellite navigation system coordinates identifying a geographic location of the corresponding UE. The computing node then trains a machine learning (ML) model for estimating UE geographic locations based on the plurality of complete MRs, wherein the ML model maps radio frequency (RF) signatures of complete MRs to corresponding UE geographic locations. In some embodiments, a radio access node obtains the ML model from the computing node, and receives an incomplete MR corresponding to a UE. Upon determining that the second MR lacks satellite navigation system coordinates, the radio access node predicts the geographic location of the UE based on measurements in the incomplete MR and the ML model.

Disclosed are techniques for wireless communication. In an aspect, a user equipment (UE) receives, over a wireless communication network operating in accordance with a first radio access technology (RAT), a configuration to provide at least one positioning state information (PSI) report, the first RAT associated with at least one first positioning technology, the configuration associated with at least one second RAT, at least one second positioning technology, or both to be used to estimate a location of the UE, obtains at least a first set of positioning measurements using the at least one second RAT, the at least one second positioning technology, or both, and transmits the at least one PSI report on physical resources allocated for a physical uplink or sidelink channel of the first RAT, the at least one PSI report including at least the first set of positioning measurements.

Methods, systems, and storage media are disclosed to estimate a count of indoor radio transmitters for a building, where the indoor radio transmitters are to be planned to build an indoor cellular network within the building. In one embodiment, a method comprises obtaining (310) locational information of the building in a database based on a query; extracting (312) features external to the building based on the locational information of the building, wherein the features external to the building capture characteristics about the building that are observable from outside of the building; and estimating (314) the count of the indoor radio transmitters for the building using the extracted features and a pre-trained model.

An information processing system comprising a portable information device, a relay apparatus that connects the portable information device to a network, and a server. The server includes a library in which, for each relay apparatus, an area where the relay apparatus is present is registered in association with relay apparatus identification information. The portable information device obtains connection authentication from the relay apparatus installed in an area where the own device is present, and when the authentication is successful, the relay apparatus that provides the authentication transmits the relay apparatus identification information to the server.

This application provide a MEC-based positioning method, a device, and a wireless communication system. The method includes: A first network element receives first positioning request information for requesting to position a terminal, and the first positioning request information carries identification information of the terminal. The first network element determines, based on the first positioning request information, a positioning functional entity for positioning the terminal, where the positioning functional entity is a positioning server. The first network element obtains second positioning request information based on the first positioning request information, and sends the second positioning request information to the positioning server. After receiving the second positioning request information, the positioning server sends measurement request information to the terminal via a user plane, to request the terminal to report measurement data. Then, the positioning server positions the terminal based on the measurement data reported by the terminal via the user plane.

This application pertains to the communications field, and discloses a positioning method, a communications device, and a network device. The positioning method includes: receiving first information, where the first information includes at least one of first machine learning model information, first preprocessing model information, and first error model information; and determining, based on the first information, information related to a location of a terminal device.

Disclosed are techniques for training a position estimation module. In an aspect, a first network entity obtains a plurality of positioning measurements, obtains a plurality of positions of one or more user equipments (UEs), the plurality of positions determined based on the plurality of positioning measurements, stores the plurality of positioning measurements as a plurality of features and the plurality of positions as a plurality of labels corresponding to the plurality of features, and trains the position estimation module with the plurality of features and the plurality of labels to determine a position of a UE from positioning measurements taken by the UE.

Neighbor relation conflict prediction is performed by operations including receiving, from a serving MCG of a terminal, a measurement report of the terminal including a plurality of signal measurements associated with an SCG represented by a PCI and an ARFCN, identifying an unlisted SCG among the plurality of signal measurements, identifying one or more nearby MCG within a threshold distance of the serving MCG, counting a number of SCG in the NRT of each nearby MCG having the PCI and the ARFCN of the unlisted SCG, applying a classification model to the counted number of SCG and an MCG-PCI-ARFCN identifier representing the serving MCG, the PCI, and the ARFCN to obtain a binary value indicating whether provisioning the unlisted SCG with the serving MCG and the plurality of nearby MCG will result in PCI conflict.

An interference detection system in a network identifies a first wireless station that has experienced radio frequency (RF) interference from an unknown source on at least one physical resource block (PRB) and identifies one or more second wireless stations that have experienced similar interference on the at least one PRB. A plurality of estimated interference source locations are determined based at least on geographic locations of the first wireless station and the one or more second wireless stations. The plurality of estimated interference source locations are scored based on a comparison of estimate interference to observed interference at the one or more second wireless stations and a geographical map is generated based on the scored plurality of estimated interference source locations, wherein the geographical map includes indicia indicative of the relative scores of the plurality of estimated interference source locations.

The described technology is generally directed towards proactive content placement for low latency mobile access. Digital content requested by a mobile device can be sent to network nodes proactively, so that the network nodes have the digital content before it is requested by the mobile device. Mobile device travel predictions can be made to predict future locations of the mobile device. The future locations can be used to determine network nodes for proactive digital content delivery. The digital content for delivery to a network node can also be predicted based on current digital content in use at the mobile device and estimated arrival times of the mobile device into service areas of next network nodes.