Disclosed is an approach to enable optimized GNSS augmentation via learning at a mobile device. In particular, the mobile device could identify device-specific GNSS rescue area(s), the device-specific GNSS rescue area(s) corresponding to geographic area(s) visited by the mobile device in which (i) at least one GNSS-based position estimate is or was unavailable and (ii) the mobile device had demand for positioning data of at least a particular quality level. The mobile device could then receive, from positioning server(s), an offline radio map representing radio data only for the device-specific GNSS rescue area(s), and could store the offline radio map in a local data storage device. In turn, the mobile device could perform position estimation(s) using the offline radio map representing radio data only for the device-specific GNSS rescue area(s).

In accordance with the disclosed approach, positioning server(s) could receive, from mobile devices, information indicating a plurality of GNSS rescue areas, each respective GNSS rescue area of the plurality of GNSS rescue areas corresponding to a respective geographic area visited by a respective one of the mobile devices in which (i) at least one GNSS-based position estimate is or was unavailable and (ii) the respective mobile device had demand for positioning data of at least a particular quality level. Given this, the server(s) could generate a GNSS rescue map representing radio data for the plurality of GNSS rescue areas. In this way, the server(s) could transmit, to a mobile device, an offline radio map representing a subset of the GNSS rescue map, to provide radio data for at least one of the GNSS rescue areas or portion thereof.

In an aspect, a network component (e.g., BS, server, etc.) obtains measurement information associated with uplink signal(s) from UE(s), with the uplink signal(s) having reciprocity with one or more downlink beams of wireless node(s) (e.g., TRP, reference UE, etc.). The network component determines (e.g., generates or refines) a meausrement (e.g., RFFP-P) model based on the measurement information. The network component provides the measurement (e.g., RFFP-P) model to a target UE. The target UE receives at least one signal (e.g., PRS) on the one or more downlink beams from the wireless node(s). The target UE processes the at least one signal (e.g., predicts target UE location) based at least in part on the measurement (e.g., RFFP-P) model.

A system for determining a position of a user in a building includes a control device, a plurality of stationary radio signal transmission devices, a radio signal receiving device, and a signal processing device. The signal processing device determines primary channel impulse responses based on the radio signals received by the receiving device. The signal processing device also determines a secondary channel impulse response based on a secondary radio signal received by the receiving device from a mobile device of a user. The channel impulse responses are evaluated to determine degrees of similarity that indicate how similar a first primary channel impulse response and the secondary channel impulse response are to one another. For each degree of similarity, a distance of the mobile device from the transmission device corresponding to the degree of similarity is determined. A position of the mobile device is determined based on the distances.

The embodiments herein relate to method performed by a radio network node, a network node, a method performed by a UE, a UE, a method performed by a location server and a location server. The method performed by the network node includes: transmitting at least one signal to other network nodes; detecting signals transmitted from said other network nodes; measuring the signal strength of each received signal; transforming said measured signal strengths into a reference point or into measurement data; and transferring or transmitting the reference point or the measurement data to a location entity or a location node or a location server in the network.

Disclosed is an approach to enable radio map download for Global Navigation Satellite System (GNSS)-denied areas. In particular, processor(s) (e.g., of positioning server(s)) could identify GNSS-denied area(s) in an initial radio map, the GNSS-denied area(s) being (i) one or more areas in which at least one GNSS signal is or was unavailable and (ii) a subset of a plurality of areas represented by the initial radio map. Subsequently, the processor(s) could generate a partial radio map representing radio data only for the GNSS-denied area(s) identified in the initial radio map, and could then transmit the partial radio map to a mobile device for storage at the mobile device. In this way, the mobile device could optimize resource usage and perform radio-based position estimations at least in the GNSS-denied area(s) that were identified.

An edge device includes a first antenna array and control circuitry that activates a sensing function to sense a surrounding area of the edge device. The control tracks a position of the first UE in motion from the edge device and further executes beamforming to direct a first beam of RF signal having a signal strength greater than a threshold to the first UE in motion, based on the track of the position of the first UE for high-performance communication.

It is inter-alia disclosed a method comprises: obtaining or holding available at least one training set of radio signal observation results, wherein a respective training set of radio signal observation results is held available in association with identification information of a corresponding area of interest on a site, wherein a respective training set of radio signal observation results is captured at a corresponding observation position within a corresponding area of interest on said site; obtaining or holding available area of interest information indicating whether at least one tracking device has been determined to have entered and/or to have been located within a corresponding area of interest on the site; obtaining or holding available current radio signal observation data of a current tracking device representing one or more current sets of radio signal observation results captured by a radio interface of the current tracking device when present on said site, wherein a respective current set of radio signal observation results is captured at a corresponding observation position on said site; determining whether the current tracking device has entered or is located within an area of interest, identification information of which is associated with the at least one training set of radio signal observation results, based on at least one current set of radio signal observation results, based on at least one training set of radio signal observation results associated with the identification information of the area of interest, and based on the area of interest information.

In an aspect, a network component (e.g., BS, server, etc.) obtains measurement information associated with uplink signal(s) from UE(s), with the uplink signal(s) having reciprocity with one or more downlink beams of wireless node(s) (e.g., TRP, reference UE, etc.). The network component determines (e.g., generates or refines) a measurement (e.g., RFFP-P) model based on the measurement information. The network component provides the measurement (e.g., RFFP-P) model to a target UE. The target UE receives at least one signal (e.g., PRS) on the one or more downlink beams from the wireless node(s). The target UE processes the at least one signal (e.g., predicts target UE location) based at least in part on the measurement (e.g., RFFP-P) model.

An apparatus obtains a set of radio data comprising signal strength related values for radio signals transmitted by a transmitter with an association of each signal strength related value with a representation of a geographical location. The apparatus applies a frequency transform to the obtained set of radio data to obtain transform coefficients, each transform coefficient comprising a transform index and an associated transform value. The apparatus selects a subset of transform indices having more significant transform values than the remaining transform indices and compresses the transform indices by encoding each transform index exploiting a probability of occurrence of an index value of a respective transform index. The same or another apparatus decodes the compressed transform indices again for use in position operations.