WO2025097443A1

WO2025097443A1 - Devices, methods, and medium for communication

Info

Publication number: WO2025097443A1
Application number: PCT/CN2023/131077
Authority: WO
Inventors: Wei Chen; Peng Guan; Zhen He; Zhaobang MIAO; Gang Wang
Original assignee: NEC Corp
Current assignee: NEC Corp
Priority date: 2023-11-10
Filing date: 2023-11-10
Publication date: 2025-05-15
Anticipated expiration: 2026-05-10

Abstract

Example embodiments of the present disclosure relate to devices, methods, and computer storage medium for communication. A first device with a deployed AI/ML model may transmit a first reference signal for positioning to a second device and may determine at least one first Rx-Tx time difference, and the second device may determine at least one second Rx-Tx time difference, although a second reference signal for positioning from the second device to the first device is absent. In addition, an LMF may determine a Rx-Tx time difference pair and further determine a distance between the first device and the second device. As such, a matching between a first Rx-Tx time difference and a second Rx-Tx time difference is made by the LMF, and the positioning for the terminal device may be enabled.

Description

DEVICES, METHODS, AND MEDIUM FOR COMMUNICATION

FIELD

Example embodiments of the present disclosure generally relate to the field of communication techniques and in particular, to devices, methods, and a computer readable medium for communication.

BACKGROUND

Supporting various positioning methods to provide reliable, timely and accurate user equipment (UE) location is one of the key features of the third generation partnership project (3GPP) standard. It has been agreed to investigate the potential for artificial intelligence (AI) /machine learning (ML) in air interface to improve comprehensive performance in 5G-adcanced. AI/ML based mechanism to improve the positioning accuracy is one of the use cases to apply AI/ML in air interface.

Multiple round trip time (Multi-RTT) positioning is a technique used in wireless communication systems, particularly in the context of indoor positioning and location-based services. It leverages the time it takes for signals to travel between a mobile device and multiple reference points (anchors) in order to calculate the device's position accurately. However, details on multi-RTT positioning combining with AI/ML still need to be further studied.

SUMMARY

In general, example embodiments of the present disclosure provide devices, methods, and a computer storage medium for communication.

In a first aspect, there is provided a first device. The first device comprises at least one processor configured to cause the first device at least to: in accordance with a determination that a second reference signal for positioning from a second device is absent, determine an assumed receiving time of the second reference signal from a configuration of the second reference signal; determine a set of first reference signals for positioning associated with the assumed receiving time, wherein the set of first reference signals comprises at least one first reference signal with at least one transmitting time; determine, based on the assumed receiving time and the at least one transmitting time, at least one first receive-transmit (RX-TX) time difference by using an AI or ML model deployed at the first device; and transmit, to a location management function (LMF) , the at least one first RX-TX time difference

In a second aspect, there is provided a second device. The second device comprises at least one processor configured to cause the second device at least to: receive, from a first device, a first reference signal for positioning at a first receiving time; determine a set of second reference signals for positioning associated with the first receiving time based on a configuration of the second reference signals, wherein the set of second reference signals comprises at least one second reference signal having at least one configured time and being muted; determine at least one second RX-TX time difference based on the first receiving time and the at least one configured time; and transmit, to an LMF, the at least one second RX-TX time difference.

In a third aspect, there is provided a first device. The first device comprises at least one processor configured to cause the first device at least to: in accordance with a determination that a configuration of second reference signal for positioning from a second device is absent, determine a reference time point as an assumed receiving time; determine a set of first reference signals for positioning associated with the assumed receiving time, wherein the set of first reference signals comprises at least one first reference signal having at least one transmitting time; and determine, based on the reference time point and the at least one transmitting time, at least one first RX-TX time difference by using an AI or ML model deployed at the first device; and transmit, to an LMF, the at least one first RX-TX time difference.

In a fourth aspect, there is provided an LMF. The LMF comprises at least one processor configured to cause the LMF at least to: receive, from a first device, at least one first RX-TX time difference being determined by using an AI or ML model deployed at the first device; receive, from a second device, at least one second RX-TX time difference being determined based on at least a received first reference signal, wherein a second reference signal for positioning from the second device is absent; determine a RX-TX time difference pair by matching one of the at least one first RX-TX time difference and one of the at least one second RX-TX time difference; and perform a positioning estimation based on the RX-TX time difference pair.

In a fifth aspect, there is provided a method of communication. The method comprises: in accordance with a determination that a second reference signal for positioning from a second device is absent, determining, at a first device, an assumed receiving time of the second reference signal from a configuration of the second reference signal; determining a set of first reference signals for positioning associated with the assumed receiving time, wherein the set of first reference signals comprises at least one first reference signal with at least one transmitting time; determining, based on the assumed receiving time and the at least one transmitting time, at least one first RX-TX time difference by using an AI or ML model deployed at the first device; and transmitting, to an LMF, the at least one first RX-TX time difference.

In a sixth aspect, there is provided a method of communication. The method comprises: receiving, at a second device from a first device, a first reference signal for positioning at a first receiving time; determining a set of second reference signals for positioning associated with the first receiving time based on a configuration of the second reference signals, wherein the set of second reference signals comprises at least one second reference signal having at least one configured time and being muted; determining at least one second RX-TX time difference based on the first receiving time and the at least one configured time; and transmitting, to an LMF, the at least one second RX-TX time difference.

In a seventh aspect, there is provided a method of communication. The method comprises: in accordance with a determination that a configuration of second reference signal for positioning from a second device is absent, determining, at a first device, a reference time point as an assumed receiving time; determining a set of first reference signals for positioning associated with the assumed receiving time, wherein the set of first reference signals comprises at least one first reference signal having at least one transmitting time; and determining, based on the reference time point and the at least one transmitting time, at least one first RX-TX time difference by using an AI or ML model deployed at the first device; and transmitting, to an LMF, the at least one first RX-TX time difference.

In an eighth aspect, there is provided a method of communication. The method comprises: receiving, at an LMF from a first device, at least one first RX-TX time difference being determined by using an AI or ML model deployed at the first device; receiving, from a second device, at least one second RX-TX time difference being determined based on at least a received first reference signal, wherein a second reference signal for positioning from the second device is absent; determining a RX-TX time difference pair by matching one of the at least one first RX-TX time difference and one of the at least one second RX-TX time difference; and performing a positioning estimation based on the RX-TX time difference pair.

In a ninth aspect, there is provided a computer readable medium having instructions stored thereon, the instructions, when executed on at least one processor, causing the at least one processor to carry out the method according to any one of the fifth to the eighth aspects above.

It is to be understood that the summary section is not intended to identify key or essential features of embodiments of the present disclosure, nor is it intended to be used to limit the scope of the present disclosure. Other features of the present disclosure will become easily comprehensible through the following description.

BRIEF DESCRIPTION OF THE DRAWINGS

Through the more detailed description of some example embodiments of the present disclosure in the accompanying drawings, the above and other objects, features and advantages of the present disclosure will become more apparent, wherein:

FIG. 1A illustrates an overall procedure of multi-RTT positioning;

FIG. 1B illustrates an example process of RTT measurement between the UE and a specific gNB;

FIG. 1C illustrates an example schematic of RTT measurement between the UE and a specific gNB;

FIG. 1D illustrates an example schematic for determining a position;

FIG. 2 illustrates an example positioning system by wireless network in which some embodiments of the present disclosure can be implemented;

FIG. 3 illustrates a signalling chart illustrating communication process in accordance with some example embodiments of the present disclosure;

FIG. 4A illustrates an example environment with an AI/ML model deployed at the network device in accordance with some example embodiments of the present disclosure;

FIG. 4B illustrates an example schematic of gNB Rx-Tx time differences and UE Rx-Tx time differences in accordance with some example embodiments of the present disclosure;

FIG. 4C illustrates an example schematic of gNB Rx-Tx time differences and UE Rx-Tx time differences in accordance with some example embodiments of the present disclosure;

FIG. 4D illustrates an example schematic of gNB Rx-Tx time differences and UE Rx-Tx time differences in accordance with some example embodiments of the present disclosure;

FIG. 5A illustrates an example environment with an AI/ML model deployed at the terminal device in accordance with some example embodiments of the present disclosure;

FIG. 5B illustrates an example schematic of gNB Rx-Tx time differences and UE Rx-Tx time differences in accordance with some example embodiments of the present disclosure;

FIG. 5C illustrates an example schematic of gNB Rx-Tx time differences and UE Rx-Tx time differences in accordance with some example embodiments of the present disclosure;

FIG. 5D illustrates an example schematic of gNB Rx-Tx time differences and UE Rx-Tx time differences in accordance with some example embodiments of the present disclosure;

FIG. 6 illustrates a flowchart of an example method implemented at a first device in accordance with some embodiments of the present disclosure;

FIG. 7 illustrates a flowchart of an example method implemented at a second device in accordance with some embodiments of the present disclosure;

FIG. 8 illustrates a flowchart of an example method implemented at a first device in accordance with some embodiments of the present disclosure;

FIG. 9 illustrates a flowchart of an example method implemented at an LMF in accordance with some embodiments of the present disclosure; and

FIG. 10 illustrates a simplified block diagram of a device that is suitable for implementing embodiments of the present disclosure.

Throughout the drawings, the same or similar reference numerals represent the same or similar element.

DETAILED DESCRIPTION

Principle of the present disclosure will now be described with reference to some example embodiments. It is to be understood that these embodiments are described only for the purpose of illustration and help those skilled in the art to understand and implement the present disclosure, without suggesting any limitation as to the scope of the disclosure. Embodiments described herein can be implemented in various manners other than the ones described below.

In the following description and claims, unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skills in the art to which this disclosure belongs.

References in the present disclosure to “one embodiment, ” “an embodiment, ” “an example embodiment, ” and the like indicate that the embodiment described may include a particular feature, structure, or characteristic, but it is not necessary that every embodiment includes the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to affect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.

It shall be understood that although the terms “first” and “second” etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element could be termed a second element, and similarly, a second element could be termed a first element, without departing from the scope of example embodiments. As used herein, the term “and/or” includes any and all combinations of one or more of the listed terms.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms “a” , “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” , “comprising” , “has” , “having” , “includes” and/or “including” , when used herein, specify the presence of stated features, elements, and/or components etc., but do not preclude the presence or addition of one or more other features, elements, components and/or combinations thereof.

In some examples, values, procedures, or apparatus are referred to as “best, ” “lowest, ” “highest, ” “minimum, ” “maximum, ” or the like. It will be appreciated that such descriptions are intended to indicate that a selection among many used functional alternatives can be made, and such selections need not be better, smaller, higher, or otherwise preferable to other selections.

As used herein, the term “communication network” refers to a network following any suitable communication standards, such as New Radio (NR) , Long Term Evolution (LTE) , LTE-Advanced (LTE-A) , Wideband Code Division Multiple Access (WCDMA) , High-Speed Packet Access (HSPA) , Narrow Band Internet of Things (NB-IoT) and so on. Furthermore, the communications between a terminal device and a network device in the communication network may be performed according to any suitable generation communication protocols, including, but not limited to, the first generation (1G) , the second generation (2G) , 2.5G, 2.75G, the third generation (3G) , the fourth generation (4G) , 4.5G, the fifth generation (5G) , 5.5G, 5G-Advanced networks, or the sixth generation (6G) communication protocols, and/or any other protocols either currently known or to be developed in the future. Embodiments of the present disclosure may be applied in various communication systems. Given the rapid development in communications, there will of course also be future type communication technologies and systems with which the present disclosure may be embodied. It should not be seen as limiting the scope of the present disclosure to only the aforementioned system.

As used herein, the term “terminal device” refers to any device having wireless or wired communication capabilities. Examples of terminal device include, but not limited to, user equipment (UE) , personal computers, desktops, mobile phones, cellular phones, smart phones, personal digital assistants (PDAs) , portable computers, tablets, wearable devices, internet of things (IoT) devices, Ultra-reliable and Low Latency Communications (URLLC) devices, Internet of Everything (IoE) devices, machine type communication (MTC) devices, device on vehicle for V2X communication where X means pedestrian, vehicle, or infrastructure/network, devices for Integrated Access and Backhaul (IAB) , Space borne vehicles or Air borne vehicles in Non-terrestrial networks (NTN) including Satellites and High Altitude Platforms (HAPs) encompassing Unmanned Aircraft Systems (UAS) , eXtended Reality (XR) devices including different types of realities such as Augmented Reality (AR) , Mixed Reality (MR) and Virtual Reality (VR) , the unmanned aerial vehicle (UAV) commonly known as a drone which is an aircraft without any human pilot, devices on high speed train (HST) , or image capture devices such as digital cameras, sensors, gaming devices, music storage and playback appliances, or Internet appliances enabling wireless or wired Internet access and browsing and the like. The ‘terminal device’ can further has ‘multicast/broadcast’ feature, to support public safety and mission critical, V2X applications, transparent IPv4/IPv6 multicast delivery, IPTV, smart TV, radio services, software delivery over wireless, group communications and IoT applications. It may also be incorporated one or multiple Subscriber Identity Module (SIM) as known as Multi-SIM. The term “terminal device” can be used interchangeably with a UE, a mobile station, a subscriber station, a mobile terminal, a user terminal or a wireless device.

As used herein, the term “network device” refers to a device which is capable of providing or hosting a cell or coverage where terminal devices can communicate. Examples of a network device include, but not limited to, a satellite, a unmanned aerial systems (UAS) platform, a Node B (NodeB or NB) , an evolved NodeB (eNodeB or eNB) , a next generation NodeB (gNB) , a transmission reception point (TRP) , a remote radio unit (RRU) , a radio head (RH) , a remote radio head (RRH) , an IAB node, a low power node such as a femto node, a pico node, a reconfigurable intelligent surface (RIS) , and the like.

In one embodiment, the terminal device may be connected with a first network device and a second network device. One of the first network device and the second network device may be a master node and the other one may be a secondary node. The first network device and the second network device may use different radio access technologies (RATs) . In one embodiment, the first network device may be a first RAT device and the second network device may be a second RAT device. In one embodiment, the first RAT device is eNB and the second RAT device is gNB. Information related with different RATs may be transmitted to the terminal device from at least one of the first network device and the second network device. In one embodiment, first information may be transmitted to the terminal device from the first network device and second information may be transmitted to the terminal device from the second network device directly or via the first network device. In one embodiment, information related with configuration for the terminal device configured by the second network device may be transmitted from the second network device via the first network device. Information related with reconfiguration for the terminal device configured by the second network device may be transmitted to the terminal device from the second network device directly or via the first network device.

Communications discussed herein may conform to any suitable standards including, but not limited to, New Radio Access (NR) , Long Term Evolution (LTE) , LTE-Evolution, LTE-Advanced (LTE-A) , Wideband Code Division Multiple Access (WCDMA) , Code Division Multiple Access (CDMA) , cdma2000, and Global System for Mobile Communications (GSM) and the like. Furthermore, the communications may be performed according to any generation communication protocols either currently known or to be developed in the future. Examples of the communication protocols include, but not limited to, the first generation (1G) , the second generation (2G) , 2.5G, 2.85G, the third generation (3G) , the fourth generation (4G) , 4.5G, the fifth generation (5G) , and the sixth (6G) communication protocols. The techniques described herein may be used for the wireless networks and radio technologies mentioned above as well as other wireless networks and radio technologies. The embodiments of the present disclosure may be performed according to any generation communication protocols either currently known or to be developed in the future. Examples of the communication protocols include, but not limited to, the first generation (1G) , the second generation (2G) , 2.5G, 2.75G, the third generation (3G) , the fourth generation (4G) , 4.5G, the fifth generation (5G) communication protocols, 5.5G, 5G-Advanced networks, or the sixth generation (6G) networks.

The terminal device or the network device may have AI or ML capability. It generally includes a model which has been trained from numerous collected data for a specific function, and can be used to predict some information.

As used herein, a model may be equivalent to at least one of the following: an AI/ML model, a ML model, an AI model, a data-driven, a data processing model, an algorithm, a functionality, a procedure, a process, an entity, a function, a feature, a feature group, a model identifier (ID) , an ID, a functionality ID, a configuration ID, a scenario ID, a site ID, or a dataset ID. As a result, the above terms may be used interchangeably.

In some embodiments, the model may be represented by or associated with a channel, a resource, a resource set, a reference signal (RS) resource, a RS resource set, a RS port, a set of RS ports, a RS port ID, or a set of RS port IDs.

In some embodiments, the model may comprise a set of weights values that may be learned during training, for example for a specific architecture or configuration, where a set of weights values may also be called a parameter set.

In some embodiments, the model may be used to predict a target cell, or measurements of a set of beams of a set of candidate cells in future based on at least historical measurements (e.g., L1-RSRP, L1-SINR) of a set of beams of a set of candidate cells.

In some embodiments, an input of the ML model (i.e., AI input) may refer to the input of a model and indicate data inputted into the model, which may be equivalent to data.

In some embodiments, an output of ML model (i.e., AI output) may refers to the output of a model and indicate result (s) outputted by the model, which is equivalent to label/data.

The terminal device or the network device may work on several frequency ranges, e.g. FR1 (410 MHz –7125 MHz) , FR2 (24.25GHz to 71GHz) , frequency band larger than 200GHz as well as Tera Hertz (THz) . It can further work on licensed/unlicensed/shared spectrum. The terminal device may have more than one connection with the network device under Multi-Radio Dual Connectivity (MR-DC) application scenario. The terminal device or the network device can work on full duplex, flexible duplex and cross division duplex modes.

The embodiments of the present disclosure may be performed in test equipment, e.g., signal generator, signal analyzer, spectrum analyzer, network analyzer, test terminal device, test network device, or channel emulator.

The term “circuitry” used herein may refer to hardware circuits and/or combinations of hardware circuits and software. For example, the circuitry may be a combination of analog and/or digital hardware circuits with software/firmware. As a further example, the circuitry may be any portions of hardware processors with software including digital signal processor (s) , software, and memory (ies) that work together to cause an apparatus, such as a terminal device or a network device, to perform various functions. In a still further example, the circuitry may be hardware circuits and or processors, such as a microprocessor or a portion of a microprocessor, that requires software/firmware for operation, but the software may not be present when it is not needed for operation. As used herein, the term circuitry also covers an implementation of merely a hardware circuit or processor (s) or a portion of a hardware circuit or processor (s) and its (or their) accompanying software and/or firmware.

As used herein, the singular forms “a” , “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. The term “includes” and its variants are to be read as open terms that mean “includes, but is not limited to. ” The term “based on” is to be read as “based at least in part on. ” The term “one embodiment” and “an embodiment” are to be read as “at least one embodiment. ” The term “another embodiment” is to be read as “at least one other embodiment. ” The terms “first, ” “second, ” and the like may refer to different or same objects. Other definitions, explicit and implicit, may be included below.

Multi-RTT positioning is a technique used in wireless communication systems. The mobile device sends signals to a fixed reference point (anchors) , and the reference point bounce back a signal to the device. The mobile device and anchors record the time difference and report it the computing equipment. With the RTT measurements from at least three anchors, the device can use triangulation techniques to determine its position. By gathering the differences of the measurements, the system can calculate the distances between the device and each anchor. Using this information and the known positions of the anchors, the system can calculate the device's position. Multi-RTT positioning offers higher accuracy compared to single-RTT methods because it considers the round-trip time to multiple anchors, allowing for more precise distance measurements. This technique is particularly useful in indoor environments where global position system (GPS) signals might be weak or unavailable. It's commonly employed in technologies like Wi-Fi positioning systems, Bluetooth-based positioning, and other indoor positioning systems to provide accurate location information for various applications, such as indoor navigation, asset tracking, and location-based services.

The Multi-RTT positioning method makes use of the UE Rx-Tx time difference measurements and downlink-positioning reference signal-reference signal received power (DL-PRS-RSRP) of downlink signals received from multiple transmission and reception points (TRPs) , measured by the UE and the measured gNB Rx-Tx time difference measurements and uplink-sounding reference signal-reference signal received power (UL-SRS-RSRP) at multiple TRPs of uplink signals transmitted from UE. The UE measures the UE Rx-Tx time difference measurements (and optionally DL-PRS-RSRP of the received signals) using assistance data received from the positioning server, and the TRPs measure the gNB Rx-Tx time difference measurements (and optionally UL-SRS-RSRP of the received signals) using assistance data received from the positioning server. The measurements are used to determine the RTT at the positioning server which are used to estimate the location of the UE.

In the Multi-RTT positioning method, the UE position is estimated based on measurements performed at both, UE and TRPs. The measurements performed at the UE and TRPs are UE/gNB Rx-Tx time difference measurements (and optionally DL-PRS-RSRP and UL-SRS-RSRP) of DL-PRS and UL-SRS, which are used by an LMF to determine the RTTs.

FIG. 1A illustrates an overall procedure 110 of Multi-RTT positioning in next generation –radio access network (NG-RAN) . The following steps are involved in the procedure 110.

Step 0. The LMF may use the procedure, such as a new radio positioning protocol A (NRPPa) DL PRS configuration information exchange, to obtain the TRP information required for Multi-RTT positioning.

Step 1. The LMF may request the positioning capabilities of the target device using the long term evolution positioning protocol (LPP) Capability Transfer procedure.

Step 2. The LMF sends a NRPPa POSITIONING INFORMATION REQUEST message to the serving gNB to request UL information for the target device.

Step 3. The serving gNB determines the resources available for UL-SRS and configures the target device with the UL-SRS resource sets at step 3a.

Step 4. The serving gNB provides the UL-SRS configuration information to the LMF in a NRPPa POSITIONING INFORMATION RESPONSE message. It is noted that it is up to implementation on whether SRS configuration is provided earlier than DL-PRS configuration.

Step 5. In the case of semi-persistent or aperiodic SRS, the LMF may request activation of UE SRS transmission by sending a NRPPa Positioning Activation Request message to the serving gNB of the target device. The gNB then activates the UE SRS transmission and sends a NRPPa Positioning Activation Response message. The target device begins the UL-SRS transmission according to the time domain behavior of UL-SRS resource configuration.

Step 6. The LMF provides the UL information to the selected gNBs in a NRPPa MEASUREMENT REQUEST message. The message includes all information required to enable the gNBs/TRPs to perform the UL measurements.

Step 7. The LMF sends a LPP Provide Assistance Data message to the target device. The message includes any required assistance data for the target device to perform the necessary DL-PRS measurements.

Step 8. The LMF sends a LPP Request Location Information message to request Multi-RTT measurements.

Step 9a: The target device performs the DL-PRS measurements from all gNBs provided in the assistance data at step 7.

Step 9b: Each gNB configured at step 6 measures the UE SRS transmissions from the target device.

Step 10. The target device reports the DL-PRS measurements for Multi-RTT to the LMF in a LPP Provide Location Information message.

Step 11. Each gNB reports the UE SRS measurements to the LMF in a NRPPa Measurement Response message.

Step 12. The LMF sends a NRPPa POSITIONING DEACTIVATION message to the serving gNB.

Step 13. The LMF determines the RTTs from the UE and gNB Rx-Tx time difference measurements for each gNB for which corresponding UL and DL measurements were provided at steps 10 and 11 and calculates the position of the target device.

AI/ML based positioning has been introduced to enhance the positioning accuracy, especially for indoor scenario with low line of sight (LOS) condition probability. For the study of benefit (s) and potential specification impact for AI/ML based positioning accuracy enhancement, one-sided model whose inference is performed entirely at the UE or at the network is prioritized in Rel-18 study item (SI) .

The UE Rx-Tx time difference is defined as T_UE-RX -T_UE-TX, where: T_UE-RX is the UE received timing of downlink subframe #i from a Transmission Point (TP) , defined by the first detected path in time. T_UE-TX is the UE transmit timing of uplink subframe #j that is closest in time to the subframe #i received from the TP.

Multiple DL PRS or CSI-RS for tracking resources, as instructed by higher layers, can be used to determine the start of one subframe of the first arrival path of the TP. For frequency range 1, the reference point for T_UE-RX measurement shall be the Rx antenna connector of the UE and the reference point for T_UE-TX measurement shall be the Tx antenna connector of the UE. For frequency range 2, the reference point for T_UE-RX measurement shall be the Rx antenna of the UE and the reference point for T_UE-TX measurement shall be the Tx antenna of the UE.

The gNB Rx-Tx time difference is defined as T_gNB-RX -T_gNB-TX, where: T_gNB-RX is the TRP received timing of uplink subframe #i containing SRS associated with UE, defined by the first detected path in time. T_gNB-TX is the TRP transmit timing of downlink subframe #j that is closest in time to the subframe #i received from the UE.

Multiple SRS resources can be used to determine the start of one subframe containing SRS. The reference point for T_gNB-RX shall be:

- for type 1-C base station: the Rx antenna connector,

- for type 1-O or 2-O base station: the Rx antenna (i.e. the centre location of the radiating region of the Rx antenna) ,

- for type 1-H base station: the Rx Transceiver Array Boundary connector.

The reference point for T_gNB-TX shall be:

- for type 1-C base station: the Tx antenna connector,

- for type 1-O or 2-O base station: the Tx antenna (i.e. the centre location of the radiating region of the Tx antenna) ,

- for type 1-H base station: the Tx Transceiver Array Boundary connector.

FIG. 1B illustrates an example process 120 of RTT measurement between the UE and a specific gNB. The process 120 may include the following steps. Setp1: the gNB initiates a DL RTT measurement signaling, e.g., PRS, at time T_gNB _-TX. Step2: the UE receives the signaling at time T_UE-RX. Step3: the UE transmits a UL RTT measurement signaling, e.g., SRS-pos, at time T_UE-TX, and reports T_UE-RX -T_UE-TX as UE Rx-Tx time difference to LMF subsequently. Step4: the gNB receives the signaling at T_gNB-RX, and reports T_gNB-RX -T_gNB _-TX as gNB Rx-Tx time difference to LMF subsequently.

Ultimately, the linear distance (d) between the gNB and the UE can be estimated at the LMF side using the formula (1) :
d=| (T_gNB-RX-T_gNB _-TX) - (T_UE-TX-T_UE-RX) |c/2 (1)

where c represents the speed of light.

In some embodiments, | | in this application may be replaced by () .

The two Rx-Tx time differences (i.e., UE Rx-Tx time difference and gNB Rx-Tx time difference) in formula (1) are correlated through both PRS and SRS to estimate the distance between gNB and UE.

In additional, the measurements of UE Rx-Tx time difference and gNB Rx-Tx time difference can be correlated with only one reference signaling, either DL positioning RS or UL positioning RS. FIG. 1C illustrates an example schematic 130 of the process.

As illustrated in FIG. 1C, the gNB Rx-Tx time difference is measured between PRS1 and SRS, while the UE Rx-Tx time difference is measured between SRS and PRS2, according to the reported gNB Rx-Tx time difference and UE Rx-Tx time difference at the LMF side, the linear distance between the gNB and the UE can be estimated at the LMF side using the following formula (2) :
d=| (T_gNB-Rx-T_gNB-Tx) + (T_UE-Rx-T_UE-Tx) - (t₁-t₀) |c (2)

The two Rx-Tx time differences (i.e., UE Rx-Tx time difference and gNB Rx-Tx time difference) in formula (2) are correlated through only SRS to estimate the distance between gNB and UE.

The LMF calculates the UE position by employing triangulation, utilizing measurements from at least three pairs of signals between gNB/TRPs and UE, for example, FIG. 1D illustrates an example schematic 140 for determining a position by using a triangulation method.

According to the discussions above, e.g. with reference to FIGS. 1B-1C, two Rx-Tx time differences from different entities (i.e. gNB and UE) should be linked by at least one reference signal. Based on the technical principles outlined above, it is essential for the gNB Rx-Tx time difference and UE Rx-Tx time difference to be correlated through at least one DL or UL positioning reference signal. Without this correlation, the LMF cannot estimate the distance between the UE and a gNB from the reported measurements. In this event, a matching between UE Rx-Tx time difference measurement and gNB Rx-Tx time difference measurement is needed when combining the AI/ML technology with multi-RTT positioning method as the time difference inferred from AI/ML model.

Embodiments of the present disclosure provide a solution of communication. In the solution, a first device may be deployed with an AI/ML model, and the AI/ML model may be used to determine at least one first Rx-Tx time difference even though a second reference signal from a second device is absent. The at least one first Rx-Tx time difference may be linked to a specific (e.g., configured) second reference signal. In this event, the LMF may determine a Rx-Tx time difference pair by matching with the first or the second reference signal. Therefore, a positioning for a terminal device may be guaranteed. Principles and implementations of the present disclosure will be described in detail below with reference to the figures.

FIG. 2 illustrates an example communication system 200 in which some embodiments of the present disclosure can be implemented. The communication system 200 may also be called as a network environment, a network system, a communication environment, a communication network, or the like, the present disclosure does not limit this aspect. The communication system 200 includes a terminal device 210, a network device 220, and an LMF 230. For example, the LMF 230 may also be called as a location and mobility function. It should be appreciated that the LMF 230 may be located in the access network or core network.

In the system 200, the network device 220 can communicate/transmit data and control information to the terminal device 210, and the terminal device 210 can also communicate/transmit data and control information to the network device 220. A link from the network device 220 to the terminal device 210 is referred to as a downlink (DL) , while a link from the terminal device 210 to the network device 220 is referred to as an uplink (UL) . DL may comprise one or more logical channels, including but not limited to a Physical Downlink Control Channel (PDCCH) and a Physical Downlink Shared Channel (PDSCH) . UL may comprise one or more logical channels, including but not limited to a Physical Uplink Control Channel (PUCCH) and a Physical Uplink Shared Channel (PUSCH) . As used herein, the term “channel” may refer to a carrier or a part of a carrier consisting of a contiguous set of resource blocks (RBs) on which a channel access procedure is performed in shared spectrum.

Communications in the system 200, between the network device 220 and the terminal device 210 for example, may be implemented according to any proper communication protocol (s) , comprising, but not limited to, cellular communication protocols of the first generation (1G) , the second generation (2G) , the third generation (3G) , the fourth generation (4G) , the fifth generation (5G) and the sixth generation (6G) and on the like, wireless local network communication protocols such as Institute for Electrical and Electronics Engineers (IEEE) 802.11 and the like, and/or any other protocols currently known or to be developed in the future. Moreover, the communication may utilize any proper wireless communication technology, comprising but not limited to: Code Divided Multiple Address (CDMA) , Frequency Divided Multiple Address (FDMA) , Time Divided Multiple Address (TDMA) , Frequency Divided Duplexer (FDD) , Time Divided Duplexer (TDD) , Multiple-Input Multiple-Output (MIMO) , Orthogonal Frequency Divided Multiple Access (OFDMA) and/or any other technologies currently known or to be developed in the future.

In the system 200, the terminal device 210 can communicate with the LMF 230 according to any proper communication protocol, such as an LTE positioning protocol (LPP) . It is to be understood that other protocol may also be applied and will not be listed herein.

Embodiments of the present disclosure can be applied to any suitable scenarios. For example, embodiments of the present disclosure can be implemented at reduced capability NR devices. Alternatively, embodiments of the present disclosure can be implemented in one of the followings: NR multiple-input and multiple-output (MIMO) , NR sidelink enhancements, NR systems with frequency above 52.6GHz, an extending NR operation up to 71GHz, narrow band-Internet of Thing (NB-IOT) /enhanced Machine Type Communication (eMTC) over non-terrestrial networks (NTN) , NTN, UE power saving enhancements, NR coverage enhancement, NB-IoT and LTE-MTC, Integrated Access and Backhaul (IAB) , NR Multicast and Broadcast Services, or enhancements on Multi-Radio Dual-Connectivity.

It is to be understood that the numbers of devices (i.e., the terminal devices 210 and the network device 220) and their connection relationships and types shown in FIG. 2 are only for the purpose of illustration without suggesting any limitation. The system 200 may include any suitable numbers of devices adapted for implementing embodiments of the present disclosure.

It has been agreed to study and provide inputs on benefit (s) and potential specification impact at least for the following cases of AI/ML based positioning accuracy enhancement:

· Case 1: UE-based positioning with UE-side model, direct AI/ML or AI/ML assisted positioning;

· Case 2a: UE-assisted/LMF-based positioning with UE-side model, AI/ML assisted positioning;

· Case 2b: UE-assisted/LMF-based positioning with LMF-side model, direct AI/ML positioning;

· Case 3a: NG-RAN node assisted positioning with gNB-side model, AI/ML assisted positioning;

· Case 3b: NG-RAN node assisted positioning with LMF-side model, direct AI/ML positioning.

If the AI/Ml model is deployed at either the gNB or UE side to deduce the Rx-Tx time difference rather than measuring it by a configured positioning reference signaling, the transmission of DL/UL positioning reference signaling is absent. Consequently, the Rx-Tx time differences from different entities cannot be matched. Therefore, there must be a mechanism implemented at both the UE and gNB sides to assist the LMF in matching the gNB Rx-Tx time difference and UE Rx-Tx time difference as a valid measurement pair for estimating the distance between the gNB and the UE.

Reference is further made to FIG. 3, which illustrates a signalling chart illustrating communication process 300 in accordance with some example embodiments of the present disclosure. The process 300 may involve a first device 301, a second device 302, and an LMF 303. There may be an AI/ML model deployed at the first device 301, while there may be no AI/ML model at the second device 302.

In some examples, with reference to FIG. 2, the first device 301 may be the network device 220 with a deployed AI/ML model, and the second device 302 may be the terminal device 210. Details of some example embodiments of which may refer to FIGS. 4A-4D below.

In some other examples, with reference to FIG. 2, the first device 301 may be the terminal device 210 with a deployed AI/ML model, and the second device 302 may be the network device 220. Details of some example embodiments of which may refer to FIGS. 5A-5D below.

In the process 300, the first device 301 transmits a first reference signal for positioning to the second device 302 at 310. In some implementations, there is no transmission of second reference signal for positioning transmitted from the second device 302 to the first device 301. In some examples, the second reference signal from the second device 302 to the first device 301 may be configured but muted. In some other examples, the second reference signal from the second device 302 to the first device 301 may not be configured.

In the process 300, the first device 301 determines at least one first Rx-Tx time difference at 320. In some implementations, the first device 301 may determine an assumed receiving time, and further determine at least one first reference signal associated with the assumed receiving time. In some implementations, the first device 301 may further generate the at least one first Rx-Tx time difference based on the assumed receiving time and at least one transmitting time of the at least one first reference signal, by using an AI/ML model deployed at the first device 301.

In some examples, the assumed receiving time may be determined as a configured time of a second reference time, or may be determined as a reference time point. For example, the reference time point may be periodically configured, or may be determined based on an inference time of the AI/ML model.

In the process 300, the first device 301 transmits the at least one first Rx-Tx time difference to the LMF 303 at 340.

In the process 300, the second device 302 determines at least one second Rx-Tx time difference at 330. In some implementations, the second device 302 may determine a receiving time of the first reference signal transmitted at 310, and further determine at least one assumed transmitting time associated with the receiving time. In some implementations, the second device 302 may further generate the at least one second Rx-Tx time difference based on the receiving time and at least one assumed transmitting time.

In some examples, the assumed transmitting time may be determined as a configured time of a second reference time, or may be determined as a reference time point. For example, the reference time point may be periodically configured, or may be indicated by the first device 301, e.g. the first device 301 may determine the reference time point based on an inference time of the AI/ML model.

In the process 300, the second device 302 transmits the at least one second Rx-Tx time difference to the LMF 303 at 350.

In addition, the LMF 303 performs a positioning estimation at 360. In some implementations, the LMF 303 may determine a distance between the first device 301 and the second device 302 based on the at least one first Rx-Tx time difference and the at least one second Rx-Tx time difference. In some implementations, the LMF 303 may further determine a positon of a UE by using a triangulation technology or another technology, e.g., by considering other gNBs/TRPs.

FIGS. 4A-4D illustrate some examples for determining Rx-Tx time differences when an AI/ML model is deployed at the network device 220 in accordance with some example embodiments of the present disclosure.

FIG. 4A illustrates an example environment 410 with an AI/ML model deployed at the network device 220. FIG. 4A shows a schematic with a transmission of DL positioning reference signal, but without a transmission of UL positioning reference signal.

In this scenario, an AI/ML model is deployed at the network device 220 (e.g. gNB) side to infer the gNB Rx-Tx time difference, which may assist the LMF in calculating a UE location. For example, this scenario may be regarded to be equivalent to case 3a discussed above: NG-RAN node assisted positioning with gNB-side model, AI/ML assisted positioning.

In this case, the DL positioning RS (such as PRS) is transmitted as legacy, but the UL positioning RS (such as SRS) is: (a) either not be configured by the gNB, or (b) configured but not be transmitted by the UE since the gNB is not required to record T_gNB-RX for gNB Rx-Tx time difference measurement.

Since the UL positioning RS is absent, there is no link between the gNB Rx-Tx time difference measurement and the UE Rx-Tx time difference measurement, accordingly these two time differences cannot be directly correlated at the LMF side. Therefore, there is a need for a procedural change to reconcile RS based measurement and AI/ML model based measurement. This change should establish a connection between the gNB and UE measurements, allowing the LMF to accurately compute the UE location based on the combined data.

In some implementations, if the UL positioning RS is absent (muted) and the UL positioning RS is configured, the network device 220 (gNB) may determine an assumed receiving time of the UL positioning RS, e.g. from a configuration of the UL positioning RSs. In some examples, the assumed receiving time may be a configured time for the UL positioning RS.

In some example embodiments, the network device 220 may determine a time range based on the assumed receiving time, and further determine a set of DL positioning RSs within the time range, where the set of DL positioning RSs includes at least one DL positioning RS.

In some example embodiments, the time range may be determined based on a previous configured UL positioning RS before the assumed receiving time and a later configured UL positioning RS after the assumed receiving time. In some examples, the time range may be represented by a starting time and an end time, that is, the time range is a time period from the starting time to the end time. For example, the starting time is a first configured time of a RS with a same link as the UL positioning RS before the assumed receiving time. For example, the end time is a second configured time of a RS with a same link as the UL positioning RS after the assumed receiving time.

In some examples, all DL positioning RSs transmitted within the time range may be included in the set of DL positioning RSs. In some examples, there may be multiple DL positioning RSs within the time range, in this case, multiple gNB Rx-Tx time differences may be determined accordingly.

In some example embodiments, the network device 220 may further generate first integrated information for each gNB Rx-Tx time difference. The network device 220 may transmit the first integrated information together with a corresponding gNB Rx-Tx time difference, to the LMF 230.

For a non-limited example, a gNB Rx-Tx time difference may be generated based on the assumed receiving time of a UL positioning RS and a first transmitting time of a DL positioning RS by using the AI/ML model.

In some examples, the first integrated information may indicate the UL positioning RS and/or the DL positioning RS. For example, the first integrated information may include a first ID of the UL positioning RS and/or a second ID of the DL positioning RS. For example, the first integrated information may include information that combines the first ID of the UL positioning RS and the second ID of the DL positioning RS.

In some other examples, the first integrated information may include a bitstring, for example, the bitstring may include two parts. For example, a first part of the bitstring may indicate whether the first transmitting time regarding the DL positioning RS is before or after the assumed receiving time. For example, a second part of the bitstring may indicate a number of DL positioning RSs between the assumed receiving time and the first transmitting time.

For example, the first part of the bitstring may include one bit, e.g., the most significant bit (MSB) in the bitstring. For example, the bit may be “1” which indicates that the first transmitting time (DL positioning RS) is before the assumed receiving time (UL positioning RS) , and the bit may be “0” which indicates that the first transmitting time (DL positioning RS) is after the assumed receiving time (UL positioning RS) . For another example, the bit may be “0” which indicates that the first transmitting time (DL positioning RS) is before the assumed receiving time (UL positioning RS) , and the bit may be “1” which indicates that the first transmitting time (DL positioning RS) is after the assumed receiving time (UL positioning RS) .

For example, the second part of the bitstring may include at least two bits. For example, a value which the at least two bits represent may equal to the number of transmitted DL positioning RSs between the assumed receiving time and the first transmitting time.

FIG. 4B illustrates an example schematic 420 of gNB Rx-Tx time differences and UE Rx-Tx time differences in accordance with some example embodiments of the present disclosure. The AI/ML model is deployed at the gNB side, when the AI/ML model for gNB Rx-Tx time difference prediction is activated, the UE suspends its UL positioning RS transmission. For example, the UL positioning RS is configured by the gNB, but is muted because of the activated AI/ML model.

From the UE, a legacy behavior may be performed. Specifically, the UE measures Rx-Tx time difference by the received DL positioning RS and the closest UL positioning RS which is configured by the gNB. With reference to FIG. 4B, the UE receives the PRS 401, and determines corresponding UE Rx-Tx time difference 1. The UE receives the PRS 402, and determines corresponding UE Rx-Tx time difference 2. The UE receives the PRS 403, and determines corresponding UE Rx-Tx time difference 3. The UE receives the PRS 404, and determines corresponding UE Rx-Tx time difference 4. The UE receives the PRS 405, and determines corresponding UE Rx-Tx time difference 5.

For the gNB, after the AI/ML model is activated, the gNB may determine a UL positioning RS which is configured but muted, such as the SRS 411 in FIG. 4B. In addition, the gNB may determine one or multiple DL positioning RSs (within a time range) , which does not include the one (s) that is (are) configured before the previous UL positioning RS of this muted UL positioning RS or after the next UL positioning RS of muted UL positioning RS. With reference to FIG. 4B, the gNB may determine 4 PRSs associated with the muted SRS 411, including PRS 401, PRS 402, PRS 403, and PRS 404. In addition, the gNB may determine corresponding 4 gNB Rx-Tx time differences 407 by using the AI/ML model. For example, the model inference may be performed at a timestamp t1, and each gNB Rx-Tx time difference is associated with the muted SRS 411 and a PRS.

In addition, the gNB generates first integrated information (bitstring) corresponding a gNB Rx-Tx time difference. With reference to FIG. 4B, the first integrated information associated with the four PRSs 401-404 includes “100” , “101” , “000” , and “001” respectively. The MSB in the bitstring is “1” indicates that the PRS 401/402 is before the muted SRS 411, or is “0” indicates that the PRS 403/404 is after the muted SRS 411. The remaining bits in the bitstring are “00” indicates that there is no inserted PRS between the PRS 402/403 and the muted SRS 411, or are “01” indicates that there is 1 inserted PRS between the PRS 401/404 and the muted SRS 411.

It is to be understood that similar gNB Rx-Tx time difference and associated first integrated information may be determined, for the muted SRS 412 and the muted SRS 413. For example, the gNB may determine “gNB Rx-Tx time difference 101” and “gNB Rx-Tx time difference 100” 408 for muted SRS 412, and determine “gNB Rx-Tx time difference 000” 409 for muted SRS 413.

For the LMF, it may receive UE Rx-Tx time differences and gNB Rx-Tx time differences. The LMF may further match one UE Rx-Tx time difference with one gNB Rx-Tx time difference to determine a Rx-Tx time difference pair.

For example, for the muted SRS 411, the LMF may match any one of “UE Rx-Tx time difference 2” , “UE Rx-Tx time difference 3” , “UE Rx-Tx time difference 4” with any one of “gNB Rx-Tx time difference 100” , “gNB Rx-Tx time difference 101” , “gNB Rx-Tx time difference 000” , “gNB Rx-Tx time difference 001” 407. For example, for the muted SRS 412, the LMF may match “UE Rx-Tx time difference 3” with “gNB Rx-Tx time difference 101” 408, or match “UE Rx-Tx time difference 4” with “gNB Rx-Tx time difference 100” 408. For example, for the muted SRS 413, the LMF may match “UE Rx-Tx time difference 5” with “gNB Rx-Tx time difference 000” 409.

As such, there will be minimal impact on UE side, this solution allows the UE side behavior to remain unchanged. This means there are no alterations required in how the UE functions, leading to a seamless user experience. In other words, this solution may require fewer specifications and modifications, a specification effort is reduced. In addition, this solution facilitates the collection of more data for model training and monitoring purposes. By keeping the UE behavior consistent, it ensures a steady flow of data, which is valuable for refining and improving AI/ML models over time.

In some implementations, the UE may generate UE Rx-Tx time difference in a different way than the legacy. FIG. 4C illustrates an example schematic 430 of gNB Rx-Tx time differences and UE Rx-Tx time differences in accordance with some example embodiments of the present disclosure. The AI/ML model is deployed at the gNB side, when the AI/ML model for gNB Rx-Tx time difference prediction is activated, the UE suspends its UL positioning RS transmission.

For the gNB, it may determine gNB Rx-Tx time differences and corresponding first integrated information in a same manner that discussed with reference FIG. 4B, shown as 407, 408, and 409.

For the UE, it may receive a PRS at a receiving time, and further determine one or more configuration time of the muted SRSs (e.g. within a time range) associated with the received PRS. For example, the UE may determine one or multiple UL positioning RSs, which does not include the one (s) that is (are) configured before the previous DL positioning RS of this received DL positioning RS or after the next DL positioning RS of this received DL positioning RS.

With reference to FIG. 4C, for the received PRS 401, the UE may determine one SRS associated with the received PRS 401, in addition, determine a corresponding UE Rx-Tx time difference 431. For the received PRS 402, the UE may determine one SRS 411 associated with the received PRS 402, in addition, determine a corresponding UE Rx-Tx time difference 432. For the received PRS 403, the UE may determine one SRS 411 associated with the received PRS 403, in addition, determine a corresponding UE Rx-Tx time difference 434. For the received PRS 404, the UE may determine two SRSs 412 and 413 associated with the received PRS 404, in addition, determine corresponding UE Rx-Tx time differences 435 and 436. For the received PRS 405, the UE may determine two SRSs 412 and 413 associated with the received PRS 404, in addition, determine corresponding UE Rx-Tx time differences 437 and 438.

In addition, the UE generates second integrated information (bitstring) corresponding a UE Rx-Tx time difference. With reference to FIG. 4C, the second integrated information is a bitstring having three bits. The MSB indicates in the bitstring is “1” indicates that the corresponding SRS is before the received PRS, or is “0” indicates that the corresponding SRS is after the received PRS. The remaining bits in the bitstring are “00” indicates that there is no inserted SRS between the corresponding SRS and the received PRS, or are “01” indicates that there is 1 inserted SRS between the corresponding SRS and the received PRS.

For the LMF, it may receive UE Rx-Tx time differences and gNB Rx-Tx time differences. The LMF may further match one UE Rx-Tx time difference with one gNB Rx-Tx time difference to determine a Rx-Tx time difference pair. For example, based on the first integrated information and the second integrated information, a Rx-Tx time difference pair includes a UE Rx-Tx time difference and a gNB Rx-Tx time difference associated with a same PRS or a same SRS.

As such, this solution facilitates the collection of more data for model training and monitoring purposes.

In some implementations, if the UL positioning RS is not configured, the network device 220 (gNB) may determine a reference time point. In other words, a reference time point may be introduced to generate a UE Rx-Tx time difference and a gNB Rx-Tx time difference. For example, the reference time point may be taken as an assumed receiving time of a UL positioning RS which is not configured. In some example embodiments, the reference time point may be assigned by gNB and indicated to the UE.

In some examples, the reference time point may be defined as periodic. For example, the reference time point may be in a periodic form with a fixed step size in time domain. For example, a periodicity of the reference time point may be the same as or may be different from a transmission periodicity of PRS (or SRS) .

In some other examples, the reference time point may be determined by gNB, e.g. based on an inference time of the AI/ML model. In some example embodiments, the reference time point is related to a timestamp of AI/ML inference. For example, the reference time point is before the timestamp of AI/ML inference, and there is a fixed time gap from the reference time point to the timestamp of AI/ML inference.

The gNB may determine a gNB Rx-Tx time difference based on a transmitted PRS and the reference time point, in addition, first information may be generated and be reported to the LMF 230 together with the gNB Rx-Tx time difference. For example, the first information may indicate the transmitted PRS, e.g., the first information includes an ID of the PRS.

The UE may determine a UE Rx-Tx time difference based on a received PRS and the reference time point, in addition, second information may be generated and be reported to the LMF 230 together with the UE Rx-Tx time difference. For example, the second information may indicate the received PRS, e.g., the second information includes an ID of the PRS.

FIG. 4D illustrates an example schematic 440 of gNB Rx-Tx time differences and UE Rx-Tx time differences in accordance with some example embodiments of the present disclosure. The AI/ML model is deployed at the gNB side, and the UL positioning RS (such as SRS) is not configured.

As shown in FIG. 4D, the gNB may determine reference time points 451, 452, and 453 respectively based on timestamps of AI/ML inference. The gNB may transmit PRS 441, 442, and 443 to the UE respectively. The gNB may determine gNB Rx-Tx time difference 1, gNB Rx-Tx time difference 2, and gNB Rx-Tx time difference 3 respectively. The UE may determine UE Rx-Tx time difference 1, UE Rx-Tx time difference 2, and UE Rx-Tx time difference 3 respectively.

For the LMF 230, it may match “UE Rx-Tx time difference 1” with “gNB Rx-Tx time difference 1” , match “UE Rx-Tx time difference 2” with “gNB Rx-Tx time difference 2”, and match “UE Rx-Tx time difference 3” with “gNB Rx-Tx time difference 3” .

In some examples, the LMF 230 may estimate a distance between UE and gNB from the UE Rx-Tx time difference reported by UE and gNB Rx-Tx time difference reported by gNB. For example, assuming the UE reported a UE Rx-Tx time difference T_UE-TX-T_{ReferencePointTime}, where T_{ReferencePointTime} is the assigned reference point time, and the gNB reported a gNB Rx-Tx time difference (which is determined based on an output of an AI/ML model) Model Output, then the LMF 230 may determine that the distance is:

As such, this solution may have a minimal overhead of UE Rx-Tx time difference measurement report by synchronizing with AI/ML model inference in time domain.

FIGS. 5A-5D illustrate some examples for determining Rx-Tx time differences when an AI/ML model is deployed at the terminal device 210 in accordance with some example embodiments of the present disclosure.

FIG. 5A illustrates an example environment 510 with an AI/ML model deployed at the terminal device 210. FIG. 5A shows a schematic with a transmission of UL positioning reference signal, but without a transmission of DL positioning reference signal.

In this scenario, an AI/ML model is deployed at the terminal device 210 (e.g. UE) side to infer the UE Rx-Tx time difference, which may assist the LMF in calculating a UE location. For example, this scenario may be regarded to be equivalent to case 2a discussed above: UE-assisted/LMF-based positioning with UE-side model, AI/ML assisted positioning.

In this case, the UL positioning RS (such as SRS) is transmitted as legacy, but the DL positioning RS (such as PRS) is: (a) either not be configured by the network (e.g. LMF 230) , or (b) configured but not be transmitted by the gNB since the UE is not required to record T_UE-RX for UE Rx-Tx time difference measurement.

Since the DL positioning RS is absent, there is no link between the UE Rx-Tx time difference measurement and the gNB Rx-Tx time difference measurement, accordingly these two time differences cannot be directly correlated at the LMF side. Therefore, there is a need for a procedural change to reconcile RS based measurement and AI/ML model based measurement. This change should establish a connection between the UE and gNB measurements, allowing the LMF to accurately compute the UE location based on the combined data.

In some implementations, if the DL positioning RS is absent (muted) and the DL positioning RS is configured, the terminal device 210 (UE) may determine an assumed receiving time of the DL positioning RS, e.g. from a configuration of the DL positioning RSs. In some examples, the assumed receiving time may be a configured time for the DL positioning RS.

In some example embodiments, the terminal device 210 may determine a time range based on the assumed receiving time, and further determine a set of UL positioning RSs within the time range, where the set of UL positioning RSs includes at least one UL positioning RS.

In some example embodiments, the time range may be determined based on a previous configured DL positioning RS before the assumed receiving time and a later configured DL positioning RS after the assumed receiving time. In some examples, the time range may be represented by a starting time and an end time, that is, the time range is a time period from the starting time to the end time. For example, the starting time is a first configured time of a RS with a same link as the DL positioning RS before the assumed receiving time. For example, the end time is a second configured time of a RS with a same link as the DL positioning RS after the assumed receiving time.

In some examples, all UL positioning RSs transmitted within the time range may be included in the set of UL positioning RSs. In some examples, there may be multiple UL positioning RSs within the time range, in this case, multiple UE Rx-Tx time differences may be determined accordingly.

In some example embodiments, the terminal device 210 may further generate first integrated information for each UE Rx-Tx time difference. The terminal device 210 may transmit the first integrated information together with a corresponding UE Rx-Tx time difference, to the LMF 230.

For a non-limited example, a UE Rx-Tx time difference may be generated based on the assumed receiving time of a DL positioning RS and a first transmitting time of a UL positioning RS by using the AI/ML model.

In some examples, the first integrated information may indicate the DL positioning RS and/or the UL positioning RS. For example, the first integrated information may include a first ID of the DL positioning RS and/or a second ID of the UL positioning RS. For example, the first integrated information may include information that combines the first ID of the DL positioning RS and the second ID of the UL positioning RS.

In some other examples, the first integrated information may include a bitstring, for example, the bitstring may include two parts. For example, a first part of the bitstring may indicate whether the first transmitting time is before or after the assumed receiving time. For example, a second part of the bitstring may indicate a number of UL positioning RSs between the assumed receiving time and the first transmitting time.

For example, the first part of the bitstring may include one bit, e.g., the most significant bit (MSB) in the bitstring. For example, the bit may be “1” which indicates that the first transmitting time (UL positioning RS) is before the assumed receiving time (DL positioning RS) , and the bit may be “0” which indicates that the first transmitting time (UL positioning RS) is after the assumed receiving time (DL positioning RS) . For another example, the bit may be “0” which indicates that the first transmitting time (UL positioning RS) is before the assumed receiving time (DL positioning RS) , and the bit may be “1” which indicates that the first transmitting time (UL positioning RS) is after the assumed receiving time (DL positioning RS) .

For example, the second part of the bitstring may include at least two bits. For example, a value which the at least two bits represent may equal to the number of transmitted UL positioning RSs between the assumed receiving time and the first transmitting time.

FIG. 5B illustrates an example schematic 520 of gNB Rx-Tx time differences and UE Rx-Tx time differences in accordance with some example embodiments of the present disclosure. The AI/ML model is deployed at the UE side, when the AI/ML model for UE Rx-Tx time difference prediction is activated, the gNB suspends its DL positioning RS transmission. For example, the DL positioning RS is configured by the NW (such as LMF 230) , but is muted because of the activated AI/ML model.

From the gNB, a legacy behavior may be performed. Specifically, the gNB measures Rx-Tx time difference by the received UL positioning RS and the closest DL positioning RS which is configured. With reference to FIG. 5B, the gNB receives the SRS 511, and determines corresponding gNB Rx-Tx time difference 1. The gNB receives the SRS 512, and determines corresponding gNB Rx-Tx time difference 2. The gNB receives the SRS 513, and determines corresponding gNB Rx-Tx time difference 3. The gNB receives the SRS 514, and determines corresponding gNB Rx-Tx time difference 4.

For the UE, after the AI/ML model is activated, the UE may determine a DL positioning RS which is configured but muted, such as the PRS 501 in FIG. 5B. In addition, the UE may determine one or multiple UL positioning RSs (within a time range) , which does not include the one (s) that is (are) configured before the previous DL positioning RS of this muted DL positioning RS or after the next DL positioning RS of muted DL positioning RS.

With reference to FIG. 5B, for the configured but muted PRS 501, the UE may determine one SRS 511 associated with the muted PRS 501, in addition, determine a corresponding UE Rx-Tx time difference 521, for example, the model inference may be performed at a timestamp t1. For the muted PRS 502, the UE may determine one SRS 512 associated with the muted PRS 502, in addition, determine a corresponding UE Rx-Tx time difference 522, for example, the model inference may be performed at a timestamp t2. For the muted PRS 503, the UE may determine one SRS 512 associated with the muted PRS 503, in addition, determine a corresponding UE Rx-Tx time difference 523, for example, the model inference may be performed at a timestamp t3. For the muted PRS 504, the UE may determine two SRSs 513 and 514 associated with the muted PRS 504, in addition, determine corresponding UE Rx-Tx time differences 524, for example, the model inference may be performed at a timestamp t4. For the muted PRS 505, the UE may determine two SRS 513 and 514 associated with the muted PRS 505, in addition, determine corresponding UE Rx-Tx time differences 525, for example, the model inference may be performed at a timestamp t5.

In addition, the UE generates first integrated information (bitstring) corresponding a UE Rx-Tx time difference. With reference to FIG. 5B, the first integrated information is a bitstring having three bits. The MSB indicates in the bitstring is “1” indicates that the corresponding SRS is before the muted PRS, or is “0” indicates that the corresponding SRS is after the muted PRS. The remaining bits in the bitstring are “00” indicates that there is no inserted SRS between the corresponding SRS and the muted PRS, or are “01” indicates that there is 1 inserted SRS between the corresponding SRS and the muted PRS.

For the LMF, it may receive gNB Rx-Tx time differences and UE Rx-Tx time differences. The LMF may further match one gNB Rx-Tx time difference with one UE Rx-Tx time difference to determine a Rx-Tx time difference pair.

For example, for the muted PRS 501, the LMF may match “gNB Rx-Tx time difference 1” with “UE Rx-Tx time difference 100” 521. For example, for the muted PRS 502, the LMF may match “gNB Rx-Tx time difference 2” with “UE Rx-Tx time difference 000” 522. For example, for the muted PRS 503, the LMF may match “gNB Rx-Tx time difference 2” with “UE Rx-Tx time difference 100” 523. For example, for the muted PRS 504, the LMF may match “gNB Rx-Tx time difference 3” with “UE Rx-Tx time difference 000” or “UE Rx-Tx time difference 001” 524. For example, for the muted PRS 505, the LMF may match “gNB Rx-Tx time difference 4” with “UE Rx-Tx time difference 100” or “UE Rx-Tx time difference 101” 525.

As such, there will be minimal impact on gNB side, this solution allows the gNB side behavior to remain unchanged. This means there are no alterations required in how the gNB functions, leading to a seamless user experience. In other words, this solution may require fewer specifications and modifications, a specification effort is reduced. In addition, this solution facilitates the collection of more data for model training and monitoring purposes. By keeping the gNB behavior consistent, it ensures a steady flow of data, which is valuable for refining and improving AI/ML models over time.

In some implementations, the gNB may generate gNB Rx-Tx time difference in a different way than the legacy. FIG. 5C illustrates an example schematic 530 of UE Rx-Tx time differences and gNB Rx-Tx time differences in accordance with some example embodiments of the present disclosure. The AI/ML model is deployed at the UE side, when the AI/ML model for UE Rx-Tx time difference prediction is activated, the gNB suspends its DL positioning RS transmission.

For the UE, it may determine UE Rx-Tx time differences and corresponding first integrated information in a same manner that discussed with reference FIG. 5B, shown as 521, 522, 523, 524, 525.

For the gNB, it may receive a SRS at a receiving time, and further determine one or more muted PRSs (e.g. within a time range) associated with the received SRS. For example, the gNB may determine one or multiple DL positioning RSs, which does not include the one (s) that is (are) configured before the previous UL positioning RS of this received UL positioning RS or after the next UL positioning RS of this received UL positioning RS.

With reference to FIG. 5C, for the received SRS 511, the gNB may determine two PRS 501 and PRS 502 associated with the received SRS 511, in addition, determine corresponding gNB Rx-Tx time differences 531 and 532. For the received SRS 512, the gNB may determine three PRSs 502, 503, and 504 associated with the received SRS 512, in addition, determine corresponding gNB Rx-Tx time differences 533, 534, and 535. For the received SRS 513, the gNB may determine two PRSs 503 and 504 associated with the received SRS 513, in addition, determine corresponding gNB Rx-Tx time differences 536 and 537. For the received SRS 514, the gNB may determine one PRS 505 associated with the received SRS 514, in addition, determine a corresponding gNB Rx-Tx time difference 538.

In addition, the gNB generates second integrated information (bitstring) corresponding a gNB Rx-Tx time difference. With reference to FIG. 5C, the second integrated information is a bitstring having three bits. The MSB indicates in the bitstring is “1” indicates that the corresponding PRS is before the received SRS, or is “0” indicates that the corresponding PRS is after the received SRS. The remaining bits in the bitstring are “00” indicates that there is no inserted PRS between the corresponding PRS and the received SRS, or are “01” indicates that there is 1 inserted PRS between the corresponding PRS and the received SRS.

For the LMF, it may receive gNB Rx-Tx time differences and UE Rx-Tx time differences. The LMF may further match one gNB Rx-Tx time difference with one UE Rx-Tx time difference to determine a Rx-Tx time difference pair. For example, based on the first integrated information and the second integrated information, a Rx-Tx time difference pair includes a gNB Rx-Tx time difference and a UE Rx-Tx time difference associated with a same SRS or a same PRS.

In some implementations, if the DL positioning RS is not configured, the terminal device 210 (UE) may determine a reference time point. In other words, a reference time point may be introduced to generate a gNB Rx-Tx time difference and a UE Rx-Tx time difference. For example, the reference time point may be taken as an assumed receiving time of a DL positioning RS which is not configured.

In some examples, the reference time point may be defined as periodic. For example, the reference time point may be in a periodic form with a fixed step size in time domain. In some example embodiments, the periodic reference time point may be assigned by gNB and indicated to the UE. For example, a periodicity of the reference time point may be the same as or may be different from a transmission periodicity of SRS (or PRS) .

In some other examples, the reference time point may be determined by UE, e.g. based on an inference time of the AI/ML model. In some example embodiments, the reference time point is related to a timestamp of AI/ML inference. For example, the reference time point is before the timestamp of AI/ML inference, and there is a fixed time gap from the reference time point to the timestamp of AI/ML inference. For example, if the AI/ML model is transparent to the gNB, the UE may transmit an indication of the reference time point to the gNB.

The UE may determine a UE Rx-Tx time difference based on a transmitted SRS and the reference time point by using the AI/ML model, in addition, first information may be generated and be reported to the LMF 230 together with the UE Rx-Tx time difference. For example, the first information may indicate the transmitted SRS, e.g., the first information includes an ID of the SRS.

The gNB may determine a gNB Rx-Tx time difference based on a received SRS and the reference time point, in addition, second information may be generated and be reported to the LMF 230 together with the gNB Rx-Tx time difference. For example, the second information may indicate the received SRS, e.g., the second information includes an ID of the SRS.

FIG. 5D illustrates an example schematic 540 of UE Rx-Tx time differences and gNB Rx-Tx time differences in accordance with some example embodiments of the present disclosure. The AI/ML model is deployed at the UE side, and the DL positioning RS (such as PRS) is not configured.

As shown in FIG. 5D, the UE may determine reference time points 551, 552, and 553 respectively based on timestamps of AI/ML inference. The UE may transmit SRS 541, 542, and 543 to the gNB respectively. The UE may determine UE Rx-Tx time difference 1, UE Rx-Tx time difference 2, and UE Rx-Tx time difference 3 respectively by using the AI/ML model. The gNB may determine gNB Rx-Tx time difference 1, gNB Rx-Tx time difference 2, and gNB Rx-Tx time difference 3 respectively.

For the LMF 230, it may match “gNB Rx-Tx time difference 1” with “UE Rx-Tx time difference 1” , match “gNB Rx-Tx time difference 2” with “UE Rx-Tx time difference 2”, and match “gNB Rx-Tx time difference 3” with “UE Rx-Tx time difference 3” .

In some examples, the LMF 230 may estimate a distance between gNB and UE from the gNB Rx-Tx time difference reported by gNB and UE Rx-Tx time difference reported by UE. For example, assuming the gNB reported a gNB Rx-Tx time difference T_gNB-TX-T_{ReferencePointTime}, where T_{ReferencePointTime} is the assigned reference point time, and the UE reported a UE Rx-Tx time difference (which is determined based on an output of an AI/ML model) Model Output, then the LMF 230 may determine that the distance is:

As such, this solution may have a minimal overhead of gNB Rx-Tx time difference measurement report by synchronizing with AI/ML model inference in time domain.

According to the example embodiments described with reference to FIGS. 3-5D, the terminal device 210 (UE) may determine at least one UE Rx-Tx time difference, and the network device 220 (gNB) may determine at least one gNB Rx-Tx time difference, even though one of a DL or UL positioning RS is absent. In addition, the LMF 230 may determine a Rx-Tx time difference pair and further determine a distance between the terminal device 210 (UE) and the network device 220 (gNB) . As such, the positioning for the terminal device 210 may be enabled.

FIG. 6 illustrates a flowchart of an example method 600 implemented at a first device in accordance with some embodiments of the present disclosure. For example, the first device may be one of: a terminal device 210 or a network device 220 with a deployed AI/ML model with reference to FIG. 2.

At block 610, if a second reference signal for positioning from a second device is absent, the first device determines an assumed receiving time of the second reference signal from a configuration of the second reference signal. At block 620, the first device determines a set of first reference signals for positioning associated with the assumed receiving time, where the set of first reference signals comprises at least one first reference signal with at least one transmitting time. At block 630, the first device determines, based on the assumed receiving time and the at least one transmitting time, at least one first RX-TX time difference by using an AI or ML model deployed at the first device. At block 640, the first device transmits, to an LMF, the at least one first RX-TX time difference.

In some example embodiments, the assumed receiving time is a configured time for the second reference signal, and the first device determines a time range based on the assumed receiving time; and determines the set of first reference signals for positioning being located within the time range.

In some example embodiments, the time range comprises at least one of: a starting time, where the starting time is a first configured time of a reference signal with a same link as the second reference signal before the assumed receiving time, and an end time, where the end time is a second configured time of a reference signal with the same link as the second reference signal after the assumed receiving time.

In some example embodiments, the at least one processor is further configured to cause the first device generates first integrated information associated with each of the at least one first RX-TX time difference, and the first device transmits, to the LMF, the first integrated information associated with each of the at least one first RX-TX time difference.

In some example embodiments, the first integrated information comprises at least one of: a first identifier of the first reference signal, or a second identifier of the second reference signal.

In some example embodiments, the first integrated information comprises a bitstring, where a first part of the bitstring indicates whether the first transmitting time is before or after the assumed receiving time, a second part of the bitstring indicate a number of inserted first reference signals between the first transmitting time and the assumed receiving time.

In some example embodiments, the first device is a network device, the second device is a terminal device, the first reference signal is a downlink positioning reference signal, the second reference signal is an uplink sounding reference signal, and the at least one first RX-TX time difference is at least one gNB RX-TX time difference.

In some example embodiments, the first device is a terminal device, the second device is a network device, the first reference signal is an uplink sounding positioning reference signal, the second reference signal is a downlink positioning reference signal, and the at least one first RX-TX time difference is at least one UE RX-TX time difference.

FIG. 7 illustrates a flowchart of an example method 700 implemented at a second device in accordance with some embodiments of the present disclosure. For example, the second device may be one of: a terminal device 210 or a network device 220 without a deployed AI/ML model with reference to FIG. 2.

At block 710, the second device receives, from a first device, a first reference signal for positioning at a first receiving time. At block 720, the second device determines a set of second reference signals for positioning associated with the first receiving time based on a configuration of the second reference signals, where the set of second reference signals comprises at least one second reference signal having at least one configured time and being muted. At block 730, the second device determines at least one second RX-TX time difference based on the first receiving time and the at least one configured time. At block 740, the second device transmits, to an LMF, the at least one second RX-TX time difference.

In some example embodiments, the second device generates second integrated information associated with each of the at least one second RX-TX time difference, where the second integrated information at least indicates the first reference signal; and the second device transmits, to the LMF, the second integrated information associated with each of the at least one second RX-TX time difference.

In some example embodiments, the second integrated information comprises at least one of: a first identifier of the first reference signal, or a second identifier of the second reference signal.

In some example embodiments, the second integrated information comprises a bitstring, where a first part of the bitstring indicates whether the configured time is before or after the first receiving time, a second part of the bitstring indicate a number of inserted second reference signals between the first receiving time and the configured time.

In some example embodiments, the first device is a network device, the second device is a terminal device, the first reference signal is a downlink positioning reference signal, and the at least one second RX-TX time difference is at least one UE RX-TX time difference.

In some example embodiments, the first device is a terminal device, the second device is a network device, the first reference signal is an uplink sounding positioning reference signal, and the at least one second RX-TX time difference is at least one gNB RX-TX time difference.

FIG. 8 illustrates a flowchart of an example method 800 implemented at a first device in accordance with some embodiments of the present disclosure. For example, the first device may be one of: a terminal device 210 or a network device 220 with a deployed AI/ML model with reference to FIG. 2.

At block 810, if a configuration of second reference signal for positioning from a second device is absent, the first device determines a reference time point as an assumed receiving time. At block 820, the first device determines a set of first reference signals for positioning associated with the assumed receiving time, where the set of first reference signals comprises at least one first reference signal having at least one transmitting time. At block 830, the first device determines, based on the reference time point and the at least one transmitting time, at least one first RX-TX time difference by using an AI or ML model deployed at the first device. At block 840, the first device transmits, to an LMF, the at least one first RX-TX time difference.

In some example embodiments, the reference time point is preconfigured as periodic.

In some example embodiments, the at least one first RX-TX time difference represents a gap between a first subframe of the reference time point and a second subframe of the transmitting time of the first reference signal being closest in time to the reference time point.

In some example embodiments, the first device transmits, to the second device, an indication of the reference time point, where the reference time point is related to a timestamp of an inference of the AI or ML model.

In some example embodiments, the first device is a network device, the second device is a terminal device, the first reference signal is a downlink positioning reference signal, and the at least one first RX-TX time difference is at least one gNB RX-TX time difference.

In some example embodiments, the first device is a terminal device, the second device is a network device, the first reference signal is an uplink sounding positioning reference signal, and the at least one first RX-TX time difference is at least one UE RX-TX time difference.

FIG. 9 illustrates a flowchart of an example method 900 implemented at an LMF in accordance with some embodiments of the present disclosure. For the purpose of discussion, the method 900 will be described from the perspective of the LMF 230 with reference to FIG. 2.

At block 910, the LMF receives, from a first device, at least one first RX-TX time difference being determined by using an AI or ML model deployed at the first device. At block 920, the LMF receives, from a second device, at least one second RX-TX time difference being determined based on at least a received first reference signal, where a second reference signal for positioning from the second device is absent. At block 930, the LMF determines a RX-TX time difference pair by matching one of the at least one first RX-TX time difference and one of the at least one second RX-TX time difference. At block 940, the LMF performs a positioning estimation based on the RX-TX time difference pair.

In some example embodiments, the LMF receives, from the first device, first integrated information associated with each of the at least one first RX-TX time difference, where the first integrated information indicates at least one of: a first identifier of the first reference signal, or a second identifier of the second reference signal. In some example embodiments, the LMF receives, from the second device, second integrated information associated with each of the at least one second RX-TX time difference, where the second integrated information indicates at least one of: the first identifier of the first reference signal, or the second identifier of the second reference signal.

In some example embodiments, the first integrated information comprises a bitstring, where a first part of the bitstring indicates whether a first transmitting time of the first reference signal is before or after a configured time of the second reference signal, a second part of the bitstring indicate a number of inserted first reference signals between the first transmitting time and the configured time of the second reference signal.

In some example embodiments, the second integrated information comprises a bitstring, where a first part of the bitstring indicates whether the configured time is before or after a first receiving time of the first reference signal, a second part of the bitstring indicate a number of inserted second reference signals between the first receiving time and the configured time.

In some example embodiments, if both the one of the at least one first RX-TX time difference and the one of the at least one second RX-TX time difference are associated with a same second reference signal, the LMF determines that the RX-TX time difference pair comprises the one of the at least one first RX-TX time difference and the one of the at least one second RX-TX time difference.

In some example embodiments, the LMF determines a difference value of the one of the at least one first RX-TX time difference and the one of the at least one second RX-TX time difference; and determines a position of a terminal device based on the absolute value.

In some example embodiments, the first device is a network device, the second device is a terminal device, the first reference signal is a downlink positioning reference signal, the at least one first RX-TX time difference is at least one gNB RX-TX time difference, and the at least one second RX-TX time difference is at least one UE RX-TX time difference.

In some example embodiments, the first device is a terminal device, the second device is a network device, the first reference signal is an uplink sounding positioning reference signal, the at least one first RX-TX time difference is at least one UE RX-TX time difference, and the at least one second RX-TX time difference is at least one gNB RX-TX time difference.

Details of some embodiments according to the present disclosure have been described with reference to FIGS. 3-9. Now an example implementation of the terminal device and the network device will be discussed below.

In some example embodiments, a first device comprises circuitry configured to: in accordance with a determination that a second reference signal for positioning from a second device is absent, determine an assumed receiving time of the second reference signal from a configuration of the second reference signal; determine a set of first reference signals for positioning associated with the assumed receiving time, wherein the set of first reference signals comprises at least one first reference signal with at least one transmitting time; determine, based on the assumed receiving time and the at least one transmitting time, at least one first RX-TX time difference by using an AI or ML model deployed at the first device; and transmit, to an LMF, the at least one first RX-TX time difference.

In some example embodiments, the assumed receiving time is a configured time for the second reference signal, and the first device comprises circuitry configured to determine the set of first reference signals for positioning by: determining a time range based on the assumed receiving time; and determining the set of first reference signals for positioning being located within the time range.

In some example embodiments, the time range comprises at least one of: a starting time, wherein the starting time is a first configured time of a reference signal with a same link as the second reference signal before the assumed receiving time, and an end time, wherein the end time is a second configured time of a reference signal with the same link as the second reference signal after the assumed receiving time.

In some example embodiments, the first device comprises circuitry configured to: generate first integrated information associated with each of the at least one first RX-TX time difference, and transmit, to the LMF, the first integrated information associated with each of the at least one first RX-TX time difference.

In some example embodiments, the first integrated information comprises a bitstring, wherein a first part of the bitstring indicates whether the first transmitting time is before or after the assumed receiving time, a second part of the bitstring indicate a number of inserted first reference signals between the first transmitting time and the assumed receiving time.

In some example embodiments, a second device comprises circuitry configured to: receive, from a first device, a first reference signal for positioning at a first receiving time; determine a set of second reference signals for positioning associated with the first receiving time based on a configuration of the second reference signals, wherein the set of second reference signals comprises at least one second reference signal having at least one configured time and being muted; determine at least one second RX-TX time difference based on the first receiving time and the at least one configured time; and transmit, to an LMF, the at least one second RX-TX time difference.

In some example embodiments, the second device comprises circuitry configured to: generate second integrated information associated with each of the at least one second RX- TX time difference, wherein the second integrated information at least indicates the first reference signal; and transmit, to the LMF, the second integrated information associated with each of the at least one second RX-TX time difference.

In some example embodiments, the second integrated information comprises a bitstring, wherein a first part of the bitstring indicates whether the configured time is before or after the first receiving time, a second part of the bitstring indicate a number of inserted second reference signals between the first receiving time and the configured time.

In some example embodiments, a first device comprises circuitry configured to: in accordance with a determination that a configuration of second reference signal for positioning from a second device is absent, determine a reference time point as an assumed receiving time; determine a set of first reference signals for positioning associated with the assumed receiving time, wherein the set of first reference signals comprises at least one first reference signal having at least one transmitting time; and determine, based on the reference time point and the at least one transmitting time, at least one first RX-TX time difference by using an AI or ML model deployed at the first device; and transmit, to an LMF, the at least one first RX-TX time difference.

In one embodiment, the first device as above, the reference time point is preconfigured as periodic.

In one embodiment, the first device as above, the at least one first RX-TX time difference represents a gap between a first subframe of the reference time point and a second subframe of the transmitting time of the first reference signal being closest in time to the reference time point.

In one embodiment, the first device as above, the first device comprises circuitry configured to: transmit, to the second device, an indication of the reference time point, wherein the reference time point is related to a timestamp of an inference of the AI or ML model.

In one embodiment, the first device as above, the first device is a network device, the second device is a terminal device, the first reference signal is a downlink positioning reference signal, and the at least one first RX-TX time difference is at least one gNB RX-TX time difference.

In one embodiment, the first device as above, the first device is a terminal device, the second device is a network device, the first reference signal is an uplink sounding positioning reference signal, and the at least one first RX-TX time difference is at least one UE RX-TX time difference.

In some example embodiments, an LMF comprises circuitry configured to: receive, from a first device, at least one first RX-TX time difference being determined by using an AI or ML model deployed at the first device; receive, from a second device, at least one second RX-TX time difference being determined based on at least a received first reference signal, wherein a second reference signal for positioning from the second device is absent; determine a RX-TX time difference pair by matching one of the at least one first RX-TX time difference and one of the at least one second RX-TX time difference; and perform a positioning estimation based on the RX-TX time difference pair.

In some example embodiments, the LMF comprises circuitry configured to: receive, from the first device, first integrated information associated with each of the at least one first RX-TX time difference, wherein the first integrated information indicates at least one of: a first identifier of the first reference signal, or a second identifier of the second reference signal; or receive, from the second device, second integrated information associated with each of the at least one second RX-TX time difference, wherein the second integrated information indicates at least one of: the first identifier of the first reference signal, or the second identifier of the second reference signal.

In some example embodiments, the first integrated information comprises a bitstring, wherein a first part of the bitstring indicates whether a first transmitting time of the first reference signal is before or after a configured time of the second reference signal, a second part of the bitstring indicate a number of inserted first reference signals between the first transmitting time and the configured time of the second reference signal.

In some example embodiments, the second integrated information comprises a bitstring, wherein a first part of the bitstring indicates whether the configured time is before or after a first receiving time of the first reference signal, a second part of the bitstring indicate a number of inserted second reference signals between the first receiving time and the configured time.

In some example embodiments, the LMF comprises circuitry configured to determine a time difference pair by: in accordance with a determination that both the one of the at least one first RX-TX time difference and the one of the at least one second RX-TX time difference are associated with a same second reference signal, determining that the RX-TX time difference pair comprises the one of the at least one first RX-TX time difference and the one of the at least one second RX-TX time difference.

In some example embodiments, the LMF comprises circuitry configured to perform the positioning estimation by: determining a difference value of the one of the at least one first RX-TX time difference and the one of the at least one second RX-TX time difference; and determining a position of a terminal device based on the absolute value.

FIG. 10 illustrates a simplified block diagram of a device 1000 that is suitable for implementing embodiments of the present disclosure. The device 1000 can be considered as a further example implementation of the first device, the second device, or the LMF as described above. Accordingly, the device 1000 can be implemented at or as at least a part of the terminal device 210, the network device 220, or the LMF 230.

As shown, the device 1000 includes a processor 1010, a memory 1020 coupled to the processor 1010, a suitable transceiver 1040 coupled to the processor 1010, and a communication interface coupled to the transceiver 1040. The memory 1020 stores at least a part of a program 1030. The transceiver 1040 may be for bidirectional communications or a unidirectional communication based on requirements. The transceiver 1040 may include at least one of a transmitter and a receiver. The transmitter and the receiver may be functional modules or physical entities. The transceiver 1040 has at least one antenna to facilitate communication, though in practice an Access Node mentioned in this application may have several ones. The communication interface may represent any interface that is necessary for communication with other network elements, such as X2/Xn interface for bidirectional communications between eNBs/gNBs, S1/NG interface for communication between a Mobility Management Entity (MME) /Access and Mobility Management Function (AMF) /serving gateway (SGW) /user plane function (UPF) and the eNB/gNB, Un interface for communication between the eNB/gNB and a relay node (RN) , or Uu interface for communication between the eNB/gNB and a terminal device.

The program 1030 is assumed to include program instructions that, when executed by the associated processor 1010, enable the device 1000 to operate in accordance with the embodiments of the present disclosure, as discussed herein with reference to FIGS. 3-9. The embodiments herein may be implemented by computer software executable by the processor 1010 of the device 1000, or by hardware, or by a combination of software and hardware. The processor 1010 may be configured to implement various embodiments of the present disclosure. Furthermore, a combination of the processor 1010 and memory 1020 may form processing means 1050 adapted to implement various embodiments of the present disclosure.

The memory 1020 may be of any type suitable to the local technical network and may be implemented using any suitable data storage technology, such as a non-transitory computer readable storage medium, semiconductor-based memory devices, magnetic memory devices and systems, optical memory devices and systems, fixed memory and removable memory, as non-limiting examples. While only one memory 1020 is shown in the device 1000, there may be several physically distinct memory modules in the device 1000. The processor 1010 may be of any type suitable to the local technical network, and may include one or more of general purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs) and processors based on multicore processor architecture, as non-limiting examples. The device 1000 may have multiple processors, such as an application specific integrated circuit chip that is slaved in time to a clock which synchronizes the main processor.

In summary, embodiments of the present disclosure may provide the following solutions.

The present disclosure provides a first device, comprising at least one processor configured to cause the first device at least to: in accordance with a determination that a second reference signal for positioning from a second device is absent, determine an assumed receiving time of the second reference signal from a configuration of the second reference signal; determine a set of first reference signals for positioning associated with the assumed receiving time, wherein the set of first reference signals comprises at least one first reference signal with at least one transmitting time; determine, based on the assumed receiving time and the at least one transmitting time, at least one first RX-TX time difference by using an AI or ML model deployed at the first device; and transmit, to an LMF, the at least one first RX-TX time difference.

In one embodiment, the first device as above, the assumed receiving time is a configured time for the second reference signal, and wherein the at least one processor is configured to cause the first device to determine the set of first reference signals for positioning by: determining a time range based on the assumed receiving time; and determining the set of first reference signals for positioning being located within the time range.

In one embodiment, the first device as above, the time range comprises at least one of: a starting time, wherein the starting time is a first configured time of a reference signal with a same link as the second reference signal before the assumed receiving time, and an end time, wherein the end time is a second configured time of a reference signal with the same link as the second reference signal after the assumed receiving time.

In one embodiment, the first device as above, the at least one processor is further configured to cause the first device to: generate first integrated information associated with each of the at least one first RX-TX time difference, and transmit, to the LMF, the first integrated information associated with each of the at least one first RX-TX time difference.

In one embodiment, the first device as above, the first integrated information comprises at least one of: a first identifier of the first reference signal, or a second identifier of the second reference signal.

In one embodiment, the first device as above, the first integrated information comprises a bitstring, wherein a first part of the bitstring indicates whether the first transmitting time is before or after the assumed receiving time, a second part of the bitstring indicate a number of inserted first reference signals between the first transmitting time and the assumed receiving time.

In one embodiment, the first device as above, the first device is a network device, the second device is a terminal device, the first reference signal is a downlink positioning reference signal, the second reference signal is an uplink sounding reference signal, and the at least one first RX-TX time difference is at least one gNB RX-TX time difference.

In one embodiment, the first device as above, the first device is a terminal device, the second device is a network device, the first reference signal is an uplink sounding positioning reference signal, the second reference signal is a downlink positioning reference signal, and the at least one first RX-TX time difference is at least one UE RX-TX time difference.

The present disclosure provides a second device, comprising at least one processor configured to cause the second device at least to: receive, from a first device, a first reference signal for positioning at a first receiving time; determine a set of second reference signals for positioning associated with the first receiving time based on a configuration of the second reference signals, wherein the set of second reference signals comprises at least one second reference signal having at least one configured time and being muted; determine at least one second RX-TX time difference based on the first receiving time and the at least one configured time; and transmit, to an LMF, the at least one second RX-TX time difference.

In one embodiment, the second device as above, the at least one processor is further configured to cause the second device to: generate second integrated information associated with each of the at least one second RX-TX time difference, wherein the second integrated information at least indicates the first reference signal; and transmit, to the LMF, the second integrated information associated with each of the at least one second RX-TX time difference.

In one embodiment, the second device as above, the second integrated information comprises at least one of: a first identifier of the first reference signal, or a second identifier of the second reference signal.

In one embodiment, the second device as above, the second integrated information comprises a bitstring, wherein a first part of the bitstring indicates whether the configured time is before or after the first receiving time, a second part of the bitstring indicate a number of inserted second reference signals between the first receiving time and the configured time.

In one embodiment, the second device as above, the first device is a network device, the second device is a terminal device, the first reference signal is a downlink positioning reference signal, and the at least one second RX-TX time difference is at least one UE RX-TX time difference.

In one embodiment, the second device as above, the first device is a terminal device, the second device is a network device, the first reference signal is an uplink sounding positioning reference signal, and the at least one second RX-TX time difference is at least one gNB RX-TX time difference.

The present disclosure provides a first device, comprising at least one processor configured to cause the first device at least to: in accordance with a determination that a configuration of second reference signal for positioning from a second device is absent, determine a reference time point as an assumed receiving time; determine a set of first reference signals for positioning associated with the assumed receiving time, wherein the set of first reference signals comprises at least one first reference signal having at least one transmitting time; and determine, based on the reference time point and the at least one transmitting time, at least one first RX-TX time difference by using an AI or ML model deployed at the first device; and transmit, to an LMF, the at least one first RX-TX time difference.

In one embodiment, the first device as above, the at least one processor is further configured to cause the first device to: transmit, to the second device, an indication of the reference time point, wherein the reference time point is related to a timestamp of an inference of the AI or ML model.

The present disclosure provides an LMF, comprising at least one processor configured to cause the LMF at least to: receive, from a first device, at least one first RX-TX time difference being determined by using an AI or ML model deployed at the first device; receive, from a second device, at least one second RX-TX time difference being determined based on at least a received first reference signal, wherein a second reference signal for positioning from the second device is absent; determine a RX-TX time difference pair by matching one of the at least one first RX-TX time difference and one of the at least one second RX-TX time difference; and perform a positioning estimation based on the RX-TX time difference pair.

In one embodiment, the LMF as above, the at least one processor is further configured to cause the LMF to perform at least one of: receive, from the first device, first integrated information associated with each of the at least one first RX-TX time difference, wherein the first integrated information indicates at least one of: a first identifier of the first reference signal, or a second identifier of the second reference signal; or receive, from the second device, second integrated information associated with each of the at least one second RX-TX time difference, wherein the second integrated information indicates at least one of: the first identifier of the first reference signal, or the second identifier of the second reference signal.

In one embodiment, the LMF as above, the first integrated information comprises a bitstring, wherein a first part of the bitstring indicates whether a first transmitting time of the first reference signal is before or after a configured time of the second reference signal, a second part of the bitstring indicate a number of inserted first reference signals between the first transmitting time and the configured time of the second reference signal.

In one embodiment, the LMF as above, the second integrated information comprises a bitstring, wherein a first part of the bitstring indicates whether the configured time is before or after a first receiving time of the first reference signal, a second part of the bitstring indicate a number of inserted second reference signals between the first receiving time and the configured time.

In one embodiment, the LMF as above, the at least one processor is configured to cause the LMF to determine a time difference pair by: in accordance with a determination that both the one of the at least one first RX-TX time difference and the one of the at least one second RX-TX time difference are associated with a same second reference signal, determining that the RX-TX time difference pair comprises the one of the at least one first RX-TX time difference and the one of the at least one second RX-TX time difference.

In one embodiment, the LMF as above, the at least one processor is configured to cause the LMF to perform the positioning estimation by: determining a difference value of the one of the at least one first RX-TX time difference and the one of the at least one second RX-TX time difference; and determining a position of a terminal device based on the absolute value.

In one embodiment, the LMF as above, the first device is a network device, the second device is a terminal device, the first reference signal is a downlink positioning reference signal, the at least one first RX-TX time difference is at least one gNB RX-TX time difference, and the at least one second RX-TX time difference is at least one UE RX-TX time difference.

In one embodiment, the LMF as above, the first device is a terminal device, the second device is a network device, the first reference signal is an uplink sounding positioning reference signal, the at least one first RX-TX time difference is at least one UE RX-TX time difference, and the at least one second RX-TX time difference is at least one gNB RX-TX time difference.

The present disclosure provides a method of communication, comprising the operations implemented at the first device discussed above. The present disclosure provides a method of communication, comprising the operations implemented at the second device discussed above. The present disclosure provides a method of communication, comprising the operations implemented at the LMF discussed above.

The present disclosure provides a first device, comprising: a processor; and a memory storing computer program codes; the memory and the computer program codes configured to, with the processor, cause the first device to perform the method implemented at the first device discussed above.

The present disclosure provides a second device, comprising: a processor; and a memory storing computer program codes; the memory and the computer program codes configured to, with the processor, cause the second device to perform the method implemented at the second device discussed above.

The present disclosure provides an LMF, comprising: a processor; and a memory storing computer program codes; the memory and the computer program codes configured to, with the processor, cause the LMF to perform the method implemented at the LMF discussed above.

The present disclosure provides a non-transient computer readable medium having instructions stored thereon, the instructions, when executed by a processor of an apparatus, causing the apparatus to perform the method implemented at a first device, a second device, or an LMF discussed above.

The present disclosure provides a computer program product having instructions stored thereon, the instructions, when executed by a processor of an apparatus, causing the apparatus to perform the method implemented at a first device, a second device, or an LMF discussed above.

Generally, various embodiments of the present disclosure may be implemented in hardware or special purpose circuits, software, logic or any combination thereof. Some aspects may be implemented in hardware, while other aspects may be implemented in firmware or software which may be executed by a controller, microprocessor or other computing device. While various aspects of embodiments of the present disclosure are illustrated and described as block diagrams, flowcharts, or using some other pictorial representation, it will be appreciated that the blocks, apparatus, systems, techniques or methods described herein may be implemented in, as non-limiting examples, hardware, software, firmware, special purpose circuits or logic, general purpose hardware or controller or other computing devices, or some combination thereof.

The present disclosure also provides at least one computer program product tangibly stored on a non-transitory computer readable storage medium. The computer program product includes computer-executable instructions, such as those included in program modules, being executed in a device on a target real or virtual processor, to carry out the process or method as described above. Generally, program modules include routines, programs, libraries, objects, classes, components, data structures, or the like that perform particular tasks or implement particular abstract data types. The functionality of the program modules may be combined or split between program modules as desired in various embodiments. Machine-executable instructions for program modules may be executed within a local or distributed device. In a distributed device, program modules may be located in both local and remote storage media.

Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowcharts and/or block diagrams to be implemented. The program code may execute entirely on a machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

The above program code may be embodied on a machine readable medium, which may be any tangible medium that may contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine readable medium may be a machine readable signal medium or a machine readable storage medium. A machine readable medium may include but not limited to an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the machine readable storage medium would include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM) , a read-only memory (ROM) , an erasable programmable read-only memory (EPROM or Flash memory) , an optical fiber, a portable compact disc read-only memory (CD-ROM) , an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

Further, while operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are contained in the above discussions, these should not be construed as limitations on the scope of the present disclosure, but rather as descriptions of features that may be specific to particular embodiments. Certain features that are described in the context of separate embodiments may also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment may also be implemented in multiple embodiments separately or in any suitable sub-combination.

Although the present disclosure has been described in language specific to structural features and/or methodological acts, it is to be understood that the present disclosure defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.

Claims

A first device comprising at least one processor configured to cause the first device at least to:

in accordance with a determination that a second reference signal for positioning from a second device is absent, determine an assumed receiving time of the second reference signal from a configuration of the second reference signal;

determine a set of first reference signals for positioning associated with the assumed receiving time, wherein the set of first reference signals comprises at least one first reference signal with at least one transmitting time;

determine, based on the assumed receiving time and the at least one transmitting time, at least one first receive-transmit (RX-TX) time difference by using an artificial intelligence (AI) or machine learning (ML) model deployed at the first device; and

transmit, to a location management function (LMF) , the at least one first RX-TX time difference.
The first device of claim 1, wherein the assumed receiving time is a configured time for the second reference signal, and wherein the at least one processor is configured to cause the first device to determine the set of first reference signals for positioning by:

determining a time range based on the assumed receiving time; and

determining the set of first reference signals for positioning being located within the time range.
The first device of claim 2, wherein the time range comprises at least one of:

a starting time, wherein the starting time is a first configured time of a reference signal with a same link as the second reference signal before the assumed receiving time, and

an end time, wherein the end time is a second configured time of a reference signal with the same link as the second reference signal after the assumed receiving time.
The first device of claim 2, wherein the at least one processor is further configured to cause the first device to:

generate first integrated information associated with each of the at least one first RX-TX time difference, and

transmit, to the LMF, the first integrated information associated with each of the at least one first RX-TX time difference.
The first device of claim 4, wherein the first integrated information comprises a bitstring, wherein a first part of the bitstring indicates whether the first transmitting time is before or after the assumed receiving time, a second part of the bitstring indicate a number of inserted first reference signals between the first transmitting time and the assumed receiving time.
The first device of claim 1, wherein the first device is a network device, the second device is a terminal device, the first reference signal is a downlink positioning reference signal, the second reference signal is an uplink sounding reference signal, and the at least one first RX-TX time difference is at least one gNB RX-TX time difference.
The first device of claim 1, wherein the first device is a terminal device, the second device is a network device, the first reference signal is an uplink sounding positioning reference signal, the second reference signal is a downlink positioning reference signal, and the at least one first RX-TX time difference is at least one user equipment (UE) RX-TX time difference.
A second device comprising at least one processor configured to cause the second device at least to:

receive, from a first device, a first reference signal for positioning at a first receiving time;

determine a set of second reference signals for positioning associated with the first receiving time based on a configuration of the second reference signals, wherein the set of second reference signals comprises at least one second reference signal having at least one configured time and being muted;

determine at least one second receive-transmit (RX-TX) time difference based on the first receiving time and the at least one configured time; and

transmit, to a location management function (LMF) , the at least one second RX-TX time difference.
The second device of claim 8, wherein the at least one processor is further configured to cause the second device to:

generate second integrated information associated with each of the at least one second RX-TX time difference, wherein the second integrated information at least indicates the first reference signal; and

transmit, to the LMF, the second integrated information associated with each of the at least one second RX-TX time difference.
The second device of claim 9, wherein the second integrated information comprises a bitstring, wherein a first part of the bitstring indicates whether the configured time is before or after the first receiving time, a second part of the bitstring indicate a number of inserted second reference signals between the first receiving time and the configured time.
The second device of claim 8, wherein the first device is a network device, the second device is a terminal device, the first reference signal is a downlink positioning reference signal, and the at least one second RX-TX time difference is at least one user equipment (UE) RX-TX time difference.
The second device of claim 8, wherein the first device is a terminal device, the second device is a network device, the first reference signal is an uplink sounding positioning reference signal, and the at least one second RX-TX time difference is at least one gNB RX-TX time difference.
A first device comprising at least one processor configured to cause the first device at least to:

in accordance with a determination that a configuration of second reference signal for positioning from a second device is absent, determine a reference time point as an assumed receiving time;

determine a set of first reference signals for positioning associated with the assumed receiving time, wherein the set of first reference signals comprises at least one first reference signal having at least one transmitting time; and

determine, based on the reference time point and the at least one transmitting time, at least one first receive-transmit (RX-TX) time difference by using an artificial intelligence (AI) or machine learning (ML) model deployed at the first device; and

transmit, to a location management function (LMF) , the at least one first RX-TX time difference.
The first device of claim 13, wherein the at least one processor is further configured to cause the first device to:

transmit, to the second device, an indication of the reference time point, wherein the reference time point is related to a timestamp of an inference of the AI or ML model.
The first device of claim 13, wherein the first device is a network device, the second device is a terminal device, the first reference signal is a downlink positioning reference signal, and the at least one first RX-TX time difference is at least one gNB RX-TX time difference.
The first device of claim 13, wherein the first device is a terminal device, the second device is a network device, the first reference signal is an uplink sounding positioning reference signal, and the at least one first RX-TX time difference is at least one user equipment (UE) RX-TX time difference.
A location management function (LMF) comprising at least one processor configured to cause the LMF at least to:

receive, from a first device, at least one first receive-transmit (RX-TX) time difference being determined by using an artificial intelligence (AI) or machine learning (ML) model deployed at the first device;

receive, from a second device, at least one second RX-TX time difference being determined based on at least a received first reference signal, wherein a second reference signal for positioning from the second device is absent;

determine a RX-TX time difference pair by matching one of the at least one first RX-TX time difference and one of the at least one second RX-TX time difference; and

perform a positioning estimation based on the RX-TX time difference pair.
The LMF of claim 17, wherein the at least one processor is further configured to cause the LMF to perform at least one of:

receive, from the first device, first integrated information associated with each of the at least one first RX-TX time difference, wherein the first integrated information indicates at least one of:

a first identifier of the first reference signal, or

a second identifier of the second reference signal; or

receive, from the second device, second integrated information associated with each of the at least one second RX-TX time difference, wherein the second integrated information indicates at least one of:

the first identifier of the first reference signal, or

the second identifier of the second reference signal.
The LMF of claim 17, wherein the at least one processor is configured to cause the LMF to determine a time difference pair by:

in accordance with a determination that both the one of the at least one first RX-TX time difference and the one of the at least one second RX-TX time difference are associated with a same second reference signal, determining that the RX-TX time difference pair comprises the one of the at least one first RX-TX time difference and the one of the at least one second RX-TX time difference.
A computer readable medium having instructions stored thereon, the instructions, when executed by a processor of an apparatus, causing the apparatus to perform operations by any one of: a first device according to any one of claims 1-7 or 13-16, a second device according to any one of claims 8-12, or a location management function according to any one of claims 17-19.