Measurement method, communication device, communication system, storage medium, and program product

Abstract

The present disclosure relates to a measurement method, a communication device, a communication system, a storage medium, and a program product. The method comprises: receiving first information from a first network element, and on the basis of the first information, determining the type of measurement to execute or stop, wherein the first information is used for indicating or suggesting at least one of the following: starting AI measurement; stopping AI measurement; starting measurement; and stopping measurement. By receiving the first information from the first network element, an access network device can determine whether to perform model reasoning-based positioning measurement, thereby providing an accurate positioning result. The method can achieve control over the model reasoning function of an access network device without exposing the model reasoning capability and performance of the access network device.

Description

Measurement methods, communication equipment, communication systems, storage media and software products Technical Field

[0001] This disclosure relates to the field of communication technology, and in particular to measurement methods, communication equipment, communication systems, storage media, and program products. Background Technology

[0002] Related technologies can be used to assist in the positioning function based on models deployed on access network devices, and it is necessary to determine how to control the use of these models. Summary of the Invention

[0003] To address the control problem of the positioning model deployed on access network equipment.

[0004] This disclosure provides measurement methods, communication devices, communication systems, storage media, and program products.

[0005] According to a first aspect of the present disclosure, a measurement method is proposed, executed by an access network device, the method comprising: receiving first information from a first network element, and determining a measurement mode to be executed or stopped based on the first information; wherein the first information is used to indicate or suggest at least one of the following: enabling AI measurement; stopping AI measurement; enabling measurement; stopping measurement.

[0006] According to a second aspect of the present disclosure, a measurement method is proposed, executed by a first network element, the method comprising: sending first information to an access network device; wherein the first information is used to indicate or suggest at least one of the following: enabling AI measurement; stopping AI measurement; enabling measurement; stopping measurement.

[0007] According to a third aspect of the present disclosure, an access network device is provided, comprising: a transceiver module for receiving first information from a first network element; and a processing module for determining a measurement mode to be executed or stopped based on the first information; wherein the first information is used to indicate or suggest at least one of the following: enabling AI measurement; stopping AI measurement; enabling measurement; and stopping measurement.

[0008] According to a fourth aspect of the present disclosure, a first network element is proposed, comprising: a processing module for determining first information; and a transceiver module for sending the first information to an access network device; wherein the first information is used to indicate or suggest at least one of the following: enabling AI measurement; stopping AI measurement; enabling measurement; and stopping measurement.

[0009] According to a fifth aspect of the present disclosure, a communication device is provided for performing the measurement method described in the first or second aspect.

[0010] According to a sixth aspect of the present disclosure, a communication system is provided, including an access network device and a first network element, wherein the access network device is configured to implement the communication method described in the first aspect, and the first network element is configured to implement the measurement method described in the second aspect.

[0011] According to a seventh aspect of the present disclosure, a storage medium is provided that stores instructions that, when executed on a communication device, cause the communication device to perform the measurement method described in the first or second aspect.

[0012] According to an eighth aspect of the present disclosure, a program product is provided, comprising at least one of a program and instructions, wherein the program and instructions, when executed by a communication device, implement the steps of the method described in the first or second aspect.

[0013] In the above embodiments, by receiving first information from the first network element, the access network device can determine whether to perform model-based inference-based positioning measurement, thereby providing accurate positioning results. This method can control the model inference function of the access network device without exposing its model inference capabilities and performance. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of this disclosure, the accompanying drawings required for describing the embodiments are introduced below. These drawings are merely some embodiments of this disclosure and do not impose specific limitations on the scope of protection of this disclosure. Figure 1 is an exemplary schematic diagram of the architecture of a communication system provided according to an embodiment of this disclosure. Figure 2A is one of the exemplary interactive schematic diagrams of a measurement method provided according to an embodiment of this disclosure. Figure 2B is another exemplary interactive schematic diagram of a measurement method provided according to an embodiment of this disclosure. Figure 2C is a third exemplary interactive schematic diagram of a measurement method provided according to an embodiment of this disclosure. Figure 2D is a fourth exemplary interactive schematic diagram of a measurement method provided according to an embodiment of this disclosure. Figure 3A is a schematic block diagram of the device structure of an access network device shown according to an embodiment of this disclosure. Figure 3B is a schematic block diagram of the device structure of a first network element shown according to an embodiment of this disclosure. Figure 4A is a structural schematic diagram of a communication device proposed in an embodiment of this disclosure. Figure 4B is a structural schematic diagram of a chip proposed in an embodiment of this disclosure. Detailed Implementation

[0015] This disclosure provides measurement methods, communication devices, communication systems, storage media, and program products.

[0016] In a first aspect, embodiments of this disclosure propose a measurement method executed by an access network device, the method comprising: receiving first information from a first network element, and determining a measurement mode to be executed or stopped based on the first information; wherein the first information is used to indicate or suggest at least one of the following: enabling AI measurement; stopping AI measurement; enabling measurement; stopping measurement.

[0017] In the above embodiments, by receiving first information from the first network element, the access network device can determine whether to perform model-based inference-based positioning measurement, thereby providing accurate positioning results. This method can control the model inference function of the access network device without exposing its model inference capabilities and performance.

[0018] In conjunction with some embodiments of the first aspect, in some embodiments, the first information is also used to determine the measurement granularity and / or measurement type.

[0019] In the above embodiments, by refining the positioning measurement, the access network equipment can more accurately control the positioning measurement, thereby improving the accuracy and efficiency of the measurement and increasing the applicability of the positioning measurement.

[0020] In conjunction with some embodiments of the first aspect, in some embodiments, the measurement granularity includes: access network equipment and / or TRP.

[0021] In conjunction with some embodiments of the first aspect, in some embodiments, the measurement type includes at least one of the following: line-of-sight; non-line-of-sight; round-trip time; base station transmit / receive time difference.

[0022] In the above embodiments, by further refining the positioning measurement, access network devices can perform measurement tasks more accurately. This refined control enhances the flexibility of the measurement process and allows for the selection of different types of measurement objects according to specific needs, thereby improving the adaptability and accuracy of the measurement.

[0023] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes: sending second information to the first network element, the second information being used to instruct the first network element on a measurement method performed by the access network device; the measurement method includes AI measurement or non-AI measurement.

[0024] In the above embodiments, by sending second information to the first network element to instruct the access network device on the measurement method to be performed, the measurement status and results can be fed back in real time, helping the first network element to quickly understand the execution status of the measurement task, thereby improving the efficiency of network management and the accuracy of the measurement task.

[0025] In conjunction with some embodiments of the first aspect, in some embodiments, the second information is also used to indicate at least one of the following: performing a measurement at the measurement granularity of the access network device; performing a measurement at the measurement granularity of the TRP; and the measurement type of the measurement.

[0026] In the above embodiments, by refining the positioning measurement, the access network equipment can more accurately control the positioning measurement, thereby improving the accuracy and efficiency of the measurement and increasing the applicability of the positioning measurement.

[0027] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes: sending third information to the first network element, the third information being used to request to stop AI measurement or request to start AI measurement.

[0028] In conjunction with some embodiments of the first aspect, in some embodiments, the third information is also used to indicate at least one of the following: requesting to enable or requesting to stop AI measurement at the measurement granularity of the access network device; requesting to enable or requesting to stop AI measurement at the measurement granularity of TRP; and the measurement type of the AI ​​measurement.

[0029] In the above embodiments, by sending third information to the first network element to instruct the access network device to request the execution of positioning measurement, the first network element can adjust the allocation of network resources according to the real-time situation, thereby further enhancing the overall performance and service quality of the network.

[0030] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes: acquiring monitoring results of the AI ​​measurement, the monitoring results being used to identify the performance of the AI ​​measurement; and determining the third information based on the monitoring results and / or the computing load of the access network device.

[0031] In the above embodiments, by monitoring the performance of the access network device in performing positioning measurements, and adjusting the positioning measurements based on the monitoring information or the computing load of the access network device, the access network device can control the positioning measurements according to the actual situation, thus preventing resource waste.

[0032] In some embodiments, in conjunction with the first aspect, the method further includes: receiving fourth information from the first network element and adjusting the measurement mode according to the fourth information; the fourth information is used to indicate stopping AI measurement or starting AI measurement.

[0033] In the above embodiments, the first network element can make timely adjustments to the current measurement through the fourth information, thereby improving the utilization efficiency of AI measurement.

[0034] In conjunction with some embodiments of the first aspect, in some embodiments, the method includes: sending fifth information to a first network element, the fifth information being used to instruct the access network device to perform measurement capability information.

[0035] In the above embodiments, by sending the fifth information to the first network element to indicate the measurement capability information of the access network device, the measurement tasks that the access network device can support in the current network environment can be accurately assessed, thereby avoiding resource waste and improving the feasibility and effectiveness of measurement task execution.

[0036] In conjunction with some embodiments of the first aspect, in some embodiments, the fifth information is used to indicate at least one of the following: whether AI measurement at the measurement granularity of access network devices is supported; whether AI measurement at the measurement granularity of TRP is supported; and the supported measurement types.

[0037] In the above embodiments, by refining the positioning measurement, the access network equipment can more accurately control the positioning measurement, thereby improving the accuracy and efficiency of the measurement and increasing the applicability of the positioning measurement.

[0038] Secondly, embodiments of this disclosure propose a measurement method executed by a first network element, the method comprising: sending first information to an access network device; wherein the first information is used to indicate or suggest at least one of the following: enabling AI measurement; stopping AI measurement; enabling measurement; stopping measurement.

[0039] In conjunction with some embodiments of the second aspect, in some embodiments, the first information is also used to determine the measurement granularity and / or measurement type.

[0040] In conjunction with some embodiments of the second aspect, in some embodiments, the measurement granularity includes: access network equipment and / or TRP.

[0041] In conjunction with some embodiments of the second aspect, in some embodiments, the measurement type includes at least one of the following: line-of-sight; non-line-of-sight; round-trip time; base station transmit / receive time difference.

[0042] In conjunction with some embodiments of the second aspect, in some embodiments, the method further includes: receiving second information from the access network device, the second information being used to instruct the first network element on a measurement method performed by the access network device; the measurement method includes AI measurement or non-AI measurement.

[0043] In conjunction with some embodiments of the second aspect, in some embodiments, the second information is also used to indicate at least one of the following: performing a measurement at the access network device level; performing a measurement at the TRP level; and the measurement type of the measurement.

[0044] In conjunction with some embodiments of the second aspect, in some embodiments, the method further includes: receiving third information from the access network device, the third information being used to request to stop AI measurement or to request to start AI measurement.

[0045] In conjunction with some embodiments of the second aspect, in some embodiments, the third information is also used to indicate at least one of the following: requesting to enable or requesting to stop AI measurement at the measurement granularity of the access network device; requesting to enable or requesting to stop AI measurement at the measurement granularity of TRP; and the measurement type of the AI ​​measurement.

[0046] In conjunction with some embodiments of the second aspect, in some embodiments, the method further includes: sending fourth information to the access network device, the fourth information being used to instruct the stopping of AI measurement or the starting of AI measurement.

[0047] In some embodiments, in conjunction with the second aspect, the method further includes: the fourth information determined based on the third information and the Quality of Service (QoS) requirements for the location.

[0048] In conjunction with some embodiments of the second aspect, in some embodiments, the method includes: receiving fifth information from the access network device, the fifth information being used to instruct the access network device to perform measurement capability information.

[0049] In conjunction with some embodiments of the second aspect, in some embodiments, the fifth information is used to indicate at least one of the following: whether AI measurement at the measurement granularity of access network devices is supported; whether AI measurement at the measurement granularity of TRP is supported; and the supported measurement types.

[0050] Thirdly, embodiments of this disclosure provide an access network device, including: a transceiver module for receiving first information from a first network element; and a processing module for determining a measurement mode to be executed or stopped based on the first information; wherein the first information is used to indicate or suggest at least one of the following: enabling AI measurement; stopping AI measurement; enabling measurement; and stopping measurement.

[0051] Fourthly, this disclosure proposes a first network element, including: a processing module for determining first information; and a transceiver module for sending the first information to an access network device; wherein the first information is used to indicate or suggest at least one of the following: enabling AI measurement; stopping AI measurement; enabling measurement; and stopping measurement.

[0052] Fifthly, embodiments of this disclosure provide a communication device for performing the measurement method described in the first or second aspect.

[0053] In a sixth aspect, embodiments of this disclosure provide a communication system including an access network device and a first network element, wherein the access network device is configured to implement the communication method described in the first aspect, and the first network element is configured to implement the measurement method described in the second aspect.

[0054] In a seventh aspect, embodiments of this disclosure provide a storage medium storing instructions that, when executed on a communication device, cause the communication device to perform the measurement method described in the first or second aspect.

[0055] Eighthly, embodiments of this disclosure provide a program product including at least one of a program and instructions, wherein when the program or instructions are executed by a communication device, they implement the steps of the method described in the first or second aspect.

[0056] It is understood that the aforementioned communication equipment, communication system, storage medium, program product, etc., are all used to execute the methods proposed in the embodiments of this disclosure. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods, and will not be repeated here.

[0057] This disclosure provides measurement methods, communication devices, communication systems, storage media, and program products. In some embodiments, the terms "measurement method" and "information processing method," "communication method," etc., may be used interchangeably.

[0058] This disclosure is not exhaustive, but merely illustrative of some embodiments, and is not intended to limit the scope of protection of this disclosure. Unless otherwise specified, each step in a particular embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a particular embodiment can also be implemented as an independent embodiment, and the order of the steps in a particular embodiment can be arbitrarily interchanged. Furthermore, the optional implementation methods in a particular embodiment can be arbitrarily combined; moreover, the embodiments can be arbitrarily combined, for example, some or all steps of different embodiments can be arbitrarily combined, and a particular embodiment can be arbitrarily combined with the optional implementation methods of other embodiments. In all embodiments of this disclosure, unless otherwise specified or logically conflicting, the terminology and / or descriptions between the embodiments are consistent and can be mutually referenced. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0059] The terminology used in the embodiments of this disclosure is for the purpose of describing particular embodiments only and is not intended to limit the scope of this disclosure.

[0060] In this embodiment of the disclosure, unless otherwise stated, elements expressed in the singular form, such as "a," "an," "the," "the," "the," "the," "the," "the," "this," etc., can mean "one and only one," or "one or more," "at least one," etc. For example, when using articles such as "a," "an," "the," etc. in translation, the noun following the article can be understood as either a singular expression or a plural expression.

[0061] In the embodiments disclosed herein, "multiple" refers to two or more.

[0062] In some embodiments, the terms “at least one of A or B, at least one of A and B”, “one or more”, “a plurality of”, “multiple”, etc., may be used interchangeably.

[0063] In some embodiments, the notation "at least one of A and B", "A and / or B", "A in one case, B in another", "in response to one case A, in response to another case B", etc., may include the following technical solutions depending on the situation: in some embodiments, A (execute A regardless of whether there is a branch B); in some embodiments, B (execute B regardless of whether there is a branch A); in some embodiments, execution is selected from A and B (A and B are selectively executed); in some embodiments, both A and B are executed. The same applies when there are more branches such as A, B, C, etc.

[0064] In some embodiments, the notation "A or B" may include the following technical solutions, depending on the situation: in some embodiments, A (execute A regardless of whether a branch B exists); in some embodiments, B (execute B regardless of whether a branch A exists); in some embodiments, execution is selected from A and B (A and B are selectively executed). The same applies when there are more branches such as A, B, and C.

[0065] The prefixes "first," "second," etc., used in the embodiments of this disclosure are merely for distinguishing different descriptive objects and do not impose restrictions on the position, order, priority, quantity, or content of the descriptive objects. The description of the descriptive objects is found in the claims or the context of the embodiments, and the use of prefixes should not constitute unnecessary restrictions. For example, if the descriptive object is a "field," the ordinal numbers preceding "field" in "first field" and "second field" do not restrict the position or order of the "fields." "First" and "second" do not restrict whether the "fields" they modify are in the same message, nor do they restrict the order of "first field" and "second field." Similarly, if the descriptive object is a "level," the ordinal numbers preceding "level" in "first level" and "second level" do not restrict the priority between "levels." Furthermore, the number of descriptive objects is not limited by ordinal numbers and can be one or more. For example, in "first device," the number of "devices" can be one or more. Furthermore, the objects modified by different prefixes can be the same or different. For example, if the object being described is "device", then "first device" and "second device" can be the same device or different devices, and their types can be the same or different. Similarly, if the object being described is "information", then "first information" and "second information" can be the same information or different information, and their content can be the same or different.

[0066] In some embodiments, “including A,” “containing A,” “for indicating A,” and “carrying A” can be interpreted as directly carrying A or indirectly indicating A.

[0067] In some embodiments, terms such as "time / frequency" and "time-frequency domain" refer to the time domain and / or frequency domain.

[0068] In some embodiments, terms such as “in response to…”, “in response to determining…”, “in the case of…”, “when…”, “when…”, “if…”, etc. can be used interchangeably. These descriptions all refer to the device making a corresponding action under certain objective circumstances. They do not necessarily limit the time, nor do they require the device to make a judgment action when implementing it, nor do they mean that there must be other limitations.

[0069] In some embodiments, the terms “greater than,” “greater than or equal to,” “not less than,” “more than,” “more than or equal to,” “not less than,” “higher than,” “higher than or equal to,” “not lower than,” and “above” can be used interchangeably, as can the terms “less than,” “less than or equal to,” “not greater than,” “less than,” “less than or equal to,” “not more than,” “lower than,” “lower than or equal to,” “not higher than,” and “below”.

[0070] In some embodiments, devices, etc., may be interpreted as physical or virtual, and their names are not limited to those described in the embodiments. Terms such as “device,” “equipment,” “circuit,” “network element,” “network function,” “network device,” “function,” “node,” “unit,” “section,” “system,” “network,” “chip,” “chip system,” “entity,” and “subject” are interchangeable.

[0071] In some embodiments, "network" can be interpreted as devices included in a network (e.g., access network devices, core network devices, etc.).

[0072] In some embodiments, the terms "access network device (AN device)," "radio access network device (RAN device)," "base station (BS)," "radio base station," "fixed station," "node," "access point," "transmission point (TP)," "reception point (RP)," "transmission / reception point (TRP)," "panel," "antenna panel," "antenna array," "cell," "macro cell," "small cell," "femto cell," "pico cell," "sector," "cell group," "serving cell," "carrier," "component carrier," and "bandwidth part (BWP)" can be used interchangeably.

[0073] In some embodiments, the terms "terminal", "terminal device", "user equipment (UE)", "user terminal", "mobile station (MS)", "mobile terminal (MT)", "subscriber station", "mobile unit", "subscriber unit", "wireless unit", "remote unit", "mobile device", "wireless device", "wireless communication device", "remote device", "mobile subscriber station", "access terminal", "mobile terminal", "wireless terminal", "remote terminal", "handset", "user agent", "mobile client", and "client" can be used interchangeably.

[0074] In some embodiments, access network devices, core network devices, or network devices can be replaced by terminals. For example, embodiments of this disclosure can also be applied to structures where communication between access network devices, core network devices, or network devices and terminals is replaced by communication between multiple terminals (e.g., device-to-device (D2D), vehicle-to-everything (V2X), etc.). In this case, the structure can also be configured such that the terminal has all or part of the functions of the access network device. Furthermore, terms such as "uplink" and "downlink" can be replaced with terms corresponding to communication between terminals (e.g., "sidelink"). For example, uplink channel, downlink channel, etc., can be replaced with sidelink channel, and uplink link, downlink, etc., can be replaced with sidelink link.

[0075] In some embodiments, the terminal may be replaced by an access network device, a core network device, or a network device. In this case, the access network device, core network device, or network device may also be configured to have all or some of the functions of the terminal.

[0076] In some embodiments, the acquisition of data, information, etc., may comply with the laws and regulations of the country where the location is situated.

[0077] In some embodiments, data, information, etc., may be obtained with the user's consent.

[0078] Furthermore, each element, each row, or each column in the table of this disclosure can be implemented as an independent embodiment, and any combination of any element, any row, or any column can also be implemented as an independent embodiment.

[0079] Figure 1 is a schematic diagram of the architecture of a communication system according to an embodiment of the present disclosure (only including the inventive point-related entities and their important counterparts).

[0080] As shown in Figure 1, the communication system 100 includes a terminal 101, an access network device 102, and a core network device 103.

[0081] In some embodiments, terminal 101 includes, for example, at least one of the following: mobile phone, wearable device, Internet of Things device, car with communication function, smart car, tablet computer, computer with wireless transceiver function, virtual reality (VR) terminal device, augmented reality (AR) terminal device, wireless terminal device in industrial control, wireless terminal device in self-driving, wireless terminal device in remote medical surgery, wireless terminal device in smart grid, wireless terminal device in transportation safety, wireless terminal device in smart city, and wireless terminal device in smart home, but is not limited thereto.

[0082] In some embodiments, the access network device 102 may be a node or device that connects a terminal to a wireless network. The access network device may include at least one of the following in a 5G communication system: an evolved Node B (eNB), a next-generation eNB (ng-eNB), a next-generation Node B (gNB), a node B (NB), a home node B (HNB), a home evolved node B (HeNB), a wireless backhaul device, a radio network controller (RNC), a base station controller (BSC), a base transceiver station (BTS), a base band unit (BBU), a mobile switching center, a base station in a 6G communication system, an open RAN, a cloud RAN, a base station in other communication systems, and an access node in a Wi-Fi system, but is not limited thereto.

[0083] In some embodiments, the technical solutions of this disclosure can be applied to the Open RAN architecture. In this case, the interfaces between or within access network devices involved in the embodiments of this disclosure can be transformed into internal interfaces of Open RAN. The processes and information interactions between these internal interfaces can be implemented by software or programs.

[0084] In some embodiments, the access network device may be composed of a central unit (CU) and a distributed unit (DU). The CU may also be called a control unit. The CU-DU structure can separate the protocol layer of the access network device. Some of the protocol layer functions are centrally controlled by the CU, while the remaining part or all of the protocol layer functions are distributed in the DU and centrally controlled by the CU. However, this is not the only possibility.

[0085] In some embodiments, the core network device 103 may be a single device, including a first network element 1031, or it may be multiple devices or a group of devices, each including all or part of the first network element 1031, etc. Network elements may be virtual or physical. The core network may include, for example, at least one of the Evolved Packet Core (EPC), 5G Core Network (5GCN), and Next Generation Core (NGC).

[0086] In some embodiments, the first network element 1031 is, for example, a Location Management Function (LMF).

[0087] In some embodiments, the first network element 1031 is used to coordinate and manage location services.

[0088] It is understood that the communication system described in this disclosure is for the purpose of more clearly illustrating the technical solutions of this disclosure, and does not constitute a limitation on the technical solutions proposed in this disclosure. As those skilled in the art will know, with the evolution of system architecture and the emergence of new business scenarios, the technical solutions proposed in this disclosure are also applicable to similar technical problems.

[0089] The following embodiments of this disclosure can be applied to the communication system 100 shown in FIG1, or to some of the main bodies, but are not limited thereto. The main bodies shown in FIG1 are illustrative. The communication system may include all or some of the main bodies in FIG1, or may include other main bodies outside of FIG1. ​​The number and form of each main body are arbitrary. Each main body may be physical or virtual. The connection relationship between the main bodies is illustrative. The main bodies may not be connected or may be connected. The connection can be in any way, it can be a direct connection or an indirect connection, it can be a wired connection or a wireless connection.

[0090] The embodiments disclosed herein can be applied to Long Term Evolution (LTE), LTE-Advanced (LTE-A), LTE-Beyond (LTE-B), SUPER 3G, IMT-Advanced, 4th generation mobile communication system (4G), 5th generation mobile communication system (5G), 5G new radio (NR), Future Radio Access (FRA), New-Radio Access Technology (RAT), New Radio (NR), New radio access (NX), Future generation radio access (FX), Global System for Mobile communications (GSM), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), and IEEE 802.20, Ultra-Wideband (UWB), Bluetooth (a registered trademark), Public Land Mobile Network (PLMN) networks, Device-to-Device (D2D) systems, Machine-to-Machine (M2M) systems, Internet of Things (IoT) systems, Vehicle-to-Everything (V2X) systems, systems utilizing other communication methods, and next-generation systems built upon them, etc. Furthermore, multiple systems can be combined (e.g., a combination of LTE or LTE-A with 5G).

[0091] In some embodiments, with the development of wireless communication technologies, such as 5G, they will permeate all areas of future society, building a comprehensive information ecosystem centered on the user. Specifically, user experience speeds can reach 100 Mbit / s to 1 Gbit / s, supporting ultimate service experiences such as mobile virtual reality; peak speeds can reach 10 Gbit / s to 20 Gbit / s, with a traffic density of 10 Mbit / s / m², supporting future growth of over a thousand times in mobile service traffic; connection density can reach 1 million connections / m², effectively supporting massive numbers of IoT devices; transmission latency can be down to the millisecond level, meeting the stringent requirements of vehicle networking and industrial control; and it can support mobile speeds of 500 km / h, ensuring a good user experience even in high-speed rail environments.

[0092] In some embodiments, artificial intelligence (AI) technology has achieved continuous breakthroughs in multiple fields. The ongoing development of fields such as intelligent voice and computer vision has not only brought a wide variety of applications to smart terminals, but has also found widespread use in education, transportation, home, healthcare, retail, security, and many other sectors, bringing convenience to people's lives while promoting industrial upgrading across various industries. AI technology is also accelerating its cross-disciplinary integration with other disciplines; its development combines knowledge from different disciplines while also providing new directions and methods for the development of various fields.

[0093] In wireless AI research, application examples of artificial intelligence include: AI-based Channel State Information (CSI) enhancement; AI-based beam management; and AI-based positioning.

[0094] In some embodiments, the architecture of AI functions includes functions such as data collection, model management, model training, and model inference.

[0095] In some embodiments, there are five deployment methods for AI-based positioning:

[0096] Direct AI / ML positioning:

[0097] Method 1: UE-based positioning with UE-side model, direct AI / ML positioning;

[0098] Method 2b: UE-assisted / LMF-based positioning with LMF-side model, direct AI / ML positioning;

[0099] Method 3b: Next-Generation Radio Access Network (NG-RAN) node assisted positioning, using an LMF-side model, direct AI / ML positioning.

[0100] AI / ML assisted positioning:

[0101] Method 2a: UE-assisted / LMF-based positioning, using UE-side model and AI / ML-assisted positioning;

[0102] Method 3a: NG-RAN node assisted positioning with gNB-side model, AI / ML assisted positioning.

[0103] In some embodiments, for the gNB-side model, the model inputs can be sample-based or path-based measurements performed by the gNB, and the output can be the following measurement types:

[0104] Line-of-sight (LOS) / Non-line-of-sight (NLOS);

[0105] Uplink Round-Trip One-Way Time (UL RTOA);

[0106] Base station transmit / receive time difference (gNB Rx-Tx time difference);

[0107] In some embodiments, performance monitoring involves an NG-RAN node performing a monitoring metric calculation for its own model.

[0108] In some embodiments, there are two ways to control the model on the base station side:

[0109] Method 1: NG-RAN nodes report the performance monitoring results to LMF so that LMF can control whether to use AI functions based on the results.

[0110] Method 2: The base station selects whether to use the AI ​​function based on its implementation. In this case, the LMF does not know whether the base station uses AI.

[0111] Reporting the performance monitoring results to the LMF may cause the base station to expose too much of the base station equipment's AI capabilities and performance to the outside world. If the base station does not report the performance monitoring results to the LMF, it will also be detrimental to the LMF in selecting the appropriate positioning method based on positioning QoS requirements and positioning performance.

[0112] Figure 2A is an interactive schematic diagram illustrating a measurement method according to an embodiment of the present disclosure. As shown in Figure 2A, the present disclosure relates to a measurement method, which includes:

[0113] In step S210, the first network element 1031 sends the first information to the access network device 102.

[0114] In some embodiments, the first network element sends first information to the access network device. The first information may include indication information for performing measurements on the access network device. The indication information may be used to indicate at least one of the following: enabling AI measurement; stopping AI measurement; enabling measurement; stopping measurement.

[0115] In some embodiments, the first network element sends first information to the access network device. The first information may include suggestion information for performing measurements on the access network device. The suggestion information may be used to suggest at least one of the following: enabling AI measurement; stopping AI measurement; enabling measurement; stopping measurement.

[0116] In some embodiments, the access network device receives first information from a first network element and determines the measurement method to be performed based on the first information; wherein, determining the measurement method to be performed may include AI measurement and / or non-AI measurement.

[0117] In some embodiments, the access device receives first information from a first network element, and determines the measurement method to be stopped based on the first information; wherein, determining the measurement method to be stopped may include AI measurement and / or non-AI measurement.

[0118] In some embodiments, the first network element may be a network element used for coordinating and managing location services.

[0119] In some embodiments, the first network element may be an LMF.

[0120] In some embodiments, the access network device may be a base station (gNB).

[0121] In some embodiments, AI measurement can be implemented using a deployed model. The collected measurement data is used for model inference to output measurement results, which can then be used for localization. This localization can include the localization of a terminal. For example, after enabling terminal localization, a reference signal can be sent to or received from the terminal. Measurement data of the reference signal can be input into the model for model inference, and a measurement result can be output. Based on this measurement result, the terminal can be located.

[0122] In some embodiments, the model deployed by the access network device can be an AI or machine learning (ML) based model, which may be referred to as an AI model or an ML model.

[0123] In some embodiments, AI measurement may also be referred to as ML measurement.

[0124] In some embodiments, localization achieved based on AI-based measurement results can be referred to as AI / ML-assisted localization.

[0125] In some embodiments, localization achieved based on the measurement results of AI measurements performed on a model deployed on an access network device can be referred to as AI / ML-assisted localization assisted by the access network device using a model on the access network device side.

[0126] In some embodiments, non-AI measurements can be measurements that do not utilize a model; for example, measurement results for a terminal can be obtained by performing data calculations on the collected measurement data.

[0127] In some embodiments, during the positioning process, the first network element or the access network device may determine which measurement method to use, including whether to use AI measurement. If the first network element determines the measurement method, the first network element may send first information including indication information to the access network device. The first information may be used to indicate at least one of the following: enable AI measurement; stop AI measurement; enable measurement; stop measurement. After receiving the first information, the access network device will determine the measurement method to use according to the content indicated by the first information, and perform measurement on the terminal based on the measurement method to obtain the measurement results and realize the positioning of the terminal.

[0128] In some embodiments, the first network element sends first information to the access network device, the first information being used to instruct the activation of AI measurement.

[0129] In some embodiments, the access network device receives first information from a first network element, the first information being used to instruct the activation of AI measurement; the access network device can determine to perform AI measurement based on the first information.

[0130] In some embodiments, the first network element sends first information to the access network device, the first information being used to instruct the AI ​​measurement to be stopped.

[0131] In some embodiments, the access network device receives first information from a first network element, the first information being used to indicate stopping AI measurement; the access network device determines to stop AI measurement based on the first information.

[0132] In some embodiments, the access network device receives first information from a first network element, the first information being used to indicate stopping AI measurement; the access network device determines to stop AI measurement based on the first information.

[0133] In some embodiments, the first network element sends first information to the access network device, the first information indicating that measurement should be initiated. At this time, it is not specified whether the specific measurement method is AI measurement or non-AI measurement.

[0134] In some embodiments, the access network device receives first information from a first network element, the first information indicating the initiation of measurement. Based on the first information and the status of the access network device (e.g., computing load and / or performance monitoring results), the access network device can determine whether to perform AI measurement and / or non-AI measurement. For example, after receiving the first information, if the access network device has sufficient computing power, it can perform AI measurement to improve positioning accuracy and resource utilization; or, if the access network device determines that the performance of AI measurement has degraded due to performance monitoring or other reasons, it can determine to perform non-AI measurement to ensure that positioning accuracy is met.

[0135] In some embodiments, the first network element sends first information to the access network device, the first information being used to instruct the measurement to stop.

[0136] In some embodiments, the access network device receives first information from a first network element, the first information being used to indicate stopping the measurement; the access network device can stop AI measurement and non-AI measurement based on the first information.

[0137] In some embodiments, during the positioning process, if the measurement method is determined by the access network device, the first network element can send first information including suggestion information to the access network device. The first information can be used to suggest at least one of the following: enabling AI measurement; stopping AI measurement; enabling measurement; stopping measurement. After receiving the first information, the access network device will determine whether to agree to the content suggested by the first information based on its own situation, such as the computing load of the access network device, and determine the measurement method to be used. The measurement method can be the same as or different from the content suggested by the first information. Based on the determined measurement method, the terminal is measured, and the measurement results are obtained to realize the positioning of the terminal.

[0138] In some embodiments, the first network element sends first information to the access network device, the first information being used to suggest enabling AI measurement.

[0139] In some embodiments, the access network device receives first information from a first network element, the first information being used to suggest enabling AI measurement; based on the first information, the access network device can determine whether to perform AI measurement or not.

[0140] In some embodiments, the first network element sends first information to the access network device, the first information being used to suggest stopping AI measurement.

[0141] In some embodiments, the access network device receives first information from a first network element, the first information being used to suggest stopping AI measurement; the access network device determines whether to stop AI measurement or not based on the first information and the conditions of the access network device (e.g., computing load and / or performance monitoring results).

[0142] In some embodiments, the first network element sends first information to the access network device, the first information being used to suggest enabling measurement. At this time, it does not suggest whether the specific measurement method is AI measurement or non-AI measurement.

[0143] In some embodiments, the access network device receives first information from a first network element, the first information being used to suggest enabling measurement; based on the first information and the status of the access network device (e.g., computing load and / or performance monitoring results), the access network device can determine whether to enable measurement, and further determine whether to perform AI measurement and / or non-AI measurement.

[0144] In some embodiments, the first network element sends first information to the access network device, the first information being used to suggest stopping the measurement.

[0145] In some embodiments, the access network device receives first information from a first network element, the first information being used to suggest stopping the measurement; based on the first information and the status of the access network device (e.g., computing load and / or performance monitoring results), the access network device can determine whether to stop AI measurement and / or non-AI measurement.

[0146] In some embodiments, the first information may also be used to determine the measurement granularity and / or measurement type.

[0147] The measurement granularity can indicate the application scope of the measurement and may include access network devices and / or TRPs. Each access network device may include one or more TRPs.

[0148] In some embodiments, a measurement granularity of the access network device can mean that the location measurement of the terminal is performed by the access network device; or that the location measurement of the terminal is performed by all TRPs included in the access network device.

[0149] In some embodiments, a measurement with a measurement granularity of TRP can be represented as a measurement of the terminal performed by one or more specified TRPs.

[0150] In some embodiments, AI measurement at the measurement granularity of the access network device can be referred to as AI measurement of the access network device, which means that the AI ​​measurement of the terminal is performed by the access network device; or that the AI ​​measurement of the terminal is performed by all TRPs included in the access network device.

[0151] In some embodiments, an AI measurement with a measurement granularity of TRP can be referred to as an AI measurement of TRP, which indicates that an AI measurement of the terminal is performed by one or more specified TRPs.

[0152] In some embodiments, the measurement granularity of non-AI measurement of the access network device can mean that the non-AI measurement of the terminal is performed by the access network device; or that the non-AI measurement of the terminal is performed by all TRPs included in the access network device.

[0153] In some embodiments, a non-AI measurement with a measurement granularity of TRP can mean that a non-AI measurement of the terminal is performed by one or more designated TRPs.

[0154] In some embodiments, the measurement type can be used to indicate the type of measurement result obtained through measurement.

[0155] In some embodiments, the measurement type may include line-of-sight (LOS) or non-line-of-sight (NLOS), for example, it may be used to determine whether a line of sight exists with a terminal. This measurement type may be represented as a LOS / NLOS measurement.

[0156] In some embodiments, the measurement type may include time-related measurements, such as those used to determine the round-trip time (RTT), relative time of arrival (RTOA), or time difference of arrival (TDOA) for uplink or downlink. This measurement type can be represented as an RTOA measurement.

[0157] In some embodiments, the measurement type may include base station transmit-receive time difference (gNB Rx-Tx time difference), for example, it can be used to determine the time difference between signals received and transmitted by a network device. This measurement type can be represented as a base station Rx-Tx time difference measurement.

[0158] In some embodiments, an AI measurement of type LOS / NLOS can be referred to as an AI measurement of LOS / NLOS, indicating that LOS / NLOS can be determined by an access network device or a specific TRP through AI measurement.

[0159] In some embodiments, an AI measurement whose measurement type is time-related measurement can be referred to as a time-related AI measurement, which indicates that a time-related measurement (e.g., RTT, RTOA, TDOA) can be determined by an access network device or a specific TRP through AI measurement.

[0160] In some embodiments, an AI measurement of base station transmit / receive time difference can be referred to as an AI measurement of base station transmit / receive time difference, which indicates that the base station transmit / receive time difference can be determined by an access network device or a specific TRP through AI measurement.

[0161] For the above AI measurements, the input to the AI ​​model can be path-based measurements (TOA (Time of Arrival), RTT (Round-Trip Time), AoA (Angle of Arrival), etc.) or sample-based measurements (PDP (Power Delay Profile), CIR (Channel Impulse Response)) of the UE signal. The output positioning result (i.e. measurement type) can be one or more of the following: LOS / NLOS, RTOA, Rx-Tx time difference.

[0162] In some embodiments, the measurement indicated or suggested by the first information may include one or more measurement granularities.

[0163] In some embodiments, the measurement indicated or suggested by the first information may include one or more measurement types.

[0164] In some embodiments, the first information may include at least one of a first instruction, a second instruction, and a third instruction.

[0165] The first indicator corresponds to the measurement granularity of the access network device and can be used to indicate whether measurement at the access network device granularity is enabled. For example, if the first indicator is "1" or "true", it means that measurement at the access network device granularity is enabled; if the first indicator is "0" or "false", it means that measurement at the access network device granularity is stopped. The measurement method can include AI measurement and / or non-AI measurement.

[0166] The second indicator corresponds to the measurement granularity of TRP and can be used to indicate whether measurement at the TRP granularity is enabled. For example, if the second indicator is "1" or "true", it means that measurement at the TRP granularity is enabled; if the second indicator is "0" or "false", it means that measurement at the TRP granularity is stopped. The measurement method can include AI measurement and / or non-AI measurement.

[0167] The third indicator corresponds to the measurement type and can be used to indicate whether to enable the corresponding measurement type. The measurement method can include AI measurement and / or non-AI measurement.

[0168] In some embodiments, the third indication may include indications corresponding to different measurement types, such as LOS / NLOS indication, RTOA indication, and base station Rx-Tx time difference indication, which are used to indicate whether to perform or stop the measurement of the corresponding measurement type. For example, if the LOS / NLOS indication and RTOA indication are "1" or "true", and the base station Rx-Tx time difference indication is "0" or "false", it indicates that the measurement type being performed may include LOS / NLOS measurement and RTOA measurement.

[0169] In some embodiments, the third indication may also employ a combined encoding method to indicate whether to perform the first measurement for each measurement type. For example, a bitmap may be used, where each bit corresponds to a measurement type. If the corresponding bit is "1", it indicates that the measurement of the corresponding measurement type is performed; if the corresponding bit is "0", it indicates that the measurement of the corresponding measurement type is stopped.

[0170] In some embodiments, the first information may include joint encoding of the first indication, the second indication, and the third indication, for example, in the form of a bitmap, which may include a first bit corresponding to the measurement granularity of the access network device, a second bit corresponding to the measurement granularity of the TRP, and a third bit corresponding to each measurement type.

[0171] In some embodiments, the first network element sends first information to the access network device. The first information may be used to instruct or suggest enabling AI measurement, as well as the measurement granularity and / or measurement type of the AI ​​measurement.

[0172] In some embodiments, the first network element sends first information to the access network device. The first information may be used to instruct or suggest stopping AI measurement, as well as the measurement granularity and / or measurement type of the AI ​​measurement.

[0173] In some embodiments, the first network element sends first information to the access network device. The first information may be used to indicate or suggest enabling measurement, as well as the measurement granularity and / or measurement type.

[0174] In some embodiments, the first network element sends first information to the access network device. The first information may be used to indicate or suggest stopping the measurement, as well as the measurement granularity and / or measurement type.

[0175] In some embodiments, the access network device may receive first information from a first network element and determine, based on the first information, whether to perform or stop AI measurement, as well as the measurement granularity and / or measurement type of the AI ​​measurement.

[0176] For example, the access network device can determine, based on the first information, to perform AI measurements of the access network device, including LOS / NLOS and RTOA; or determine, based on the first information, to stop AI measurements of the base station Rx-Tx time difference.

[0177] In some embodiments, the access network device may receive first information from a first network element and determine the measurement granularity and / or measurement type of the non-AI measurement to be performed or stopped based on the first information.

[0178] Step S220: Access network device 102 performs measurement or stops measurement on terminal 101.

[0179] In some embodiments, the access network device determines the measurement mode to be performed or stopped based on the first information, and performs measurement on the terminal, which may employ AI measurement and / or non-AI measurement.

[0180] In some embodiments, when the access network device determines to perform AI measurement based on the first information, it can perform AI measurement on the terminal, that is, it can obtain the measurement result of the terminal by performing model inference on the collected measurement data.

[0181] In some embodiments, when an access network device determines, based on first information, to perform an AI measurement on a terminal at the measurement granularity and / or measurement type, the AI ​​measurement may be performed at that measurement granularity and / or measurement type.

[0182] For example, if the access network device determines to perform AI measurement based on the first information, and the measurement granularity of the AI ​​measurement is the access network device and the measurement type includes LOS / NLOS measurement, then the terminal can perform AI measurement on the access network device with the measurement type including LOS / NLOS.

[0183] In some embodiments, when the access network device determines to stop AI measurement based on the first information, it can perform non-AI measurement on the terminal, for example, by performing data calculations on the collected measurement data to obtain the measurement results for the terminal.

[0184] In some embodiments, when an access network device determines, based on first information, to perform a non-AI measurement at the measurement granularity and / or measurement type, it may perform a non-AI measurement on a terminal at that measurement granularity and / or measurement type.

[0185] In some embodiments, if the access network device determines to stop non-AI measurements based on first information, it may perform AI measurements on the terminal.

[0186] In some embodiments, when the access network device determines to perform a measurement based on the first information, it may perform AI measurement and / or non-AI measurement on the terminal.

[0187] In some embodiments, if the access network device determines to stop measuring based on first information, it may stop performing measurements on the terminal.

[0188] In some embodiments, after completing the measurement of the terminal and obtaining the measurement results, the access network device may send a measurement report containing the measurement results to the first network element.

[0189] In the above embodiments, by receiving first information from the first network element, the access network device can determine whether to perform AI measurement based on model inference, thereby providing accurate positioning results. This method can determine whether to use the access network device's model inference function to improve positioning accuracy without exposing the access network device's model inference capabilities and performance.

[0190] The communication method involved in the embodiments of this disclosure may include at least one of steps S210 to S220. For example, step S210 may be implemented as a standalone embodiment, step S220 may be implemented as a standalone embodiment, and steps S210+S220 may be implemented as standalone embodiments, but are not limited thereto.

[0191] In some embodiments, step S210 is optional and may be omitted or replaced in different embodiments.

[0192] In some embodiments, step S220 is optional and may be omitted or replaced in different embodiments.

[0193] In some embodiments, the steps and their optional implementations in other embodiments described before or after this embodiment, as well as other related parts in the specification, can be referred to, and will not be repeated here.

[0194] Figure 2B is an interactive schematic diagram of a measurement method according to an embodiment of the present disclosure. As shown in Figure 2B, the embodiment of the present disclosure relates to a measurement method, which, compared with the measurement method shown in Figure 2A, adds step S211 after step S220.

[0195] Step S211: Access network device 102 sends second information to first network element 1031.

[0196] In some embodiments, after performing a measurement on a terminal, the access network device may send second information to a first network element. The second information is used to instruct the first network element on the measurement method performed by the access network device. The measurement method may include AI measurement or non-AI measurement.

[0197] In some embodiments, the second information may be associated with the measurement results of the terminal and used to indicate to the first network element the measurement method corresponding to the reported measurement results, that is, to indicate to the first network element whether the reported measurement results are obtained by using AI measurement.

[0198] In some embodiments, when the measurement method is determined by the access network device, since the measurement method determined by the access network device may differ from the content suggested by the first network element in the first information, or the first network element does not explicitly indicate whether to use AI measurement in the first information, the access network device may send second information to the first network element after performing the measurement on the terminal. The second information is used to indicate to the first network element the measurement method performed by the access network device, that is, to indicate to the first network element whether the measurement result reported to the first network element is the measurement result obtained by using AI measurement.

[0199] In some embodiments, the first network element receives second information from the access network device, the second information being used to indicate the measurement method performed by the access network device; wherein, the second information may be associated with the reported measurement results; the first network element can determine the measurement method corresponding to the reported measurement results based on the second information, so as to determine whether the measurement results are obtained by using AI measurement.

[0200] In some embodiments, the access network device sends second information to the first network element, the second information being used to instruct the access network device to perform AI measurement.

[0201] In some embodiments, the first network element receives second information from the access network device, the second information being used to instruct the access network device to perform AI measurement; based on the second information, it can be determined that the reported measurement result is the measurement result obtained by using AI measurement.

[0202] In some embodiments, the access network device sends second information to the first network element, the second information being used to instruct the access network device to perform non-AI measurement.

[0203] In some embodiments, the first network element receives second information from the access network device, the second information being used to instruct the access network device to perform non-AI measurement; based on the second information, it can be determined that the reported measurement result is not a measurement result obtained using AI measurement.

[0204] In some embodiments, the second information may further include measurement results of the terminal and indicate the execution method corresponding to the measurement results.

[0205] For example, the access network device performs AI measurement on terminal 1 and non-AI measurement on terminal 2; the access network device can send second information to the first network element, the second information including the measurement results of terminal 1 and the measurement results of terminal 2, and instruct to use AI measurement to obtain the measurement results of terminal 1 and non-AI measurement to obtain the measurement results of terminal 2.

[0206] In some embodiments, the second information may also be used to indicate the measurement granularity and / or measurement type, that is, to indicate the measurement granularity and / or measurement type corresponding to the reported measurement results.

[0207] The measurement granularity may include access network equipment and / or TRP.

[0208] The measurement type may include at least one of the following: LOS / NLOS measurement; RTOA measurement; base station Rx-Tx time difference measurement.

[0209] In some embodiments, the second information may be used to instruct the execution of AI measurements by the access network device, that is, to instruct the reported measurement results to be obtained by using AI measurements by the access network device.

[0210] In some embodiments, the second information may also be used to indicate the type of measurement for the AI ​​measurement performed by the access network device.

[0211] In some embodiments, the second information may be used to indicate the execution of AI measurements using TRP, that is, to indicate that the reported measurement results are the measurement results obtained by using AI measurements with TRP.

[0212] In some embodiments, the second information may also be used to indicate the measurement type of the AI ​​measurement performed in the TRP.

[0213] In some embodiments, the second information may be used to indicate the non-AI measurement performed by the access network device, that is, to indicate that the reported measurement result is the measurement result obtained by using the non-AI measurement of the access network device.

[0214] In some embodiments, the second information may also be used to indicate the type of measurement for which non-AI measurements are performed by the access network device.

[0215] In some embodiments, the second information can be used to indicate the non-AI measurement performed by TRP, that is, it can be used to indicate that the reported measurement result is the measurement result obtained by non-AI measurement using TRP.

[0216] In some embodiments, the second information may also be used to indicate the measurement type of the non-AI measurement of the performed TRP.

[0217] In some embodiments, the second information may include a first usage instruction, a second usage instruction, and a third usage instruction. The first usage instruction may be used to indicate whether the measurement granularity being performed is that of an access network device; the second usage instruction may be used to indicate whether the measurement granularity being performed is that of a TRP; and the third usage instruction may be used to indicate the type of measurement being performed.

[0218] For example, if the second usage instruction is "1" or "true" and the first usage instruction is "0" or "false", then the second information is used to instruct the first network element to perform a measurement with a measurement granularity of TRP.

[0219] In some embodiments, the third usage indication may include usage indications corresponding to each different measurement type, such as LOS / NLOS usage indication, RTOA usage indication, base station Rx-Tx time difference usage indication, etc., which are used to indicate whether to perform the corresponding measurement type.

[0220] In some embodiments, the third indication can employ a combined encoding method to indicate the type of measurement performed. For example, a bitmap can be used, where each bit corresponds to a measurement type. If the corresponding bit is "1", it indicates that the corresponding measurement type has been performed.

[0221] In some embodiments, the second information may include a joint encoding of the first usage instruction, the second usage instruction, and the third usage instruction, for example, in the form of a bitmap. The bitmap may include a first bit corresponding to the measurement granularity of the access network device, a second bit corresponding to the measurement granularity of the TRP, and a third bit corresponding to each measurement type.

[0222] The communication method involved in the embodiments of this disclosure may include at least one of steps S210, S220, and S211. For example, step S210 may be implemented as an independent embodiment, step S220 may be implemented as an independent embodiment, step S211 may be implemented as an independent embodiment, steps S210+S220 may be implemented as an independent embodiment, steps S220+S211 may be implemented as an independent embodiment, steps S210+S211 may be implemented as an independent embodiment, and steps S210+S220+S211 may be implemented as an independent embodiment, but is not limited thereto.

[0223] In some embodiments, steps S220 and S211 may be performed in an alternate order or simultaneously.

[0224] In some embodiments, steps S220 and S211 are optional, and one or more of these steps may be omitted or substituted in different embodiments.

[0225] In some embodiments, steps S210 and S220 are optional, and one or more of these steps may be omitted or substituted in different embodiments.

[0226] In some embodiments, the steps and their optional implementations in other embodiments described before or after this embodiment, as well as other related parts in the specification, can be referred to, and will not be repeated here.

[0227] Figure 2C is an interactive schematic diagram of a measurement method according to an embodiment of the present disclosure. As shown in Figure 2C, the embodiment of the present disclosure relates to a measurement method, which, compared with the measurement method shown in Figure 2A, adds steps S212 and S213.

[0228] Step S212: Access network device 102 sends third information to first network element 1031.

[0229] In some embodiments, the access network device sends third information to the first network element, wherein the third information is used to request the first network element to at least one of the following: enable AI measurement, stop AI measurement, enable measurement, stop measurement, etc.

[0230] In some embodiments, when the measurement method is determined by the first network element, the access network device may send third information to the first network element. The third information is used to request the first network element to at least one of the following: enable AI measurement, stop AI measurement, enable measurement, stop measurement, etc.

[0231] In some embodiments, the first network element may receive third information from the access network device, the third information being used to request at least one of the following: enable AI measurement, stop AI measurement, enable measurement, stop measurement, etc.

[0232] In some embodiments, after determining the measurement method to be executed or stopped based on the first information, the access network device can determine whether it needs to adjust the current measurement method according to its own needs and / or capabilities, such as the computing load of the access network device. If adjustment is required, it can determine the content requested by the third information based on a preset adjustment strategy and send the third information to the first network element. The content requested by the third information may include the measurement method to be adjusted, and may include at least one of the following: enabling AI measurement, stopping AI measurement, enabling measurement, stopping measurement, etc.

[0233] In some embodiments, during the execution of AI measurement, the access network device can monitor the AI ​​measurement based on a preset monitoring method, and the monitoring results can be used to identify the performance of the AI ​​measurement.

[0234] The methods for monitoring AI measurements can be tailored to specific needs. For example, they can acquire the model's input data (measurement data) and output data (measurement results) during the AI ​​measurement process, as well as the corresponding ground truth labels. The performance of the AI ​​measurement can then be evaluated based on these data, using the resulting performance score as the monitoring result. For instance, the accuracy of model inference can be assessed by comparing the consistency between the output data and the ground truth labels corresponding to the same input data.

[0235] In some embodiments, the monitoring results of AI measurements may include: monitoring results of the model used for AI measurements; or monitoring results of AI measurements at a certain measurement granularity; or monitoring results of AI measurements for a certain measurement type.

[0236] In some embodiments, the access network device may determine whether the current AI measurement needs to be modified based on the monitoring results of the AI ​​measurement and the computing load of the access network device (or the computing load of the TRP); if so, it may send third information to the first network element, the third information being used to request to stop the AI ​​measurement; or request to start the AI ​​measurement in progress.

[0237] In some embodiments, if the monitoring results of AI measurement indicate that the performance of AI measurement is poor (e.g., below a preset performance threshold) and / or the computing load of the access network device reaches a certain level (e.g., above a preset computing load threshold), a third message can be sent to the first network element to request the cessation of AI measurement or the cessation of partial AI measurement.

[0238] In some embodiments, if the monitoring results of AI measurement indicate that the performance of AI measurement is good and / or the computing load of the access network device is low, a third message can be sent to the first network element to request the activation of AI measurement, or the activation of partial AI measurement, or the addition of AI measurement.

[0239] In some embodiments, the third information may also be used to indicate the measurement granularity at which the AI ​​measurement is requested to be started or stopped.

[0240] The measurement granularity may include the access network device and / or the TRP. That is, the third information may be a request to start or stop AI measurement with the access network device as the measurement granularity, and / or a request to start or stop AI measurement with the TRP as the granularity (for example, the third information includes the TRP identifier).

[0241] In some embodiments, the third information may also be used to indicate the type of measurement for which an AI measurement is requested to be started or stopped.

[0242] The measurement type may include at least one of the following: LOS / NLOS measurement; RTOA measurement; base station Rx-Tx time difference measurement.

[0243] In some embodiments, the third information may request to enable or stop AI measurements of LOS / NLOS measurement type;

[0244] In some embodiments, the third information may request to enable or stop AI measurement with RTOA measurement as the measurement type;

[0245] In some embodiments, the third information may request to enable or stop AI measurement of the measurement type Rx-Tx time difference measurement;

[0246] In some embodiments, third information may be used to request at least one of the measurement method, measurement granularity, and measurement type that need to be adjusted.

[0247] In some embodiments, the third information can be used to request the cessation of AI measurement of the access network device or to request the commencement of AI measurement of the access network device.

[0248] In some embodiments, the third information may also be used to indicate the measurement type of the AI ​​measurement of the access network device that requests to stop, or the measurement type of the AI ​​measurement of the access network device that requests to start.

[0249] In some embodiments, the third information can be used to request the cessation of AI measurement of TRP or to request the commencement of AI measurement of TRP.

[0250] In some embodiments, the third information may be used to indicate the measurement type of the AI ​​measurement for which the TRP is requested to be stopped, or the measurement type of the AI ​​measurement for which the TRP is requested to be started.

[0251] In some embodiments, the third information may include a first request indication, a second request indication, and a third request indication. The first request indication indicates whether the measurement granularity to be stopped or started is an access network device; the second request indication indicates whether the measurement granularity to be stopped or started is a TRP; and the third request indication indicates the measurement type of the AI ​​measurement to be stopped or started.

[0252] For example, if the first request indication is "1" or "true", and the second and third request indications are "0" or "false", then the third information can be used to request the activation of AI measurement at the measurement granularity of the access network device.

[0253] In some embodiments, the third request indication includes usage indications corresponding to each different measurement type, such as LOS / NLOS request indication, RTOA request indication, base station Rx-Tx time difference request indication, etc., which are used to indicate whether to request the corresponding AI measurement measurement type.

[0254] In some embodiments, the third request indication can use a combined encoding method to indicate the requested measurement type. For example, a bitmap can be used, where each bit corresponds to a measurement type. If the corresponding bit is "1", it indicates that the corresponding AI measurement type has been requested.

[0255] In some embodiments, the third information may include a joint encoding of the first request indication, the second request indication, and the third request indication, for example, in the form of a bitmap. The bitmap may include a first bit corresponding to the measurement granularity of the access network device, a second bit corresponding to the measurement granularity of the TRP, and a third bit corresponding to the measurement type of each AI measurement.

[0256] In some embodiments, if the access network device determines to perform AI measurement on the terminal based on the first information and monitors the AI ​​measurement of the access network device, and the monitoring result shows that the performance of the AI ​​measurement of the access network device is poor, or the computing load of the access network device reaches a certain computing load threshold, the access network device may send third information to the first network element to request to stop the AI ​​measurement of the access network device, and may further request to enable the AI ​​measurement of TRP.

[0257] In some embodiments, if the access network device determines, based on the first information, that the measurement type of the AI ​​measurement performed on the terminal includes LOS / NLOS measurement, RTOA measurement, and base station Rx-Tx time difference measurement, and the obtained monitoring results show that the performance of the LOS / NLOS measurement of the AI ​​measurement of the access network device is poor, the access network device may send third information to the first network element to request the cessation of the LOS / NLOS measurement of the AI ​​measurement of the access network device.

[0258] In some embodiments, if the access network device determines to perform AI measurement of TRP on the terminal based on the first information; and the monitoring results show that the performance of AI measurement of TRP is good and the computing load of the access network device is low; the access network device may send third information to the first network element to request to enable AI measurement of the access network device.

[0259] Step S213: The first network element 1031 sends the fourth information to the access network device 102.

[0260] In some embodiments, after receiving third information from the access network device, the first network element can determine whether to agree to the content of the third information request based on the content of the third information request, and send fourth information to the access network device 102. The fourth information is used to indicate to the access network device the update information of the measurement method, for example, it may include stopping AI measurement or starting AI measurement.

[0261] In some embodiments, the first network element may determine the update information indicated by the fourth information based on the third information and the QoS requirements for positioning.

[0262] In some embodiments, the first network element can determine whether to agree to the content of the third information request based on the third information and the QoS requirements for positioning; if it agrees, it can send fourth information to the access network device, wherein the update information indicated by the fourth information is the same as the content of the third information request. For example, if the third information is used to request the activation of AI measurement, the fourth information can be used to indicate the activation of AI measurement.

[0263] In some embodiments, if the first network element determines the content of the request for the third information based on the third information and the QoS requirements for positioning, it can send the fourth information to the access network device. The fourth information is used to indicate the update information for the measurement. For example, if the third information is used to request the start of AI measurement, the fourth information can be used to indicate the stop of AI measurement. Alternatively, the first network element may choose to ignore the third information and not send the fourth information to the access network device to indicate that the current measurement does not need to be updated.

[0264] In some embodiments, the first network element may also partially agree to the content of the third information request based on the third information and the QoS requirements for positioning, and send fourth information to the access network device. The fourth information indicates update information for measurement. For example, if the third information is used to request the activation of AI measurement of the access network device, the fourth information may be used to indicate the activation of AI measurement of some access network devices, such as AI measurement of the access network device under the specified measurement type; or AI measurement of TRP.

[0265] In some embodiments, after sending third information to the first network element, the access network device can receive fourth information from the first network element. The fourth information is used to indicate updated information on the measurement method, such as stopping AI measurement or starting AI measurement. The access network device determines the measurement method to be executed or stopped based on the four pieces of information.

[0266] In some embodiments, if the access network device does not receive fourth information from the first network element after sending third information to the first network element, it continues to perform the current measurement.

[0267] In some embodiments, the fourth information may also be used to indicate measurement granularity and / or measurement type.

[0268] The measurement granularity may include access network equipment and / or TRP.

[0269] The measurement type may include at least one of the following: LOS / NLOS measurement; RTOA measurement; base station Rx-Tx time difference measurement.

[0270] In some embodiments, the fourth information may be used to indicate updated information for at least one of the measurement method, measurement granularity, and measurement type.

[0271] In some embodiments, the fourth information may be used to instruct the stopping of AI measurement of the access network device or to enable AI measurement of the access network device.

[0272] In some embodiments, the fourth information may also be used to indicate the measurement type of AI measurements of stopped access network devices, or to indicate the measurement type of AI measurements of started access network devices.

[0273] In some embodiments, the fourth information may be used to instruct the stopping of AI measurement of TRP or to instruct the starting of AI measurement of TRP.

[0274] In some embodiments, the fourth information may be used to indicate the measurement type of the AI ​​measurement for a stopped TRP, or to indicate the measurement type of the AI ​​measurement for an started TRP.

[0275] In some embodiments, the fourth information may adopt the same information format as the first information.

[0276] In some embodiments, the fourth information may include a first update indication, a second update indication, and a third update indication. The first update indication is used to indicate whether measurement at the access network device granularity is enabled or disabled; for example, if the first update indication is "1" or "true", it indicates that measurement at the access network device granularity is enabled; if the first update indication is "0" or "false", it indicates that measurement at the access network device granularity is disabled. The measurement may include AI measurement and / or non-AI measurement.

[0277] The second update instruction can be used to indicate whether to enable or stop measurements with a measurement granularity of TRP; for example, if the second instruction is "1" or "true", it indicates that measurements with a measurement granularity of TRP are performed; if the second update instruction is "0" or "false", it indicates that measurements with a measurement granularity of TRP are stopped. The measurements can include AI measurements and / or non-AI measurements.

[0278] The third update instruction can be used to indicate whether to enable or disable measurements of a corresponding measurement type. These measurements can include AI measurements and / or non-AI measurements.

[0279] In some embodiments, the third update indication may include update indications corresponding to different measurement types, such as LOS / NLOS update indication, RTOA update indication, and base station Rx-Tx time difference update indication, which are used to indicate whether to enable or stop the measurement of the corresponding measurement type. For example, if the LOS / NLOS update indication and RTOA update indication are "1" or "true", and the base station Rx-Tx time difference update indication is "0" or "false", then the measurement types that are enabled may include LOS / NLOS measurement and RTOA measurement.

[0280] In some embodiments, the third update indication may also employ a combined encoding method to indicate whether to enable measurement for each measurement type. For example, a bitmap may be used, where each bit corresponds to a measurement type. If the corresponding bit is "1", it indicates that measurement for the corresponding measurement type is enabled; if the corresponding bit is "0", it indicates that measurement for the corresponding measurement type is stopped.

[0281] In some embodiments, the fourth information may include joint encoding of the first update indication, the second update indication, and the third update indication, for example, in the form of a bitmap, which may include a first bit corresponding to the measurement granularity of the access network device, a second bit corresponding to the measurement granularity of the TRP, and a third bit corresponding to each measurement type.

[0282] In some embodiments, the access network device may adjust the measurement of the terminal according to the fourth information; perform the adjusted measurement on the terminal, obtain the measurement result, and send it to the first network element.

[0283] In some embodiments, the access network device may send third information to the first network element (step S212) before, after, or simultaneously with performing measurement on the terminal (step S220). Correspondingly, the access network device may receive fourth information sent by the first network element (step S213) before, after, or simultaneously with performing measurement on the terminal (step S220).

[0284] For example, after performing AI measurement on the terminal, the access network device can send a third message to the first network element to request the cessation of AI measurement based on the monitoring results of the AI ​​measurement and / or the computing load; the first network element can send a fourth message based on the third message and the QoS requirements for positioning to indicate the cessation of AI measurement; the access network device starts performing non-AI measurement on the terminal based on the fourth message.

[0285] For example, after performing non-AI measurements on the terminal, the access network device can send a third message to the first network element to request the start of AI measurements based on the computing power load of the access network device; the first network element sends a fourth message based on the third message and the QoS requirements for positioning to indicate the start of AI measurements; the access network device starts performing AI measurements on the terminal based on the fourth message.

[0286] For example, after performing AI measurement of TRP on the terminal, the access network device can send a third message to the first network element based on the monitoring results of the AI ​​measurement of TRP and / or the computing load to request the start of AI measurement of the access network device; the first network element can send a fourth message based on the third message and the QoS requirements for positioning to instruct the start of AI measurement of the access network device; the access network device starts performing AI measurement of the access network device on the terminal according to the fourth message.

[0287] The communication method involved in the embodiments of this disclosure may include at least one of steps S210, S212, S213, and S220. For example, step S210 may be implemented as an independent embodiment, step S212 may be implemented as an independent embodiment, step S213 may be implemented as an independent embodiment, step S220 may be implemented as an independent embodiment, step S210+S220 may be implemented as an independent embodiment, step S210+S212 may be implemented as an independent embodiment, step S212+S213 may be implemented as an independent embodiment, step S210+S212+S220 may be implemented as an independent embodiment, step S212+S213+S220 may be implemented as an independent embodiment, and step S210+S212+S213+S220 may be implemented as an independent embodiment, but is not limited thereto.

[0288] In some embodiments, steps S212 and S213 may be executed in an alternate order or simultaneously, or may be executed repeatedly in an overlapping manner.

[0289] In some embodiments, steps S220 and S212+S213 can be executed in an alternate order or simultaneously, or they can be executed repeatedly in an overlapping manner.

[0290] In some embodiments, steps S220 and S211 are optional, and one or more of these steps may be omitted or substituted in different embodiments.

[0291] In some embodiments, steps S210 and S220 are optional, and one or more of these steps may be omitted or substituted in different embodiments.

[0292] In some embodiments, the steps and their optional implementations in other embodiments described before or after this embodiment, as well as other related parts in the specification, can be referred to, and will not be repeated here.

[0293] In some embodiments, prior to step S210 in Figures 2A, 2B, and 2C, the first network element needs to determine the capability information of the access network device to perform measurements, or the availability information for performing location measurements. Based on this capability information, the first network element can generate first information, i.e., determine indication or suggestion information for performing measurements on the access network device.

[0294] In some embodiments, the access network device may send fifth information to the first network element, wherein the fifth information is used to indicate the access network device's ability to perform measurements, such as whether the access network device supports AI measurements.

[0295] In some embodiments, the fifth information may also be used to indicate measurement granularity and / or measurement type.

[0296] The measurement granularity may include access network equipment and / or TRP.

[0297] The measurement type may include at least one of the following: LOS / NLOS measurement; RTOA measurement; base station Rx-Tx time difference measurement.

[0298] In some embodiments, the fifth piece of information may be used to indicate whether the access network device supports AI measurement of the access network device.

[0299] In some embodiments, the fifth information may also be used to indicate the measurement type of the AI ​​measurement of the supported access network device.

[0300] In some embodiments, the fifth information can be used to indicate whether the access network device supports AI measurement of TRP.

[0301] In some embodiments, the fifth information may also be used to indicate the measurement type of the AI ​​measurement for the supported TRP.

[0302] In some embodiments, the fifth information may include a first availability indication, a second availability indication, and a third availability indication. The first availability indication may be used to indicate whether measurements at the access network device level are supported; the second availability indication may be used to indicate whether measurements at the TRP level are supported; and the third availability indication may be used to indicate the supported measurement types. The measurement methods include AI measurements and / or non-AI measurements.

[0303] For example, if the second availability indicator is "1" or "true" and the first availability indicator is "0" or "false", then the fifth information is used to indicate that the access network device supports measurements with a measurement granularity of TRP.

[0304] In some embodiments, the third availability indication may include availability indications corresponding to each different measurement type, such as LOS / NLOS availability indication, RTOA availability indication, base station Rx-Tx time difference availability indication, etc., which are used to indicate whether the corresponding measurement type is supported.

[0305] In some embodiments, the third availability indicator may also employ a combined encoding method to indicate the supported measurement types. For example, a bitmap may be used, where each bit corresponds to a measurement type. If the corresponding bit is "1", it indicates that the corresponding measurement type is supported.

[0306] In some embodiments, the fifth information can be carried by TRP information, that is, the fifth information can be sent to the first network element through the TRP information interaction process.

[0307] In some embodiments, the fifth information may be sent to the first network element through an interaction process based on the TRP information of the New Radio Positioning Protocol-A (NRPPa).

[0308] In some embodiments, the first network element may first send a TRP information request message to the access network device, such as an NRPPa TRP INFORMATION REQUEST message, to request the access network device's capability information to perform measurements.

[0309] The access network device sends a TRP information response message carrying the fifth information, such as an NRPPa TRP INFORMATION RESPONSE message, to the first network element to indicate the capability information to perform the measurement.

[0310] In some embodiments, the names of information, etc., are not limited to the names described in the embodiments. Terms such as "information", "message", "signal", "signaling", "report", "configuration", "indication", "instruction", "command", "channel", "parameter", "domain", "field", "symbol", "symbol", "codebook", "codeword", "codepoint", "bit", "data", "program", and "chip" can be used interchangeably.

[0311] In some embodiments, the terms "codebook," "codeword," and "precoding matrix" can be used interchangeably. For example, a codebook can be a collection of one or more codewords / precoding matrices.

[0312] In some embodiments, terms such as “uplink”, “uplink”, and “physical uplink” can be used interchangeably, as can terms such as “downlink”, “downlink”, and “physical downlink”, and terms such as “sidelink”, “sidelink”, “sidelink communication”, “sidelink communication”, “direct connection”, “direct link”, “direct communication”, and “direct link communication”.

[0313] In some embodiments, the terms “downlink control information (DCI),” “downlink (DL) assignment,” “DL DCI,” “uplink (UL) grant,” and “UL DCI” can be used interchangeably.

[0314] In some embodiments, terms such as "physical downlink shared channel (PDSCH)" and "DL data" can be used interchangeably, as can terms such as "physical uplink shared channel (PUSCH)" and "UL data".

[0315] In some embodiments, the terms “radio”, “wireless”, “radio access network (RAN)”, “access network (AN)”, and “RAN-based” can be used interchangeably.

[0316] In some embodiments, the terms "search space", "search space set", "search space configuration", "search space set configuration", "control resource set (CORESET)", and "CORESET configuration" can be used interchangeably.

[0317] In some embodiments, the terms "synchronization signal (SS)," "synchronization signal block (SSB)," "reference signal (RS)," "pilot," and "pilot signal" can be used interchangeably.

[0318] In some embodiments, terms such as “moment,” “point in time,” “time,” and “time location” can be used interchangeably, as can terms such as “duration,” “segment,” “time window,” “window,” and “time.”

[0319] In some embodiments, the terms "component carrier (CC)," "cell," "frequency carrier," and "carrier frequency" can be used interchangeably.

[0320] In some embodiments, the terms “resource block (RB)”, “physical resource block (PRB)”, “sub-carrier group (SCG)”, “resource element group (REG)”, “PRB pair”, “RB pair”, “resource element (RE)”, and “sub-carrier” can be used interchangeably.

[0321] In some embodiments, terms such as wireless access scheme and waveform can be used interchangeably.

[0322] In some embodiments, the terms "precoding", "precoder", "weight", "precoding weight", "quasi-co-location (QCL)", "transmission configuration indication (TCI) status", "spatial relation", "spatial domain filter", "transmission power", "phase rotation", "antenna port", "antenna port group", "layer", "the number of layers", "rank", "resource", "resource set", "resource group", "beam", "beam width", "beam angular degree", "antenna", "antenna element", and "panel" can be used interchangeably.

[0323] In some embodiments, the terms “frame”, “radio frame”, “subframe”, “slot”, “sub-slot”, “mini-slot”, “symbol”, “symbol”, and “transmission time interval (TTI)” can be used interchangeably.

[0324] In some embodiments, "acquire," "get," "obtain," "receive," "transmit," "bidirectional transmission," and "send and / or receive" can be used interchangeably and can be interpreted as receiving from other entities, acquiring from protocols, acquiring from higher layers, obtaining through self-processing, or autonomous implementation. Protocols include, for example, at least one of the 3GPP protocol, Wi-Fi protocol, and audio and / or video protocols.

[0325] In some embodiments, terms such as “send,” “transmit,” “report,” “distribute,” “transmit,” “bidirectional transmission,” “send and / or receive” can be used interchangeably.

[0326] In some embodiments, terms such as "certain," "preset," "default," "set," "indicated," "a certain," "any," and "first" can be used interchangeably. "Certain A," "preset A," "default A," "set A," "indicated A," "a certain A," "any A," and "first A" can be interpreted as A pre-defined in a protocol or the like, or as A obtained through setting, configuration, or instruction, or as specific A, a certain A, any A, or first A, but are not limited thereto.

[0327] In some embodiments, the determination or judgment can be made by a value represented by 1 bit (0 or 1), or by a true or false value (boolean), or by a comparison of numerical values ​​(e.g., a comparison with a predetermined value), but is not limited thereto.

[0328] In some embodiments, "not expecting to receive" can be interpreted as not receiving on time domain resources and / or frequency domain resources, or as not performing subsequent processing on the data and / or instructions received; "not expecting to send" can be interpreted as not sending, or as sending but not expecting the receiver to respond to the sent content.

[0329] In some embodiments, if an arrow in the interaction diagram representing the sending of information, signaling, etc. from one subject to another passes through other subjects, it can be interpreted as the information being forwarded from one subject to another via other subjects, or it can be interpreted as the information being sent from one subject to another without passing through other subjects.

[0330] In some embodiments, the inventive points of this application include at least one of the following:

[0331] 1. LMF needs to determine the functional availability (capability information) of the base station's AI measurement (positioning measurement, i.e., obtaining auxiliary measurement results for positioning through AI inference).

[0332] Among them, LMF can obtain the functional availability of AI measurement from the base station through the TRP information interaction process.

[0333] The functional availability of AI measurements can be indicated based on at least one of the base station, TRP, and measurement type (first availability indication, second availability indication, and third availability indication).

[0334] The measurement types include at least one of LOS / NLOS measurement, RTOA measurement, and base station Rx-Tx time difference measurement.

[0335] The availability of AI measurement functionality can include combinations for at least two measurement types.

[0336] 2. During a location process, determine whether to use AI measurement, including two methods:

[0337] Method 1: LMF determines whether AI measurement is used. LMF can determine whether the base station uses AI measurement based on the base station request.

[0338] In some embodiments, the LMF may send an AI measurement instruction (first information) to the base station, and the base station performs AI measurement according to the AI ​​measurement instruction, wherein the AI ​​measurement instruction may be an instruction with at least one of the base station, TRP and measurement type as the granularity (first instruction, second instruction and third instruction).

[0339] In some embodiments, the base station sends an AI measurement request (third information) to the LMF to indicate whether an AI measurement needs to be enabled or disabled. The base station determines the content of the AI ​​measurement request based on monitoring results of the AI ​​measurement performance or the base station's computing load. The AI ​​measurement to be enabled or disabled can be indicated at a granularity of at least one of the base station, TRP, and measurement type (first request indication, second request indication, and third request indication).

[0340] In some embodiments, the LMF can determine whether to use the AI ​​model (fourth information) based on at least one of the AI ​​measurement request and the location QoS requirement sent by the base station.

[0341] Method 2: The base station determines whether to use AI measurement based on the LMF's recommended information (first information) and its own situation.

[0342] In some embodiments, the LMF sends a recommendation for AI measurement to the base station, and the base station can determine whether to use AI measurement based on the LMF's recommendation. The base station's choice may differ from the LMF's recommendation.

[0343] In some embodiments, the base station needs to indicate to the LMF whether AI measurement (second information) has been used, wherein the indication may be granular with at least one of the base station, TRP, and measurement type (first usage indication, second usage indication, and third usage indication).

[0344] Figure 2D is an interactive schematic diagram illustrating a measurement method according to an embodiment of the present disclosure. As shown in Figure 2D, an embodiment of the present disclosure may include the following steps:

[0345] In step S230, the LMF sends a TRP information request (NRPPa TRP INFORMATION REQUEST) message to the base station.

[0346] Optionally, the TRP information type may be included in the TRP information request message.

[0347] In some embodiments, if the AI ​​measurement type is included in the TRP information type, the base station needs to include the availability information of the AI ​​measurement in the TRP information response message.

[0348] In step S231, the base station sends a TRP information response (NRPPa TRP INFORMATION RESPONSE) message to the LMF. The TRP information response message includes availability information measured by AI (the fifth piece of information).

[0349] The availability information for AI measurement functions includes at least one of the following:

[0350] Base station AI measurement availability indication (first availability indication);

[0351] TRP AI measures availability indication (second availability indication);

[0352] LOS / NLOS AI measurement availability indicator (LOS / NLOS availability indicator);

[0353] RTOA AI Measurement Availability Indicator (RTOA Availability Indicator);

[0354] Base station Rx-Tx time difference AI measurement availability indication (base station Rx-Tx time difference availability indication);

[0355] In some embodiments, the AI ​​measurement functionality availability information can be a bitmap, where each bit can be used to indicate whether a specific measurement type supports AI measurement.

[0356] Step S232: After starting the AI ​​positioning function, the LMF sends an NRPPa measurement request message to the base station. The measurement request message carries first information, which may be AI measurement indication information (method 1) or AI measurement suggestion information (method 2).

[0357] The first piece of information includes at least one of the following:

[0358] Base station AI measurement indication (first indication);

[0359] TRP AI measurement indication (second indication);

[0360] LOS / NLOS AI measurement indication (LOS / NLOS indication);

[0361] RTOA AI measurement indication (RTOA indication);

[0362] Base station Rx-Tx time difference AI measurement indication (base station Rx-Tx time difference indication).

[0363] In some embodiments, the first information corresponds one-to-one with the measurement type, as shown in Table 1 below. The TRP Measurement Quantities Item includes the TRP Measurement Type, the Requested AI Indicator, and the Requested AI LOS / NLOS. The TRP Measurement Type can be determined through enumeration and includes: Base Station Transmit / Receive Time Difference (gNB-RxTxTimeDiff), Uplink Probe Reference Signal Received Power (UL-SRS-RSRP), Uplink Angle of Arrival (UL-AoA), Uplink Round Trip Time (UL-RTOA), Multiple Uplink Angle of Arrival (Multiple UL-AoA), and Uplink Received Signal Code Power (UL-RSCP). If the AI ​​Measurement Indicator is "true", it means that the corresponding measurement type requires AI measurement. Table 1

[0364] In some embodiments, the first information shown is a bitmap, as shown in Table 2 below. A 4-bit (size(4)) bit string indicates the requested AI measurement type. Each bit can correspond to a measurement type (the first bit corresponds to UL RTOA, the second bit to LOS / NLOS, and the third bit to gNB-RxTxTimeDiff). For example, a value of "1" in the corresponding bit indicates that AI measurement is used for that measurement type, and a value of "0" indicates that AI measurement is not used for that measurement type. This method can reduce signaling overhead and facilitate information expansion. Table 2

[0365] In step S240, when the base station receives a confirmation to perform AI measurement, it activates the AI-based positioning functionality. The collected measurement data is used as input data for model inference, and the output data obtained from the inference is used as the measurement result.

[0366] In step S233, the base station sends a measurement response (NRPPa MEASUREMENT RESPONSE) message or a measurement report message to the LMF, which includes second information that can be used to instruct AI measurement to use instruction information (method 2).

[0367] AI measurement uses instructions that include at least one of the following:

[0368] Base station AI measurement usage instructions (first usage instructions);

[0369] TRP AI Measurement Usage Instructions (Second Usage Instructions);

[0370] LOS / NLOS AI Measurement Usage Instructions (LOS / NLOS Usage Instructions);

[0371] RTOA AI Measurement Usage Instructions (RTOA Usage Instructions);

[0372] Base station Rx-Tx time difference AI measurement usage instructions (Base station Rx-Tx time difference usage instructions).

[0373] Step S241: The base station performs AI performance evaluation to determine the performance output. As shown in Figure 2D, performance metrics can be evaluated based on the input data, output data, and corresponding real data labels collected during model inference as the performance evaluation results.

[0374] In step S234, the base station sends a measurement response (NRPPa MEASUREMENT RESPONSE) or a measurement report message to the LMF. This includes third information, which may be a request for AI measurement (Method 1).

[0375] The request information for AI measurement includes at least one of the following:

[0376] Base station AI measurement request indication (on or off) (first request indication);

[0377] TRP AI Measurement Request Instruction (On or Off) (Second Request Instruction);

[0378] LOS / NLOS AI Measurement Request Indicator (On or Off) (LOS / NLOS Request Indicator);

[0379] RTOA AI Measurement Request Indicator (On or Off) (RTOA Request Indicator);

[0380] Base station Rx-Tx time difference AI measurement request indication (on or off) (Base station Rx-Tx time difference request indication).

[0381] In step S235, the LMF determines whether to use AI measurement based on the AI ​​measurement request information and the location QoS, and sends an NRPPa measurement update to the base station, which includes the fourth information.

[0382] In some embodiments, the steps and their optional implementations in other embodiments described before or after this embodiment, as well as other related parts in the specification, can be referred to, and will not be repeated here.

[0383] This disclosure also proposes an apparatus (also referred to as a communication device, etc.) for implementing any of the above methods. For example, an apparatus is proposed that includes units or modules for implementing the steps performed by the terminal in any of the above methods. Furthermore, another apparatus is proposed that includes units or modules for implementing the steps performed by a network device (e.g., an access network device, a core network functional node, a core network device, etc.) in any of the above methods.

[0384] It should be understood that the division of units or modules in the above device is only a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. Furthermore, the units or modules in the device can be implemented by a processor calling software: for example, the device includes a processor connected to a memory containing instructions. The processor calls the instructions stored in the memory to implement any of the above methods or to implement the functions of the units or modules in the above device. The processor can be, for example, a general-purpose processor, such as a Central Processing Unit (CPU) or a microprocessor, and the memory can be internal or external to the device. Alternatively, the units or modules in the device can be implemented in the form of hardware circuits. The functionality of some or all of the units or modules can be achieved through the design of these hardware circuits, which can be understood as one or more processors. For example, in one implementation, the hardware circuit is an application-specific integrated circuit (ASIC). The functionality of some or all of the units or modules is achieved through the design of the logical relationships between the components within the circuit. In another implementation, the hardware circuit can be implemented using a programmable logic device (PLD). Taking a field-programmable gate array (FPGA) as an example, it can include a large number of logic gates. The connection relationships between the logic gates are configured through configuration files, thereby achieving the functionality of some or all of the units or modules. All units or modules of the above device can be implemented entirely through processor-called software, entirely through hardware circuits, or partially through processor-called software with the remaining parts implemented through hardware circuits.

[0385] In this embodiment, the processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction read and execute capabilities, such as a Central Processing Unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a microprocessor), or a digital signal processor (DSP). In another implementation, the processor can implement certain functions through the logical relationships of hardware circuits. The logical relationships of the aforementioned hardware circuits are fixed or reconfigurable. For example, the processor is a hardware circuit implemented using an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration document and configuring the hardware circuit can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units or modules. Furthermore, it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as a Neural Network Processing Unit (NPU), a Tensor Processing Unit (TPU), or a Deep Learning Processing Unit (DPU).

[0386] Figure 3A is a schematic diagram of the structure of an access network device according to an embodiment of this disclosure. The access network device 3100 is used to execute any of the above methods. In some embodiments, as shown in Figure 3A, the access network device 3100 may include at least one of a transceiver module 3101, a processing module 3102, etc. In some embodiments, the transceiver module 3101 is used to receive first information from a first network element; the processing module 3102 is used to determine a measurement mode to be executed or stopped based on the first information; the first information is used to indicate or suggest at least one of the following: enabling AI measurement; stopping AI measurement; enabling measurement; stopping measurement. Optionally, the transceiver module is used to execute at least one of the communication steps (e.g., steps S210-S212, S230-S235, but not limited thereto) executed by the access network device 102 in any of the above methods, which will not be elaborated here. Optionally, the processing module is used to execute at least one of the other steps (e.g., steps S220, S240-S241, but not limited thereto) executed by the terminal 101 in any of the above methods, which will not be elaborated here.

[0387] Figure 3B is a schematic diagram of the structure of the first network element proposed in an embodiment of this disclosure. The first network element 3200 is used to perform any of the above methods. In some embodiments, as shown in Figure 3B, the first network element 3200 may include at least one of a transceiver module 3201, a processing module 3202, etc. In some embodiments, the processing module 3202 is used to determine first information; the transceiver module 3201 is used to send the first information to the access network device; wherein the first information is used to indicate or suggest at least one of the following: start AI measurement; stop AI measurement; start measurement; stop measurement. Optionally, the transceiver module 3201 is used to perform at least one of the communication steps (e.g., steps S210-S212, S230-S235, but not limited thereto) performed by the first network element 1031 in any of the above methods, which will not be described in detail here. Optionally, the processing module 3202 is used to perform at least one of the other steps performed by the network device 102 in any of the above methods, which will not be described in detail here.

[0388] In some embodiments, the transceiver module may include a transmitting module and / or a receiving module, which may be separate or integrated. Optionally, the transceiver module may be interchangeable with a transceiver.

[0389] In some embodiments, the processing module may be a single module or may include multiple sub-modules. Optionally, the multiple sub-modules may each perform all or part of the steps required by the processing module.

[0390] In some embodiments, the processing module can be interchanged with the processor, and the transceiver module can be interchanged with the transceiver.

[0391] Figure 4A is a schematic diagram of the structure of the communication device 4100 proposed in an embodiment of this disclosure. The communication device 4100 can be a network device (e.g., access network device, core network device, etc.), a terminal (e.g., user equipment, etc.), a chip, chip system, or processor that supports the network device in implementing any of the above methods, or a chip, chip system, or processor that supports the terminal in implementing any of the above methods. The communication device 4100 can be used to implement the methods described in the above method embodiments; for details, please refer to the descriptions in the above method embodiments.

[0392] As shown in Figure 4A, the communication device 4100 is used to execute any of the above methods. In some embodiments, the communication device 4100 includes one or more processors 4101. The processor 4101 may be a general-purpose processor or a special-purpose processor, such as a baseband processor or a central processing unit. The baseband processor may be used to process communication protocols and communication data, and the central processing unit may be used to control communication devices (e.g., base stations, baseband chips, terminal devices, terminal device chips, DUs or CUs, etc.), execute programs, and process program data. Optionally, the communication device 4100 is used to execute any of the above methods. Optionally, one or more processors 4101 are used to invoke instructions to cause the communication device 4100 to execute any of the above methods.

[0393] In some embodiments, the communication device 4100 further includes one or more transceivers 4102. When the communication device 4100 includes one or more transceivers 4102, the transceiver 4102 performs at least one of the communication steps such as sending and / or receiving in the above method (e.g., steps S210-S212, S230-S235, but not limited thereto), and the processor 4101 performs at least one of other steps (e.g., steps S220, S240-S241, but not limited thereto). In optional embodiments, the transceiver may include a receiver and / or a transmitter, which may be separate or integrated together. Optionally, the terms transceiver, transceiver unit, transceiver, transceiver circuit, interface circuit, interface, etc., can be used interchangeably; the terms transmitter, transmitting unit, transmitter, transmitting circuit, etc., can be used interchangeably; the terms receiver, receiving unit, receiver, receiving circuit, etc., can be used interchangeably.

[0394] In some embodiments, the communication device 4100 further includes one or more memories 4103 for storing data and / or instructions. Optionally, one or more processors 4101 are used to invoke instructions stored in the memory 4103 to cause the communication device 4100 to perform any of the above methods. Optionally, all or part of the memory 4103 may also be located outside the communication device 4100. In an optional embodiment, the communication device 4100 may include one or more interface circuits 4104. Optionally, the interface circuit 4104 is connected to the memory 4102 and can be used to receive data and / or instructions from the memory 4102 or other devices, and can be used to send data and / or instructions to the memory 4102 or other devices. For example, the interface circuit 4104 can read data and / or instructions stored in the memory 4102 and send the data and / or instructions to the processor 4101.

[0395] The communication device 4100 described in the above embodiments may be a network device or a terminal, but the scope of the communication device 4100 described in this disclosure is not limited thereto, and the structure of the communication device 4100 may not be limited by FIG4A. The communication device may be a standalone device or may be part of a larger device. For example, the communication device may be: (1) a standalone integrated circuit IC, or chip, or chip system or subsystem; (2) a collection of one or more ICs, optionally, the IC collection may also include storage components for storing data, programs and / or instructions; (3) an ASIC, such as a modem; (4) a module that can be embedded in other devices; (5) a receiver, terminal device, smart terminal device, cellular phone, wireless device, handheld device, mobile unit, vehicle device, network device, cloud device, artificial intelligence device, etc.; (6) others, etc.

[0396] Figure 4B is a schematic diagram of the structure of chip 4200 according to an embodiment of this disclosure. For cases where the communication device 4100 can be a chip or a chip system, please refer to the schematic diagram of chip 4200 shown in Figure 4B, but it is not limited thereto.

[0397] Chip 4200 includes one or more processors 4201. Chip 4200 is used to perform any of the above methods.

[0398] In some embodiments, chip 4200 further includes one or more interface circuits 4202. Optionally, terms such as interface circuit, interface, and transceiver pin can be used interchangeably. In some embodiments, chip 4200 further includes one or more memories 4203 for storing data and / or instructions. Optionally, all or part of the memories 4203 may be located outside of chip 4200. Optionally, the interface circuits 4202 are connected to the memories 4203, and the interface circuits 4202 can be used to receive data and / or instructions from the memories 4203 or other devices, and can be used to send data and / or instructions to the memories 4203 or other devices. For example, the interface circuits 4202 can read data and / or instructions stored in the memories 4203 and send the data and / or instructions to the processor 4201.

[0399] In some embodiments, the interface circuit 4202 performs at least one of the communication steps such as sending and / or receiving in the above-described method (e.g., steps S210, S211, S212, S221-S224, S226-S227, but not limited thereto). The interface circuit 4202 performing the communication steps such as sending and / or receiving in the above-described method refers, for example, to the interface circuit 4202 performing data and / or instruction interaction between the processor 4201, the chip 4200, the memory 4203, or the transceiver device. In some embodiments, the processor 4201 performs at least one of other steps (e.g., steps S213, S225, but not limited thereto).

[0400] The modules and / or devices described in the various embodiments, such as virtual devices, physical devices, and chips, can be combined or separated arbitrarily as needed. Optionally, some or all steps can also be performed collaboratively by multiple modules and / or devices, which is not limited here.

[0401] This disclosure also proposes a storage medium storing instructions that, when executed on a communication device, cause the communication device to perform any of the above methods. Optionally, the storage medium is an electronic storage medium. Optionally, the storage medium is a computer-readable storage medium, but not limited thereto; it may also be a storage medium readable by other devices. Optionally, the storage medium may be a non-transitory storage medium, but not limited thereto; it may also be a temporary storage medium.

[0402] This disclosure also proposes a program product, including a program and / or instructions, which, when executed by a communication device, cause the communication device to perform any of the above methods. Optionally, the program product is a computer program product. Optionally, the program product is stored on the storage medium.

[0403] This disclosure also proposes a computer program that, when run on a computer, causes the computer to perform any of the above methods.

Claims

1. A measurement method, performed by an access network device, characterized in that, The method includes: Receive the first information from the first network element and determine the measurement mode to be executed or stopped based on the first information; The first information is used to indicate or suggest at least one of the following: Enable AI measurement; Stop AI measurement; Start measurement; Stop the measurement.

2. The method according to claim 1, characterized in that, The first information is also used to determine the measurement granularity and / or measurement type.

3. The method according to claim 2, characterized in that, The measurement granularity includes: access network equipment and / or TRP.

4. The method according to claim 2, characterized in that, The measurement type includes at least one of the following: Sight distance; Non-line-of-sight; Round trip time; The time difference between base station transmission and reception.

5. The method according to any one of claims 1-4, characterized in that, The method further includes: Send a second message to the first network element, the second message being used to instruct the first network element on the measurement method performed by the access network device; the measurement method includes AI measurement or non-AI measurement.

6. The method according to claim 5, characterized in that, The second information is also used to indicate at least one of the following: Perform measurements at the access network device level; Perform a measurement with a particle size of TRP; The measurement type of the measurement.

7. The method according to any one of claims 1-6, characterized in that, The method further includes: Send a third message to the first network element, the third message being used to request to stop AI measurement or to request to start AI measurement.

8. The method according to claim 7, characterized in that, The third information is also used to indicate at least one of the following: Request to enable or stop AI measurement at the access network device level; Request to enable or stop AI measurement with a measurement granularity of TRP; The measurement type of the AI ​​measurement.

9. The method according to claim 7 or 8, characterized in that, The method further includes: Obtain monitoring results for the AI ​​measurements, the monitoring results being used to identify the performance of the AI ​​measurements; The third information is determined based on the monitoring results and / or the computing load of the access network equipment.

10. The method according to any one of claims 7-9, characterized in that, The method further includes: Receive fourth information from the first network element, and adjust the measurement method according to the fourth information; The fourth piece of information is used to indicate whether to stop AI measurement or start AI measurement.

11. The method according to any one of claims 1-10, characterized in that, The method includes: Send a fifth message to the first network element, the fifth message being used to instruct the access network device to perform measurement capability information.

12. The method according to claim 11, characterized in that, The fifth piece of information is used to indicate at least one of the following: Does it support AI measurement at the access network device level? Does it support AI measurement with a measurement granularity of TRP? Supported AI measurement types.

13. A measurement method, performed by a first network element, characterized in that, The method includes: Send first information to the access network device, the first information being used to instruct or suggest at least one of the following: Enable AI measurement; Stop AI measurement; Start measurement; Stop the measurement.

14. The method according to claim 13, characterized in that, The first information is also used to determine the measurement granularity and / or measurement type.

15. The method according to claim 14, characterized in that, The measurement granularity includes: access network equipment and / or TRP.

16. The method according to claim 14, characterized in that, The measurement type includes at least one of the following: Sight distance; Non-line-of-sight; Round trip time; The time difference between base station transmission and reception.

17. The method according to any one of claims 13-16, characterized in that, The method further includes: The first network element receives second information from the access network device, the second information being used to instruct the first network element on the measurement method performed by the access network device; the measurement method includes AI measurement or non-AI measurement.

18. The method according to claim 17, characterized in that, The second information is also used to indicate at least one of the following: Perform measurements at the access network device level; Perform a measurement with a particle size of TRP; The measurement type of the measurement.

19. The method according to any one of claims 13-18, characterized in that, The method further includes: The third information is received from the access network device, which is used to request to stop AI measurement or to request to start AI measurement.

20. The method according to claim 19, characterized in that, The third information is also used to indicate at least one of the following: Request to enable or stop AI measurement at the access network device level; Request to enable or stop AI measurement with a measurement granularity of TRP; The measurement type of the AI ​​measurement.

21. The method according to claim 19 or 20, characterized in that, The method further includes: A fourth message is sent to the access network device, the fourth message being used to instruct the AI ​​measurement to be stopped or started.

22. The method according to claim 21, characterized in that, The method further includes: The fourth information is determined based on the third information and the Quality of Service (QoS) requirements for positioning.

23. The method according to any one of claims 13-22, characterized in that, The method includes: The access network device receives fifth information, which is used to instruct the access network device to perform measurement capability information.

24. The method according to claim 23, characterized in that, The fifth piece of information is used to indicate at least one of the following: Does it support AI measurement at the access network device level? Does it support AI measurement with a measurement granularity of TRP? Supported measurement types.

25. An access network device, characterized in that, include: The transceiver module is used to receive first information from the first network element; The processing module is used to determine whether to execute or stop the measurement method based on the first information; The first information is used to indicate or suggest at least one of the following: Enable AI measurement; Stop AI measurement; Start measurement; Stop the measurement.

26. A first network element, characterized in that, include: The processing module is used to determine the first piece of information; The transceiver module is used to send the first information to the access network equipment; The first information is used to indicate or suggest at least one of the following: Enable AI measurement; Stop AI measurement; Start measurement; Stop the measurement.

27. A communication device, characterized in that, The communication device is used to perform the measurement method according to any one of claims 1-12 and 13-24.

28. A communication system, characterized in that, It includes access network equipment and core network equipment, wherein the access network equipment is configured to implement the measurement method of any one of claims 1-12, and the core network equipment is configured to implement the measurement method of any one of claims 13-24.

29. A storage medium storing instructions, characterized in that, When the instruction is executed on the communication device, the communication device performs the measurement method as described in any one of claims 1-12, 13-24.

30. A program product comprising at least one of a program and instructions, characterized in that, When at least one of the programs or instructions is executed by the communication device, it implements the steps of the method according to any one of claims 1-23 and 13-24.

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