Positioning method and apparatus, and communication device, communication system, storage medium and program product

Abstract

Provided in the embodiments of the present disclosure are a positioning method and apparatus, and a communication device, a communication system, a storage medium and a program product. The method is executed by a first node, and the method comprises: acquiring measurement data obtained by a first node measuring a positioning reference signal at n time-domain sampling points, wherein the measurement data comprises first power data and latency data, the first power data indicating the measured power of the positioning reference signal, and the latency data indicating a measurement time series of the first power data, and n is a positive integer; and sending first information to a second node, wherein the first information is used for the second node to determine positioning information, and the first information comprises the latency data of the n pieces of measurement data obtained by the first node by means of measurement, the latency data of the n pieces of measurement data being sorted in the first information according to the magnitudes of first power data of the n pieces of measurement data. The technical solution provided in the embodiments of the present disclosure is conducive to reducing the data reporting overheads of a communication system while ensuring positioning accuracy.

Description

Positioning method and device, communication equipment, communication system and storage medium, program product Technical Field

[0001] The present disclosure relates to the field of communication technology, and in particular to positioning methods and devices, communication equipment, communication systems and storage media, and program products. Background Art

[0002] High-precision positioning based on artificial intelligence (AI) models is an important application of AI technology in the field of communications and is also a key component of the Third Generation Partnership Project (3GPP). rd One of the important research directions of 3GPP standardization.

[0003] Summary of the Invention

[0004] Embodiments of the present disclosure provide a positioning method and apparatus, a communication device and storage medium, and a program product.

[0005] According to a first aspect of an embodiment of the present disclosure, a positioning method is provided, wherein the method is performed by a first node and includes:

[0006] Obtaining measurement data obtained by the first node measuring a positioning reference signal at n time domain sampling points; the measurement data includes first power data and delay data; the first power data indicates the measured power of the positioning reference signal; the delay data indicates the measurement timing of the first power data; and n is a positive integer;

[0007] Sending first information to a second node; the first information is used by the second node to determine positioning information, the first information including delay data of n measurement data measured by the first node; the delay data of the n measurement data are sorted in the first information according to the size of the first power data of the n measurement data.

[0008] According to a second aspect of an embodiment of the present disclosure, a positioning method is provided, wherein the method is performed by a second node and includes:

[0009] receiving first information sent by a first node; the first information including delay data of n measurement data measured by the first node; the delay data of the n measurement data being sorted in the first information according to the magnitude of first power data of the n measurement data; the n measurement data being obtained by the first node by measuring a positioning reference signal at n time domain sampling points, the first power data indicating the measured power of the positioning reference signal; the delay data indicating a measurement timing of the first power data; and n being a positive integer;

[0010] Determine positioning information based on the first information.

[0011] According to a third aspect of an embodiment of the present disclosure, a positioning method is provided, wherein the method is performed by a communication system, and the method includes:

[0012] The first node obtains measurement data obtained by the first node measuring the positioning reference signal at n time domain sampling points; the measurement data includes first power data and delay data; the first power data indicates the measured power of the positioning reference signal; the delay data indicates the measurement timing of the first power data; and n is a positive integer;

[0013] The first node sends first information to the second node; the first information is used by the second node to determine positioning information, the first information including delay data of n measurement data measured by the first node; the delay data of the n measurement data are sorted in the first information according to the magnitude of the first power data of the n measurement data;

[0014] The second node determines positioning information according to the first information.

[0015] According to a fourth aspect of an embodiment of the present disclosure, a first node is provided, wherein the first node includes:

[0016] a processing module configured to obtain measurement data obtained by the first node measuring a positioning reference signal at n time domain sampling points; the measurement data including first power data and delay data; the first power data indicating the measured power of the positioning reference signal; the delay data indicating the measurement timing of the first power data; and n being a positive integer;

[0017] A sending module is configured to send first information to a second node; the first information is used by the second node to determine positioning information, the first information including delay data of n measurement data measured by the first node; the delay data of the n measurement data are sorted in the first information according to the size of the first power data of the n measurement data.

[0018] According to a fifth aspect of an embodiment of the present disclosure, a second node is provided, wherein the second node includes:

[0019] a receiving module configured to receive first information sent by a first node; the first information includes delay data of n measurement data measured by the first node; the delay data of the n measurement data are sorted in the first information according to the magnitude of first power data of the n measurement data; the n measurement data are obtained by the first node measuring a positioning reference signal at n time domain sampling points, the first power data indicates the measured power of the positioning reference signal; the delay data indicates a measurement timing of the first power data; and n is a positive integer;

[0020] The determination module is configured to determine positioning information according to the first information.

[0021] According to a sixth aspect of an embodiment of the present disclosure, a communication system is provided, wherein the communication system includes a first node and a second node, the first node is configured to implement the positioning method provided by the first aspect, and the second node is configured to implement the positioning method provided by the second aspect.

[0022] According to a seventh aspect of an embodiment of the present disclosure, a communication device is provided, wherein the communication device includes:

[0023] one or more processors;

[0024] The processor is used to call instructions to enable the communication device to execute the positioning method provided by the first aspect or the second aspect.

[0025] According to an eighth aspect of an embodiment of the present disclosure, a storage medium is provided, wherein the storage medium stores instructions, and when the instructions are executed on a communication device, the communication device executes the positioning method provided by the first aspect or the second aspect.

[0026] According to a ninth aspect of an embodiment of the present disclosure, a computer program product is provided, wherein the computer program product includes a computer program or instructions, and when the computer program or instructions are executed by a processor or a communication device, the communication device executes the positioning method provided by the first aspect or the second aspect.

[0027] The technical solution provided by the embodiments of the present disclosure facilitates a first node to obtain n measurement data for positioning in the time domain sampling point dimension (i.e., the time dimension). When reporting the measurement data, the first node sends a first message to the second node, where the first message carries the delay data of the n measurement data but does not carry the first power data of the n measurement data, thereby effectively reducing data reporting overhead. On this basis, in order to ensure positioning accuracy, the delay data of the n measurement data are sorted in the first message according to the size of the first power data of the n measurement data, so that the receiving end can recover the order of the first power data corresponding to the n delay data, thereby achieving positioning.

[0028] It should be understood that the foregoing general description and the following detailed description are merely exemplary and explanatory and are not restrictive of the embodiments of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present invention and, together with the description, serve to explain the principles of the embodiments of the present invention.

[0030] FIG1A is a schematic diagram showing an architecture of a communication system according to an exemplary embodiment;

[0031] FIG1B is a schematic flow chart showing a positioning method based on an AI model according to an exemplary embodiment;

[0032] FIG1C is a schematic flow chart showing another positioning method based on an AI model according to an exemplary embodiment;

[0033] FIG1D is a schematic diagram illustrating an application mode of positioning technology based on an AI model according to an exemplary embodiment;

[0034] FIG2A is an interactive schematic diagram showing a positioning method according to an exemplary embodiment;

[0035] FIG2B is an interactive schematic diagram showing a positioning method according to an exemplary embodiment;

[0036] FIG3A is a schematic flow chart showing a positioning method according to an exemplary embodiment;

[0037] FIG3B is a schematic flow chart showing a positioning method according to an exemplary embodiment;

[0038] FIG3C is a schematic diagram showing a flow chart of a positioning method according to an exemplary embodiment;

[0039] FIG4A is a schematic flow chart showing a positioning method according to an exemplary embodiment;

[0040] FIG4B is a schematic flow chart showing a positioning method according to an exemplary embodiment;

[0041] FIG4C is a schematic diagram showing a flow chart of a positioning method according to an exemplary embodiment;

[0042] FIG5 is an interactive schematic diagram showing a positioning method according to an exemplary embodiment;

[0043] FIG6 is a schematic diagram showing an application process of an AI positioning model according to an exemplary embodiment;

[0044] FIG7A is a schematic structural diagram of a first node according to an exemplary embodiment;

[0045] FIG7B is a schematic structural diagram of a second node according to an exemplary embodiment;

[0046] FIG8A is a schematic structural diagram of a communication device according to an exemplary embodiment;

[0047] FIG8B is a schematic structural diagram of a chip according to an exemplary embodiment. DETAILED DESCRIPTION

[0048] Embodiments of the present disclosure provide a positioning method and apparatus, a communication device, a communication system and storage medium, and a program product.

[0049] In a first aspect, an embodiment of the present disclosure provides a positioning method, wherein the method is performed by a first node and includes:

[0050] Obtain measurement data obtained by the first node from measuring a positioning reference signal at n time domain sampling points; the measurement data includes first power data and delay data; the first power data indicates the measured power of the positioning reference signal; the delay data indicates the measurement timing of the first power data; n is a positive integer; send first information to the second node; the first information is used by the second node to determine positioning information, the first information includes delay data of n measurement data measured by the first node; the delay data of the n measurement data are sorted in the first information according to the size of the first power data of the n measurement data.

[0051] In the above embodiment, the first node obtains n measurement data for positioning in the time domain sampling point dimension (i.e., the time dimension), and when reporting the measurement data, the first node sends a first message to the second node, where the first message carries the delay data of the n measurement data but does not carry the first power data of the n measurement data, thereby effectively reducing the data reporting overhead; on this basis, in order to ensure positioning accuracy, the delay data of the n measurement data are sorted in the first message according to the size of the first power data of the n measurement data, so that the receiving end can restore the order of the first power data corresponding to the n delay data, thereby achieving positioning.

[0052] In conjunction with some embodiments of the first aspect, in some embodiments, obtaining measurement data obtained by the first node measuring the positioning reference signal at n time-frequency sampling points includes:

[0053] Obtaining measurement data obtained by the first node at N time domain sampling points, where N is greater than or equal to n;

[0054] According to the measurement data of the N time-domain sampling points, the measurement data of n time-domain sampling points that meet the first condition are selected.

[0055] In the above embodiment, the first node selects n measurement data that meet the first condition from the measurement data obtained at N time-domain sampling points, and reports data based on the n measurement data. Because n is less than or equal to N, the amount of measurement data that the first node needs to report can be reduced, thereby reducing data reporting overhead.

[0056] In combination with some embodiments of the first aspect, in some embodiments, the measurement data of the n time domain sampling points that meet the first condition are the measurement data of the n time domain sampling points where the first power data is the largest.

[0057] In the above embodiment, the first node selects, based on the first power data, the measurement data of the n time domain sampling points with the largest first power data from the measurement data obtained by measuring at N time domain sampling points. Since the larger the first power data measured at the time domain sampling point, the smaller the attenuation of the positioning reference signal reaching the positioning terminal at that time, that is, the more likely the transmission path is a line-of-sight path, the more information can be provided for assisting positioning, and the more helpful it is in improving positioning accuracy. Therefore, by reporting the measurement data of the n time domain sampling points with the largest first power data, positioning accuracy is improved. In this way, measurement data that is not effective for improving positioning accuracy is eliminated, thereby reducing unnecessary signaling overhead.

[0058] In combination with some embodiments of the first aspect, in some embodiments, the first information includes n bit vectors; one bit vector is used to carry delay data in the measurement data of a time domain sampling point.

[0059] In the above embodiment, binary bit vectors are used to carry the delay data in the measurement data of the time-domain sampling points, eliminating the need for additional processing of the delay data, such as encoding or decoding. This improves data transmission efficiency and reduces resource waste caused by additional processing of the delay data. Furthermore, the n bit vectors within the first information are used to indicate the delay data in the measurement data of the n time-domain sampling points, respectively, thereby enabling reporting of the delay data for the n time-domain sampling points.

[0060] In combination with some embodiments of the first aspect, in some embodiments, the i-th bit vector in the n bit vectors is used to indicate the delay data measured at the i-th time domain sampling point in the first sorting result or the second sorting result; the first sorting result is the sorting result from large to small of the first power data measured at the N time domain sampling points; the second sorting result is the sorting result from small to large of the first power data measured at the N time domain sampling points.

[0061] In the above embodiment, the order of the first power data corresponding to the delay data indicated by the n bit vectors is determined based on the order of the n bit vectors, so that the second node can recover the order of the first power data corresponding to the n delay data based on the order of the n bit vectors in the received first information, and set the second power data corresponding to the delay data corresponding to the n bit vectors based on the order of the first power data, thereby achieving positioning. In conjunction with some embodiments of the first aspect, in some embodiments, the delay data includes the numbers of time domain sampling points.

[0062] In the above embodiment, since the number of the time domain sampling point corresponding to the measurement data can indicate the measurement timing of the first power data measured at the time domain sampling point, the number of the time domain sampling point can be used as the delay data in the measurement data measured at the time domain sampling point, so as to directly report the number of the time domain sampling point. On the one hand, it is beneficial to reduce the data reporting overhead, and on the other hand, it is also beneficial for the second node to determine the time domain sampling point positions of the n received measurement data according to the number of the time domain sampling point.

[0063] In conjunction with some embodiments of the first aspect, in some embodiments, second information sent by the second node is received; the second information is used by the first node to determine a reporting type of the measurement data; and the reporting type includes at least one of the following:

[0064] The first type, when the first type is adopted, the delay data in the measurement data is sent to the second node;

[0065] The second type: when the second type is adopted, the delay data and the first power data in the measurement data are both sent to the second node.

[0066] In the above embodiment, the second node controls the reporting type of the measurement data of the first node through the second information, so that the first node can report the measurement data in different reporting types according to the different requirements of the second node for the measurement data and / or the configuration and deployment of the positioning model in the second node, so that the measurement data reported by the first node can match the positioning capability of the second node, the positioning model configured by the second node and / or the actual transmission capability of the communication system.

[0067] In conjunction with some embodiments of the first aspect, in some embodiments, the second information is further used to indicate one of the following:

[0068] The number n of the delay data carried in the first information;

[0069] The delay data carried by the first information is arranged in ascending or descending order according to the first power data.

[0070] In the above embodiment, the second information is used to indicate the number n of the delay data carried in the first information and / or the sorting method of the delay data carried by the first information, so that the first node completes the preprocessing and reporting of the measurement data according to the instructions of the second information, and also facilitates the measurement data reported by the first node to be correctly recovered by the second node.

[0071] In a second aspect, an embodiment of the present disclosure provides a positioning method, wherein the method is performed by a second node, and the method includes:

[0072] receiving first information sent by a first node; the first information including delay data of n measurement data measured by the first node; the delay data of the n measurement data being sorted in the first information according to the magnitude of first power data of the n measurement data; the n measurement data being obtained by the first node by measuring a positioning reference signal at n time domain sampling points, the first power data indicating the measured power of the positioning reference signal; the delay data indicating a measurement timing of the first power data; and n being a positive integer;

[0073] Determine positioning information based on the first information.

[0074] In the above embodiment, the second node receives the first information sent by the first node, and obtains the delay data of n measurement data used for positioning measured by the first node in the time domain sampling point dimension (i.e., the time dimension) based on the first information, and determines the size sorting of the first power data of the n measurement data based on the arrangement of the delay data of the n measurement data, thereby realizing positioning, thereby reducing the data reporting overhead of the communication system while ensuring the positioning accuracy.

[0075] In combination with some embodiments of the second aspect, in some embodiments, the first information includes n bit vectors; one bit vector is used to carry delay data in the measurement data of a time domain sampling point.

[0076] In combination with some embodiments of the second aspect, in some embodiments, the i-th bit vector in the n bit vectors is used to indicate the delay data measured at the i-th time domain sampling point in the first sorting result or the second sorting result; the first sorting result is the sorting result from large to small of the first power data measured at the N time domain sampling points; the second sorting result is the sorting result from small to large of the first power data measured at the N time domain sampling points.

[0077] In combination with some embodiments of the second aspect, in some embodiments, the delay data includes the numbers of time domain sampling points.

[0078] In conjunction with some embodiments of the second aspect, in some embodiments, the method further includes:

[0079] According to the order of the delay data of the n measurement data in the first information, the second power data of the measurement data of the n time domain sampling points is set; wherein the size ordering of the second power data of the measurement data of the n time domain sampling points is the same as the size ordering of the first power data of the measurement data of the n time domain sampling points.

[0080] With reference to some embodiments of the second aspect, in some embodiments, determining positioning information according to the first information includes:

[0081] The n pieces of the second power data are processed by a positioning model to obtain the positioning information output by the positioning model.

[0082] In conjunction with some embodiments of the second aspect, in some embodiments, the method further includes:

[0083] Sending second information to the first node; the second information is used by the first node to determine a reporting type of the measurement data; the reporting type includes at least one of the following:

[0084] The first type, when the first type is adopted, the delay data in the measurement data is sent to the second node;

[0085] The second type: when the second type is adopted, the delay data and the first power data in the measurement data are both sent to the second node.

[0086] In conjunction with some embodiments of the second aspect, in some embodiments, the second information is further used to indicate at least one of the following:

[0087] The number n of the delay data carried in the first information;

[0088] The delay data carried by the first information is arranged in ascending or descending order according to the first power data.

[0089] In conjunction with some embodiments of the second aspect, in some embodiments, the method further includes:

[0090] Get the positioning model;

[0091] The second information is determined based on the positioning model; the reporting type indicated by the second information is determined by an input parameter of the positioning model.

[0092] In a third aspect, an embodiment of the present disclosure provides a positioning method, wherein the method is performed by a communication system, and the method includes:

[0093] The first node obtains measurement data obtained by the first node measuring the positioning reference signal at n time domain sampling points; the measurement data includes first power data and delay data; the first power data indicates the measured power of the positioning reference signal; the delay data indicates the measurement timing of the first power data; and n is a positive integer;

[0094] The first node sends first information to the second node; the first information is used by the second node to determine positioning information, the first information including delay data of n measurement data measured by the first node; the delay data of the n measurement data are sorted in the first information according to the magnitude of the first power data of the n measurement data;

[0095] The second node determines positioning information according to the first information.

[0096] In a fourth aspect, an embodiment of the present disclosure provides a first node, wherein the first node includes:

[0097] a processing module configured to obtain measurement data obtained by the first node measuring a positioning reference signal at n time domain sampling points; the measurement data including first power data and delay data; the first power data indicating the measured power of the positioning reference signal; the delay data indicating the measurement timing of the first power data; and n being a positive integer;

[0098] A sending module is configured to send first information to a second node; the first information is used by the second node to determine positioning information, the first information including delay data of n measurement data measured by the first node; the delay data of the n measurement data are sorted in the first information according to the size of the first power data of the n measurement data.

[0099] In a fifth aspect, an embodiment of the present disclosure provides a second node, wherein the second node includes:

[0100] a receiving module configured to receive first information sent by a first node; the first information includes delay data of n measurement data measured by the first node; the delay data of the n measurement data are sorted in the first information according to the magnitude of first power data of the n measurement data; the n measurement data are obtained by the first node measuring a positioning reference signal at n time domain sampling points, the first power data indicates the measured power of the positioning reference signal; the delay data indicates a measurement timing of the first power data; and n is a positive integer;

[0101] The determination module is configured to determine positioning information according to the first information.

[0102] In a sixth aspect, an embodiment of the present disclosure provides a communication system, wherein the communication system includes a first node and a second node, the first node is configured to implement the positioning method described in the optional implementation manner of the first aspect, and the second node is configured to implement the positioning method described in the optional implementation manner of the second aspect.

[0103] In a seventh aspect, an embodiment of the present disclosure provides a communication device, the communication device comprising:

[0104] one or more processors;

[0105] The processor is used to call instructions to enable the communication device to execute the positioning method described in the optional implementation manner of the first aspect or the second aspect.

[0106] In an eighth aspect, an embodiment of the present disclosure provides a storage medium, wherein the storage medium stores instructions, which, when executed on a communication device, enable the communication device to execute the positioning method described in the optional implementation of the first aspect or the second aspect.

[0107] In a ninth aspect, an embodiment of the present disclosure provides a program product, which, when executed by a communication device, enables the communication device to execute the positioning method described in the optional implementation manner of the first aspect or the second aspect.

[0108] In a tenth aspect, an embodiment of the present disclosure provides a computer program, which, when executed on a computer, enables the computer to execute the positioning method described in the optional implementation of the first aspect or the second aspect.

[0109] It is understandable that the first node, the second node, the communication device, the communication system, the storage medium, the program product, and the computer program are all used to perform the method provided by the embodiments of the present disclosure. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects of the corresponding method and will not be repeated here.

[0110] The present disclosure provides a positioning method and apparatus, a communication device, a communication system, a storage medium, and a program product. In some embodiments, the terms positioning method, information processing method, and data processing method are interchangeable, and the terms communication system and information processing system are interchangeable.

[0111] The embodiments of the present disclosure are not exhaustive and are merely illustrative of some embodiments, and are not intended to be a specific limitation on the scope of protection of the present disclosure. In the absence of contradiction, each step in a certain 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 certain embodiment can also be implemented as an independent embodiment, and the order of the steps in a certain embodiment can be arbitrarily exchanged. In addition, the optional implementation methods in a certain embodiment can be arbitrarily combined; in addition, the embodiments can be arbitrarily combined. For example, some or all steps of different embodiments can be arbitrarily combined, and a certain embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0112] In each embodiment of the present disclosure, unless otherwise specified or provided for by logic, the terms and / or descriptions between the embodiments are consistent and can be referenced by each other. The technical features in different embodiments can be combined to form a new embodiment based on their inherent logical relationships.

[0113] The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments and are not intended to limit the present disclosure.

[0114] In the embodiments of the present disclosure, unless otherwise specified, elements expressed in the singular, such as "a", "an", "the", "above", "said", "the", "the", etc., may mean "one and only one", or "one or more", "at least one", etc. For example, when using articles such as "a", "an", "the" in English in translation, the noun following the article may be understood as a singular expression or a plural expression.

[0115] In the embodiments of the present disclosure, “plurality” refers to two or more.

[0116] In some embodiments, the terms "at least one," "one or more," "a plurality of," "multiple," etc. may be used interchangeably.

[0117] In some embodiments, descriptions such as "at least one of A and B," "A and / or B," "in one case A, in another case B," or "in one case A, in another case B" may include the following technical solutions depending on the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed); and in some embodiments, A and B (both A and B are executed). The same applies when there are more branches such as A, B, and C.

[0118] In some embodiments, "A or B" and other descriptions may include the following technical solutions depending on the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed). The above is also applicable when there are more branches such as A, B, C, etc.

[0119] The prefixes such as "first" and "second" in the embodiments of the present disclosure are only used to distinguish different description objects and do not constitute any restriction on the position, order, priority, quantity or content of the description objects. For the statement of the description object, please refer to the description in the context of the claims or embodiments, and no unnecessary restriction should be constituted due to the use of prefixes. For example, if the description object is a "field", the ordinal number before the "field" in the "first field" and the "second field" does not limit the position or order between the "fields". "First" and "second" do not limit whether the "fields" they modify are in the same message, nor do they limit the order of the "first field" and the "second field". For another example, if the description object is a "level", the ordinal number before the "level" in the "first level" and the "second level" does not limit the priority between the "levels". For another example, the number of description objects is not limited by the ordinal number and can be one or more. Taking "first device" as an example, the number of "devices" can be one or more. In addition, the objects modified by different prefixes can be the same or different. For example, if the description object is "device", then the "first device" and the "second device" can be the same device or different devices, and their types can be the same or different; for another example, if the description object is "information", then the "first information" and the "second information" can be the same information or different information, and their contents can be the same or different.

[0120] In some embodiments, “including A,” “comprising A,” “used to indicate A,” and “carrying A” can be interpreted as directly carrying A or indirectly indicating A.

[0121] In some embodiments, terms such as "...", "determine...", "in the case of...", "at the time of...", "when...", "if...", "if...", etc. can be used interchangeably.

[0122] In some embodiments, terms such as "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 less than", and "above" can be replaced with each other, and terms such as "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" can be replaced with each other.

[0123] In some embodiments, devices, etc. can be interpreted as physical or virtual, and their names are not limited to the names recorded in the embodiments. Terms such as "device", "equipment", "device", "circuit", "network element", "node", "function", "unit", "section", "system", "network", "chip", "chip system", "entity", and "subject" can be used interchangeably.

[0124] In some embodiments, "network" can be interpreted as devices included in the network (eg, access network equipment, core network equipment, etc.).

[0125] 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", "bandwidth part (BWP)" and the like may be used interchangeably.

[0126] 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, client, etc. can be used interchangeably.

[0127] In some embodiments, the access network device, the core network device, or the network device can be replaced by a terminal. For example, the various embodiments of the present disclosure can also be applied to a structure in which the communication between the access network device, the core network device, or the network device and the terminal is replaced by communication between multiple terminals (for example, device-to-device (D2D), vehicle-to-everything (V2X), etc.). In this case, it is also possible to set the structure in which the terminal has all or part of the functions of the access network device. In addition, terms such as "uplink" and "downlink" can also be replaced by terms corresponding to communication between terminals (for example, "side"). For example, uplink channels, downlink channels, etc. can be replaced by side channels, and uplinks, downlinks, etc. can be replaced by side links.

[0128] 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, the core network device, or the network device may have a structure that has all or part of the functions of the terminal.

[0129] In some embodiments, obtaining data, information, etc. may comply with the laws and regulations of the country where the data is obtained.

[0130] In some embodiments, data, information, etc. may be obtained with the user's consent.

[0131] In addition, each element, each row, or each column in the table of the embodiment of the present disclosure can be implemented as an independent embodiment, and the combination of any elements, any rows, and any columns can also be implemented as an independent embodiment.

[0132] FIG1A is a schematic diagram showing the architecture of a communication system according to an exemplary embodiment.

[0133] As shown in FIG. 1A , a communication system 100 includes a first node 101 and a second node 102 .

[0134] In some embodiments, the first node 101 may include: a terminal 1011 or an access network device 1012 .

[0135] In some embodiments, the terminal 1011 includes, for example, a mobile phone, a wearable device, an Internet of Things device, a car with communication function, a smart car, a tablet computer, a computer with wireless transceiver function, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal device in industrial control, a wireless terminal device in self-driving, a wireless terminal device in remote medical surgery, a wireless terminal device in a smart grid, a wireless terminal device in transportation safety, a wireless terminal device in a smart city, and at least one of a wireless terminal device in a smart home, but is not limited thereto.

[0136] In some embodiments, the access network device 1012 can be, for example, a node or device that accesses the terminal to a wireless network. The access network device may include an evolved NodeB (eNB), a next generation evolved NodeB (ng-eNB), a next generation NodeB (gNB), a node B (NB), a home node B (HNB), a home evolved nodeB (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 base station (Open RAN), a cloud base station (Cloud RAN), a base station in other communication systems, and at least one of an access node in a Wi-Fi system, but is not limited thereto.

[0137] In some embodiments, the technical solution of the present disclosure can be applied to the Open RAN architecture. In this case, the interfaces between or within the access network devices involved in the embodiments of the present disclosure can be transformed into internal interfaces of the Open RAN, and the processes and information interactions between these internal interfaces can be implemented through software or programs.

[0138] In some embodiments, the access network device can be composed of a centralized unit (CU) and a distributed unit (DU), where the CU can also be called a control unit. The CU-DU structure can be used to split the protocol layer of the access network device, with the functions of some protocol layers centrally controlled by the CU, and the functions of the remaining part or all of the protocol layers distributed in the DU, which is centrally controlled by the CU, but is not limited to this.

[0139] In some embodiments, the second node 102 may be a core network device 1021 .

[0140] In some embodiments, the core network device 1021 may be a single device, including the first network element 1021a, or may be multiple devices or a group of devices, each including the first network element 1021a. The network element may be virtual or physical. The core network may include, for example, at least one of an Evolved Packet Core (EPC), a 5G Core Network (5GCN), and a Next Generation Core (NGC).

[0141] In some embodiments, the first network element 1021a is, for example, a location management function (LMF).

[0142] It can be understood that the communication system described in the embodiment of the present disclosure is for the purpose of more clearly illustrating the technical solution of the embodiment of the present disclosure, and does not constitute a limitation on the technical solution provided by the embodiment of the present disclosure. Ordinary technicians in this field can know that with the evolution of the system architecture and the emergence of new business scenarios, the technical solution provided by the embodiment of the present disclosure is also applicable to similar technical problems.

[0143] The following embodiments of the present disclosure may be applied to the communication system 100 shown in FIG1A , or a portion thereof, but are not limited thereto. The entities shown in FIG1A are illustrative only. The communication system may include all or part of the entities shown in FIG1A , or may include other entities other than those shown in FIG1A . The number and form of the entities may be arbitrary. The connection relationship between the entities is illustrative only. The entities may be connected or disconnected, and the connection may be in any manner, including direct or indirect, wired or wireless.

[0144] The embodiments of the present disclosure 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 (registered trademark)), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.20, Ultra-WideBand (UWB), Bluetooth (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 utilizing other communication methods, and next-generation systems based on and extending these methods. Furthermore, multiple systems may be combined (for example, a combination of LTE or LTE-A with 5G).

[0145] In recent years, high-precision positioning technology has become a hot research topic to meet the demand for location-based services in various commercial service scenarios and industrial IoT scenarios. It facilitates services such as indoor navigation, augmented and virtual reality, and autonomous driving. Implementing high-precision positioning services based on existing wireless communication network infrastructure is a key area of ​​mobile communication technology research and a key component of wireless communication standardization research throughout history.

[0146] In some embodiments, high-precision positioning is achieved in indoor and outdoor scenarios by introducing multiple positioning methods such as time measurement and angle measurement. With the increasing demand for related business services, 3GPP has launched a project to enhance positioning accuracy for commercial scenarios and Industrial Internet of Things (IIOT) scenarios, with the goal of achieving high-precision positioning at the decimeter level, and is committed to meeting the high-precision location service needs of the consumer and enterprise markets. However, some classic positioning algorithms, such as TDOA and Multi-RTT algorithms specified in the 3GPP standard, are difficult to meet the very strict positioning accuracy requirements in scenarios such as IIOT, which in turn affects related business services.

[0147] With the continuous development of artificial intelligence technology in recent years, AI-based solutions have been widely used in the field of wireless communications. Deep neural network models are capable of effectively performing complex data processing and feature modeling processes and are now being applied to solve many key problems in wireless communications. AI-based target positioning is a key application case of artificial intelligence technology in the communications field and a major research direction for 3GPP standardization. Existing technical solutions can use deep neural network models to model the mapping relationship between channel measurement data and target location coordinates, achieving higher positioning accuracy than traditional positioning methods.

[0148] In some embodiments, the research on high-precision positioning technology based on AI mainly considers two specific implementation methods, including direct positioning based on an AI model and indirect positioning assisted by an AI model. As shown in Figures 1B and 1C. Figure 1B is a flow chart of a positioning method based on an AI model according to an exemplary embodiment; Figure 1C is a flow chart of another positioning method based on an AI model according to an exemplary embodiment.

[0149] Exemplarily, direct positioning based on the AI ​​model, that is, the input of the AI ​​model is the channel measurement data used for positioning, and the output is the positioning result, that is, the terminal location coordinates.

[0150] Indirect positioning based on an AI model: The AI ​​model takes as input the channel measurement data used for positioning and outputs intermediate positioning parameters, which can include parameters such as time of arrival (ToA) and azimuth angles of arrival (AoA). Based on these intermediate positioning parameters, the terminal's position coordinates, or positioning results, can be calculated using traditional positioning methods.

[0151] In the direct positioning and indirect positioning methods based on the AI ​​model, the input of the AI ​​model is the channel measurement data used for positioning, which can usually be the channel impulse response (CIR) calculated based on the positioning reference signal. Specifically, the terminal can calculate the downlink CIR based on the positioning reference signal (PRS) sent by the access network device. The access network device can also calculate the uplink CIR based on the sounding reference signal (SRS-Pos) sent by the terminal for positioning.

[0152] In some embodiments, depending on the specific device used to implement positioning, the high-precision positioning technology based on the AI ​​model can be divided into five modes, as shown in Figure 1D. Figure 1D is a schematic diagram of the application mode of positioning technology based on the AI ​​model according to an exemplary embodiment.

[0153] Mode 1: Direct or indirect positioning on the terminal side. The terminal calculates channel measurement data used for positioning, such as CIR, based on the PRS sent by the access network device. This data is then input into an AI model to directly obtain the terminal's location coordinates. Alternatively, the UE inputs the channel measurement data used for positioning into an AI model to obtain intermediate positioning parameters such as ToA or AoA. Traditional positioning methods are then used to obtain the terminal's location coordinates. After obtaining the positioning results (i.e., location coordinates), the terminal reports them to the LMF.

[0154] Mode 2: Terminal-assisted indirect positioning on the LMF side. The terminal calculates channel measurement data used for positioning, such as CIR, based on the PRS sent by the access network device. This channel measurement data is then fed into the AI ​​model to obtain intermediate positioning parameters, such as ToA or AoA. These intermediate positioning parameters are then reported to the LMF, which then uses traditional positioning methods to obtain the terminal's location coordinates.

[0155] Mode 3: Terminal-assisted direct positioning on the LMF side. The terminal calculates channel measurement data used for positioning, such as CIR, based on the PRS sent by the access network device and reports the channel measurement data used for positioning to the LMF. The LMF inputs the received channel measurement data into the AI ​​model to obtain the terminal's location coordinates.

[0156] Mode 4: Indirect positioning on the LMF side assisted by access network equipment. The access network equipment calculates channel measurement data for positioning, such as CIR, based on the SRS-Pos sent by the UE. The channel measurement data is input into the AI ​​model to obtain intermediate positioning parameters, such as ToA or AoA. These intermediate positioning parameters are then reported to the LMF, which then uses traditional positioning methods to obtain the terminal's location coordinates.

[0157] Mode 5: Direct positioning on the LMF side assisted by access network equipment. The access network equipment calculates channel measurement data for positioning, such as CIR, based on the SRS-Pos sent by the UE and reports the channel measurement data used for positioning to the LMF. The LMF inputs the received channel measurement data into the AI ​​model to obtain the terminal location coordinates.

[0158] In the five modes described above, data acquisition and model inference may be implemented on different devices. For modes 1, 2, and 4, the channel measurement data required for the AI ​​model input is obtained by the terminal or access network device based on positioning reference signal measurements. The AI ​​model is also deployed on the terminal or access network device. Therefore, the terminal or access network device can directly input its acquired channel measurement data into the AI ​​model to obtain positioning results, without involving the reporting and transmission of the channel measurement data used for positioning.

[0159] For Mode 3 and Mode 5, the channel measurement data used for AI positioning must first be calculated and obtained by the terminal or access network equipment based on the positioning reference signal, then reported to the LMF, input into the AI ​​positioning model and obtain the positioning result, namely the terminal position coordinates.

[0160] FIG2A is an interactive diagram illustrating a positioning method according to an exemplary embodiment. As shown in FIG2A , the present disclosure embodiment relates to a positioning method for a communication system 100, the method comprising:

[0161] Step S2101: The third node sends a positioning reference signal to the first node.

[0162] In some embodiments, the first node may be a channel data measurement node, and the third node may be a reference signal sending node.

[0163] In some embodiments, the first node may be a terminal or an access network device; the third node may be an access network device or a terminal.

[0164] For example, in modes 1 to 3 shown in Figure 1D, the first node may be a terminal and the third node may be an access network device. In modes 4 and 5, the first node may be an access network device and the third node may be a terminal.

[0165] In some embodiments, the positioning reference signal is a reference signal sent by the third node to the first node for positioning.

[0166] In some embodiments, the positioning reference signal may include at least one of the following:

[0167] Downlink positioning reference signal PRS;

[0168] Uplink sounding reference signal SRS-Pos used for positioning.

[0169] For example, in modes 1, 2, and 3, the access network device as the third node may send a PRS to the terminal as the first node. For another example, in modes 4 and 5, the terminal as the third node may send an SRS-Pos to the access network device as the first node.

[0170] In some embodiments, the positioning reference signal may be other reference signals used for positioning, which is not limited in the embodiments of the present disclosure.

[0171] Step S2102: The first node obtains measurement data of N time domain sampling points.

[0172] In some embodiments, the first node may measure the positioning reference signal sent by the third node to obtain measurement data.

[0173] In some embodiments, the measurement data is measurement data obtained by the first node at N time domain sampling points; where N is a positive integer.

[0174] It is worth noting that due to the presence of multiple propagation paths in the channel, the signal received by the first node within a sampling time may be the superposition of multiple pulse signals propagated via different propagation paths. The measurement data of the embodiment of the present disclosure is obtained by the first node measuring the superimposed pulse signal propagated through multiple paths in the dimension of the time domain sampling point. It is understandable that the measurement data measured by the first node at a time domain sampling point is obtained by the first node measuring multiple pulse signals propagated along multiple propagation paths within the sampling time corresponding to the time domain sampling point.

[0175] In some embodiments, the measurement data may include first power data and delay data; wherein the first power data indicates the measured power of the positioning reference signal; and the delay data indicates the measurement timing of the first power data.

[0176] In some embodiments, the first power data may indicate a maximum measured power obtained by measuring positioning reference signals transmitted through multiple different channel propagation paths at a time domain sampling point.

[0177] In some embodiments, the time delay data may include numbers of time domain sampling points.

[0178] In some embodiments, the measurement data may be a channel impulse response (CIR), a power delay profile (PDP) and / or a delay profile (DP).

[0179] In some embodiments, the CIR data may be used to indicate the power, delay, and phase of the positioning reference signal measured by the first node in the time domain sampling point dimension.

[0180] It should be noted that CIR data can have multiple time-domain sampling points. The time-domain sampling point dimension of CIR refers to the number of sampling points within a symbol duration T. If the number of sampling points is set to m, the time-domain sampling point dimension ranges from 1 to m. The time interval between two adjacent sampling points is T / m.

[0181] For example, within the duration of a symbol, the signal waveform of the positioning reference signal received by the first node may be a superposition of multiple signal waveforms propagated via multipath. Multiple time domain sampling points may be set within the duration of a symbol, and the data at each time domain sampling point includes amplitude and delay, i.e., first power data and delay data corresponding to each time domain sampling point in the measurement data.

[0182] In some embodiments, CIR data can indicate the impact on the signal during channel propagation, and reflect the changes that occur to the signal after it propagates through the channel, including the attenuation of the energy of the pulse signal caused by path loss and shadow fading, and the superposition of multiple different pulse signals received successively at the receiving end due to the existence of multiple propagation paths in the channel.

[0183] In some embodiments, the CIR data is a complex matrix whose dimension is mainly related to the number of positioning reference signal sending nodes TRP and the number of time domain sampling points. The CIR data of each TRP is a complex number at multiple time domain sampling points, containing three parts of information: power, phase and delay.

[0184] It is worth noting that the first node can use the complete CIR data as input to the positioning model. Although this method can achieve higher positioning accuracy, it has a high data reporting overhead.

[0185] In some embodiments, the PDP data may be used to indicate the power and delay of the positioning reference signal measured by the first node in the time domain sampling point dimension.

[0186] It should be noted that the PDP data retains the power and delay information of the CIR data. The dimension of the PDP data is related to the number of positioning reference signal sending nodes TRP and the number of time domain sampling points.

[0187] It's worth noting that compared to CIR data, PDP data has a lower dimension. Reporting PDP data as input to the positioning model can reduce data reporting overhead. However, when using PDP data as input to the positioning model, the first node needs to report the first power data for each time domain sampling point. This first power data is typically a floating-point number, requiring more bits to transmit, resulting in still high data reporting overhead.

[0188] In some embodiments, the DP data may be used to indicate a delay of a positioning reference signal measured by the first node in a time domain sampling point dimension.

[0189] It should be noted that the DP data retains the delay information of the CIR data. The dimension of the DP data is valid with the number of positioning reference signal sending nodes TRP and the number of time domain sampling points that retain the delay information.

[0190] It is worth noting that, compared with CIR data and PDP data, reporting DP data as the input of the positioning model can significantly reduce data reporting overhead, but it is difficult to achieve high positioning accuracy.

[0191] Step S2103: The first node selects measurement data of n time-domain sampling points that meet the first condition.

[0192] In some embodiments, the first node selects measurement data of n time domain sampling points that meet a first condition based on measurement data of N time domain sampling points; wherein N is greater than or equal to n.

[0193] In some embodiments, the measurement data of the n time-domain sampling points may be measurement data that meets the first condition among the measurement data of the N time-domain sampling points.

[0194] It should be noted that the measurement data of the n time-domain sampling points that meet the first condition is the measurement data selected by the first node for input into the positioning model. It is understood that selecting n measurement data that meet the first condition from the measurement data of N time-domain sampling points for positioning can reduce data reporting overhead of the communication system.

[0195] In some embodiments, the number n of selected measurement data meeting the first condition may be determined according to a protocol.

[0196] In some embodiments, the measurement data of the n time-domain sampling points that meet the first condition may be measurement data in which the first power data is greater than or equal to a preset power threshold.

[0197] In some embodiments, the measurement data of the n time-domain sampling points that meet the first condition are the measurement data of the n time-domain sampling points with the largest first power data.

[0198] It should be noted that, taking CIR data as an example, while complete CIR data has a high dimensionality, the data itself exhibits certain distribution characteristics. For example, in the time domain sampling point dimension, the power data in the CIR data at most time domain sampling points is close to 0 or below the preset power threshold. Only a small number of time domain sampling points have higher power data in the CIR data, indicating the propagation path information of the higher-power signal received by the receiver. These time domain sampling points are typically located at the front end. Generally, the data with higher values ​​in the CIR data plays a more important role in positioning.

[0199] Taking PDP data as an example, PDP data includes power and delay data at each time-domain sampling point. Delay data and power data at delay sampling points with high power data have a greater impact on positioning. Therefore, this data, namely the delay and power data at delay sampling points with high power data, can be used as input for the positioning model.

[0200] In some embodiments, the measurement data of N time domain sampling points can be sorted from large to small according to the first power data to obtain a sorting result; based on the sorting result, the first n measurement data in the sorting result are selected as the measurement data of the n time domain sampling points that meet the first condition.

[0201] Step S2104: The first node sends first information to the second node.

[0202] In some embodiments, the second node may be a core network device or a location management function LMF.

[0203] In some embodiments, the second node receives the first information sent by the first node.

[0204] In some embodiments, the first information is used by the second node to determine positioning information.

[0205] In some embodiments, the first information includes measurement data of n time domain sampling points measured by the first node.

[0206] It should be noted that the measurement data of the n time domain sampling points can be used by the second node to perform positioning model inference. The second node can perform model inference based on the measurement data of the n time domain sampling points, rather than all N measurement data, to assist the second node in determining positioning information.

[0207] In this way, the first node selects measurement data of n time domain sampling points that meet the first condition from the measurement data of N time domain sampling points and reports them for positioning, which can reduce the data reporting overhead of the communication system and the complexity of the positioning model.

[0208] In some embodiments, the first information includes delay data of measurement data of n time domain sampling points measured by the first node; the delay data of the n measurement data are sorted in the first information according to the size of the first power data of the n measurement data.

[0209] It should be noted that to further reduce data reporting overhead, the first node can report the delay data from the measurement data of n time-domain sampling points. To ensure a certain level of positioning accuracy, the delay data of the n measurement data in the first information reported by the first node are sorted by the magnitude of the first power data of the n measurement data. This allows the second node to estimate the first power data corresponding to the n delay data based on the order of the n delay data in the first information; the second node can then perform positioning model inference based on the n delay data and the estimated first power data corresponding to the n delay data.

[0210] In some embodiments, the n delay data in the first information are arranged in ascending order according to the first power data.

[0211] In some embodiments, the n delay data in the first information are arranged in descending order according to the first power data.

[0212] In some embodiments, the ordering of the delay data carried by the first information is determined by a protocol.

[0213] In some embodiments, the first information may include n arrays; one array is used to carry delay data in the measurement data of one time domain sampling point.

[0214] It is worth noting that the n arrays in the first information are one-dimensional arrays.

[0215] In some embodiments, an array may include one or more bits, and the value of one bit or multiple bits may indicate the delay data in the measurement data of the corresponding time-domain sampling point.

[0216] In some embodiments, the i-th array is used to carry delay data measured at the i-th time domain sampling point in the first sorting result or the second sorting result.

[0217] The first sorting result is a result of sorting the first power data measured at N time domain sampling points from large to small; the second sorting result is a result of sorting the first power data measured at N time domain sampling points from small to large.

[0218] In some embodiments, the first information may include a two-dimensional array of n rows, where each row of elements in the two-dimensional array is used to carry delay data in the measurement data of a time-domain sampling point.

[0219] In some embodiments, the first information includes n bit vectors; one bit vector is used to carry delay data in the measurement data of one time domain sampling point.

[0220] In some embodiments, the vector length of the bit vector may be determined by N.

[0221] In some embodiments, the vector length of the bit vector may be log2N.

[0222] In some embodiments, the i-th bit vector in the n bit vectors is used to indicate delay data measured at the i-th time domain sampling point in the first sorting result or the second sorting result.

[0223] The first sorting result is a result of sorting the first power data measured at N time domain sampling points from large to small; the second sorting result is a result of sorting the first power data measured at N time domain sampling points from small to large.

[0224] Exemplarily, the i-th bit vector represents the number of the time-domain sampling point where the i-th first power data is the largest.

[0225] Step S2105: The second node sets second power data of the measurement data of n time domain sampling points.

[0226] In some embodiments, the second node sets second power data of the measurement data of n time domain sampling points according to the first information.

[0227] In some embodiments, the second node sets the second power data of the measurement data of the n time domain sampling points according to the order of the delay data of the measurement data of the n time domain sampling points in the first information.

[0228] For example, if the delay data carried in the first information is sorted in descending order, the second node may set a larger second power data for the time-domain sampling point corresponding to the delay data based on the delay data's sequence number in the first information. A smaller sequence number indicates a larger first power data corresponding to the delay data.

[0229] In some embodiments, the second power data may be an estimate of the first power data.

[0230] In some embodiments, the second power data may be quantized power data.

[0231] It is worth noting that the order of the second power data of the measurement data of the n time domain sampling points is the same as the order of the first power data of the measurement data of the n time domain sampling points.

[0232] In some embodiments, the second node may set the second power data corresponding to the delay data indicated by the bit vector according to the order of the bit vectors in the first information.

[0233] In some embodiments, the amplitude of the time domain sampling point position indicated by the i-th bit vector is set to ni; or, the amplitude of the time domain sampling point position indicated by the i-th bit vector is set to i.

[0234] It can be understood that when the delay data carried by the first information is arranged in descending order according to the first power data, the second node can set the amplitude of the time domain sampling point position indicated by the i-th bit vector in the first information to ni, that is, set the second power data of the time domain sampling point indicated by the i-th bit vector to ni.

[0235] When the delay data carried by the first information is arranged in ascending order according to the first power data, the second node may set the amplitude of the time domain sampling point position indicated by the i-th bit vector in the first information to i, that is, set the second power data of the time domain sampling point indicated by the i-th bit vector to i.

[0236] In some embodiments, the second node may set the power value of the power intensity level corresponding to the sorting result to the second power data corresponding to the delay data indicated by the bit vector according to the sorting result of the bit vector in the first information.

[0237] It is understandable that the second node may be pre-set with multiple power values, and different power values ​​have different power intensity levels.

[0238] In some embodiments, the second node determines the time domain sampling point position corresponding to the i-th bit vector according to the bit value of the i-th bit vector among the n bit vectors.

[0239] In some embodiments, the bit value of the bit vector is used to indicate the number of the corresponding time-domain sampling point.

[0240] It should be noted that the n measurement data are obtained by the first node at n time domain sampling points, and each time domain sampling point corresponds to one measurement data; the number of the time domain sampling point corresponding to the measurement data can indicate the measurement timing of the first power data measured at the time domain sampling point, so the bit value of the bit vector corresponding to the time domain sampling point can be set according to the number of the time domain sampling point, thereby shortening the vector length of the bit vector.

[0241] Step S2106: The second node determines the positioning information.

[0242] In some embodiments, the second node determines positioning information based on the n second power data.

[0243] In some embodiments, the second node processes the n second power data using a positioning model to obtain positioning information output by the positioning model.

[0244] Here, the positioning model may be an AI positioning model pre-trained based on training data corresponding to n second power data.

[0245] In some embodiments, the positioning model can be used for direct positioning, directly outputting positioning results based on input data.

[0246] After obtaining the second power data of the measurement data of n time domain sampling points, the second node may input the second power data of the n time domain sampling points into a pre-trained positioning model to obtain positioning information output by the positioning model.

[0247] In some embodiments, the positioning model configured by the second node includes: a first model and / or a second model;

[0248] Among them, the first model is an AI positioning model trained based on training data corresponding to N first power data; the second model is an AI positioning model trained based on training data corresponding to n second power data.

[0249] It should be noted that the initial model can be trained in advance using the training data corresponding to the first power data or the training data corresponding to the second power data to obtain the first model or the second model; by configuring the first model and / or the second model in the second node, the second node can use the first model and / or the second model to process the measurement data reported by the first node, and obtain the positioning results output by the first model and / or the second model to achieve positioning.

[0250] When the measurement data reported by the first node to the second node includes first power data and delay data, the second node may process the N first power data reported by the first node through the first model to obtain positioning information output by the first model.

[0251] In a case where the measurement data reported by the first node to the second node includes delay data, the second node processes the n second power data using the second model to obtain positioning information output by the second model.

[0252] In this way, the second node can set the second power data of the measurement data of n time domain sampling points based on the sorting of the delay data of the measurement data of n time domain sampling points in the first information. On the one hand, the second power data of the measurement data of n time domain sampling points is used as the input of the positioning model to achieve positioning and ensure positioning accuracy; on the other hand, the first node effectively reduces the data reporting overhead by reporting the delay data of the measurement data of n time domain sampling points.

[0253] In some embodiments, the term "information" can be interchangeable with terms such as "message", "signal", "signaling", "report", "configuration", "indication", "instruction", "command", "channel", "parameter", "field", and "data".

[0254] In some embodiments, the term "send" can be interchangeable with terms such as "transmit", "report", and "transmit".

[0255] The positioning method involved in the embodiments of the present disclosure may include at least one of steps S2101 to S2106. For example, step S2101 combined with step S2102 may be implemented as an independent embodiment, and step S2101 combined with step S2102, step S2104, and step S2106 may be implemented as an independent embodiment, but the present invention is not limited thereto.

[0256] In some embodiments, steps S2103, S2104, and S2105 are optional, and one or more of these steps may be omitted or replaced in different embodiments. It is understood that when the first node is configured with a positioning model, the first node may input the measurement data of the N time-domain sampling points acquired into the positioning model to achieve positioning, without the first node having to report the measurement data to the second node.

[0257] In some embodiments, steps S2103 and S2105 are optional, and one or more of these steps may be omitted or replaced in different embodiments. It is understood that when the first node sends measurement data of N time domain sampling points to the second node, the second node may directly determine positioning information based on the first power data of the measurement data without setting the second power data.

[0258] FIG2B is an interactive diagram illustrating a positioning method according to an exemplary embodiment. As shown in FIG2B , the present disclosure embodiment relates to a positioning method for a communication system 100, the method comprising:

[0259] Step S2201: The second node sends second information to the first node.

[0260] In some embodiments, the first node may be a terminal or an access network device. In mode 3 as shown in FIG1D , the first node may be a terminal; in mode 5, the first node may be an access network device. The second node may be a core network device or a location management function (LMF).

[0261] In some embodiments, the second node may be a node for providing positioning services, for example, a Gateway Mobile Location Center (GMLC) entity.

[0262] In some embodiments, the first node receives second information sent by the second node.

[0263] In some embodiments, the second information is used by the first node to determine a reporting type of the measurement data.

[0264] In some embodiments, the reporting type of the measurement data includes at least one of the following:

[0265] The first type, when the first type is adopted, the delay data in the measurement data is sent to the second node;

[0266] The second type: when the second type is adopted, both the delay data and the first power data in the measurement data are sent to the second node.

[0267] It should be noted that when the second information indicates that the measurement data reporting type is the first type, the first node sends the delay data from the measurement data of multiple time-domain sampling points to the second node. It is worth noting that, in this case, to ensure positioning accuracy, the multiple delay data sent by the first node to the second node are sorted by the magnitude of the first power data. This allows the second node to set the second power data for the measurement data of the multiple time-domain sampling points based on the sorting of the received multiple delay data, and to use the multiple second power data for positioning.

[0268] If the second information indicates that the measurement data reporting type is the second type, the first node may send the delay data and first power data from the measurement data at multiple time-domain sampling points to the second node. This allows the second node to perform positioning based on the received multiple first power data. It is worth noting that while this method can ensure higher positioning accuracy, it also incurs a higher data reporting overhead.

[0269] Due to different reporting types of measurement data, the first node performs different data preprocessing and data reporting processes on the measurement data measured at multiple time domain sampling points, and the second node also performs different data post-processing on the measurement data received at multiple time domain sampling points. Therefore, in order to facilitate the first node and the second node to perform matching data preprocessing, data reporting, and data post-processing, thereby achieving positioning; the second node may send second information to the first node so that the first node determines the reporting type of the measurement data based on the second information.

[0270] In some embodiments, the method further comprises:

[0271] The second node obtains a positioning model; and determines second information based on the positioning model.

[0272] In some embodiments, the second node obtains the positioning model, including:

[0273] Obtain input parameter information of the positioning model; the input parameter information includes at least one of the following:

[0274] Input parameter type;

[0275] The number of input parameters.

[0276] In some embodiments, the reporting type indicated by the second information is determined by an input parameter of a positioning model.

[0277] In some embodiments, the second node is configured with a first model, and the second information sent by the second node to the first node indicates that the reporting type of the measurement data is the first type;

[0278] The second model configured by the second node, the second information sent by the second node to the first node indicates that the reporting type of the measurement data is the second type.

[0279] The input parameter of the first model is the second power data; the input parameter of the second model is the first power data.

[0280] It is understandable that the first model can be obtained by training based on the training data corresponding to the second power data. The second model can be obtained by training based on the training data corresponding to the first power data.

[0281] In some embodiments, the second information is further used to indicate at least one of the following:

[0282] The number n of delay data carried in the first information;

[0283] The delay data carried by the first information is arranged in ascending or descending order according to the first power data.

[0284] It should be noted that the number n of delay data carried in the first information and / or the sorting method of the n delay data in the first information are determined by the second node. The second node informs the first node of the above information through the second information, and the first node performs data preprocessing and reporting on the n measurement data according to the second information, so that the second node can also perform matching data post-processing on the delay data of the received n measurement data, so that the measurement data reported by the first node can be correctly obtained by the second node to achieve positioning.

[0285] Step S2202: The third node sends a positioning reference signal.

[0286] In some embodiments, optional implementations of step S2202 can refer to the optional implementation of step S2101 in Figure 2A and other related parts of the embodiment involved in Figure 2A, which will not be repeated here.

[0287] Step S2203: The first node obtains measurement data obtained by measuring N time domain sampling points.

[0288] In some embodiments, optional implementations of step S2203 can refer to the optional implementation of step S2102 in FIG. 2A and other related parts of the embodiment involved in FIG. 2A , which will not be repeated here.

[0289] Step S2204: The first node selects measurement data of n time-domain sampling points that meet the first condition.

[0290] In some embodiments, optional implementations of step S2204 can refer to the optional implementation of step S2103 in FIG. 2A and other related parts of the embodiment involved in FIG. 2A , which will not be repeated here.

[0291] Step S2205: The first node sends first information to the second node.

[0292] In some embodiments, optional implementations of step S2205 can refer to the optional implementation of step S2104 in FIG. 2A and other related parts of the embodiment involved in FIG. 2A , which will not be repeated here.

[0293] Step S2206: The second node sets second power data of the measurement data of n time domain sampling points.

[0294] In some embodiments, optional implementations of step S2206 can refer to the optional implementation of step S2105 in FIG2A and other related parts of the embodiment involved in FIG2A , which will not be repeated here.

[0295] Step S2207: The second node determines the positioning information.

[0296] In some embodiments, optional implementations of step S2207 can refer to the optional implementation of step S2106 in FIG2A and other related parts of the embodiment involved in FIG2A , which will not be repeated here.

[0297] The positioning method involved in the embodiments of the present disclosure may include at least one of steps S2201 to S2207. For example, steps S2202 to S2206 may be implemented as independent embodiments, step S2202 combined with step S2203 may be implemented as an independent embodiment, and step S2202 combined with step S2203, step S2205, and step S2207 may be implemented as independent embodiments, but the present disclosure is not limited thereto.

[0298] In some embodiments, step S2201 is optional, and one or more of these steps may be omitted or replaced in different embodiments. It is understood that the first node may determine the reporting type of the measurement data according to the protocol agreement, without requiring the second node to send the second information to the first node.

[0299] In some embodiments, steps S2201, S2204, S2203, and S2206 are optional, and one or more of these steps may be omitted or replaced in different embodiments. It is understood that when the first node is configured with a positioning model, the first node may input the acquired measurement data of the N time-domain sampling points into the positioning model to achieve positioning; there is no need for the second node to send the second information, nor is there a need for the first node to report the measurement data to the second node.

[0300] In some embodiments, steps S2201, S2204, and S2206 are optional, and one or more of these steps may be omitted or replaced in different embodiments. It is understood that when the first node sends measurement data of N time domain sampling points to the second node, the second node may directly determine positioning information based on the first power data of the measurement data without setting the second power data.

[0301] FIG3A is a flow chart of a positioning method according to an exemplary embodiment. As shown in FIG3A , the present disclosure embodiment relates to a positioning method, which is executed by a first node and includes:

[0302] Step S3101: Receive a positioning reference signal sent by a third node.

[0303] In some embodiments, optional implementations of step S3101 can refer to the optional implementation of step S2101 in Figure 2A and other related parts of the embodiment involved in Figure 2A, which will not be repeated here.

[0304] Step S3102: Acquire measurement data of N time domain sampling points.

[0305] In some embodiments, optional implementations of step S3102 can refer to the optional implementation of step S2102 in Figure 2A and other related parts of the embodiment involved in Figure 2A, which will not be repeated here.

[0306] Step S3103: Select measurement data of n time-domain sampling points that meet the first condition.

[0307] In some embodiments, optional implementations of step S3103 can refer to the optional implementation of step S2103 in Figure 2A and other related parts of the embodiment involved in Figure 2A, which will not be repeated here.

[0308] Step S3104: Send the first information to the second node.

[0309] In some embodiments, optional implementations of step S3104 can refer to the optional implementation of step S2104 in Figure 2A and other related parts of the embodiment involved in Figure 2A, which will not be repeated here.

[0310] The positioning method involved in the embodiment of the present disclosure may include at least one of steps S3101 to S3104. For example, step S3101 combined with step S3102 may be implemented as an independent embodiment, but is not limited thereto.

[0311] In some embodiments, steps S3103 and S3104 are optional, and one or more of these steps may be omitted or replaced in different embodiments. It is understood that when the first node is configured with a positioning model, the first node may input the measurement data of the N time-domain sampling points acquired into the positioning model to achieve positioning, without the first node having to report the measurement data to the second node.

[0312] FIG3B is a flow chart of a positioning method according to an exemplary embodiment. As shown in FIG3B , the present disclosure embodiment relates to a positioning method, which is executed by a first node and includes:

[0313] Step S3201: Receive second information sent by the second node.

[0314] In some embodiments, optional implementations of step S3201 can refer to the optional implementation of step S2201 in Figure 2B and other related parts of the embodiment involved in Figure 2B, which will not be repeated here.

[0315] Step S3202: Receive a positioning reference signal sent by a third node.

[0316] In some embodiments, optional implementations of step S3202 may refer to the optional implementations of step S2101 in FIG. 2A and other related parts of the embodiment involved in FIG. 2A , which will not be described in detail here.

[0317] Step S3203: Acquire measurement data of N time domain sampling points.

[0318] In some embodiments, optional implementations of step S3203 can refer to the optional implementation of step S2102 in Figure 2A and other related parts of the embodiment involved in Figure 2A, which will not be repeated here.

[0319] Step S3204: Select measurement data of n time-domain sampling points that meet the first condition.

[0320] In some embodiments, optional implementations of step S3204 can refer to the optional implementation of step S2103 in FIG. 2A and other related parts of the embodiment involved in FIG. 2A , which will not be repeated here.

[0321] Step S3205: Send the first information to the second node.

[0322] In some embodiments, optional implementations of step S3205 can refer to the optional implementation of step S2104 in Figure 2A and other related parts of the embodiment involved in Figure 2A, which will not be repeated here.

[0323] The positioning method involved in the embodiment of the present disclosure may include at least one of steps S3201 to S3205. For example, steps S3202 to S3205 may be implemented as independent embodiments, and step S3202 combined with step S3203 may be implemented as independent embodiments, but the present invention is not limited thereto.

[0324] In some embodiments, step S3201 is optional, and one or more of these steps may be omitted or replaced in different embodiments. It is understood that the first node may determine the reporting type of the measurement data according to the protocol agreement, without requiring the second node to send the second information to the first node.

[0325] In some embodiments, steps S3201, S3204, and S3205 are optional, and one or more of these steps may be omitted or replaced in different embodiments. It is understood that when the first node is configured with a positioning model, the first node may input the acquired measurement data of the N time-domain sampling points into the positioning model to achieve positioning; there is no need for the second node to send the second information, nor is there a need for the first node to report the measurement data to the second node.

[0326] FIG3C is a flow chart of a positioning method according to an exemplary embodiment. As shown in FIG3C , the present disclosure embodiment relates to a positioning method, which is performed by a first node and includes:

[0327] Step S3301: Obtain measurement data obtained by the first node measuring the positioning reference signal at n time domain sampling points.

[0328] In some embodiments, the measurement data includes first power data and delay data; the first power data indicates the measured power of the positioning reference signal; the delay data indicates the measurement timing of the first power data; and n is a positive integer.

[0329] Step S3302: Send first information to the second node.

[0330] In some embodiments, the first information is used by the second node to determine positioning information.

[0331] In some embodiments, the first information includes delay data of n measurement data measured by the first node; the delay data of the n measurement data are sorted in the first information according to the size of the first power data of the n measurement data.

[0332] In some embodiments, obtaining measurement data obtained by the first node measuring the positioning reference signal at n time-frequency sampling points includes:

[0333] Obtaining measurement data obtained by the first node at N time domain sampling points; N is greater than or equal to n;

[0334] According to the measurement data of the N time-domain sampling points, the measurement data of n time-domain sampling points that meet the first condition are selected.

[0335] In some embodiments, the measurement data of the n time-domain sampling points that meet the first condition are the measurement data of the n time-domain sampling points with the largest first power data.

[0336] In some embodiments, the first information includes n bit vectors; one bit vector is used to carry delay data in the measurement data of one time domain sampling point.

[0337] In some embodiments, the i-th bit vector in the n bit vectors is used to indicate the delay data measured at the i-th time domain sampling point in the first sorting result or the second sorting result; the first sorting result is the sorting result from large to small of the first power data measured at N time domain sampling points; the second sorting result is the sorting result from small to large of the first power data measured at N time domain sampling points.

[0338] In some embodiments, the time delay data includes numbers of time domain sampling points.

[0339] In some embodiments, the method further comprises:

[0340] Receive second information sent by the second node; the second information is used by the first node to determine a reporting type of the measurement data; the reporting type includes at least one of the following:

[0341] The first type, when the first type is adopted, the delay data in the measurement data is sent to the second node;

[0342] The second type: when the second type is adopted, both the delay data and the first power data in the measurement data are sent to the second node.

[0343] In some embodiments, the second information is further used to indicate one of the following:

[0344] The number n of delay data carried in the first information;

[0345] The delay data carried by the first information is arranged in ascending or descending order according to the first power data.

[0346] FIG4A is a flow chart of a positioning method according to an exemplary embodiment. As shown in FIG4A , the present embodiment relates to a positioning method, which is performed by a second node and includes:

[0347] Step S4101: Receive first information sent by a first node.

[0348] In some embodiments, optional implementations of step S4101 can refer to the optional implementation of step S2104 in Figure 2A and other related parts of the embodiment involved in Figure 2A, which will not be repeated here.

[0349] Step S4102: setting second power data of measurement data of n time domain sampling points.

[0350] In some embodiments, optional implementations of step S4102 can refer to the optional implementation of step S2105 in Figure 2A and other related parts of the embodiment involved in Figure 2A, which will not be repeated here.

[0351] Step S4103: Determine positioning information.

[0352] In some embodiments, optional implementations of step S4103 can refer to the optional implementation of step S2106 in FIG2A and other related parts of the embodiment involved in FIG2A , which will not be repeated here.

[0353] The positioning method involved in the embodiment of the present disclosure may include at least one of steps S4101 to S4103. For example, step S4101 and step S4103 may be implemented as independent embodiments, but are not limited thereto.

[0354] In some embodiments, step S4102 is optional, and one or more of these steps may be omitted or replaced in different embodiments. It is understood that when the first node sends measurement data of N time domain sampling points to the second node, the second node may directly determine positioning information based on the first power data of the measurement data without setting the second power data.

[0355] FIG4B is a flow chart of a positioning method according to an exemplary embodiment. As shown in FIG4B , the present embodiment relates to a positioning method, which is performed by a second node and includes:

[0356] Step S4201: Send second information to the first node.

[0357] In some embodiments, optional implementations of step S4201 can refer to the optional implementation of step S2201 in Figure 2B and other related parts of the embodiment involved in Figure 2B, which will not be repeated here.

[0358] Step S4202: Receive first information sent by the first node.

[0359] In some embodiments, optional implementations of step S4202 can refer to the optional implementation of step S2104 in Figure 2A and other related parts of the embodiment involved in Figure 2A, which will not be repeated here.

[0360] Step S4203: setting second power data of the measurement data of n time domain sampling points.

[0361] In some embodiments, optional implementations of step S4203 can refer to the optional implementation of step S2105 in FIG2A and other related parts of the embodiment involved in FIG2A , which will not be repeated here.

[0362] Step S4204: Determine positioning information.

[0363] In some embodiments, optional implementations of step S4203 can refer to the optional implementation of step S2106 in Figure 2A and other related parts of the embodiment involved in Figure 2A, which will not be repeated here.

[0364] The positioning method involved in the embodiment of the present disclosure may include at least one of steps S4201 to S4204. For example, steps S4202 to S4204 may be implemented as independent embodiments, and steps S4202 and S4204 may be implemented as independent embodiments, but are not limited thereto.

[0365] In some embodiments, step S4201 is optional, and one or more of these steps may be omitted or replaced in different embodiments. It is understood that the first node may determine the reporting type of the measurement data according to the protocol agreement without requiring the second node to send the second information to the first node.

[0366] In some embodiments, steps S4201 and S4203 are optional, and one or more of these steps may be omitted or replaced in different embodiments. It is understood that when the first node sends measurement data of N time domain sampling points to the second node, the second node may directly determine positioning information based on the first power data of the measurement data without setting the second power data.

[0367] FIG4C is a flow chart of a positioning method according to an exemplary embodiment. As shown in FIG4C , the present embodiment relates to a positioning method, which is performed by a second node and includes:

[0368] Step S4301: Receive first information sent by a first node.

[0369] In some embodiments, the first information includes delay data of n measurement data measured by the first node.

[0370] In some embodiments, the delay data of the n measurement data are sorted in the first information according to the size of the first power data of the n measurement data.

[0371] In some embodiments, the n measurement data are obtained by the first node measuring the positioning reference signal at n time domain sampling points, the first power data indicates the measured power of the positioning reference signal; the delay data indicates the measurement timing of the first power data; and n is a positive integer.

[0372] Step S4302: Determine positioning information based on the first information.

[0373] In some embodiments, the first information includes n bit vectors; one bit vector is used to carry delay data in the measurement data of one time domain sampling point.

[0374] In some embodiments, the i-th bit vector in the n bit vectors is used to indicate the delay data measured at the i-th time domain sampling point in the first sorting result or the second sorting result; the first sorting result is the sorting result from large to small of the first power data measured at N time domain sampling points; the second sorting result is the sorting result from small to large of the first power data measured at N time domain sampling points.

[0375] In some embodiments, the time delay data includes numbers of time domain sampling points.

[0376] In some embodiments, the method further comprises:

[0377] According to the sorting of the delay data of the n measurement data in the first information, the second power data of the measurement data of the n time domain sampling points are set; wherein, the size sorting of the second power data of the measurement data of the n time domain sampling points is the same as the size sorting of the first power data of the measurement data of the n time domain sampling points.

[0378] In some embodiments, determining the positioning information based on the first information includes:

[0379] The n second power data are processed by the positioning model to obtain positioning information output by the positioning model.

[0380] In some embodiments, the method further comprises:

[0381] Sending second information to the first node; the second information is used by the first node to determine a reporting type of the measurement data; the reporting type includes at least one of the following:

[0382] The first type, when the first type is adopted, the delay data in the measurement data is sent to the second node;

[0383] The second type: when the second type is adopted, both the delay data and the first power data in the measurement data are sent to the second node.

[0384] In some embodiments, the second information is further used to indicate at least one of the following:

[0385] The number n of delay data carried in the first information;

[0386] The delay data carried by the first information is arranged in ascending or descending order according to the first power data.

[0387] In some embodiments, the method further comprises:

[0388] Get the positioning model;

[0389] Based on the positioning model, second information is determined; the reporting type indicated by the second information is determined by an input parameter of the positioning model.

[0390] FIG5 is an interactive diagram of a positioning method according to an exemplary embodiment. As shown in FIG5 , the present disclosure embodiment relates to a positioning method for a communication system 100, and the method includes one of the following steps:

[0391] Step S5101: The first node obtains measurement data obtained by measuring the positioning reference signal at n time domain sampling points.

[0392] In some embodiments, the measurement data includes first power data and delay data; the first power data indicates the measured power of the positioning reference signal; the delay data indicates the measurement timing of the first power data; and n is a positive integer.

[0393] Step S5102: The first node sends first information to the second node.

[0394] In some embodiments, the first information is used by the second node to determine positioning information, and the first information includes delay data of n measurement data measured by the first node.

[0395] In some embodiments, the delay data of the n measurement data are sorted in the first information according to the size of the first power data of the n measurement data.

[0396] Step S5103: The second node determines positioning information based on the first information.

[0397] In some embodiments, the above method may include the methods of the above-mentioned communication system side, terminal side, access network equipment side, core network equipment side, etc., which will not be repeated here.

[0398] In some embodiments, the application process of the deep learning-based terminal positioning solution includes two parts: model training and model inference. Among them, model training can be understood as using training data to train the initial network model to obtain an AI model. Model inference can be understood as deploying the AI ​​model trained with training data on the terminal, access network equipment or LMF, and then in actual use, the terminal, access network equipment or LMF inputs the channel measurement data used for positioning into the AI ​​model to obtain the positioning results output by the AI ​​model, thereby completing the terminal positioning work in the actual system.

[0399] For application modes 3 and 5 of terminal positioning based on AI models, the channel measurement data used for positioning must first be reported by the terminal or access network equipment to the LMF, and then input into the AI ​​model by the LMF to complete model inference and obtain the positioning result. Although the use of AI models for terminal positioning can achieve high positioning accuracy, the input data required by the AI ​​model, that is, the channel measurement data used for positioning, has a high data reporting overhead, which will occupy too many communication transmission resources, have a significant impact on the operation of the communication system, and is not conducive to promoting the application of AI-based terminal positioning technology in actual communication systems. Therefore, it is necessary to consider the trade-off between the positioning data reporting overhead and positioning accuracy.

[0400] In some embodiments, the channel impulse response (CIR) calculated by the receiver based on the positioning reference signal is typically used as input to the AI ​​model. The CIR represents the effects on the signal during channel propagation and reflects changes in the signal after propagation through the channel, including energy attenuation of the pulse signal caused by path loss and shadow fading.

[0401] Due to the presence of multiple propagation paths in the channel, the receiving end receives a superposition of multiple different pulse signals. CIR data is a complex matrix whose dimensionality is primarily related to the number of reference signal transmitting nodes (TRPs) and the number of time-domain sampling points. The CIR data for each TRP is a complex number at multiple time-domain sampling points, containing information on power, phase, and delay. While using complete CIR data directly as input for AI models can achieve high positioning accuracy, it carries significant data reporting overhead.

[0402] In some embodiments, it is considered to process the CIR data and retain only a portion of the information to obtain power delay profile (PDP) and delay profile (DP) data. These two types of data can also be used as input for the AI ​​model.

[0403] The PDP retains the power and delay information of the CIR data. In some embodiments, the processing method for obtaining the PDP data may be: calculating the modulus of the complex number at each time domain sampling point in the CIR data as the amplitude value of the PDP data at each time domain sampling point.

[0404] The dimensionality of PDP data is related to the number of reference signal transmitting nodes (TRPs) and the number of time-domain sampling points. The PDP data for each TRP is a real number at multiple time-domain sampling points. Compared to CIR, PDP data has a lower dimensionality, reducing data reporting overhead.

[0405] DP only retains the delay information of CIR data. In some embodiments, the processing method for obtaining DP data may be: after obtaining PDP data based on CIR data, retain the delay information of some time domain sampling points with the largest amplitude values ​​in the PDP data.

[0406] The dimension of DP data is related to the number of reference signal sending nodes TRP and the number of time domain sampling points that retain delay information, and the data reporting overhead is further reduced.

[0407] Compared with CIR data, although using PDP and DP data as AI model input can reduce data reporting overhead, it still has some problems.

[0408] For PDP data, since it is necessary to report the power data at each time domain sampling point, where the power data is generally a floating point number and requires more bits to transmit, although the data reporting overhead required for reporting PDP data is lower than that for reporting CIR data, the data reporting overhead for PDP data is still relatively large.

[0409] For DP data, only the time delay information of multiple time domain sampling points needs to be reported. Although the data reporting overhead required for reporting DP data is very small, it is difficult to achieve high positioning accuracy based on DP data.

[0410] In some embodiments, since the terminal or access network device needs to report the channel measurement data used for AI positioning to the LMF, reporting CIR and PDP data can achieve higher positioning accuracy, but the data reporting overhead is large, and it is difficult to achieve higher positioning accuracy by using DP data with smaller data reporting overhead as AI model input.

[0411] An embodiment of the present disclosure proposes a method for acquiring and reporting channel measurement data of quantized power information. First, the channel measurement data obtained based on the positioning reference signal measurement is processed at the channel data measurement node used for positioning (including the terminal and the access network equipment), and then the measurement data reporting method proposed in the embodiment of the present disclosure is used to report the data. The data receiving end, i.e., the AI ​​model inference node (such as LMF), post-processes the received data according to the method proposed in this solution.

[0412] In this way, while ensuring positioning accuracy, the data transmission overhead of channel measurement data used for AI positioning can be significantly reduced, which is conducive to promoting the application of AI-based high-precision positioning technology in actual communication systems.

[0413] In some embodiments, the complete CIR data is high-dimensional, but the data itself exhibits certain distribution characteristics. In the time-domain sampling point dimension, most of the data is close to zero, while a small amount of non-zero data is typically concentrated at the early time-domain sampling points, indicating the propagation path of the higher-power signal received by the receiver.

[0414] Generally speaking, data with larger values ​​in CIR plays a more important role in positioning. According to the method mentioned above, the complex numbers at the time domain sampling points of the CIR data are converted into the corresponding moduli as the amplitude values ​​of the PDP data at each time domain sampling point, that is, the power values ​​of the PDP data at each time domain sampling point. Among them, the delay and power information at the time domain sampling point position with larger power values ​​have a greater impact on achieving target positioning, that is, this part of the data is the more important input data for the AI ​​positioning model. Therefore, the delay information of multiple time domain sampling point positions with the largest power in the PDP data can be selected, that is, only the delay information is reported instead of the power information, thereby greatly reducing the data reporting overhead.

[0415] Since it is difficult to achieve high positioning accuracy when DP data that only retains partial data delay information is used as input data for the AI ​​positioning model, the present disclosure proposes a positioning method that mainly includes three steps: data preprocessing, data reporting, and data post-processing:

[0416] (1) Data preprocessing:

[0417] After the channel data measurement node obtains CIR data based on the reference signal used for positioning, it first obtains PDP data based on the CIR data.

[0418] The PDP data includes power data and delay data at N time domain sampling points. The power data is usually represented more accurately using floating point numbers or other types.

[0419] The channel data measurement node retains the delay data t and corresponding power data p of the n time domain sampling points with the largest power values ​​in the PDP data. n can be determined according to the actual positioning accuracy and data reporting overhead, and N is greater than or equal to n.

[0420] It can be understood that the channel data measurement node can be understood as the first node in the embodiment of the present disclosure; the power data can be understood as the first power data in the embodiment of the present disclosure.

[0421] (2) Data reporting:

[0422] The channel data measurement node sorts the delay data t and power data p of the n time domain sampling points retained according to the power values, and reports the n delay data t in sequence according to the sorting results.

[0423] The method for reporting n delay data t may include:

[0424] Report n bit vectors of length log2 N, where the i-th bit vector represents the time domain sampling point number corresponding to the i-th maximum power value.

[0425] (3) Data post-processing

[0426] After receiving the reported data, the AI ​​model inference node (mainly LMF) performs data post-processing in the order in which the data is received.

[0427] For the received i-th (i=1~n) delay data, the AI ​​model inference node sets the quantized power information a for it i The smaller i is, the larger the power data corresponding to the delay data is. Set a accordingly. i The larger the value.

[0428] It can be understood that the AI ​​model inference node can be understood as the second node of the embodiment of the present disclosure; the quantized power information set by the AI ​​model inference node can be understood as the second power data of the embodiment of the present disclosure.

[0429] In some embodiments, the amplitude at the time domain sampling point corresponding to the received i-th time delay data may be set to ni.

[0430] It is worth noting that the above data post-processing method is to report data in order of power data from large to small. On the contrary, reporting data in order of power from small to large also falls within the protection scope of this method. It is sufficient to change the data reporting and data post-processing methods synchronously.

[0431] As shown in FIG6 , FIG6 is a schematic diagram of an application process of an AI positioning model according to an exemplary embodiment.

[0432] Step S6101: The AI ​​model inference node sends a channel measurement data reporting type indication for positioning to the channel data measurement node.

[0433] It can be understood that the channel measurement data reporting type indication used for positioning can be understood as the second information in the embodiment of the present disclosure.

[0434] The AI ​​model inference node sends a reporting type indication to the channel data measurement node so that the two will perform matching data preprocessing, reporting, and post-processing in subsequent processes and channel measurement data reporting types.

[0435] For example, if the channel measurement data reporting type indication for positioning sent by the AI ​​model inference node to the channel data measurement node is channel measurement data for determining quantized power information, the AI ​​model inference node and the channel data measurement node use the data preprocessing, reporting, and post-processing methods proposed in the present invention to complete related operations.

[0436] Step S6102: The reference signal sending node sends a positioning reference signal to the channel data measurement node.

[0437] It can be understood that the reference signal sending node can be understood as the third node in the embodiment of the present disclosure.

[0438] In mode 3, the reference signal sending node is the access network device, the positioning reference signal is the PRS, and the channel data measurement node is the terminal. In mode 5, the reference signal sending node is the terminal, the positioning reference signal is the SRS-Pos, and the channel data measurement node is the access network device.

[0439] Step S6103: The channel data measurement node obtains channel measurement data.

[0440] The channel data measurement node receives the positioning reference signal and calculates and obtains complete CIR data based on the positioning reference signal.

[0441] Step S6104: The channel data measurement node performs data preprocessing on the channel measurement data.

[0442] The channel data measurement node applies the data preprocessing proposed in the embodiment of the present disclosure to obtain channel measurement data for determining quantized power information.

[0443] Step S6105: The channel data measurement node sends the preprocessed channel measurement data to the AI ​​model inference node.

[0444] The channel data measurement node reports the processed channel measurement data to the AI ​​model inference node.

[0445] Step S6106: The AI ​​model inference node receives the channel measurement data and performs data post-processing on the received channel measurement data.

[0446] Step S6107: The AI ​​model inference node performs positioning model inference based on the processed channel measurement data.

[0447] The AI ​​model inference node inputs the processed data into the AI ​​model and obtains the positioning results output by the AI ​​model, namely the terminal location coordinates.

[0448] The embodiments of the present disclosure are aimed at application scenarios in which positioning is completed based on an AI model, and are directed to an application mode in which the LMF receives channel measurement data reported by a terminal or access network device as input to the AI ​​model to obtain the terminal location coordinates.

[0449] The embodiments of the present disclosure also provide an apparatus for implementing any of the above methods. For example, an apparatus is provided, comprising units or modules for implementing each step performed by a terminal in any of the above methods. For another example, another apparatus is provided, comprising units or modules for implementing each step performed by a network device (e.g., an access network device or a core network device) in any of the above methods.

[0450] It should be understood that the division of the various units or modules in the above devices is merely a division of logical functions. In actual implementation, they may be fully or partially integrated into a physical entity, or they may be physically separated. In addition, the units or modules in the device may be implemented in the form of a processor calling software: for example, the device includes a processor, the processor is connected to a memory, and the memory stores instructions. The processor calls the instructions stored in the memory to implement any of the above methods or implement the functions of the various units or modules of the above devices, wherein the processor is, for example, a general-purpose processor, such as a central processing unit (CPU) or a microprocessor, and the memory is a memory within the device or a memory outside the device. Alternatively, the units or modules in the device can be implemented in the form of hardware circuits, and the functions of some or all of the units or modules can be realized by designing the hardware circuits. The above-mentioned hardware circuits can be understood as one or more processors; for example, in one implementation, the above-mentioned hardware circuit is an application-specific integrated circuit (ASIC), which realizes the functions of some or all of the above units or modules by designing the logical relationship of the components in the circuit; for example, in another implementation, the above-mentioned hardware circuit can be realized by a programmable logic device (PLD). Taking a field programmable gate array (FPGA) as an example, it can include a large number of logic gate circuits, and the connection relationship between the logic gate circuits is configured by configuring the configuration file, thereby realizing the functions of some or all of the above units or modules. All units or modules of the above devices can be realized in the form of software called by the processor, or in the form of hardware circuits, or in part by the form of software called by the processor, and the rest by hardware circuits.

[0451] In the embodiments of the present disclosure, a processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction reading and execution 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 relationship of a hardware circuit. The logical relationship of the above-mentioned hardware circuit is fixed or reconfigurable. For example, the processor is a hardware circuit implemented by 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 to implement the hardware circuit configuration 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. In addition, 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), a deep learning processing unit (DPU), etc.

[0452] FIG7A is a schematic diagram showing the structure of a first node according to an exemplary embodiment. As shown in FIG7A , the first node includes:

[0453] The processing module 7101 is configured to obtain measurement data obtained by the first node measuring the positioning reference signal at n time domain sampling points; the measurement data includes first power data and delay data; the first power data indicates the measured power of the positioning reference signal; the delay data indicates the measurement timing of the first power data; and n is a positive integer.

[0454] The sending module 7102 is configured to send first information to the second node; the first information is used by the second node to determine the positioning information, and the first information includes delay data of n measurement data measured by the first node; the delay data of the n measurement data are sorted in the first information according to the size of the first power data of the n measurement data.

[0455] In some embodiments, the processing module may be used by the first node to execute steps related to information processing in any positioning method.

[0456] In some embodiments, the sending module may be used by the first node to perform steps related to information sending in any positioning method.

[0457] In some embodiments, the first device may further include: a receiving module.

[0458] In some embodiments, the receiving module may correspond to a network interface and / or a transceiver antenna of the first node.

[0459] In some embodiments, the receiving module may be used by the first node to perform steps related to information reception in any positioning method.

[0460] In some embodiments, the processing module is configured to obtain measurement data obtained by the first node at N time domain sampling points; N is greater than or equal to n; and select measurement data of n time domain sampling points that meet the first condition based on the measurement data of the N time domain sampling points.

[0461] In some embodiments, the measurement data of the n time-domain sampling points that meet the first condition are the measurement data of the n time-domain sampling points with the largest first power data.

[0462] In some embodiments, the first information includes n bit vectors; one bit vector is used to carry delay data in the measurement data of one time domain sampling point.

[0463] In some embodiments, the i-th bit vector in the n bit vectors is used to indicate the delay data measured at the i-th time domain sampling point in the first sorting result or the second sorting result; the first sorting result is the sorting result from large to small of the first power data measured at N time domain sampling points; the second sorting result is the sorting result from small to large of the first power data measured at N time domain sampling points.

[0464] In some embodiments, the time delay data includes numbers of time domain sampling points.

[0465] In some embodiments, the receiving module is configured to receive second information sent by the second node; the second information is used by the first node to determine a reporting type of the measurement data; the reporting type includes at least one of the following:

[0466] The first type, when the first type is adopted, the delay data in the measurement data is sent to the second node;

[0467] The second type: when the second type is adopted, both the delay data and the first power data in the measurement data are sent to the second node.

[0468] In some embodiments, the second information is further used to indicate one of the following:

[0469] The number n of delay data carried in the first information;

[0470] The delay data carried by the first information is arranged in ascending or descending order according to the first power data.

[0471] FIG7B is a schematic diagram showing the structure of a second node according to an exemplary embodiment. As shown in FIG7B , the second node includes:

[0472] The receiving module 7201 is configured to receive first information sent by a first node; the first information includes delay data of n measurement data measured by the first node; the delay data of the n measurement data are sorted in the first information according to the magnitude of first power data of the n measurement data; the n measurement data are obtained by the first node measuring a positioning reference signal at n time domain sampling points, the first power data indicates the measured power of the positioning reference signal; the delay data indicates a measurement timing of the first power data; and n is a positive integer.

[0473] The determination module 7202 is configured to determine positioning information according to the first information.

[0474] In some embodiments, the receiving module may correspond to a network interface and / or a transceiver antenna of the second node.

[0475] In some embodiments, the receiving module may be used by the second node to perform steps related to information reception in any positioning method.

[0476] In some embodiments, the determination module may be used by the second node to perform steps related to information determination in any positioning method.

[0477] In some embodiments, the second node further includes: a sending module and a processing module.

[0478] In some embodiments, the sending module may be used by the second node to perform steps related to information sending in any positioning method.

[0479] In some embodiments, the processing module may be used by the second node to execute steps related to information processing in any positioning method.

[0480] In some embodiments, the first information includes n bit vectors; one bit vector is used to carry delay data in the measurement data of one time domain sampling point.

[0481] In some embodiments, the i-th bit vector in the n bit vectors is used to indicate the delay data measured at the i-th time domain sampling point in the first sorting result or the second sorting result; the first sorting result is the sorting result from large to small of the first power data measured at N time domain sampling points; the second sorting result is the sorting result from small to large of the first power data measured at N time domain sampling points.

[0482] In some embodiments, the time delay data includes numbers of time domain sampling points.

[0483] In some embodiments, the processing module is configured to set the second power data of the measurement data of n time domain sampling points based on the sorting of the delay data of the n measurement data in the first information; wherein the size sorting of the second power data of the measurement data of the n time domain sampling points is the same as the size sorting of the first power data of the measurement data of the n time domain sampling points.

[0484] In some embodiments, the determination module is configured to process the n second power data using a positioning model to obtain positioning information output by the positioning model.

[0485] In some embodiments, the sending module is configured to send second information to the first node; the second information is used by the first node to determine a reporting type of the measurement data; the reporting type includes at least one of the following:

[0486] The first type, when the first type is adopted, the delay data in the measurement data is sent to the second node;

[0487] The second type: when the second type is adopted, both the delay data and the first power data in the measurement data are sent to the second node.

[0488] In some embodiments, the second information is further used to indicate at least one of the following:

[0489] The number n of delay data carried in the first information;

[0490] The delay data carried by the first information is arranged in ascending or descending order according to the first power data.

[0491] In some embodiments, the determination module is configured to obtain a positioning model; determine the second information based on the positioning model; and the reporting type indicated by the second information is determined by an input parameter of the positioning model.

[0492] Figure 8A is a schematic diagram of the structure of a communication device according to an exemplary embodiment. Communication device 8100 can be a network device (e.g., an access network device or a core network device), a terminal (e.g., a user device), a chip, a chip system, or a processor that supports a network device to implement any of the above methods, or a chip, a chip system, or a processor that supports a terminal to implement any of the above positioning methods. Communication device 8100 can be used to implement the positioning method described in the above method embodiment. For details, please refer to the description of the above method embodiment.

[0493] As shown in Figure 8A, the communication device 8100 includes one or more processors 8101. The processor 8101 can be a general-purpose processor or a dedicated processor, for example, a baseband processor or a central processing unit. The baseband processor can be used to process communication protocols and communication data, and the central processing unit can be used to control the communication device (such as a base station, a baseband chip, a terminal device, a terminal device chip, a DU or a CU, etc.), execute programs, and process program data. The processor 8101 is used to call instructions to enable the communication device 8100 to perform any of the above communication methods.

[0494] In some embodiments, the communication device 8100 further includes one or more memories 8102 for storing instructions. Optionally, all or part of the memories 8102 may be located outside the communication device 8100.

[0495] In some embodiments, the communication device 8100 further includes one or more transceivers 8103. When the communication device 8100 includes one or more transceivers 8103, the communication steps such as sending and receiving in the above method are performed by the transceiver 8103, and the other steps are performed by the processor 8101.

[0496] In some embodiments, a transceiver may include a receiver and a transmitter, which may be separate or integrated. Optionally, the terms transceiver, transceiver unit, transceiver, and transceiver circuit may be used interchangeably; the terms transmitter, transmitting unit, transmitter, and transmitting circuit may be used interchangeably; and the terms receiver, receiving unit, receiver, and receiving circuit may be used interchangeably.

[0497] Optionally, the communication device 8100 further includes one or more interface circuits 8104, which are connected to the memory 8102. The interface circuits 8104 can be used to receive signals from the memory 8102 or other devices, and can be used to send signals to the memory 8102 or other devices. For example, the interface circuits 8104 can read instructions stored in the memory 8102 and send the instructions to the processor 8101.

[0498] The communication device 8100 described in the above embodiment may be a network device or a terminal, but the scope of the communication device 8100 described in the present disclosure is not limited thereto, and the structure of the communication device 8100 may not be limited by FIG. 8A. The communication device may be an independent device or may be part of a larger device. For example, the communication device may be: (1) an independent integrated circuit IC, or a chip, or a chip system or subsystem; (2) a collection of one or more ICs, optionally, the above IC collection may also include a storage component for storing data or programs; (3) an ASIC, such as a modem; (4) a module that can be embedded in other devices; (5) a receiver, a terminal device, an intelligent terminal device, a cellular phone, a wireless device, a handheld device, a mobile unit, an in-vehicle device, a network device, a cloud device, an artificial intelligence device, etc.; (6) others, etc.

[0499] FIG8B is a schematic diagram showing the structure of a chip according to an exemplary embodiment. In the case where the communication device 8100 can be a chip or a chip system, reference can be made to the schematic diagram of the structure of the chip 8200 shown in FIG8B , but the present invention is not limited thereto.

[0500] The chip 8200 includes one or more processors 8201 , and the processor 8201 is used to call instructions so that the chip 8200 executes any of the above communication methods.

[0501] In some embodiments, chip 8200 further includes one or more interface circuits 8202, which are connected to memory 8203. Interface circuit 8202 can be used to receive signals from memory 8203 or other devices, and can be used to send signals to memory 8203 or other devices. For example, interface circuit 8202 can read instructions stored in memory 8203 and send the instructions to processor 8201. Optionally, the terms interface circuit, interface, transceiver pin, and transceiver are interchangeable.

[0502] In some embodiments, the chip 8200 further includes one or more memories 8203 for storing instructions. Alternatively, all or part of the memories 8203 may be outside the chip 8200.

[0503] The present disclosure also provides a storage medium having instructions stored thereon, which, when executed on the communication device 8100, causes the communication device 8100 to execute 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 may also be a storage medium readable by other devices. Optionally, the storage medium may be a non-transitory storage medium, but may also be a transient storage medium.

[0504] The present disclosure further provides a program product, which, when executed by the communication device 8100, enables the communication device 8100 to perform any of the above communication methods. Optionally, the program product is a computer program product.

[0505] The present disclosure also provides a computer program, which, when executed on a computer, enables the computer to execute any one of the above communication methods.

[0506] Other embodiments of the present invention will readily occur to those skilled in the art after considering the specification and practicing the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the invention that follow from the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the invention being indicated by the following claims.

[0507] It should be understood that the present invention is not limited to the exact construction described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A positioning method, wherein: Executed by the first node, the method includes: Obtaining measurement data obtained by the first node measuring a positioning reference signal at n time domain sampling points; the measurement data includes first power data and delay data; the first power data indicates the measured power of the positioning reference signal; the delay data indicates the measurement timing of the first power data; and n is a positive integer; Sending first information to a second node; the first information is used by the second node to determine positioning information, the first information including delay data of n measurement data measured by the first node; the delay data of the n measurement data are sorted in the first information according to the size of the first power data of the n measurement data.

2. The method according to claim 1, wherein The obtaining measurement data obtained by the first node measuring the positioning reference signal at n time-frequency sampling points includes: Obtaining measurement data obtained by the first node at N time domain sampling points, where N is greater than or equal to n; According to the measurement data of the N time-domain sampling points, the measurement data of n time-domain sampling points that meet the first condition are selected.

3. The method according to claim 2, wherein: The measurement data of the n time-domain sampling points that meet the first condition are the measurement data of the n time-domain sampling points at which the first power data is the largest.

4. The method according to any one of claims 1 to 3, wherein: The first information includes n bit vectors; one bit vector is used to carry delay data in the measurement data of a time domain sampling point.

5. The method according to claim 4, wherein The i-th bit vector among the n bit vectors is used to indicate the delay data measured at the i-th time domain sampling point in the first sorting result or the second sorting result; the first sorting result is the sorting result from large to small of the first power data measured at the N time domain sampling points; the second sorting result is the sorting result from small to large of the first power data measured at the N time domain sampling points.

6. The method according to any one of claims 1 to 5, wherein: The time delay data includes the numbers of time domain sampling points.

7. The method according to any one of claims 1 to 6, wherein: The method further comprises: receiving second information sent by the second node; the second information is used by the first node to determine a reporting type of the measurement data; the reporting type includes at least one of the following: The first type, when the first type is adopted, the delay data in the measurement data is sent to the second node; The second type: when the second type is adopted, the delay data and the first power data in the measurement data are both sent to the second node.

8. The method according to claim 7, wherein: The second information is further used to indicate one of the following: The number n of the delay data carried in the first information; The delay data carried by the first information is arranged in ascending or descending order according to the first power data.

9. A positioning method, wherein: Executed by the second node, the method includes: receiving first information sent by a first node; the first information including delay data of n measurement data measured by the first node; the delay data of the n measurement data being sorted in the first information according to the magnitude of first power data of the n measurement data; the n measurement data being obtained by the first node by measuring a positioning reference signal at n time domain sampling points, the first power data indicating the measured power of the positioning reference signal; the delay data indicating a measurement timing of the first power data; and n being a positive integer; Determine positioning information based on the first information.

10. The method according to claim 9, wherein: The first information includes n bit vectors; one bit vector is used to carry delay data in the measurement data of a time domain sampling point.

11. The method according to claim 10, wherein: The i-th bit vector among the n bit vectors is used to indicate the delay data measured at the i-th time domain sampling point in the first sorting result or the second sorting result; the first sorting result is the sorting result from large to small of the first power data measured at the N time domain sampling points; the second sorting result is the sorting result from small to large of the first power data measured at the N time domain sampling points.

12. The method according to any one of claims 9 to 11, wherein: The time delay data includes the numbers of time domain sampling points.

13. The method according to any one of claims 9 to 12, wherein: The method further comprises: According to the order of the delay data of the n measurement data in the first information, the second power data of the measurement data of the n time domain sampling points is set; wherein the size ordering of the second power data of the measurement data of the n time domain sampling points is the same as the size ordering of the first power data of the measurement data of the n time domain sampling points.

14. The method according to claim 13, wherein: The determining the positioning information according to the first information includes: The n pieces of the second power data are processed by a positioning model to obtain the positioning information output by the positioning model.

15. The method according to any one of claims 9 to 14, wherein: The method further comprises: Sending second information to the first node; the second information is used by the first node to determine a reporting type of the measurement data; the reporting type includes at least one of the following: The first type, when the first type is adopted, the delay data in the measurement data is sent to the second node; The second type: when the second type is adopted, the delay data and the first power data in the measurement data are both sent to the second node.

16. The method according to claim 15, wherein The second information is further used to indicate at least one of the following: The number n of the delay data carried in the first information; The delay data carried by the first information is arranged in ascending or descending order according to the first power data.

17. The method according to claim 15 or 16, wherein The method further comprises: Get the positioning model; The second information is determined based on the positioning model; the reporting type indicated by the second information is determined by an input parameter of the positioning model.

18. A positioning method, wherein: Executed by a communication system, the method includes: The first node obtains measurement data obtained by the first node measuring the positioning reference signal at n time domain sampling points; the measurement data includes first power data and delay data; the first power data indicates the measured power of the positioning reference signal; the delay data indicates the measurement timing of the first power data; and n is a positive integer; The first node sends first information to the second node; the first information is used by the second node to determine positioning information, the first information including delay data of n measurement data measured by the first node; the delay data of the n measurement data are sorted in the first information according to the magnitude of the first power data of the n measurement data; The second node determines positioning information according to the first information.

19. A first node, wherein: The first node includes: a processing module configured to obtain measurement data obtained by the first node measuring a positioning reference signal at n time domain sampling points; the measurement data including first power data and delay data; the first power data indicating the measured power of the positioning reference signal; the delay data indicating the measurement timing of the first power data; and n being a positive integer; A sending module is configured to send first information to a second node; the first information is used by the second node to determine positioning information, the first information including delay data of n measurement data measured by the first node; the delay data of the n measurement data are sorted in the first information according to the size of the first power data of the n measurement data.

20. A second node, wherein: The second node includes: a receiving module configured to receive first information sent by a first node; the first information includes delay data of n measurement data measured by the first node; the delay data of the n measurement data are sorted in the first information according to the magnitude of first power data of the n measurement data; the n measurement data are obtained by the first node measuring a positioning reference signal at n time domain sampling points, the first power data indicates the measured power of the positioning reference signal; the delay data indicates a measurement timing of the first power data; and n is a positive integer; The determination module is configured to determine positioning information according to the first information.

21. A communication system, wherein: The communication system includes a first node and a second node; the first node is configured to implement the positioning method according to any one of claims 1 to 8, and the second node is configured to implement the positioning method according to any one of claims 9 to 17.

22. A communication device, wherein: The communication device comprises: one or more processors; The processor is configured to call instructions to enable the communication device to execute the positioning method according to any one of claims 1 to 8 or claims 9 to 17.

23. A storage medium, wherein: The storage medium stores instructions, and when the instructions are executed on the communication device, the communication device executes the positioning method according to any one of claims 1 to 8 or claims 9 to 17.

24. A computer program product, wherein The computer program product includes a computer program or instructions, and when the computer program or instructions are executed by a communication device, the communication device executes the positioning method according to any one of claims 1 to 8 or claims 9 to 17.

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