WO2023160633A1 - 一种通信方法及装置 - Google Patents

一种通信方法及装置 Download PDF

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Publication number
WO2023160633A1
WO2023160633A1 PCT/CN2023/077981 CN2023077981W WO2023160633A1 WO 2023160633 A1 WO2023160633 A1 WO 2023160633A1 CN 2023077981 W CN2023077981 W CN 2023077981W WO 2023160633 A1 WO2023160633 A1 WO 2023160633A1
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WO
WIPO (PCT)
Prior art keywords
channel estimation
positioning
information
estimation information
pieces
Prior art date
Application number
PCT/CN2023/077981
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English (en)
French (fr)
Inventor
孙雅琪
吴艺群
孙琰
Original Assignee
华为技术有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Publication of WO2023160633A1 publication Critical patent/WO2023160633A1/zh

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/023—Services making use of location information using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/0204—Channel estimation of multiple channels
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Definitions

  • the present disclosure relates to the field of communication technologies, and in particular, to a communication method and device.
  • a wireless communication network such as a mobile communication network
  • services supported by the network are becoming more and more diverse, and therefore requirements to be met are also becoming more and more diverse.
  • the network needs to be able to support ultra-high rates, ultra-low delays, and/or ultra-large connections, which make network planning, network configuration, and/or resource scheduling more and more complicated.
  • the functions of the network become more and more powerful, such as supporting higher and higher spectrum, supporting high-order multiple input multiple output (MIMO) technology, supporting beamforming, and/or supporting new technologies such as beam management, etc. technology, making network energy saving a hot research topic.
  • MIMO multiple input multiple output
  • beamforming supporting beamforming
  • new technologies such as beam management, etc. technology
  • the present disclosure provides a communication method and device, in order to realize flexible positioning by using artificial intelligence and improve the accuracy of positioning.
  • the present disclosure provides a communication method, which may be executed by a location server, or by a processor in the location server, where the location server may be a location management function (location management function, LMF) network element, or the like.
  • the location server may be a location management function (location management function, LMF) network element, or the like.
  • obtaining M pieces of channel estimation information where the m-th channel estimation information among the M pieces of channel estimation information is the estimated information of the channel between the m-th cell node and the terminal device among the M cell nodes; wherein, M is A positive integer, m is a positive integer ranging from 1 to M; according to the M channel estimation information, determine the type of target positioning mode; according to the type of target positioning mode, obtain N channel estimation information, and the N
  • the channel estimation information is used for the positioning of the terminal device; wherein, the nth channel estimation information among the N pieces of channel estimation information is the channel between the nth cell node among the N cell nodes and the terminal device
  • the target positioning method is determined based on the estimated information of the cell node and the terminal device, and then the estimated information between multiple cell nodes and the terminal device is selected according to the target positioning method to locate the terminal device, which can match the communication environment in real time and switch flexibly
  • the positioning method helps to improve the accuracy of positioning.
  • obtaining a positioning requirement the positioning requirement is used to obtain the M pieces of channel estimation information used to determine the type of the target positioning method; the positioning requirement is used to indicate a positioning index Value conditions need to be met, and the M pieces of channel estimation information can be used to determine the value of the positioning index.
  • the method further includes: sending first request information, where the first request information is used to request the M pieces of channel estimation information, and the first request information includes an information about targeting metrics.
  • the device providing channel estimation information can know the type of parameters that should be indicated by the M channel estimation information, which helps to improve the efficiency of determining the target positioning method.
  • the positioning index may include one or more of the following: the type of the communication path between the cell node and the terminal device, and the type of the communication path includes a direct path or non-direct path; the positioning accuracy corresponding to at least one type of positioning method.
  • the nth second channel estimation information in the N pieces of channel estimation information is used to indicate one or more of the following parameters : the distance between the nth cell node and the terminal device; the signal transmission delay or signal transmission delay difference between the nth cell node and the terminal device; the nth cell The signal departure angle or signal arrival angle corresponding to the node.
  • the nth second channel estimation information among the N pieces of channel estimation information is used to indicate the distance between the nth cell node and the terminal device Channel information for the channel.
  • obtaining channel estimation information matching the type of target positioning method facilitates the implementation of subsequent target positioning methods.
  • the acquiring N pieces of channel estimation information according to the type of the target positioning method includes: sending second request information, and the second request information is used to request the N pieces of channel estimation information information, the second request information includes information indicating the type of the target positioning manner; receiving the N pieces of channel estimation information.
  • the device providing channel estimation information can know the type of parameters that should be indicated by the N pieces of channel estimation information, which helps to improve the efficiency of implementing the target positioning method.
  • the method further includes: within a set time period, positioning the terminal device according to the N pieces of channel estimation information.
  • the present disclosure provides a communication method, including: sending M pieces of channel estimation information, where the M pieces of channel estimation information are used to determine the type of target positioning method; wherein, the mth piece of the M pieces of channel estimation information
  • the channel estimation information is the estimation information of the channel between the mth cell node and the terminal equipment among the M cell nodes, M is a positive integer, and m is a positive integer ranging from 1 to M;
  • the acquisition is used to request N channel estimates Second request information for information, where the second request information includes information indicating the type of the target positioning method; sending the N pieces of channel estimation information, and the N pieces of channel estimation information are used for the terminal device Positioning; wherein, the nth channel estimation information among the N pieces of channel estimation information is the channel estimation information between the nth cell node and the terminal device among the N cell nodes;
  • the N cell nodes include For the M cell nodes, N is a positive integer less than or equal to M, and n is a positive integer ranging from 1 to N.
  • the method further includes: obtaining first request information, where the first request information is used to request the M pieces of channel estimation information, and the first request information includes information indicating positioning requirements or positioning indicators. information; wherein, the positioning requirement is used to indicate the value condition that the positioning index needs to meet, and the M pieces of channel estimation information can be used to determine the value of the positioning index.
  • the positioning index includes one or more of the following: the type of the communication path between the cell node and the terminal device, and the type of the communication path includes a direct path or Indirect path; positioning accuracy corresponding to at least one type of positioning method.
  • the nth channel estimation information among the N pieces of channel estimation information is used to indicate one or more of the following parameters: the The distance between the nth cell node and the terminal device; the signal transmission delay or signal transmission delay difference between the nth cell node and the terminal device; the nth cell node corresponds to The signal departure angle or signal arrival angle.
  • the nth channel estimation information among the N pieces of channel estimation information is used to indicate that the nth cell node is related to the Channel information for a channel between end devices.
  • the present disclosure provides a communication device, which may be a location management function (LMF) network element, hereinafter referred to as LMF; it may also be a device in LMF, or it may be used in conjunction with LMF installation.
  • LMF location management function
  • the communication device may include a one-to-one corresponding module for executing the method/operation/step/action described in the first aspect.
  • the module may be a hardware circuit, or software, or a combination of hardware circuit and software.
  • the communication device may include a processing module and a communication module.
  • a communication module configured to obtain M pieces of channel estimation information, where the m-th channel estimation information among the M pieces of channel estimation information is the channel estimation information between the m-th cell node and the terminal device among the M cell nodes; wherein , M is a positive integer, and m is a positive integer ranging from 1 to M;
  • a processing module configured to determine the type of target positioning method according to the M pieces of channel estimation information
  • the processing module is further configured to control the communication module to acquire N pieces of channel estimation information according to the type of the target positioning method, and the N pieces of channel estimation information are used for positioning of the terminal device; wherein, the N pieces of channel estimation information
  • the nth channel estimation information in the N cell nodes is the channel estimation information between the nth cell node and the terminal device; the N cell nodes are included in the M cell nodes, and N is less than It is a positive integer equal to M, and n is a positive integer ranging from 1 to N.
  • the communication module is further configured to obtain positioning requirements, where the positioning requirements are used to obtain the M pieces of channel estimation information used to determine the type of the target positioning method; the positioning requirements are used to A value condition that the positioning index needs to meet is indicated, and the M pieces of channel estimation information can be used to determine the value of the positioning index.
  • the communication module is further configured to: send first request information, where the first request information is used to request the M pieces of channel estimation information, and the first request information includes information for indicating the Positioning requirements or information about the positioning indicator.
  • the positioning index includes one or more of the following: the type of the communication path between the cell node and the terminal device, and the type of the communication path includes a direct path or Indirect path; positioning accuracy corresponding to at least one type of positioning method.
  • the nth second channel estimation information in the N pieces of channel estimation information is used to indicate one or more of the following parameters : the distance between the nth cell node and the terminal device; the signal transmission delay or signal transmission delay difference between the nth cell node and the terminal device; the nth cell The signal departure angle or signal arrival angle corresponding to the node.
  • the nth second channel estimation information among the N pieces of channel estimation information is used to indicate the distance between the nth cell node and the terminal device Channel information for the channel.
  • the processing module is further configured to: send second request information through the communication module, where the second request information is used to request the N pieces of channel estimation information, and the second request information includes Based on the information indicating the type of the target positioning method; receiving the N pieces of channel estimation information through a communication module.
  • the processing module is further configured to locate the terminal device according to the N pieces of channel estimation information within a set time period.
  • the present disclosure provides a communication device.
  • the communication device may be a terminal device or a core network device; it may also be a device in a terminal device or a core network device, or it may be matched with a terminal device or used with a core network device Match the device used.
  • the communication device may include a one-to-one corresponding module for executing the method/operation/step/action described in the second aspect.
  • the module may be a hardware circuit, or software, or a combination of hardware circuit and software.
  • the communication device may include a processing module and a communication module.
  • a communication module configured to send M pieces of channel estimation information, where the M pieces of channel estimation information are used to determine the type of target positioning mode; wherein, the m-th channel estimation information in the M pieces of channel estimation information is M cell nodes In the estimated information of the channel between the mth cell node and the terminal equipment, M is a positive integer, and m is a positive integer ranging from 1 to M;
  • the communication module is further configured to acquire second request information for requesting N pieces of channel estimation information, where the second request information includes information indicating the type of the target positioning method;
  • a processing module configured to send the N pieces of channel estimation information through a communication module, and the N pieces of channel estimation information are used for positioning of the terminal device; wherein, the nth channel estimation information in the N pieces of channel estimation information is the channel estimation information between the nth cell node and the terminal device among the N cell nodes; the N cell nodes are included in the M cell nodes, N is a positive integer less than or equal to M, and n is Take a positive integer from 1 to N.
  • the communication module is further configured to obtain first request information, the first request information is used to request the M pieces of channel estimation information, and the first request information includes Or information about a positioning index; wherein, the positioning requirement is used to indicate a value condition that the positioning index needs to meet, and the M pieces of channel estimation information can be used to determine the value of the positioning index.
  • the processing module is further configured to determine the M pieces of channel estimation information according to the first request information.
  • the positioning index includes one or more of the following: the type of the communication path between the cell node and the terminal device, and the type of the communication path includes a direct path or Indirect path; positioning accuracy corresponding to at least one type of positioning method.
  • the nth channel estimation information among the N pieces of channel estimation information is used to indicate one or more of the following parameters: the The distance between the nth cell node and the terminal device; the signal transmission delay or signal transmission delay difference between the nth cell node and the terminal device; the nth cell node corresponds to The signal departure angle or signal arrival angle.
  • the nth channel estimation information among the N pieces of channel estimation information is used to indicate that the nth cell node is related to the Channel information for a channel between end devices.
  • the present disclosure provides a communication device, where the communication device includes a processor, configured to implement the method described in the first aspect above.
  • the processor is coupled to the memory, and the memory is used to store instructions and data.
  • the communication device may also include a memory; the communication device may also include a communication interface, which is used for the device to communicate with other devices.
  • the communication interface may be a transceiver, a circuit, A bus, module, pin, or other type of communication interface.
  • the communication device includes a processor for acquiring M channel estimates using a communication interface information, the m-th channel estimation information among the M pieces of channel estimation information is the estimation information of the channel between the m-th cell node and the terminal equipment among the M cell nodes; wherein, M is a positive integer, and m is the round A positive integer from 1 to M;
  • the nth channel estimation information among the N pieces of channel estimation information is the channel estimation information between the nth cell node among the N cell nodes and the terminal equipment; the N cell nodes are included in the For the M cell nodes, N is a positive integer less than or equal to M, and n is a positive integer ranging from 1 to N.
  • the present disclosure provides a communication device, where the communication device includes a processor, configured to implement the method described in the second aspect above.
  • the processor is coupled to the memory, and the memory is used to store instructions and data.
  • the communication device may also include a memory; the communication device may also include a communication interface, which is used for the device to communicate with other devices.
  • the communication interface may be a transceiver, a circuit, A bus, module, pin, or other type of communication interface.
  • the communication device includes a processor, configured to use a communication interface to send M pieces of channel estimation information, where the M pieces of channel estimation information are used to determine the type of target positioning method; wherein, the M channels
  • the mth channel estimation information in the estimation information is the estimation information of the channel between the mth cell node and the terminal equipment among the M cell nodes, M is a positive integer, and m is a positive integer ranging from 1 to M; and using
  • the communication interface acquires second request information for requesting N pieces of channel estimation information, where the second request information includes information indicating the type of the target positioning method; and using the communication interface to send the N pieces of channel estimation information,
  • the N pieces of channel estimation information are used for the positioning of the terminal equipment; wherein, the nth channel estimation information in the N pieces of channel estimation information is the difference between the nth cell node among the N cell nodes and the terminal equipment
  • the estimation information of the channel among them; the N cell nodes are included in the M cell nodes, N is a positive integer less
  • the present disclosure provides a communication system, including the communication device described in the third aspect or the fifth aspect; and, the communication device described in the fourth aspect or the sixth aspect.
  • the present disclosure further provides a computer program, which, when running on a computer, causes the computer to execute the method provided in the first aspect or the second aspect.
  • the present disclosure further provides a computer program product, including instructions, which, when run on a computer, cause the computer to execute the method provided in the first aspect or the second aspect.
  • the present disclosure also provides a computer-readable storage medium, where a computer program or instruction is stored in the computer-readable storage medium, and when the computer program or instruction is run on a computer, the computer executes The method provided in the first aspect or the second aspect above.
  • the present disclosure further provides a chip, which is used to read a computer program stored in a memory, and execute the method provided in the first aspect or the second aspect above.
  • the present disclosure further provides a chip system, which includes a processor, configured to support a computer device to implement the method provided in the first aspect or the second aspect above.
  • the chip system further includes a memory, and the memory is used to store necessary programs and data of the computer device.
  • the system-on-a-chip may consist of chips, or may include chips and other discrete devices.
  • FIG. 1A is one of the structural schematic diagrams of the communication system provided by the present disclosure.
  • FIG. 1B is one of the structural schematic diagrams of the communication system provided by the present disclosure.
  • FIG. 1C is one of the structural schematic diagrams of the communication system provided by the present disclosure.
  • Fig. 2 is a schematic diagram of the principle of a positioning method based on TDOA
  • FIG. 3 is a schematic diagram of a time-domain channel response
  • FIG. 4 is a schematic structural diagram of a signal transmission path
  • FIG. 5A is a schematic diagram of a weak head path scenario
  • FIG. 5B is a schematic diagram of an NLOS path scenario
  • FIG. 6 is one of the structural schematic diagrams of the communication system provided by the present disclosure.
  • Figure 7A is a schematic diagram of a neuron structure
  • FIG. 7B is a schematic diagram of the layer relationship of the neural network
  • FIG. 8A is a schematic diagram of an AI-based uplink positioning scenario
  • FIG. 8B is a schematic diagram of another AI-based uplink positioning scenario
  • FIG. 9 is one of the schematic flowcharts of the communication method provided by the present disclosure.
  • FIG. 10 is a schematic diagram of a probability-related positioning accuracy
  • Fig. 11 is a schematic flow chart of an adaptive switching positioning method
  • FIG. 12 is one of the schematic flowcharts of the communication method provided by the present disclosure.
  • FIG. 13 is one of the schematic flowcharts of the communication method provided by the present disclosure.
  • FIG. 14 is one of the structural schematic diagrams of the communication device provided by the present disclosure.
  • Fig. 15 is one of the structural schematic diagrams of the communication device provided by the present disclosure.
  • the present disclosure refers to at least one (item) as follows, indicating one (item) or more (items).
  • a plurality of (items) refers to two (items) or more than two (items).
  • "And/or" describes the association relationship of associated objects, indicating that there may be three types of relationships, for example, A and/or B may indicate: A exists alone, A and B exist simultaneously, and B exists independently.
  • the character "/" generally indicates that the contextual objects are an "or” relationship.
  • first, second, etc. may be used in the present disclosure to describe various objects, these objects should not be limited by these terms. These terms are only used to distinguish one object from another.
  • the communication system can be a third generation (3 th generation, 3G) communication system (such as a universal mobile telecommunications system (universal mobile telecommunications system, UMTS)), a fourth generation 4th generation (4G) communication system (such as long term evolution (LTE) system), 5th generation ( 5th generation, 5G) communication system, worldwide interconnected microwave access (worldwide interoperability for microwave access, WiMAX) or wireless local area network (wireless local area network, WLAN) system, or a fusion system of multiple systems, or a future communication system, such as a sixth generation (6th generation, 6G) communication system, etc.
  • 3G third generation
  • 3G such as a universal mobile telecommunications system (universal mobile telecommunications system, UMTS)
  • 4G 4th generation
  • LTE long term evolution
  • 5th generation ( 5th generation, 5G) communication system worldwide interconnected microwave access (worldwide interoperability for microwave access, WiMAX) or wireless local area network (wireless local area network, WLAN) system
  • the 5G communication system may also be called a new radio (new radio, NR) system.
  • a network element in a communication system may send signals to another network element or receive signals from another network element.
  • the signal may include information, signaling, or data.
  • a network element may also be replaced by an entity, a network entity, a device, a communication device, a communication module, a node, a communication node, etc., and the present disclosure takes a network element as an example for description.
  • the communication system may include at least one terminal device and at least one access network device, the access network device may send a downlink signal to the terminal device, and/or the terminal device may send an uplink signal to the access network device; in addition, it can be understood that , if the communication system includes multiple terminal devices, the multiple terminal devices can also send signals to each other, that is, both the signal sending network element and the signal receiving network element can be terminal devices.
  • the communication system 100 includes an access network device 110 , an access network device 120 , an access network device 130 and a terminal device 140 .
  • the terminal device 140 may send an uplink signal to one or more access network devices among the access network device 110 , the access network device 120 and the access network device 130 .
  • One or more access network devices among the access network device 110 , the access network device 120 and the access network device 130 may send a downlink signal to the terminal device 140 .
  • the terminal equipment and access network equipment involved in FIG. 1A will be described in detail below.
  • the access network device may be a base station (base station, BS).
  • the access network device may also be called a network device, an access node (access node, AN), or a wireless access node (radio access node, RAN).
  • the base station may have various forms, such as a macro base station, a micro base station, a relay station, or an access point.
  • the access network device can be connected to a core network (such as an LTE core network or a 5G core network, etc.), and the access network device can provide wireless access services for terminal devices.
  • a core network such as an LTE core network or a 5G core network, etc.
  • Access network equipment includes, but is not limited to, at least one of the following: base stations in 5G, such as transmission and reception points (Transmission Reception Point, TRP) or next-generation node B (generation nodeB, gNB), open radio access network (open radio access network, O-RAN) in the access network equipment or modules included in the access network equipment, evolved node B (evolved node B, eNB), radio network controller (radio network controller, RNC), node B (node B , NB), base station controller (base station controller, BSC), base transceiver station (base transceiver station, BTS), home base station (for example, home evolved nodeB, or home node B, HNB), base band unit (base band unit, BBU), sending and receiving point (transmitting and receiving point, TRP), transmitting point (transmitting point, TP), and/or mobile switching center, etc.
  • base stations in 5G such as transmission and reception points (Transmission Reception Point, TRP) or next-generation node B
  • the access network device may also be a radio unit (radio unit, RU), a centralized unit (centralized unit, CU), a distributed unit (distributed unit, DU), a centralized unit control plane (CU control plane, CU-CP) node , or a centralized unit user plane (CU user plane, CU-UP) node.
  • the access network device may be a vehicle-mounted device, a wearable device, or an access network device in a future evolved public land mobile network (public land mobile network, PLMN).
  • PLMN public land mobile network
  • the communication device used to realize the function of the access network equipment may be the access network equipment, or the network equipment with some functions of the access network equipment, or a device capable of supporting the access network equipment to realize the function , such as a chip system, a hardware circuit, a software module, or a hardware circuit plus a software module, the device can be installed in the access network equipment or matched with the access network equipment.
  • description is made by taking the communication device for realizing the function of the access network device as an example of the access network device.
  • Terminal equipment is also called terminal, user equipment (UE), mobile station (mobile station, MS), mobile terminal (mobile terminal, MT) and so on.
  • a terminal device may be a device that provides voice and/or data connectivity to a user.
  • Terminal equipment can communicate with one or more core networks through access network equipment.
  • Terminal equipment can be deployed on land, including indoors, outdoors, handheld, and/or vehicle; can also be deployed on water (such as ships, etc.); can also be deployed in the air (such as aircraft, balloons and satellites, etc.) .
  • End devices include handheld devices with wireless connectivity, other processing devices connected to wireless modems, or vehicle-mounted devices.
  • the terminal device may be a portable, pocket, hand-held, computer built-in or vehicle-mounted mobile device.
  • terminal equipment are: personal communication service (PCS) phones, cordless phones, session initiation protocol (SIP) phones, wireless local loop (WLL) stations, personal digital assistants (personal digital assistant, PDA), wireless network camera, mobile phone (mobile phone), tablet computer, notebook computer, palmtop computer, mobile Internet device (mobile internet device, MID), wearable device such as smart watch, virtual reality (virtual reality) , VR) equipment, augmented reality (augmented reality, AR) equipment, wireless terminals in industrial control (industrial control), terminals in car networking systems, wireless terminals in self-driving (self driving), smart grid (smart grid) ), wireless terminals in transportation safety, wireless terminals in smart city (smart city) such as smart fuel dispensers, terminal equipment on high-speed rail and wireless terminals in smart home (smart home), such as Smart speakers, smart coffee machines, smart printers, etc.
  • PCS personal communication service
  • SIP session initiation protocol
  • WLL wireless local loop
  • PDA personal digital assistants
  • wireless network camera mobile phone (mobile phone),
  • the communication device used to realize the function of the terminal device may be a terminal device, or a terminal device with some terminal functions, or a device capable of supporting the terminal device to realize this function, such as a chip system, which may be Installed in the terminal equipment or matched with the terminal equipment.
  • a system-on-a-chip may be composed of chips, and may also include chips and other discrete devices.
  • the number and types of devices in the communication system shown in FIG. 1A are only for illustration, and the present disclosure is not limited thereto.
  • the communication system may also include more terminal devices and more access networks.
  • the device may also include other network elements, for example, may include core network elements, and/or network elements for implementing artificial intelligence functions.
  • the method provided in the present disclosure involves positioning technology for terminal equipment.
  • a positioning server 150 is introduced into the communication system shown in FIG. 1A above, and the positioning server 150 is used for estimating the position of the terminal equipment.
  • the positioning server 150 in FIG. 1B may be implemented by an LMF network element.
  • the communication system includes not only access network equipment and terminal equipment, but also core network elements, such as access and mobility management function (AMF) network element and location management function (location management function, LMF) network element.
  • AMF access and mobility management function
  • LMF location management function
  • the access network devices may be base stations of the same standard, or base stations of different network standards.
  • Fig. 1C shows a 5G base station, such as gNB; and a 4G base station, such as ng-eNB, which can access the 5G core network.
  • the terminal device represented by UE in FIG.
  • the gNB can communicate through the NR-Uu interface, such as using the NR-Uu interface to transmit signaling related to positioning.
  • the terminal device and the ng-eNB communicate through the LTE-Uu interface, for example, the LTE-Uu interface is used to transmit positioning-related signaling.
  • the gNB and AMF communicate through the NG-C interface, and the ng-eNB and AMF communicate through the NG-C interface.
  • the NG-C interface can be used to transmit signaling related to positioning.
  • the AMF and the LMF communicate through the NL1 interface, for example, use the NL1 interface to transmit signaling related to positioning.
  • the positioning server may detect characteristic parameters between the terminal device and a fixed (that is, a known location) access network device, and obtain the distance between the terminal device and the access network device. Relative position or angle information, so as to estimate the position of the terminal device.
  • some characteristic parameters include: signal quality, distance, signal transmission delay (or propagation time) or delay difference, signal departure angle, signal arrival angle, etc.;
  • the signal quality can be reflected by signal-to-noise ratio, signal strength, signal field strength, signal energy, signal received power, etc.
  • one of the terminal device or the access network device sends a reference signal; the other party measures the reference signal to obtain channel information, and according to the channel information, the characteristic parameters between the terminal device and the access network device can be determined, and the characteristic parameters can also be It is called the measurement quantity, and then reports the measurement quantity to the LMF.
  • the access network device or the cell of the access network device sends a positioning reference signal (positioning reference signal, PRS) to the terminal device, and the terminal device measures the PRS to obtain downlink channel information, and then the terminal device obtains downlink channel information based on the downlink channel information Determine the measurement amount, and report the measurement amount to the LMF for positioning of the terminal device.
  • PRS positioning reference signal
  • the terminal device can send a sounding reference signal (SRS) to the access network device or the cell of the access network device, and the access network device or the cell of the access network device measures the SRS to obtain the uplink channel information, and then the access network device or the cell of the access network device determines the measurement amount according to the uplink channel information, and reports the measurement amount to the LMF for positioning of the terminal device.
  • SRS sounding reference signal
  • a positioning method based on a time difference of arrival which can utilize the synchronized positions of at least three access network devices to locate a terminal device.
  • the three access network devices are marked as eNB1, eNB2, and eNB3 respectively.
  • the distances between the three access network devices and the terminal devices are d1, d2, and d3 respectively, and the propagation times of the corresponding signals are respectively t1, t2, t3.
  • three access network devices respectively send PRSs to the terminal device, which are denoted as P1, P2, and P3 respectively.
  • the eNB1 can be set as a reference node, and the terminal device can measure the arrival time difference between P2 and P1, that is, t 2 -t 1 , also called a reference signal time difference (reference signal time difference, RSTD).
  • the terminal device can deduce d 2 -d 1 by using t 2 -t 1 , and obtain a curve so that each point on the curve satisfies that the distance difference between eNB2 and eNB1 is d 2 -d 1 ; similarly, the terminal device
  • the arrival time difference between P3 and P1 can be measured, that is, t 3 -t 1 , using t 3 -t 1 can infer d 3 -d 1 , and obtain another curve that satisfies every point on this curve to eNB3 and eNB1
  • the distance difference is d 3 -d 1 .
  • the terminal device can determine its own position by using the intersection point of the above two curves.
  • the terminal device may report at least one parameter among signal propagation time, time difference of arrival, distance or inferred distance difference between different access network devices and the terminal device to the LMF, and the LMF may determine the above two curves, and the two The intersection point of the two curves, thereby determining the position of the terminal device.
  • the correspondingly obtained time difference of arrival can be expressed as an interval range.
  • the interval corresponding to the schematic curve in Figure 2 is represented by a dotted line, and the position of the terminal device is obtained between the two curves The overlap between the intervals (indicated in black).
  • ( xi , y i ) represents the position coordinates of the eNBi, and the value of i is 1, 2 or 3; (x, y) represents the position coordinates of the terminal device to be obtained, and c represents the speed of light.
  • the TDOA-based positioning method described above performs positioning according to the PRS sent by the access network device to the terminal device.
  • This positioning method may also be called DL-TDOA or OTDOA.
  • the TDOA-based positioning method is a method for performing positioning according to the SRS sent by the terminal device to the access network device, then this positioning method may also be called UL-TDOA.
  • the signal here is the signal transmitted between the access network device and the terminal device, and both AoA and AoD are equivalent to the The angle of preparation. That is, in the scenario where the access network device sends PRS to the terminal device for positioning, at least two access network devices can send PRS to the terminal device, and the terminal device measures the PRS sent by different access network devices to determine the location of each access network device. The corresponding AoD, or determine the angle difference between the AoD corresponding to each access network device and the AoD reference value.
  • the AoD reference value may be an AoD corresponding to one of the at least two access network devices, or a preset AoD.
  • the terminal device reports the AoD or angle difference corresponding to at least two access network devices to the LMF, and the LMF can determine the position of the terminal device according to the AoD or angle difference corresponding to at least two access network devices.
  • the terminal device may send SRS to at least two access network devices, and different access network devices measure the SRS from the terminal device to determine the location of each access network device.
  • the AoA reference value may be an AoA corresponding to one of the at least two access network devices, or a preset AoA.
  • Each access network device reports its corresponding AoA or angle difference to the LMF, and the LMF can determine the location of the terminal device according to the AoA or angle difference corresponding to at least two access network devices.
  • the LMF can exchange positioning configuration information with the terminal device or the access network device in advance to determine the terminal device to be positioned, the access network device participating in the positioning of the terminal device, which positioning method to use, downlink positioning ( That is, positioning according to the PRS) or uplink positioning (positioning according to the SRS), and configurations such as measurement quantities.
  • the following takes the DL-TDOA method as an example to introduce the positioning process based on the LTE positioning protocol (LPP) in the 5G system.
  • LPP protocol specifies the process of exchanging information between the terminal device and the LMF, that is, the terminal device and the LMF can exchange information through LPP messages.
  • the LPP message is transparently transmitted across the access network device and the AMF to realize the interaction between the terminal device and the LMF.
  • the terminal device and the LMF exchange positioning configuration information.
  • the positioning configuration information includes positioning capabilities and positioning assistance information. This process can be triggered by the LMF or the terminal device. For example, when the LMF triggers the transmission of positioning assistance information, the LMF determines that the positioning assistance information needs to be provided to the terminal device, and sends an LPP Provide Assistance Data (LPP Provide Assistance Data) message to the terminal device. For another example, when the terminal device triggers the transmission of positioning assistance information, the terminal device first determines the required positioning assistance information, and sends an LPP request assistance data (LPP Request Assistance Data) message to the LMF, and the LPP request assistance data message can be used to indicate Positioning assistance information required by the terminal device.
  • LPP Provide Assistance Data LPP Provide Assistance Data
  • the LMF sends an LPP provide assistance data message to the terminal device to provide the positioning assistance information required by the terminal device.
  • the positioning capability indicates information such as the positioning method supported by the terminal device, the adopted protocol and process, and configurable parameters;
  • the positioning assistance information includes one or more of the following parameters: the physical cell ID of the terminal device, the global cell ID, the access ID of the access network device, PRS configuration of the access network device, synchronization signal/physical broadcast channel block (SSB) information of the access network device, spatial direction information of the PRS, geographic location coordinates of the access network device, access network device Information such as the time difference between network-connected devices and reference nodes.
  • SSB synchronization signal/physical broadcast channel block
  • the terminal device and the LMF exchange positioning information that is, the measurement quantity (or location measurement result) determined by the terminal device measuring the PRS sent by each access network device is fed back to the LMF.
  • This process can be triggered by the terminal device or the LMF.
  • the LMF sends an LPP Request Location Information (LPP Request Location Information) message to the terminal device.
  • LPP Request Location Information is used to indicate the location measurement results required by the LMF, measurement configuration information, and required responses. time and other information.
  • the terminal device sends an LPP Provide Location Information (LPP Provide Location Information) message to the LMF before the required response time to feed back the measurement amount.
  • the terminal device When the terminal device triggers positioning information interaction, the terminal device sends an LPP providing positioning information message to the LMF to feed back the measurement amount.
  • the measurement quantity may include the arrival time stamp of the PRS, the propagation time of the PRS, and the arrival time stamp corresponding to the PRS. Time difference of arrival, received signal power of PRS and other information.
  • the measurement quantity may also include information for identifying the access network device, for example, including physical cell ID, global cell ID, access network device ID, etc. corresponding to different measurement quantities.
  • NR positioning protocol A NR Positioning Protocol A
  • the access network device and the LMF are connected through the AMF.
  • the NRPPa protocol is transparent to the AMF. The transparent transmission of NRPPa data units across the AMF makes the access network device and the LMF implements interaction.
  • the positioning assistance information of the access network device includes physical cell ID, global cell ID, ID of the access network device, PRS configuration of the access network device, SSB information of the access network device, spatial direction information of the PRS, access network device geographic location coordinates, etc.
  • the LMF sends a TRP Information Request (TRP Information Request) message to the access network device.
  • TRP Information Request is used to request the positioning assistance information of the access network device required by the LMF, and the access network device sends a TRP Information Response (TRP Information Response) message to the LMF.
  • the TRP information response message is used to indicate the positioning assistance information of the access network device needed by the LMF, or the access network device sends a TRP Information Failure (TRP Information Failure) message to the LMF, and the TRP information failure message is used to indicate failure reason.
  • TRP Information Failure TRP Information Failure
  • Figure 3 shows the power
  • the signal power of the first period of time-domain sampling points is weak, corresponding to the noise signal ;
  • the reference signal is classified into a signal propagated by a non-line of sight (NLOS) or a signal propagated by a line of sight (LOS).
  • NLOS non-line of sight
  • LOS line of sight
  • the NLOS between the access network device and the terminal device means that there is an obstacle between the access network and the terminal device, so that the signal cannot be transmitted directly
  • the LOS between the access network device and the terminal device refers to the Signals between end devices are direct propagation.
  • Figure 4 shows that the LOS path (dotted line) between the access network device and the terminal device is blocked by trees, and what actually arrives is the NLOS (solid line) reflected by the wall.
  • the distance of the NLOS path is greater than the distance of the LOS path.
  • a weak first path scenario shown in FIG. 5A is called a weak first path because the strength of the first path is weaker than that of the subsequent delay path.
  • the actual weak first path is regarded as noise, and the path after the weak first path is identified as the first path, which leads to a large error in the identification of the first path and reduces the accuracy of positioning.
  • the identified reference signal propagates through the NLOS path, that is, arrives after reflection, and the distance traveled is shorter than the straight-line distance corresponding to the LOS path between the terminal device and the access network device. This will lead to a large difference between the identified first path and the corresponding first path of the LOS path.
  • the position of the first path corresponding to the LOS path in the delay domain is ahead of the identified first path in the delay domain. position on the It can be seen that in the method of positioning the terminal device by using the measurement quantity, the error of the head path estimation in the aforementioned weak head path or NLOS path scenario is very large, resulting in a large error in the estimated position of the terminal device.
  • the positioning server can obtain the channel information of the channel between the terminal device and the fixed (that is, known location) access network device, and use AI technology to analyze the obtained channel information to estimate the location of the end device.
  • one of the terminal device or the access network device sends a reference signal; the other party measures the reference signal to obtain channel information, and then reports the channel information to the LMF.
  • the channel information can be terminal
  • the device or the access network device measures the channel response obtained by measuring the reference signal, or may also be based on a feature of the channel response.
  • the feature based on the channel response may be the channel response after several transformations such as normalization and truncation, or the feature based on the channel response may be artificial empirical features such as variance and mean value extracted from the channel response; or, based on The feature of the channel response may be a feature extracted from the acquired channel response by the terminal device or the access network device using an AI technology.
  • the foregoing communication system may also include a network element implementing an AI function.
  • an AI function (such as an AI module or an AI entity) may be configured in an existing network element in a communication system to implement AI-related operations.
  • the existing network element may be an access network device (such as gNB), a terminal device, a core network device, or a network management device.
  • an independent network element may also be introduced into the communication system to perform AI-related operations.
  • the independent network element may be called an AI network element or an AI node, etc., and this disclosure does not limit the name.
  • the network element performing AI-related operations is a network element with a built-in AI function (such as an AI module or an AI entity).
  • AI-related operations may also be referred to as AI functions.
  • the AI network element can establish a communication connection with the network elements included in the aforementioned communication system, such as terminal equipment, access network equipment, and core network elements.
  • the communication system includes terminal equipment, access network equipment, AMF network elements, and LMF network elements.
  • the introduction of AI network elements can communicate with terminal equipment, access network equipment, AMF network elements, and LMF network elements establish a communication connection between them.
  • the AI model is the specific realization of the AI function.
  • the AI model represents the mapping relationship between the input and output of the model. It can refer to a function model that maps an input of a certain dimension to an output of a certain dimension.
  • the AI model can be a neural network or other machine learning models, such as decision trees, support vector machines, etc.
  • the AI model may be referred to simply as a model.
  • the AI function may include at least one of the following: data collection (collecting training data and/or reasoning data), data preprocessing, model training (or model learning), model information release (configuration model information), model Inference, or release of inference results. Among them, reasoning can also be called prediction.
  • the AI model may be referred to simply as a model.
  • Machine learning is an important technical way to realize artificial intelligence. For example, machine learning can learn models or rules from raw data. Machine learning is divided into supervised learning, unsupervised learning, and reinforcement learning.
  • supervised learning uses machine learning algorithms to learn the mapping relationship between samples and sample labels, and uses machine learning models to express the learned mapping relationship.
  • the process of training a machine learning model is the process of learning this mapping relationship.
  • the sample is a received signal containing noise
  • the sample label is the real constellation point corresponding to the received signal.
  • Machine learning expects to learn the mapping relationship between samples and sample labels through training.
  • model parameters are optimized by calculating the error between the model's output (i.e., the predicted value) and the sample label.
  • the learned mapping relationship can be used to predict the sample label of each new sample.
  • the mapping relationship learned by supervised learning can include linear mapping and nonlinear mapping. According to the type of sample labels, machine learning tasks can be divided into classification tasks and regression tasks.
  • unsupervised learning uses algorithms to discover the internal patterns of the samples by itself.
  • algorithms such as autoencoder, confrontational generative network, etc.
  • the model learns the mapping relationship from sample to sample.
  • the relationship between the predicted value of the model and the sample itself is calculated. The error between them is used to optimize the model parameters and realize self-supervised learning.
  • Self-supervised learning can be used in signal compression and decompression recovery applications Use the scene.
  • Reinforcement learning is a class of algorithms that learn strategies to solve problems by interacting with the environment. Unlike supervised learning and unsupervised learning, reinforcement learning does not have clear sample labels. The algorithm needs to interact with the environment to obtain reward signals from environmental feedback, and then adjust decision-making actions to obtain greater reward signal values. For example, in downlink power control, the reinforcement learning model adjusts the downlink transmission power of each terminal according to the total system throughput fed back by the wireless network, and expects to obtain a higher system throughput. The goal of reinforcement learning is also to learn the mapping relationship between the environment state and the optimal decision-making action. Training in reinforcement learning is achieved through iterative interactions with the environment.
  • a neural network is a specific implementation of AI or machine learning technology. According to the general approximation theorem, the neural network can theoretically approximate any continuous function, so that the neural network has the ability to learn any mapping.
  • Traditional communication systems need to rely on rich expert knowledge to design communication modules, while deep learning communication systems based on neural networks can automatically discover hidden pattern structures from a large number of data sets, establish mapping relationships between data, and achieve better results than traditional communication systems. The performance of the modeling method.
  • each neuron performs a weighted sum operation on its input values, and outputs the operation result through an activation function.
  • FIG. 7A it is a schematic diagram of a neuron structure.
  • the weight of i is used to weight x i .
  • the bias for performing weighted summation of the input values according to the weights is, for example, b.
  • the output of the neuron is:
  • the output of the neuron is:
  • b may be various possible values such as decimals, integers (such as 0, positive integers or negative integers), or complex numbers.
  • the activation functions of different neurons in a neural network can be the same or different.
  • a neural network generally includes multiple layers, each layer may include one or more neurons. By increasing the depth and/or width of the neural network, the expressive ability or function fitting ability of the neural network can be improved, and more powerful information extraction and abstract modeling capabilities can be provided for complex systems.
  • the depth of the neural network may refer to the number of layers included in the neural network, and the number of neurons included in each layer may be referred to as the width of the layer.
  • a neural network includes an input layer and an output layer. The input layer of the neural network processes the received input information through neurons, and passes the processing result to the output layer, and the output layer obtains the output result of the neural network.
  • the neural network includes an input layer, a hidden layer, and an output layer.
  • a neural network processes the received input information through neurons, and passes the processing results to the middle hidden layer.
  • the processing results are calculated to obtain the calculation results, and the hidden layer transmits the calculation results to the output layer or the adjacent hidden layer, and finally the output layer obtains the output result of the neural network.
  • a neural network may include one hidden layer, or include multiple hidden layers connected in sequence, without limitation.
  • each neuron performs a weighted sum operation on its input values, and the weighted sum result generates an output through a nonlinear function.
  • the parameters of all neurons of a neural network constitute the parameters of this neural network.
  • the neural network involved in the present disclosure is, for example, a deep neural network (DNN).
  • DNN generally has multiple hidden layers, and the weight corresponding to each neuron in the DNN is the model parameter of the DNN.
  • DNN can use monitoring Supervised learning or unsupervised learning strategies to optimize model parameters.
  • DNNs can include feedforward neural networks (FNN), convolutional neural networks (CNN) and recurrent neural networks (RNN).
  • FNN feedforward neural networks
  • CNN convolutional neural networks
  • RNN recurrent neural networks
  • FIG. 7B illustrate a neural network structure.
  • the characteristic of FNN is that neurons in adjacent layers are completely connected between pairs.
  • CNNs can be applied to process data with a grid-like structure.
  • the data with a similar grid structure may include time series data (discrete sampling on the time axis) and image data (two-dimensional discrete sampling) and the like.
  • the convolutional layer of CNN does not use all the input information for convolution operation at one time, but sets one or more fixed-size windows, and uses each window to intercept part of the input information for convolution operation.
  • Such a design can greatly reduce the calculation amount of model parameters.
  • performing a convolution operation on any one of one or more fixed-size windows can be understood as performing multiplication and then addition operations on the coefficients of the window (such as weighting coefficients) and part of the input information intercepted by the window .
  • the output information corresponding to the window can be obtained.
  • the coefficients of different windows may be configured independently.
  • different windows can be configured with different coefficients, which can enable CNN to better extract the features of the input data.
  • the coefficients of the window may include convolution kernels.
  • the types of part of the input information intercepted by different windows can be different.
  • the people and objects in the same picture can be understood as different types of information, and one window can be intercepted in two fixed-size windows The person in the picture, another window can intercept the thing in the picture.
  • RNN is a DNN network that utilizes feedback time series information. Its input includes the new input value at the current moment and the part of the output value of the RNN at the previous moment, where the output value at the previous moment can be determined by the activation function and the input at the previous moment.
  • RNN is suitable for obtaining sequence features that are correlated in time, and is suitable for application scenarios such as speech recognition and channel coding and decoding.
  • a loss function can be defined.
  • the loss function describes the gap or difference between the output value of the neural network and the ideal target value, and the disclosure does not limit the specific form of the loss function.
  • the training process of the neural network is the process of adjusting the parameters of the neural network so that the value of the loss function is less than the threshold, or the value of the loss function meets the target requirements. Adjusting the parameters of the neural network, for example, adjusting at least one of the following parameters: the number of layers of the neural network, the width, the weight of the neurons, or the parameters in the activation function of the neurons.
  • the access network device or the cell node of the access network device sends a PRS to the terminal device, and the terminal device measures the PRS to obtain a downlink channel response, and then the terminal device can report the obtained downlink channel response to the LMF, Or the terminal device may extract features from the obtained downlink channel response based on the AI model, and report the feature based on the downlink channel response to the LMF.
  • the LMF can determine the position of the terminal device according to the AI model and the acquired downlink channel response or based on the characteristics of the downlink channel response.
  • the terminal device can send SRS to the access network device or the cell node of the access network device, and the access network device or the cell node of the access network device measures the SRS to obtain the uplink channel response, and then the access network device or The cell node of the access network device can report the obtained uplink channel response to the LMF; or, the access network device or the cell node of the access network device can also extract features from the obtained uplink channel response based on the AI model, and use the The characteristics of the uplink channel response are reported to the LMF. Furthermore, the LMF can determine the position of the terminal device according to the AI model and the acquired uplink channel response or based on the characteristics of the uplink channel response.
  • the AI model can be deployed on the LMF side, and multiple access network devices, namely, access network device 1, access network device 2, and access network device 3.
  • Send the channel response to the LMF, and the LMF takes the channel responses of multiple access network devices as the input of the AI model, and outputs the location information of the terminal device.
  • the channel response sent by each access network device to the LMF includes 16*4096 complex information.
  • each access network device among multiple access network devices is based on an AI model, uses the obtained channel response as the input of the AI model, and outputs features based on the channel response, referred to as channel features. Furthermore, each access network device among the multiple access network devices sends channel characteristics to the LMF; wherein, the dimension of the channel characteristics is determined by the output dimension of the AI model on the access network device side, for example, the access network device side can learn from the dimension Extract the channel feature with dimension [128] from the channel response of [16,4096] and send it to LMF.
  • the channel characteristics of multiple access network devices are used as the input of the AI model, and the location information of the terminal device is output. Assuming that the number of antennas of the access network device is 16 and the number of subcarriers is 4096, the channel response sent by each access network device to the LMF includes 16*4096 pieces of complex information.
  • the foregoing manner of positioning a terminal device by using measurement quantities may also be referred to as a non-AI positioning manner, or a non-AI positioning mode.
  • the method of using AI technology to analyze channel information to locate a terminal device may also be called an AI positioning method, or an AI positioning mode.
  • an AI positioning method if there is a weak first path or the reference signal propagates through the NLOS path, there is a big difference between the identified first path and the real first path, which will make the estimated terminal device location accuracy is poor.
  • the positioning accuracy can be enhanced by using AI technology, but the transmission overhead related to channel information is relatively large, which will cause a waste of air interface resources.
  • the present disclosure provides a communication method, which can be used for locating a terminal device.
  • it is possible to dynamically switch the positioning mode that meets the positioning accuracy requirements, realize adaptive adjustment of the positioning mode, and flexibly make a compromise between positioning accuracy and information transmission overhead.
  • a communication method is illustrated, and the method mainly includes the following procedures.
  • the LMF acquires M pieces of channel estimation information.
  • the m-th channel estimation information among the M pieces of channel estimation information is the estimation information of the channel between the m-th cell node and the terminal equipment among the M cell nodes; wherein, M is a positive integer, and m is the round A positive integer from 1 to M.
  • the M pieces of channel estimation information are used to determine the type of the target positioning method.
  • the LMF may acquire M pieces of channel estimation information from the terminal device or M cell nodes.
  • the m-th channel estimation information among the M pieces of channel estimation information may come from the m-th cell node or terminal device.
  • the mth cell node sends the mth channel estimation information to the LMF, or the mth cell node sends the mth channel estimation information to other core network elements.
  • the unit sends M pieces of channel estimation information obtained from M cell nodes to the LMF; in the downlink positioning scenario, the terminal device sends the mth channel estimation information to the LMF.
  • the value of M may be determined by the number of cell nodes in the communication environment that can participate in locating the terminal device, which may be 1 or a positive integer greater than 1, such as 2 or 3, and so on.
  • the first device may actively send the m-th channel estimation information to the LMF, and the m-th channel estimation information may be estimated information that the first device can obtain by measuring the channel between the cell node and the terminal device based on its own capabilities.
  • the LMF or a third-party network element can pre-configure the reporting period of the M channel estimation information, so that the first device can periodically report the m-th channel estimation information, thereby triggering the LMF to adjust the positioning mode.
  • positioning requirements for determining a positioning mode may be pre-configured in the LMF, the terminal device, and the cell node.
  • the targeting requirement is used to indicate the conditions that the targeting metric needs to meet.
  • the parameter type indicated by the m-th channel estimation information may be determined in combination with the positioning requirement, so as to ensure that the sent m-th channel estimation information can participate in determining the value of the positioning index.
  • the LMF determines the type of the target positioning method according to the M pieces of channel estimation information.
  • the LMF can determine the value of the positioning index according to the obtained M pieces of channel estimation information; then the LMF can determine the type of the target positioning method according to the value of the positioning index and the positioning requirements.
  • the positioning index is a type of a communication path between the cell node and the terminal device, and the type of the communication path includes a direct path (LOS path) or a non-direct path (NLOS path).
  • the positioning requirement corresponding to this positioning index is: judge whether to enable the AI mode according to the number of LOS paths/NLOS paths, that is, whether to use the AI positioning method.
  • the LMF can determine the type of communication path between each of the M cell nodes and the terminal device according to the obtained M pieces of channel estimation information, whether it is a LOS path or an NLOS path, and then determine the number of LOS paths or NLOS paths.
  • the LMF may determine that the type of the target positioning mode is a non-AI positioning mode.
  • the LMF may determine that the type of the target positioning mode is to enable the AI positioning mode.
  • enabling the AI positioning mode is divided into an AI positioning mode, or an AI positioning mode combined with a non-AI positioning mode.
  • the positioning indicator is the positioning accuracy corresponding to the currently used positioning method.
  • the positioning requirements corresponding to the positioning index are: the requirements for positioning accuracy, or described as the positioning accuracy requirements that the positioning method needs to meet.
  • LMF can determine the positioning accuracy corresponding to the currently used positioning method according to the obtained M channel estimation information, judge whether the positioning accuracy meets the positioning accuracy requirements specified or preset by the location requester, and then determine the type of target positioning method according to the judgment result .
  • the currently used positioning method is AI positioning method. If the positioning accuracy corresponding to the AI positioning method does not meet the positioning accuracy requirements, LMF can determine that the type of target positioning method is a non-AI positioning method; if the positioning accuracy corresponding to the AI positioning method meets the positioning accuracy requirements Accuracy requirements, the LMF can determine that the type of target positioning mode is to open the AI positioning mode.
  • the LMF can determine that the AI positioning mode is turned on, specifically the AI positioning method; when the difference between the positioning accuracy corresponding to the AI positioning mode and the positioning accuracy requirement is less than the set difference value, the LMF can determine that the AI positioning mode is turned on, specifically as Combination of AI positioning method and non-AI positioning method.
  • the type of positioning method currently used is a non-AI positioning method. If the positioning accuracy corresponding to the non-AI positioning method meets the positioning accuracy requirements, LMF can determine that the type of the target positioning method is a non-AI positioning method, that is, keep the currently used positioning method remains unchanged; if the positioning accuracy corresponding to the non-AI positioning method does not meet the positioning accuracy requirements, the LMF can determine that the type of the target positioning method is the AI positioning method.
  • the LMF can determine whether the non-AI positioning method meets the positioning accuracy requirements based on the accuracy of the acquired measurements. Taking the TDOA-based positioning method shown in Figure 2 as an example, when the terminal device reports the time difference of arrival, it can also report a piece of information indicating the accuracy of measuring the time difference of arrival, such as OTDOA-MeasQuality, corresponding to Figure 2. The dotted line shows the time difference of arrival Interval range. Furthermore, the LMF can judge whether the positioning accuracy of the non-AI positioning method is based on the range of the intersection (that is, the overlapping part as shown in Figure 2 ) between the obtained intervals of multiple time differences of arrival. Meet the positioning accuracy requirements.
  • the positioning accuracy corresponding to the AI positioning method can be determined according to the statistical error during offline training.
  • the data set is divided into a training set and a verification set, and the AI model trained based on the training set is tested on the verification set to obtain the error of each sample on the verification set, and the cumulative distribution function of the error is obtained by statistical error (cumulative distribution function, CDF), as shown in Figure 10, the positioning accuracy of different probabilities can be obtained.
  • CDF cumulative distribution function
  • 90% corresponds to a positioning accuracy of 0.57m.
  • the positioning accuracy corresponding to the AI positioning method can also be determined by the distance between the training set samples.
  • AI-based positioning relies on collecting a large amount of fingerprint information, that is, placing a beacon at a certain distance in a certain area.
  • the samples of the training set are formed by sending reference signals between the beacon node and the base station. Therefore, the distance of the beacon node can reflect the positioning accuracy corresponding to the AI positioning method. Beacons with different densities can be placed in different areas.
  • the LMF can match the received features with the features in the database to determine the area where the terminal device is located, so as to obtain the positioning accuracy of the area, that is, AI The positioning accuracy corresponding to the positioning method; and then judge whether the positioning accuracy of the AI positioning method meets the positioning accuracy requirements.
  • LMF can train an AI model for obtaining positioning accuracy.
  • the input of this AI model can be one or more information in channel response, channel quality, antenna configuration, reference signal configuration, etc., and the output is positioning accuracy.
  • a relational table may also be deployed in the LMF, and the relational table stores the correspondence between one or more pieces of information in channel response, channel quality, antenna configuration, reference signal configuration, etc. and positioning accuracy. That is, when the LMF obtains one or more pieces of information in channel response, channel quality, antenna configuration, reference signal configuration, etc., it can read the corresponding positioning accuracy from the relational table.
  • the relationship table may be obtained statistically from offline training data.
  • the positioning index is the positioning accuracy corresponding to the AI positioning mode and the positioning accuracy corresponding to the non-AI positioning mode.
  • the positioning requirement corresponding to this positioning index is to determine whether to enable the AI mode according to the positioning accuracy difference between the AI positioning mode and the non-AI positioning mode. Then the LMF can determine the positioning accuracy corresponding to the AI positioning mode and the positioning accuracy corresponding to the non-AI positioning mode according to the acquired M pieces of channel estimation information. Furthermore, the LMF can determine the type of the target positioning method according to the difference in positioning accuracy between the AI positioning method and the non-AI positioning method.
  • the LMF may determine that the type of the target positioning mode is the AI positioning mode.
  • the LMF may determine that the type of the target positioning mode is a non-AI positioning mode.
  • the LMF can determine that the type of the target positioning method is a non-AI positioning method, because the non-AI positioning method is based on the measurement quantity. Positioning, compared with the AI positioning method based on channel information, can save transmission overhead.
  • the LMF acquires N pieces of channel estimation information according to the type of the target positioning method.
  • the N pieces of channel estimation information are used for the positioning of the terminal device; wherein, the nth channel estimation information among the N pieces of channel estimation information is the connection between the nth cell node among the N cell nodes and the terminal device Estimation information of a channel between devices; the N cell nodes are included in the M cell nodes, N is a positive integer greater than 1 and less than or equal to M, and n is a positive integer ranging from 1 to N.
  • the LMF may acquire N pieces of channel estimation information from the terminal device or M cell nodes.
  • the nth channel estimation information among the N pieces of channel estimation information may come from the nth cell node or the terminal device among the N cell nodes included in the M cell nodes.
  • the nth cell node The node sends the nth channel estimation information to the LMF, or the nth cell node sends the nth channel estimation information to other core network elements, and the other core network elements send the acquired N channel estimation information to the LMF;
  • the terminal device sends the nth channel estimation information to the LMF.
  • N is equal to M; or, when M When the communication paths between part of the cell nodes and the terminal equipment in the number of cell nodes are LOS paths, the value of N is the same as the number of part of the cell nodes corresponding to the LOS paths in the M cells. If the positioning requirement does not involve considering the type of communication path, N can be equal to M, or the number of cell nodes that can participate in the positioning of the terminal device can be satisfied.
  • the LMF can obtain the nth channel from the second device by referring to the following method estimated information.
  • the LMF may send second request information to the second device, where the second request information is used to request channel estimation information required for positioning the terminal device, that is, the aforementioned N pieces of channel estimation information.
  • the second device sends n-th channel estimation information to the LMF in response to the second request information.
  • the LMF may include information used to indicate the type of the target positioning manner in the second request information.
  • the second device determines the nth channel estimation information matching the type of the object positioning method according to the information indicating the type of the object positioning method, and reports the nth channel estimation information to the LMF.
  • the LMF may determine the type of parameters indicated by the N pieces of channel estimation information to be acquired according to the type of the target positioning method, and the parameter type matches the type of the target positioning method. Further, the LMF may include N parameter types indicated by the channel estimation information in the second request information. The second device reports the nth channel estimation information to the LMF according to the parameter type indicated by the N pieces of channel estimation information. In addition, it should be noted that the parameter types indicated by each piece of channel estimation information in the N pieces of channel estimation information are the same. Since the N cell nodes are included in the M cell nodes, there is a situation in the present disclosure that the second device and the first device represent the same cell node.
  • the nth second channel estimation information among the N pieces of second channel estimation information is used
  • the measurement amount includes one or more parameters in the following: the distance between the nth cell node and the terminal device; the signal between the nth cell node and the terminal device Transmission delay or signal transmission delay difference; signal departure angle or signal arrival angle corresponding to the nth cell node; signal quality between the nth cell node and the terminal device.
  • the nth second channel estimation information among the N pieces of second channel estimation information is used to Channel information indicating a channel between the nth cell node and the terminal device.
  • the type of the target positioning method corresponds to the third value, that is, the type of the target positioning method is a combination of an AI positioning method and a non-AI positioning method
  • the nth channel estimation information of the N pieces of second channel estimation information is used to indicate the channel information and the measurement quantity of the channel between the nth cell node and the terminal device.
  • the parameters included in the measurement quantity can be understood with reference to the definitions of the foregoing examples, and this disclosure is not limited thereto .
  • the LMF locates the terminal device according to the N pieces of channel estimation information.
  • the LMF may locate the terminal device according to the above-described AI positioning method and the channel information indicated by the N pieces of channel estimation information. If the type of target positioning method is non-AI positioning method, LMF can follow the non-AI positioning method described above and N channel estimation information Indicates the measured quantity to locate the terminal device. This disclosure will not describe it in detail.
  • the LMF can locate the terminal device according to the AI positioning method to obtain the first positioning result; and locate the terminal device according to the non-AI positioning method to obtain the first positioning result. 2. Positioning results. Furthermore, the LMF may combine the first positioning result and the second positioning result to determine a final positioning result.
  • an effective time period for implementing the target positioning method may be set, such as being recorded as a set time period or called a set time period.
  • the LMF uses the determined target positioning method to locate the terminal device within the set time period after determining the target positioning method; after the set time period, the LMF needs to re-determine the type of the target positioning method according to the aforementioned S901 ⁇ S902 methods , that is, to reacquire channel estimation information that is used to locate the terminal device in a matching target positioning manner.
  • Such a design can realize the periodic adjustment of the positioning method, so as to adapt to the actual communication environment in time and improve the positioning accuracy.
  • the LMF can initiate a judgment every set time period (corresponding to executing S901-S902) to adjust the current positioning mode, so as to realize the AI positioning mode, non-AI positioning mode, Or adaptive switching between the combination of AI positioning method and non-AI positioning method.
  • the LMF may also send the positioning result and the positioning method used to calculate the positioning result to the location requester.
  • the above method provided in the present disclosure can realize dynamic adjustment of the positioning mode, match the actual communication environment in time, flexibly select a suitable positioning mode, and help improve the accuracy of estimating the position of the terminal device.
  • a communication method is illustrated, which mainly includes the following process.
  • the LMF sends first request information, where the first request information is used to request M pieces of channel estimation information.
  • the LMF sends the first request information to M cell nodes or terminal devices.
  • the m-th channel estimation information among the M pieces of channel estimation information is the estimation information of the channel between the m-th cell node and the terminal equipment among the M cell nodes; wherein, M is a positive integer, and m is taken from 1 to A positive integer of M.
  • the M pieces of channel estimation information are used to determine the type of the target positioning method.
  • the LMF sends the first request information to the mth cell to request the mth channel estimation information related to the mth cell, or the LMF sends the first request information to other core network elements to request The first request information is forwarded to each of the M cell nodes through other core network elements.
  • the LMF sends first request information to the terminal device, so as to request the terminal device to measure M pieces of channel estimation information.
  • the value of M may be determined by the number of cell nodes in the communication environment that can participate in locating the terminal device, which may be 1 or a positive integer greater than 1, such as 2 or 3, and so on.
  • the LMF may send first request information to the first device, where the first request information is specifically used to request m-th channel estimation information related to the first device. Then the first device sends its related m-th channel estimation information to the LMF.
  • the LMF or a third-party network element can pre-configure the reporting period of the M channel estimation information, so that the LMF can periodically send the first request information to the first device to request the first device to feed back the m-th channel estimation information , thus triggering the adjustment of the LMF to the positioning method.
  • the LMF may send the first request information to the first device according to a positioning requirement (or called a positioning policy) used to determine a positioning manner.
  • the positioning requirement is used to indicate the value conditions that the positioning index needs to meet.
  • the first request information can be specifically used to request the M channel estimation information that the LMF wants to obtain, so that the M channel estimation information can be used For determining the value of the positioning index, or described as parameters indicated by the M pieces of channel estimation information can be used to determine the value of the positioning index.
  • the LMF may include one or more of the following information in the first request information: information indicating positioning requirements; information indicating positioning indicators; and parameter types indicated by the M pieces of channel estimation information.
  • the LMF may first obtain capability information of the first device according to a positioning requirement or a positioning index, and the capability information is used to indicate whether the mth channel estimation information that can be obtained by the first device can determine the value of the index parameter. Furthermore, according to the capability information and positioning index of the first device, the LMF includes in the first request information the parameter type indicated by the channel estimation information used to determine the target positioning mode type, that is, the parameter type indicated by the M pieces of channel estimation information. Wherein, the parameter types indicated by each piece of channel estimation information in the M pieces of channel estimation information are the same. The first device determines the m-th channel estimation information related to the first device to be sent to the LMF according to the parameter type indicated by the foregoing M pieces of channel estimation information.
  • the LMF may include information indicating positioning requirements or positioning indicators in the first request information.
  • the first device obtains the first request information, it determines to send the location request (or positioning indicators) to the LMF according to its own capabilities.
  • the m-th channel estimation information related to the first device so that the m-th channel estimation information can be used to determine the value of the positioning index.
  • the positioning requirement or the positioning indicator corresponding to the positioning requirement in the above embodiment may be pre-configured in the LMF, or the location requester indicates the positioning requirement or the positioning indicator corresponding to the positioning requirement to the LMF, and the location request
  • the party refers to the network element that needs to obtain the location of the terminal device.
  • the location requester may be a third-party network element such as another core network element, or may be a terminal device.
  • the location request direction LMF indicates positioning requirements, and different positioning requirements correspond to different positioning indicators.
  • the positioning index and the corresponding parameter types indicated by the M pieces of channel estimation information are illustrated below.
  • the positioning index is a type of a communication path between the cell node and the terminal device, and the type of the communication path includes a direct path (LOS path) or a non-direct path (NLOS path).
  • LOS path direct path
  • NLOS path non-direct path
  • the LMF can determine that the positioning index is the type of the aforementioned communication path. Based on this, the LMF may acquire capability information of the first device, where the capability information is specifically used to indicate whether the first device has a LOS path/NLOS path identification capability. Furthermore, the LMF can request the m-th channel estimation information from the first device in combination with its current positioning method and positioning index. For details, refer to the following implementation:
  • the positioning method currently used by LMF is a non-AI positioning method.
  • the parameter type indicated by the mth channel estimation information requested by the LMF from the first device is the type of the communication path between the cell node and the terminal device. Since the information overhead for indicating the LOS path/NLOS path is relatively small, the LMF can first request the type of the communication path each time it is positioned, so as to judge in a timely manner whether to enable the AI mode.
  • the mth channel estimation information sent by the first device indicates that the type of the communication path is LOS path or NLOS path, which can be marked with 1/0, such as "1" means LOS path, and "0" means NLOS path.
  • the first device sends the m-th channel estimation information indicating the probability that the type of the communication path is the LOS path/NLOS path. Based on this, when the LMF acquires M channel estimation information, it can determine the types of M communication paths, and the mth communication path among the M communication paths is the communication path between the mth cell node and the terminal device.
  • the LMF can determine that the parameter types indicated by the M channel estimation information are cell nodes and Channel information of the channel between the terminal devices.
  • the LMF may include an identifier for indicating channel information in the first request information sent to the first device, and then the first device reports the first request to the LMF according to the request of the LMF. Device-related channel information. Based on this, the LMF can acquire M pieces of channel information, and the mth channel information among the M pieces of channel information corresponds to the channel between the mth cell node and the terminal device. Furthermore, the LMF can determine the type of the communication path between the M cell nodes and the terminal device by itself according to the obtained M pieces of channel information.
  • the LMF may trigger or the LMF configures the first device to report the channel information periodically, for example, every Report once at a set time interval, or report once every time the positioning reaches the set number of times according to the number of positioning.
  • the periodic reporting of channel information is used by the LMF to periodically judge whether to enable the AI mode.
  • an AI judgment cycle can be defined to instruct the first device to report the information used to determine the target positioning method. channel information.
  • the judging period may be defined as the aforementioned set time interval, or may also be defined as the aforementioned set times.
  • the LMF may also add the information used when the first device extracts the characteristics based on the channel response to the request for the first request information. Instructions for the AI model.
  • the positioning method currently used by LMF is the AI positioning method.
  • the LMF since the LMF currently uses the AI positioning method, it means that the LMF has obtained the channel information of the channel between the cell node and the terminal device, then the LMF can determine the cell node and the terminal device according to the historically obtained channel information. The type of communication path between. In this manner, the LMF may not send the first request information to the first device.
  • the LMF when the first device has the LOS path/NLOS path identification capability, the LMF sends the first request information to the first device, including M pieces of channel estimation information indicating that the parameter type is the cell node and the Describes the type of communication path between end devices. Furthermore, the first device reports to the LMF the type of the communication path related to the first device according to the request of the LMF, and the LMF can determine the types of the M communication paths based on the obtained M pieces of channel estimation information, and the mth communication path among the M communication paths The communication path is a communication path between the mth cell node and the terminal device.
  • the positioning indicator is the positioning accuracy corresponding to the currently used positioning method.
  • the LMF can determine the positioning index as the positioning accuracy corresponding to the current positioning method according to the positioning accuracy requirements.
  • the LMF can request relevant channel estimation information from the first device in combination with its current positioning method and positioning index. For details, refer to the following implementation:
  • the positioning method currently used by LMF is a non-AI positioning method.
  • the m-th channel estimation information requested by the LMF from the first device corresponds to the measurement quantity mentioned above.
  • the mth channel estimation information is used to indicate one or more of the following parameters: the distance between the mth cell node and the terminal device; the signal between the mth cell node and the terminal device Transmission delay or signal transmission delay difference; signal departure angle or signal arrival angle corresponding to the mth cell node; signal quality between the mth cell node and the terminal device.
  • the first device reports the measurement quantities related to the first device to the LMF according to the request of the LMF; the LMF can determine M measurement quantities, and the m-th measurement quantity among the M measurement quantities corresponds to the connection between the m-th cell node and the terminal device. Channel.
  • the positioning method currently used by LMF is the AI positioning method.
  • the parameter type indicated by the mth channel estimation information requested by the LMF from the first device is the channel information of the channel between the mth cell node and the terminal device, and the channel information can be used by the LMF to determine the mth cell node by itself
  • the type of communication path to and from the end device is determined.
  • LMF obtains M channel estimation information, which can be rooted According to the M pieces of channel estimation information, the type of the communication path between each of the M cells and the terminal equipment is determined.
  • the m-th channel estimation information sent by the first device is required to be channel information, since the overhead corresponding to the channel information is relatively large, it can be triggered by the LMF or the LMF configures the first device to report the channel information periodically, for example, every Report once at a set time interval, or report once every time the positioning reaches the set number of times according to the number of positioning.
  • the periodic reporting of channel information here is used by the LMF to periodically judge whether to enable the AI mode.
  • an AI judgment cycle can be defined to instruct the first device to report the channel used to determine the positioning method. information.
  • the judging period may be defined as the aforementioned set time interval, or may also be defined as the aforementioned set times.
  • the LMF may also add in the first request information the AI model used when the first device extracts the characteristics based on the channel response instruct.
  • the first device reports channel information related to the first device to the LMF according to the request of the LMF, and the LMF can determine M channel information, and the m-th channel information in the M channel information corresponds to the connection between the m-th cell node and the terminal device. Channel.
  • the first device can also report the channel information to the LMF at the same time related measurements.
  • the positioning index is the positioning accuracy corresponding to the AI positioning mode and the positioning accuracy corresponding to the non-AI positioning mode.
  • the LMF can determine the positioning index according to the positioning requirement, including the positioning accuracy corresponding to the AI positioning mode and the positioning accuracy corresponding to the non-AI positioning mode. Based on this, the m-th channel estimation information requested by the LMF from the first device according to the positioning index includes the measurement quantity corresponding to the non-AI positioning mode and the channel information corresponding to the AI positioning mode.
  • the first device reports the measurement quantities and channel information related to the first device to the LMF according to the request of the LMF, and the LMF can obtain M measurement quantities and M channel information, and the m-th measurement quantity among the M measurement quantities corresponds to the m-th measurement quantity A channel between a cell node and a terminal device, and the m-th channel information among the M channel information corresponds to a channel between the m-th cell node and the terminal device.
  • the LMF acquires M pieces of channel estimation information.
  • the LMF can obtain M pieces of channel estimation information from the terminal equipment or M cell nodes.
  • the m-th channel estimation information among the M pieces of channel estimation information may come from the m-th cell node or terminal device.
  • the mth cell node sends the mth channel estimation information to the LMF, or the mth cell node sends the mth channel estimation information to the core network element, and the core network element
  • the M pieces of channel estimation information acquired by the cell node are sent to the LMF; in the downlink positioning scenario, the terminal device sends the mth channel estimation information to the LMF.
  • the value of M may be determined by the number of cell nodes in the communication environment that can participate in locating the terminal device, which may be 1 or a positive integer greater than 1, such as 2 or 3, and so on.
  • the LMF determines the type of the target positioning method according to the M pieces of channel estimation information.
  • this step may be performed with reference to the implementation manner of S902, which will not be repeated in this disclosure.
  • the LMF acquires N pieces of channel estimation information according to the type of the target positioning method.
  • the LMF can obtain N pieces of channel estimation information from the terminal equipment or M cell nodes.
  • the nth channel estimation information among the N pieces of channel estimation information may come from the nth cell node or the terminal device among the N cell nodes included in the M cell nodes.
  • this step may be performed with reference to the implementation manner of S903, which will not be repeated in this disclosure.
  • the LMF locates the terminal device according to the N pieces of channel estimation information.
  • this step may be performed with reference to the implementation manner of S904, which will not be repeated in this disclosure.
  • the LMF instructs the terminal device or the cell node to report the channel estimation information used in the decision-making positioning mode, which can quickly realize the dynamic adjustment of the positioning mode, match the actual communication environment in time, and flexibly select the appropriate positioning mode. It is beneficial to improve the accuracy of estimating the location of the terminal device.
  • a communication method is illustrated, which mainly includes the following process.
  • the location requester sends first information to the LMF, where the first information is used to indicate the positioning mode desired by the location requester.
  • the positioning mode can also be described as a positioning mode type.
  • the location requester may be a terminal device or another third-party network element, and the location requester may also be described as a third device or another name, which is not limited in the present disclosure.
  • the positioning mode indicated by the first information is an AI positioning mode; or, the positioning mode indicated by the first information is a non-AI positioning mode; or, the positioning mode indicated by the first information is a combination of an AI positioning mode and a non-AI positioning mode; or, The positioning mode indicated by the information is an automatic switching mode, and the automatic switching mode indicates that the LMF dynamically adjusts the positioning mode to be an AI positioning mode, a non-AI positioning mode, or a combination of an AI positioning mode and a non-AI positioning mode.
  • the first information when the positioning mode is an automatic switching mode, it may also include information indicating a positioning requirement.
  • the positioning requirement can be used for LMF decision-making target positioning mode, and the positioning requirement is used to indicate the position that the positioning index needs to meet. value condition.
  • the location requester may select a positioning mode according to service requirements. For example, when the location requester is a terminal device, it may have certain requirements on air interface overhead. Exemplarily, if the location requester requires positioning services with short delays and does not have high requirements for positioning accuracy, it can be determined that the positioning mode indicated by the first information is a non-AI positioning method; if the location requesting party requires high positioning accuracy If the location requester needs a more robust positioning result and does not have high requirements on time delay and air interface overhead, it can be determined that the positioning mode indicated by the first information is AI positioning mode Determine that the positioning mode indicated by the first information is a combination of AI positioning mode and non-AI positioning mode; if the location requester needs a more robust positioning result and hopes that the delay and air interface overhead are as small as possible, the positioning mode indicated by the first information can be determined For automatic switching mode.
  • the location requester may also acquire capability information of the LMF, so as to determine the positioning modes supported and/or unsupported by the capabilities of the LMF. Then, the first information is sent to the LMF in combination with the capability of the LMF, where the positioning mode indicated by the first information is the positioning mode supported by the LMF.
  • the LMF determines the type of the target positioning method according to the first information.
  • the LMF may determine whether to support the positioning mode indicated by the first information based on its own capabilities. If supported, the LMF determines the positioning mode indicated by the first information as the type of target positioning mode. If not, in an optional implementation, the LMF can report its own capabilities to the location requester, and then the location requester will re-indicate the desired positioning mode for the LMF based on business requirements, and repeat this process until the LMF Until the positioning mode desired by the location requester can be supported. In another optional implementation manner, the LMF can combine its own capabilities to determine the location of the target by itself. type, and notify the location requester of the type of target positioning method.
  • the LMF can determine the positioning mode indicated by the first information as the target positioning The type of method.
  • the LMF may determine the type of target positioning mode in real time or periodically according to S901-S902 in Solution 1 or S1201-S1203 in Solution 2, which is not discussed in this disclosure. to repeat.
  • the LMF acquires N pieces of channel estimation information according to the type of the target positioning method.
  • the N pieces of channel estimation information are used for positioning of the terminal equipment, and the nth channel estimation information among the N pieces of channel estimation information is the information of the channel between the nth cell node and the terminal equipment among the N cell nodes participating in the positioning of the terminal equipment estimated information.
  • N is a positive integer
  • n is a positive integer from 1 to N.
  • the LMF can obtain N pieces of channel estimation information from N cell nodes or terminal devices, and the N pieces of channel estimation information match the types of the aforementioned target positioning methods.
  • the nth channel estimation information among the N pieces of channel estimation information may come from the nth cell node or the terminal device among the N cell nodes included in the M cell nodes.
  • the core network element will obtain the N
  • the nth channel estimation information is sent to the LMF; in the downlink positioning scenario, the terminal device sends the nth channel estimation information to the LMF.
  • the LMF can obtain the nth channel estimation information from the second device by referring to the following manner.
  • the LMF may send second request information to the second device, where the second request information is used to request channel estimation information required for positioning the terminal device, that is, the aforementioned N pieces of channel estimation information.
  • the second device sends n-th channel estimation information to the LMF in response to the second request information.
  • the LMF may include information used to indicate the type of the target positioning manner in the second request information.
  • the second device determines the nth channel estimation information matching the type of the object positioning method according to the information indicating the type of the object positioning method, and reports the nth channel estimation information to the LMF.
  • the LMF may determine the type of parameters indicated by the N pieces of channel estimation information to be acquired according to the type of the target positioning method, and the parameter type matches the type of the target positioning method. Further, the LMF may include N parameter types indicated by the channel estimation information in the second request information. The second device reports the nth channel estimation information to the LMF according to the parameter type indicated by the N pieces of channel estimation information.
  • the parameter types indicated by each channel estimation information in the N pieces of channel estimation information are the same.
  • the following takes the parameter type indicated by the nth channel estimation information as an example to illustrate the parameter types indicated by the nth channel estimation information corresponding to different types of positioning methods.
  • the nth channel estimation information is used to indicate the channel information of the channel between the nth cell node and the terminal device.
  • the nth channel estimation information is used to indicate the measurement amount, and the measurement amount includes one or more parameters in the following: the nth cell node and the The distance between terminal devices; the signal transmission delay or signal transmission delay difference between the nth cell node and the terminal device; the signal departure angle or signal arrival angle corresponding to the nth cell node; Signal quality between the nth cell node and the terminal device.
  • the nth channel estimation information is used to indicate the channel information of the channel between the nth cell node and the terminal device and
  • the measurement amount includes one or more of the following parameters: the distance between the nth cell node and the terminal device; the signal transmission time between the nth cell node and the terminal device Delay or signal transmission delay difference; signal departure angle or signal arrival angle corresponding to the nth cell node; signal quality between the nth cell node and the terminal device.
  • the LMF locates the terminal device according to the N pieces of channel estimation information.
  • the positioning result may be determined with reference to the manner described in S904, which will not be repeated in this disclosure.
  • the LMF sends second information to the location requester, where the second information is used to indicate a positioning result.
  • the LMF may also send information used to indicate the target positioning method used to calculate the positioning result to the location requester.
  • Such a design can facilitate the position requester to refer to the information to select a positioning mode when requesting a position subsequently.
  • the location requester selects the positioning mode as the automatic switching mode, the type of the target locator fed back by the location requester is a non-AI positioning method, but the positioning result is very different from the positioning result predicted by the location requester based on other sensors. Then the location requester can re-request the location result obtained based on the AI location method.
  • the above-mentioned method provided by the present disclosure flexibly decides on the positioning method based on the requirements of the location requesting party, and realizes dynamic adjustment of the positioning method to match the actual communication environment in time, which is conducive to improving the accuracy of estimating the location of the terminal device.
  • the present disclosure provides a communication device 1400 , where the communication device 1400 includes a processing module 1401 and a communication module 1402 .
  • the communication device 1400 may be an LMF, or it may be a communication device that is applied to or matched with an LMF and can implement a communication method performed on the LMF side; or, the communication device 1400 may be a cell node, or it may be a cell node Or it can be used in conjunction with a cell node to implement a communication device that implements a communication method on the cell node side; or, the communication device 1400 can be a terminal device, or it can be applied to a terminal device or used in conjunction with a terminal device, and can implement a communication method on the terminal device side.
  • a communication device for performing a communication method may be a network element of the core network, or may be applied to a network element of the core network or matched with a network element of the core network, and can realize a communication method performed by the network element side of the core network communication device.
  • the communication module may also be referred to as a transceiver module, a transceiver, a transceiver, or a transceiver device and the like.
  • a processing module may also be called a processor, a processing board, a processing unit, or a processing device.
  • the communication module is used to perform the sending and receiving operations on the LMF side or the first device side in the above method.
  • the device used to implement the receiving function in the communication module can be regarded as a receiving unit, and the device used to implement the receiving function in the communication module can be regarded as a receiving unit.
  • a device with a sending function is regarded as a sending unit, that is, the communication module includes a receiving unit and a sending unit.
  • the processing module 1401 can be used to realize the processing function of the LMF in the embodiment shown in FIG. 9 or FIG. 12
  • the communication module 1402 can be used to realize the processing function described in the embodiment shown in FIG. Transceiver function of LMF.
  • the communication device can also be understood with reference to the third aspect in the summary of the invention and possible designs in the third aspect.
  • the processing module 1401 can be used to implement the processing functions of the core network element or terminal equipment in the embodiment shown in FIG. 9 or FIG. Or the sending and receiving function of the network element of the core network or the terminal device in the embodiment shown in FIG. 12 .
  • the communication device can also be understood with reference to the fourth aspect in the summary of the invention and possible designs in the fourth aspect.
  • the processing module 1401 can be used to realize the processing function of the cell node in the embodiment shown in FIG. 9 or FIG. 12
  • the communication module 1402 can be used to realize the small The sending and receiving function of the district node.
  • the aforementioned communication module and/or processing module may be realized by a virtual module, for example, the processing module may be realized by a software function unit or a virtual device, and the communication module may be realized by a software function or a virtual device.
  • the processing module or the communication module may also be implemented by a physical device, for example, if the device is implemented by a chip/chip circuit, the communication module may be an input and output circuit and/or a communication interface, and perform an input operation (corresponding to the aforementioned receiving operation), Output operation (corresponding to the aforementioned sending operation); the processing module is an integrated processor or a microprocessor or an integrated circuit.
  • each functional module in each embodiment of this disclosure can be integrated into a processor , can also be a separate physical existence, or two or more modules can be integrated into one module.
  • the above-mentioned integrated modules can be implemented in the form of hardware or in the form of software function modules.
  • the present disclosure also provides a communication device 1500 .
  • the communication device 1500 may be a chip or a chip system.
  • the system-on-a-chip may be constituted by chips, and may also include chips and other discrete devices.
  • the communication device 1500 may be used to implement the function of any network element in the communication system described in the foregoing embodiments.
  • the communication device 1500 may include at least one processor 1510, and the processor 1510 is coupled to a memory.
  • the memory may be located in the device, the memory may be integrated with the processor, or the memory may be located outside the device.
  • the communication device 1500 may further include at least one memory 1520 .
  • the memory 1520 stores necessary computer programs, computer programs or instructions and/or data for implementing any of the above embodiments; the processor 1510 may execute the computer programs stored in the memory 1520 to complete the method in any of the above embodiments.
  • the communication device 1500 may further include a communication interface 1530, and the communication device 1500 may perform information exchange with other devices through the communication interface 1530.
  • the communication interface 1530 may be a transceiver, a circuit, a bus, a module, a pin or other types of communication interfaces.
  • the communication interface 1530 in the device 1500 can also be an input and output circuit, which can input information (or call it receiving information) and output information (or call it sending information)
  • the processor is an integrated processor or a microprocessor or an integrated circuit or a logic circuit, and the processor can determine output information according to input information.
  • the coupling in the present disclosure is an indirect coupling or communication connection between devices, units or modules, which may be in electrical, mechanical or other forms, and is used for information exchange between devices, units or modules.
  • the processor 1510 may cooperate with the memory 1520 and the communication interface 1530 .
  • the specific connection medium among the processor 1510, the memory 1520, and the communication interface 1530 is not limited in the present disclosure.
  • the bus 1540 may be a peripheral component interconnect standard (peripheral component interconnect, PCI) bus or an extended industry standard architecture (extended industry standard architecture, EISA) bus or the like.
  • PCI peripheral component interconnect
  • EISA extended industry standard architecture
  • the bus can be divided into address bus, data bus, control bus and so on. For ease of representation, only one thick line is used in FIG. 15 , but it does not mean that there is only one bus or one type of bus.
  • a processor may be a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, and may implement or execute the present invention.
  • a general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method disclosed in conjunction with the present disclosure may be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in the processor.
  • the memory may be a non-volatile memory, such as a hard disk (hard disk drive, HDD) or a solid-state drive (solid-state drive, SSD), etc., or a volatile memory (volatile memory), such as random memory Access memory (random-access memory, RAM).
  • a memory is, but is not limited to, any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
  • the memory in the present disclosure may also be a circuit or any other device capable of implementing a storage function for storing program instructions and/or data.
  • the communication device 1500 can be applied to a terminal device, and the specific communication device 1500 can be a terminal device, or can support a core network element or a terminal device, to implement any of the above-mentioned embodiments.
  • the memory 1520 stores computer programs (or instructions) and/or data for realizing the functions of the terminal device in any of the foregoing embodiments.
  • the processor 1510 may execute the computer program stored in the memory 1520 to complete the method performed by the terminal device in any of the foregoing embodiments.
  • the communication interface in the communication apparatus 1500 can be used to interact with the LMF, send information to the LMF or receive information from the LMF.
  • the communication device 1500 can be applied to a cell node, and the specific communication device 1500 can be a cell node, or can support a core network element or a cell node, to implement any of the above-mentioned embodiments.
  • the memory 1520 stores computer programs (or instructions) and/or data for realizing the functions of the cell node in any of the above embodiments.
  • the processor 1510 may execute the computer program stored in the memory 1520 to complete the method performed by the cell node in any of the foregoing embodiments.
  • the communication interface in the communication device 1500 can be used to interact with the LMF, send information to the LMF or receive information from the LMF.
  • the communication device 1500 can be applied to a core network element, and the specific communication device 1500 can be a core network element, or can support a core network element or a core network element, so as to realize the above-mentioned An apparatus that functions as a network element of the core network in any of the embodiments.
  • the memory 1520 stores computer programs (or instructions) and/or data for realizing the functions of the network elements of the core network in any of the foregoing embodiments.
  • the processor 1510 may execute the computer program stored in the memory 1520 to complete the method performed by the network element of the core network in any of the foregoing embodiments.
  • the communication interface in the communication device 1500 can be used to interact with the LMF or the cell node, send information to the LMF or receive information from the cell node.
  • the communication device 1500 may be applied to LMF, and the specific communication device 1500 may be an LMF, or a device capable of supporting LMF and realizing the function of LMF in any of the above-mentioned embodiments.
  • the memory 1520 stores computer programs (or instructions) and/or data implementing the functions of the LMF in any of the above-mentioned embodiments.
  • the processor 1510 may execute the computer program stored in the memory 1520 to complete the method performed by the LMF in any of the foregoing embodiments.
  • the communication interface in the communication device 1500 can be used to interact with terminal equipment, cell nodes, core network elements, etc., such as sending information to terminal equipment, cell nodes, or core network elements or receiving information from terminal equipment, cell nodes, etc. Information about nodes or core network elements.
  • the communication device 1500 provided in this embodiment can be applied to a terminal device, a cell node or a core network element to complete the method performed by the terminal device, a cell node or a core network element, or applied to an LMF to complete the method performed by the LMF. Therefore, the technical effect that it can obtain can refer to the above method examples, and will not be repeated here.
  • the present disclosure provides a communication system, including a terminal device, a cell node, and an LMF.
  • a terminal device including a terminal device, a cell node, and an LMF.
  • core network elements are also included.
  • the terminal device, cell node or core network element and LMF may implement the communication method provided in the embodiment shown in FIG. 9 or FIG. 12 .
  • the present disclosure also provides a computer program.
  • the computer program When the computer program is run on a computer, the computer is executed from the perspective of a cell node, a terminal device, a core network element, or an LMF. 12 or the communication method provided in the embodiment shown in FIG. 13 .
  • the present disclosure also provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a computer, the computer can read from a cell node, a terminal device, a core network From the perspective of a network element or an LMF, the communication method provided in the embodiment shown in FIG. 9 , FIG. 12 or FIG. 13 is executed.
  • the storage medium may be any available medium that can be accessed by a computer.
  • Computer-readable media may include RAM, read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), CD- ROM or other optical disk storage, magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
  • the present disclosure also provides a chip, the chip is used to read the computer program stored in the memory, and execute the program shown in Figure 9, Figure 12 or The communication method provided in the embodiment shown in FIG. 13 .
  • the present disclosure provides a chip system
  • the chip system includes a processor, and is used to support a computer device to implement the cell node, terminal equipment, core network element or Functions involved in LMF.
  • the chip system further includes a memory, and the memory is used to store necessary programs and data of the computer device.
  • the system-on-a-chip may consist of chips, or may include chips and other discrete devices.
  • the technical solution provided by the present disclosure may be fully or partially realized by software, hardware, firmware or any combination thereof.
  • software When implemented using software, it may be implemented in whole or in part in the form of a computer program product.
  • the computer program product includes one or more computer instructions.
  • the computer program instructions When the computer program instructions are loaded and executed on a computer, the processes or functions according to the present disclosure are produced in whole or in part.
  • the computer may be a general computer, a dedicated computer, a computer network, an LMF, a terminal device, a cell node, a core network element or other programmable devices.
  • the computer instructions may be stored in or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from a website, computer, server or data center Transmission to another website site, computer, server or data center by wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.).
  • the computer-readable storage medium may be any available medium that can be accessed by a computer, or a data storage device such as a server or a data center integrated with one or more available media.
  • the available medium may be a magnetic medium (for example, a floppy disk, a hard disk, or a magnetic tape), an optical medium (for example, a digital video disc (digital video disc, DVD)), or a semiconductor medium.
  • the various embodiments can refer to each other, for example, the methods and/or terms between the method embodiments can refer to each other, such as the functions and/or terms between the device embodiments
  • Mutual references can be made, for example, functions and/or terms between the apparatus embodiment and the method embodiment can be referred to each other.

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Abstract

本公开提供一种通信方法及装置，能够实现灵活定位，提升定位的准确性。该方法包括：获取M个信道估计信息，M个信道估计信息中的第m个信道估计信息是M个小区节点中第m个小区节点与终端设备之间的信道的估计信息；其中，M为正整数，m为取遍1至M的正整数；根据M个信道估计信息，确定目标定位方式的类型；根据目标定位方式的类型，获取N个信道估计信息，N个信道估计信息用于终端设备的定位；其中，N个信道估计信息中的第n个信道估计信息是N个小区节点中第n个小区节点与终端设备之间的信道的估计信息；N个小区节点包含于M个小区节点，N为小于等于M的正整数，n为取遍1至N的正整数。

Description

一种通信方法及装置
相关申请的交叉引用
本申请要求在2022年02月25日提交中华人民共和国知识产权局、申请号为202210179627.2、申请名称为“一种通信方法及装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本公开涉及通信技术领域，尤其涉及一种通信方法及装置。
背景技术
在无线通信网络中，例如在移动通信网络中，网络支持的业务越来越多样，因此需要满足的需求也越来越多样。例如，网络需要能够支持超高速率、超低时延、和/或超大连接，该特点使得网络规划、网络配置、和/或资源调度越来越复杂。此外，由于网络的功能越来越强大，例如支持的频谱越来越高、支持高阶多入多出(multiple input multiple output，MIMO)技术、支持波束赋形、和/或支持波束管理等新技术，使得网络节能成为了热门研究课题。这些新需求、新场景和新特性给网络规划、运维和高效运营带来了前所未有的挑战。为了迎接该挑战，可以将人工智能技术引入无线通信网络中，从而实现网络智能化。基于此，如何在网络中有效地实现人工智能是一个值得研究的问题。
发明内容
本公开提供一种通信方法及装置，以期利用人工智能实现灵活定位，提升定位的准确性。
第一方面，本公开提供一种通信方法，该方法可以由定位服务器执行，或定位服务器中的处理器等执行，定位服务器可以是位置管理服务功能(location management function，LMF)网元等。包括：获取M个信道估计信息，所述M个信道估计信息中的第m个信道估计信息是M个小区节点中第m个小区节点与终端设备之间的信道的估计信息；其中，M为正整数，m为取遍1至M的正整数；根据所述M个信道估计信息，确定目标定位方式的类型；根据所述目标定位方式的类型，获取N个信道估计信息，所述N个信道估计信息用于所述终端设备的定位；其中，所述N个信道估计信息中的第n个信道估计信息是N个小区节点中第n个小区节点与所述终端设备之间的信道的估计信息；所述N个小区节点包含于所述M个小区节点，N为小于等于M的正整数，n为取遍1至N的正整数。
上述设计中，基于小区节点与终端设备的估计信息决策目标定位方式，再按照目标定位方式选取多个小区节点与终端设备之间的估计信息进行终端设备的定位，能够实时匹配通信环境，灵活切换定位方式，有助于提升定位的准确性。
在一种可能的设计中，还包括：获取定位要求，所述定位要求用于获取用于确定所述目标定位方式的类型的所述M个信道估计信息；所述定位要求用于指示定位指标需要符合的取值条件，所述M个信道估计信息能够用于确定所述定位指标的取值。这样的设计，能 够保证选择的目标定位方式满足定位要求。
在一种可能的设计中，还包括：发送第一请求信息，所述第一请求信息用于请求所述M个信道估计信息，所述第一请求信息包括用于指示所述定位要求或者所述定位指标的信息。通过这样的设计，提供信道估计信息的设备可以得知M个信道估计信息应当指示的参数类型，有助于提升确定目标定位方式的效率。
在一种可选的设计中，所述定位指标可以包括以下中的一种或多种：所述小区节点和所述终端设备之间的通信路径的类型，所述通信路径的类型包括直射路径或非直射路径；至少一种类型的定位方式对应的定位精度。
在一种可选的设计中，所述目标定位方式的类型对应第一值时，所述N个信道估计信息中的第n个第二信道估计信息用于指示以下中的一个或多个参数：所述第n个小区节点与所述终端设备之间的距离；所述第n个小区节点与所述终端设备之间的信号传输时延或信号传输时延差；所述第n个小区节点对应的信号出发角度或信号到达角度。或者，所述目标定位方式的类型对应第二值时，所述N个信道估计信息中的第n个第二信道估计信息用于指示所述第n个小区节点与所述终端设备之间的信道的信道信息。
在这样的设计中，获取与目标定位方式的类型匹配的信道估计信息，便于后续目标定位方式的实施。
在一种可选的设计中，所述根据所述目标定位方式的类型，获取N个信道估计信息，包括：发送第二请求信息，所述第二请求信息用于请求所述N个信道估计信息，所述第二请求信息包括用于指示所述目标定位方式的类型的信息；接收所述N个信道估计信息。通过这样的设计，提供信道估计信息的设备可以得知N个信道估计信息应当指示的参数类型，有助于提升实施目标定位方式的效率。
在一种可选的设计中，还包括：在设定时间段内，根据所述N个信道估计信息对所述终端设备进行定位。通过设置目标定位方式的有效使用时长，实现周期性地对于定位方式的调整，动态匹配通信环境，使得对终端设备的定位更为灵活。
第二方面，本公开提供一种通信方法，包括：发送M个信道估计信息，所述M个信道估计信息用于确定目标定位方式的类型；其中，所述M个信道估计信息中的第m个信道估计信息是M个小区节点中第m个小区节点与终端设备之间的信道的估计信息，M为正整数，m为取遍1至M的正整数；获取用于请求N个信道估计信息的第二请求信息，所述第二请求信息包括用于指示所述目标定位方式的类型的信息；发送所述N个信道估计信息，所述N个信道估计信息用于所述终端设备的定位；其中，所述N个信道估计信息中的第n个信道估计信息是N个小区节点中第n个小区节点与所述终端设备之间的信道的估计信息；所述N个小区节点包含于所述M个小区节点，N为小于等于M的正整数，n为取遍1至N的正整数。
在一种可选的设计中，还包括：获取第一请求信息，所述第一请求信息用于请求所述M个信道估计信息，所述第一请求信息包括用于指示定位要求或者定位指标的信息；其中，所述定位要求用于指示所述定位指标需要符合的取值条件，所述M个信道估计信息能够用于确定所述定位指标的取值。
在一种可选的设计中，所述定位指标包括以下中的一种或多种：所述小区节点和所述终端设备之间的通信路径的类型，所述通信路径的类型包括直射路径或非直射路径；至少一种类型的定位方式对应的定位精度。
在一种可选的设计中，所述目标定位方式的类型对应第一值时，所述N个信道估计信息中的第n个信道估计信息用于指示以下中的一个或多个参数：所述第n个小区节点与所述终端设备之间的距离；所述第n个小区节点与所述终端设备之间的信号传输时延或信号传输时延差；所述第n个小区节点对应的信号出发角度或信号到达角度。
在一种可选的设计中，所述目标定位方式的类型对应第二值时，所述N个信道估计信息中的第n个信道估计信息用于指示所述第n个小区节点与所述终端设备之间的信道的信道信息。
第三方面，本公开提供一种通信装置，该通信装置可以是位置管理服务功能(location management function，LMF)网元，如下简称LMF；也可以是LMF中的装置，或者是能够和LMF匹配使用的装置。一种设计中，该通信装置可以包括执行第一方面中所描述的方法/操作/步骤/动作所一一对应的模块，该模块可以是硬件电路，也可是软件，也可以是硬件电路结合软件实现。一种设计中，该通信装置可以包括处理模块和通信模块。
一种示例：
通信模块，用于获取M个信道估计信息，所述M个信道估计信息中的第m个信道估计信息是M个小区节点中第m个小区节点与终端设备之间的信道的估计信息；其中，M为正整数，m为取遍1至M的正整数；
处理模块，用于根据所述M个信道估计信息，确定目标定位方式的类型；
处理模块，还用于根据所述目标定位方式的类型，控制通信模块获取N个信道估计信息，所述N个信道估计信息用于所述终端设备的定位；其中，所述N个信道估计信息中的第n个信道估计信息是N个小区节点中第n个小区节点与所述终端设备之间的信道的估计信息；所述N个小区节点包含于所述M个小区节点，N为小于等于M的正整数，n为取遍1至N的正整数。
在一种可能的设计中，通信模块，还用于获取定位要求，所述定位要求用于获取用于确定所述目标定位方式的类型的所述M个信道估计信息；所述定位要求用于指示定位指标需要符合的取值条件，所述M个信道估计信息能够用于确定所述定位指标的取值。
在一种可能的设计中，通信模块，还用于：发送第一请求信息，所述第一请求信息用于请求所述M个信道估计信息，所述第一请求信息包括用于指示所述定位要求或者所述定位指标的信息。
在一种可选的设计中，所述定位指标包括以下中的一种或多种：所述小区节点和所述终端设备之间的通信路径的类型，所述通信路径的类型包括直射路径或非直射路径；至少一种类型的定位方式对应的定位精度。
在一种可选的设计中，所述目标定位方式的类型对应第一值时，所述N个信道估计信息中的第n个第二信道估计信息用于指示以下中的一个或多个参数：所述第n个小区节点与所述终端设备之间的距离；所述第n个小区节点与所述终端设备之间的信号传输时延或信号传输时延差；所述第n个小区节点对应的信号出发角度或信号到达角度。或者，所述目标定位方式的类型对应第二值时，所述N个信道估计信息中的第n个第二信道估计信息用于指示所述第n个小区节点与所述终端设备之间的信道的信道信息。
在一种可选的设计中，处理模块，还用于：通过通信模块发送第二请求信息，所述第二请求信息用于请求所述N个信道估计信息，所述第二请求信息包括用于指示所述目标定位方式的类型的信息；通过通信模块接收所述N个信道估计信息。
在一种可选的设计中，处理模块，还用于在设定时间段内，根据所述N个信道估计信息对所述终端设备进行定位。
第四方面，本公开提供一种通信装置，该通信装置可以是终端设备或核心网设备；也可以是终端设备或核心网设备中的装置，或者是能够和终端设备匹配使用或和核心网设备匹配使用的装置。一种设计中，该通信装置可以包括执行第二方面中所描述的方法/操作/步骤/动作所一一对应的模块，该模块可以是硬件电路，也可是软件，也可以是硬件电路结合软件实现。一种设计中，该通信装置可以包括处理模块和通信模块。
一种示例：
通信模块，用于发送M个信道估计信息，所述M个信道估计信息用于确定目标定位方式的类型；其中，所述M个信道估计信息中的第m个信道估计信息是M个小区节点中第m个小区节点与终端设备之间的信道的估计信息，M为正整数，m为取遍1至M的正整数；
通信模块，还用于获取用于请求N个信道估计信息的第二请求信息，所述第二请求信息包括用于指示所述目标定位方式的类型的信息；
处理模块，用于通过通信模块发送所述N个信道估计信息，所述N个信道估计信息用于所述终端设备的定位；其中，所述N个信道估计信息中的第n个信道估计信息是N个小区节点中第n个小区节点与所述终端设备之间的信道的估计信息；所述N个小区节点包含于所述M个小区节点，N为小于等于M的正整数，n为取遍1至N的正整数。
在一种可选的设计中，通信模块，还用于获取第一请求信息，所述第一请求信息用于请求所述M个信道估计信息，所述第一请求信息包括用于指示定位要求或者定位指标的信息；其中，所述定位要求用于指示所述定位指标需要符合的取值条件，所述M个信道估计信息能够用于确定所述定位指标的取值。处理模块，还用于根据所述第一请求信息，确定所述M个信道估计信息。
在一种可选的设计中，所述定位指标包括以下中的一种或多种：所述小区节点和所述终端设备之间的通信路径的类型，所述通信路径的类型包括直射路径或非直射路径；至少一种类型的定位方式对应的定位精度。
在一种可选的设计中，所述目标定位方式的类型对应第一值时，所述N个信道估计信息中的第n个信道估计信息用于指示以下中的一个或多个参数：所述第n个小区节点与所述终端设备之间的距离；所述第n个小区节点与所述终端设备之间的信号传输时延或信号传输时延差；所述第n个小区节点对应的信号出发角度或信号到达角度。
在一种可选的设计中，所述目标定位方式的类型对应第二值时，所述N个信道估计信息中的第n个信道估计信息用于指示所述第n个小区节点与所述终端设备之间的信道的信道信息。
第五方面，本公开提供一种通信装置，所述通信装置包括处理器，用于实现上述第一方面所描述的方法。处理器与存储器耦合，存储器用于存储指令和数据，所述处理器执行所述存储器中存储的指令时，可以实现上述第一方面描述的方法。可选的，所述通信装置还可以包括存储器；所述通信装置还可以包括通信接口，所述通信接口用于该装置与其它设备进行通信，示例性的，通信接口可以是收发器、电路、总线、模块、管脚或其它类型的通信接口。
在一种可能的设备中，该通信装置包括处理器，用于利用通信接口获取M个信道估计 信息，所述M个信道估计信息中的第m个信道估计信息是M个小区节点中第m个小区节点与终端设备之间的信道的估计信息；其中，M为正整数，m为取遍1至M的正整数；
以及根据所述M个信道估计信息，确定目标定位方式的类型；并根据所述目标定位方式的类型，获取N个信道估计信息，所述N个信道估计信息用于所述终端设备的定位；其中，所述N个信道估计信息中的第n个信道估计信息是N个小区节点中第n个小区节点与所述终端设备之间的信道的估计信息；所述N个小区节点包含于所述M个小区节点，N为小于等于M的正整数，n为取遍1至N的正整数。
第六方面，本公开提供一种通信装置，所述通信装置包括处理器，用于实现上述第二方面所描述的方法。处理器与存储器耦合，存储器用于存储指令和数据，所述处理器执行所述存储器中存储的指令时，可以实现上述第二方面描述的方法。可选的，所述通信装置还可以包括存储器；所述通信装置还可以包括通信接口，所述通信接口用于该装置与其它设备进行通信，示例性的，通信接口可以是收发器、电路、总线、模块、管脚或其它类型的通信接口。
在一种可能的设备中，该通信装置包括处理器，用于利用通信接口发送M个信道估计信息，所述M个信道估计信息用于确定目标定位方式的类型；其中，所述M个信道估计信息中的第m个信道估计信息是M个小区节点中第m个小区节点与终端设备之间的信道的估计信息，M为正整数，m为取遍1至M的正整数；以及利用通信接口获取用于请求N个信道估计信息的第二请求信息，所述第二请求信息包括用于指示所述目标定位方式的类型的信息；并利用通信接口发送所述N个信道估计信息，所述N个信道估计信息用于所述终端设备的定位；其中，所述N个信道估计信息中的第n个信道估计信息是N个小区节点中第n个小区节点与所述终端设备之间的信道的估计信息；所述N个小区节点包含于所述M个小区节点，N为小于等于M的正整数，n为取遍1至N的正整数。
第七方面，本公开提供了一种通信系统，包括如第三方面或第五方面中所描述的通信装置；以及，如第四方面或第六方面中所描述的通信装置。
第八方面，本公开还提供了一种计算机程序，当所述计算机程序在计算机上运行时，使得所述计算机执行上述第一方面或第二方面提供的方法。
第九方面，本公开还提供了一种计算机程序产品，包括指令，当所述指令在计算机上运行时，使得计算机执行上述第一方面或第二方面提供的方法。
第十方面，本公开还提供了一种计算机可读存储介质，所述计算机可读存储介质中存储有计算机程序或指令，当所述计算机程序或者指令在计算机上运行时，使得所述计算机执行上述第一方面或第二方面中提供的方法。
第十一方面，本公开还提供了一种芯片，所述芯片用于读取存储器中存储的计算机程序，执行上述第一方面或第二方面中提供的方法。
第十二方面，本公开还提供了一种芯片系统，该芯片系统包括处理器，用于支持计算机装置实现上述第一方面或第二方面中提供的方法。在一种可能的设计中，所述芯片系统还包括存储器，所述存储器用于保存该计算机装置必要的程序和数据。该芯片系统可以由芯片构成，也可以包含芯片和其他分立器件。
附图说明
图1A为本公开提供的通信系统的结构示意图之一；
图1B为本公开提供的通信系统的结构示意图之一；
图1C为本公开提供的通信系统的结构示意图之一；
图2为一种基于TDOA的定位方法的原理示意图；
图3为一种时域信道响应示意图；
图4为一种信号传输路径的结构示意图；
图5A为一种弱首径场景示意图；
图5B为一种NLOS径场景示意图；
图6为本公开提供的通信系统的结构示意图之一；
图7A为神经元结构的一种示意图；
图7B为神经网络的层关系的一种示意图；
图8A为一种基于AI的上行定位场景示意图；
图8B为另一种基于AI的上行定位场景示意图；
图9为本公开提供的通信方法的流程示意图之一；
图10为一种概率相关的定位精度示意图；
图11为一种自适应切换定位方式的流程示意图；
图12为本公开提供的通信方法的流程示意图之一；
图13为本公开提供的通信方法的流程示意图之一；
图14为本公开提供的通信装置的结构示意图之一；
图15为本公开提供的通信装置的结构示意图之一。
具体实施方式
为了使本公开的目的、技术方案和优点更加清楚，下面将结合附图对本公开作进一步地详细描述。
本公开如下涉及的至少一个(项)，指示一个(项)或多个(项)。多个(项)，是指两个(项)或两个(项)以上。“和/或”，描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。字符“/”一般表示前后关联对象是一种“或”的关系。另外，应当理解，尽管在本公开中可能采用术语第一、第二等来描述各对象、但这些对象不应限于这些术语。这些术语仅用来将各对象彼此区分开。
本公开如下描述中所提到的术语“包括”和“具有”以及它们的任何变形，意图在于覆盖不排他的包含。例如包含了一系列步骤或单元的过程、方法、系统、产品或设备没有限定于已列出的步骤或单元，而是可选地还包括其他没有列出的步骤或单元，或可选地还包括对于这些过程、方法、产品或设备固有的其它步骤或单元。需要说明的是，本公开中，“示例性的”或者“例如”等词用于表示作例子、例证或说明。本公开中被描述为“示例性的”或者“例如”的任何方法或设计方案不应被解释为比其它方法或设计方案更优选或更具优势。确切而言，使用“示例性的”或者“例如”等词旨在以具体方式呈现相关概念。
本公开提供的技术可以应用于各种通信系统，例如，该通信系统可以是第三代(3th generation，3G)通信系统(例如通用移动通信系统(universal mobile telecommunication system，UMTS))、第四代(4th generation，4G)通信系统(例如长期演进(long term evolution，LTE)系统)、第五代(5th generation，5G)通信系统、全球互联微波接入(worldwide interoperability  for microwave access，WiMAX)或者无线局域网(wireless local area network，WLAN)系统、或者多种系统的融合系统，或者是未来的通信系统，例如第六代(6th generation，6G)通信系统等。其中，5G通信系统还可以称为新无线(new radio，NR)系统。通信系统中的一个网元可以向另一个网元发送信号或从另一个网元接收信号。其中信号可以包括信息、信令或者数据等。其中，网元也可以被替换为实体、网络实体、设备、通信设备、通信模块、节点、通信节点等等，本公开中以网元为例进行描述。
例如，通信系统可以包括至少一个终端设备和至少一个接入网设备，接入网设备可以向终端设备发送下行信号，和/或终端设备可以向接入网设备发送上行信号；此外可以理解的是，若通信系统中包括多个终端设备，多个终端设备之间也可以互发信号，即信号的发送网元和信号的接收网元均可以是终端设备。
参见图1A示意一种通信系统100，作为示例，该通信系统100包括接入网设备110、接入网设备120、接入网设备130以及终端设备140。终端设备140可以发送上行信号给接入网设备110、接入网设备120以及接入网设备130中一个或多个接入网设备。接入网设备110、接入网设备120以及接入网设备130中一个或多个接入网设备可以向终端设备140发送下行信号。
下面对图1A所涉及的终端设备和接入网设备进行详细说明。
(1)接入网设备
接入网设备可以为基站(base station，BS)。接入网设备还可以称为网络设备、接入节点(access node，AN)、无线接入节点(radio access node，RAN)。其中，基站可能有多种形式，比如宏基站、微基站、中继站或接入点等。接入网设备可以与核心网(如LTE的核心网或者5G的核心网等)连接，接入网设备可以为终端设备提供无线接入服务。接入网设备例如包括但不限于以下至少一个：5G中的基站，如发送接收点(Transmission Reception Point，TRP)或下一代节点B(generation nodeB，gNB)、开放无线接入网(open radio access network，O-RAN)中的接入网设备或者接入网设备包括的模块、演进型节点B(evolved node B，eNB)、无线网络控制器(radio network controller，RNC)、节点B(node B，NB)、基站控制器(base station controller，BSC)、基站收发台(base transceiver station，BTS)、家庭基站(例如，home evolved nodeB，或home node B，HNB)、基带单元(base band unit，BBU)、收发点(transmitting and receiving point，TRP)、发射点(transmitting point，TP)、和/或移动交换中心等。或者，接入网设备还可以是无线单元(radio unit，RU)、集中单元(centralized unit，CU)、分布单元(distributed unit,DU)、集中单元控制面(CU control plane，CU-CP)节点、或集中单元用户面(CU user plane，CU-UP)节点。或者，接入网设备可以为车载设备、可穿戴设备或者未来演进的公共陆地移动网络(public land mobile network，PLMN)中的接入网设备等。
本公开中，用于实现接入网设备功能的通信装置可以是接入网设备，也可以是具有接入网设备部分功能的网络设备，也可以是能够支持接入网设备实现该功能的装置，例如芯片系统，硬件电路、软件模块、或硬件电路加软件模块，该装置可以被安装在接入网设备中或者和接入网设备匹配使用。本公开的方法中，以用于实现接入网设备功能的通信装置是接入网设备为例进行描述。
(2)终端设备
终端设备又称之为终端、用户设备(user equipment，UE)、移动台(mobile station， MS)、移动终端(mobile terminal，MT)等。终端设备可以是一种向用户提供语音和/或数据连通性的设备。终端设备可通过接入网设备与一个或多个核心网进行通信。终端设备可以被部署在陆地上，包括室内、室外、手持、和/或车载；也可以被部署在水面上(如轮船等)；还可以被部署在空中(例如飞机、气球和卫星上等)。终端设备包括具有无线连接功能的手持式设备、连接到无线调制解调器的其他处理设备或车载设备等。终端设备可以是便携式、袖珍式、手持式、计算机内置的或者车载的移动装置。一些终端设备的举例为：个人通信业务(personal communication service，PCS)电话、无绳电话、会话发起协议(session initiation protocol，SIP)话机、无线本地环路(wireless local loop，WLL)站、个人数字助理(personal digital assistant，PDA)、无线网络摄像头、手机(mobile phone)、平板电脑、笔记本电脑、掌上电脑、移动互联网设备(mobile internet device，MID)、可穿戴设备如智能手表、虚拟现实(virtual reality，VR)设备、增强现实(augmented reality，AR)设备、工业控制(industrial control)中的无线终端、车联网系统中的终端、无人驾驶(self driving)中的无线终端、智能电网(smart grid)中的无线终端、运输安全(transportation safety)中的无线终端、智慧城市(smart city)中的无线终端如智能加油器，高铁上的终端设备以及智慧家庭(smart home)中的无线终端，如智能音响、智能咖啡机、智能打印机等。
本公开中，用于实现终端设备功能的通信装置可以是终端设备，也可以是具有终端部分功能的终端设备，也可以是能够支持终端设备实现该功能的装置，例如芯片系统，该装置可以被安装在终端设备中或者和终端设备匹配使用。本公开中，芯片系统可以由芯片构成，也可以包括芯片和其他分立器件。本公开提供的技术方案中，以用于实现终端设备功能的通信装置是终端设备或UE为例进行描述。
应理解，图1A所示的通信系统中各个设备的数量、类型仅作为示意，本公开并不限于此，实际应用中在通信系统中还可以包括更多的终端设备、更多的接入网设备，还可以包括其它网元，例如可以包括和核心网网元、和/或用于实现人工智能功能的网元。
本公开提供的方法涉及对终端设备的定位技术，参见图1B，在上述图1A所示的通信系统中引入了定位服务器150，该定位服务器150用于估算终端设备的位置。
具体地，图1B中的定位服务器150可以由LMF网元实现。参见图1C示意的一种通信系统，该通信系统中除包括接入网设备、终端设备之外，还包括核心网网元，如接入和移动管理功能(access and mobility management function，AMF)网元和位置管理服务功能(location management function，LMF)网元。在图1C示意的通信系统中，接入网设备可以是同一制式下的基站，也可以是不同网络制式下的基站。例如，图1C示意出一个5G基站，如gNB；以及一个可以接入5G核心网的4G基站，如ng-eNB。终端设备(图1C中以UE表示)和gNB之间可以通过NR-Uu接口进行通信，如利用NR-Uu接口传输定位相关的信令。终端设备和ng-eNB之间通过LTE-Uu接口进行通信，如利用LTE-Uu接口传输定位相关的信令。gNB和AMF之间通过NG-C接口进行通信，ng-eNB和AMF之间通过NG-C接口进行通信，例如NG-C接口可以用于传输定位相关的信令。AMF和LMF之间通过NL1接口进行通信，例如利用NL1接口传输定位相关的信令。
在一种对终端设备进行定位的方式中，定位服务器可以对终端设备和固定(即已知位置)的接入网设备之间的特征参数进行检测，获取终端设备和接入网设备之间的相对位置或角度信息，从而对终端设备的位置进行估算。其中，一些特征参数举例包括：信号质量、距离、信号传输时延(或称传播时间)或者时延差、信号出发角度、信号到达角度等；其 中，信号质量可以由信噪比、信号强度、信号场强、信号能量、信号接收功率等体现。
具体地，终端设备或者接入网设备中的一方发送参考信号；另一方测量参考信号获取信道信息，并根据该信道信息可以确定终端设备和接入网设备之间的特征参数，特征参数也可以被称为测量量，进而向LMF上报测量量。例如在下行定位场景中，接入网设备或者接入网设备的小区向终端设备发送定位参考信号(positioning reference signal，PRS)，终端设备测量PRS获取下行信道信息，进而终端设备根据该下行信道信息确定测量量，并将测量量上报给LMF用于终端设备的定位。例如在上行定位场景中，终端设备可以向接入网设备或接入网设备的小区发送探测参考信号(sounding reference signal，SRS)，接入网设备或接入网设备的小区测量SRS获取上行信道信息，进而接入网设备或接入网设备的小区根据该上行信道信息确定测量量，并将测量量上报给LMF用于终端设备的定位。下面举例介绍一些定位方法：
一种基于到达时间差(time difference of arrival，TDOA)的定位方法，可以利用同步的至少三个接入网设备的位置对终端设备进行定位。如图2所示，三个接入网设备分别标记为eNB1、eNB2、eNB3，该3个接入网设备和终端设备之间的距离分别为d1、d2、d3，对应信号的传播时间分别为t1、t2、t3。例如，3个接入网设备分别向终端设备发送PRS，分别记为P1，P2，和P3。可以设定eNB1为参考节点，终端设备可以测量P2和P1的到达时间差，即t2-t1，也称为参考信号时间差(reference signal time difference,RSTD)。终端设备利用t2-t1可以推断出d2-d1，并获得一条曲线使得该曲线上的每个点都满足到eNB2和eNB1的距离差为d2-d1；类似地，终端设备可以测量P3和P1的到达时间差，即t3-t1，利用t3-t1可以推断出d3-d1，并获得另一条曲线满足该曲线上的每个点都满足到eNB3和eNB1的距离差为d3-d1。终端设备利用上述两个曲线的交点，即可以确定自身的位置。或者，终端设备可以将不同接入网设备与终端设备之间的信号传播时间、到达时间差、距离或者推断的距离差中的至少一个参数上报给LMF，则LMF可以确定上述两个曲线，以及两个曲线的交点，从而确定终端设备的位置。另外，由于不同接入网设备之间存在一定的同步误差，对应获取的到达时间差可以表示为一个区间范围，如对应图2示意曲线所处的区间以虚线表示，得到终端设备的位置处于两曲线所在区间之间的重叠部分(以黑色示意)。
具体地，可采用如下公式计算终端设备的位置：
其中，(xi,yi)表示eNBi的位置坐标，i的取值为1、2或者3；(x,y)表示待求终端设备的位置坐标，c表示光速。
上述描述的基于TDOA的定位方法，是根据接入网设备向终端设备发送PRS来进行定位，这种定位方法也可以称为DL-TDOA或OTDOA。类似地，如果基于TDOA的定位方法是根据终端设备向接入网设备发送SRS来进行定位的方法，那么这种定位方法也可以称为UL-TDOA。
一种基于信号到达角度(angle of arrival,AoA)或信号出发角度(angle of departure,AoD)的定位方法，可以利用同步的至少两个接入网设备的位置对终端设备进行定位。其中，这里的信号是接入网设备和终端设备之间传输的信号，AoA以及AoD均为相当于接入网设 备来说的角度。即在根据接入网设备向终端设备发送PRS进行定位的场景中，可以由至少两个接入网设备向终端设备发送PRS，终端设备测量不同接入网设备发送的PRS确定各个接入网设备所对应的AoD，或者确定各个接入网设备对应的AoD与AoD参考值之间的角度差值。可选的，AoD参考值可以是至少两个接入网设备中一个接入网设备对应的AoD，或预设的AoD。终端设备将至少两个接入网设备对应的AoD或者角度差值上报给LMF，LMF可以根据至少两个接入网设备对应的AoD或者角度差值，确定终端设备的位置。在根据终端设备向接入网设备发送SRS进行定位的场景中，可以由终端设备向至少两个接入网设备发送SRS，不同接入网设备测量来自终端设备的SRS确定各个接入网设备所对应的AoA，或者确定各个接入网设备对应的AoA与AoA参考值之间的角度差值。可选的，AoA参考值可以是至少两个接入网设备中一个接入网设备对应的AoA，或预设的AoA。各个接入网设备将自身对应的AoA或者角度差值上报给LMF，LMF可以根据至少两个接入网设备对应的AoA或者角度差值，确定终端设备的位置。
在实施上述定位方法时，LMF可以预先与终端设备或接入网设备交互定位配置信息，以确定待定位的终端设备、参与终端设备定位的接入网设备、使用哪种定位方法、下行定位(即根据PRS进行定位)或者上行定位(根据SRS进行定位)、以及测量量等配置。下面以DL-TDOA方法为例，介绍在5G系统中基于LTE定位协议(LTE positioning protocol,LPP)的定位流程。其中，LPP协议规定了终端设备和LMF之间交互信息的流程，即终端设备和LMF之间可以通过LPP消息交互信息。需要说明的是，按照终端设备-接入网设备-AMF-LMF的方式相连，LPP消息跨接入网设备和AMF进行透明传输实现终端设备和LMF之间的交互。
首先，终端设备和LMF交互定位配置信息，定位配置信息包括定位能力和定位辅助信息，这个过程可以是LMF或者终端设备触发。例如，当LMF触发定位辅助信息传输时，LMF决定需要提供给终端设备的定位辅助信息，并且向终端设备发送一条LPP提供辅助数据(LPP Provide Assistance Data)消息。又如，当终端设备触发定位辅助信息传输时，终端设备首先确定需要的定位辅助信息，并向LMF发送一条LPP请求辅助数据(LPP Request Assistance Data)消息，该LPP请求辅助数据消息可以用于指示终端设备需要的定位辅助信息。LMF向终端设备发送LPP提供辅助数据消息，以提供终端设备需要的定位辅助信息。其中，定位能力表示终端设备支持的定位方法、采用的协议和流程、可配置的参数等信息；定位辅助信息包括以下一个或多个参数：终端设备所在的物理小区ID、全局小区ID、接入网设备的ID、接入网设备的PRS配置、接入网设备的同步信号块(synchronization signal/physical broadcast channel block，SSB)信息、PRS的空间方向信息、接入网设备的地理位置坐标、接入网设备和参考节点的时间差等信息。
其次，终端设备和LMF交互定位信息，即将终端设备测量各个接入网设备发送的PRS确定的测量量(或称，定位测量结果)反馈给LMF，这个过程可以由终端设备或LMF触发。例如，当LMF触发定位信息交互时，LMF向终端设备发送LPP请求定位信息(LPP Request Location Information)消息，该LPP请求定位信息消息用于指示LMF需要的定位测量结果，测量配置信息，要求的响应时间等信息。然后，终端设备在要求的响应时间之前向LMF发送LPP提供定位信息(LPP Provide Location Information)消息，以反馈测量量。当终端设备触发定位信息交互时，终端设备向LMF发送LPP提供定位信息消息，以反馈测量量。其中，测量量可以包括PRS的到达时间戳、PRS的传播时间、PRS对应的到 达时间差、PRS的接收信号功率等信息。此外，测量量还可以包括用于标识接入网设备的信息，例如包括不同测量量对应的物理小区ID、全局小区ID、接入网设备ID等。
除了终端设备和LMF之间需要交互定位辅助信息和定位信息以外，接入网设备和LMF之间也需要交互一些定位辅助信息，通常由LMF触发接入网设备和LMF之间交互定位辅助信息，相关流程由NR定位协议A(NR positioning protocol A,NRPPa)规定，接入网设备与LMF之间通过AMF相连，NRPPa协议对于AMF是透明的，NRPPa数据单元跨AMF透明传输使得接入网设备和LMF实现交互。接入网设备的定位辅助信息包括物理小区ID、全局小区ID、接入网设备的ID、接入网设备的PRS配置、接入网设备的SSB信息、PRS的空间方向信息、接入网设备的地理位置坐标等。LMF向接入网设备发送TRP信息请求(TRP Information Request)消息，TRP信息请求消息用于请求LMF需要的接入网设备的定位辅助信息，接入网设备向LMF发送TRP信息响应(TRP Information Response)消息，TRP信息响应消息用于指示LMF需要的确定需要的接入网设备的定位辅助信息，或者接入网设备向LMF发送TRP信息失败(TRP Information Failure)消息，TRP信息失败消息用于指示失败原因。
在实际场景下，由于噪声和干扰的影响，测量参考信号确定的信号传播时间或者相关角度可能存在一定的测量误差，对应的定位结果也会存在一定误差。例如，图3示意了测量参考信号得到的时域信道响应在不同时域采样点上的功率|h(t)|^2，开始一段时域采样点的信号功率较弱，对应的是噪声信号；中间有一段时域采样点的信号功率较强，对应的是实际信号的多径响应。即实际场景下，需要在存在干扰和噪声的环境下判断实际信号的起始位置，从而获得准确的信号传播时间或相关角度。确定实际信号的起始位置也称为首径识别问题。此外，参考信号分为由非直射路径(non-line of sight,NLOS)传播的信号或者由直射路径(line of sight,LOS)传播的信号。其中，接入网设备和终端设备之间的NLOS是指接入网和终端设备之间存在障碍物，使得信号不能直射传播，接入网设备和终端设备之间的LOS是指接入网和终端设备之间的信号是直射传播。例如图4示意，接入网设备和终端设备之间的LOS径(虚线)被树木遮挡，实际到达的是经过墙面反射的NLOS(实线)，NLOS径的距离大于LOS径的距离。在对终端设备进行定位时，如果将NLOS误认为是LOS，基于NLOS测量参考信号会对终端设备的定位造成较大的估计误差。
例如图5A示意的一种弱首径场景，由于首径强度弱于后面的时延径强度弱，被称之为弱首径。在传统的识别方法中会将实际的弱首径当作噪声，而将弱首径之后的一条径识别为首径，导致首径识别误差较大，降低定位的准确性。又如图5B示意的一种NLOS径场景，识别出的参考信号经由NLOS径传播，即经过反射到达的，经过的距离要比终端设备和接入网设备之间的LOS径所对应的直线距离长，这样会导致识别出的首径与LOS径对应的首径相差较大，如图5B示意，LOS径对应的首径在时延域上的位置提前于识别出的首径在时延域上的位置。可以看出利用测量量进行终端设备的定位的方式，在前述弱首径或NLOS径的场景中进行首径估计的误差很大，导致估计出的终端设备的位置误差也很大。
在另一种对终端设备进行定位的方式中，定位服务器可以获取终端设备和固定(即已知位置)的接入网设备之间的信道的信道信息，利用AI技术对获取的信道信息进行分析以估算终端设备的位置。具体地，终端设备或者接入网设备中的一方发送参考信号；另一方测量参考信号获取信道信息，进而向LMF上报信道信息。其中，信道信息可以是终端 设备或者接入网设备测量参考信号获取的信道响应，或者，也可以是基于信道响应的特征。可选的，基于信道响应的特征可以是经过归一化、截断等若干变换的信道响应，或者，基于信道响应的特征可以是从信道响应中提取的方差、均值等人工经验特征；或者，基于信道响应的特征可以是终端设备或者接入网设备利用AI技术从获取的信道响应提取的特征。
其中，AI可以通过各种可能的技术实现，例如通过机器学习(machine learning，ML)技术实现。在本公开中，前述通信系统也可以包括实现AI功能的网元。例如，可以在通信系统中已有网元内配置AI功能(如AI模块或者AI实体)来实现AI相关的操作。例如在5G新无线(new radio，NR)系统中，该已有网元可以是接入网设备(如gNB)、终端设备、核心网设备、或网管等。或者，也可以在通信系统中引入独立的网元来执行AI相关的操作。该独立的网元可以称为AI网元或者AI节点等，本公开对此名称不进行限制。在这种情况下，执行AI相关的操作的网元为内置AI功能(如AI模块或者AI实体)的网元。AI相关的操作还可以称为AI功能。AI功能的具体介绍请参见下文。AI网元可以与前述通信系统中包括的网元，如终端设备、接入网设备、核心网网元等建立通信连接。示例性的，参见图6，通信系统中包括终端设备、接入网设备、AMF网元、LMF网元，引入AI网元可以与终端设备、接入网设备、AMF网元、LMF网元之间建立通信连接。
为了便于理解，下面首先结合A1～A4，对本公开涉及的AI的部分用语进行介绍。可以理解的是，该介绍并不作为对本公开的限定。
A1，AI模型
AI模型是AI功能的具体实现，AI模型表征了模型的输入和输出之间的映射关系，可以指将某种维度的输入映射到某种维度的输出的函数模型。AI模型可以是神经网络或者其他机器学习模型，如决策树、支持向量机等。本公开中，可以将AI模型简称为模型。本公开中，AI功能可以包括以下至少一项：数据收集(收集训练数据和/或推理数据)、数据预处理、模型训练(或称，模型学习)、模型信息发布(配置模型信息)、模型推理、或推理结果发布。其中，推理又可以称为预测。本公开中，可以将AI模型简称为模型。
A2，机器学习
机器学习是实现人工智能的一种重要技术途径，如机器学习可以从原始数据中学习模型或规则，机器学习分为监督学习、非监督学习、强化学习。
监督学习依据已采集到的样本(或称样本值)和样本标签，利用机器学习算法学习样本到样本标签的映射关系，并用机器学习模型来表达学到的映射关系。训练机器学习模型的过程就是学习这种映射关系的过程。如信号检测中，样本为含噪声的接收信号，样本标签为该接收信号对应的真实星座点，机器学习期望通过训练学到样本与样本标签之间的映射关系。在训练时，通过计算模型的输出(即预测值)与样本标签的误差来优化模型参数。一旦映射关系学习完成，就可以利用学到的映射关系来预测每一个新样本的样本标签。监督学习学到的映射关系可以包括线性映射、非线性映射。根据样本标签的类型可将机器学习的任务分为分类任务和回归任务。
无监督学习依据采集到的样本，利用算法自行发掘样本的内在模式。无监督学习中有一类算法(如自编码器、对抗生成型网络等)可以将样本自身作为监督信号，模型学习从样本到样本的映射关系，训练时，通过计算模型的预测值与样本本身之间的误差来优化模型参数，实现自监督学习。自监督学习可用于信号压缩及解压恢复的应 用场景。
强化学习是一类通过与环境交互来学习解决问题的策略的算法。与监督学习、无监督学习不同，强化学习并没有明确的样本标签，算法需要与环境进行交互，获取环境反馈的奖励信号，进而调整决策动作以获得更大的奖励信号数值。如在下行功率控制中，强化学习模型根据无线网络反馈的系统总吞吐率，调整各个终端的下行发送功率，进而期望获得更高的系统吞吐率。强化学习的目标也是学习环境状态与最优决策动作之间的映射关系。强化学习的训练是通过与环境的迭代交互而实现的。
A3，神经网络
神经网络是AI或机器学习技术的一种具体实现形式。根据通用近似定理，神经网络在理论上可以逼近任意连续函数，从而使得神经网络具备学习任意映射的能力。传统的通信系统需要借助丰富的专家知识来设计通信模块，而基于神经网络的深度学习通信系统可以从大量的数据集中自动发现隐含的模式结构，建立数据之间的映射关系，获得优于传统建模方法的性能。
神经网络的思想来源于大脑组织的神经元结构。例如，每个神经元都对其输入值进行加权求和运算，通过一个激活函数输出运算结果。如图7A所示，为神经元结构的一种示意图。假设神经元的输入为x＝[x0,x1,…,xn]，与各个输入对应的权值分别为w＝[w,w1,…,wn]，其中，wi作为xi的权值，用于对xi进行加权。根据权值对输入值进行加权求和的偏置例如为b。激活函数的形式可以有多种，假设一个神经元的激活函数为：y＝f(z)＝max(0,z)，则该神经元的输出为： 再例如，一个神经元的激活函数为：y＝f(z)＝z，则该神经元的输出为：其中，b可以是小数、整数(例如0、正整数或负整数)、或复数等各种可能的取值。神经网络中不同神经元的激活函数可以相同或不同。
神经网络一般包括多个层，每层可包括一个或多个神经元。通过增加神经网络的深度和/或宽度，能够提高该神经网络的表达能力或称函数拟合能力，为复杂系统提供更强大的信息提取和抽象建模能力。其中，神经网络的深度可以是指神经网络包括的层数，其中每层包括的神经元个数可以称为该层的宽度。在一种实现方式中，神经网络包括输入层和输出层。神经网络的输入层将接收到的输入信息经过神经元处理，将处理结果传递给输出层，由输出层得到神经网络的输出结果。在另一种实现方式中，神经网络包括输入层、隐藏层和输出层，神经网络的输入层将接收到的输入信息经过神经元处理，将处理结果传递给中间的隐藏层，隐藏层对接收的处理结果进行计算，得到计算结果，隐藏层将计算结果传递给输出层或者相邻的隐藏层，最终由输出层得到神经网络的输出结果。其中，一个神经网络可以包括一个隐藏层，或者包括多个依次连接的隐藏层，不予限制。
如上述已经介绍，每个神经元都对其输入值做加权求和运算，并加权求和结果通过一个非线性函数产生输出。将神经网络中神经元加权求和运算的权值以及非线性函数称作神经网络的参数。以max{0,x}为非线性函数的神经元为例，做操作的神经元的参数为权值为w＝[w,w1,…,wn],其中，加权求和的偏置为b。一个神经网络所有神经元的参数构成这个神经网络的参数。
本公开涉及的神经网络例如深度神经网络(deep neural network,DNN)，DNN一般具有多个隐藏层，在DNN中每个神经元对应的权值即为DNN的模型参数。DNN可以使用监 督学习或非监督学习策略来优化模型参数。根据网络的构建方式，DNN可以包括前馈神经网络(feedforward neural network,FNN)、卷积神经网络(convolutional neural networks,CNN)和递归神经网络(recurrent neural network,RNN)。以FNN为例，参见图7B示意一种神经网络结构，FNN的特点为相邻层的神经元两两之间完全相连。
CNN可以应用于处理具有类似网格结构的数据。其中，具有类似网格结构的数据可以包括时间序列数据(时间轴离散采样)和图像数据(二维离散采样)等。CNN的卷积层并不一次性利用全部的输入信息做卷积运算，而是设定一个或多个固定大小的窗，采用各个窗截取部分输入信息做卷积运算。这样的设计可以较大程度地降低模型参数的计算量。具体地，针对一个或多个固定大小的窗中的任意一个窗做卷积运算，可以理解为以该窗的系数(如加权系数)和该窗所截取的部分输入信息进行先乘后加运算。卷积运算后可以得到该窗对应的输出信息。其中，不同窗的系数可以是独立配置的。例如，不同窗可以配置不同的系数，这可以使得CNN更好的提取输入数据的特征。窗的系数可以包括卷积核。可选的，不同窗截取的部分输入信息的类型可以不同，示例性的，同一副图中的人和物可以理解为不同类型的信息，在设定两个固定大小的窗中一个窗可以截取该图中的人，另一个窗可以截取该图中的物。
RNN是一种利用反馈时间序列信息的DNN网络。它的输入包括当前时刻的新的输入值和RNN在前一时刻的输出值中的部分，其中前一时刻的输出值可以由激活函数和前一时刻的输入所确定。RNN适合获取在时间上具有相关性的序列特征，适用于语音识别、信道编译码等应用场景。
另外，在神经网络的训练过程中，可以定义损失函数。损失函数描述了神经网络的输出值与理想目标值之间的差距或差异，本公开并不限制损失函数的具体形式。神经网络的训练过程就是通过调整神经网络的参数，使得损失函数的取值小于门限，或者使得损失函数的取值满足目标需求的过程。调整神经网络的参数，例如调整如下参数中的至少一种：神经网络的层数、宽度、神经元的权值、或、神经元的激活函数中的参数。
具体地，在下行定位场景中，接入网设备或者接入网设备的小区节点向终端设备发送PRS，终端设备测量PRS获取下行信道响应，进而终端设备可以将获取的下行信道响应上报给LMF，或者终端设备可以基于AI模型从获取的下行信道响应提取特征，并将该基于下行信道响应的特征上报给LMF。进而LMF可以根据AI模型和获取的下行信道响应或者基于下行信道响应的特征，确定终端设备的位置。例如在上行定位场景中，终端设备可以向接入网设备或接入网设备的小区节点发送SRS，接入网设备或接入网设备的小区测量SRS获取上行信道响应，进而接入网设备或接入网设备的小区节点可以将获取的上行信道响应上报给LMF；或者，接入网设备或接入网设备的小区节点也可以基于AI模型从获取的上行信道响应提取特征，并将该基于上行信道响应的特征上报给LMF。进而LMF可以根据AI模型和获取的上行信道响应或者基于上行信道响应的特征，确定终端设备的位置。
示例性的，如图8A示意一种基于AI的上行定位场景，可以将AI模型部署在LMF侧，多个接入网设备，即接入网设备1、接入网设备2、接入网设备3向LMF发送信道响应，LMF将多个接入网设备的信道响应作为AI模型的输入，输出终端设备的位置信息。假设接入网设备的天线数为16，子载波个数为4096，则每个接入网设备向LMF发送的信道响应包括16*4096个复数信息。
示例性的，如图8B示意另一种采基于AI的上行定位场景，可以将AI模型部署在接 入网设备以及LMF侧，多个接入网设备中每个接入网设备基于AI模型，将获取的信道响应作为该AI模型的输入，输出基于信道响应的特征，简称信道特征。进而，多个接入网设备中每个接入网设备向LMF发送信道特征；其中，信道特征的维度由接入网设备侧的AI模型的输出维度决定，例如接入网设备侧可以从维度为[16,4096]的信道响应中提取维度为[128]的信道特征，发送给LMF。LMF基于自身部署的AI模型，将多个接入网设备的信道特征作为AI模型的输入，输出终端设备的位置信息。假设接入网设备的天线数为16，子载波个数为4096，则每个接入网设备向LMF发送的信道响应包括16*4096个复数信息。
为便于理解，上述利用测量量对终端设备进行定位的方式也可以称作非AI定位方式，或者非AI定位模式。利用AI技术分析信道信息对终端设备进行定位的方式也可以称作AI定位方式，或者AI定位模式。且由上可知，在非AI定位方式中，如果存在首径较弱或者参考信号传播经由NLOS径的情况，识别出的首径与真实的首径之间差别很大，会使得估计得到终端设备的位置准确性较差。而在AI定位方式中，利用AI技术能够增强定位精度，但是涉及信道信息的传输开销较大，会造成空口资源的浪费。
基于此，本公开提供一种通信方法，能够用于终端设备的定位。在本公开中，可以动态切换符合定位精度要求的定位方式，实现定位方式的自适应调整，灵活地在定位精度和信息传输开销之间进行折中。
下面通过方案一～方案三对本公开提供的通信方法进行详细说明。
方案一
参见图9示意一种通信方法，该方法主要包括如下流程。
S901，LMF获取M个信道估计信息。
其中，所述M个信道估计信息中的第m个信道估计信息是M个小区节点中第m个小区节点与终端设备之间的信道的估计信息；其中，M为正整数，m为取遍1至M的正整数。M个信道估计信息用于确定目标定位方式的类型。
具体地，如图9示意，LMF可以从终端设备或者M个小区节点获取M个信道估计信息。其中，M个信道估计信息中的第m个信道估计信息可以来自于第m个小区节点或者终端设备。例如在上行定位场景中，由第m个小区节点向LMF发送第m个信道估计信息，或者第m个小区节点向其他的核心网网元发送第m个信道估计信息，前述其他的核心网网元将从M个小区节点获取的M个信道估计信息发送给LMF；在下行定位场景中，由终端设备向LMF发送第m个信道估计信息。可选的，M的取值可以由通信环境中能够参与对终端设备定位的小区节点数量确定，可能是1也可能是大于1的正整数，如2或3等等。
为便于理解，如下以第一设备表示M个小区节点中的第m个小区节点、终端设备或其他的核心网网元为例进行描述。第一设备可以主动向LMF发送第m个信道估计信息，该第m个信道估计信息可以是第一设备侧基于自身能力，测量小区节点与终端设备之间的信道能够得到的估计信息。可选的，可以由LMF或者第三方网元预配置有关M个信道估计信息的上报周期，使得第一设备可以周期性地上报第m个信道估计信息，从而触发LMF对于定位方式的调整。
可选的，可以预先在LMF、终端设备和小区节点中配置用于决策定位方式的定位要求。该定位要求用于指示定位指标需要满足的条件。第一设备在发送第m个信道估计信息时， 可以结合该定位要求确定第m个信道估计信息指示的参数类型，以确保发送的第m个信道估计信息能够参与确定该定位指标的取值。
S902，LMF根据所述M个信道估计信息，确定目标定位方式的类型。
具体地，LMF可以根据获取的M个信道估计信息，确定定位指标的取值；然后LMF根据定位指标的取值和定位要求，确定目标定位方式的类型。
下面对应S901中的描述，对定位指标和对应的目标定位方式的类型进行举例说明。
示例1，所述定位指标为所述小区节点和所述终端设备之间的通信路径的类型，所述通信路径的类型包括直射路径(LOS径)或非直射路径(NLOS径)。该定位指标对应的定位要求为：根据LOS径/NLOS径的数量判断是否开启AI模式，即是否使用AI定位方式。LMF可根据获取的M个信道估计信息，确定M个小区节点中每个小区节点和终端设备之前的通信路径的类型为LOS径还是NLOS径，进而确定其中LOS径的数量或者NLOS径的数量。
例如，当LOS径的数量大于或等于设定数量，或者占M个的比例大于或等于设定比例时，LMF可以确定目标定位方式的类型为非AI定位方式。
例如，当LOS径的数量小于设定数量，或者占M个的比例小于设定比例时，LMF可以确定目标定位方式的类型为开启AI定位模式。其中，开启AI定位模式分为AI定位方式，或者，AI定位方式结合非AI定位方式。
示例2，所述定位指标为当前使用的定位方式对应的定位精度。
该定位指标对应的定位要求为：对于定位精度的要求，或描述为定位方式所需要满足的定位精度要求。LMF可以根据获取的M个信道估计信息，确定当前使用的定位方式对应的定位精度，判断该定位精度是否符合位置请求方指定或预设的定位精度要求，进而根据判断结果确定目标定位方式的类型。
例如当前使用的定位方式为AI定位方式，若AI定位方式对应的定位精度不符合定位精度要求，则LMF可以确定目标定位方式的类型为非AI定位方式；若AI定位方式对应的定位精度符合定位精度要求，则LMF可以确定目标定位方式的类型为开启AI定位模式。可选的，关于开启AI定位模式具体是AI定位方式还是AI定位方式结合非AI定位方式，可以参照如下方式实施：当AI定位方式对应的定位精度与定位精度要求之间的差异大于或等于设定差异值时，LMF可以确定开启AI定位模式具体为AI定位方式；当AI定位方式对应的定位精度与定位精度要求之间的差异小于设定差异值时，LMF可以确定开启AI定位模式具体为AI定位方式和非AI定位方式结合。
又如当前使用的定位方式的类型为非AI定位方式，若非AI定位方式对应的定位精度符合定位精度要求，则LMF可以确定目标定位方式的类型为非AI定位方式，即保持当前使用的定位方式不变；若非AI定位方式对应的定位精度不符合定位精度要求，则LMF可以确定目标定位方式的类型为AI定位方式。
具体地，关于LMF确定非AI定位方式是否符合定位精度要求，可参照如下方式实施：
LMF可以根据获取的测量量的精度，来确定非AI定位方式是否符合定位精度要求。以图2示意的基于TDOA的定位方法为例，终端设备上报到达时间差时还可以上报一个用于指示测量该到达时间差的准确度的信息，例如OTDOA-MeasQuality，对应图2以虚线示意到达时间差的区间范围。进而LMF可以根据获取的多个到达时间差的区间范围之间的交集(即如图2示意的重叠部分)的范围大小，判断非AI定位方式的定位精度是否 满足定位精度要求。
关于LMF确定AI定位方式是否符合定位精度要求，可参照如下方式实施：
例如，AI定位方式对应的定位精度可以根据离线训练时统计误差确定。例如在离线训练时将数据集划分为训练集和验证集，将基于训练集训练好的AI模型，在验证集上进行测试，得到验证集上各个样本的误差，统计误差得到误差的累积分布函数(cumulative distribution function,CDF)，如图10所示，则可以得到不同概率的定位精度。例如90％对应的定位精度为0.57m等。
例如，AI定位方式对应的定位精度还可以由训练集样本之间的距离来确定，通常基于AI的定位依靠采集大量的指纹信息，即在某个区域内每隔某个距离放置一个信标，通过信标节点与基站之间发送参考信号，组成训练集的样本。因此信标节点的距离可以体现AI定位方式对应的定位精度。对于不同区域可以放置不同密度的信标，在使用AI定位方式时，LMF可以根据接收到的特征与数据库中的特征进行匹配确定终端设备所在的区域，从而可以得到该区域的定位精度，即AI定位方式对应的定位精度；进而判断AI定位方式的定位精度是否满足定位精度要求。
例如，LMF可以训练一个用于得到定位精度的AI模型，该AI模型的输入可以是信道响应、信道质量、天线配置、参考信号配置等中的一个或多个信息，输出为定位精度。
例如，也可以在LMF部署一个关系表，该关系表中存储信道响应、信道质量、天线配置、参考信号配置等中的一个或多个信息与定位精度之间的对应关系。即LMF在得到信道响应、信道质量、天线配置、参考信号配置等中的一个或多个信息时，可以从关系表中读取对应的定位精度。可选的，该关系表可以是根据离线训练数据统计得到的。
示例3，所述定位指标为AI定位方式对应的定位精度以及非AI定位方式对应的定位精度。
该定位指标对应的定位要求为按照AI定位方式与非AI定位方式之间的定位精度差异，判断是否开启AI模式。则LMF可以根据获取的M个信道估计信息，确定AI定位方式对应的定位精度以及非AI定位方式对应的定位精度。进而LMF可以根据AI定位方式与非AI定位方式之间的定位精度差异，确定目标定位方式的类型。
例如，当AI定位方式对应的定位精度高于非AI定位方式对应的定位精度时，LMF可以确定目标定位方式的类型为AI定位方式。或者，当非AI定位方式对应的定位精度高于AI定位方式对应的定位精度时，LMF可以确定目标定位方式的类型为非AI定位方式。或者，当非AI定位方式与AI定位方式之间的定位精度差异小于设定差异值时，LMF可以确定目标定位方式的类型为非AI定位方式，这是由于非AI定位方式是基于测量量进行定位，相较于基于信道信息进行定位的AI定位方式，可以节省传输开销。
S903，LMF根据目标定位方式的类型，获取N个信道估计信息。
其中，所述N个信道估计信息用于所述终端设备的定位；其中，所述N个信道估计信息中的第n个信道估计信息是N个小区节点中第n个小区节点与所述终端设备之间的信道的估计信息；所述N个小区节点包含于所述M个小区节点，N为大于1，且小于等于M的正整数，n为取遍1至N的正整数。
具体地，如图9示意，LMF可以从终端设备或者M个小区节点获取N个信道估计信息。其中，N个信道估计信息中第n个信道估计信息可以来自于M个小区节点包含的N个小区节点中的第n个小区节点或者终端设备。例如在上行定位场景中，由第n个小区节 点向LMF发送第n个信道估计信息，或者第n个小区节点向其他的核心网网元发送第n个信道估计信息，其他的核心网网元将获取的N个信道估计信息发送给LMF；在下行定位场景中，由终端设备向LMF发送第n个信道估计信息。可选的，对应S901～S902中描述的方案，如果定位要求涉及考虑通信路径的类型，当M个小区节点与终端设备之间的通信路径均为LOS径时，N等于M；或者，当M个小区节点中部分小区节点与终端设备之间的通信路径为LOS径时，N的取值与M个小区中对应LOS径的部分小区节点的数量相同。如果定位要求不涉及考虑通信路径的类型，则N可以等于M，或者满足能够参与终端设备的定位需要的小区节点的数量即可。
为便于理解，如下以第二设备表示N个小区节点中的第n个小区节点、终端设备或其他的核心网设备为例进行描述，LMF可参照如下方式，从第二设备获取第n个信道估计信息。
LMF在确定目标定位方式的类型后，可以向第二设备发送第二请求信息，该第二请求信息用于请求对终端设备进行定位所需的信道估计信息，即前述N个信道估计信息。第二设备响应于第二请求信息，向LMF发送第n个信道估计信息。
一种可选的实施方式中，LMF可以在第二请求信息中包括用于指示目标定位方式的类型的信息。第二设备根据用于指示目标定位方式的类型的信息，确定与目标定位方式的类型匹配的第n个信道估计信息，并将第n个信道估计信息上报给LMF。
另一种可选的实施方式中，LMF可以根据目标定位方式的类型，确定希望获取的N个信道估计信息指示的参数类型，该参数类型与目标定位方式的类型匹配。进而LMF可以在第二请求信息中包括N个信道估计信息指示的参数类型。第二设备根据该N个信道估计信息指示的参数类型，上报第n个信道估计信息给LMF。此外需要说明的是，N个信道估计信息中各个信道估计信息指示的参数类型均相同。由于N个小区节点包含于M个小区节点，本公开中存在第二设备与第一设备表示同一个小区节点的情况。
示例性的，如果所述目标定位方式的类型对应第一值，即目标定位方式的类型为非AI定位方式，则所述N个第二信道估计信息中的第n个第二信道估计信息用于指示测量量，测量量包括以下中的一个或多个参数：所述第n个小区节点与所述终端设备之间的距离；所述第n个小区节点与所述终端设备之间的信号传输时延或信号传输时延差；所述第n个小区节点对应的信号出发角度或信号到达角度；所述第n个小区节点与所述终端设备之间的信号质量。
示例性的，如果所述目标定位方式的类型对应第二值，即目标定位方式的类型为AI定位方式，则所述N个第二信道估计信息中的第n个第二信道估计信息用于指示所述第n个小区节点与所述终端设备之间的信道的信道信息。
示例性的，如果所述目标定位方式的类型对应第三值，即目标定位方式的类型为AI定位方式与非AI定位方式结合，则所述N个第二信道估计信息中的第n个第二信道估计信息用于指示所述第n个小区节点与所述终端设备之间的信道的信道信息以及测量量，测量量包括的参数可参照前述示例的定义理解，本公开对此不予限制。
S904，LMF根据所述N个信道估计信息，对所述终端设备进行定位。
具体地，如果目标定位方式的类型为AI定位方式，LMF可以按照上文描述的AI定位方式以及N个信道估计信息指示的信道信息，对终端设备进行定位。如果目标定位方式的类型为非AI定位方式，LMF可以按照上文描述的非AI定位方式以及N个信道估计信息 指示的测量量，对终端设备进行定位。本公开对此不再进行赘述。
如果目标定位方式的类型为AI定位方式与非AI定位方式结合，则LMF可以按照AI定位方式对终端设备进行定位，得到第一定位结果；以及按照非AI定位方式对终端设备进行定位，得到第二定位结果。进而LMF可以结合第一定位结果和第二定位结果，确定最终的定位结果。
可选的，可以设定实施目标定位方式的有效时长，如记作设定时间段或称设定时长。LMF在确定目标定位方式后的设定时间段内，利用确定的目标定位方式进行终端设备的定位；经过设定时间段后，LMF需要再次按照前述S901～S902的方式重新确定目标定位方式的类型，即重新获取匹配目标定位方式用于对终端设备进行定位的信道估计信息。这样的设计可以实现周期性调整定位方式，以便于及时适应实际通信环境，提升定位精度。以前述示例3为例，如图11示意，LMF可以每隔设定时间段发起一次判断(对应执行S901～S902)，对当前定位方式进行调整，从而实现在AI定位方式、非AI定位方式、或AI定位方式与非AI定位方式结合之间的自适应切换。
进一步可选的，LMF还可以向位置请求方发送定位结果以及计算该定位结果所使用的定位方式。
本公开提供的上述方法，能够实现定位方式进行动态的调整，及时匹配实际的通信环境，灵活选择合适的定位方式，有利于提升估计终端设备位置的准确性。
方案二
参见图12示意一种通信方法，主要包括如下流程。
S1201，LMF发送第一请求信息，所述第一请求信息用于请求M个信道估计信息。
具体地，如图12示意，LMF向M个小区节点或终端设备发送第一请求信息。所述M个信道估计信息中的第m个信道估计信息是M个小区节点中第m个小区节点与终端设备之间的信道的估计信息；其中，M为正整数，m为取遍1至M的正整数。M个信道估计信息用于确定目标定位方式的类型。
例如在上行定位场景中，LMF向第m个小区发送第一请求信息，以请求第m个小区相关的第m个信道估计信息，或者LMF向其他的核心网网元发送第一请求信息，以通过其他的核心网网元转发第一请求信息给M个小区节点中各个小区节点。在下行定位场景中，LMF向终端设备发送第一请求信息，以请求终端设备测量M个信道估计信息。可选的，M的取值可以由通信环境中能够参与对终端设备定位的小区节点数量确定，可能是1也可能是大于1的正整数，如2或3等等。
为便于理解，如下以第一设备表示M个小区节点中的第m个小区节点、终端设备或前述其他的核心网设备为例进行描述。LMF可以向第一设备发送第一请求信息，所述第一请求信息具体用于请求第一设备相关的第m个信道估计信息。然后第一设备再向LMF发送其相关的第m个信道估计信息。可选的，可以由LMF或者第三方网元预配置有关M个信道估计信息的上报周期，使得LMF可以周期性向第一设备发送第一请求信息，以请求第一设备反馈第m个信道估计信息，从而触发LMF对于定位方式的调整。
具体地，LMF可以根据用于决策定位方式的定位要求(或称定位策略)，向第一设备发送第一请求信息。该定位要求用于指示定位指标需要符合的取值条件，该第一请求信息具体可以用于请求LMF希望获取的M个信道估计信息，使得M个信道估计信息能够用 于确定定位指标的取值，或描述为M个信道估计信息指示的参数能够用于确定定位指标的取值。
可选的，LMF可以在第一请求信息中包括以下中的一个或多个信息：指示定位要求的信息；指示定位指标的信息；M个信道估计信息指示的参数类型。
例如，LMF可以先根据定位要求或定位指标，获取第一设备的能力信息，该能力信息用于指示第一设备能够得到的第m个信道估计信息是否可以确定指标参数的取值。进而LMF根据第一设备的能力信息和定位指标，在第一请求信息中包括用于确定目标定位方式类型的信道估计信息所指示的参数类型，即M个信道估计信息指示的参数类型。其中，M个信道估计信息中各个信道估计信息指示的参数类型相同。第一设备根据前述M个信道估计信息指示的参数类型，确定向LMF发送的第一设备相关的第m个信道估计信息。
例如，LMF可以在第一请求信息中包括用于指示定位要求或定位指标的信息，第一设备获取到第一请求信息时，根据定位要求(或定位指标)和自身的能力，确定向LMF发送的第一设备相关的第m个信道估计信息，使得该第m个信道估计信息能够用于确定定位指标的取值。
可选的，上述实施方式中的定位要求或定位要求对应的定位指标可以是预配置在LMF中的，或者是位置请求方将定位要求或定位要求对应的定位指标指示给LMF的，该位置请求方指的是需要获取终端设备的位置的网元。例如位置请求方可以是第三方网元如其他的核心网网元，也可以是终端设备等。其中，例如位置请求方向LMF指示定位要求，不同的定位要求对应不同的定位指标。下面对定位指标和对应的M个信道估计信息指示的参数类型进行举例说明。
示例1，所述定位指标为所述小区节点和所述终端设备之间的通信路径的类型，所述通信路径的类型包括直射路径(LOS径)或非直射路径(NLOS径)。
示例性的，如果第三方网元向LMF指示定位要求为：根据LOS径/NLOS径的数量判断是否开启AI模式，即是否使用AI定位方式，则LMF可以确定定位指标为前述通信路径的类型。基于此，LMF可以获取第一设备的能力信息，该能力信息具体用于指示第一设备是否具备LOS径/NLOS径识别能力。进而LMF可以结合自身当前应用的定位方式以及定位指标，向第一设备请求第m个信道估计信息，具体的可参照如下实施：
(一)LMF当前应用的定位方式为非AI定位方式。
当第一设备具备LOS径/NLOS径识别能力时，LMF向第一设备请求的第m个信道估计信息指示的参数类型为小区节点和所述终端设备之间的通信路径的类型。由于指示LOS径/NLOS径的信息开销较小，LMF可以在每次定位时都先请求通信路径的类型，从而及时的判断是否需要开启AI模式。第一设备发送第m个信道估计信息指示通信路径的类型为LOS径或NLOS径，可以使用1/0标识，如“1”表示LOS径，“0”表示NLOS径。或者，第一设备发送第m个信道估计信息指示通信路径的类型为LOS径/NLOS径的概率。基于此，LMF在获取M个信道估计信息时，可确定M个通信路径的类型，M个通信路径的中第m个通信路径是第m个小区节点与终端设备之间的通信路径。
当终端设备，M个小区节点中的部分小区节点或M个小区节点中的全部小区节点不具备LOS径/NLOS径识别能力时，LMF可确定M个信道估计信息指示的参数类型为小区节点和所述终端设备之间的信道的信道信息。LMF可以在向第一设备发送的第一请求信息中包括用于指示信道信息的标识，进而第一设备根据LMF的请求，向LMF上报第一 设备相关的信道信息。基于此，LMF可以获取M个信道信息，M个信道信息的中第m个信道信息对应第m个小区节点与终端设备之间的信道。进而LMF可以根据获取的M个信道信息，自行确定M个小区节点与终端设备之间的通信路径的类型。
可选的，如果需要第一设备发送的第m个信道估计信息为信道信息，由于信道信息对应的开销较大，可以由LMF触发或者LMF配置第一设备周期性地上报信道信息，例如每隔设定时间间隔上报一次，或者按照定位次数，每当定位达到设定次数时上报一次。需要说明的是，这里的周期性上报信道信息是用于LMF周期性地判断是否开启AI模式，实际应用时，可以定义一个AI判断周期，用于指示第一设备上报用于确定目标定位方式的信道信息。判断周期可以定义为前述设定时间间隔，或者也可以定义为前述设定次数。
此外，如果需要第一设备发送的第m个信道估计信息具体是基于信道响应的特征，LMF还可以在用于请求第一请求信息中，增加对于第一设备提取基于信道响应的特征时所用的AI模型的指示。
(二)LMF当前应用的定位方式为AI定位方式。
一种可选的实施方式，由于LMF当前应用AI定位方式，说明LMF已经获取过小区节点与终端设备之间的信道的信道信息，则LMF可以根据历史获取的信道信息，确定小区节点与终端设备之间的通信路径的类型。在该方式中，LMF可以不用向第一设备发送第一请求信息。
另一种可选的实施方式中，当第一设备具备LOS径/NLOS径识别能力时，LMF向第一设备发送第一请求信息中包括M个信道估计信息指示的参数类型为小区节点和所述终端设备之间的通信路径的类型。进而第一设备根据LMF的请求，向LMF上报第一设备相关的通信路径的类型，LMF则可基于获取的M个信道估计信息确定M个通信路径的类型，M个通信路径中的第m个通信路径是第m个小区节点与终端设备之间的通信路径。
示例2，所述定位指标为当前使用的定位方式对应的定位精度。
可选的，如果位置请求方向LMF指示定位要求为对于定位精度的要求，如指标满足90％的概率误差在1m以下的定位精度要求，或者存在预设的定位精度要求。则LMF可以根据定位精度要求确定定位指标为当前定位方式对应的定位精度。LMF可以结合自身当前使用的定位方式以及定位指标，向第一设备请求相关的信道估计信息，具体的可参照如下实施：
(一)LMF当前应用的定位方式为非AI定位方式。
LMF向第一设备请求的第m个信道估计信息对应上文提及的测量量。具体地，第m个信道估计信息用于指示以下中的一个或多个参数：第m个小区节点与所述终端设备之间的距离；第m个小区节点与所述终端设备之间的信号传输时延或信号传输时延差；第m个小区节点对应的信号出发角度或信号到达角度；第m个小区节点与所述终端设备之间的信号质量。
进而第一设备根据LMF的请求，向LMF上报第一设备相关的测量量；LMF则可确定M个测量量，M个测量量中第m个测量量对应第m个小区节点与终端设备之间的信道。
(二)LMF当前应用的定位方式为AI定位方式。
LMF向第一设备请求的第m个信道估计信息指示的参数类型为第m个小区节点与所述终端设备之间的信道的信道信息，该信道信息可以用于LMF自行确定第m个小区节点与终端设备之间的通信路径的类型。以此类推，LMF获取到M个信道估计信息，可以根 据M个信道估计信息，确定M个小区中各个小区与终端设备之间的通信路径的类型。
可选的，如果是需要第一设备发送的第m个信道估计信息为信道信息，由于信道信息对应的开销较大，可以由LMF触发或者LMF配置第一设备周期性上报信道信息，例如每隔设定时间间隔上报一次，或者按照定位次数，每当定位达到设定次数时上报一次。需要说明的是，这里的周期性上报信道信息是用于LMF周期性地判断是否开启AI模式，实际应用时，可以定义一个AI判断周期，用于指示第一设备上报用于确定定位方式的信道信息。判断周期可以定义为前述设定时间间隔，或者也可以定义为前述设定次数。
此外，如果需要第一设备发送的第m个信道估计信息具体是基于信道响应的特征，LMF还可以在第一请求信息中，增加对于第一设备提取基于信道响应的特征时所用的AI模型的指示。
进而第一设备根据LMF的请求，向LMF上报第一设备相关的信道信息，LMF则可确定M个信道信息，M个信道信息中第m个信道信息对应第m个小区节点与终端设备之间的信道。
此外可选的，由于测量量对应的传输开销较少，如果在示例一或示例2中，第一设备确定向LMF上报的是信道信息，则第一设备还可以在上报信道信息同时向LMF上报相关的测量量。
示例3，所述定位指标为AI定位方式对应的定位精度以及非AI定位方式对应的定位精度。
可选的，如果第三方网元向LMF指示定位要求为按照AI定位方式与非AI定位方式之间的定位精度差异，判断是否开启AI模式。则LMF可以根据该定位要求确定定位指标包括AI定位方式对应的定位精度以及非AI定位方式对应的定位精度。基于此，LMF根据定位指标，向第一设备请求的第m个信道估计信息包括非AI定位方式对应的测量量以及AI定位方式对应的信道信息。其中，有关请求信道信息的具体方案可以参照示例2中(二)描述的实施，本公开对此不再进行赘述。
进而第一设备根据LMF的请求，向LMF上报第一设备相关的测量量和信道信息，LMF则可获取M个测量量和M个信道信息，M个测量量中第m个测量量对应第m个小区节点与终端设备之间的信道，M个信道信息中第m个信道信息对应第m个小区节点与终端设备之间的信道。
S1202，LMF获取M个信道估计信息。
如图12示意，LMF可以从终端设备或者M个小区节点获取M个信道估计信息。
其中，M个信道估计信息中的第m个信道估计信息可以来自于第m个小区节点或者终端设备。例如在上行定位场景中，由第m个小区节点向LMF发送第m个信道估计信息，或者第m个小区节点向核心网网元发送第m个信道估计信息，核心网网元将从M个小区节点获取的M个信道估计信息发送给LMF；在下行定位场景中，由终端设备向LMF发送第m个信道估计信息。可选的，M的取值可以由通信环境中能够参与对终端设备定位的小区节点数量确定，可能是1也可能是大于1的正整数，如2或3等等。
S1203，LMF根据所述M个信道估计信息，确定目标定位方式的类型。
具体地，该步骤可参照S902的实施方式执行，本公开对此不再进行赘述。
S1204，LMF根据目标定位方式的类型，获取N个信道估计信息。
如图12示意，LMF可以从终端设备或者M个小区节点获取N个信道估计信息。其中， N个信道估计信息中第n个信道估计信息可以来自于M个小区节点包含的N个小区节点中的第n个小区节点或者终端设备。
具体地，该步骤可参照S903的实施方式执行，本公开对此不再进行赘述。
S1205，LMF根据所述N个信道估计信息，对所述终端设备进行定位。
具体地，该步骤可参照S904的实施方式执行，本公开对此不再进行赘述。
本公开提供的上述方法，由LMF指示终端设备或小区节点上报决策定位方式所用的信道估计信息，能够快速实现定位方式进行动态的调整，及时匹配实际的通信环境，灵活选择合适的定位方式，有利于提升估计终端设备位置的准确性。
方案三
参见图13示意一种通信方法，主要包括如下流程。
S1301，位置请求方向LMF发送第一信息，第一信息用于指示位置请求方希望的定位模式。
其中，定位模式也可以描述为定位方式类型。位置请求方可以是终端设备或者其他的第三方网元，位置请求方也可以描述为第三设备或者其他名称，本公开对此不予限制。
第一信息指示的定位模式为AI定位方式；或者，第一信息指示的定位模式为非AI定位方式；或者，第一信息指示的定位模式为AI定位方式和非AI定位方式结合；或者，第一信息指示的定位模式为自动切换模式，自动切换模式表示由LMF动态调整定位方式为AI定位方式、非AI定位方式、或者AI定位方式与非AI定位方式结合。
可选的，第一信息指示定位模式为自动切换模式时，还可以包括用于指示定位要求的信息，该定位要求可以用于LMF决策目标定位方式，定位要求用于指示定位指标需要满足的取值条件。
可选的，位置请求方可以根据业务的要求进行定位模式的选择，如位置请求方是终端设备时，可以对空口开销有一定的要求。示例性的，如果位置请求方需要时延较短的定位服务，对定位精度的要求不高，则可以确定第一信息指示的定位模式为非AI定位方式；如果位置请求方需要定位精度较高的服务，对时延的要求不高，则可以确定第一信息指示的定位模式为AI定位方式；如果位置请求方需要较为鲁棒的定位结果，对时延和空口开销的要求不高，可以确定第一信息指示的定位模式为AI定位方式和非AI定位方式结合；如果位置请求方需要较为鲁棒的定位结果且希望时延和空口开销尽可能小时，可以确定第一信息指示的定位模式为自动切换模式。
进一步可选的，位置请求方在选择定位模式或发送第一信息之前，还可以获取LMF的能力信息，以确定LMF的能力支持的定位模式和/或不支持的定位模式。然后结合LMF的能力向LMF发送第一信息，该第一信息所指示的定位模式为LMF支持的定位模式。
S1302，LMF根据第一信息，确定目标定位方式的类型。
对应S1301，如果位置请求方通过第一信息指示定位模式时未考虑LMF的能力，则LMF可以自身的能力，判断是否支持第一信息指示的定位模式。如果支持，则LMF将第一信息指示的定位模式，确定为目标定位方式的类型。如果不支持，则一种可选的实施方式中，LMF可以将自身的能力上报给位置请求方，进而位置请求方结合业务要求，重新为LMF指示希望的定位模式，重复这一过程，直至LMF能够支持位置请求方希望的定位模式为止。另一种可选的实施方式中，LMF可以结合自身的能力，自行确定目标定位方式的 类型，并将目标定位方式的类型通知给位置请求方。
对应S1301，如果位置请求方通过第一信息指示定位模式时考虑了LMF的能力，第一信息指示的定位模式符合LMF的能力，那么LMF则可将第一信息指示的定位模式，确定为目标定位方式的类型。
此外，如果第一信息指示的定位模式为自动切换模式时，LMF可以按照方案一中S901～S902或者方案二中S1201～S1203实时或者周期性地确定目标定位方式的类型，本公开对此不再进行赘述。
S1303，LMF根据目标定位方式的类型，获取N个信道估计信息。
其中，N个信道估计信息用于终端设备的定位，N个信道估计信息中第n个信道估计信息为参与终端设备定位的N个小区节点中第n个小区节点与终端设备之间的信道的估计信息。N为正整数，n取遍1至N的正整数。
具体地，如图13示意，LMF可以从N个小区节点或者终端设备获取N个信道估计信息，N个信道估计信息与前述目标定位方式的类型相匹配。其中，N个信道估计信息中第n个信道估计信息可以来自于M个小区节点包含的N个小区节点中的第n个小区节点或者终端设备。例如在上行定位场景中，由第n个小区节点向LMF发送第n个信道估计信息，或者第n个小区节点向核心网网元发送第n个信道估计信息，核心网网元将获取的N个信道估计信息发送给LMF；在下行定位场景中，由终端设备向LMF发送第n个信道估计信息。
为便于理解，以第二设备表示N个小区节点中的第n个小区节点、终端设备或核心网设备为例，LMF可参照如下方式，从第二设备获取第n个信道估计信息。
LMF在确定目标定位方式的类型后，可以向第二设备发送第二请求信息，该第二请求信息用于请求对终端设备进行定位所需的信道估计信息，即前述N个信道估计信息。第二设备响应于第二请求信息，向LMF发送第n个信道估计信息。
一种可选的实施方式中，LMF可以在第二请求信息中包括用于指示目标定位方式的类型的信息。第二设备根据用于指示目标定位方式的类型的信息，确定与目标定位方式的类型匹配的第n个信道估计信息，并将第n个信道估计信息上报给LMF。
另一种可选的实施方式中，LMF可以根据目标定位方式的类型，确定希望获取的N个信道估计信息指示的参数类型，该参数类型与目标定位方式的类型匹配。进而LMF可以在第二请求信息中包括N个信道估计信息指示的参数类型。第二设备根据该N个信道估计信息指示的参数类型，上报第n个信道估计信息给LMF。
其中，N个信道估计信息中各个信道估计信息指示的参数类型相同。下面以第n个信道估计信息指示的参数类型为例，对于不同类型定位方式对应的第n个信道估计信息指示的参数类型进行举例说明。
示例性的，如果目标定位方式的类型为AI定位方式，第n个信道估计信息用于指示所述第n个小区节点与所述终端设备之间的信道的信道信息。
示例性的，如果目标定位方式的类型为非AI定位方式，第n个信道估计信息用于指示测量量，测量量包括以下中的一个或多个参数：所述第n个小区节点与所述终端设备之间的距离；所述第n个小区节点与所述终端设备之间的信号传输时延或信号传输时延差；所述第n个小区节点对应的信号出发角度或信号到达角度；所述第n个小区节点与所述终端设备之间的信号质量。
示例性的，如果目标定位方式的类型为AI定位方式与非AI定位方式结合，第n个信道估计信息用于指示所述第n个小区节点与所述终端设备之间的信道的信道信息以及测量量，测量量包括以下中的一个或多个参数：所述第n个小区节点与所述终端设备之间的距离；所述第n个小区节点与所述终端设备之间的信号传输时延或信号传输时延差；所述第n个小区节点对应的信号出发角度或信号到达角度；所述第n个小区节点与所述终端设备之间的信号质量。
S1304，LMF根据N个信道估计信息，对终端设备进行定位。
具体地，可参照S904描述的方式确定定位结果，本公开对此不再进行赘述。
S1305，LMF向位置请求方发送第二信息，第二信息用于指示定位结果。
可选的，LMF还可以向位置请求方发送用于指示计算该定位结果所使用的目标定位方式的信息。这样的设计可以便于位置请求方在后续请求位置时，参考该信息选择定位模式。例如当位置请求方选择定位模式为自动切换模式后，位置请求方反馈的目标定位方的类型为非AI定位方式，但定位结果与位置请求方根据其他传感器预测的定位结果之间差别很大，则位置请求方可以重新请求基于AI定位方式得到的定位结果。
本公开提供的上述方法，基于位置请求方的需求灵活决策定位方式，并实现对于定位方式的动态调整，及时匹配实际的通信环境，有利于提升估计终端设备位置的准确性。
基于同一构思，参见图14，本公开提供了一种通信装置1400，该通信装置1400包括处理模块1401和通信模块1402。该通信装置1400可以是LMF，也可以是应用于LMF或者和LMF匹配使用，能够实现LMF侧执行的通信方法的通信装置；或者，该通信装置1400可以是小区节点，也可以是应用于小区节点或者和小区节点匹配使用，能够实现小区节点侧执行的通信方法的通信装置；或者，该通信装置1400可以是终端设备，也可以是应用于终端设备或者和终端设备匹配使用，能够实现终端设备侧执行的通信方法的通信装置；或者，该通信装置1400可以是核心网网元，也可以是应用于核心网网元或者和核心网网元匹配使用，能够实现核心网网元侧执行的通信方法的通信装置。
其中，通信模块也可以称为收发模块、收发器、收发机、或收发装置等。处理模块也可以称为处理器，处理单板，处理单元、或处理装置等。可选的，通信模块用于执行上述方法中LMF侧或第一设备侧的发送操作和接收操作，可以将通信模块中用于实现接收功能的器件视为接收单元，将通信模块中用于实现发送功能的器件视为发送单元，即通信模块包括接收单元和发送单元。
该通信装置1400应用于LMF时，处理模块1401可用于实现图9或者图12所示实施例中所述LMF的处理功能，通信模块1402可用于实现图9或者图12所述实施例中所述LMF的收发功能。或者也可以参照发明内容中第三方面以及第三方面中可能的设计理解该通信装置。
该通信装置1400应用于核心网网元或终端设备时，处理模块1401可用于实现图9或者图12所示实施例中核心网网元或终端设备的处理功能，通信模块1402可用于实现图9或者图12所述实施例中核心网网元或终端设备的收发功能。或者也可以参照发明内容中第四方面以及第四方面中可能的设计理解该通信装置。
该通信装置1400应用于小区节点时，处理模块1401可用于实现图9或者图12所示实施例中小区节点的处理功能，通信模块1402可用于实现图9或者图12所述实施例中小 区节点的收发功能。
此外需要说明的是，前述通信模块和/或处理模块可通过虚拟模块实现，例如处理模块可通过软件功能单元或虚拟装置实现，通信模块可以通过软件功能或虚拟装置实现。或者，处理模块或通信模块也可以通过实体装置实现，例如若该装置采用芯片/芯片电路实现，所述通信模块可以是输入输出电路和/或通信接口，执行输入操作(对应前述接收操作)、输出操作(对应前述发送操作)；处理模块为集成的处理器或者微处理器或者集成电路。
本公开中对模块的划分是示意性的，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，另外，在本公开各个实施例中的各功能模块可以集成在一个处理器中，也可以是单独物理存在，也可以两个或两个以上模块集成在一个模块中。上述集成的模块既可以采用硬件的形式实现，也可以采用软件功能模块的形式实现。
基于相同的技术构思，本公开还提供了一种通信装置1500。例如，该通信装置1500可以是芯片或者芯片系统。可选的，在本公开中芯片系统可以由芯片构成，也可以包含芯片和其他分立器件。
通信装置1500可用于实现前述实施例描述的通信系统中任一网元的功能。通信装置1500可以包括至少一个处理器1510，该处理器1510与存储器耦合，可选的，存储器可以位于该装置之内，存储器可以和处理器集成在一起，存储器也可以位于该装置之外。例如，通信装置1500还可以包括至少一个存储器1520。存储器1520保存实施上述任一实施例中必要计算机程序、计算机程序或指令和/或数据；处理器1510可能执行存储器1520中存储的计算机程序，完成上述任一实施例中的方法。
通信装置1500中还可以包括通信接口1530，通信装置1500可以通过通信接口1530和其它设备进行信息交互。示例性的，所述通信接口1530可以是收发器、电路、总线、模块、管脚或其它类型的通信接口。当该通信装置1500为芯片类的装置或者电路时，该装置1500中的通信接口1530也可以是输入输出电路，可以输入信息(或称，接收信息)和输出信息(或称，发送信息)，处理器为集成的处理器或者微处理器或者集成电路或则逻辑电路，处理器可以根据输入信息确定输出信息。
本公开中的耦合是装置、单元或模块之间的间接耦合或通信连接，可以是电性，机械或其它的形式，用于装置、单元或模块之间的信息交互。处理器1510可能和存储器1520、通信接口1530协同操作。本公开中不限定上述处理器1510、存储器1520以及通信接口1530之间的具体连接介质。
可选的，参见图15，所述处理器1510、所述存储器1520以及所述通信接口1530之间通过总线1540相互连接。所述总线1540可以是外设部件互连标准(peripheral component interconnect，PCI)总线或扩展工业标准结构(extended industry standard architecture，EISA)总线等。所述总线可以分为地址总线、数据总线、控制总线等。为便于表示，图15中仅用一条粗线表示，但并不表示仅有一根总线或一种类型的总线。
在本公开中，处理器可以是通用处理器、数字信号处理器、专用集成电路、现场可编程门阵列或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件，可以实现或者执行本公开中的公开的各方法、步骤及逻辑框图。通用处理器可以是微处理器或者任何常规的处理器等。结合本公开所公开的方法的步骤可以直接体现为硬件处理器执行完成，或者用处理器中的硬件及软件模块组合执行完成。
在本公开中，存储器可以是非易失性存储器，比如硬盘(hard disk drive，HDD)或固态硬盘(solid-state drive，SSD)等，还可以是易失性存储器(volatile memory)，例如随机存取存储器(random-access memory，RAM)。存储器是能够用于携带或存储具有指令或数据结构形式的期望的程序代码并能够由计算机存取的任何其他介质，但不限于此。本公开中的存储器还可以是电路或者其它任意能够实现存储功能的装置，用于存储程序指令和/或数据。
在一种可能的实施方式中，该通信装置1500可以应用于终端设备，具体通信装置1500可以是终端设备，也可以是能够支持核心网网元或终端设备，实现上述涉及的任一实施例中终端设备的功能的装置。存储器1520保存实现上述任一实施例中的终端设备的功能的计算机程序(或指令)和/或数据。处理器1510可执行存储器1520存储的计算机程序，完成上述任一实施例中终端设备执行的方法。应用于终端设备，该通信装置1500中的通信接口可用于与LMF进行交互，向LMF发送信息或者接收来自LMF的信息。
在一种可能的实施方式中，该通信装置1500可以应用于小区节点，具体通信装置1500可以是小区节点，也可以是能够支持核心网网元或小区节点，实现上述涉及的任一实施例中小区节点的功能的装置。存储器1520保存实现上述任一实施例中的小区节点的功能的计算机程序(或指令)和/或数据。处理器1510可执行存储器1520存储的计算机程序，完成上述任一实施例中小区节点执行的方法。应用于小区节点，该通信装置1500中的通信接口可用于与LMF进行交互，向LMF发送信息或者接收来自LMF的信息。
在一种可能的实施方式中，该通信装置1500可以应用于核心网网元，具体通信装置1500可以是核心网网元，也可以是能够支持核心网网元或核心网网元，实现上述涉及的任一实施例中核心网网元的功能的装置。存储器1520保存实现上述任一实施例中的核心网网元的功能的计算机程序(或指令)和/或数据。处理器1510可执行存储器1520存储的计算机程序，完成上述任一实施例中核心网网元执行的方法。应用于核心网网元，该通信装置1500中的通信接口可用于与LMF或小区节点进行交互，向LMF发送信息或者接收来自小区节点的信息。
在一种可能的实施方式中，该通信装置1500可以应用于LMF，具体通信装置1500可以是LMF，也可以是能够支持LMF，实现上述涉及的任一实施例中LMF的功能的装置。存储器1520保存实现上述任一实施例中的LMF的功能的计算机程序(或指令)和/或数据。处理器1510可执行存储器1520存储的计算机程序，完成上述任一实施例中LMF执行的方法。应用于LMF，该通信装置1500中的通信接口可用于与终端设备、小区节点、核心网网元等进行交互，如向终端设备、小区节点或核心网网元发送信息或者接收来自终端设备、小区节点或核心网网元的信息。
由于本实施例提供的通信装置1500可应用于终端设备、小区节点或核心网网元，完成上述终端设备、小区节点或核心网网元执行的方法，或者应用于LMF，完成LMF执行的方法。因此其所能获得的技术效果可参考上述方法示例，在此不再赘述。
基于以上实施例，本公开提供了一种通信系统，包括终端设备、小区节点和LMF。可选的，还包括核心网元。其中，所述终端设备、小区节点或核心网网元和LMF可以实现图9或者图12所示的实施例中所提供的通信方法。
基于以上实施例，本公开还提供了一种计算机程序，当所述计算机程序在计算机上运行时，使得所述计算机从小区节点、终端设备、核心网网元或者LMF的角度执行图9、图 12或图13所示的实施例中所提供的通信方法。
基于以上实施例，本公开还提供了一种计算机可读存储介质，该计算机可读存储介质中存储有计算机程序，所述计算机程序被计算机执行时，使得计算机从小区节点、终端设备、核心网网元或者LMF的角度执行图9、图12或图13所示的实施例中所提供的通信方法。其中，存储介质可以是计算机能够存取的任何可用介质。以此为例但不限于：计算机可读介质可以包括RAM、只读存储器(read-only memory，ROM)、电可擦可编程只读存储器(electrically erasable programmable read-only memory，EEPROM)、CD-ROM或其他光盘存储、磁盘存储介质或者其他磁存储设备、或者能够用于携带或存储具有指令或数据结构形式的期望的程序代码并能够由计算机存取的任何其他介质。
基于以上实施例，本公开还提供了一种芯片，所述芯片用于读取存储器中存储的计算机程序，从小区节点、终端设备、核心网网元或者LMF的角度执行图9、图12或图13所示的实施例中所提供的通信方法。
基于以上实施例，本公开提供了一种芯片系统，该芯片系统包括处理器，用于支持计算机装置实现图9、图12或图13描述实施例中小区节点、终端设备、核心网网元或者LMF所涉及的功能。在一种可能的设计中，所述芯片系统还包括存储器，所述存储器用于保存该计算机装置必要的程序和数据。该芯片系统，可以由芯片构成，也可以包含芯片和其他分立器件。
本公开提供的技术方案可以全部或部分地通过软件、硬件、固件或者其任意组合来实现。当使用软件实现时，可以全部或部分地以计算机程序产品的形式实现。所述计算机程序产品包括一个或多个计算机指令。在计算机上加载和执行所述计算机程序指令时，全部或部分地产生按照本公开所述的流程或功能。所述计算机可以是通用计算机、专用计算机、计算机网络、LMF、终端设备、小区节点、核心网网元或者其他可编程装置。所述计算机指令可以存储在计算机可读存储介质中，或者从一个计算机可读存储介质向另一个计算机可读存储介质传输，例如，所述计算机指令可以从一个网站站点、计算机、服务器或数据中心通过有线(例如同轴电缆、光纤、数字用户线(digital subscriber line，DSL))或无线(例如红外、无线、微波等)方式向另一个网站站点、计算机、服务器或数据中心进行传输。所述计算机可读存储介质可以是计算机可以存取的任何可用介质或者是包含一个或多个可用介质集成的服务器、数据中心等数据存储设备。所述可用介质可以是磁性介质(例如，软盘、硬盘、磁带)、光介质(例如，数字视频光盘(digital video disc，DVD))、或者半导体介质等。
在本公开中，在无逻辑矛盾的前提下，各实施例之间可以相互引用，例如方法实施例之间的方法和/或术语可以相互引用，例如装置实施例之间的功能和/或术语可以相互引用，例如装置实施例和方法实施例之间的功能和/或术语可以相互引用。
显然，本领域的技术人员可以对本公开进行各种改动和变型而不脱离本公开的范围。这样，倘若本公开的这些修改和变型属于本公开权利要求及其等同技术的范围之内，则本公开也意图包含这些改动和变型在内。

Claims (32)

  1. 一种通信方法，其特征在于，包括：
    获取M个信道估计信息，所述M个信道估计信息中的第m个信道估计信息是M个小区节点中第m个小区节点与终端设备之间的信道的估计信息；其中，M为正整数，m为取遍1至M的正整数；
    根据所述M个信道估计信息，确定目标定位方式的类型；
    根据所述目标定位方式的类型，获取N个信道估计信息，所述N个信道估计信息用于所述终端设备的定位；其中，所述N个信道估计信息中的第n个信道估计信息是N个小区节点中第n个小区节点与所述终端设备之间的信道的估计信息；所述N个小区节点包含于所述M个小区节点，N为小于等于M的正整数，n为取遍1至N的正整数。
  2. 如权利要求1所述的方法，其特征在于，还包括：
    获取定位要求，所述定位要求用于获取用于确定所述目标定位方式的类型的所述M个信道估计信息；所述定位要求用于指示定位指标需要符合的取值条件，所述M个信道估计信息能够用于确定所述定位指标的取值。
  3. 如权利要求2所述的方法，其特征在于，还包括：
    发送第一请求信息，所述第一请求信息用于请求所述M个信道估计信息，所述第一请求信息包括用于指示所述定位要求或者所述定位指标的信息。
  4. 如权利要求2所述的方法，其特征在于，所述定位指标包括以下中的一种或多种：
    所述小区节点和所述终端设备之间的通信路径的类型，所述通信路径的类型包括直射路径或非直射路径；
    至少一种类型的定位方式对应的定位精度。
  5. 如权利要求1-4任一项所述的方法，其特征在于，所述目标定位方式的类型对应第一值时，所述N个信道估计信息中的第n个信道估计信息用于指示以下中的一个或多个参数：
    所述第n个小区节点与所述终端设备之间的距离；
    所述第n个小区节点与所述终端设备之间的信号传输时延或信号传输时延差；
    所述第n个小区节点对应的信号出发角度或信号到达角度。
  6. 如权利要求1-4任一项所述的方法，其特征在于，所述目标定位方式的类型对应第二值时，所述N个信道估计信息中的第n个信道估计信息用于指示所述第n个小区节点与所述终端设备之间的信道的信道信息。
  7. 如权利要求1-6任一项所述的方法，其特征在于，所述根据所述目标定位方式的类型，获取N个信道估计信息，包括：
    发送第二请求信息，所述第二请求信息用于请求所述N个信道估计信息，所述第二请求信息包括用于指示所述目标定位方式的类型的信息；
    接收所述N个信道估计信息。
  8. 如权利要求1-7任一项所述的方法，其特征在于，还包括：
    在设定时间段内，根据所述N个信道估计信息对所述终端设备进行定位。
  9. 一种通信方法，其特征在于，包括：
    发送M个信道估计信息，所述M个信道估计信息用于确定目标定位方式的类型；其 中，所述M个信道估计信息中的第m个信道估计信息是M个小区节点中第m个小区节点与终端设备之间的信道的估计信息，M为正整数，m为取遍1至M的正整数；
    获取用于请求N个信道估计信息的第二请求信息，所述第二请求信息包括用于指示所述目标定位方式的类型的信息；
    发送所述N个信道估计信息，所述N个信道估计信息用于所述终端设备的定位；其中，所述N个信道估计信息中的第n个信道估计信息是N个小区节点中第n个小区节点与所述终端设备之间的信道的估计信息；所述N个小区节点包含于所述M个小区节点，N为小于等于M的正整数，n为取遍1至N的正整数。
  10. 如权利要求9所述的方法，其特征在于，还包括：
    获取第一请求信息，所述第一请求信息用于请求所述M个信道估计信息，所述第一请求信息包括用于指示定位要求或者定位指标的信息；其中，所述定位要求用于指示所述定位指标需要符合的取值条件，所述M个信道估计信息能够用于确定所述定位指标的取值。
  11. 如权利要求10所述的方法，其特征在于，所述定位指标包括以下中的一种或多种：
    所述小区节点和所述终端设备之间的通信路径的类型，所述通信路径的类型包括直射路径或非直射路径；
    至少一种类型的定位方式对应的定位精度。
  12. 如权利要求9-11任一项所述的方法，其特征在于，所述目标定位方式的类型对应第一值时，所述N个信道估计信息中的第n个信道估计信息用于指示以下中的一个或多个参数：
    所述第n个小区节点与所述终端设备之间的距离；
    所述第n个小区节点与所述终端设备之间的信号传输时延或信号传输时延差；
    所述第n个小区节点对应的信号出发角度或信号到达角度。
  13. 如权利要求9-11任一项所述的方法，其特征在于，所述目标定位方式的类型对应第二值时，所述N个信道估计信息中的第n个信道估计信息用于指示所述第n个小区节点与所述终端设备之间的信道的信道信息。
  14. 一种通信装置，其特征在于，包括：
    通信模块，用于获取M个信道估计信息，所述M个信道估计信息中的第m个信道估计信息是M个小区节点中第m个小区节点与终端设备之间的信道的估计信息；其中，M为正整数，m为取遍1至M的正整数；
    处理模块，用于根据所述M个信道估计信息，确定目标定位方式的类型；
    所述处理模块，还用于根据所述目标定位方式的类型，控制所述通信模块获取N个信道估计信息，所述N个信道估计信息用于所述终端设备的定位；其中，所述N个信道估计信息中的第n个信道估计信息是N个小区节点中第n个小区节点与所述终端设备之间的信道的估计信息；所述N个小区节点包含于所述M个小区节点，N为小于等于M的正整数，n为取遍1至N的正整数。
  15. 如权利要求14所述的装置，其特征在于，所述通信模块，还用于获取定位要求，所述定位要求用于获取用于确定所述目标定位方式的类型的所述M个信道估计信息；所述定位要求用于指示定位指标需要符合的取值条件，所述M个信道估计信息能够用于确定所述定位指标的取值。
  16. 如权利要求15所述的装置，其特征在于，所述通信模块，还用于发送第一请求信 息，所述第一请求信息用于请求所述M个信道估计信息，所述第一请求信息包括用于指示所述定位要求或者所述定位指标的信息。
  17. 如权利要求15所述的装置，其特征在于，所述定位指标包括以下中的一种或多种：所述小区节点和所述终端设备之间的通信路径的类型，所述通信路径的类型包括直射路径或非直射路径；至少一种类型的定位方式对应的定位精度。
  18. 如权利要求14-17任一项所述的装置，其特征在于，所述目标定位方式的类型对应第一值时，所述N个信道估计信息中的第n个第二信道估计信息用于指示以下中的一个或多个参数：所述第n个小区节点与所述终端设备之间的距离；所述第n个小区节点与所述终端设备之间的信号传输时延或信号传输时延差；所述第n个小区节点对应的信号出发角度或信号到达角度。
  19. 如权利要求14-17任一项所述的装置，其特征在于，所述目标定位方式的类型对应第二值时，所述N个信道估计信息中的第n个第二信道估计信息用于指示所述第n个小区节点与所述终端设备之间的信道的信道信息。
  20. 如权利要求14-19任一项所述的装置，其特征在于，所述处理模块，还用于：
    通过所述通信模块发送第二请求信息，所述第二请求信息用于请求所述N个信道估计信息，所述第二请求信息包括用于指示所述目标定位方式的类型的信息；
    通过所述通信模块接收所述N个信道估计信息。
  21. 如权利要求14-19任一项所述的装置，其特征在于，所述处理模块，还用于在设定时间段内，根据所述N个信道估计信息对所述终端设备进行定位。
  22. 一种通信装置，其特征在于，包括：
    通信模块，用于发送M个信道估计信息，所述M个信道估计信息用于确定目标定位方式的类型；其中，所述M个信道估计信息中的第m个信道估计信息是M个小区节点中第m个小区节点与终端设备之间的信道的估计信息，M为正整数，m为取遍1至M的正整数；
    所述通信模块，还用于获取用于请求N个信道估计信息的第二请求信息，所述第二请求信息包括用于指示所述目标定位方式的类型的信息；
    处理模块，用于通过所述通信模块发送所述N个信道估计信息，所述N个信道估计信息用于所述终端设备的定位；其中，所述N个信道估计信息中的第n个信道估计信息是N个小区节点中第n个小区节点与所述终端设备之间的信道的估计信息；所述N个小区节点包含于所述M个小区节点，N为小于等于M的正整数，n为取遍1至N的正整数。
  23. 如权利要求22所述的装置，其特征在于，
    所述通信模块，还用于获取第一请求信息，所述第一请求信息用于请求所述M个信道估计信息，所述第一请求信息包括用于指示定位要求或者定位指标的信息；其中，所述定位要求用于指示所述定位指标需要符合的取值条件，所述M个信道估计信息能够用于确定所述定位指标的取值；
    所述处理模块，还用于根据所述第一请求信息，确定所述M个信道估计信息。
  24. 如权利要求23所述的装置，其特征在于，所述定位指标包括以下中的一种或多种：所述小区节点和所述终端设备之间的通信路径的类型，所述通信路径的类型包括直射路径或非直射路径；至少一种类型的定位方式对应的定位精度。
  25. 如权利要求22-24任一项所述的装置，其特征在于，所述目标定位方式的类型对应 第一值时，所述N个信道估计信息中的第n个信道估计信息用于指示以下中的一个或多个参数：所述第n个小区节点与所述终端设备之间的距离；所述第n个小区节点与所述终端设备之间的信号传输时延或信号传输时延差；所述第n个小区节点对应的信号出发角度或信号到达角度。
  26. 如权利要求22-24任一项所述的装置，其特征在于，所述目标定位方式的类型对应第二值时，所述N个信道估计信息中的第n个信道估计信息用于指示所述第n个小区节点与所述终端设备之间的信道的信道信息。
  27. 一种通信装置，其特征在于，用于实现如权利要求9-13任一项所述的方法。
  28. 一种通信装置，其特征在于，包括：
    处理器，所述处理器和存储器耦合，所述处理器用于调用所述存储器存储的计算机程序指令，以执行如权利要求1-8任一项所述的方法。
  29. 一种通信装置，其特征在于，包括：
    处理器，所述处理器和存储器耦合，所述处理器用于调用所述存储器存储的计算机程序指令，以执行如权利要求9-13任一项所述的方法。
  30. 一种通信系统，其特征在于，包括权利要求14-21以及28中任一项所述的通信装置，以及权利要求15-26以及29中任一项所述的通信装置。
  31. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质上存储有指令，当所述指令在计算机上运行时，使得计算机执行如权利要求1-8任一项所述的方法或如权利要求9-13任一项所述的方法。
  32. 一种计算机程序产品，其特征在于，包括指令，当所述指令在计算机上运行时，使得计算机执行如权利要求1-8任一项所述的方法或如权利要求9-13任一项所述的方法。
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111565414A (zh) * 2019-02-13 2020-08-21 华为技术有限公司 一种确定定向定位参考信号的方法及装置
CN111756494A (zh) * 2019-03-28 2020-10-09 华为技术有限公司 用于定位的方法与装置
CN113518302A (zh) * 2020-04-09 2021-10-19 大唐移动通信设备有限公司 一种定位参考信号配置方法、lmf、基站及终端
CN113840224A (zh) * 2020-06-08 2021-12-24 华为技术有限公司 通信方法及装置

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111565414A (zh) * 2019-02-13 2020-08-21 华为技术有限公司 一种确定定向定位参考信号的方法及装置
CN111756494A (zh) * 2019-03-28 2020-10-09 华为技术有限公司 用于定位的方法与装置
CN113518302A (zh) * 2020-04-09 2021-10-19 大唐移动通信设备有限公司 一种定位参考信号配置方法、lmf、基站及终端
CN113840224A (zh) * 2020-06-08 2021-12-24 华为技术有限公司 通信方法及装置

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