WO2025245705A1 - 通信方法、设备和存储介质 - Google Patents

通信方法、设备和存储介质

Info

Publication number
WO2025245705A1
WO2025245705A1 PCT/CN2024/095837 CN2024095837W WO2025245705A1 WO 2025245705 A1 WO2025245705 A1 WO 2025245705A1 CN 2024095837 W CN2024095837 W CN 2024095837W WO 2025245705 A1 WO2025245705 A1 WO 2025245705A1
Authority
WO
WIPO (PCT)
Prior art keywords
information
terminal device
value
network device
path loss
Prior art date
Legal status (The legal status 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 status listed.)
Pending
Application number
PCT/CN2024/095837
Other languages
English (en)
French (fr)
Inventor
陶旭华
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing Xiaomi Mobile Software Co Ltd
Original Assignee
Beijing Xiaomi Mobile Software Co Ltd
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.)
Filing date
Publication date
Application filed by Beijing Xiaomi Mobile Software Co Ltd filed Critical Beijing Xiaomi Mobile Software Co Ltd
Priority to PCT/CN2024/095837 priority Critical patent/WO2025245705A1/zh
Priority to CN202480025717.3A priority patent/CN121444371A/zh
Publication of WO2025245705A1 publication Critical patent/WO2025245705A1/zh
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

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Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/373—Predicting channel quality or other radio frequency [RF] parameters

Definitions

  • This disclosure relates to the field of communication technology, and in particular to a communication method, device and storage medium.
  • Machine learning algorithms are currently one of the most important methods for implementing Artificial Intelligence (AI) technology. By learning from large amounts of training data, machine learning can produce AI models, which can then be used to predict events. In many fields, AI models trained using machine learning can achieve highly accurate predictions. In the field of communications, AI models can also be used to obtain predictive data for certain scenarios, thereby improving network performance.
  • AI Artificial Intelligence
  • This disclosure provides a communication method, device, and storage medium.
  • a communication method comprising:
  • the terminal device makes a prediction based on the first information to obtain the path loss value between the terminal device and the network device.
  • a communication method comprising:
  • the network device sends a second message to the terminal device.
  • the second message is used to indicate the first transmission message.
  • the first transmission message is the power value or signal strength value of the path loss reference signal PLRS sent by the network device.
  • the first transmission message is used by the terminal device to predict the path loss value between the terminal device and the network device.
  • a terminal device comprising:
  • the processing module is configured to make a prediction based on the first information to obtain the path loss value between the terminal device and the network device.
  • a network device comprising:
  • the transceiver module is configured to send second information to a terminal device.
  • the second information is used to indicate first transmission information.
  • the first transmission information is the power value or signal strength value of the path loss reference signal PLRS sent by the network device.
  • the first transmission information is used by the terminal device to predict the path loss value between the terminal device and the network device.
  • a communication device comprising:
  • One or more processors wherein the communication device may be used to execute an optional implementation of the first aspect or the second aspect.
  • a communication system including a terminal device and a network device, wherein the terminal device is configured to perform the method described in the optional implementation of the first aspect, and the network device is configured to perform the method described in the optional implementation of the second aspect.
  • a storage medium stores instructions that, when executed on a communication device, cause the communication device to perform the method as described in an optional implementation of the first or second aspect.
  • the terminal device predicts the path loss value between the terminal device and the network device based on the first information.
  • the terminal device does not need to measure the downlink path loss reference signal; it can predict the path loss value between the terminal device and the network device based on the first information, thereby reducing the power consumption of the terminal device and saving electricity.
  • Figure 1A is a schematic diagram of the architecture of a communication system according to an embodiment of the present disclosure.
  • Figure 1B is a schematic diagram illustrating a measurement process according to an embodiment of the present disclosure.
  • Figure 1C is a schematic diagram illustrating a prediction process according to an embodiment of the present disclosure.
  • Figure 2A is an interactive schematic diagram of a communication method according to an embodiment of the present disclosure.
  • Figure 2B is a schematic diagram illustrating a model training according to an embodiment of the present disclosure.
  • Figure 2C is a schematic diagram illustrating a prediction process according to an embodiment of the present disclosure.
  • Figure 2D is a schematic diagram illustrating a prediction process according to an embodiment of the present disclosure.
  • Figure 3A is a flowchart illustrating a communication method according to an embodiment of the present disclosure.
  • Figure 3B is a flowchart illustrating a communication method according to an embodiment of the present disclosure.
  • Figure 3C is a flowchart illustrating a communication method according to an embodiment of the present disclosure.
  • Figure 3D is a flowchart illustrating a communication method according to an embodiment of the present disclosure.
  • Figure 3E is a flowchart illustrating a communication method according to an embodiment of the present disclosure.
  • Figure 4 is a flowchart illustrating a communication method according to an embodiment of the present disclosure.
  • Figure 5 is an interactive schematic diagram of a communication method according to an embodiment of the present disclosure.
  • Figure 6A is a schematic diagram of the structure of a terminal device proposed in an embodiment of this disclosure.
  • Figure 6B is a schematic diagram of the structure of a network device proposed in an embodiment of this disclosure.
  • Figure 7A is a schematic diagram of the structure of the communication device proposed in an embodiment of this disclosure.
  • Figure 7B is a schematic diagram of the chip structure proposed in an embodiment of this disclosure.
  • This disclosure provides a communication method, device, and storage medium.
  • embodiments of this disclosure provide a communication method, the method comprising:
  • the terminal device makes a prediction based on the first information to obtain the path loss value between the terminal device and the network device.
  • the terminal device does not need to measure the downlink path loss reference signal.
  • the path loss value between the terminal device and the network device is predicted based on the first information, thereby reducing the power consumption of the terminal device and saving power.
  • the first information includes at least the following parameters:
  • the first transmission information is the power value or signal strength value of the path loss reference signal PLRS transmitted by the network device within a first time period, where the first time period is the time period before the current moment.
  • the first received information is the power value or signal strength value of the PL RS measured by the terminal device within the first time period;
  • the first beam index is the beam index value corresponding to the PL RS;
  • the terminal device can predict the path loss value between the terminal device and the network device based on at least one of the first transmission information, the first reception information, the first beam index, and the first location, thereby improving the efficiency of obtaining the path loss value.
  • the terminal device predicts the path loss value between the terminal device and the network device based on the first information, including:
  • the first information is input into the first model to obtain the path loss value output by the first model, wherein the first model is an artificial intelligence (AI)/machine learning (ML) model.
  • AI artificial intelligence
  • ML machine learning
  • the path loss value between the terminal device and the network device can be predicted by AI/ML model, making the method of obtaining the path loss value simpler.
  • the first model is trained using first sample information, which includes at least the following parameters:
  • the second transmission information, the second reception information, the second beam index, and the second location of the terminal device are specified.
  • the second transmission information is the power value or signal strength value of the PL RS transmitted by the network device
  • the second reception information is the power value or signal strength value of the PL RS measured by the terminal device
  • the second beam index is the beam index value corresponding to the PL RS.
  • a first model can be obtained by training the first sample information.
  • the first sample information is information prior to the first information time period.
  • a first model can be trained based on the first sample information obtained before the first information.
  • the method further includes:
  • the system receives second information sent by the network device, the second information being used to indicate the first transmission information.
  • the network device may send second information indicating the first transmission information to the terminal device.
  • the uplink transmit power is determined based on the path loss value.
  • the terminal device can determine the uplink transmit power based on the path loss value, making the determination of the uplink transmit power more efficient.
  • embodiments of this disclosure provide a communication method, the method comprising:
  • the network device sends a second message to the terminal device.
  • the second message is used to indicate the first transmission message.
  • the first transmission message is the power value or signal strength value of the path loss reference signal PLRS sent by the network device.
  • the first transmission message is used by the terminal device to predict the path loss value between the terminal device and the network device.
  • the path loss value is used by the terminal device to determine the uplink transmit power.
  • embodiments of this disclosure provide a terminal device, which may include at least one of a transceiver module and a processing module.
  • the terminal device can be used to execute an optional implementation of the first aspect.
  • embodiments of this disclosure provide a network device that may include at least one of a transceiver module and a processing module; wherein the network device may be used to perform an optional implementation of the second aspect.
  • embodiments of this disclosure provide a terminal device that may include one or more processors; wherein the terminal device may be used to execute an optional implementation of the first aspect.
  • embodiments of this disclosure provide a network device that may include one or more processors; wherein the network device may be used to perform an optional implementation of the second aspect.
  • embodiments of this disclosure provide a communication system that may include: a terminal device and a network device; wherein the terminal device is configured to perform the method described in the optional implementation of the first aspect, and the network device is configured to perform the method described in the optional implementation of the second aspect.
  • embodiments of this disclosure provide a storage medium storing instructions that, when executed on a communication device, cause the communication device to perform the method as described in an optional implementation of the first or second aspect.
  • embodiments of this disclosure provide a program product that, when executed by a communication device, causes the communication device to perform the method as described in an optional implementation of the first or second aspect.
  • embodiments of this disclosure provide a computer program that, when run on a computer, causes the computer to perform the methods described in an optional implementation of the first or second aspect.
  • embodiments of this disclosure provide a chip or chip system.
  • the chip or chip system includes processing circuitry configured to perform the methods described in optional implementations of the first or second aspect.
  • This disclosure provides a communication method, device, and storage medium.
  • the terms “information transmission method” and “information processing method,” “communication method,” etc. can be used interchangeably; the terms “information transmission device” and “information processing device,” “communication device,” “communication equipment,” etc., can be used interchangeably; and the terms “information processing system,” “communication system,” etc., can be used interchangeably.
  • each step in a particular embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined.
  • a solution after removing some steps in a particular embodiment can also be implemented as an independent embodiment, and the order of the steps in a particular embodiment can be arbitrarily interchanged.
  • the optional implementation methods in a particular embodiment can be arbitrarily combined; moreover, the embodiments can be arbitrarily combined, for example, some or all steps of different embodiments can be arbitrarily combined, and a particular embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.
  • multiple can refer to two or more.
  • the terms “at least one of”, “one or more”, “a plurality of”, “multiple”, etc., may be used interchangeably.
  • the notation "at least one of A and B", “A and/or B", “A in one case, B in another”, “in response to one case A, in response to another case B”, etc. may include the following technical solutions depending on the situation: in some embodiments, A (execute A regardless of B); in some embodiments, B (execute B regardless of A); in some embodiments, execution is selected from A and B (A and B are selectively executed); in some embodiments, A and B (both A and B are executed). The same applies when there are more branches such as A, B, C, etc.
  • the notation "A or B” may include the following technical solutions, depending on the situation: in some embodiments, A (execution of A regardless of B); in some embodiments, B (execution of B regardless of A); in some embodiments, execution is selected from A and B (A and B are selectively executed). The same applies when there are more branches such as A, B, C, etc.
  • the descriptive object is a "field,” then the ordinal numbers before “field” in “first field” and “second field” do not restrict the position or order of the "fields,” nor do “first” and “second” restrict whether the "fields” they modify are in the same message, nor do they restrict the order of "first field” and “second field.”
  • the descriptive object is a "level,” then the ordinal numbers before “level” in “first level” and “second level” do not restrict the priority between “levels.”
  • the number of objects is not limited by ordinal numbers; there can be one or more. For example, in “first device,” the number of "devices" can be one or more.
  • objects modified by different prefixes can be the same or different. For instance, if the object is described as “device,” then “first device” and “second device” can be the same device or different devices, and their types can be the same or different. Similarly, if the object is described as “information,” then “first information” and “second information” can be the same information or different information, and their content can be the same or different.
  • “including A,” “containing A,” “for indicating A,” and “carrying A” can be interpreted as directly carrying A or indirectly indicating A.
  • the terms “in response to...”, “in response to determining...”, “in the case of...”, “when...”, “if...”, “if...”, etc., can be used interchangeably.
  • the terms “greater than,” “greater than or equal to,” “not less than,” “more than,” “more than or equal to,” “not less than,” “higher than,” “higher than or equal to,” “not lower than,” and “above” can be used interchangeably, as can the terms “less than,” “less than or equal to,” “not greater than,” “less than,” “less than or equal to,” “not more than,” “lower than,” “lower than or equal to,” “not higher than,” and “below”.
  • devices, etc. may be interpreted as physical or virtual, and their names are not limited to those described in the embodiments.
  • Terms such as “device,” “equipment,” “circuit,” “network element,” “node,” “function,” “unit,” “section,” “system,” “network,” “chip,” “chip system,” “entity,” and “subject” are interchangeable.
  • network can be interpreted as devices included in a network (e.g., access network devices, core network devices, etc.).
  • Access Network Device also refers to "Radio Access Network Device (RAN Device),” “Base Station (BS),” “Radio Base Station,” “Fixed Station,” “Node,” “Access Point,” “Transmission Point (TP),” “Reception Point (RP),” and “Transmission and/or Reception Point (RP).”
  • the terms “Reception Point (TRP),” “Panel,” “Antenna Panel,” “Antenna Array,” “Cell,” “Macro Cell,” “Small Cell,” “Femto Cell,” “Pico Cell,” “Sector,” “Cell Group,” “Serving Cell,” “Carrier,” “Component Carrier,” and “Bandwidth Part (BWP)” are interchangeable.
  • terminal In some embodiments, the terms "terminal”, “terminal device”, “user equipment (UE)”, “user terminal”, “mobile station (MS)”, “mobile terminal (MT)", “subscriber station”, “mobile unit”, “subscriber unit”, “wireless unit”, “remote unit”, “mobile device”, “wireless device”, “wireless communication device”, “remote device”, “mobile subscriber station”, “access terminal”, “mobile terminal”, “wireless terminal”, “remote terminal”, “handset”, “user agent”, “mobile client”, and “client” can be used interchangeably.
  • access network devices, core network devices, or network devices can be replaced with terminals.
  • embodiments of this disclosure can also be applied to structures where communication between access network devices, core network devices, or network devices and terminals is replaced with communication between multiple terminals (e.g., device-to-device (D2D), vehicle-to-everything (V2X), etc.).
  • the structure can also be configured such that the terminal has all or part of the functions of the access network device.
  • terms such as "uplink” and “downlink” can be replaced with terms corresponding to communication between terminals (e.g., "sidelink”).
  • uplink channel, downlink channel, etc. can be replaced with sidelink channel or direct channel
  • uplink link, downlink, etc. can be replaced with sidelink link or direct link.
  • the terminal may be replaced by an access network device, a core network device, or a network device.
  • the access network device, core network device, or network device may also be configured to have all or some of the functions of the terminal.
  • the acquisition of data, information, etc. may comply with the laws and regulations of the country where the location is situated.
  • data, information, etc. may be obtained with the user's consent.
  • each element, each row, or each column in the table of this disclosure can be implemented as an independent embodiment, and any combination of any element, any row, or any column can also be implemented as an independent embodiment.
  • Figure 1A is a schematic diagram of the architecture of a communication system according to an embodiment of the present disclosure.
  • the communication system 100 may include a terminal device 101 and a network device 102.
  • terminal device 101 may include at least one of the following: mobile phone, wearable device, Internet of Things device, car with communication function, smart car, tablet computer, computer with wireless transceiver function, virtual reality (VR) terminal device, augmented reality (AR) terminal device, wireless terminal device in industrial control, wireless terminal device in self-driving, wireless terminal device in remote medical surgery, wireless terminal device in smart grid, wireless terminal device in transportation safety, wireless terminal device in smart city, and wireless terminal device in smart home, but is not limited thereto.
  • VR virtual reality
  • AR augmented reality
  • network device 102 may include at least one of access network device and core network device.
  • the access network device may be a node or device that connects a terminal device to a wireless network.
  • the access network device may include, but is not limited to, at least one of the following in a 5G communication system: evolved Node B (eNB), next-generation evolved Node B (ng-eNB), next-generation Node B (gNB), node B (NB), home node B (HNB), home evolved node B (HeNB), radio backhaul device, radio network controller (RNC), base station controller (BSC), base transceiver station (BTS), base band unit (BBU), mobile switching center, base station in a 6G communication system, open RAN, cloud RAN, base station in other communication systems, and access node in a Wi-Fi system.
  • eNB evolved Node B
  • ng-eNB next-generation evolved Node B
  • gNB next-generation Node B
  • gNB next-generation Node B
  • NB node B
  • HNB home node B
  • HeNB home evolved node
  • the technical solutions of this disclosure can be applied to the Open RAN architecture.
  • the interfaces between or within access network devices involved in the embodiments of this disclosure can be transformed into internal interfaces of Open RAN.
  • the processes and information interactions between these internal interfaces can be implemented by software or programs.
  • the access network device may be composed of a central unit (CU) and a distributed unit (DU).
  • the CU may also be called a control unit.
  • the CU-DU structure can separate the protocol layer of the access network device. Some protocol layer functions are centrally controlled by the CU, while the remaining part or all protocol layer functions are distributed in the DU and centrally controlled by the CU. However, this is not the only possibility.
  • the core network equipment may be a single device, multiple devices, or a group of devices.
  • the core network may include at least one of the following: Evolved Packet Core (EPC), 5G Core Network (5GCN), and Next Generation Core (NGC).
  • EPC Evolved Packet Core
  • 5GCN 5G Core Network
  • NGC Next Generation Core
  • the following embodiments of this disclosure can be applied to the communication system 100 shown in FIG1A, or to some of the main bodies, but are not limited thereto.
  • the main bodies shown in FIG1A are examples.
  • the communication system may include all or some of the main bodies in FIG1A, or it may include other main bodies outside of FIG1A.
  • the number and form of each main body are arbitrary.
  • Each main body may be physical or virtual.
  • the connection relationship between the main bodies is an example.
  • the main bodies may not be connected or may be connected.
  • the connection can be in any way, it can be a direct connection or an indirect connection, it can be a wired connection or a wireless connection.
  • LTE Long Term Evolution
  • LTE-A LTE-Advanced
  • LTE-B LTE-Beyond
  • SUPER 3G IMT-Advanced
  • 4G 4th generation mobile communication system
  • 5G 5th generation mobile communication system
  • 5G 5G New Radio
  • F New Radio Access
  • RAT New Radio
  • NX New Radio Access
  • F Future generation radio access
  • GSM Global System for Mobile communications
  • CDMA2000 Global System for Mobile communications
  • UMB Ultra Mobile Broadband
  • IEEE 802.11 Wi-Fi (registered trademark)
  • IEEE 802.16 WiMAX (registered trademark)
  • IEEE 802.20 Ultra-Wideband (UWB)
  • Bluetooth registered trademark
  • PLMN Public Land Mobile Network
  • D2D Device-to-Device
  • M2M Machine-to-Machine
  • IoT Internet of Things
  • V2X Vehicle-to-Everything
  • V2X Vehicle-to-Everything
  • systems utilizing other communication methods and next-generation systems extended from them.
  • next-generation systems extended from them can be combined (e.g., a combination of LTE or LTE-A with 5G).
  • the 5G NR system introduces prediction based on Artificial Intelligence (AI)/Machine Learning (ML) models to simplify processes and improve performance in certain scenarios.
  • AI Artificial Intelligence
  • ML Machine Learning
  • One typical scenario is the uplink power control process.
  • the UE determines the uplink transmission power according to the following formula:
  • P PRACH,b,f,c (i) min ⁇ P CMAX,f,c (i),P PRACH,target,f,c +PL b,f,c ⁇ [dBm] (1)
  • P PRACH,b,f,c (i) is the UE's transmit power
  • b represents ULBWP
  • f is the carrier frequency
  • c is the serving cell
  • P CMAX,f,c (i) is the configured maximum transmit power of the UE, the protocol value is defined in 38.101-1
  • P PRACH,target,f,c is the target PRACH's receive power on the network side
  • PL b,f,c is the path loss value obtained by the UE based on DLRS measurement.
  • Path loss is the power pulsation (PL) value evaluated based on the signal strength of the downlink reference signal (SSB or CSI-RS) measured by the UE.
  • Figure 1B is a schematic diagram of a measurement process according to an embodiment of this disclosure. As shown in Figure 1B, the UE needs to frequently measure the downlink PLRS, resulting in high power consumption. Furthermore, if the channel changes rapidly, the downlink measurement cannot accurately reflect the current PL value.
  • FIG. 1C is a schematic diagram illustrating a prediction process according to an embodiment of the present disclosure. As shown in Figure 1C, the UE can predict the PL value through AI, and then determine the uplink transmission power based on the predicted PL value.
  • Figure 2A is an interactive schematic diagram illustrating a communication method according to an embodiment of the present disclosure. This method can be executed by the aforementioned communication system. As shown in Figure 2A, the method may include:
  • Step S2101 The network device sends the second information to the terminal device.
  • the terminal device may receive second information.
  • the terminal device may receive second information sent by a network device.
  • the terminal device may also receive second information sent by other entities.
  • the second information may be used to indicate the first transmission information.
  • the first transmission information may be the power value or signal strength value of a path loss reference signal (PLRS) sent by the network device.
  • PLRS path loss reference signal
  • "emission” may also be referred to as "sending”.
  • the PL RS can be a downlink reference signal, such as a synchronization signal block (SSB) and/or a channel state information reference signal (CSI-RS), which is not limited in this disclosure.
  • SSB synchronization signal block
  • CSI-RS channel state information reference signal
  • the first transmission information could be the power value or signal strength value of the SSB, or, for another example, the first transmission information could be the power value or signal strength value of the CSI-RS.
  • the first transmission information may be a power value or signal strength value of a PL RS, or it may include power values or signal strength values of multiple PL RSs.
  • the network device may transmit the power values or signal strength values of the PL RS at different times according to the protocol.
  • a network device when a network device sends a PL RS to a terminal device, it may simultaneously send the second information to the terminal device.
  • the network device may also send second information indicating the power value or signal strength value of the PLRS to the terminal device before or after sending the PLRS to the terminal device, and this disclosure does not limit this.
  • the first transmission information can be used by the terminal device to predict the path loss value between the terminal device and the network device.
  • the name of the first transmission information is not limited, and may be, for example, “first transmission power” or “first signal strength”.
  • Step S2102 The terminal device inputs the first information into the first model and obtains the path loss value output by the first model.
  • the first information may include at least the following parameters:
  • the first transmission information is the power value or signal strength value of the PL RS transmitted by the network device within a first time period, where the first time period is the time period before the current moment;
  • the first received information is the power value or signal strength value of the PL RS measured by the terminal device within the first time period;
  • the first beam index is the beam index value corresponding to the PL RS;
  • the current position of the terminal device is the current position of the terminal device.
  • the first transmission information may be the power value or signal strength value of a PL RS received by the terminal device within the first time period.
  • the PL RS may be any PL RS received by the terminal device within the first time period, or, for another example, the PL RS may be the last PL RS received by the terminal device within the first time period, i.e., the last PL RS received by the terminal device before the current time.
  • the first transmission information may be the power value or signal strength value of a plurality of PL RS received by the terminal device within the first time period.
  • the first transmission information may be the average power value or average signal strength value of the plurality of PL RS transmitted by the network device; or, for another example, the first transmission information may be the maximum power value or maximum signal strength value among the plurality of PL RS transmitted by the network device; or, for yet another example, the first transmission information may be the minimum power value or minimum maximum signal strength value among the plurality of PL RS transmitted by the network device.
  • the terminal device may store each first transmission information received within the first time period.
  • the terminal device may receive PL RS sent by the network device.
  • the terminal device may measure the received PL RS to obtain the power value or signal strength value of the PL RS.
  • the first received information may be the power value or signal strength value of a PL RS measured by the terminal device within the first time period.
  • the PL RS may be any PL RS received by the terminal device within the first time period, or, for another example, the PL RS may be the last PL RS received by the terminal device within the first time period, i.e., the last PL RS received by the terminal device before the current time.
  • the first received information may be the power value or signal strength value of a plurality of PLRS measured by the terminal device within the first time period.
  • the first received information may be the average power value or average signal strength value of the plurality of PLRS measured by the terminal device; or, for another example, the first received information may be the maximum power value or maximum signal strength value among the plurality of PLRS measured by the terminal device.
  • the first received information may be the minimum power value or the minimum maximum signal strength value among the plurality of PL RS measured by the terminal device.
  • the first transmission information and the first reception information may correspond to the same PLRS.
  • the first transmission information is the power value or signal strength value of the PLRS transmitted by the network device at a first moment
  • the first reception information is the power value or signal strength value of the PLRS transmitted by the network device at a first moment measured by the terminal device.
  • first transmission information and the first reception information may correspond to different PL RS, and this embodiment of the present disclosure does not limit this.
  • the first beam index may be the index value of the beam used by the network device to transmit PL RS.
  • the first transmit information is the power value or signal strength value of the PL RS transmitted by the network device at a first moment
  • the first receive information is the power value or signal strength value of the PL RS transmitted by the network device at a first moment measured by the terminal device
  • the first beam index is the index value of the beam used by the network device when transmitting PL RS at the first moment.
  • the first location may be the location where the terminal device measures the power value or signal strength value of the PL RS.
  • the first model may be an AI/ML model.
  • the first model can be used to predict the path loss value between the terminal device and the network device.
  • the first model is trained using first sample information, which may include at least the following parameters:
  • the second transmit information, the second receive information, the second beam index, and the second location of the terminal device are included.
  • the second transmit information is the power value or signal strength value of the PL RS sent by the network device
  • the second receive information is the power value or signal strength value of the PL RS measured by the terminal device
  • the second beam index is the beam index value corresponding to the PL RS.
  • the method of obtaining the first sample information can refer to the method of obtaining the first information described above, and will not be repeated here.
  • the PL RS corresponding to the first sample information can be any PL RS obtained within a historical time period, and this disclosure does not limit this.
  • the model after obtaining the first sample information, can be trained based on the first sample information to obtain the first model.
  • the first model can be obtained by training the model using multiple first sample information.
  • the multiple first sample information may be information acquired by the terminal device at different locations and/or at different times.
  • the first sample information may be information prior to the first information time period.
  • the first sample information can be information obtained before the current moment.
  • Figure 2B is a schematic diagram illustrating model training according to an embodiment of the present disclosure. As shown in Figure 2B, by inputting the second transmission information, the second reception information, the second beam index, and the second position of the terminal device into the AI/ML model, a predicted path loss value can be output.
  • the training process of the first model can be described with reference to existing technology, and will not be repeated here.
  • the terminal device can input the first transmission information, the first reception information, the first beam index, and the first location into the first model to obtain the path loss value between the terminal device and the network device output by the first model.
  • the first model can be trained using any one or more pieces of information from the first sample information.
  • a first model trained with different information can predict path loss values for different scenarios.
  • a first model trained with second transmit information, second receive information, and a second beam index can be used to predict path loss values for a future time period; as another example, a first model trained with second transmit information, a second beam index, and a second location can be used to predict path loss values for a specified location.
  • the parameters input to the first model are the same as the parameters used to train the first model.
  • the information input when predicting path loss values using the first model can include the first transmit information, the first receive information, and the first beam index.
  • the first model can be used to predict path loss values over a time period.
  • the first model can be trained using second transmission information, second reception information, and a second beam index.
  • the second transmission information is the power value or signal strength value of the PL RS sent by the network device
  • the second reception information is the power value or signal strength value of the PL RS measured by the terminal device
  • the second beam index is the beam index value corresponding to the PL RS.
  • the first information input to the first model may include at least the following parameters:
  • the first transmission information, the first reception information, and the first beam index are the first transmission information, the first reception information, and the first beam index.
  • the first terminal can input the first transmission information, the first reception information, and the first beam index into the first model to obtain the path loss value of the second time period output by the first model, wherein the second time period is the time period after the first time period.
  • the first time period is (1,...,i-1), and the second time period is (i,...,i+j).
  • i can be the current time, that is, the first time period includes the time period before the current time, and the second time period can include the current time and the time period after the current time.
  • Figure 2C is a schematic diagram illustrating a prediction process according to an embodiment of the present disclosure.
  • the input of the first model is a first time...
  • the first transmission information of the first interval, the first reception information of the first time period, and the first beam index of the first time period are used as the output of the first model, which is the path loss value of the second time period.
  • the first model can be used to predict the path loss value at a location.
  • the first model can be trained using second transmission information, a second beam index, and a second location of the terminal device.
  • the second transmission information is the power value or signal strength value of the PL RS sent by the network device
  • the second beam index is the beam index value corresponding to the PL RS.
  • the first information input to the first model may include at least the following parameters:
  • the first transmission information the first beam index, and the first position.
  • the first terminal can input the first transmission information, the first beam index, and the first position into the first model to obtain the path loss value of the first position output by the first model.
  • path loss value at the first location can be understood as “path loss value of the terminal device at the first location during the second time period”.
  • path loss value of the terminal device at the first location at time i can be predicted.
  • Figure 2D is a schematic diagram illustrating a prediction process according to an embodiment of the present disclosure.
  • the inputs of the first model are the first transmission information at time i, the first beam index, and the first position at time i
  • the output of the first model is the path loss value at the first position at time i.
  • Step S2103 The terminal device determines the uplink transmission power based on the path loss value.
  • terminal devices can determine the uplink transmit power according to the methods defined in the existing protocols, which will not be elaborated here.
  • the terminal device does not need to measure the downlink path loss reference signal.
  • the path loss value between the terminal device and the network device is predicted based on the first information to determine the uplink transmission power, thereby reducing the power consumption of the terminal device and saving power.
  • step S2101 may be implemented as an independent embodiment
  • step S2102 may be implemented as an independent embodiment
  • step S2103 may be implemented as an independent embodiment
  • step S2101 + step S2102 may be implemented as an independent embodiment
  • any two steps in steps S2101 to S2103 can be interchanged or they can be performed simultaneously.
  • steps S2101 to S2103 are optional, and one or more of these steps may be omitted or substituted in different embodiments.
  • step S2101 may be omitted.
  • the names of information, etc. are not limited to the names described in the embodiments.
  • Terms such as “information”, “message”, “signal”, “signaling”, “report”, “configuration”, “indication”, “instruction”, “command”, “channel”, “parameter”, “domain”, “field”, “symbol”, “symbol”, “codebook”, “codeword”, “codepoint”, “bit”, “data”, “program”, and “chip” can be used interchangeably.
  • “get,” “obtain,” “receive,” “transmit,” “bidirectional transmission,” and “send and/or receive” can be used interchangeably and can be interpreted as receiving from other entities, obtaining from protocols, obtaining from higher layers, obtaining through self-processing, or autonomous implementation, among other meanings.
  • terms such as “certain,” “preset,” “default,” “set,” “indicated,” “a certain,” “any,” and “first” can be used interchangeably.
  • “Certain A,” “preset A,” “default A,” “set A,” “indicated A,” “a certain A,” “any A,” and “first A” can be interpreted as A pre-defined in a protocol or the like, or as A obtained through setting, configuration, or instruction, or as specific A, a certain A, any A, or first A, but are not limited thereto.
  • Figure 3A is a flowchart illustrating a communication method according to an embodiment of the present disclosure. As shown in Figure 3A, the present disclosure relates to a communication method that can be executed by a terminal device. The method may include:
  • Step S3101 Receive the second information.
  • step S3101 can be found in the optional implementation of step S2101 in Figure 2A and other related parts in the embodiments involved in Figure 2A, which will not be repeated here.
  • Step S3102 Input the first information into the first model to obtain the path loss value output by the first model.
  • step S3102 can be found in the optional implementation of step S2102 in Figure 2A and other related parts in the embodiments involved in Figure 2A, which will not be repeated here.
  • Step S3103 Determine the uplink transmit power based on the path loss value.
  • step S3103 can be found in the optional implementation of step S2103 in Figure 2A and other related parts in the embodiments involved in Figure 2A, which will not be repeated here.
  • step S3101 may be implemented as an independent embodiment
  • step S3102 may be implemented as an independent embodiment
  • step S3103 may be implemented as an independent embodiment
  • step S3101 + step S3102 may be implemented as an independent embodiment
  • any two steps in steps S3101 to S3103 can be interchanged or they can be performed simultaneously.
  • steps S3101 to S3103 are optional, and one or more of these steps may be omitted or substituted in different embodiments.
  • step S3101 may be omitted.
  • Figure 3B is a flowchart illustrating a communication method according to an embodiment of the present disclosure. As shown in Figure 3B, the present disclosure relates to a communication method that can be executed by a terminal device. The method may include:
  • Step S3201 Receive the second information.
  • step S3201 can be found in the optional implementation of step S2101 in Figure 2A, and other related parts in the embodiments involved in Figure 2A, which will not be repeated here.
  • Step S3202 Input the first transmission information, the first reception information, and the first beam index into the first model to obtain the path loss value of the second time period output by the first model.
  • step S3202 can be found in the optional implementation of step S2102 in Figure 2A, as well as other related parts in the embodiments involved in Figure 2A, which will not be repeated here.
  • Step S3203 Determine the uplink transmit power based on the path loss value.
  • step S3203 can be found in the optional implementation of step S2103 in Figure 2A, as well as other related parts in the embodiments involved in Figure 2A, which will not be repeated here.
  • the above steps are all optional.
  • step S3201 may be implemented as a separate embodiment
  • step S3202 may be implemented as a separate embodiment
  • step S3203 may be implemented as a separate embodiment
  • step S3201 + step S3202 may be implemented as a separate embodiment.
  • any two steps in steps S3201 to S3203 can be interchanged or they can be performed simultaneously.
  • steps S3201 to S3203 are optional, and one or more of these steps may be omitted or substituted in different embodiments.
  • step S3201 may be omitted.
  • Figure 3C is a flowchart illustrating a communication method according to an embodiment of the present disclosure. As shown in Figure 3C, the present disclosure relates to a communication method that can be executed by a terminal device. The method may include:
  • Step S3301 Receive the second information.
  • step S3301 can be found in the optional implementation of step S2101 in Figure 2A, and other related parts in the embodiments involved in Figure 2A, which will not be repeated here.
  • Step S3302 Input the first transmission information, the first beam index and the first position into the first model to obtain the path loss value of the first position output by the first model.
  • step S3302 can be found in the optional implementation of step S2102 in Figure 2A, as well as other related parts in the embodiments involved in Figure 2A, which will not be repeated here.
  • Step S3303 Determine the uplink transmit power based on the path loss value.
  • step S3303 can be found in the optional implementation of step S2103 in Figure 2A, as well as other related parts in the embodiments involved in Figure 2A, which will not be repeated here.
  • step S3301 may be implemented as an independent embodiment
  • step S3302 may be implemented as an independent embodiment
  • step S3303 may be implemented as an independent embodiment
  • step S3301 + step S3302 may be implemented as an independent embodiment
  • any two steps in steps S3301 to S3303 can be interchanged or they can be performed simultaneously.
  • steps S3301 to S3303 are optional, and one or more of these steps may be omitted or substituted in different embodiments.
  • step S3301 may be omitted.
  • Figure 3D is a flowchart illustrating a communication method according to an embodiment of the present disclosure. As shown in Figure 3D, the present disclosure relates to a communication method that can be executed by a terminal device. The method may include:
  • Step S3401 Train the first model using the first sample information to obtain the first model.
  • the first sample information may include at least the following parameters: second transmission information, second reception information, second beam index, and second location of the terminal device.
  • step S3401 can be found in the explanation of step S2102 in Figure 2A, and will not be repeated here.
  • the first model can be trained using the second transmitted information, the second received information, and the second beam index; as another example, the first model can be trained using the second transmitted information, the second beam index, and the second position; yet another example, the first model can be trained using the second transmitted information, the second received information, and the second beam index.
  • the first model is obtained by training the received information.
  • Step S3402 Input the first information into the first model to obtain the path loss value output by the first model.
  • the first information may include at least the following parameters: first transmission information, first reception information, first beam index, and first position.
  • step S3402 can be found in the explanation of step S2102 in Figure 2A, and will not be repeated here.
  • the first information input to the first model may include at least one of first transmission information, first reception information, and first beam index.
  • the first information may include first transmission information, first reception information, and first beam index; for another example, the first information may include first transmission information and first reception information; for yet another example, the first information may include first transmission information and first beam index; and for yet another example, the first information may include first transmission information.
  • the first information input to the first model may include at least one of first transmission information, first beam index, and first position.
  • the first information may include first transmission information, first beam index, and first position; for another example, the first information may include first transmission information and first position; for yet another example, the first information may include first beam index and first position; and for yet another example, the first information may include first position.
  • Figure 3E is a flowchart illustrating a communication method according to an embodiment of the present disclosure. As shown in Figure 3E, the present disclosure relates to a communication method that can be executed by a terminal device. The method may include:
  • Step S3501 Based on the first information, make a prediction to obtain the path loss value between the terminal device and the network device.
  • step S3501 can be found in the optional implementations of step S2101 in Figure 2A, step S3101 in Figure 3A, step S3201 in Figure 3B, step S3301 in Figure 3C, and step S3401 in Figure 3D, as well as other related parts in the embodiments involved in Figures 2A, 3A, 3B, 3C, and 3D, which will not be repeated here.
  • the first information includes at least the following parameters:
  • the first transmission information is the power value or signal strength value of the path loss reference signal PLRS transmitted by the network device within a first time period, where the first time period is the time period before the current moment.
  • the first received information is the power value or signal strength value of the PL RS measured by the terminal device within the first time period;
  • the first beam index is the beam index value corresponding to the PL RS;
  • the terminal device predicts the path loss value between the terminal device and the network device based on the first information, including:
  • the first information is input into the first model to obtain the path loss value output by the first model, wherein the first model is an artificial intelligence (AI)/machine learning (ML) model.
  • AI artificial intelligence
  • ML machine learning
  • the first model is trained using first sample information, which includes at least the following parameters:
  • the second transmission information, the second reception information, the second beam index, and the second location of the terminal device are specified.
  • the second transmission information is the power value or signal strength value of the PL RS transmitted by the network device
  • the second reception information is the power value or signal strength value of the PL RS measured by the terminal device
  • the second beam index is the beam index value corresponding to the PL RS.
  • the first sample information is information prior to the first information time period.
  • the method further includes:
  • the system receives second information sent by the network device, the second information being used to indicate the first transmission information.
  • the method further includes:
  • the uplink transmit power is determined based on the path loss value.
  • Figure 4 is a flowchart illustrating a communication method according to an embodiment of the present disclosure. As shown in Figure 4, the present disclosure relates to a communication method that can be executed by a network device. The method may include:
  • Step S4101 Send the second message.
  • step S4101 can be found in the optional implementation of step S2101 in Figure 2A, and other related parts in the embodiments involved in Figure 2A, which will not be repeated here.
  • the second information is used to indicate first transmission information, where the first transmission information is the power value or signal strength value of the path loss reference signal (PLRS) transmitted by the network device.
  • the first transmission information is used by the terminal device to predict the terminal device's... The path loss value between the network device and the network device.
  • the path loss value is used by the terminal device to determine the uplink transmit power.
  • Figure 5 is an interactive schematic diagram illustrating a communication method according to an embodiment of the present disclosure. As shown in Figure 5, the present disclosure relates to a communication method that can be executed by a communication system. The method may include:
  • Step S5101 The network device sends the second information to the terminal device.
  • step S5101 can be found in the optional implementations of step S2101 in Figure 2A, step S3101 in Figure 3A, step S3201 in Figure 3B, step S3301 in Figure 3C, step S3401 in Figure 3D, step S4101 in Figure 4, and other related parts in the embodiments involved in Figures 2A, 3A, 3B, 3C, 3D, and 4, which will not be repeated here.
  • Step S5102 The terminal device makes a prediction based on the first information to obtain the path loss value between the terminal device and the network device.
  • step S5102 can be found in the optional implementations of step S2102 in Figure 2A, step S3102 in Figure 3A, step S3202 in Figure 3B, step S3302 in Figure 3C, and step S3402 in Figure 3D, as well as other related parts in the embodiments involved in Figures 2A, 3A, 3B, 3C, and 3D, which will not be repeated here.
  • the above methods may include the methods described in the embodiments of the communication system, terminal device, network device, etc., which will not be repeated here.
  • an AI/ML model is trained based on dataset A (SetA) and outputs a path loss PL value that meets performance requirements, wherein the data parameters of the dataset (SetA) used for model training include at least one or more of the following parameter information:
  • the measurement results of the PLRS measurement sample (received power value (Pr) or received signal strength value (Rx_RSRP));
  • the output of training an AI/ML model is the path loss PL value.
  • input dataset B (Set B) predict and output the path loss PL value, wherein the data parameter information of the dataset (Set B) used for model prediction can be in the following manner:
  • the measurement results of the PLRS measurement sample (received power value (Pr) or received signal strength value (Rx_RSRP));
  • the path loss PL value is predicted within a certain time period (time i,...,i+j).
  • the input data are the power value/RSRP value of the transmitted and measured PLRS and the corresponding beam index value of the PLRS within a certain time period (time 1,...,i-1).
  • the path loss PL value of the current UE location is predicted within a certain time period (time i,...,i+j).
  • the input data are the current UE location information, the signal transmitted by the PLRS, and the corresponding beam index value of the PLRS.
  • a communication system may include a terminal device and a network device, wherein the terminal device may execute the communication method executed by the terminal device in the foregoing embodiments of this disclosure; and the network device may execute the communication method executed by the network device in the foregoing embodiments of this disclosure.
  • This disclosure also provides an apparatus for implementing any of the above methods.
  • an apparatus is provided that includes units or modules for implementing the steps performed by the terminal in any of the above methods.
  • another apparatus is provided that includes units or modules for implementing the steps performed by a network device (e.g., an access network device, a core network functional node, a core network device, etc.) in any of the above methods.
  • a network device e.g., an access network device, a core network functional node, a core network device, etc.
  • the division of units or modules in the above device is only a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated.
  • the units or modules in the device can be implemented by a processor calling software: for example, the device includes a processor connected to a memory containing instructions. The processor calls the instructions stored in the memory to implement any of the above methods or to implement the functions of the units or modules in the above device.
  • the processor can be, for example, a general-purpose processor, such as a Central Processing Unit (CPU) or a microprocessor, and the memory can be internal or external to the device.
  • the units or modules in the device can be implemented in the form of hardware circuits.
  • the functions of some or all of the units or modules can be achieved through the design of the hardware circuits, which can be understood as one or more processors.
  • the hardware circuit is an Application-Specific Integrated Circuit (ASIC), and the functions of some or all of the units or modules are achieved through the design of the logical relationships between the components within the circuit.
  • the hardware circuit can be implemented using a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), which can include... It includes a large number of logic gates, and the connection relationships between the logic gates are configured through configuration files to realize the functions of some or all of the above units or modules. All units or modules of the above device can be implemented entirely through processor calling software, entirely through hardware circuits, or partially through processor calling software with the remainder implemented through hardware circuits.
  • PLD Programmable Logic Device
  • FPGA Field Programmable Gate Array
  • the processor is a circuit with signal processing capabilities.
  • the processor can be a circuit with instruction read and execute capabilities, such as a Central Processing Unit (CPU), a microprocessor, a Graphics Processing Unit (GPU) (which can be understood as a microprocessor), or a Digital Signal Processor (DSP).
  • the processor can implement certain functions through the logical relationships of hardware circuits. The logical relationships of the aforementioned hardware circuits are fixed or reconfigurable.
  • the processor is a hardware circuit implemented using an Application-Specific Integrated Circuit (ASIC) or a Programmable Logic Device (PLD), such as an FPGA.
  • ASIC Application-Specific Integrated Circuit
  • PLD Programmable Logic Device
  • the process of the processor loading a configuration document and configuring the hardware circuit can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units or modules.
  • it can also be hardware circuits designed for artificial intelligence, which can be understood as ASICs, such as Neural Network Processing Unit (NPU), Tensor Processing Unit (TPU), Deep Learning Processing Unit (DPU), etc.
  • ASICs such as Neural Network Processing Unit (NPU), Tensor Processing Unit (TPU), Deep Learning Processing Unit (DPU), etc.
  • FIG. 6A is a schematic diagram of the structure of a terminal device according to an embodiment of this disclosure.
  • the terminal device 101 may include at least one of a processing module 6101, a transceiver module 6102, etc.
  • the processing module 6101 is configured to predict the path loss value between the terminal device and the network device based on first information.
  • the processing module 6101 may be used to perform at least one of the processing steps (e.g., step S2102, but not limited thereto) performed by the terminal device 101 in any of the above methods, which will not be elaborated here.
  • the transmitting module and the receiving module may be separate or integrated together.
  • the transceiver module may be interchangeable with a transceiver.
  • the processing module may be a single module or may include multiple sub-modules.
  • the multiple sub-modules may each perform all or part of the steps required by the processing module.
  • the processing module may be interchangeable with a processor.
  • FIG. 6B is a schematic diagram of the structure of a network device according to an embodiment of this disclosure.
  • the network device 102 may include at least one of a transceiver module 6201, a processing module 6202, etc.
  • the transceiver module 6201 is configured to send second information to a terminal device, the second information being used to indicate first transmission information, the first transmission information being the power value or signal strength value of a path loss reference signal PLRS sent by the network device, and the first transmission information being used by the terminal device to predict the path loss value between the terminal device and the network device.
  • the transceiver module 6201 may be used to perform at least one of the communication steps such as sending and/or receiving performed by the network device 102 in any of the above methods (e.g., step S2101, but not limited thereto), which will not be elaborated here.
  • the transceiver module may include a transmitting module and/or a receiving module, which may be separate or integrated.
  • the transceiver module may be interchangeable with a transceiver.
  • FIG. 7A is a schematic diagram of the structure of the communication device 7100 proposed in an embodiment of this disclosure.
  • the communication device 7100 can be a network device (e.g., access network device, core network device, etc.), a terminal (e.g., user equipment, etc.), a chip, chip system, or processor that supports the first device in implementing any of the above methods, or a chip, chip system, or processor that supports the terminal in implementing any of the above methods.
  • the communication device 7100 can be used to implement the methods described in the above method embodiments; for details, please refer to the descriptions in the above method embodiments.
  • the communication device 7100 includes one or more processors 7101.
  • the processor 7101 can be a general-purpose processor or a dedicated processor, such as a baseband processor or a central processing unit (CPU).
  • the baseband processor can be used to process communication protocols and communication data, while the CPU can be used to control communication devices (e.g., base stations, baseband chips, IoT devices, IoT device chips, DUs or CUs, etc.), execute programs, and process program data.
  • the communication device 7100 is used to execute any of the above methods.
  • the communication device 7100 further includes one or more memories 7102 for storing instructions.
  • the memories 7102 may also be located outside the communication device 7100.
  • the communication device 7100 further includes one or more transceivers 7103.
  • the transceivers 7103 perform at least one of the communication steps such as sending and/or receiving in the above method (e.g., step S2101, but not limited thereto), and the processor 7101 performs at least one of other steps (e.g., step S2102, but not limited thereto).
  • a transceiver may include a receiver and/or a transmitter, which may be separate or integrated.
  • the terms transceiver, transceiver unit, transceiver, transceiver circuit, etc. may be used interchangeably; the terms transmitter, transmitting unit, transmitter, transmitting circuit, etc., may be used interchangeably; and the terms receiver, receiving unit, receiver, receiving circuit, etc., may be used interchangeably.
  • the communication device 7100 may include one or more interface circuits.
  • the interface circuit is connected to the memory 7102, and the interface circuit can be used to receive signals from the memory 7102 or other devices, and can be used to send signals to the memory 7102 or other devices.
  • the interface circuit can read instructions stored in the memory 7102 and send the instructions to the processor 7101.
  • the communication device 7100 described in the above embodiments may be a first device or an Internet of Things (IoT) device, but the scope of the communication device 7100 described in this disclosure is not limited thereto, and the structure of the communication device 7100 may not be limited by FIG. 7A.
  • the communication device may be a standalone device or may be part of a larger device.
  • the communication device may be: (1) a standalone integrated circuit IC, or chip, or chip system or subsystem; (2) a collection of one or more ICs, optionally, the IC collection may also include storage components for storing data and programs; (3) ASICs, such as modems; (4) modules that can be embedded in other devices; (5) receivers, IoT devices, smart IoT devices, cellular phones, wireless devices, handheld devices, mobile units, vehicle-mounted devices, first devices, cloud devices, artificial intelligence devices, etc.; (6) others, etc.
  • Figure 7B is a schematic diagram of the structure of the chip 7200 according to an embodiment of this disclosure.
  • the communication device 7100 can be a chip or a chip system
  • the schematic diagram of the chip 7200 shown in Figure 7B can be referenced, but is not limited thereto.
  • Chip 7200 includes one or more processors 7201, which are used to perform any of the above methods.
  • chip 7200 further includes one or more interface circuits 7203.
  • interface circuit 7203 is connected to memory 7202, and interface circuit 7203 can be used to receive signals from memory 7202 or other devices, and interface circuit 7203 can be used to send signals to memory 7202 or other devices.
  • interface circuit 7203 can read instructions stored in memory 7202 and send the instructions to processor 7201.
  • the interface circuit 7203 performs at least one of the communication steps such as sending and/or receiving in the above method (e.g., step S2101, but not limited thereto), and the processor 7201 performs at least one of the other steps (e.g., step S2102, but not limited thereto).
  • interface circuit In some embodiments, the terms interface circuit, interface, transceiver pin, transceiver, etc., can be used interchangeably.
  • chip 7200 further includes one or more memories 7202 for storing instructions.
  • all or part of the memories 7202 may be located outside of chip 7200.
  • This disclosure also proposes a storage medium storing instructions that, when executed on a communication device 7100, cause the communication device 7100 to perform any of the above methods.
  • the storage medium is an electronic storage medium.
  • the storage medium is a computer-readable storage medium, but not limited thereto; it may also be a storage medium readable by other devices.
  • the storage medium may be a non-transitory storage medium, but not limited thereto; it may also be a temporary storage medium.
  • This disclosure also provides a program product that, when executed by the communication device 7100, causes the communication device 7100 to perform any of the above methods.
  • the program product may be a computer program product.
  • This disclosure also proposes a computer program that, when run on a computer, causes the computer to perform any of the above methods.

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Abstract

本公开涉及一种通信方法、设备和存储介质。该方法包括：终端设备根据第一信息进行预测，得到所述终端设备与网络设备之间的路径损耗值。也就是说，终端设备不需要对下行路径损耗参考信号进行测量，根据第一信息预测得到终端设备与网络设备之间的路径损耗值，从而降低了终端设备的功耗，节省电量。

Description

通信方法、设备和存储介质 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、设备和存储介质。
背景技术
机器学习算法是目前人工智能(Artificial Intelligence，AI)技术最重要的实现方法之一。通过机器学习对大量的训练数据进行学习，可以获得AI模型，通过AI模型可以对事件进行预测。在很多领域，机器学习训练得到的AI模型都可以获得非常精准的预测结果。在通信领域，也可以通过AI模型得到某些场景下的预测数据，以便提升网络性能。
发明内容
本公开实施例提出了一种通信方法、设备和存储介质。
根据本公开实施例的第一方面，提出了一种通信方法，所述方法包括：
终端设备根据第一信息进行预测，得到所述终端设备与网络设备之间的路径损耗值。
根据本公开实施例的第二方面，提出了一种通信方法，所述方法包括：
网络设备向终端设备发送第二信息，所述第二信息用于指示第一发射信息，所述第一发射信息为所述网络设备发送的路径损耗参考信号PL RS的功率值或者信号强度值，所述第一发射信息用于所述终端设备预测所述终端设备与所述网络设备之间的路径损耗值。
根据本公开实施例的第三方面，提出了一种终端设备，包括：
处理模块，被配置为根据第一信息进行预测，得到所述终端设备与网络设备之间的路径损耗值。
根据本公开实施例的第四方面，提出了一种网络设备，包括：
收发模块，被配置为向终端设备发送第二信息，所述第二信息用于指示第一发射信息，所述第一发射信息为所述网络设备发送的路径损耗参考信号PL RS的功率值或者信号强度值，所述第一发射信息用于所述终端设备预测所述终端设备与所述网络设备之间的路径损耗值。
根据本公开实施例的第五方面，提出了一种通信设备，包括：
一个或多个处理器；其中，该通信设备可以用于执行第一方面或第二方面的可选实现方式。
根据本公开实施例的第六方面，提出了一种通信系统，包括终端设备与网络设备，其中，所述终端设备被配置为执行如第一方面的可选实现方式所描述的方法，所述网络设备被配置为执行如第二方面的可选实现方式所描述的方法。
根据本公开实施例的第七方面，提出了一种存储介质，该存储介质存储有指令，当该指令在通信设备上运行时，使得该通信设备执行如第一方面或第二方面的可选实现方式所描述的方法。
本公开实施例提供的技术方案可以产生以下有益效果：终端设备根据第一信息进行预测，得到所述终端设备与网络设备之间的路径损耗值。也就是说，终端设备不需要对下行路径损耗参考信号进行测量，根据第一信息预测得到终端设备与网络设备之间的路径损耗值，从而降低了终端设备的功耗，节省电量。
应当理解的是，以上的一般描述和后文的细节描述仅是示例性和解释性的，并不能限制本公开。
附图说明
为了更清楚地说明本公开实施例中的技术方案，以下对实施例描述所需的附图进行介绍，以下附图仅仅是本公开的一些实施例，不对本公开的保护范围造成具体限制。
图1A是根据本公开实施例示出的一种通信系统的架构示意图。
图1B是根据本公开实施例示出的一种测量过程的示意图。
图1C是根据本公开实施例示出的一种预测过程的示意图。
图2A是根据本公开实施例示出的一种通信方法的交互示意图。
图2B是根据本公开实施例示出的一种模型训练的示意图。
图2C是根据本公开实施例示出的一种预测过程的示意图。
图2D是根据本公开实施例示出的一种预测过程的示意图。
图3A是根据本公开实施例示出的一种通信方法的流程示意图。
图3B是根据本公开实施例示出的一种通信方法的流程示意图。
图3C是根据本公开实施例示出的一种通信方法的流程示意图。
图3D是根据本公开实施例示出的一种通信方法的流程示意图。
图3E是根据本公开实施例示出的一种通信方法的流程示意图。
图4是根据本公开实施例示出的一种通信方法的流程示意图。
图5是根据本公开实施例示出的一种通信方法的交互示意图。
图6A是本公开实施例提出的一种终端设备的结构示意图。
图6B是本公开实施例提出的一种网络设备的结构示意图。
图7A是本公开实施例提出的通信设备的结构示意图。
图7B是本公开实施例提出的芯片的结构示意图。
具体实施方式
本公开实施例提出了一种通信方法、设备和存储介质。
第一方面，本公开实施例提出了一种通信方法，所述方法包括：
终端设备根据第一信息进行预测，得到所述终端设备与网络设备之间的路径损耗值。
在上述实施例中，终端设备不需要对下行路径损耗参考信号进行测量，根据第一信息预测得到终端设备与网络设备之间的路径损耗值，从而降低了终端设备的功耗，节省电量。
结合第一方面的一些实施例，在一些实施例中，所述第一信息至少包括以下参数：
第一发射信息，所述第一发射信息为所述网络设备在第一时间段内发送的路径损耗参考信号PL RS的功率值或者信号强度值，所述第一时间段为当前时刻之前的时间段；
第一接收信息，所述第一接收信息为所述终端设备在所述第一时间段内测量的所述PL RS的功率值或者信号强度值；
第一波束索引，所述第一波束索引为所述PL RS对应的波束索引值；
所述终端设备当前时刻所处的第一位置。
在上述实施例中，终端设备可以根据第一发射信息、第一接收信息、第一波束索引、第一位置中的至少一项预测得到终端设备与网络设备之间的路径损耗值，提高了路径损耗值的获取效率。
结合第一方面的一些实施例，在一些实施例中，所述终端设备根据第一信息进行预测，得到所述终端设备与网络设备之间的路径损耗值包括：
将所述第一信息输入第一模型，得到所述第一模型输出的所述路径损耗值，其中，所述第一模型为人工智能AI/机器学习ML模型。
在上述实施例中，可以通过AI/ML模型预测得到终端设备与网络设备之间的路径损耗值，使得路径损耗值的获取方式更加简便。
结合第一方面的一些实施例，在一些实施例中，所述第一模型是通过第一样本信息训练得到的，所述第一样本信息至少包括以下参数：
第二发射信息、第二接收信息、第二波束索引、所述终端设备的第二位置，其中，所述第二发射信息为所述网络设备发送的PL RS的功率值或者信号强度值、所述第二接收信息为所述终端设备测量的所述PL RS的功率值或者信号强度值，所述第二波束索引为所述PL RS对应的波束索引值。
在上述实施例中，可以通过第一样本信息训练得到第一模型。
结合第一方面的一些实施例，在一些实施例中，所述第一样本信息为所述第一信息时间段之前的信息。
在上述实施例中，可以根据在第一信息之前获取的第一样本信息训练得到第一模型。
结合第一方面的一些实施例，在一些实施例中，所述方法还包括：
接收所述网络设备发送的第二信息，所述第二信息用于指示所述第一发射信息。
在上述实施例中，网络设备可以向终端设备发送指示第一发射信息的第二信息。
结合第一方面的一些实施例，在一些实施例中，根据所述路径损耗值确定上行发射功率。
在上述实施例中，终端设备可以根据路径损耗值确定上行发射功率，使得上行发射功率的确定效率更高。
第二方面，本公开实施例提出了一种通信方法，所述方法包括：
网络设备向终端设备发送第二信息，所述第二信息用于指示第一发射信息，所述第一发射信息为所述网络设备发送的路径损耗参考信号PL RS的功率值或者信号强度值，所述第一发射信息用于所述终端设备预测所述终端设备与所述网络设备之间的路径损耗值。
结合第二方面的一些实施例，在一些实施例中，所述路径损耗值用于所述终端设备确定上行发射功率。
第三方面，本公开实施例提出了一种终端设备，该终端设备可以包括收发模块、处理模块中的至少一 者；其中，该终端设备可以用于执行第一方面的可选实现方式。
第四方面，本公开实施例提出了一种网络设备，该网络设备可以包括收发模块、处理模块中的至少一者；其中，该网络设备可以用于执行第二方面的可选实现方式。
第五方面，本公开实施例提出了一种终端设备，该终端设备可以包括：一个或多个处理器；其中，该终端设备可以用于执行第一方面的可选实现方式。
第六方面，本公开实施例提出了一种网络设备，该网络设备可以包括：一个或多个处理器；其中，该网络设备可以用于执行第二方面的可选实现方式。
第七方面，本公开实施例提出了一种通信系统，该通信系统可以包括：终端设备和网络设备；其中，该终端设备被配置为执行如第一方面的可选实现方式所描述的方法，该网络设备被配置为执行如第二方面的可选实现方式所描述的方法。
第八方面，本公开实施例提出了一种存储介质，该存储介质存储有指令，当该指令在通信设备上运行时，使得该通信设备执行如第一方面或第二方面的可选实现方式所描述的方法。
第九方面，本公开实施例提出了一种程序产品，该程序产品被通信设备执行时，使得该通信设备执行如第一方面或第二方面的可选实现方式所描述的方法。
第十方面，本公开实施例提出了计算机程序，当其在计算机上运行时，使得计算机执行如第一方面或第二方面的可选实现方式所描述的方法。
第十一方面，本公开实施例提供了一种芯片或芯片系统。该芯片或芯片系统包括处理电路，被配置为执行如第一方面或第二方面的可选实现方式所描述的方法。
可以理解地，上述终端设备、网络设备、通信设备、通信系统、存储介质、程序产品、计算机程序、芯片或芯片系统均可以用于执行本公开实施例所提出的方法。因此，其所能达到的有益效果可以参考对应方法中的有益效果，此处不再赘述。
本公开实施例提出了一种通信方法、设备和存储介质。在一些实施例中，信息传输方法与信息处理方法、通信方法等术语可以相互替换；信息传输装置与信息处理装置、通信装置、通信设备等术语可以相互替换；信息处理系统、通信系统等术语可以相互替换。
本公开实施例并非穷举，仅为部分实施例的示意，不作为对本公开保护范围的具体限制。在不矛盾的情况下，某一实施例中的每个步骤均可以作为独立实施例来实施，且各步骤之间可以任意组合，例如，在某一实施例中去除部分步骤后的方案也可以作为独立实施例来实施，且在某一实施例中各步骤的顺序可以任意交换，另外，某一实施例中的可选实现方式可以任意组合；此外，各实施例之间可以任意组合，例如，不同实施例的部分或全部步骤可以任意组合，某一实施例可以与其他实施例的可选实现方式任意组合。
在各本公开实施例中，如果没有特殊说明以及逻辑冲突，各实施例之间的术语和/或描述具有一致性，且可以互相引用，不同实施例中的技术特征根据其内在的逻辑关系可以组合形成新的实施例。
本公开实施例中所使用的术语只是为了描述特定实施例的目的，而并非作为对本公开的限制。
在本公开实施例中，除非另有说明，以单数形式表示的元素，如“一个”、“一种”、“该”、“上述”、“所述”、“前述”、“这一”等，可以表示“一个且只有一个”，也可以表示“一个或多个”、“至少一个”等。例如，在翻译中使用如英语中的“a”、“an”、“the”等冠词(article)的情况下，冠词之后的名词可以理解为单数表达形式，也可以理解为复数表达形式。
在一些实施例中，“多个”可以指两个或两个以上。
在一些实施例中，“至少一者(至少一项、至少一个)(at least one of)”、“一个或多个(一项或多项)(one or more)”、“多个(a plurality of)”、“多个(multiple)等术语可以相互替换。
在一些实施例中，“A、B中的至少一者”、“A和/或B”、“在一情况下A，在另一情况下B”、“响应于一情况A，响应于另一情况B”等记载方式，根据情况可以包括以下技术方案：在一些实施例中A(与B无关地执行A)；在一些实施例中B(与A无关地执行B)；在一些实施例中从A和B中选择执行(A和B被选择性执行)；在一些实施例中A和B(A和B都被执行)。当有A、B、C等更多分支时也类似上述。
在一些实施例中，“A或B”等记载方式，根据情况可以包括以下技术方案：在一些实施例中A(与B无关地执行A)；在一些实施例中B(与A无关地执行B)；在一些实施例中从A和B中选择执行(A和B被选择性执行)。当有A、B、C等更多分支时也类似上述。
本公开实施例中的“第一”、“第二”等前缀词，仅仅为了区分不同的描述对象，不对描述对象的位置、顺序、优先级、数量或内容等构成限制，对描述对象的陈述参见权利要求或实施例中上下文的描述，不应因为使用前缀词而构成多余的限制。例如，描述对象为“字段”，则“第一字段”和“第二字段”中“字段”之前的序数词并不限制“字段”之间的位置或顺序，“第一”和“第二”并不限制其修饰的“字段”是否在同一个消息中，也不限制“第一字段”和“第二字段”的先后顺序。再如，描述对象为“等级”，则“第一等级”和“第二等级”中“等级”之前的序数词并不限制“等级”之间的优先级。再如，描述对 象的数量并不受序数词的限制，可以是一个或者多个，以“第一装置”为例，其中“装置”的数量可以是一个或者多个。此外，不同前缀词修饰的对象可以相同或不同，例如，描述对象为“装置”，则“第一装置”和“第二装置”可以是相同的装置或者不同的装置，其类型可以相同或不同；再如，描述对象为“信息”，则“第一信息”和“第二信息”可以是相同的信息或者不同的信息，其内容可以相同或不同。
在一些实施例中，“包括A”、“包含A”、“用于指示A”、“携带A”，可以解释为直接携带A，也可以解释为间接指示A。
在一些实施例中，“响应于……”、“响应于确定……”、“在……的情况下”、“在……时”、“当……时”、“若……”、“如果……”等术语可以相互替换。
在一些实施例中，“大于”、“大于或等于”、“不小于”、“多于”、“多于或等于”、“不少于”、“高于”、“高于或等于”、“不低于”、“以上”等术语可以相互替换，“小于”、“小于或等于”、“不大于”、“少于”、“少于或等于”、“不多于”、“低于”、“低于或等于”、“不高于”、“以下”等术语可以相互替换。
在一些实施例中，装置等可以解释为实体的、也可以解释为虚拟的，其名称不限定于实施例中所记载的名称。“装置”、“设备(equipment)”、“设备(device)”、“电路”、“网元”、“节点”、“功能”、“单元”、“部件(section)”、“系统”、“网络”、“芯片”、“芯片系统”、“实体”、“主体”等术语可以相互替换。
在一些实施例中，“网络”可以解释为网络中包含的装置(例如，接入网设备、核心网设备等)。
在一些实施例中，“接入网设备(Access Network Device，AN Device)”也、“无线接入网设备(Radio Access Network Device，RAN Device)”、“基站(Base Station，BS)”、“无线基站(Radio Base Station)”、“固定台(Fixed Station)”、“节点(Node)”、“接入点(Access Point)”、“发送点(Transmission Point，TP)”、“接收点(Reception Point，RP)”、“发送和/或接收点(Transmission/Reception Point，TRP)”、“面板(Panel)”、“天线面板(Antenna Panel)”、“天线阵列(Antenna Array)”、“小区(Cell)”、“宏小区(Macro Cell)”、“小型小区(Small Cell)”、“毫微微小区(Femto Cell)”、“微微小区(Pico Cell)”、“扇区(Sector)”、“小区组(Cell Group)”、“服务小区”、“载波(Carrier)”、“分量载波(Component Carrier)”、“带宽部分(Bandwidth Part，BWP)”等术语可以相互替换。
在一些实施例中，“终端(Terminal)”、“终端设备(Terminal Device)”、“用户设备(User Equipment，UE)”、“用户终端(User Terminal)”、“移动台(Mobile Station，MS)”、“移动终端(Mobile Terminal，MT)”、订户站(Subscriber Station)、移动单元(Mobile Unit)、订户单元(Subscriber Unit)、无线单元(Wireless Unit)、远程单元(Remote Unit)、移动设备(Mobile Device)、无线设备(Wireless Device)、无线通信设备(Wireless Communication Device)、远程设备(Remote Device)、移动订户站(Mobile Subscriber Station)、接入终端(Access Terminal)、移动终端(Mobile Terminal)、无线终端(Wireless Terminal)、远程终端(Remote Terminal)、手持设备(Handset)、用户代理(User Agent)、移动客户端(Mobile Client)、客户端(Client)等术语可以相互替换。
在一些实施例中，接入网设备、核心网设备、或网络设备可以被替换为终端。例如，针对将接入网设备、核心网设备、或网络设备以及终端间的通信置换为多个终端间的通信(例如，设备对设备(device-to-device，D2D)、车联网(vehicle-to-everything，V2X)等)的结构，也可以应用本公开的各实施例。在该情况下，也可以设为终端具有接入网设备所具有的全部或部分功能的结构。此外，“上行”、“下行”等术语也可以被替换为与终端间通信对应的术语(例如，“侧行(side)”)。例如，上行信道、下行信道等可以被替换为侧行信道或直连信道，上行链路、下行链路等可以被替换为侧行链路或直连链路。
在一些实施例中，终端可以被替换为接入网设备、核心网设备、或网络设备。在该情况下，也可以设为接入网设备、核心网设备、或网络设备具有终端所具有的全部或部分功能的结构。
在一些实施例中，获取数据、信息等可以遵照所在地国家的法律法规。
在一些实施例中，可以在得到用户同意后获取数据、信息等。
此外，本公开实施例的表格中的每一元素、每一行、或每一列均可以作为独立实施例来实施，任意元素、任意行、任意列的组合也可以作为独立实施例来实施。
图1A是根据本公开实施例示出的一种通信系统的架构示意图。如图1A所示，该通信系统100可以包括终端设备(Terminal Device)101、网络设备102。
在一些实施例中，终端设备101可以包括手机(mobile phone)、可穿戴设备、物联网设备、具备通信功能的汽车、智能汽车、平板电脑(Pad)、带无线收发功能的电脑、虚拟现实(Virtual Reality，VR)终端设备、增强现实(Augmented Reality，AR)终端设备、工业控制(Industrial Control)中的无线终端设备、无人驾驶(Self-Driving)中的无线终端设备、远程手术(Remote Medical Surgery)中的无线终端设备、智能电网(Smart Grid)中的无线终端设备、运输安全(Transportation Safety)中的无线终端设备、智慧城市(Smart City)中的无线终端设备、智慧家庭(Smart Home)中的无线终端设备中的至少一者，但不限于此。
在一些实施例中，网络设备102可以包括接入网设备、核心网设备中的至少一者。
在一些实施例中，接入网设备可以是将终端设备接入到无线网络的节点或设备，接入网设备可以包括5G通信系统中的演进节点B(evolved NodeB，eNB)、下一代演进节点B(next generation eNB，ng-eNB)、下一代节点B(next generation NodeB，gNB)、节点B(node B，NB)、家庭节点B(home node B，HNB)、家庭演进节点B(home evolved nodeB，HeNB)、无线回传设备、无线网络控制器(Radio Network Controller，RNC)、基站控制器(Base Station Controller，BSC)、基站收发台(Base Transceiver Station，BTS)、基带单元(Base Band Unit，BBU)、移动交换中心、6G通信系统中的基站、开放型基站(Open RAN)、云基站(Cloud RAN)、其他通信系统中的基站、Wi-Fi系统中的接入节点中的至少一者，但不限于此。
在一些实施例中，本公开的技术方案可适用于Open RAN架构，此时，本公开实施例所涉及的接入网设备间或者接入网设备内的接口可变为Open RAN的内部接口，这些内部接口之间的流程和信息交互可以通过软件或者程序实现。
在一些实施例中，接入网设备可以由集中单元(Central Unit，CU)与分布式单元(Distributed Unit，DU)组成的，其中，CU也可以称为控制单元(Control Unit)，采用CU-DU的结构可以将接入网设备的协议层拆分开，部分协议层的功能放在CU集中控制，剩下部分或全部协议层的功能分布在DU中，由CU集中控制DU，但不限于此。
在一些实施例中，核心网设备可以是一个设备，也可以是多个设备或设备群。核心网可以包括演进分组核心(Evolved Packet Core，EPC)、5G核心网络(5G Core Network，5GCN)、下一代核心(Next Generation Core，NGC)中的至少一者。
可以理解的是，本公开实施例描述的通信系统是为了更加清楚的说明本公开实施例的技术方案，并不构成对于本公开实施例提出的技术方案的限定，本领域普通技术人员可知，随着系统架构的演变和新业务场景的出现，本公开实施例提出的技术方案对于类似的技术问题同样适用。
下述本公开实施例可以应用于图1A所示的通信系统100、或部分主体，但不限于此。图1A所示的各主体是示例，通信系统可以包括图1A中的全部或部分主体，也可以包括图1A以外的其他主体，各主体数量和形态为任意，各主体可以是实体的也可以是虚拟的，各主体之间的连接关系是示例，各主体之间可以不连接也可以连接，其连接可以是任意方式，可以是直接连接也可以是间接连接，可以是有线连接也可以是无线连接。
本公开各实施例可以应用于长期演进(Long Term Evolution，LTE)、LTE-Advanced(LTE-A)、LTE-Beyond(LTE-B)、SUPER 3G、IMT-Advanced、第四代移动通信系统(4th generation mobile communication system，4G)、)、第五代移动通信系统(5th generation mobile communication system，5G)、5G新空口(new radio，NR)、未来无线接入(Future Radio Access，FRA)、新无线接入技术(New-Radio Access Technology，RAT)、新无线(New Radio，NR)、新无线接入(New Radio Access，NX)、未来一代无线接入(Future generation radio access，FX)、Global System for Mobile communications(GSM(注册商标))、CDMA2000、超移动宽带(Ultra Mobile Broadband，UMB)、IEEE 802.11(Wi-Fi(注册商标))、IEEE 802.16(WiMAX(注册商标))、IEEE 802.20、超宽带(Ultra-WideBand，UWB)、蓝牙(Bluetooth(注册商标))、陆上公用移动通信网(Public Land Mobile Network，PLMN)网络、设备到设备(Device-to-Device，D2D)系统、机器到机器(Machine to Machine，M2M)系统、物联网(Internet of Things，IoT)系统、车联网(Vehicle-to-Everything，V2X)、利用其他通信方法的系统、基于它们而扩展的下一代系统等。此外，也可以将多个系统组合(例如，LTE或者LTE-A与5G的组合等)应用。
在本公开的一些实施例中，5GNR系统引入了基于人工智能(Artificial Itelligence，AI)/机器学习(Machine Learning，ML)模型预测来简化某些场景的过程及提升性能，其中一个典型场景为上行功率控制过程，例如在传统的开环功率控制过程中，UE根据以下公式确定上行发送功率：
PPRACH,b,f,c(i)＝min{PCMAX,f,c(i),PPRACH,target,f,c+PLb,f,c}[dBm]   (1)
其中，PPRACH,b,f,c(i)为UE的发送功率，b表示ULBWP，f为载波频率(carrier frequency)，c为服务小区(serving cell)；PCMAX,f,c(i)为配置UE最大发送功率，协议值定义在38.101-1中；PPRACH,target,f,c为目标PRACH在网络侧的接收功率；PLb,f,c为UE基于DLRS测量获得的路径损耗值(pathloss)。
路径损耗(pathloss)是基于UE测量下行参考信号(SSB或CSI-RS)的信号强度评估出的PL值。图1B是根据本公开实施例示出的一种测量过程的示意图。如图1B所示，UE需要频繁测量下行PLRS，功耗较大，并且如果信道变化较快的情况下，根据下行的测量并不能准确的反应当前的PL值。
在一些实施例中，为了减少下行PLRS测量并省电，可以基于AL/ML模型的训练和预测，输出预测 的PL值。图1C是根据本公开实施例示出的一种预测过程的示意图。如图1C所示，UE可以通过AI预测PL值，再根据预测的PL值，确定上行发送功率。
图2A是根据本公开实施例示出的一种通信方法的交互示意图。该方法可以由上述通信系统执行。如图2A所示，该方法可以包括：
步骤S2101、网络设备向终端设备发送第二信息。
在一些实施例中，终端设备可以接收第二信息。例如，终端设备可以接收网络设备发送的第二信息。再例如，终端设备也可以接收其他实体发送的第二信息。
在一些实施例中，该第二信息可以用于指示第一发射信息。
在一些实施例中，该第一发射信息可以是网络设备发送的路径损耗参考信号(PathlossReference Signal，PL RS)的功率值或者信号强度值。
在一些实施例中，“发射”也可以称为“发送”。
在一些实施例中，PL RS可以是下行参考信号，例如同步信号块(Synchronization Signal Block，SSB)和/或信道状态信息参考信号(Channel State Information Reference Signal，CSI-RS)，本公开实施例对此不作限定。
例如，该第一发射信息可以是SSB的功率值或者信号强度值，再例如，该第一发射信息可以是CSI-RS的功率值或者信号强度值。
在一些实施例中，该第一发射信息可以是一个PL RS的功率值或者信号强度值，也可以包括多个PL RS的功率值或者信号强度值。
在一些实施例中，若该第一发射信息包括多个PL RS的功率值或者信号强度值，则网络设备可以按照协议约定在不同时刻发送PL RS的功率值或者信号强度值。
在一些实施例中，网络设备向终端设备发送PL RS时，可以同时向终端设备发送该第二信息。
在一些实施例中，网络设备也可以在向终端设备发送该PL RS之前或之后，向终端设备发送指示该PLRS的功率值或者信号强度值的第二信息，本公开实施例对此不作限定。
在一些实施例中，该第一发射信息可以用于终端设备预测终端设备与网络设备之间的路径损耗值。
在一些实施例中，该第一发射信息的名称不做限定，例如可以是“第一发射功率”、“第一信号强度”等。
步骤S2102、终端设备将第一信息输入第一模型，得到第一模型输出的路径损耗值。
在一些实施例中，该第一信息至少可以包括以下参数：
第一发射信息，该第一发射信息为网络设备在第一时间段内发送的PL RS的功率值或者信号强度值，该第一时间段为当前时刻之前的时间段；
第一接收信息，该第一接收信息为终端设备在该第一时间段内测量的该PL RS的功率值或者信号强度值；
第一波束索引，该第一波束索引为该PL RS对应的波束索引值；
终端设备当前时刻所处的第一位置。
在一些实施例中，该第一发射信息可以是终端设备在该第一时间段内接收到的一个PL RS的功率值或者信号强度值。例如，该PL RS可以是终端设备在该第一时间段内接收到的任一PL RS，再例如，该PL RS可以是终端设备在该第一时间段内接收到的最后一个PL RS，即终端设备在当前时刻之前最后一次接收到的PL RS。
在一些实施例中，该第一发射信息可以是终端设备在该第一时间段内接收到的多个PL RS的功率值或者信号强度值。例如，该第一发射信息可以是网络设备发送的该多个PL RS的平均功率值或者平均信号强度值，又例如，该第一发射信息可以是网络设备发送的该多个PL RS中的最大功率值或者最大信号强度值，再例如，该第一发射信息可以是网络设备发送的该多个PL RS中的最小功率值或者最小最大信号强度值。
在一些实施例中，终端设备可以存储该第一时间段内接收到的每个第一发射信息。
在一些实施例中，终端设备可以接收网络设备发送的PL RS。
在一些实施例中，终端设备可以对接收到的PL RS进行测量，得到该PL RS的功率值或者信号强度值。
在一些实施例中，该第一接收信息可以是终端设备在该第一时间段内测量的一个PL RS的功率值或者信号强度值。例如，该PL RS可以是终端设备在该第一时间段内接收到的任一PL RS，再例如，该PL RS可以是终端设备在该第一时间段内接收到的最后一个PL RS，即终端设备在当前时刻之前最后一次接收到的PL RS。
在一些实施例中，该第一接收信息可以是终端设备在该第一时间段内测量的多个PL RS的功率值或者信号强度值。例如，该第一接收信息可以是终端设备测量的该多个PL RS的平均功率值或者平均信号强度值，又例如，该第一接收信息可以是终端设备测量的该多个PL RS中的最大功率值或者最大信号强度值， 再例如，该第一接收信息可以是终端设备测量的该多个PL RS中的最小功率值或者最小最大信号强度值。
在一些实施例中，该第一发射信息、该第一接收信息可以对应相同的PL RS。例如，该第一发射信息是网络设备第一时刻发送的PL RS的功率值或者信号强度值，该第一接收信息是终端设备测量的网络设备第一时刻发送的PL RS的功率值或者信号强度值。
需要说明的是，该第一发射信息、该第一接收信息也可以对应不同的PL RS，本公开实施例对此不作限定。
在一些实施例中，该第一波束索引可以是网络设备用于发送PL RS的波束的索引值。例如，该第一发射信息是网络设备第一时刻发送的PL RS的功率值或者信号强度值，该第一接收信息是终端设备测量的网络设备第一时刻发送的PL RS的功率值或者信号强度值，该第一波束索引为网络设备在第一时刻发送PL RS时使用的波束的索引值。
在一些实施例中，该第一位置可以是终端设备测量PL RS的功率值或者信号强度值的位置。
在一些实施例中，该第一模型可以是AI/ML模型。
在一些实施例中，该第一模型可以用于预测终端设备与网络设备之间的路径损耗值。
在一些实施例中，该第一模型是通过第一样本信息训练得到的，该第一样本信息至少可以包括以下参数：
第二发射信息、第二接收信息、第二波束索引、终端设备的第二位置，该第二发射信息为网络设备发送的PL RS的功率值或者信号强度值、该第二接收信息为终端设备测量的该PL RS的功率值或者信号强度值，该第二波束索引为该PL RS对应的波束索引值。
在一些实施例中，该第一样本信息的获取方式可以参照上述第一信息的获取方式，此处不再赘述。
在一些实施例中，该第一样本信息对应的PL RS可以是历史时间段获取的任意PL RS，本公开实施例对此不作限定。
在一些实施例中，在获取该第一样本信息后，可以根据该第一样本信息进行模型训练，得到该第一模型。
在一些实施例中，可以通过多个第一样本信息进行模型训练，得到该第一模型。
在一些实施例中，多个第一样本信息可以是终端设备在不同位置和/或不同时刻获取的信息。
在一些实施例中，该第一样本信息可以是该第一信息时间段之前的信息。
例如，若该第一信息为当前时刻获取的信息，则该第一样本信息可以是该当前时刻之前获取的信息。
图2B是根据本公开实施例示出的一种模型训练的示意图。如图2B所示，将第二发射信息、第二接收信息、第二波束索引、终端设备的第二位置输入AI/ML模型，可以输出预测的路径损耗值。
在一些实施例中，该第一模型的训练过程可以参照现有技术的描述，此处不再赘述。
在一些实施例中，终端设备可以将第一发射信息、第一接收信息、第一波束索引、第一位置输入该第一模型，得到该第一模型输出的终端设备与网络设备之间的路径损耗值。
在一些实施例中，可以通过第一样本信息中的任意一个或多个信息训练得到该第一模型。
在一些实施例中，通过不同信息训练得到的第一模型可以预测不同场景的路径损耗值。例如，通过第二发射信息、第二接收信息以及第二波束索引训练得到的第一模型，可以用于预测未来时间段的路径损耗值；再例如，通过第二发射信息、第二波束索引以及第二位置训练得到的第一模型，可以用于预测指定位置的路径损耗值。
需要说明的是，通过该第一模型预测路径损耗值时，输入该第一模型的参数与训练该第一模型的参数相同。例如，若该第一模型是通过第二发射信息、第二接收信息以及第二波束索引训练得到的，则通过该第一模型预测路径损耗值时输入的信息可以包括第一发射信息、第一接收信息以及第一波束索引。
在一些实施例中，该第一模型可以用于预测一个时间段的路径损耗值。
在一些实施例中，该第一模型可以通过第二发射信息、第二接收信息、第二波束索引训练得到，该第二发射信息为网络设备发送的PL RS的功率值或者信号强度值、该第二接收信息为终端设备测量的该PL RS的功率值或者信号强度值，该第二波束索引为该PL RS对应的波束索引值。
在一些实施例中，在预测一个时间段的路径损耗值时，输入该第一模型的第一信息至少可以包括以下参数：
该第一发射信息、该第一接收信息、该第一波束索引。
在一些实施例中，第一终端可以将该第一发射信息、该第一接收信息以及该第一波束索引输入该第一模型，得到该第一模型输出的第二时间段的路径损耗值，该第二时间段为该第一时间段之后的时间段。
例如，第一时间段为(1,…,i-1)，该第二时间段为(i,…,i+j)。其中，i可以是当前时刻，即该第一时间段包括当前时刻之前的时间段，该第二时间段可以包括当前时刻及该当前时刻之后的时间段。
图2C是根据本公开实施例示出的一种预测过程的示意图。如图2C所示，该第一模型的输入为第一时 间段的第一发射信息、第一时间段的第一接收信息以及第一时间段的第一波束索引，该第一模型的输出为第二时间段的路径损耗值。
在一些实施例中，该第一模型可以用于预测一个位置的路径损耗值。
在一些实施例中，该第一模型可以通过第二发射信息、第二波束索引、终端设备的第二位置训练得到，该第二发射信息为网络设备发送的PL RS的功率值或者信号强度值，该第二波束索引为该PL RS对应的波束索引值。
在一些实施例中，在预测一个位置的路径损耗值时，输入该第一模型的第一信息至少可以包括以下参数：
该第一发射信息、该第一波束索引、该第一位置。
在一些实施例中，第一终端可以将该第一发射信息、该第一波束索引以及该第一位置输入该第一模型，得到该第一模型输出的该第一位置的路径损耗值。
在一些实施例中，“第一位置的路径损耗值”可以理解为“第二时间段内终端设备在第一位置的路径损耗值”。例如，可以预测i时刻终端设备在第一位置的路径损耗值。
图2D是根据本公开实施例示出的一种预测过程的示意图。如图2D所示，该第一模型的输入为i时刻的第一发射信息、第一波束索引以及i时刻的第一位置，该第一模型的输出为i时刻的第一位置的路径损耗值。
步骤S2103、终端设备根据路径损耗值确定上行发射功率。
需要说明的是，终端设备可以根据现有协议定义的方式确定上行发射功率，此处不再赘述。
采用上述方法，终端设备不需要对下行路径损耗参考信号进行测量，根据第一信息预测得到终端设备与网络设备之间的路径损耗值，以确定上行发射功率，从而降低了终端设备的功耗，节省电量。
本公开实施例所涉及的方法可以包括上述步骤S2101～步骤S2103中的至少一者。例如，步骤S2101可以作为独立实施例来实施，步骤S2102可以作为独立实施例来实施，步骤S2103可以作为独立实施例来实施，步骤S2101+步骤S2102可以作为独立实施例来实施。
在一些实施例中，步骤S2101～步骤S2103中的任意两个步骤之间可以交换顺序或同时执行。
在一些实施例中，步骤S2101～步骤S2103是可选的，在不同实施例中可以对这些步骤中的一个或多个步骤进行省略或替代。例如，步骤S2101可以省略。
在一些实施例中，可参见图2A所对应的说明书之前或之后记载的其他可选实现方式。
在一些实施例中，信息等的名称不限定于实施例中所记载的名称，“信息(information)”、“消息(message)”、“信号(signal)”、“信令(signaling)”、“报告(report)”、“配置(configuration)”、“指示(indication)”、“指令(instruction)”、“命令(command)”、“信道”、“参数(parameter)”、“域”、“字段”、“符号(symbol)”、“码元(symbol)”、“码本(codebook)”、“码字(codeword)”、“码点(codepoint)”、“比特(bit)”、“数据(data)”、“程序(program)”、“码片(chip)”等术语可以相互替换。
在一些实施例中，“获取”、“获得”、“得到”、“接收”、“传输”、“双向传输”、“发送和/或接收”可以相互替换，其可以解释为从其他主体接收，从协议中获取，从高层获取，自身处理得到、自主实现等多种含义。
在一些实施例中，“发送”、“发射”、“上报”、“下发”、“传输”、“双向传输”、“发送和/或接收”等术语可以相互替换。
在一些实施例中，“特定(certain)”、“预定(preseted)”、“预设”、“设定”、“指示(indicated)”、“某一”、“任意”、“第一”等术语可以相互替换，“特定A”、“预定A”、“预设A”、“设定A”、“指示A”、“某一A”、“任意A”、“第一A”可以解释为在协议等中预先规定的A，也可以解释为通过设定、配置、或指示等得到的A，也可以解释为特定A、某一A、任意A、或第一A等，但不限于此。
图3A是根据本公开实施例示出的一种通信方法的流程示意图。如图3A所示，本公开实施例涉及通信方法，该方法可以由终端设备执行。该方法可以包括：
步骤S3101、接收第二信息。
该步骤S3101的可选实现方式可以参见图2A的步骤S2101的可选实现方式、及图2A所涉及的实施例中其他关联部分，此处不再赘述。
步骤S3102、将第一信息输入第一模型，得到第一模型输出的路径损耗值。
该步骤S3102的可选实现方式可以参见图2A的步骤S2102的可选实现方式、及图2A所涉及的实施例中其他关联部分，此处不再赘述。
步骤S3103、根据路径损耗值确定上行发射功率。
该步骤S3103的可选实现方式可以参见图2A的步骤S2103的可选实现方式、及图2A所涉及的实施例中其他关联部分，此处不再赘述。
本公开实施例所涉及的方法可以包括上述步骤S3101～步骤S3103中的至少一者。例如，步骤S3101可以作为独立实施例来实施，步骤S3102可以作为独立实施例来实施，步骤S3103可以作为独立实施例来实施，步骤S3101+步骤S3102可以作为独立实施例来实施。
在一些实施例中，步骤S3101～步骤S3103中的任意两个步骤之间可以交换顺序或同时执行。
在一些实施例中，步骤S3101～步骤S3103是可选的，在不同实施例中可以对这些步骤中的一个或多个步骤进行省略或替代。例如，步骤S3101可以省略。
图3B是根据本公开实施例示出的一种通信方法的流程示意图。如图3B所示，本公开实施例涉及通信方法，该方法可以由终端设备执行。该方法可以包括：
步骤S3201、接收第二信息。
该步骤S3201的可选实现方式可以参见图2A的步骤S2101的可选实现方式、及图2A所涉及的实施例中其他关联部分，此处不再赘述。
步骤S3202、将第一发射信息、第一接收信息以及第一波束索引输入第一模型，得到第一模型输出的第二时间段的路径损耗值。
该步骤S3202的可选实现方式可以参见图2A的步骤S2102的可选实现方式、以及图2A所涉及的实施例中其他关联部分，此处不再赘述。
步骤S3203、根据路径损耗值确定上行发射功率。
该步骤S3203的可选实现方式可以参见图2A的步骤S2103的可选实现方式、以及图2A所涉及的实施例中其他关联部分，此处不再赘述。
在一些实施例中，上述步骤均为可选步骤。
本公开实施例所涉及的方法可以包括上述步骤S3201～步骤S3203中的至少一者。例如，步骤S3201可以作为独立实施例来实施，步骤S3202可以作为独立实施例来实施，步骤S3203可以作为独立实施例来实施，步骤S3201+步骤S3202可以作为独立实施例来实施。
在一些实施例中，步骤S3201～步骤S3203中的任意两个步骤之间可以交换顺序或同时执行。
在一些实施例中，步骤S3201～步骤S3203是可选的，在不同实施例中可以对这些步骤中的一个或多个步骤进行省略或替代。例如，步骤S3201可以省略。
图3C是根据本公开实施例示出的一种通信方法的流程示意图。如图3C所示，本公开实施例涉及通信方法，该方法可以由终端设备执行。该方法可以包括：
步骤S3301、接收第二信息。
该步骤S3301的可选实现方式可以参见图2A的步骤S2101的可选实现方式、及图2A所涉及的实施例中其他关联部分，此处不再赘述。
步骤S3302、将第一发射信息、第一波束索引以及第一位置输入第一模型，得到第一模型输出的第一位置的路径损耗值。
该步骤S3302的可选实现方式可以参见图2A的步骤S2102的可选实现方式、以及图2A所涉及的实施例中其他关联部分，此处不再赘述。
步骤S3303、根据路径损耗值确定上行发射功率。
该步骤S3303的可选实现方式可以参见图2A的步骤S2103的可选实现方式、以及图2A所涉及的实施例中其他关联部分，此处不再赘述。
本公开实施例所涉及的方法可以包括上述步骤S3301～步骤S3303中的至少一者。例如，步骤S3301可以作为独立实施例来实施，步骤S3302可以作为独立实施例来实施，步骤S3303可以作为独立实施例来实施，步骤S3301+步骤S3302可以作为独立实施例来实施。
在一些实施例中，步骤S3301～步骤S3303中的任意两个步骤之间可以交换顺序或同时执行。
在一些实施例中，步骤S3301～步骤S3303是可选的，在不同实施例中可以对这些步骤中的一个或多个步骤进行省略或替代。例如，步骤S3301可以省略。
图3D是根据本公开实施例示出的一种通信方法的流程示意图。如图3D所示，本公开实施例涉及通信方法，该方法可以由终端设备执行。该方法可以包括：
步骤S3401、通过第一样本信息训练得到第一模型。
在一些实施例中，该第一样本信息至少可以包括以下参数：第二发射信息、第二接收信息、第二波束索引、终端设备的第二位置。
需要说明的是，该步骤S3401中的第一样本信息可以参见图2A的步骤S2102中的解释说明，此处不再赘述。
例如，可以通过第二发射信息、第二接收信息、第二波束索引训练得到该第一模型；再例如，可以通过第二发射信息、第二波束索引、第二位置训练得到该第一模型；又例如，可以通过第二发射信息、第二 接收信息训练得到该第一模型。
需要说明的是，上述训练该第一模型的参数为举例说明，本公开实施例对此不作限定。
同样需要说明的是，用于训练该第一模型的参数越多，训练得到的该第一模型的准确率越高。
步骤S3402、将第一信息输入第一模型，得到第一模型输出的路径损耗值。
在一些实施例中，该第一信息至少可以包括以下参数：第一发射信息、第一接收信息、第一波束索引、第一位置。
需要说明的是，该步骤S3402中的第一信息可以参见图2A的步骤S2102中的解释说明，此处不再赘述。
在一些实施例中，输入该第一模型的第一信息可以包括第一发射信息、第一接收信息、第一波束索引中的至少一项。例如，该第一信息可以包括第一发射信息、第一接收信息、第一波束索引，再例如，该第一信息可以包括第一发射信息、第一接收信息，又例如，该第一信息可以包括第一发射信息、第一波束索引，又例如，该第一信息可以包括第一发射信息。
在一些实施例中，输入该第一模型的第一信息可以包括第一发射信息、第一波束索引、第一位置中的至少一项。例如，该第一信息可以包括第一发射信息、第一波束索引、第一位置，再例如，该第一信息可以包括第一发射信息、第一位置，又例如，该第一信息可以包括第一波束索引、第一位置，又例如，该第一信息可以包括第一位置。
需要说明的是，上述输入该第一模型的第一信息为举例说明，本公开实施例对此不作限定。
同样需要说明的是，输入第一模型的参数越多，该第一模型预测得到的路径损耗值越准确。
图3E是根据本公开实施例示出的一种通信方法的流程示意图。如图3E所示，本公开实施例涉及通信方法，该方法可以由终端设备执行。该方法可以包括：
步骤S3501、根据第一信息进行预测，得到终端设备与网络设备之间的路径损耗值。
该步骤S3501的可选实现方式可以参见图2A的步骤S2101、图3A的步骤S3101、图3B的步骤S3201、图3C的步骤S3301、图3D的步骤S3401的可选实现方式、及图2A、图3A、图3B、图3C、图3D所涉及的实施例中其他关联部分，此处不再赘述。
在一些实施例中，所述第一信息至少包括以下参数：
第一发射信息，所述第一发射信息为所述网络设备在第一时间段内发送的路径损耗参考信号PL RS的功率值或者信号强度值，所述第一时间段为当前时刻之前的时间段；
第一接收信息，所述第一接收信息为所述终端设备在所述第一时间段内测量的所述PL RS的功率值或者信号强度值；
第一波束索引，所述第一波束索引为所述PL RS对应的波束索引值；
所述终端设备当前时刻所处的第一位置。
在一些实施例中，所述终端设备根据第一信息进行预测，得到所述终端设备与网络设备之间的路径损耗值包括：
将所述第一信息输入第一模型，得到所述第一模型输出的所述路径损耗值，其中，所述第一模型为人工智能AI/机器学习ML模型。
在一些实施例中，所述第一模型是通过第一样本信息训练得到的，所述第一样本信息至少包括以下参数：
第二发射信息、第二接收信息、第二波束索引、所述终端设备的第二位置，其中，所述第二发射信息为所述网络设备发送的PL RS的功率值或者信号强度值、所述第二接收信息为所述终端设备测量的所述PL RS的功率值或者信号强度值，所述第二波束索引为所述PL RS对应的波束索引值。
在一些实施例中，所述第一样本信息为所述第一信息时间段之前的信息。
在一些实施例中，所述方法还包括：
接收所述网络设备发送的第二信息，所述第二信息用于指示所述第一发射信息。
在一些实施例中，所述方法还包括：
根据所述路径损耗值确定上行发射功率。
图4是根据本公开实施例示出的一种通信方法的流程示意图。如图4所示，本公开实施例涉及通信方法，该方法可以由网络设备执行。该方法可以包括：
步骤S4101、发送第二信息。
该步骤S4101的可选实现方式可以参见图2A的步骤S2101的可选实现方式、及图2A所涉及的实施例中其他关联部分，此处不再赘述。
在一些实施例中，所述第二信息用于指示第一发射信息，所述第一发射信息为所述网络设备发送的路径损耗参考信号PL RS的功率值或者信号强度值，所述第一发射信息用于所述终端设备预测所述终端设备 与所述网络设备之间的路径损耗值。
在一些实施例中，所述路径损耗值用于所述终端设备确定上行发射功率。
图5是根据本公开实施例示出的一种通信方法的交互示意图。如图5所示，本公开实施例涉及通信方法，该方法可以由通信系统执行。该方法可以包括：
步骤S5101、网络设备向终端设备发送第二信息。
该步骤S5101的可选实现方式可以参见图2A的步骤S2101、图3A的步骤S3101、图3B的步骤S3201、图3C的步骤S3301、图3D的步骤S3401、图4的步骤S4101的可选实现方式、及图2A、图3A、图3B、图3C、图3D、图4所涉及的实施例中其他关联部分，此处不再赘述。
步骤S5102、终端设备根据第一信息进行预测，得到终端设备与网络设备之间的路径损耗值。
该步骤S5102的可选实现方式可以参见图2A的步骤S2102、图3A的步骤S3102、图3B的步骤S3202、图3C的步骤S3302、图3D的步骤S3402的可选实现方式、及图2A、图3A、图3B、图3C、图3D所涉及的实施例中其他关联部分，此处不再赘述。
在一些实施例中，上述方法可以包括上述通信系统、终端设备、网络设备等的实施例所述的方法，此处不再赘述。
在一些实施例中，根据数据集A(SetA)，训练AI/ML模型并输出满足性能要求的路径损耗PL值，其中用于模型训练的数据集(SetA)的数据参数至少包括以下一项或多项参数信息：
PL RS的发射功率值(Pt)或者信号强度值(Tx_RSRP)；
PLRS测量样本的测量结果(接收功率值(Pr)或者接收信号强度值(Rx_RSRP))；
PLRS的波束索引(beamindex)；
UE位置信息；
在一些实施例中，基于AI/ML模型训练的输出为路径损耗PL值。
在一些实施例中，根据上述训练完的AI/ML模型，输入数据集B(Set B)，预测并输出路径损耗PL值，其中用于模型预测的数据集(SetB)的数据参数信息可以是以下方式：
输入数据参数方式1：
PL RS的发射功率值(Pt)或者信号强度值(Tx_RSRP)；
PLRS测量样本的测量结果(接收功率值(Pr)或者接收信号强度值(Rx_RSRP))；
PLRS的波束索引(beamindex)。
输入数据参数方式2：
PL RS的发射功率值(Pt)或者信号强度值(Tx_RSRP)；
PLRS的波束索引(beamindex)；
UE位置信息；
在一些实施例中，基于上述训练的AI/ML模型，在某一段时间内(时刻i,…,i+j)预测路径损耗PL值，输入数据为某一时间段内(时刻1,…,i-1)的发送和测量的PLRS的功率值/RSRP值和对应的PLRS的波束索引值。
在一些实施例中，基于上述训练的AI/ML模型，在某一段时间内(时刻i,…,i+j)预测当前UE位置的路径损耗PL值，输入的数据为当前UE位置信息、PLRS发射的信号和对应的PLRS的波束索引值。
在本公开的一些实施例中，提供一种通信系统，该通信系统可以包括终端设备和网络设备，其中，该终端设备可以执行本公开前述实施例中的由终端设备执行的通信方法；该网络设备可以执行本公开前述实施例中由网络设备执行的通信方法。
本公开实施例还提出用于实现以上任一方法的装置，例如，提出一装置，上述装置包括用以实现以上任一方法中终端所执行的各步骤的单元或模块。再如，还提出另一装置，包括用以实现以上任一方法中网络设备(例如接入网设备、核心网功能节点、核心网设备等)所执行的各步骤的单元或模块。
应理解以上装置中各单元或模块的划分仅是一种逻辑功能的划分，在实际实现时可以全部或部分集成到一个物理实体上，也可以物理上分开。此外，装置中的单元或模块可以以处理器调用软件的形式实现：例如装置包括处理器，处理器与存储器连接，存储器中存储有指令，处理器调用存储器中存储的指令，以实现以上任一方法或实现上述装置各单元或模块的功能，其中处理器例如为通用处理器，例如中央处理单元(Central Processing Unit，CPU)或微处理器，存储器为装置内的存储器或装置外的存储器。或者，装置中的单元或模块可以以硬件电路的形式实现，可以通过对硬件电路的设计实现部分或全部单元或模块的功能，上述硬件电路可以理解为一个或多个处理器；例如，在一种实现中，上述硬件电路为专用集成电路(Application-Specific Integrated Circuit，ASIC)，通过对电路内元件逻辑关系的设计，实现以上部分或全部单元或模块的功能；再如，在另一种实现中，上述硬件电路为可以通过可编程逻辑器件(Programmable Logic Device，PLD)实现，以现场可编程门阵列(Field Programmable Gate Array，FPGA)为例，其可以包 括大量逻辑门电路，通过配置文件来配置逻辑门电路之间的连接关系，从而实现以上部分或全部单元或模块的功能。以上装置的所有单元或模块可以全部通过处理器调用软件的形式实现，或全部通过硬件电路的形式实现，或部分通过处理器调用软件的形式实现，剩余部分通过硬件电路的形式实现。
在本公开实施例中，处理器是具有信号处理能力的电路，在一种实现中，处理器可以是具有指令读取与运行能力的电路，例如中央处理单元(Central Processing Unit，CPU)、微处理器、图形处理器(Graphics Processing Unit，GPU)(可以理解为微处理器)、或数字信号处理器(Digital Signal Processor，DSP)等；在另一种实现中，处理器可以通过硬件电路的逻辑关系实现一定功能，上述硬件电路的逻辑关系是固定的或可以重构的，例如处理器为专用集成电路(Application-Specific Integrated Circuit，ASIC)或可编程逻辑器件(Programmable Logic Device，PLD)实现的硬件电路,例如FPGA。在可重构的硬件电路中，处理器加载配置文档，实现硬件电路配置的过程，可以理解为处理器加载指令，以实现以上部分或全部单元或模块的功能的过程。此外，还可以是针对人工智能设计的硬件电路，其可以理解为ASIC，例如神经网络处理单元(Neural Network Processing Unit，NPU)、张量处理单元(Tensor Processing Unit，TPU)、深度学习处理单元(Deep learning Processing Unit，DPU)等。
图6A是本公开实施例提出的一种终端设备的结构示意图。如图6A所示，该终端设备101可以包括处理模块6101、收发模块6102等中的至少一者。在一些实施例中，该处理模块6101，被配置为根据第一信息进行预测，得到所述终端设备与网络设备之间的路径损耗值。可选地，该处理模块6101可以用于执行以上任一方法中终端设备101执行的处理步骤(例如步骤S2102，但不限于此)中的至少一者，此处不再赘述。发送模块和接收模块可以是分离的，也可以集成在一起。可选地，收发模块可以与收发器相互替换。
在一些实施例中，处理模块可以是一个模块，也可以包括多个子模块。可选地，上述多个子模块分别执行处理模块所需执行的全部或部分步骤。可选地，处理模块可以与处理器相互替换。
图6B是本公开实施例提出的一种网络设备的结构示意图。如图6B所示，该网络设备102可以包括：收发模块6201、处理模块6202等中的至少一者。在一些实施例中，该收发模块6201，被配置为向终端设备发送第二信息，所述第二信息用于指示第一发射信息，所述第一发射信息为所述网络设备发送的路径损耗参考信号PL RS的功率值或者信号强度值，所述第一发射信息用于所述终端设备预测所述终端设备与所述网络设备之间的路径损耗值。可选地，该收发模块6201可以用于执行以上任一方法中网络设备102执行的发送和/或接收等通信步骤(例如步骤S2101，但不限于此)中的至少一者，此处不再赘述。
在一些实施例中，收发模块可以包括发送模块和/或接收模块，发送模块和接收模块可以是分离的，也可以集成在一起。可选地，收发模块可以与收发器相互替换。
图7A是本公开实施例提出的通信设备7100的结构示意图。通信设备7100可以是网络设备(例如接入网设备、核心网设备等)，也可以是终端(例如用户设备等)，也可以是支持第一设备实现以上任一方法的芯片、芯片系统、或处理器等，还可以是支持终端实现以上任一方法的芯片、芯片系统、或处理器等。通信设备7100可用于实现上述方法实施例中描述的方法，具体可以参见上述方法实施例中的说明。
如图7A所示，通信设备7100包括一个或多个处理器7101。处理器7101可以是通用处理器或者专用处理器等，例如可以是基带处理器或中央处理器。基带处理器可以用于对通信协议以及通信数据进行处理，中央处理器可以用于对通信装置(如，基站、基带芯片，物联网设备、物联网设备芯片，DU或CU等)进行控制，执行程序，处理程序的数据。通信设备7100用于执行以上任一方法。
在一些实施例中，通信设备7100还包括用于存储指令的一个或多个存储器7102。可选地，全部或部分存储器7102也可以处于通信设备7100之外。
在一些实施例中，通信设备7100还包括一个或多个收发器7103。在通信设备7100包括一个或多个收发器7103时，收发器7103执行上述方法中的发送和/或接收等通信步骤(例如步骤S2101，但不限于此)中的至少一者，处理器7101执行其他步骤(例如步骤S2102，但不限于此)中的至少一者。
在一些实施例中，收发器可以包括接收器和/或发送器，接收器和发送器可以是分离的，也可以集成在一起。可选地，收发器、收发单元、收发机、收发电路等术语可以相互替换，发送器、发送单元、发送机、发送电路等术语可以相互替换，接收器、接收单元、接收机、接收电路等术语可以相互替换。
在一些实施例中，通信设备7100可以包括一个或多个接口电路。可选地，接口电路与存储器7102连接，接口电路可用于从存储器7102或其他装置接收信号，可用于向存储器7102或其他装置发送信号。例如，接口电路可读取存储器7102中存储的指令，并将该指令发送给处理器7101。
以上实施例描述中的通信设备7100可以是第一设备或者物联网设备，但本公开中描述的通信设备7100的范围并不限于此，通信设备7100的结构可以不受图7A的限制。通信设备可以是独立的设备或者可以是较大设备的一部分。例如所述通信设备可以是：1)独立的集成电路IC，或芯片，或，芯片系统或子系统；(2)具有一个或多个IC的集合，可选地，上述IC集合也可以包括用于存储数据，程序的存储部件；(3) ASIC，例如调制解调器(Modem)；(4)可嵌入在其他设备内的模块；(5)接收机、物联网设备、智能物联网设备、蜂窝电话、无线设备、手持机、移动单元、车载设备、第一设备、云设备、人工智能设备等等；(6)其他等等。
图7B是本公开实施例提出的芯片7200的结构示意图。对于通信设备7100可以是芯片或芯片系统的情况，可以参见图7B所示的芯片7200的结构示意图，但不限于此。
芯片7200包括一个或多个处理器7201，芯片7200用于执行以上任一方法。
在一些实施例中，芯片7200还包括一个或多个接口电路7203。可选地，接口电路7203与存储器7202连接，接口电路7203可以用于从存储器7202或其他装置接收信号，接口电路7203可用于向存储器7202或其他装置发送信号。例如，接口电路7203可读取存储器7202中存储的指令，并将该指令发送给处理器7201。
在一些实施例中，接口电路7203执行上述方法中的发送和/或接收等通信步骤(例如步骤S2101，但不限于此)中的至少一者，处理器7201执行其他步骤(例如步骤S2102，但不限于此)中的至少一者。
在一些实施例中，接口电路、接口、收发管脚、收发器等术语可以相互替换。
在一些实施例中，芯片7200还包括用于存储指令的一个或多个存储器7202。可选地，全部或部分存储器7202可以处于芯片7200之外。
本公开实施例还提出存储介质，上述存储介质上存储有指令，当上述指令在通信设备7100上运行时，使得通信设备7100执行以上任一方法。可选地，上述存储介质是电子存储介质。可选地，上述存储介质是计算机可读存储介质，但不限于此，其也可以是其他装置可读的存储介质。可选地，上述存储介质可以是非暂时性(non-transitory)存储介质，但不限于此，其也可以是暂时性存储介质。
本公开实施例还提出程序产品，上述程序产品被通信设备7100执行时，使得通信设备7100执行以上任一方法。可选地，上述程序产品可以是计算机程序产品。
本公开实施例还提出计算机程序，当其在计算机上运行时，使得计算机执行以上任一方法。

Claims (14)

  1. 一种通信方法，其特征在于，所述方法包括：
    终端设备根据第一信息进行预测，得到所述终端设备与网络设备之间的路径损耗值。
  2. 根据权利要求1所述的方法，其特征在于，所述第一信息至少包括以下参数：
    第一发射信息，所述第一发射信息为所述网络设备在第一时间段内发送的路径损耗参考信号PL RS的功率值或者信号强度值，所述第一时间段为当前时刻之前的时间段；
    第一接收信息，所述第一接收信息为所述终端设备在所述第一时间段内测量的所述PL RS的功率值或者信号强度值；
    第一波束索引，所述第一波束索引为所述PL RS对应的波束索引值；
    所述终端设备当前时刻所处的第一位置。
  3. 根据权利要求2所述的方法，其特征在于，所述终端设备根据第一信息进行预测，得到所述终端设备与网络设备之间的路径损耗值包括：
    将所述第一信息输入第一模型，得到所述第一模型输出的所述路径损耗值，其中，所述第一模型为人工智能AI/机器学习ML模型。
  4. 根据权利要求3所述的方法，其特征在于，所述第一模型是通过第一样本信息训练得到的，所述第一样本信息至少包括以下参数：
    第二发射信息、第二接收信息、第二波束索引、所述终端设备的第二位置，其中，所述第二发射信息为所述网络设备发送的PL RS的功率值或者信号强度值、所述第二接收信息为所述终端设备测量的所述PL RS的功率值或者信号强度值，所述第二波束索引为所述PL RS对应的波束索引值。
  5. 根据权利要求4所述的方法，其特征在于，所述第一样本信息为所述第一信息时间段之前的信息。
  6. 根据权利要求2-5任一项所述的方法，其特征在于，所述方法还包括：
    接收所述网络设备发送的第二信息，所述第二信息用于指示所述第一发射信息。
  7. 根据权利要求1-6任一项所述的方法，其特征在于，所述方法还包括：
    根据所述路径损耗值确定上行发射功率。
  8. 一种通信方法，其特征在于，所述方法包括：
    网络设备向终端设备发送第二信息，所述第二信息用于指示第一发射信息，所述第一发射信息为所述网络设备发送的路径损耗参考信号PL RS的功率值或者信号强度值，所述第一发射信息用于所述终端设备预测所述终端设备与所述网络设备之间的路径损耗值。
  9. 根据权利要求8所述的方法，其特征在于，所述路径损耗值用于所述终端设备确定上行发射功率。
  10. 一种终端设备，其特征在于，包括：
    处理模块，被配置为根据第一信息进行预测，得到所述终端设备与网络设备之间的路径损耗值。
  11. 一种网络设备，其特征在于，包括：
    收发模块，被配置为向终端设备发送第二信息，所述第二信息用于指示第一发射信息，所述第一发射信息为所述网络设备发送的路径损耗参考信号PL RS的功率值或者信号强度值，所述第一发射信息用于所述终端设备预测所述终端设备与所述网络设备之间的路径损耗值。
  12. 一种通信设备，其特征在于，其特征在于，包括：
    一个或多个处理器；
    其中，所述通信设备用于执行权利要求1至7或权利要求8至9中任一项所述的通信方法。
  13. 一种存储介质，所述存储介质存储有指令，其特征在于，当所述指令在通信设备上运行时，使得 所述通信设备执行如权利要求1至7或权利要求8至9中任一项所述的通信方法。
  14. 一种通信系统，其特征在于，所述通信系统包括终端设备和网络设备，其中，所述终端设备被配置为实现权利要求1至7中任一项所述的通信方法，所述网络设备被配置为实现权利要求8至9中任一项所述的通信方法。
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