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WO2024140422A1 - Procédé de surveillance de performance d'unité d'ia, terminal et dispositif côté réseau - Google Patents

Procédé de surveillance de performance d'unité d'ia, terminal et dispositif côté réseau Download PDF

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Publication number
WO2024140422A1
WO2024140422A1 PCT/CN2023/140773 CN2023140773W WO2024140422A1 WO 2024140422 A1 WO2024140422 A1 WO 2024140422A1 CN 2023140773 W CN2023140773 W CN 2023140773W WO 2024140422 A1 WO2024140422 A1 WO 2024140422A1
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WO
WIPO (PCT)
Prior art keywords
information
unit
side device
network side
terminal
Prior art date
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PCT/CN2023/140773
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English (en)
Chinese (zh)
Inventor
任千尧
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Vivo Mobile Communication Co Ltd
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Vivo Mobile Communication Co Ltd
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Publication of WO2024140422A1 publication Critical patent/WO2024140422A1/fr
Anticipated expiration legal-status Critical
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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
    • H04B7/0621—Feedback content
    • H04B7/0626—Channel coefficients, e.g. channel state information [CSI]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/0204—Channel estimation of multiple channels
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/0224—Channel estimation using sounding signals
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/16—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L5/00—Arrangements affording multiple use of the transmission path
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L5/00—Arrangements affording multiple use of the transmission path
    • H04L5/003—Arrangements for allocating sub-channels of the transmission path
    • H04L5/0048—Allocation of pilot signals, i.e. of signals known to the receiver

Definitions

  • the present application belongs to the field of communication technology, and specifically relates to a performance monitoring method, terminal and network-side equipment of an AI unit.
  • AI artificial intelligence
  • CSI channel state information
  • the embodiments of the present application provide a performance monitoring method, terminal and network-side device for an AI unit, which can reduce the overhead of AI model performance monitoring.
  • a performance monitoring method for an AI unit comprising:
  • the terminal determines monitoring information based on the first channel information
  • the AI unit includes a first unit configured at the terminal and a second unit configured at the network side device, the first channel information is channel information input to the first unit, and the monitoring information includes at least one of the following:
  • a performance monitoring method for an AI unit comprising:
  • the network side device determines whether the AI unit is valid based on the monitoring information
  • the first measurement information and the identification ID of the first reference base are The first measurement information and the identification ID of the first reference base
  • the performance monitoring result is used to indicate whether the AI unit is effective.
  • a determination module configured to determine monitoring information based on the first channel information
  • the AI unit includes a first unit configured at the terminal and a second unit configured at the network side device, the first channel information is channel information input to the first unit, and the monitoring information includes at least one of the following:
  • a processing module configured to determine whether the AI unit is valid based on the monitoring information
  • the performance monitoring result is used to indicate whether the AI unit is effective.
  • a terminal comprising a processor and a memory, wherein the memory stores a program or instruction that can be run on the processor, and when the program or instruction is executed by the processor, the steps of the method described in the first aspect are implemented.
  • a network side device comprising a processor and a communication interface; wherein the communication interface is used to receive monitoring information from a terminal;
  • the processor is used to determine whether the AI unit is valid based on the monitoring information
  • the performance monitoring result is used to indicate whether the AI unit is effective.
  • a performance monitoring system for an AI unit including: a terminal and a network side device, wherein the terminal can be used to execute the steps of the method described in the first aspect, and the network side device can be used to execute the steps of the method described in the second aspect.
  • a readable storage medium on which a program or instruction is stored.
  • the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented, or the steps of the method described in the second aspect are implemented.
  • a chip comprising a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the method described in the first aspect, or to implement the method described in the second aspect.
  • a computer program/program product is provided, wherein the computer program/program product is stored in a storage medium, and the computer program/program product is executed by at least one processor to implement the steps of the method described in the first aspect, or to implement the steps of the method described in the second aspect.
  • the terminal determines and sends monitoring information to the network side device based on the first channel information input to the first unit.
  • the monitoring information includes first measurement information or performance monitoring results.
  • the first measurement information indicates the first correlation between the first channel information and the first reference base, or the performance monitoring result indicates whether the AI unit is valid.
  • the network side device can determine whether the AI unit is valid based on the monitoring information, thereby replacing the transmission of AI unit input information/output information with the transmission of measurement information of the first channel information and the first reference base, thereby reducing information transmission overhead and achieving rapid model monitoring.
  • since there is no need to transmit the reference base in real time only the ID of the reference base needs to be transmitted when in use. This can also reduce information transmission overhead, reduce AI model performance monitoring overhead, and achieve rapid model monitoring.
  • FIG2 is a flow chart of a method for monitoring the performance of an AI unit according to an embodiment of the present application
  • LTE Long Term Evolution
  • LTE-A Long Term Evolution
  • CDMA Code Division Multiple Access
  • TDMA Time Division Multiple Access
  • FDMA Frequency Division Multiple Access
  • OFDMA Orthogonal Frequency Division Multiple Access
  • SC-FDMA Single-carrier Frequency Division Multiple Access
  • NR new radio
  • the neural network-based CSI compression feedback scheme is: the terminal uses the coding network to compress and encode the channel information, sends the compressed content to the base station, and uses the decoding network at the base station to decode the compressed content to restore the channel information.
  • the decoding network of the base station and the coding network of the terminal need to be jointly trained to achieve a reasonable match.
  • the input of the coding model is channel information, and the output is coding information.
  • the input of the decoding model is coding information, and the output is channel information.
  • the main evaluation indicator of AI model performance is the correlation between the input channel information and the recovered channel information.
  • FIG. 2 is a flow chart of a method for monitoring the performance of an AI unit according to an embodiment of the present application. As shown in FIG. 2 , the method includes steps 201-202; wherein:
  • Step 202 The terminal sends the monitoring information to the network side device; wherein the AI unit includes a first unit configured at the terminal and a second unit configured at the network side device, the first channel information is channel information input to the first unit, and the monitoring information includes at least one of the following:
  • the terminal selects one or more reference bases in the first reference base set, calculates the measurement value of each reference base and the first channel information, and reports the ID of the corresponding reference base and the corresponding measurement value. For example, the terminal selects the reference base with the largest measurement value as the first reference base, or the reference base with the highest correlation as the first reference base.
  • the monitoring information includes the first measurement information.
  • the network side device selects a second reference basis from the second reference basis set, where the identifier of the second reference basis is a reference basis ID; and the network side device sends the reference basis ID to the terminal.
  • the reference basis ID includes at least one of the following: beam index and/or delay index; Type II codebook parameters.
  • the monitoring information includes the performance monitoring result.
  • the network side device selects a second reference base from the second reference base set, and the identifier of the second reference base is a reference base ID; the network side device calculates a second correlation between the second channel information and the second reference base to obtain second measurement information; the network side device sends the reference base ID and/or the second measurement information to the terminal.
  • the second measurement information is used to indicate a second degree of association between second channel information and a second reference base
  • the second channel information is channel information output by the second unit
  • the second reference base is a reference base corresponding to the reference base ID in a second reference base set.
  • Method 4 The terminal selects one or more reference bases in the first reference base set as the first reference base; the terminal calculates the first correlation between the first channel information and the first reference base, and determines the performance monitoring result based on the first correlation; wherein the monitoring information includes the performance monitoring result.
  • the first reference base may include the characteristics of the training data of the AI unit, such as model A.
  • the terminal determines whether the first channel information and the training data of the AI model have similar distribution characteristics or a certain correlation by comparing the first channel information with the first reference base, and thereby determines whether the first channel information is suitable for compression using the AI model based on the correlation judgment result.
  • a collection of historical channel information such as a collection of historical channel information of a terminal
  • the first reference basis set includes a fixed reference basis set and/or a dynamic reference basis set; wherein the dynamic The reference base set is determined by the historical channel information of the terminal.
  • the fixed reference base set includes one or more pre-agreed or configured reference bases; the fixed reference base set satisfies at least one of the following: (a) agreed by the protocol; (b) configured by the network side device; (c) configured by the network side device and matched with the AI unit.
  • the length of the reference base in the dynamic reference base set is agreed upon by a protocol or configured by the network side device.
  • the reference basis in the second reference basis set includes at least one of the following:
  • the second reference basis set includes a fixed reference basis set and/or a dynamic reference basis set; wherein the dynamic reference basis set is determined by historical channel information on the network side device side.
  • the fixed reference basis set includes one or more pre-agreed or configured reference bases; the fixed reference basis set satisfies at least one of the following: (a) agreed upon by the protocol; (b) configured by the network side device, that is, both the network side device and the terminal are known; (c) configured by the network side device and matched with the AI unit.
  • each reference basis can be mutually orthogonal.
  • the length of the reference base in the dynamic reference base set is agreed upon by a protocol or configured by the network side device.
  • first reference basis set used by the terminal and the second reference basis set used by the network side device may be the same.
  • first reference basis set and the second reference basis set correspond to the same fixed reference basis set.
  • the first reference basis set used by the terminal and the second reference basis set used by the network side device may be different.
  • the dynamic reference basis set corresponding to the first reference basis set is different from the dynamic reference basis set corresponding to the second reference basis set.
  • the set lengths of the first reference basis set and the second reference basis set may be the same.
  • Each reference basis in the first reference basis set and each reference basis in the second reference basis set are in a one-to-one correspondence.
  • the first reference basis is the historical channel estimation result of the terminal, or the simulated lossy channel estimation
  • the second reference basis is the precoding matrix result of the historical CSI reporting corresponding to the first reference basis.
  • first reference base set and the second reference base set can be updated in a rolling manner.
  • the length or size of the reference base set is indicated by the protocol or the network side device.
  • the updates of the two reference base sets are performed synchronously, and a certain number of expired or earliest reference bases are discarded respectively.
  • the terminal calculates the K DFT orthogonal bases with the strongest projection coefficients as the content of the first reference basis set based on the channel matrix at each moment, and the network side device uses the strongest K projected DFT orthogonal bases corresponding to the channel matrix restored by the channel characteristic information reported by the terminal at the corresponding moment as the first reference basis set.
  • the terminal and the network side device update their respective reference basis sets, or each time AI model monitoring is required, the terminal and the network side device update their respective reference basis sets based on the most recent or preset number of CSI.
  • the implementation manner in which the terminal sends the monitoring information to the network side device may include at least one of the following manners:
  • Method 1 When the terminal sends the first CSI to the network side device, the terminal sends the monitoring information to the network side device; the monitoring information is carried in the first CSI, for example, an additional information can be added to the normal CSI.
  • Method 2 The terminal sends a second CSI to the network side device, where the second CSI is used to report the monitoring information; the second CSI is configured by the network side device through CSI report config.
  • the terminal can report the model monitoring information as uplink control information (Uplink Control Information, UCI) through the physical uplink shared channel (PUSCH) or PUCCH, and can also upload the model monitoring information as data through PUSCH.
  • UCI Uplink Control Information
  • PUSCH physical uplink shared channel
  • PUCCH Physical Uplink shared channel
  • the channel information is a precoding vector of a layer.
  • the protocol stipulates a common reference basis set, including 32 orthogonal orthogonal bases, each of which is a reference basis, and the dimension of each orthogonal basis is 32.
  • these 32 orthogonal bases can be DFT orthogonal bases or other orthogonal bases.
  • the specific orthogonal bases can be determined during the AI model training process.
  • the terminal selects the strongest reference basis from the set:
  • the terminal traverses all reference bases, calculates the squared general cosine similarity (SGCS) between the precoding vector at the current moment and each reference base, and then selects the reference base with the largest SGCS as the target reference base.
  • SGCS squared general cosine similarity
  • the terminal caches the precoding vectors during each previous CSI measurement and traverses the SGCS of the reference basis set, and selects the reference basis corresponding to the historical maximum SGCS as the target reference basis.
  • the terminal reports the ID corresponding to the target reference base and the calculated SGCS to the base station.
  • the base station After the base station receives the CSI and the monitoring information reported by the terminal, it uses the decoding model to restore the corresponding precoding matrix according to the channel characteristic information in the CSI, finds the corresponding reference base in the reference base set according to the target reference base ID, calculates the SGCS of the restored precoding matrix and the target reference base, and compares them with the SGCS reported by the terminal to determine the status of the AI model.
  • the base station uses a single result. If the base station finds that the SGCS reported by the terminal is greater than the recovered SGCS and exceeds a certain threshold, the base station considers that the model is invalid and considers switching the model or switching to a non-AI CSI feedback method.
  • the base station uses historical results, and the base station compares the SGCS within a period of time, for example, directly summing or summing the squares.
  • Base station usage trend judgment that is, there is no threshold, the base station records the difference between the two SGCS within a period of time, if there is If there is a significant improvement, or multiple significant improvements, the judgment will be invalid.
  • the reference basis set used by the base station and the reference basis set used by the terminal are different, that is, the reference basis in the reference basis set of the base station is the result of CSI compression and reporting of the reference basis in the reference basis set of the terminal.
  • the reference base set can be updated in a rolling manner, that is, the protocol stipulates the length of a reference base set, the terminal and the base station update synchronously, and discard expired reference bases.
  • the special reference basis can be a DFT orthogonal basis, represented by a DFT index, or by a Type II parameter.
  • the first reference base includes at least one reference base.
  • the number of reference bases included in the first reference base is agreed upon by the protocol or configured by the network side device.
  • the AI unit includes an AI model.
  • the first unit includes a first AI model, such as an encoding model; the second unit includes a second AI model, such as a decoding model.
  • the first unit performs a first process, such as a compression encoding process based on an AI model.
  • the network side device receives the compressed content, and the second unit performs a second process, such as a decoding and recovery process based on an AI model.
  • the compression encoding process based on the AI model and the decoding and recovery process based on the AI model in this application are completely different concepts from channel coding and channel decoding.
  • the network side device sends indication information to the terminal; wherein the indication information is used to instruct the terminal to monitor the performance of the AI unit.
  • the network side device receives a physical uplink control channel PUCCH sent by the terminal, where the PUCCH carries the monitoring information.
  • FIG. 4 is a schematic diagram of a performance monitoring device for an AI unit provided in an embodiment of the present application. As shown in FIG. 4 , the performance monitoring device 400 for an AI unit is applied to a terminal and includes:
  • a determination module 401 configured to determine monitoring information based on the first channel information
  • the first measurement information and the identification ID of the first reference base are The first measurement information and the identification ID of the first reference base
  • the performance monitoring result is used to indicate whether the AI unit is effective.
  • monitoring information is determined and sent to the network side device, and the monitoring information includes first measurement information or performance monitoring results.
  • the first measurement information indicates the first correlation between the first channel information and the first reference base, or the performance monitoring result indicates whether the AI unit is valid, so that after obtaining the monitoring information, the network side device can determine whether the AI unit is valid based on the monitoring information, thereby replacing the transmission of AI unit input information/output information with the transmission of measurement information of the first channel information and the first reference base, thereby reducing information transmission overhead and realizing rapid model monitoring.
  • the ID of the reference base needs to be transmitted when in use, which can also reduce information transmission overhead, reduce AI model performance monitoring overhead, and realize rapid model monitoring.
  • the first receiving module is used to receive indication information from the network side device, where the indication information is used to instruct the terminal to monitor the performance of the AI unit.
  • the determination module 401 is specifically configured to select one or more reference bases from a first reference base set, and the terminal uses each of the reference bases as the first reference base, calculates the first degree of association between the first channel information and the first reference base, and obtains the first measurement information;
  • the monitoring information includes the first measurement information and the ID of the first reference base.
  • the determination module 401 is specifically configured to:
  • the first correlation degree between the first channel information and the first reference basis is calculated to obtain the first measurement information; wherein the monitoring information includes the first measurement information.
  • the device further comprises:
  • the second receiving module is used to receive the reference base ID sent by the network side device.
  • the monitoring information includes the performance monitoring result.
  • the second measurement information is used to indicate a second correlation between second channel information and a second reference base
  • the second channel information is channel information output by the second unit
  • the second reference base is a reference base corresponding to the reference base ID in a second reference base set.
  • the device further comprises:
  • the third receiving module is used to receive the reference base ID and/or the second measurement information sent by the network side device.
  • the determination module 401 is specifically configured to:
  • the terminal selects one or more reference bases from the first reference base set as the first reference base;
  • the terminal calculates the first correlation between the first channel information and the first reference base, and determines the performance monitoring result based on the first correlation; wherein the monitoring information includes the performance monitoring result; and the first reference base includes features of the training data of the AI unit.
  • the first reference basis set includes at least one of the following:
  • a fixed reference basis set wherein the fixed reference basis set includes one or more pre-agreed or configured reference bases; the fixed reference basis set satisfies at least one of the following: agreed upon by a protocol; configured by the network side device; configured by the network side device and matched with the AI unit;
  • a dynamic reference basis set is determined by historical channel information.
  • the length of the reference base in the dynamic reference base set is agreed upon by a protocol or configured by the network side device.
  • a feature vector associated with the training data distribution of the AI unit is A feature vector associated with the training data distribution of the AI unit.
  • the ID of the first reference basis includes at least one of the following:
  • Type II TypeII codebook parameters
  • the first sending module is specifically used for at least one of the following:
  • the monitoring information is sent to the network side device.
  • the monitoring information is carried in the first CSI.
  • the first correlation degree includes: a first similarity between the first channel information and a first reference basis.
  • the first reference base includes at least one reference base.
  • the number of reference bases included in the first reference base is agreed upon by a protocol or configured by the network side device.
  • the AI unit includes an AI model.
  • FIG. 5 is a second structural diagram of a performance monitoring device of an AI unit provided in an embodiment of the present application. As shown in FIG. 5 , the performance monitoring device 500 of the AI unit is applied to a network side device, and includes:
  • the fourth receiving module 501 is used to receive monitoring information from the terminal;
  • a processing module 502 configured to determine whether the AI unit is valid based on the monitoring information
  • the AI unit includes a first unit configured on the terminal and a second unit configured on the network side device, and the monitoring information includes at least one of the following:
  • first measurement information used to indicate a first correlation between first channel information and a first reference basis, the first channel information being channel information input to the first unit;
  • the first measurement information and the identification ID of the first reference base are The first measurement information and the identification ID of the first reference base
  • the performance monitoring result is used to indicate whether the AI unit is effective.
  • monitoring information is received from the terminal, and the monitoring information includes first measurement information or performance monitoring results.
  • the first measurement information indicates the first correlation between the first channel information and the first reference base, or the performance monitoring result indicates whether the AI unit is valid, so that after obtaining the monitoring information, the network side device can determine whether the AI unit is valid based on the monitoring information, thereby replacing the transmission of the AI unit input information/output information with the transmission of the measurement information of the first channel information and the first reference base, thereby reducing the information transmission overhead and realizing fast model monitoring.
  • the ID of the reference base needs to be transmitted when in use, which can also reduce the information transmission overhead, reduce the AI model performance monitoring overhead, and realize fast model monitoring.
  • the device further comprises:
  • the second sending module is used to send indication information to the terminal; wherein the indication information is used to instruct the terminal to monitor the performance of the AI unit.
  • processing module 502 is specifically configured to:
  • the AI unit Based on the first metric information and the second metric information, it is determined whether the AI unit is valid.
  • the device further comprises:
  • a first selection module configured to select a second reference basis from the second reference basis set, wherein the identifier of the second reference basis is a reference basis ID;
  • the third sending module is used to send the reference base ID to the terminal.
  • processing module 502 is specifically configured to:
  • the AI unit Based on the first metric information and the second metric information, it is determined whether the AI unit is valid.
  • a fourth sending module is used to send the reference base ID and/or the second measurement information to the terminal.
  • the processing module 502 is specifically configured to determine whether the AI unit is valid based on the performance monitoring result.
  • the second reference basis set includes at least one of the following:
  • a fixed reference basis set wherein the fixed reference basis set includes one or more pre-agreed or configured reference bases; the fixed reference basis set satisfies at least one of the following: agreed upon by a protocol; configured by the network side device; configured by the network side device and matched with the AI unit;
  • a dynamic reference basis set is determined by historical channel information.
  • the length of the reference base in the dynamic reference base set is agreed upon by a protocol or configured by the network side device.
  • the reference basis in the second reference basis set includes at least one of the following:
  • a feature vector associated with the training data distribution of the AI unit is A feature vector associated with the training data distribution of the AI unit.
  • the ID of the first reference basis includes at least one of the following:
  • a physical uplink control channel PUCCH sent by the terminal is received, where the PUCCH carries the monitoring information.
  • the first correlation degree includes: a first similarity between the first channel information and a first reference basis.
  • the second reference base includes at least one reference base.
  • the performance monitoring device of the AI unit in the embodiment of the present application can be an electronic device, such as an electronic device with an operating system, or a component in an electronic device, such as an integrated circuit or a chip.
  • the electronic device can be a terminal, or it can be other devices other than a terminal.
  • the terminal can include but is not limited to the types of terminal 11 listed above, and other devices can be servers, network attached storage (NAS), etc., which are not specifically limited in the embodiment of the present application.
  • the performance monitoring device of the AI unit provided in the embodiment of the present application can implement the various processes implemented by the method embodiments of Figures 2 to 5 and achieve the same technical effect. To avoid repetition, it will not be repeated here.
  • the communication interface is used to send the monitoring information to the network side device
  • first measurement information used to indicate a first correlation between the first channel information and a first reference basis
  • the first measurement information and the identification ID of the first reference base are The first measurement information and the identification ID of the first reference base
  • the performance monitoring result is used to indicate whether the AI unit is effective.
  • This terminal embodiment corresponds to the above-mentioned terminal side method embodiment.
  • Each implementation process and implementation method of the above-mentioned method embodiment can be applied to this terminal embodiment and can achieve the same technical effect.
  • FIG. 7 is a schematic diagram of the structure of a terminal provided in an embodiment of the present application.
  • the terminal 700 includes but is not limited to In: at least some of the components in the radio frequency unit 701, the network module 702, the audio output unit 703, the input unit 704, the sensor 705, the display unit 706, the user input unit 707, the interface unit 708, the memory 709 and the processor 710.
  • the terminal 700 may also include a power source (such as a battery) for supplying power to each component, and the power source may be logically connected to the processor 710 through a power management system, so as to implement functions such as managing charging, discharging, and power consumption management through the power management system.
  • a power source such as a battery
  • the terminal structure shown in FIG7 does not constitute a limitation on the terminal, and the terminal may include more or fewer components than shown in the figure, or combine certain components, or arrange components differently, which will not be described in detail here.
  • the input unit 704 may include a graphics processing unit (GPU) 7041 and a microphone 7042, and the graphics processor 7041 processes the image data of a static picture or video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode.
  • the display unit 706 may include a display panel 7061, and the display panel 7061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc.
  • the user input unit 707 includes a touch panel 7071 and at least one of other input devices 7072.
  • the touch panel 7071 is also called a touch screen.
  • the touch panel 7071 may include two parts: a touch detection device and a touch controller.
  • Other input devices 7072 may include, but are not limited to, a physical keyboard, function keys (such as a volume control key, a switch key, etc.), a trackball, a mouse, and a joystick, which will not be repeated here.
  • the memory 709 can be used to store software programs or instructions and various data.
  • the memory 709 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data, wherein the first storage area may store an operating system, an application program or instruction required for at least one function (such as a sound playback function, an image playback function, etc.), etc.
  • the memory 709 may include a volatile memory or a non-volatile memory, or the memory 709 may include a transient and non-transient memory.
  • the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory.
  • the volatile memory may be a random access memory (RAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate synchronous dynamic random access memory (DDRSDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synchronous link dynamic random access memory (SLDRAM) and a direct memory bus random access memory (DRRAM).
  • the memory 709 in the embodiment of the present application includes but is not limited to these and any other suitable types of memories.
  • the processor 710 may include one or more processing units; optionally, the processor 710 integrates an application processor and a modem processor, wherein the application processor mainly processes operations related to the operating system, user interface, and application programs, and the modem processor mainly processes wireless communication signals, such as a baseband processor. It is understandable that the above-mentioned modem processor The processor may not be integrated into the processor 710.
  • the processor 710 is configured to determine monitoring information based on the first channel information
  • the radio frequency unit 701 is used to send the monitoring information to the network side device;
  • the AI unit includes a first unit configured at the terminal and a second unit configured at the network side device, the first channel information is channel information input to the first unit, and the monitoring information includes at least one of the following:
  • first measurement information used to indicate a first correlation between the first channel information and a first reference basis
  • the first measurement information and the identification ID of the first reference base are The first measurement information and the identification ID of the first reference base
  • the performance monitoring result is used to indicate whether the AI unit is effective.
  • the terminal determines and sends monitoring information to the network side device based on the first channel information input to the first unit.
  • the monitoring information includes first measurement information or performance monitoring results.
  • the first measurement information indicates the first correlation between the first channel information and the first reference base, or the performance monitoring result indicates whether the AI unit is valid, so that after obtaining the monitoring information, the network side device can determine whether the AI unit is valid based on the monitoring information, thereby replacing the transmission of AI unit input information/output information with the transmission of measurement information of the first channel information and the first reference base, thereby reducing information transmission overhead and achieving rapid model monitoring.
  • the ID of the reference base needs to be transmitted when in use, which can also reduce information transmission overhead, reduce AI model performance monitoring overhead, and achieve rapid model monitoring.
  • the embodiment of the present application also provides a network side device, including a processor and a communication interface; wherein the communication interface is used to receive monitoring information from a terminal;
  • the processor is used to determine whether the AI unit is valid based on the monitoring information
  • the AI unit includes a first unit configured on the terminal and a second unit configured on a network side device, and the monitoring information includes at least one of the following:
  • first measurement information used to indicate a first correlation between first channel information and a first reference basis, the first channel information being channel information input to the first unit;
  • the first measurement information and the identification ID of the first reference base are The first measurement information and the identification ID of the first reference base
  • the performance monitoring result is used to indicate whether the AI unit is effective.
  • This network side device embodiment corresponds to the above-mentioned network side device method embodiment.
  • Each implementation process and implementation method of the above-mentioned method embodiment can be applied to this network side device embodiment and can achieve the same technical effect.
  • FIG8 is a schematic diagram of the structure of a network side device provided in an embodiment of the present application.
  • the network side device 800 includes: an antenna 801, a radio frequency device 802, a baseband device 803, a processor 804, and a memory 805.
  • the antenna 801 is connected to the radio frequency device 802.
  • the radio frequency device 802 receives information through the antenna 801 and sends the received information to the baseband device 803 for processing.
  • the baseband device 803 processes the information to be sent and sends it to the radio frequency device 802.
  • the radio frequency device 802 processes the received information and sends it out through the antenna 801.
  • the method executed by the network-side device in the above embodiment may be implemented in the baseband device 803, which includes a baseband processor.
  • the baseband device 803 may include, for example, at least one baseband board, on which a plurality of chips are arranged, as shown in FIG. As shown, one of the chips is, for example, a baseband processor, which is connected to the memory 805 through a bus interface to call the program in the memory 805 to execute the network device operations shown in the above method embodiment.
  • the network side device may also include a network interface 806, which is, for example, a common public radio interface (CPRI).
  • a network interface 806, which is, for example, a common public radio interface (CPRI).
  • CPRI common public radio interface
  • the network side device 800 of the embodiment of the present application also includes: instructions or programs stored in the memory 805 and executable on the processor 804.
  • the processor 804 calls the instructions or programs in the memory 805 to execute the method described above... and achieve the same technical effect. To avoid repetition, it will not be repeated here.
  • An embodiment of the present application also provides a performance monitoring system for an AI unit, including: a terminal and a network side device, wherein the terminal can be used to execute the steps of the performance monitoring method for the AI unit on the terminal side as described above, and the network side device can be used to execute the steps of the performance monitoring method for the AI unit on the network side device side as described above.
  • An embodiment of the present application also provides a readable storage medium, which may be volatile or non-volatile, and stores a program or instruction.
  • a program or instruction When the program or instruction is executed by a processor, the various processes of the performance monitoring method embodiment of the above-mentioned AI unit are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.
  • the processor is the processor in the terminal described in the above embodiment.
  • the readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.
  • An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the performance monitoring method embodiment of the above-mentioned AI unit, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.
  • the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.
  • the embodiment of the present application further provides a computer program/program product, which is stored in a storage medium, and is executed by at least one processor to implement the various processes of the above-mentioned AI unit performance monitoring method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.
  • the above embodiment method can be It can be implemented by means of software plus a necessary general hardware platform, or by hardware, but in many cases the former is a better implementation method.
  • the technical solution of the present application, or the part that contributes to the prior art can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM/RAM, disk, CD), and includes several instructions for enabling a terminal (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

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  • Engineering & Computer Science (AREA)
  • Signal Processing (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Power Engineering (AREA)
  • Databases & Information Systems (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Evolutionary Computation (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Artificial Intelligence (AREA)
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  • Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Data Exchanges In Wide-Area Networks (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

La présente demande se rapporte au domaine technique des communications, et divulgue un procédé de surveillance de performance d'unité d'IA, un terminal et un dispositif côté réseau. Le procédé de surveillance de performance d'unité d'IA dans des modes de réalisation de la présente demande comprend les étapes suivantes : un terminal détermine des informations de surveillance sur la base de premières informations de canal ; et le terminal envoie les informations de surveillance au dispositif côté réseau ; une unité IA comprenant une première unité agencée sur le terminal et une seconde unité agencée sur le dispositif côté réseau ; les premières informations de canal représentant une entrée d'informations de canal à la première unité ; et les informations de surveillance comprenant des premières informations de mesure utilisées pour indiquer un premier degré d'association des premières informations de canal et d'une première base de référence ; et/ou un identifiant (ID) des premières informations de mesure et un ID de la première base de référence ; et/ou un résultat de surveillance de performance utilisé pour indiquer si l'unité IA est valide ou n'est pas valide.
PCT/CN2023/140773 2022-12-26 2023-12-21 Procédé de surveillance de performance d'unité d'ia, terminal et dispositif côté réseau Ceased WO2024140422A1 (fr)

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CN202211679082.8 2022-12-26
CN202211679082.8A CN118265043A (zh) 2022-12-26 2022-12-26 Ai单元的性能监测方法、终端及网络侧设备

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Citations (4)

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Publication number Priority date Publication date Assignee Title
US20140056272A1 (en) * 2011-04-22 2014-02-27 China Academy Of Telecommunications Technology Method, device, and system for reporting channel quality indicator
CN112204532A (zh) * 2018-08-30 2021-01-08 华为技术有限公司 一种终端对ai任务支持能力的评测方法及终端
CN112508044A (zh) * 2019-09-16 2021-03-16 华为技术有限公司 人工智能ai模型的评估方法、系统及设备
CN114363921A (zh) * 2020-10-13 2022-04-15 维沃移动通信有限公司 Ai网络参数的配置方法和设备

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140056272A1 (en) * 2011-04-22 2014-02-27 China Academy Of Telecommunications Technology Method, device, and system for reporting channel quality indicator
CN112204532A (zh) * 2018-08-30 2021-01-08 华为技术有限公司 一种终端对ai任务支持能力的评测方法及终端
CN112508044A (zh) * 2019-09-16 2021-03-16 华为技术有限公司 人工智能ai模型的评估方法、系统及设备
CN114363921A (zh) * 2020-10-13 2022-04-15 维沃移动通信有限公司 Ai网络参数的配置方法和设备

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