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WO2024055974A1 - Procédé et appareil de transmission de cqi, terminal et dispositif côté réseau - Google Patents

Procédé et appareil de transmission de cqi, terminal et dispositif côté réseau Download PDF

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Publication number
WO2024055974A1
WO2024055974A1 PCT/CN2023/118440 CN2023118440W WO2024055974A1 WO 2024055974 A1 WO2024055974 A1 WO 2024055974A1 CN 2023118440 W CN2023118440 W CN 2023118440W WO 2024055974 A1 WO2024055974 A1 WO 2024055974A1
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WIPO (PCT)
Prior art keywords
terminal
cqi
network side
side device
precoding
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PCT/CN2023/118440
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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 WO2024055974A1 publication Critical patent/WO2024055974A1/fr
Anticipated expiration legal-status Critical
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/10—Scheduling measurement reports ; Arrangements for measurement reports

Definitions

  • This application belongs to the field of communication technology, and specifically relates to a CQI transmission method, device, terminal and network side equipment.
  • the terminal projects the precoding matrix on the selected orthogonal basis and reports the stronger coefficients to the base station.
  • the terminal can calculate the base station based on the reported content.
  • the restored precoding matrix is used to calculate the signal-to-noise ratio to obtain the Channel Quality Indicator (CQI), so that the CQI corresponds to the reported precoding matrix.
  • CQI Channel Quality Indicator
  • the terminal cannot calculate the CQI that matches the reported precoding matrix indicator (PMI). If the base station Directly using the reported CQI will cause deviations in the scheduling results, resulting in erroneous transmissions.
  • PMI reported precoding matrix indicator
  • Embodiments of the present application provide a CQI transmission method, device, terminal and network-side equipment, which can solve the problem in related technologies that the terminal cannot calculate the CQI that matches the reported PMI, resulting in deviation in the network-side equipment scheduling results.
  • a CQI transmission method including:
  • the terminal acquires a first CQI, where, if the first condition is met, the first CQI is a CQI calculated by the terminal based on the first precoding, the rank indicator RI and the channel state information reference signal indicator CRI;
  • the terminal reports the first CQI to the network side device
  • the first condition includes at least one of the following:
  • the terminal is configured with a target high-layer parameter, and the target high-layer parameter is used to instruct the terminal to use the first precoding to calculate the first CQI;
  • the terminal receives the first instruction information sent by the network side device, and the first instruction information is used to instruct the terminal to use the first precoding to calculate the first CQI;
  • the terminal performs channel state information CSI compression based on the artificial intelligence AI coding model
  • the terminal uses an AI codebook
  • the terminal is not configured with an AI decoding model
  • the terminal is configured with an AI decoding model, and the AI decoding model is not associated with the network side device.
  • a CQI transmission method including:
  • the network side device receives the first CQI reported by the terminal
  • the first CQI is the CQI calculated by the terminal based on the first precoding, RI and CRI;
  • the first condition includes any of the following:
  • the terminal is configured with a target high-layer parameter, and the target high-layer parameter is used to instruct the terminal to use the first precoding to calculate the first CQI;
  • the terminal receives the first instruction information sent by the network side device, and the first instruction information is used to instruct the terminal to use the first precoding to calculate the first CQI;
  • the terminal performs channel state information CSI compression based on the artificial intelligence AI coding model
  • the terminal uses an AI codebook
  • the terminal is not configured with an AI decoding model
  • the terminal is configured with an AI decoding model, and the AI decoding model is not associated with the network side device.
  • a CQI transmission device including:
  • Obtaining module configured to obtain a first CQI, where, if the first condition is met, the first CQI is a CQI calculated by the device based on the first precoding, the rank indicator RI and the channel state information reference signal indicator CRI. ;
  • a reporting module configured to report the first CQI to the network side device
  • the first condition includes at least one of the following:
  • the device is configured with a target high-layer parameter, and the target high-layer parameter is used to instruct the device to use the first precoding to calculate the first CQI;
  • the device receives first indication information sent by a network side device, where the first indication information is used to instruct the device to use the first precoding to calculate the first CQI;
  • the device performs channel state information CSI compression based on the artificial intelligence AI coding model
  • the device uses an AI codebook
  • the device is not configured with an AI decoding model
  • the device is configured with an AI decoding model, and the AI decoding model is not associated with the network side device.
  • a CQI transmission device including:
  • the receiving module is used to receive the first CQI reported by the terminal;
  • the first CQI is the CQI calculated by the terminal based on the first precoding, RI and CRI;
  • the first condition includes any of the following:
  • the terminal is configured with a target high-layer parameter, and the target high-layer parameter is used to instruct the terminal to use the first precoding to calculate the first CQI;
  • the terminal receives first instruction information sent by the device, where the first instruction information is used to instruct the terminal to use the first precoding to calculate the first CQI;
  • the terminal performs channel state information CSI compression based on the artificial intelligence AI coding model
  • the terminal uses an AI codebook
  • the terminal is not configured with an AI decoding model
  • the terminal is configured with an AI decoding model, and the AI decoding model is not associated with the network side device.
  • a terminal in a fifth aspect, includes a processor and a memory.
  • the memory stores programs or instructions that can be run on the processor.
  • the program or instructions are executed by the processor, the following implementations are implemented: The steps of the CQI transmission method described in one aspect.
  • a terminal including a processor and a communication interface, wherein the processor is configured to obtain a first CQI, wherein, when the first condition is met, the first CQI is the device based on The CQI calculated by the first precoding, rank indicator RI and channel state information reference signal indicator CRI, the communication interface is used to report the first CQI to the network side device;
  • the first condition includes at least one of the following:
  • the terminal is configured with a target high-layer parameter, and the target high-layer parameter is used to instruct the terminal to use the first precoding to calculate the first CQI;
  • the terminal receives the first instruction information sent by the network side device, and the first instruction information is used to instruct the terminal to use the first precoding to calculate the first CQI;
  • the terminal performs channel state information CSI compression based on the artificial intelligence AI coding model
  • the terminal uses an AI codebook
  • the terminal is not configured with an AI decoding model
  • the terminal is configured with an AI decoding model, and the AI decoding model is not associated with the network side device.
  • a network side device in a seventh aspect, includes a processor and a memory.
  • the memory stores programs or instructions that can be run on the processor.
  • the program or instructions are executed by the processor.
  • a network side device including a processor and a communication interface, wherein the communication interface is used to receive the first CQI reported by the terminal;
  • the first CQI is the CQI calculated by the terminal based on the first precoding, RI and CRI;
  • the first condition includes any of the following:
  • the terminal is configured with a target high-layer parameter, and the target high-layer parameter is used to instruct the terminal to use the first precoding to calculate the first CQI;
  • the terminal receives the first instruction information sent by the network side device, and the first instruction information is used to instruct the terminal to use the first precoding to calculate the first CQI;
  • the terminal performs channel state information CSI compression based on the artificial intelligence AI coding model
  • the terminal uses an AI codebook
  • the terminal is not configured with an AI decoding model
  • the terminal is configured with an AI decoding model, and the AI decoding model is not associated with the network side device.
  • a ninth aspect provides a communication system, including: a terminal and a network side device.
  • the terminal can be used to perform the steps of the CQI transmission method as described in the first aspect.
  • the network side device can be used to perform the steps of the CQI transmission method as described in the second aspect. The steps of the CQI transmission method.
  • a readable storage medium is provided. Programs or instructions are stored on the readable storage medium. When the programs or instructions are executed by a processor, the steps of the CQI transmission method as described in the first aspect are implemented, or Implement the steps of the CQI transmission method described in the second aspect.
  • a chip in an eleventh aspect, includes a processor and a communication interface.
  • the communication interface is coupled to the processor.
  • the processor is used to run programs or instructions to implement the method described in the first aspect. CQI transmission method, or implement the CQI transmission method as described in the second aspect.
  • a computer program/program product is provided, 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 as described in the first aspect CQI transmission method, or implement the CQI transmission method as described in the second aspect.
  • the terminal when the first condition is met, calculates the first CQI based on the first precoding, RI and CRI, reports the first CQI to the network side device, and then uses AI coding in the terminal
  • the model performs CSI compression
  • the network side device uses the AI decoding model to perform CSI recovery
  • the terminal reports the first CQI calculated by the first precoding
  • the network side device can process the first CQI by itself and recover it through the AI decoding model.
  • the precoding relationship ensures accurate scheduling of terminals by network side equipment and avoids transmission errors.
  • Figure 1 is a block diagram of a wireless communication system applicable to the embodiment of the present application.
  • Figure 2 is a flow chart of a CQI transmission method provided by an embodiment of the present application.
  • FIG. 3 is a flow chart of another CQI transmission method provided by an embodiment of the present application.
  • FIG. 4 is a structural diagram of a CQI transmission device provided by an embodiment of the present application.
  • FIG. 5 is a structural diagram of another CQI transmission device provided by an embodiment of the present application.
  • Figure 6 is a structural diagram of a communication device provided by an embodiment of the present application.
  • Figure 7 is a structural diagram of a terminal provided by an embodiment of the present application.
  • Figure 8 is a structural diagram of a network side device provided by an embodiment of the present application.
  • first, second, etc. in the description and claims of this application are used to distinguish similar objects and are not used to describe a specific order or sequence. It is understood that the terms so used are interchangeable where appropriate, So that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by “first” and “second” are generally of the same type, and the number of objects is not limited, for example
  • the first object can be one or multiple.
  • “and/or” in the description and claims indicates at least one of the connected objects, and the character “/” generally indicates that the related objects are in an "or” relationship.
  • LTE Long Term Evolution
  • LTE-Advanced, LTE-A 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
  • FIG. 1 shows a block diagram of a wireless communication system to which embodiments of the present application are applicable.
  • the wireless communication system includes a terminal 11 and a network side device 12.
  • the terminal 11 can be a mobile phone, a tablet computer (Tablet Personal Computer), a laptop computer (Laptop Computer), or a notebook computer, a personal digital assistant (Personal Digital Assistant, PDA), a handheld computer, a netbook, or a super mobile personal computer.
  • Tablet Personal Computer Tablet Personal Computer
  • laptop computer laptop computer
  • PDA Personal Digital Assistant
  • PDA Personal Digital Assistant
  • UMPC ultra-mobile personal computer
  • UMPC mobile Internet device
  • MID mobile Internet device
  • augmented reality augmented reality, AR
  • VR virtual reality
  • robots wearable devices
  • Vehicle user equipment VUE
  • pedestrian terminal pedestrian terminal
  • PUE pedestrian terminal
  • smart home home equipment with wireless communication functions, such as refrigerators, TVs, washing machines or furniture, etc.
  • game consoles personal computers (personal computer, PC), teller machine or self-service machine and other terminal-side devices.
  • Wearable devices include: smart watches, smart bracelets, smart headphones, smart glasses, smart jewelry (smart bracelets, smart bracelets, smart rings, smart necklaces, smart anklets) bracelets, smart anklets, etc.), smart wristbands, smart clothing, etc.
  • the network side equipment 12 may include access network equipment or core network equipment, where the access network equipment may also be called wireless access network equipment, radio access network (Radio Access Network, RAN), radio access network function or wireless access network unit.
  • Access network equipment can include base stations, Wireless Local Area Network (WLAN) access points or WiFi nodes, etc.
  • WLAN Wireless Local Area Network
  • the base station can be called Node B, Evolved Node B (eNB), access point, base transceiver station ( Base Transceiver Station (BTS), radio base station, radio transceiver, Basic Service Set (BSS), Extended Service Set (ESS), home B-node, home evolved B-node, sending and receiving point ( Transmitting Receiving Point (TRP) or some other suitable term in the field, as long as the same technical effect is achieved, the base station is not limited to specific technical terms. It should be noted that in the embodiment of this application, only the NR system is used The base station is introduced as an example, and the specific type of base station is not limited.
  • channel state information is crucial to channel capacity.
  • the transmitter can optimize signal transmission based on CSI to better match the channel status.
  • channel quality indicator CQI
  • MCS modulation and coding scheme
  • precoding matrix indicator precoding matrix indicator
  • PMI precoding matrix indicator
  • Eigen beamforming Eigen beamforming
  • the base station sends a channel state information reference signal (CSI Reference Signal, CSI-RS) on certain time-frequency resources in a certain time slot.
  • CSI-RS channel state information reference signal
  • the terminal performs channel estimation based on the CSI-RS and calculates the time slot.
  • the PMI is fed back to the base station through the codebook.
  • the base station combines the channel information based on the codebook information fed back by the terminal. The base station uses this to perform data precoding and multi-user scheduling before the next CSI report.
  • the terminal can change the PMI reported on each subband to report PMI based on delay. Since the channels in the delay domain are more concentrated, PMI with fewer delays can approximately represent the PMI of all subbands. That is, the delay field information will be compressed before reporting.
  • the base station can precode the CSI-RS in advance and send the coded CSI-RS to the terminal. What the terminal sees is the channel corresponding to the coded CSI-RS. The terminal only needs to Just select several ports with greater strength among the indicated ports and report the coefficients corresponding to these ports.
  • neural network or machine learning methods can be used.
  • the CSI compression recovery process estimates the CSI-RS for the terminal, calculates the channel information, passes the calculated channel information or the original estimated channel information through the coding network (also called the coding model) to obtain the coding result, and sends the coding result to the base station, which receives it.
  • the encoded result is input into the decoding network (also called the decoding model) to restore the channel information.
  • the CSI compression feedback scheme based on neural networks is to compress and encode the channel information at the terminal, send the compressed content to the base station, and decode the compressed content at the base station to restore the channel information.
  • the base station The decoding model and the encoding model of the terminal need to be jointly trained to achieve a reasonable matching degree.
  • the input of the encoding model is channel information, and the output is encoding information.
  • the input of the decoding model is encoding information, and the output is channel information.
  • the encoding model and the decoding model are usually trained through the following three schemes:
  • the neural network model forms a joint neural network model through the encoder of the terminal and the decoder of the base station, and is jointly trained by the network side. After the training is completed, the base station sends the encoding model to the terminal.
  • Solution 2 The terminal and the base station each train their own encoding model and decoding model, and perform matching through the matching process, so that the encoding model of the terminal and the decoding model of the base station match each other.
  • Option 3 The terminal trains the encoding model and the decoding model.
  • the base station trains the decoding model based on the original data and the encoding results of the terminal. At this time, the base station does not need to train the encoding model.
  • the base station trains the network model and sends the encoding part to the terminal, or the terminal and the base station separately train the encoding and solution code part, and then perform matching, it may happen that the terminal does not know the decoding model of the base station, that is, the terminal cannot calculate the channel information recovered by the base station.
  • the terminal projects the precoding matrix on the selected orthogonal basis and reports the stronger coefficients to the base station.
  • the terminal can calculate the precoding matrix restored by the base station based on the reported content and use the restored
  • the precoding matrix calculates the signal-to-noise ratio to obtain the CQI, so that the CQI corresponds to the reported precoding matrix.
  • the terminal cannot obtain the precoding matrix recovered by the base station, the terminal cannot calculate the CQI that matches the reported PMI. Inconsistent understanding of the CQI algorithm between the base station and the terminal will cause the base station to be unable to directly use the terminal report. The CQI will lead to deviations in scheduling results, resulting in erroneous transmissions or a waste of time and frequency resources.
  • the present disclosure proposes a CQI transmission method.
  • Figure 2 is a flow chart of a CQI transmission method provided by an embodiment of the present disclosure. As shown in Figure 2, the method includes the following steps:
  • Step 201 The terminal acquires a first CQI, where, if the first condition is met, the first CQI is a reference signal indicator obtained by the terminal based on the first precoding, a rank indicator (Rank indicator, RI) and a channel state information (CSI-RS Resource Indicator, CRI) calculated CQI;
  • the first CQI is a reference signal indicator obtained by the terminal based on the first precoding, a rank indicator (Rank indicator, RI) and a channel state information (CSI-RS Resource Indicator, CRI) calculated CQI;
  • Step 202 The terminal reports the first CQI to the network side device.
  • the first condition includes at least one of the following:
  • the terminal is configured with a target high-layer parameter, and the target high-layer parameter is used to instruct the terminal to use the first precoding to calculate the first CQI;
  • the terminal receives the first instruction information sent by the network side device, and the first instruction information is used to instruct the terminal to use the first precoding to calculate the first CQI;
  • the terminal performs CSI compression based on the AI coding model
  • the terminal uses an AI codebook
  • the terminal is not configured with an AI decoding model
  • the terminal is configured with an AI decoding model, and the AI decoding model is not associated with the network side device.
  • the terminal calculates the first CQI based on the first precoding, RI and CRI, and Report the first CQI to the network side device.
  • the first indication information may be carried in CSI report configuration information (CSI report config) or in CSI-RS resource configuration information (CSI-RS resource config), or the first indication information may also be Independent Downlink Control Information (DCI), Medium Access Control Element (MAC CE) or Radio Resource Control (Radio Resource Control, RRC) indication.
  • DCI Independent Downlink Control Information
  • MAC CE Medium Access Control Element
  • RRC Radio Resource Control
  • the network side device when the terminal uses an AI coding model to perform CSI compression and output channel characteristic information, the network side device usually also includes an AI decoding model that matches the AI coding model to decode the channel characteristic information reported by the terminal. code to recover the precoding.
  • the terminal since the terminal cannot obtain the precoding restored by the base station, the terminal calculates the first CQI based on the first precoding, RI and CRI, and reports the first CQI to the network side device.
  • the network side device knows that the terminal In the case where the first CQI is calculated based on the first precoding, the network side device can handle the relationship between the precoding restored through the AI decoding model and the first CQI by itself to ensure accurate scheduling of the terminal by the network side device.
  • the terminal is not configured with an AI decoding model, that is, the terminal is configured with an AI encoding model, but does not know the corresponding AI decoding model configured on the network side device, or the terminal is configured with an AI decoding model, but the AI decoding model is not connected with the network.
  • the terminal is associated with the side device (such as the base station), that is, the terminal does not know which AI decoding model the base station will use.
  • the terminal calculates the first CQI based on the first precoding, RI and CRI, and reports the above to the network side device. First CQI. In this way, the terminal reports the first CQI calculated by the accurate first precoding, so that the network side device can handle the relationship between the first CQI and the precoding restored through the AI decoding model to ensure accurate scheduling of the terminal by the network side device. .
  • the terminal is configured with the target high-level parameters, and the terminal performs CSI calculation based on the AI coding model.
  • the calculation includes precoding or channel information compression through the AI coding model.
  • the terminal can also precode first , RI and CRI to calculate the first CQI, and report the first CQI to the network side device.
  • the terminal can also calculate the first CQI using the first precoding, RI and CRI, and report the first CQI to the network side device.
  • the first condition that the terminal satisfies may include at least one of the above. That is, there are many specific situations in which the terminal satisfies the first condition, which will not be listed here.
  • the RI and CRI may be the RI and CRI reported by the terminal to the network side device.
  • the terminal when the above first condition is met, calculates the first CQI based on the first precoding, RI and CRI, reports the first CQI to the network side device, and then uses AI coding in the terminal
  • the model performs CSI compression and the network-side device uses the AI decoding model to recover the precoding
  • the terminal reports the first CQI calculated by the accurate first precoding to ensure that the network-side device can process the first CQI by itself and use the AI
  • the decoding model restores the precoding relationship to ensure accurate scheduling of the terminal by the network side device and avoid transmission errors.
  • the first precoding includes any of the following:
  • Original precoding which is precoding without orthogonal basis projection.
  • the terminal may calculate the first CQI based on the SVD precoding, RI and CRI, or may calculate the first CQI based on the original precoding, RI and CRI.
  • the SVD precoding may refer to the original precoding obtained through SVD processing.
  • the SVD process does not change the amount of precoding information, but only changes the matrix dimension.
  • the matrix dimension of the SVD precoding is relative to The original precoding matrix dimension is smaller.
  • the embodiment of this application does not specifically limit the specific calculation method of the first precoding.
  • the first CQI is the terminal based on the second precoding,
  • the RI and the CRI calculate the CQI.
  • the second precoding is precoding through orthogonal basis projection, for example, the second precoding is PMI.
  • the second precoding is the precoding restored by the AI decoding model.
  • the first condition is that the terminal is configured with the target high-level parameter.
  • the terminal does not meet the first condition, that is, the terminal is not configured with the target high-level parameter.
  • the terminal may be based on the reported Calculate the first CQI based on the PMI, RI and CRI, and report the first CQI to the network side device.
  • the first condition is that the terminal performs CSI compression based on the AI coding model.
  • the terminal does not meet the first condition, that is, the terminal does not need to perform CSI compression through the AI coding model.
  • the terminal can calculate the first CQI based on PMI, RI and CRI, and report the first CQI to the network side device.
  • the terminal can calculate the first CQI based on SVD precoding or original precoding, RI and CRI. If the first condition is not met, the terminal can calculate the first CQI based on PMI, RI and CRI calculate the first CQI. In this way, the method of calculating the first CQI can be defined whether the terminal satisfies the first condition or does not satisfy the first condition, and thus whether the terminal satisfies the first condition or the terminal does not satisfy the first condition Under this condition, the network side equipment can handle the relationship between the first CQI and the precoding restored through the AI decoding model by itself, thereby ensuring accurate scheduling of the terminal by the network side equipment.
  • the terminal reports the first CQI to the network side device, including:
  • the terminal reports the first CQI and the channel characteristic information generated by the AI coding model to the network side device.
  • the terminal may report the channel characteristic information and the calculated first CQI to the network side device together.
  • the network side device can perform precoding recovery on the reported channel characteristic information based on the AI decoding model, and the network side device can handle the relationship between the first CQI and the recovered precoding by itself.
  • the method also includes:
  • the terminal reports the compensation information of the first CQI to the network side device; or,
  • the terminal reports the model identifier of the first target AI coding model used to the network side device, and the model identifier is used to determine the compensation information of the first CQI corresponding to the first target AI coding model.
  • the terminal may also report the compensation information of the first CQI to the network side device, and then the network side device can adjust the first CQI based on the compensation information.
  • the reporting period of the compensation information is different from the reporting period of the first CQI.
  • the reporting period of the compensation information may be greater than the reporting period of the first CQI.
  • the compensation information is reported only once when the first CQI is reported 10 times, or the compensation information is updated.
  • the compensation information includes a CQI impact factor or a precoding (preocder) impact factor.
  • the CQI impact factor or precoding impact factor may be protocol agreement or preconfigured.
  • the terminal reports the compensation information of the first CQI to the network side device, including any one of the following:
  • the terminal reports to the network side device the loss ratio or loss level of the second precoding matrix relative to the first precoding matrix, where the first precoding matrix is the precoding matrix input to the AI coding model, and the second precoding matrix
  • the precoding matrix is the precoding matrix output by the AI decoding model
  • the terminal reports the compensation value of the first CQI to the network side device.
  • the terminal can also know the loss of the precoding matrix after compression by the AI encoding model and decompression by the AI decoding model.
  • the loss may be the loss ratio or loss level of the second precoding matrix restored by the AI decoding model relative to the first precoding matrix before compression by the AI encoding model.
  • the terminal reports the loss ratio or loss level, and then the network side The device can adjust the received first CQI based on the loss ratio and the loss level.
  • the terminal can learn the compensation value of the first CQI that the terminal needs to report based on the loss, and then the terminal can report the compensation value, and then The network side device can adjust the first CQI based on the compensation value.
  • the compensation value may be a positive value or a negative value, and the network side device may add the compensation value to the first CQI for adjustment.
  • the terminal may report the usage to the network side device.
  • the model identification Identity document, ID
  • the network side device can also know which AI encoding model is used by the terminal, and then the network side device can also know the AI encoding.
  • the loss of the precoding matrix between the model and the AI decoding model used by the network side device is used to adjust the received first CQI based on the loss.
  • the terminal reports the compensation information of the first CQI to the network side device, including:
  • the terminal When the terminal switches the AI coding model used, the terminal reports the compensation information of the first CQI to the network side device.
  • the terminal may include multiple AI coding models, and the model parameters of different AI coding models may be different, so the loss of the precoding matrix after being compressed by different AI coding models may also be different, and then each time the terminal When switching the AI coding model used, after reporting the first CQI, the terminal also needs to report the compensation information of the first CQI to the network side device to ensure that the network side device performs the processing of the first CQI based on the compensation information. The first CQI is adjusted.
  • the terminal when the terminal switches the AI coding model used, the terminal reports the compensation information of the first CQI to the network side device, including:
  • the terminal When the terminal switches to using the second target AI coding model, the terminal sends the second target AI coding model and the compensation of the first CQI corresponding to the second target AI coding model to the network side device. information.
  • the terminal may include multiple AI coding models, each AI coding model corresponding to a compensation information, and the terminal simultaneously calculates the compensation information corresponding to the model when training the AI coding model; the terminal uses
  • the terminal reports the switched AI coding model (that is, the second target AI coding model) and the compensation corresponding to the AI coding model to the network side device. information, so that the network side device can clarify which AI coding model the terminal uses, and at the same time, can adjust the first CQI based on the compensation information.
  • the second target AI coding model and the corresponding compensation information may be sent at the same time, or may be sent separately.
  • sending the second target AI coding model and the compensation information of the first CQI corresponding to the second target AI coding model to the network side device includes:
  • the second target AI coding model and first information to the network side device respectively, where the first information includes the compensation information of the first CQI corresponding to the second target AI coding model and the second The model identifier of the target AI encoding model.
  • the network side device can also clarify which AI coding model the compensation information corresponds to, so as to avoid information confusion. .
  • the terminal when the terminal switches the AI coding model used, the terminal reports the compensation information of the first CQI to the network side device, including:
  • the terminal receives second instruction information sent by the network side device, and the second instruction information is used to instruct the terminal to report the compensation information of the first CQI when switching the AI coding model used;
  • the terminal Based on the second indication information, the terminal reports the compensation information of the CQI to the network side device when the terminal switches the AI coding model used.
  • the network side device may instruct the terminal to report the compensation information of the first CQI each time the AI coding model used is switched through the second indication information.
  • the terminal reporting the compensation information of the first CQI to the network side device may also include:
  • the terminal reports CSI to the network side device, where the CSI carries compensation information of the first CQI.
  • the compensation information of the first CQI may be carried in the CSI for reporting.
  • the terminal reports CSI to the network side device, including:
  • the terminal receives third indication information sent by the network side device, where the third indication information is used to instruct the CSI reported by the terminal to carry the compensation information of the first CQI;
  • the terminal reports CSI to the network side device based on the third indication information, and the CSI carries compensation information of the first CQI.
  • the network side device instructs the terminal to carry the compensation information of the first CQI in the CSI through the third indication information for reporting, and then the terminal carries the compensation information of the first CQI in the reported CSI based on the third indication information.
  • the compensation information allows the network side device to adjust the received first CQI based on the compensation information.
  • the method before the terminal reports the compensation information of the first CQI to the network side device, the method further includes:
  • the terminal adjusts the compensation information of the first CQI based on a feedback result of data reception, where the feedback result of data reception includes correct data reception or incorrect data reception.
  • the terminal can adjust the compensation information of the first CQI according to the feedback result of correct or incorrect data reception, and then report the adjusted compensation information to the network side device, thereby ensuring that the network side device is based on the received data.
  • the compensation information adjusts the first CQI.
  • the terminal adjusts the compensation information of the first CQI based on the feedback result of data reception, including:
  • the terminal reduces the compensation value of the first CQI
  • the terminal increases the compensation value of the first CQI.
  • the compensation value of the first CQI can be appropriately reduced. If the data reception is incorrect, for example, multiple feedback results indicate that the data reception is incorrect, it means that the first CQI is incorrect.
  • One CQI may be on the high side, and in this case the compensation value of the first CQI can be increased.
  • the terminal adjusts the compensation value of the first CQI through the feedback result of data reception, so that the network side device adjusts the first CQI based on the adjusted compensation value reported by the terminal, ensuring that the network side device can handle the adjustment by itself
  • the relationship between the final first CQI and the actually received precoding is thus ensured by the network side device for accurate scheduling of the terminal.
  • Figure 3 is a flow chart of another CQI transmission method provided by an embodiment of the present application. As shown in Figure 3, the method includes the following steps:
  • Step 301 The network side device receives the first CQI reported by the terminal.
  • the first CQI is the CQI calculated by the terminal based on the first precoding, RI and CRI;
  • the first condition includes any of the following:
  • the terminal is configured with a target high-layer parameter, and the target high-layer parameter is used to instruct the terminal to use the first precoding to calculate the first CQI;
  • the terminal receives the first instruction information sent by the network side device, and the first instruction information is used to instruct the terminal to use the first precoding to calculate the first CQI;
  • the terminal performs channel state information CSI compression based on the artificial intelligence AI coding model
  • the terminal uses an AI codebook
  • the terminal is not configured with an AI decoding model
  • the terminal is configured with an AI decoding model, and the AI decoding model is not associated with the network side device.
  • the first precoding includes any of the following:
  • Original precoding which is precoding without orthogonal basis projection.
  • the first CQI is a CQI calculated by the terminal based on the second precoding, the RI and the CRI.
  • the second precoding is orthogonal basis projected precoding.
  • the method also includes:
  • the network side device receives the compensation information of the first CQI reported by the terminal; or,
  • the network side device receives the model identifier of the first target AI coding model used reported by the terminal, and the model identifier is used to determine the compensation information of the first CQI corresponding to the first target AI coding model.
  • the network side device receives the compensation information of the first CQI reported by the terminal, including any one of the following: :
  • the network side device receives the loss ratio or loss level of the second precoding matrix relative to the first precoding matrix reported by the terminal, and the first precoding matrix is the precoding matrix input to the AI coding model, so The second precoding matrix is a precoding matrix output by the AI decoding model;
  • the network side device receives the compensation value of the first CQI reported by the terminal.
  • the method further includes:
  • the network side device adds the compensation value based on the first CQI.
  • the network side device receives the compensation information of the first CQI reported by the terminal, including:
  • the network side device receives the second target AI coding model reported by the terminal and the compensation information of the first CQI corresponding to the second target AI coding model.
  • the second target AI coding model is switched by the terminal.
  • the network side device receives the second target AI coding model reported by the terminal and the compensation information of the first CQI corresponding to the second target AI coding model, including:
  • the network side device receives the second target AI coding model and first information reported by the terminal.
  • the first information includes the compensation information of the first CQI corresponding to the second target AI coding model and the The model identifier of the second target AI encoding model.
  • the method before the network side device receives the compensation information of the first CQI reported by the terminal, the method further includes:
  • the network side device sends second instruction information to the terminal, where the second instruction information is used to instruct the terminal to report the compensation information of the first CQI when the AI coding model used is switched.
  • the network side device receives the compensation information of the first CQI reported by the terminal, including:
  • the network side device receives the CSI reported by the terminal, and the CSI carries compensation information of the first CQI.
  • the method further includes:
  • the network side device sends third indication information to the terminal, where the third indication information is used to instruct the CSI reported by the terminal to carry the compensation information of the first CQI.
  • the network side device receives the first CQI reported by the terminal, including:
  • the network side device receives the first CQI reported by the terminal and the channel characteristic information generated by the AI coding model.
  • the terminal when the terminal meets the above first condition, uses the first precoding, RI and CRI to calculate the first CQI and report the first CQI to the network side device, so that the network side device can process the relationship between the first CQI and the actually received precoding by itself, thereby ensuring accurate scheduling of the terminal by the network side device.
  • the CQI transmission method provided by the embodiment of the present application is applied to network side equipment, corresponding to the above-mentioned CQI transmission method applied to the terminal side.
  • the relevant concepts and specific implementation processes involved in the embodiment of the present application can be Referring to the description in the method embodiment shown in FIG. 2 above, no details will be described again in the embodiment of this application.
  • the execution subject may be a CQI transmission device.
  • a CQI transmission device performing a CQI transmission method is used as an example to illustrate the CQI transmission device provided by the embodiment of the present application.
  • FIG 4 is a structural diagram of a CQI transmission device provided by an embodiment of the present application.
  • the CQI transmission device 400 includes:
  • Obtaining module 401 configured to obtain a first CQI, where, if the first condition is met, the first CQI is calculated by the device based on the first precoding, the rank indicator RI and the channel state information reference signal indicator CRI. CQI;
  • the reporting module 402 is used to report the first CQI to the network side device
  • the first condition includes at least one of the following:
  • the device is configured with a target high-layer parameter, and the target high-layer parameter is used to instruct the device to use the first precoding to calculate the first CQI;
  • the device receives first indication information sent by a network side device, where the first indication information is used to instruct the device to use the first precoding to calculate the first CQI;
  • the device performs channel state information CSI compression based on the artificial intelligence AI coding model
  • the device uses an AI codebook
  • the device is not configured with an AI decoding model
  • the device is configured with an AI decoding model, and the AI decoding model is not associated with the network side device.
  • the first precoding includes any of the following:
  • Original precoding which is precoding without orthogonal basis projection.
  • the first CQI is a CQI calculated by the device based on the second precoding, the RI and the CRI.
  • the second precoding is orthogonal basis projected precoding.
  • reporting module 402 is also used to:
  • the compensation information includes a CQI impact factor or a precoding impact factor.
  • the reporting module 402 is also configured to perform any of the following:
  • the first precoding matrix is a precoding matrix input to the AI coding model
  • the second precoding matrix is a precoding matrix output by the AI decoding model
  • reporting module 402 is also used to:
  • the device When the AI coding model used is switched, the device reports the compensation information of the first CQI to the network side device.
  • reporting module 402 is also used to:
  • the device When the device switches to using the second target AI coding model, the device sends the second target AI coding model and the compensation of the first CQI corresponding to the second target AI coding model to the network side device. information.
  • reporting module 402 is also used to:
  • the second target AI coding model and first information to the network side device respectively, where the first information includes the compensation information of the first CQI corresponding to the second target AI coding model and the second The model identifier of the target AI encoding model.
  • the device also includes:
  • a receiving module configured to receive second indication information sent by the network side device, where the second indication information is used to instruct the device to report the compensation information of the first CQI when switching the AI coding model used;
  • the reporting module 402 is also configured to: based on the second indication information, when the device switches the AI coding model used, report the compensation information of the CQI to the network side device.
  • reporting module 402 is also used to:
  • the CSI Report the CSI to the network side device, where the CSI carries compensation information of the first CQI.
  • the receiving module is also used to:
  • the reporting module 402 is further configured to: report CSI to the network side device based on the third indication information, and the CSI carries the compensation information of the first CQI.
  • the device also includes:
  • An adjustment module configured to adjust the compensation information of the first CQI based on a feedback result of data reception, where the feedback result of data reception includes correct data reception or incorrect data reception.
  • the adjustment module is also used to:
  • the compensation value of the first CQI is increased.
  • reporting module 402 is also used to:
  • the device when the first condition is met, uses the first precoding, RI and CRI to to calculate the first CQI and report the first CQI to the network side device, and then the device can calculate the first CQI that matches the reported precoding, ensuring that the network side device can process the first CQI by itself and the actual reception precoding relationship to ensure accurate scheduling of the device by the network side device.
  • the CQI transmission device 400 in the embodiment of the present application may be an electronic device, such as an electronic device with an operating system, or may be a component in the electronic device, such as an integrated circuit or chip.
  • the electronic device may be a terminal or other devices other than the terminal.
  • terminals may include but are not limited to the types of terminals 11 listed above, and other devices may be servers, network attached storage (Network Attached Storage, NAS), etc., which are not specifically limited in the embodiment of this application.
  • the CQI transmission device 400 provided by the embodiment of the present application can implement each process implemented by the terminal in the method embodiment described in Figure 2, and achieve the same technical effect. To avoid duplication, details will not be described here.
  • the CQI transmission device 500 includes:
  • the receiving module 501 is used to receive the first CQI reported by the terminal;
  • the first CQI is the CQI calculated by the terminal based on the first precoding, RI and CRI;
  • the first condition includes any of the following:
  • the terminal is configured with a target high-layer parameter, and the target high-layer parameter is used to instruct the terminal to use the first precoding to calculate the first CQI;
  • the terminal receives first indication information sent by the device, where the first indication information is used to instruct the terminal to use the first precoding to calculate the first CQI;
  • the terminal performs channel state information CSI compression based on the artificial intelligence AI coding model
  • the terminal uses an AI codebook
  • the terminal is not configured with an AI decoding model
  • the terminal is configured with an AI decoding model, and the AI decoding model is not associated with the network side device.
  • the first precoding includes any of the following:
  • Original precoding which is precoding without orthogonal basis projection.
  • the first CQI is a CQI calculated by the terminal based on the second precoding, the RI and the CRI.
  • the second precoding is orthogonal basis projected precoding.
  • the receiving module 501 is also used to:
  • the interface The collection module 501 is also used to perform any of the following:
  • the first precoding matrix is the precoding matrix input to the AI coding model.
  • the second precoding matrix The matrix is the precoding matrix output by the AI decoding model;
  • the device also includes:
  • a processing module configured to add the compensation value based on the first CQI.
  • the device also includes:
  • a sending module configured to send second indication information to the terminal, where the second indication information is used to instruct the terminal to report the compensation information of the first CQI when the AI coding model used is switched.
  • the receiving module 501 is also used to:
  • the sending module is also used to:
  • the receiving module 501 is also used to:
  • the device receives the first CQI calculated by the terminal based on the first precoding, RI and CRI when the first condition is met, thereby ensuring that the device can independently process the first CQI and actual reception. precoding relationship to ensure accurate scheduling of the terminal by the device.
  • the CQI transmission device 500 provided by the embodiment of the present application can implement each process implemented by the network side device in the method embodiment described in Figure 3, and achieve the same technical effect. To avoid duplication, the details will not be described here.
  • this embodiment of the present application also provides a communication device 600, which includes a processor 601 and a memory 602.
  • the memory 602 stores programs or instructions that can be run on the processor 601, for example.
  • the communication device 600 is a terminal, when the program or instruction is executed by the processor 601, each step of the method embodiment described in Figure 2 is implemented, and the same technical effect can be achieved.
  • the communication device 600 is a network-side device, when the program or instruction is executed by the processor 601, each step of the method embodiment described in FIG. 3 is implemented, and the same technical effect can be achieved. To avoid duplication, the details will not be described here.
  • An embodiment of the present application also provides a terminal, including a processor and a communication interface.
  • the processor is configured to obtain a first CQI, where, if the first condition is met, the first CQI is the device based on the first CQI. CQI calculated by precoding, RI and CRI; the communication interface is used to report the first CQI to the network side device.
  • This terminal embodiment corresponds to the above-mentioned terminal-side method embodiment.
  • Each implementation process and implementation manner 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 hardware structure of a terminal that implements an embodiment of the present application.
  • the terminal 700 includes but is not limited to: radio frequency unit 701, network module 702, audio output unit 703, input At least part of the unit 704, the sensor 705, the display unit 706, the user input unit 707, the interface unit 708, the memory 709, the processor 710, and the like.
  • the terminal 700 may also include a power supply (such as a battery) that supplies power to various components.
  • the power supply may be logically connected to the processor 710 through a power management system, thereby managing charging, discharging, and power consumption through the power management system. Management and other functions.
  • the terminal structure shown in FIG. 7 does not constitute a limitation on the terminal.
  • the terminal may include more or fewer components than shown in the figure, or some components may be combined or arranged differently, which will not be described again here.
  • the input unit 704 may include a graphics processing unit (Graphics Processing Unit, GPU) 7041 and a microphone 7042.
  • the graphics processor 7041 is responsible for the image capture device (GPU) in the video capture mode or the image capture mode. Process the image data of still pictures or videos obtained by cameras (such as cameras).
  • the display unit 706 may include a display panel 7061, which may be configured in the form of a liquid crystal display, an organic light emitting diode, or the like.
  • the user input unit 707 includes a touch panel 7071 and at least one of other input devices 7072 .
  • Touch panel 7071 also called 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 physical keyboards, function keys (such as volume control keys, switch keys, etc.), trackballs, mice, and joysticks, which will not be described again here.
  • the radio frequency unit 701 after receiving downlink data from the network side device, can transmit it to the processor 710 for processing; in addition, the radio frequency unit 701 can send uplink data to the network side device.
  • the radio frequency unit 701 includes, but is not limited to, an antenna, amplifier, transceiver, coupler, low noise amplifier, duplexer, etc.
  • Memory 709 may be used to store software programs or instructions as well as 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 instructions required for at least one function (such as a sound playback function, Image playback function, etc.) etc.
  • memory 709 may include volatile memory or non-volatile memory, or memory 709 may include both volatile and non-volatile memory.
  • non-volatile memory can be read-only memory (Read-Only Memory, ROM), programmable read-only memory (Programmable ROM, PROM), erasable programmable read-only memory (Erasable PROM, EPROM), electrically removable memory. Erase programmable read-only memory (Electrically EPROM, EEPROM) or flash memory.
  • Volatile memory can be random access memory (Random Access Memory, RAM), static random access memory (Static RAM, SRAM), dynamic random access memory (Dynamic RAM, DRAM), synchronous dynamic random access memory (Synchronous DRAM, SDRAM), double data rate synchronous dynamic random access memory (Double Data Rate SDRAM, DDRSDRAM), enhanced synchronous dynamic random access memory (Enhanced SDRAM, ESDRAM), synchronous link dynamic random access memory (Synch link DRAM) , SLDRAM) and direct memory bus random access memory (Direct Rambus RAM, DRRAM).
  • RAM Random Access Memory
  • SRAM static random access memory
  • DRAM dynamic random access memory
  • DRAM synchronous dynamic random access memory
  • SDRAM double data rate synchronous dynamic random access memory
  • Double Data Rate SDRAM Double Data Rate SDRAM
  • DDRSDRAM double data rate synchronous dynamic random access memory
  • Enhanced SDRAM, ESDRAM enhanced synchronous dynamic random access memory
  • Synch link DRAM synchronous link dynamic random access memory
  • SLDRAM direct memory bus
  • the processor 710 may include one or more processing units; optionally, the processor 710 integrates an application processor and a modem processor, where the application processor mainly handles operations related to the operating system, user interface, application programs, etc., Modem processors mainly process wireless communication signals, such as baseband processors. It can be understood that the above-mentioned modem processor may not be integrated into the processor 710.
  • the processor 710 is used to obtain the first CQI, where, if the first condition is met, the first CQI is the CQI calculated by the device based on the first precoding, RI and CRI;
  • Radio frequency unit 701 configured to report the first CQI to the network side device
  • the first condition includes at least one of the following:
  • the terminal is configured with a target high-layer parameter, and the target high-layer parameter is used to instruct the terminal to use the first precoding to calculate the first CQI;
  • the terminal receives the first instruction information sent by the network side device, and the first instruction information is used to instruct the terminal to use the first precoding to calculate the first CQI;
  • the terminal performs channel state information CSI compression based on the artificial intelligence AI coding model
  • the terminal uses an AI codebook
  • the terminal is not configured with an AI decoding model
  • the terminal is configured with an AI decoding model, and the AI decoding model is not associated with the network side device.
  • the terminal when the first condition is met, calculates the first CQI based on the first precoding, RI and CRI, reports the first CQI to the network side device, and then uses the AI coding model in the terminal
  • the terminal reports the first CQI calculated by the first precoding
  • the network-side device can process the first CQI and the CQI recovered through the AI decoding model by itself. Precoding relationship to ensure accurate scheduling of terminals by network side equipment and avoid transmission errors.
  • terminal 700 provided by the embodiment of the present application can implement each process of the method embodiment described in Figure 2 and achieve the same technical effect. To avoid duplication, the details will not be described here.
  • An embodiment of the present application also provides a network-side device, including a processor and a communication interface.
  • the communication interface is used to receive the first CQI reported by the terminal; wherein, when the first condition is met, the first CQI is The CQI calculated by the terminal based on the first precoding, RI and CRI.
  • This network-side device embodiment corresponds to the above-mentioned network-side device method embodiment.
  • Each implementation process and implementation manner of the above-mentioned method embodiment can be applied to this network-side device embodiment, and can achieve the same technical effect.
  • the embodiment of the present application also provides a network side device.
  • the network side device 800 includes: an antenna 81 , a radio frequency device 82 , a baseband device 83 , a processor 84 and a memory 85 .
  • the antenna 81 is connected to the radio frequency device 82 .
  • the radio frequency device 82 receives information through the antenna 81 and sends the received information to the baseband device 83 for processing.
  • the baseband device 83 processes the information to be sent and sends it to the radio frequency device 82.
  • the radio frequency device 82 processes the received information and then sends it out through the antenna 81.
  • the method performed by the network side device in the above embodiment can be implemented in the baseband device 83, which includes a baseband processor.
  • the baseband device 83 may include, for example, at least one baseband board on which multiple chips are disposed, as shown in FIG. Program to perform the network device operations shown in the above method embodiments.
  • the network side device may also include a network interface 86, which is, for example, a common public wireless interface. public radio interface (CPRI).
  • a network interface 86 which is, for example, a common public wireless interface. public radio interface (CPRI).
  • CPRI public radio interface
  • the network side device 800 in this embodiment of the present invention also includes: instructions or programs stored in the memory 85 and executable on the processor 84.
  • the processor 84 calls the instructions or programs in the memory 85 to execute the various operations shown in Figure 5. The method of module execution and achieving the same technical effect will not be described in detail here to avoid duplication.
  • Embodiments of the present application also provide a readable storage medium.
  • Programs or instructions are stored on the readable storage medium.
  • the program or instructions are executed by a processor, each process of the method embodiment described in Figure 2 is implemented, or Each process of the method embodiment described in Figure 3 above can achieve the same technical effect. To avoid repetition, it will not be described again here.
  • the processor is the processor in the terminal described in the above embodiment.
  • the readable storage medium includes computer readable storage media, such as computer read-only memory ROM, random access memory RAM, magnetic disk or optical disk, etc.
  • An embodiment of the present application further provides a chip.
  • the chip includes a processor and a communication interface.
  • the communication interface is coupled to the processor.
  • the processor is used to run programs or instructions to implement the method described in Figure 2.
  • chips mentioned in the embodiments of this application may also be called system-on-chip, system-on-a-chip, system-on-chip or system-on-chip, etc.
  • Embodiments of the present application further provide a computer program/program product.
  • the computer program/program product is stored in a storage medium.
  • the computer program/program product is executed by at least one processor to implement the method described in Figure 2 above.
  • Each process of the embodiment, or each process of implementing the above method embodiment described in Figure 3, can achieve the same technical effect. To avoid repetition, it will not be described again here.
  • Embodiments of the present application also provide a communication system, including: a terminal and a network-side device.
  • the terminal can be used to perform the steps of the method described in Figure 2.
  • the network-side device can be used to perform the steps of the method described in Figure 3. step.
  • the methods of the above embodiments can be implemented by means of software plus the necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is better. implementation.
  • the technical solution of the present application can be embodied in the form of a computer software product that is essentially or contributes to the existing technology.
  • the computer software product is stored in a storage medium. (such as ROM/RAM, magnetic disk, optical disk), including a number of instructions to cause a terminal (which can be a mobile phone, computer, server, air conditioner, or network equipment, etc.) to execute the method described in various embodiments of this application.

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Abstract

La présente demande relève du domaine technique des communications et divulgue un procédé et un appareil de transmission de CQI, un terminal et un dispositif côté réseau. Le procédé de transmission de CQI d'un mode de réalisation de la présente demande comprend les étapes suivantes : un terminal acquiert un premier CQI, de sorte que lorsqu'une première condition est satisfaite, le premier CQI soit un CQI calculé par le terminal sur la base d'un premier précodage, d'un RI et d'un CRI ; le terminal rapporte le premier CQI à un dispositif côté réseau. La première condition comprend au moins l'un des éléments suivants : le terminal est configuré avec un paramètre de haut niveau cible, le paramètre de haut niveau cible étant utilisé pour ordonner au terminal d'utiliser le premier précodage pour calculer le premier CQI ; le terminal reçoit de premières informations d'instruction, les premières informations d'instruction étant utilisées pour ordonner au terminal d'utiliser le premier précodage pour calculer le premier CQI ; le terminal effectue une compression d'informations d'état de canal (CSI) sur la base d'un modèle de codage d'IA ; le terminal utilise un livre de codes d'IA ; le terminal n'est pas configuré avec un modèle de décodage d'IA ; et le terminal est configuré avec un modèle de décodage d'IA, le modèle de décodage d'IA n'étant pas associé au dispositif côté réseau.
PCT/CN2023/118440 2022-09-15 2023-09-13 Procédé et appareil de transmission de cqi, terminal et dispositif côté réseau Ceased WO2024055974A1 (fr)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2025209263A1 (fr) * 2024-04-02 2025-10-09 维沃移动通信有限公司 Procédé et appareil de transmission d'informations et dispositif

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112514275A (zh) * 2018-07-27 2021-03-16 Lg 电子株式会社 用于在无线通信系统中报告信道状态信息的方法和装置
WO2021062875A1 (fr) * 2019-10-04 2021-04-08 Qualcomm Incorporated Application d'une restriction de sous-ensemble de répertoire de codes à un indicateur de matrice de précodage et une indication de qualité de canal pour des informations d'état de canal de type ii
US20210195462A1 (en) * 2019-12-19 2021-06-24 Qualcomm Incorporated Configuration of artificial intelligence (ai) modules and compression ratios for user-equipment (ue) feedback
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
CN112514275A (zh) * 2018-07-27 2021-03-16 Lg 电子株式会社 用于在无线通信系统中报告信道状态信息的方法和装置
WO2021062875A1 (fr) * 2019-10-04 2021-04-08 Qualcomm Incorporated Application d'une restriction de sous-ensemble de répertoire de codes à un indicateur de matrice de précodage et une indication de qualité de canal pour des informations d'état de canal de type ii
US20210195462A1 (en) * 2019-12-19 2021-06-24 Qualcomm Incorporated Configuration of artificial intelligence (ai) modules and compression ratios for user-equipment (ue) feedback
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

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
DEUTSCHE TELEKOM: "Use cases for AI/ML in RAN and potential benefits", 3GPP DRAFT; R3-206198, 3RD GENERATION PARTNERSHIP PROJECT (3GPP), MOBILE COMPETENCE CENTRE ; 650, ROUTE DES LUCIOLES ; F-06921 SOPHIA-ANTIPOLIS CEDEX ; FRANCE, vol. RAN WG3, no. E-meeting; 20201102 - 20201112, 22 October 2020 (2020-10-22), Mobile Competence Centre ; 650, route des Lucioles ; F-06921 Sophia-Antipolis Cedex ; France , XP051941655 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2025209263A1 (fr) * 2024-04-02 2025-10-09 维沃移动通信有限公司 Procédé et appareil de transmission d'informations et dispositif

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