Cqi determination method, device, medium, program, and product
By determining channel scenario parameter values through channel estimation and channel parameters, and combining SNR and MI mapping models, the target CQI can be quickly determined. This solves the problems of computational complexity and poor adaptability in existing technologies, and achieves efficient and accurate determination of CQI.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BEIJING SPREADTRUM HI TECH COMM TECH CO LTD
- Filing Date
- 2026-01-27
- Publication Date
- 2026-06-02
AI Technical Summary
In existing technologies, highly reliable LQM determination schemes are computationally complex and a single LQM-CQI mapping relationship cannot cover all channel scenarios, resulting in low CQI acquisition accuracy and efficiency.
Channel estimation is performed by receiving downlink reference signals sent by the base station to determine channel state information. Channel scenario parameter values are constructed using channel parameter estimation information, and the target CQI is determined in multiple channel quality information lookup tables. The signal-to-noise ratio (SNR) is calculated by combining PMI, channel and noise estimation information, and the weighted mutual information (WMI) is quickly determined using the SNR and MI mapping model, thereby determining the target CQI.
It improves the accuracy and efficiency of CQI determination, adapts to different channel scenarios, avoids complex calculations, and quickly matches the current channel quality status.
Smart Images
Figure CN122137430A_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the field of wireless communication technology, and in particular to a CQI determination method, apparatus, medium, program, and product. Background Technology
[0002] In downlink transmission of wireless communication, terminal devices need to report Channel Quality Index (CQI) to the base station so that the base station can determine the current channel conditions and select appropriate transmission mode, modulation mode and coding rate for downlink data transmission.
[0003] In related technologies, by establishing a relationship between Link Quality Metric (LQM) and CQI mapping, the direct mapping of CQI can be achieved after determining LQM.
[0004] However, in related technologies, highly reliable LQM determination schemes are not only computationally complex, but also the single LQM and CQI mapping relationship cannot fully characterize the uncertainty of the communication link, which leads to low accuracy and efficiency in CQI acquisition. Summary of the Invention
[0005] This disclosure was made in view of the above-mentioned problems. This disclosure provides a method, apparatus, medium, procedure and product for determining CQI, which improves the efficiency and accuracy of CQI determination.
[0006] According to a first aspect of this disclosure, a CQI determination method is provided, the method being applied to a user terminal, comprising:
[0007] The system receives downlink reference signals transmitted by the base station and performs channel estimation based on the downlink reference signals to obtain channel state information. The channel state information includes channel parameter estimation information, precoding matrix identifier (PMI) estimation information, channel estimation information, and noise estimation information. Based on the channel parameter estimation information, the channel scenario parameter values are determined, and in the candidate channel quality information lookup tables of multiple channel scenarios, the target channel quality information lookup table corresponding to the channel scenario parameter values and the current modulation and coding scheme is determined. The candidate channel quality information lookup table includes multiple channel quality indices (CQIs) under different modulation and coding schemes, as well as a weighted mutual information (WMI) threshold associated with each CQI. WMI is used to characterize the degree of information correlation between the modulated signal bits at the transmitting end and the demodulated signal bits at the receiving end in a channel environment with inter-flow interference. Based on PMI estimation information, channel estimation information, and noise estimation information, the signal-to-noise ratio (SNR) is determined, and based on the SNR and the mapping model of SNR and mutual information (MI), the WMI corresponding to each CQI is determined. The target CQI is determined based on the WMI corresponding to each CQI and the WMI threshold associated with each CQI in the target channel quality information lookup table.
[0008] According to a second aspect of this disclosure, a network device is provided, the network device including a memory, a processor, and a computer program stored in the memory, the processor executing the computer program to implement the method of the first aspect.
[0009] According to a third aspect of this disclosure, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the method described in the first aspect.
[0010] According to a fourth aspect of this disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the method described in the first aspect.
[0011] The CQI determination method, device, medium, program, and product provided in this disclosure determine channel scenario parameter values characterizing the channel scenario type based on channel parameter estimation information extracted from the downlink reference signal, and determine a target channel quality information lookup table that conforms to the current modulation and coding scheme and channel scenario type. This solves the problem of poor adaptability of traditional single channel quality lookup tables to different scenarios, thereby improving the accuracy of the determined CQI. At the same time, the SNR is calculated based on PMI, channel and noise estimation information, and the weighted mutual information value corresponding to each CQI is obtained through the SNR and MI mapping model. Then, the target CQI is determined by comparing the weighted mutual information threshold associated with each CQI in the target channel quality information lookup table that matches the current scenario. Without the need for complex calculation methods, the MI used to characterize the channel quality status can be quickly determined through the mapping model between SNR and MI, so as to quickly determine the target CQI in the target channel quality information lookup table that matches the current scenario.
[0012] It should be understood that both the foregoing general description and the following detailed description are exemplary and intended to provide further illustration of the claimed technology. Attached Figure Description
[0013] The above and other objects, features, and advantages of this disclosure will become more apparent from the more detailed description of the embodiments thereof in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of this disclosure and form part of the specification. They are used together with the embodiments of this disclosure to explain the disclosure and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.
[0014] Figure 1This is a schematic diagram illustrating an application scenario of a CQI determination scheme according to an embodiment of this disclosure.
[0015] Figure 2 This is a flowchart of a CQI determination method according to an embodiment of this disclosure.
[0016] Figure 3 This is a schematic diagram illustrating the target mapping relationship between multiple CQI BLERs and WMIs within a preset simulation SNR range, according to an embodiment of this disclosure.
[0017] Figure 4 This is a schematic diagram illustrating the relationship between TP and preset simulation SNR range under different CQI conditions according to an embodiment of this disclosure.
[0018] Figure 5 This is a schematic diagram of the SNR-AMI relationship curve, representing a coefficient fitting result and a Monte Carlo simulation result according to an embodiment of this disclosure.
[0019] Figure 6 This is a schematic block diagram of the functional modules of the CQI determination device according to an embodiment of the present disclosure.
[0020] Figure 7 This is a schematic diagram of a computer program product according to an embodiment of the present disclosure.
[0021] Figure 8 This is a hardware block diagram of an electronic device according to an embodiment of the present disclosure. Detailed Implementation
[0022] To make the objectives, technical solutions, and advantages of this disclosure more apparent, exemplary embodiments according to this disclosure will now be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this disclosure, and not all embodiments of this disclosure. It should be understood that this disclosure is not limited to the exemplary embodiments described herein.
[0023] In downlink transmission of wireless communication, after determining the LQM used to characterize the channel link quality, the user terminal can query the target CQI corresponding to the determined LQM according to the pre-constructed mapping relationship between LQM and CQI, and then report the target CQI to the base station for the base station to perform downlink data transmission based on the target CQI. Among them, LQM can be a signal-to-noise ratio (SNR) type LQM (such as instantaneous SNR, exponential effective SNR mapping (EESM) or mutual information effective SNR mapping (MIESM) etc.), or a bit error rate (BER) type LQM (such as raw bit error rate (RBER) etc.).
[0024] However, the CQI determination schemes provided in related technologies have several drawbacks. First, the calculation of high-reliability LQM often requires Monte Carlo integration, leading to high complexity in determining the LQM. Furthermore, commonly used LQMs lack a unified theoretical closed-form solution. Even with simplified LQM determination schemes through approximation, the complexity and reliability of the determined LQM vary significantly across different scenarios. Second, channels in real-world communication environments are dynamically changing (e.g., obstruction by tall buildings in cities, Doppler effects during high-speed movement, and differences in channel attenuation across different frequency bands). Under different environments, the actual channel quality and optimal transmission strategy corresponding to the same LQM value should also differ. Therefore, the single LQM-CQI mapping relationship provided in related technologies cannot cover the needs of all channel scenarios, resulting in poor reliability of the determined CQI.
[0025] To address the aforementioned problems, this disclosure provides a CQI determination scheme. Figure 1 A schematic diagram illustrating a CQI determination application scenario according to an exemplary embodiment of this disclosure is shown. Figure 1 As shown, the implementation scenario 100 includes a base station 101 and a user terminal 102. The base station 101 is a set of network devices deployed by the communication operator to enable the user terminal to access the network wirelessly. The user terminal 102 is an electronic device with wireless communication capabilities, such as a mobile phone, drone, wearable device, laptop, or IoT device.
[0026] The base station 101 and the user terminal 102 can establish a wireless connection so that the user terminal 102 can implement the CQI determination scheme provided in this embodiment. The base station 101 and the user terminal 102 can establish a wireless connection based on the 5G New Radio (NR) system or the 4G Long Term Evolution (LTE) system.
[0027] Figure 2 A flowchart illustrating an exemplary embodiment of the present disclosure of a CQI determination method is shown. The CQI determination method is applied in a user terminal, such as... Figure 2 As shown, the method in this embodiment of the disclosure may include: Step S201: Receive the downlink reference signal sent by the base station, and perform channel estimation based on the downlink reference signal to obtain channel state information; The channel state information includes channel parameter estimation information, precoding matrix indicator (PMI) estimation information, channel estimation information, and noise estimation information. Step S202: Determine the channel scenario parameter values based on the channel parameter estimation information, and determine the target channel quality information lookup table corresponding to the channel scenario parameter values and the current modulation and coding scheme from the candidate channel quality information lookup tables of multiple channel scenarios. The candidate channel quality information lookup table includes multiple channel quality indices (CQIs) under different modulation and coding schemes, as well as a weighted mutual information (WMI) threshold associated with each CQI. WMI is used to characterize the degree of information correlation between the modulated signal bits at the transmitting end and the demodulated signal bits at the receiving end in a channel environment with inter-flow interference. Step S203: Based on PMI estimation information, channel estimation information and noise estimation information, determine the signal-to-noise ratio (SNR), and based on SNR, and the mapping model of SNR and mutual information (MI), determine the WMI corresponding to each CQI; Step S204: Determine the target CQI based on the WMI corresponding to each CQI and the WMI threshold associated with each CQI in the target channel quality information lookup table.
[0028] In summary, the CQI determination method provided in this disclosure determines the channel scenario parameter values characterizing the channel scenario type based on the channel parameter estimation information extracted from the downlink reference signal, and determines the target channel quality information lookup table that conforms to the current modulation and coding scheme and channel scenario type. This solves the problem of poor adaptability of the traditional single channel quality lookup table to different scenarios, thereby improving the accuracy of the determined CQI. At the same time, it calculates the SNR based on PMI, channel and noise estimation information, and obtains the weighted mutual information value corresponding to each CQI through the SNR and MI mapping model. Then, it determines the target CQI by comparing the weighted mutual information threshold associated with each CQI in the target channel quality information lookup table that matches the current scenario. This method does not require complex calculation methods but can quickly determine the MI used to characterize the channel quality status through the mapping model between SNR and MI, so as to quickly determine the target CQI in the target channel quality information lookup table that matches the current scenario.
[0029] The following are Figure 2 The specific implementation methods of each step in the illustrated embodiment are described in detail below: In step S201, the user terminal receives the downlink reference signal sent by the base station and performs channel estimation based on the downlink reference signal to obtain channel state information.
[0030] In this embodiment, the downlink reference signal may vary depending on the wireless communication system. For example, in a 4G LTE wireless communication system, the downlink reference signal may be a Common Reference Signal (CRS), and in a 5G NR wireless communication system, the downlink reference signal may be a Channel State Information Reference Signal (CSI-RS). The channel state information includes channel parameter estimation information, precoding matrix identifier PMI estimation information, channel estimation information, and noise estimation information. The channel estimation information is a set of raw quantized data used to describe the amplitude attenuation and phase change of the transmitted signal caused by the wireless channel under specific time-frequency resources and antenna dimensions. The channel parameter estimation information is a set of parameters extracted based on the channel estimation information to characterize the time-varying and multipath characteristics of the channel. The channel parameter estimation information includes delay spread, Doppler spread, and channel condition number.
[0031] In one optional implementation, the process by which the user terminal performs channel estimation based on the downlink reference signal to obtain channel state information includes: comparing the sequence of the downlink reference signal with the sequence of the ideal reference signal stored locally, and calculating the channel matrix (i.e., channel estimation information) through a channel estimation algorithm; then, collecting the power data of the received signal within the guard interval of the idle subcarrier without data transmission or the downlink reference signal, calculating the power or variance of the noise, and forming noise estimation information; further, determining the delay spread value, Doppler spread value, and channel condition number based on the channel estimation information to obtain channel parameter estimation information; finally, traversing the preset precoding matrix codebook, combining each precoding matrix with the channel estimation information to calculate the corresponding channel capacity or signal-to-noise ratio gain, and selecting the index corresponding to the precoding matrix with the optimal gain to generate precoding matrix identifier (PMI) estimation information; wherein, in this embodiment, the channel estimation algorithm can be least squares (LS) or minimum mean square error (MMSE), etc., and this embodiment does not limit it.
[0032] It should be noted that, in the embodiments of this disclosure, the differences in channel scenarios essentially stem from the differences in their temporal dispersion, frequency dispersion, and angular dispersion characteristics. Specifically, the temporal and frequency dispersions of the channel are determined by delay spread and Doppler spread, respectively, while the angular dispersion characteristics are jointly determined by the angular spreads of the azimuth and elevation angles of the transmitter (TX) and receiver (RX), manifested as the product of the array manifolds, and ultimately reflected in the spatial correlation of Multiple Input Multiple Output (MIMO). Therefore, the channel condition number, as an indicator of MIMO wireless channel quality or separability, is used to characterize the angular dispersion characteristics of the channel. In the field of communication, any communication channel characterizing its spatiotemporal-frequency characteristics... The model is: ;(Formula 1) In Formula 1, The time-varying frequency response matrix of the channel, For the first Complex gain coefficient of stripe diameter, Sampling time, For carrier frequency, Indicates TX azimuth angle and pitch angle The antenna array response, Indicates the RX azimuth angle and pitch angle The antenna array response, This is the delay spread value. This is the Doppler extension value.
[0033] Based on the above, the process by which the user terminal determines the delay spread, Doppler spread, and channel condition number based on channel estimation information includes: estimating the delay spread by performing an inverse Fourier transform on the channel estimation information in the frequency domain and calculating the statistics of the power delay spectrum; then estimating the Doppler spread by performing a Fourier transform on the channel estimation information in the time domain and analyzing the Doppler power spectrum; and finally, estimating the channel condition number by performing singular value decomposition on the channel matrix (i.e., the channel estimation information).
[0034] In step S202, the user terminal determines the channel scenario parameter value based on the channel parameter estimation information, and determines the target channel quality information lookup table corresponding to the channel scenario parameter value and the current modulation and coding scheme from the candidate channel quality information lookup tables of multiple channel scenarios.
[0035] In this embodiment of the disclosure, the channel scenario parameter value is used to characterize the quality of the channel condition. In order to efficiently characterize the channel condition based on the delay spread value, Doppler spread value and channel condition number in the channel parameter estimation information, the user terminal can pre-store the correspondence between the delay spread value, Doppler spread value and channel condition number into multiple delay spread value intervals and multiple delay spread levels, the correspondence between multiple Doppler spread value intervals and multiple Doppler spread levels, and the correspondence between multiple channel condition number intervals and multiple channel condition levels, to obtain a set of channel dispersion relations. This allows the channel scenario parameter value to be determined by looking up the corresponding relations after obtaining the channel parameter estimation information.
[0036] Optionally, the set of channel dispersion relations can be predetermined by the wireless communication service provider and synchronized to the user terminal.
[0037] For example, suppose the delay spread value is... There are 1 level, 2 levels of Doppler spread, and 3 levels of channel condition number. The set of channel dispersion relations is then determined by the number of levels. The middle can represent Channel scenarios: ;(Formula 2) In one optional implementation, the process by which the user terminal determines the channel scenario parameter value based on channel parameter estimation information includes: determining the delay spread level associated with the delay spread value interval to which the delay spread value belongs in the correspondence between multiple delay spread value intervals and multiple delay spread levels as the target delay spread level; then, determining the Doppler spread value level associated with the Doppler spread value interval to which the Doppler spread value belongs in the correspondence between multiple Doppler spread value intervals and multiple Doppler spread levels as the target Doppler spread value level; and further, determining the channel condition level associated with the channel condition number interval to which the channel condition number belongs in the correspondence between multiple channel condition number intervals and multiple channel condition levels as the target channel condition level; and further, determining the ternary array composed of the target delay spread level, the target Doppler spread value level, and the target channel condition level as the channel scenario parameter value. By partitioning the delay spread, Doppler spread, and channel condition number, each interval can be divided into different levels. The triplet composed of the delay spread level, Doppler spread level, and channel condition number level can be defined as a scenario parameter. This allows the user terminal to quickly determine the current channel scenario parameter value after obtaining the channel parameter estimation information.
[0038] Optionally, if the channel dispersion relation set is not synchronized to the user terminal by the wireless communication service provider, after obtaining the channel parameter estimation information, the user terminal can request the wireless communication service provider to return a determined channel scenario parameter value based on the channel parameter estimation information transmitted by the user terminal, based on the channel parameter estimation information transmitted by the user terminal. The process by which the wireless communication service provider determines the channel scenario parameter value based on the channel parameter estimation information can be referred to the above embodiments, and will not be elaborated here.
[0039] It should be noted that, in this embodiment of the disclosure, different coding and modulation schemes are provided in different wireless communication systems. Taking the 5G NR system as an example, the 5G NR system can provide four modulation and coding schemes, as shown in Tables 1 to 4. Tables 1 to 4 respectively show multiple CQIs (CQI indices) under the four modulation and coding schemes provided by the 5G NR system, as well as the correlation between the modulation mode, code rate, and spectral efficiency associated with each CQI. The modulation mode may include Quadrature Amplitude Modulation (QAM) and Quadrature Phase Shift Keying (QPSK). Keying (QPSK); In order to consider different channel conditions and different modulation and coding schemes and determine the CQI that is more suitable for the current communication scenario, the candidate channel quality information lookup table includes multiple channel quality indices (CQIs) under different modulation and coding schemes, as well as a WMI threshold associated with each CQI. WMI is used to characterize the degree of information correlation between the modulated signal bits at the transmitting end and the demodulated signal bits at the receiving end in a channel environment with inter-stream interference.
[0040] Table 1: Modulation and Coding Schemes for 5G NR Systems
[0041] Table 2: Modulation and Coding Schemes for 5G NR Systems
[0042] Table 3: Modulation and Coding Schemes for 5G NR Systems
[0043] Table 4: Modulation and Coding Schemes for 5G NR Systems
[0044] Optionally, in this embodiment of the disclosure, the wireless communication service provider may predetermine a lookup table of candidate channel quality information for multiple channel scenarios and synchronize the lookup table of candidate channel quality information for multiple channel scenarios to the user terminal through the base station.
[0045] In one optional implementation, the process by which the wireless communication service provider determines a lookup table of candidate channel quality information for multiple channel scenarios may include: obtaining the target mapping relationship between the block error rate (BLER) and the mean squared error (WMI) of multiple CQIs under each modulation and coding scheme of different channel scenarios within a preset simulated SNR range; determining the initial WMI of each CQI under each modulation and coding scheme of different channel scenarios based on the target mapping relationship and the BLER threshold under each modulation and coding scheme of different channel scenarios; and adjusting the initial WMI of each CQI under each modulation and coding scheme of different channel scenarios with the optimization objective of maximizing throughput (TP), thereby obtaining the WMI threshold of each CQI under each modulation and coding scheme of different channel scenarios. By obtaining the target mapping relationship between BLER and MI covering different channel scenarios and modulation and coding schemes through simulation, and ensuring the scenario adaptability of the finally determined MI threshold used for evaluating CQI based on the BLER threshold, the link transmission efficiency is further optimized by the MI adjustment with the objective of maximizing throughput, so as to achieve efficient resource utilization of the CQI determined based on the MI threshold of each CQI under each modulation and coding scheme of different channel scenarios during data transmission.
[0046] Among them, the initial WMI obtained from the simulation for: ;(Formula 3) In formula 3, This represents the initial WMI values corresponding to CQI1 through CQI15.
[0047] WMI threshold for each CQI for: ;(Formula 4) In formula 4, This represents the WMI thresholds corresponding to CQI1 through CQI15.
[0048] For example, such as Figure 3 As shown, Figure 3 This diagram illustrates the target mapping relationship between BLER and WMI of multiple CQIs within a preset simulated SNR range under a coding scheme for a channel scenario provided in this embodiment of the present disclosure. The horizontal axis represents WMI, and the vertical axis represents BLER. Figure 3 Each curve in the code corresponds to a CQI; for example... Figure 4 As shown, Figure 4 The diagram illustrates the relationship between TP and preset simulation SNR intervals under different CQIs provided in this embodiment of the present disclosure. During the simulation process, the optimization objective is to require that the envelope of the TP curve of the simulated CQI should be on the outermost side of the fixed CQI.
[0049] For example, taking a 5G NR system as an example, as shown in Table 5, Table 5 shows the WMI threshold for each CQI under four modulation and coding schemes in a channel scenario.
[0050] Table 5
[0051] In one optional implementation, before determining the target channel quality information lookup table corresponding to the channel scenario parameter values and the current modulation and coding scheme from the candidate channel quality information lookup tables of multiple channel scenarios, the user terminal may read the candidate channel quality information lookup tables of multiple channel scenarios that are stored in advance, so as to determine the relevant target channel quality information lookup table under the current scenario based on the candidate channel quality information lookup tables of multiple channel scenarios that are stored in advance in the user terminal.
[0052] Optionally, if the user terminal does not obtain the candidate channel quality information lookup table for multiple channel scenarios from the wireless communication service provider, the user terminal may request the wireless communication service provider to return a determined target channel quality information lookup table based on the channel scenario parameter values transmitted by the user terminal and the current modulation and coding scheme, according to the request from the base station.
[0053] It should be noted that in the embodiments disclosed herein, the current modulation and coding scheme is sent from the base station to the user terminal after the user terminal and the base station establish a wireless communication link. For example, in a 5G NR system, the current modulation and coding scheme can be any one of the schemes in Tables 1-4.
[0054] In step S203, the user terminal determines the signal-to-noise ratio (SNR) based on the PMI estimation information, channel estimation information, and noise estimation information, and determines the WMI corresponding to each CQI based on the SNR and the mapping model of SNR and mutual information (MI).
[0055] In this embodiment of the disclosure, the mapping model between SNR and MI is a relationship model between SNR and SNR. The mapping model includes a first mapping model under conditions of no inter-flow interference and a second mapping model under conditions of inter-flow interference. The first and second mapping models are constructed based on a baseline mapping model of SNR and MI. In the baseline mapping model of SNR and MI, MI stands for Average Mutual Information (AMI). The baseline mapping model of SNR and MI is as follows: ;(Formula 5) In Formula 5, Indicates adoption Modulated average mutual information This indicates the order of the QAM, where M can take values of 4, 16, 64, 256, or 1024. Indicates SNR, and These are the fitting coefficients. The number of fitting coefficients can be determined based on actual needs, and this disclosure does not limit this number.
[0056] Among them, the The first data stream The SNR of each subcarrier is: ;(Formula 6) In formula 6, for The unit square, Indicates the opponent's formation Find the inverse and take the first... Line number Column elements, This is the equivalent channel estimation matrix. , For the first Channel estimation information for each subcarrier, This is the precoding matrix corresponding to the PMI. The precoding matrix corresponding to the PMI is obtained by querying the predefined codebook of the communication protocol based on the PMI estimation information. For noise variance, the power measurement value is determined based on noise estimation information.
[0057] Optionally, in this embodiment of the disclosure, in order to further ensure the accuracy of CQI under different modulation and coding schemes determined by the user terminal, the wireless service communication provider can determine different fitting coefficients for the modulation mode corresponding to each CQI.
[0058] In one optional implementation, the process by which the wireless service communicator determines different fitting coefficients for the modulation mode corresponding to each CQI includes: obtaining reference mapping relationship data of SNR and MI under various modulation modes through Monte Carlo simulation, and using a nonlinear least squares algorithm to minimize the mean square error between the fitted MI calculated by the SNR and MI benchmark mapping model based on the fitting coefficients and the reference MI in the reference mapping relationship data, thereby obtaining different fitting coefficients for the modulation mode corresponding to each CQI. By determining different fitting coefficients applied to the mapping model of SNR and mutual information for different modulation modes, the matching degree between the determined WMI corresponding to each CQI and the current communication scheme and communication scenario is further improved.
[0059] Example, fit coefficient for: ;(Formula 7) For example, as shown in Table 6, Table 6 illustrates the fitting coefficients for different QAM orders in a 5G NR system provided by embodiments of this disclosure. and The value.
[0060] Table 6
[0061] In Table 6, for 1024QAM, 256QAM and 64QAM, there are 4 fitting coefficients, where the first 4 rows are the values of fitting coefficient a and the last 4 rows are the values of fitting coefficient b. For 16QAM and 4QAM, there are 2 fitting coefficients, where the first 2 rows are the values of fitting coefficient a and the last 2 rows are the values of fitting coefficient b.
[0062] like Figure 5 As shown, Figure 5 This diagram illustrates the SNR-AMI relationship curve characterized by the coefficient fitting results and Monte Carlo simulation results provided in the embodiments of this disclosure. Figure 5 It can be seen that, under the modulation modes of 4QAM, 16QAM, 64QAM, 256QAM and 1024QAM, the relationship between SNR and AMI fitted by the method of this disclosure basically coincides with the relationship curve between SNR and AMI obtained by Monte Carlo simulation, indicating the reliability of the SNR to MI benchmark mapping model constructed in the embodiments of this disclosure.
[0063] It should be noted that, in this embodiment of the disclosure, the first mapping model constructed based on the baseline mapping model of SNR and MI is as follows: ;(Formula 8) In Formula 8, The bit MI value represents the value under conditions of no inter-stream interference, referring to the value under the condition of no inter-stream interference. The upper bound of the normalized bit MI in the modulation mode. and The content of the labels is the same.
[0064] The second mapping model is: ;(Formula 9) In Formula 9, This represents the bit MI value determined under inter-stream interference conditions. express The total MI value of each data stream Indicates removal The first data stream in the data stream After the data streams, the remaining ones The total MI value of each data stream, of which, ;(Formula 10) ;(Formula 11) In formulas 10 and 11, and They are respectively and The unit square, Indicates the removal of the first The equivalent channel estimation matrix of the data stream. for: ;(Formula 12) In Formula 12, Represents the precoding matrix corresponding to PMI Remove the first The matrix following the column.
[0065] It is understood that, in the embodiments of this disclosure, the process by which the user terminal determines the signal-to-noise ratio (SNR) based on PMI estimation information, channel estimation information, and noise estimation information may include: for each subcarrier of each data stream, obtaining the precoding matrix corresponding to the PMI by querying a predefined codebook of the communication protocol according to the PMI estimation information; then, determining the product of the precoding matrix corresponding to the PMI and the channel estimation information to obtain the equivalent channel estimation matrix; and determining the noise variance based on the power measurement value based on the noise estimation information; finally, inputting the equivalent channel estimation matrix and the noise variance into the SNR solution model to obtain the SNR of each subcarrier of each data stream, wherein the SNR solution model is the model represented by Equation 6.
[0066] In one optional implementation, in a scenario where the wireless service communication provider determines different fitting coefficients for the modulation mode corresponding to each CQI and synchronizes these different fitting coefficients with the user terminal, the user terminal, after determining the signal-to-noise ratio (SNR), can read a table showing the relationship between multiple modulation modes and fitting coefficients. After determining the SNR, the user terminal can directly and quickly determine the target fitting coefficients associated with the modulation mode corresponding to each CQI based on the table of relationships between multiple modulation modes and fitting coefficients stored in the user terminal, thereby improving the efficiency of determining the WMI corresponding to each CQI.
[0067] Optionally, if the different fitting coefficients of the modulation mode corresponding to each CQI are not synchronized to the user terminal by the wireless communication service provider, the user terminal can request the wireless communication service provider based on the base station after obtaining the signal-to-noise ratio to return the different fitting coefficients of the modulation mode corresponding to each CQI, so as to ensure the reliability of determining the target CQI.
[0068] In one optional implementation, the process by which the user terminal determines the WMI corresponding to each CQI based on the SNR and a mapping model of SNR and mutual information MI includes: searching for a target fitting coefficient associated with the modulation mode corresponding to each CQI in a table of multiple modulation modes and fitting coefficients; then, for each CQI, inputting the target fitting coefficient and SNR into a first mapping model to obtain a first MI associated with the modulation mode corresponding to the CQI; and inputting the target fitting coefficient and SNR into a second mapping model to obtain a second MI associated with the modulation mode corresponding to the CQI; and determining the WMI corresponding to the CQI based on the first MI and the second MI associated with the modulation mode corresponding to the CQI. On the one hand, for complex channel environments with inter-flow interference, mapping models for SNR and MI considering only inter-flow interference and mapping models for SNR and MI considering only the absence of inter-flow interference are constructed. By combining the MI determined by the two mapping models, the WMI corresponding to each CQI in the complex channel environment is comprehensively determined. This prevents resource waste caused by only considering inter-flow interference or resource over-division caused by not considering inter-flow interference, and can more accurately determine the WMI corresponding to each CQI. On the other hand, different fitting coefficients are determined in the mapping model of SNR and MI for the modulation mode corresponding to each CQI, which can further improve the matching degree between the determined WMI of each CQI and the current communication environment.
[0069] In one optional implementation, the process by which the user terminal determines the WMI corresponding to the CQI based on a first MI and a second MI associated with the modulation mode corresponding to the CQI includes: reading a first weight associated with a first mapping model and a second weight associated with a second mapping model; then, based on the first weight and the second weight, determining the weighted average between the first MI and the second MI associated with the modulation mode corresponding to the CQI to obtain the WMI corresponding to the CQI. The first weight and the second weight can be determined based on actual needs, and this disclosure does not limit this. By assigning different weights to the MIs determined when only inter-flow interference is considered and when only inter-flow interference is considered, and then performing a weighted average, the WMI corresponding to the CQI is obtained. Since the weight values can be determined based on the actual communication environment, the adaptability of the CQI's WMI to the current communication environment can be further determined.
[0070] The terminal device determines the weighted average between the first MI and the second MI, which are associated with the modulation mode corresponding to the CQI, based on the first weight and the second weight, to obtain the WMI corresponding to the CQI: ;(Formula 13) In Formula 13, As the first weight, It is the second weight.
[0071] In step S204, the user terminal determines the target CQI based on the WMI corresponding to each CQI and the WMI threshold associated with each CQI in the target channel quality information lookup table.
[0072] In this embodiment of the disclosure, the target CQI is the CQI that the user terminal needs to transmit to the base station. The base station can send data to the user terminal based on the modulation scheme, coding rate and spectral efficiency corresponding to the target CQI.
[0073] In one optional implementation, the user terminal determines the target CQI based on the WMI corresponding to each CQI and the WMI threshold associated with each CQI in the target channel quality information lookup table. This includes: for each CQI, if the WMI corresponding to the CQI is greater than the WMI threshold associated with the CQI in the target channel quality information lookup table, then the CQI is identified as a candidate CQI; then, if there are multiple candidate CQIs, the largest CQI among the multiple candidate CQIs is identified as the target CQI. Since a larger CQI indicates better downlink channel quality and supported transmission performance, when the WMI of multiple CQIs is greater than the WMI threshold associated with the CQI in the target channel quality information lookup table, the largest CQI is identified as the target CQI, so that the base station can fully utilize channel resources, thereby improving the transmission efficiency of downlink data.
[0074] Optionally, if there is only one candidate CQI, the candidate CQI is determined as the target CQI so that the base station can reliably transmit data to the user terminal.
[0075] An exemplary embodiment of this disclosure provides a CQI determination device, which can be a user terminal. Figure 6 A schematic block diagram of the functional modules of a CQI determination apparatus according to an exemplary embodiment of the present disclosure is shown. Figure 6 As shown, the CQI determining device 600 includes: The receiving module 601 is configured to receive downlink reference signals transmitted by the base station and perform channel estimation based on the downlink reference signals to obtain channel state information. The channel state information includes channel parameter estimation information, precoding matrix identifier (PMI) estimation information, channel estimation information, and noise estimation information. The first determining module 602 is configured to determine the channel scenario parameter value based on the channel parameter estimation information, and determine the target channel quality information lookup table corresponding to the channel scenario parameter value and the current modulation and coding scheme in the candidate channel quality information lookup table of multiple channel scenarios. The candidate channel quality information lookup table includes multiple channel quality indices (CQI) under different modulation and coding schemes, and a weighted mutual information (WMI) threshold associated with each CQI. The WMI is used to characterize the degree of information correlation between the modulated signal bits of the transmitting end and the demodulated signal bits of the receiving end in the inter-flow interference channel environment. The second determining module 603 is configured to determine the signal-to-noise ratio (SNR) based on PMI estimation information, channel estimation information, and noise estimation information, and to determine the WMI corresponding to each CQI based on the SNR and the mapping model of SNR and mutual information MI. The third determining module 604 is configured to determine the target CQI based on the WMI corresponding to each CQI and the WMI threshold associated with each CQI in the target channel quality information lookup table.
[0076] Optionally, the mapping model includes a first mapping model under conditions of no inter-flow interference and a second mapping model under conditions of inter-flow interference. The second determining module 603 is configured as follows: In the table showing the relationship between multiple modulation modes and fitting coefficients, find the target fitting coefficient associated with the modulation mode corresponding to each CQI; For each CQI, the target fitting coefficient and the SNR are input into the first mapping model to obtain a first MI associated with the modulation mode corresponding to the CQI; and the target fitting coefficient and the SNR are input into the second mapping model to obtain a second MI associated with the modulation mode corresponding to the CQI. Based on the first MI and the second MI associated with the modulation mode corresponding to the CQI, the WMI corresponding to the CQI is determined.
[0077] Optionally, the second determining module 603 is configured to: Read the first weight associated with the first mapping model, and the second weight associated with the second mapping model; Based on the first weight and the second weight, the weighted average between the first MI and the second MI associated with the modulation mode corresponding to the CQI is determined, and the WMI corresponding to the CQI is obtained.
[0078] Optional, such as Figure 6 As shown, the device further includes a reading module 605, configured to: The relationship table of the multiple modulation modes and fitting coefficients is read. The relationship table of the multiple modulation modes and fitting coefficients is obtained by Monte Carlo simulation to obtain reference mapping relationship data of SNR and MI under multiple modulation modes. The nonlinear least squares algorithm is used to determine the minimum mean square error between the fitted MI calculated by the SNR and MI benchmark mapping model according to the fitting coefficients and the reference MI in the reference mapping relationship data.
[0079] Optionally, the channel parameter estimation information includes delay spread, Doppler spread, and channel condition number, and the first determining module 602 is configured to: Among the correspondences between multiple delay spread value ranges and multiple delay spread levels, the delay spread level associated with the delay spread value range to which the delay spread value belongs is determined as the target delay spread level. Among the correspondences between multiple Doppler expansion value intervals and multiple Doppler expansion levels, the Doppler expansion value level associated with the Doppler expansion value interval to which the Doppler expansion value belongs is determined as the target Doppler expansion value level. Among the correspondences between multiple channel condition number intervals and multiple channel condition levels, the channel condition level associated with the channel condition number interval to which the channel condition number belongs is determined as the target channel condition level. The ternary array consisting of the target delay spread level, the target Doppler spread value level, and the target channel condition level is determined as the channel scenario parameter value.
[0080] Optionally, the third determining module 604 is configured to: For each CQI, if the WMI corresponding to the CQI is greater than the WMI threshold associated with the CQI in the target channel quality information lookup table, then the CQI is determined as a candidate CQI. When there are multiple candidate CQIs, the largest CQI among the multiple candidate CQIs is determined as the target CQI.
[0081] Optionally, the reading module 605 is further configured to: Read a pre-stored candidate channel quality information lookup table for multiple channel scenarios. The candidate channel quality information lookup table is obtained by acquiring the target mapping relationship between the block error rate (BLER) and the wMI (weighted index) of multiple CQIs under each modulation and coding scheme of different channel scenarios within a preset simulated SNR range. Based on the target mapping relationship and the BLER threshold under each modulation and coding scheme of different channel scenarios, determine the initial wMI of each CQI under each modulation and coding scheme of different channel scenarios. And, with the throughput TP (total throughput) as the optimization objective, adjust the initial wMI of each CQI under each modulation and coding scheme of different channel scenarios.
[0082] Exemplary embodiments of this disclosure also provide an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor. The memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to cause the electronic device to perform a method according to an embodiment of this disclosure.
[0083] Exemplary embodiments of this disclosure also provide a non-transitory computer-readable storage medium storing a computer program, wherein the computer program, when executed by a computer's processor, is used to cause the computer to perform a method according to embodiments of this disclosure.
[0084] like Figure 7 As shown, an exemplary embodiment of this disclosure also provides a computer program product 700, including a computer program 701, wherein the computer program, when executed by a computer's processor, is used to cause the computer to perform a method according to an embodiment of this disclosure.
[0085] refer to Figure 8 The present invention describes a structural block diagram of an electronic device 800 that can serve as a user terminal of the present disclosure, which is an example of a hardware device that can be applied to various aspects of the present disclosure. The electronic device is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.
[0086] like Figure 8As shown, the electronic device 800 includes a computing unit 801, which can perform various appropriate actions and processes based on a computer program stored in a read-only memory (ROM) 802 or a computer program loaded from a storage unit 808 into a random access memory (RAM) 803. The RAM 803 may also store various programs and data required for the operation of the electronic device 800. The computing unit 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.
[0087] Multiple components in electronic device 800 are connected to I / O interface 805, including: input unit 806, output unit 807, storage unit 808, and communication unit 809. Input unit 806 can be any type of device capable of inputting information to electronic device 800. Input unit 806 can receive input digital or character information and generate key signal inputs related to user settings and / or function control of electronic device. Output unit 807 can be any type of device capable of presenting information and may include, but is not limited to, a display, speaker, video / audio output terminal, vibrator, and / or printer. Storage unit 808 may include, but is not limited to, disks and optical discs. Communication unit 809 allows electronic device 800 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks, and may include, but is not limited to, modems, network cards, infrared communication devices, wireless communication transceivers, and / or chipsets, such as Bluetooth™ devices, WiFi devices, WiMax devices, cellular communication devices, and / or the like.
[0088] The computing unit 801 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 801 performs the various methods and processes described above. For example, in some embodiments, the methods of the exemplary embodiments of this disclosure can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 808. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 800 via ROM 802 and / or communication unit 809. In some embodiments, the computing unit 801 can be configured to perform the methods of the exemplary embodiments of this disclosure by any other suitable means (e.g., by means of firmware).
[0089] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.
[0090] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.
[0091] As used in this disclosure, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, device, and / or apparatus (e.g., disk, optical disk, memory, programmable logic device (PLD)) for providing machine instructions and / or data to a programmable processor, including machine-readable media that receive machine instructions as machine-readable signals. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.
[0092] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).
[0093] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.
[0094] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed on a computer, the processes or functions described in the embodiments of this disclosure are performed entirely or partially. The computer can be a general-purpose computer, a special-purpose computer, a computer network, a terminal, a user equipment, or other programmable device. The computer program or instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another. For example, the computer program or instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; it can also be an optical medium, such as a digital video disc (DVD); or it can be a semiconductor medium, such as a solid-state drive (SSD).
[0095] Although this disclosure has been described in conjunction with specific features and embodiments, it will be apparent that various modifications and combinations can be made therein without departing from the spirit and scope of this disclosure. Accordingly, this specification and drawings are merely exemplary illustrations of the disclosure as defined by the appended claims and are to be considered as covering any and all modifications, variations, combinations, or equivalents within the scope of this disclosure. It is obvious that those skilled in the art can make various alterations and modifications to this disclosure without departing from its spirit and scope. Thus, this disclosure is also intended to include any such modifications and modifications that fall within the scope of the claims of this disclosure and their equivalents.
Claims
1. A method for determining CQI, characterized in that, The method is applied to a user terminal and includes: The system receives downlink reference signals transmitted by the base station and performs channel estimation based on the downlink reference signals to obtain channel state information. The channel state information includes channel parameter estimation information, precoding matrix identifier (PMI) estimation information, channel estimation information, and noise estimation information. Based on the channel parameter estimation information, the channel scenario parameter values are determined, and in the candidate channel quality information lookup tables of multiple channel scenarios, the target channel quality information lookup table corresponding to the channel scenario parameter values and the current modulation and coding scheme is determined. The candidate channel quality information lookup table includes multiple channel quality indices (CQIs) under different modulation and coding schemes, as well as a weighted mutual information (WMI) threshold associated with each CQI. WMI is used to characterize the degree of information correlation between the modulated signal bits at the transmitting end and the demodulated signal bits at the receiving end in a channel environment with inter-flow interference. Based on PMI estimation information, channel estimation information, and noise estimation information, the signal-to-noise ratio (SNR) is determined, and based on the SNR and the mapping model of SNR and mutual information (MI), the WMI corresponding to each CQI is determined. The target CQI is determined based on the WMI corresponding to each CQI and the WMI threshold associated with each CQI in the target channel quality information lookup table.
2. The method according to claim 1, characterized in that, The mapping model includes a first mapping model under conditions of no inter-flow interference and a second mapping model under conditions of inter-flow interference. The determination of the WMI corresponding to each CQI based on the SNR and the mapping model of SNR and mutual information MI includes: In the table showing the relationship between multiple modulation modes and fitting coefficients, find the target fitting coefficient associated with the modulation mode corresponding to each CQI; For each CQI, the target fitting coefficient and the SNR are input into the first mapping model to obtain a first MI associated with the modulation mode corresponding to the CQI; and the target fitting coefficient and the SNR are input into the second mapping model to obtain a second MI associated with the modulation mode corresponding to the CQI. Based on the first MI and the second MI associated with the modulation mode corresponding to the CQI, the WMI corresponding to the CQI is determined.
3. The method according to claim 2, characterized in that, Determining the WMI corresponding to the CQI based on the first MI and the second MI associated with the modulation mode corresponding to the CQI includes: Read the first weight associated with the first mapping model, and the second weight associated with the second mapping model; Based on the first weight and the second weight, the weighted average between the first MI and the second MI associated with the modulation mode corresponding to the CQI is determined, and the WMI corresponding to the CQI is obtained.
4. The method according to claim 2, characterized in that, Before searching for the target fitting coefficient associated with the modulation mode corresponding to each CQI in the table of multiple modulation modes and fitting coefficients, the method further includes: The relationship table of the multiple modulation modes and fitting coefficients is read. The relationship table of the multiple modulation modes and fitting coefficients is obtained by Monte Carlo simulation to obtain reference mapping relationship data of SNR and MI under multiple modulation modes. The nonlinear least squares algorithm is used to determine the minimum mean square error between the fitted MI calculated by the SNR and MI benchmark mapping model according to the fitting coefficients and the reference MI in the reference mapping relationship data.
5. The method according to claim 1, characterized in that, The channel parameter estimation information includes delay spread, Doppler spread, and channel condition number. Determining channel scenario parameter values based on the channel parameter estimation information includes: Among the correspondences between multiple delay spread value ranges and multiple delay spread levels, the delay spread level associated with the delay spread value range to which the delay spread value belongs is determined as the target delay spread level. Among the correspondences between multiple Doppler expansion value intervals and multiple Doppler expansion levels, the Doppler expansion value level associated with the Doppler expansion value interval to which the Doppler expansion value belongs is determined as the target Doppler expansion value level. Among the correspondences between multiple channel condition number intervals and multiple channel condition levels, the channel condition level associated with the channel condition number interval to which the channel condition number belongs is determined as the target channel condition level. The ternary array consisting of the target delay spread level, the target Doppler spread value level, and the target channel condition level is determined as the channel scenario parameter value.
6. The method according to claim 1, characterized in that, The determination of the target CQI based on the WMI corresponding to each CQI and the WMI threshold associated with each CQI in the target channel quality information lookup table includes: For each CQI, if the WMI corresponding to the CQI is greater than the WMI threshold associated with the CQI in the target channel quality information lookup table, then the CQI is determined as a candidate CQI. When there are multiple candidate CQIs, the largest CQI among the multiple candidate CQIs is determined as the target CQI.
7. The method according to claim 1, characterized in that, The method further includes: Read a pre-stored candidate channel quality information lookup table for multiple channel scenarios. The candidate channel quality information lookup table is obtained by acquiring the target mapping relationship between the block error rate (BLER) and the wMI (weighted index) of multiple CQIs under each modulation and coding scheme of different channel scenarios within a preset simulated SNR range. Based on the target mapping relationship and the BLER threshold under each modulation and coding scheme of different channel scenarios, determine the initial wMI of each CQI under each modulation and coding scheme of different channel scenarios. And, with the throughput TP (total throughput) as the optimization objective, adjust the initial wMI of each CQI under each modulation and coding scheme of different channel scenarios.
8. A network device, the network device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the method according to any one of claims 1 to 7.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method described in any one of claims 1 to 7.
10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method described in any one of claims 1 to 7.