Initial MCS value determination method, electronic device and storage medium

Abstract

The embodiment of the present invention relates to the field of communication technology, and discloses a method for determining an initial MCS value. In the present invention, by determining the current interval of N measurement parameters of the terminal that affect the MCS value of the modulation and coding mechanism; wherein the interval of each measurement parameter is obtained by pre-dividing the possible value range of the measurement parameter; N is a natural number greater than 0; according to the current interval of the N measurement parameters, and the distribution probability of different outer loop MCS values ​​of the N measurement parameters in each interval obtained by pre-statistics, the initial outer loop MCS value of the terminal is calculated in real time; according to the initial outer loop MCS value and the inner loop MCS value of the terminal, a means of determining the initial MCS value of the terminal is determined, so that in the adaptive modulation and coding AMC process, a more suitable initial MCS value is determined, thereby achieving the purpose of accelerating the UE scheduling MCS convergence speed and improving the system spectrum efficiency.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of communication technology, and in particular to a method for determining an initial MCS value, an electronic device, and a storage medium. Background Art

[0002] In LTE and NR systems, AMC (Adaptive Modulation and Coding) is used to determine MCS (Modulation and Coding Scheme). The AMC process is the process of dynamically selecting an appropriate MCS based on changes in channel conditions. Normally, the UE's initial MCS = inner loop MCS + initial outer loop MCS. Among them, the inner loop MCS is determined by the UE's real-time channel quality, while the initial outer loop MCS is given based on experience and is often a fixed value. During real-time scheduling, the UE scheduling MCS = inner loop MCS + outer loop MCS. Among them, the inner loop MCS is still determined by the UE's real-time channel quality, while the outer loop MCS is gradually adjusted based on the initial outer loop MCS and the BLER (Block Error Ratio) of several UE data transmissions.

[0003] There are at least the following problems in the above related technologies: in an actual system, the initial MCS of the UE and the scheduling MCS after its final convergence are often quite different, which affects the BLER after the MCS value is finally determined, resulting in poor user experience. Summary of the invention

[0004] The purpose of the embodiments of the present invention is to provide a method for determining an initial MCS value, an electronic device and a storage medium, so that a more appropriate initial MCS value can be determined in the adaptive modulation coding (AMC) process, thereby achieving the purpose of accelerating the UE scheduling MCS convergence speed and improving the system spectrum efficiency.

[0005] To solve the above technical problems, an embodiment of the present invention provides an initial MCS determination method, comprising the following steps: determining the current interval of N measurement parameters of a terminal that affect the MCS value of a modulation and coding mechanism; wherein the interval of each measurement parameter is obtained by pre-dividing the possible value range of the measurement parameter into intervals; N is a natural number greater than 0; according to the current interval of the N measurement parameters and the distribution probability of different outer loop MCS values ​​of the N measurement parameters in each interval obtained by statistics in advance, the initial outer loop MCS value of the terminal is calculated in real time; and according to the initial outer loop MCS value and the inner loop MCS value of the terminal, the initial MCS value of the terminal is determined.

[0006] An embodiment of the present invention also provides an electronic device, comprising: at least one processor, and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor executes the method for determining the initial MCS value as described above.

[0007] An embodiment of the present invention further provides a computer-readable storage medium storing a computer program, which implements the above-mentioned method for determining an initial MCS value when executed by a processor.

[0008] Compared with the related art, the implementation method of the present invention divides the possible value range of the measurement parameter into intervals in advance to obtain the intervals of each measurement parameter, and statistically calculates the distribution probability of different outer loop MCS values ​​of each N measurement parameter in each interval. First, determine the interval in which the measurement parameters of the N modulation and coding mechanism MCS values ​​are currently located, calculate the initial outer loop MCS value of the terminal according to the distribution probability, and then obtain the initial MCS value according to the terminal inner loop MCS value and the calculated initial outer loop, so that in the adaptive modulation and coding AMC process, a more suitable initial MCS value is determined, thereby achieving the purpose of accelerating the convergence speed of the UE scheduling MCS value and improving the system spectrum efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] One or more embodiments are exemplarily described by pictures in the corresponding drawings, and these exemplified descriptions do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0010] Figure 1 is a flowchart of a method for determining an initial MCS according to a first embodiment of the present invention;

[0011] Figure 2 is a flow chart of obtaining the distribution probability of different outer loop MCS values ​​of N measurement parameters in each interval according to the first embodiment of the present invention;

[0012] Figure 3 is a flow chart of a method for determining an initial MCS according to a second embodiment of the present invention;

[0013] Figure 4 FIG. 4 is a schematic structural diagram of an electronic device according to a third embodiment of the present invention. DETAILED DESCRIPTION

[0014] To make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. However, it will be appreciated by those skilled in the art that in the embodiments of the present invention, many technical details are proposed in order to enable the reader to better understand the present application. However, even without these technical details and various changes and modifications based on the following embodiments, the technical scheme claimed in the present application can be implemented. The division of the following embodiments is for the convenience of description, and should not constitute any limitation on the specific implementation of the present invention. The various embodiments can be combined and referenced with each other without contradiction.

[0015] The first embodiment of the present invention relates to a method for determining an initial MCS. In this embodiment, the interval in which N measurement parameters of a terminal that affect the MCS value of a modulation and coding mechanism are currently located is determined; wherein the interval of each measurement parameter is obtained by pre-dividing the possible value range of the measurement parameter into intervals; N is a natural number greater than 0; based on the interval in which the N measurement parameters are currently located, and the distribution probability of different outer loop MCS values ​​of the N measurement parameters in each interval obtained by pre-statistics, the initial outer loop MCS value of the terminal is calculated in real time; based on the initial outer loop MCS value and the inner loop MCS value of the terminal, the initial MCS value of the terminal is determined.

[0016] The following is a specific description of the implementation details of the method for determining the initial MCS value of this embodiment. The following content is only provided for the convenience of understanding the implementation details and is not necessary for implementing this solution.

[0017] The method for determining the initial MCS value in this embodiment is as follows: Figure 1 As shown, specifically including:

[0018] Step 101, determining the current interval of N measurement parameters of the terminal that affect the modulation and coding scheme MCS value; wherein the interval of each measurement parameter is obtained by pre-dividing the possible value range of the measurement parameter into intervals; and N is a natural number greater than 0.

[0019] Specifically, in this embodiment, the measurement parameters that affect the MCS value of the modulation and coding mechanism include but are not limited to: channel quality indication CQI (Channel Quality Indication), sounding reference signal SRS (Sounding Reference Signal), signal to interference-plus-Noise ratio SINR (Signal to Interference-plus-Noise Ratio) or beam forming gain BF (Beam Forming). The value range of each MCS value measurement parameter is pre-divided into several intervals, and the interval division method includes but is not limited to evenly dividing its value range according to the system accuracy requirements. When the base station starts the process of determining the MCS value of the UE, at least one of them, or a combination of any parameters, is selected as the measurement parameter that affects the MCS value of the modulation and coding mechanism, and then determines in which interval the current value of the selected parameter is. Let i∈{0,...,I-1} represent the relevant measurement parameter index of the MCS value, where I represents the number of MCS value measurement parameters. At the same time, let k i ∈{0,...,K i -1} represents the value interval index of the measurement parameter i of the MCS value, where K i Indicates the number of value intervals of MCS value measurement parameter i.

[0020] In an example, CQI is taken as the only MCS value measurement parameter. Assuming that the value range of CQI is (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15) and is evenly divided into 4 intervals, then k0∈{0, ..., 3}, K0=10, that is, the specific division method is when CQI∈{0, 1, 2, 3}, the index value k0=0; when CQI∈{4, 5, 6, 7}, the index value k0=1; when CQI∈{8, 9, 10, 11}, the index value k0=2; when CQI∈{12, 13, 14, 15,}, the index value k0=3.

[0021] In another example, the selected MCS measurement parameters include: CQI, and SRS-SINR. At this time, i∈{0, 1} represents the MCS value measurement parameter index, I=2. Let k0∈{0,...,3}, then K0=4. The specific interval division method is k0=0, that is, when CQI∈{0,1,2,3}, k0=1, that is, when CQI∈{4,5,6,7}, k0=2 when CQI∈{8,9,10,11}, k0=3, that is, when CQI∈{12,13,14,15}. Let k1∈{0,...,3}, then K1=4. The specific interval division method is k1=0, that is, when SRS-SINR≤10dB, k1=1, that is, when 10dB<SRS-SINR≤15dB, k1=2, that is, when 15dB<SRS-SINR≤20dB, k1=3, that is, when SRS-SINR>20dB.

[0022] Step 102: Determine the distribution probability of different outer loop MCS values ​​corresponding to the interval where the N measurement parameters of the terminal are currently located according to the statistical distribution probability of different outer loop MCS values ​​of the N measurement parameters in each interval.

[0023] Specifically, the base station records in advance the historical data of the MCS values ​​of all user UEs scheduled in a certain period of time, performs statistics on the data, and calculates the distribution probability of each measurement parameter in each interval of the value range.

[0024] In this embodiment, the method for obtaining the distribution probability of different outer ring MCS values ​​of N measurement parameters in each interval is as follows: Figure 2 As shown, specifically including:

[0025] Step 201: determine N measurement parameters and set a sliding time window.

[0026] Specifically, the measurement parameters required for the current UE scheduling MCS process of the base station are selected, and the time length of the sliding time window is set. The length of the sliding time window is generally set based on experience, and a suitable value T is taken according to the specific working conditions of the base station. For example, a base station with a large number of UEs can set a smaller T value, while a base station with a small number of UEs can set a larger T value. Setting the time length too long will result in too much sample data. Since the working pressure of the base station is different in different time periods, the sample data far away from the current moment does not have a good reference value, thereby affecting the final determined initial MCS value; setting the time length too short will result in too little sample data, and the statistically obtained distribution probability confidence is low, which will also affect the final determined initial MCS value.

[0027] Step 202: Count the interval of each MCS value measurement parameter of all UEs in each scheduling and the outer loop MCS value of the UE at the scheduling time.

[0028] Specifically, the duration of the sliding time window is T. For the current time t, the sliding time window represents the period from tT to t-1. The system reads the data of all UEs performing MCS scheduling during this period, and counts the intervals where each MCS value measurement parameter of all UEs is located and the outer loop MCS value of the UE at each scheduling. Finally, the probability that the outer loop MCS is equal to any value when any MCS value measurement parameter belongs to any interval in the current sliding window is calculated.

[0029] Step 203, calculating the probability that the outer loop MCS is equal to any value when any MCS value measurement parameter belongs to any interval within the sliding time window.

[0030] Specifically, in this implementation, let t represent the current time of the MCS determination process, m represent the outer loop MCS value, It means that from time tT to time t-1, that is, within the sliding time window, all UE scheduling MCS value measurement parameters i belong to interval k i The number of times, Indicates that all UE scheduling MCS values ​​within the sliding time window are measured by parameter i belonging to interval k i The number of times the outer loop MCS is equal to m. Count the sliding time window tT to t-1 and make Indicates that from tT to t-1, when the scheduled UE MCS value measurement parameter i belongs to interval k i When , the statistical probability that the outer ring MCS is equal to m is Calculate the sliding time window, that is, the time period from tT to t-1 Among them, for all times t, all measured parameters i and all values ​​k of all measured parameters i , both make k i , Established, that is

[0031] Taking CQI as the only MCS value measurement parameter as an example, the measurement parameter index value of CQI is 0. Taking the sliding time window length T = 200000ms, the current time is t, then the statistics of all UE scheduling MCS value measurement parameters i in the time period from tT to t-1 belong to interval k i The number of And all scheduled UE MCS value measurement parameters i belong to interval k i And the outer loop MCS is equal to the number of times m Assume that the statistical results are as follows:

[0032]

[0033]

[0034] By calculating the sliding time window

[0035]

[0036] Take the measurement parameters including CQI and SRS-SINR as an example, the measurement parameter index value of CQI is 0, and the index value of SRS-SINR is 1. Take T = 200000ms, and count the sliding time window tT to t-1 time period and assumed

[0037]

[0038]

[0039]

[0040] Calculate the sliding time window

[0041]

[0042]

[0043] Step 103: Obtain a target outer loop MCS value that can maximize the sum of the distribution probabilities of the outer loop MCS values ​​corresponding to the intervals in which the N measurement parameters are currently located.

[0044] Specifically, the base station first obtains the values ​​of each measurement parameter in the current MCS value determination process, and then determines the distribution probability of different outer loop MCS values ​​corresponding to the interval where the N measurement parameters of the current terminal are currently located. The distribution probabilities corresponding to each MCS value are summed to obtain the target outer loop MCS value that can maximize the sum of the distribution probabilities of the outer loop MCS values ​​corresponding to the interval where the N measurement parameters are currently located. The statistical probability of different outer loop MCS values ​​corresponding to the interval where the measurement parameters related to each MCS value of the UE are located is obtained. The outer loop MCS value that can maximize the weighted probability sum of the interval where all the measurement parameters related to the MCS value of the UE are located is calculated, and this value is used as the initial outer loop MCS of the UE. The weight used for weighting can be simply set to 1 divided by the number of measurement parameters related to the MCS value, or the number of samples in the interval where the measurement parameters related to the MCS value of the UE are arbitrarily specified by the UE can be divided by the total number of samples in the interval where all the measurement parameters related to the MCS value of the UE are located. Finally, the initial MCS of the UE is obtained in combination with the inner loop MCS value calculated in real time.

[0045] By learning the historical scheduling samples of the system within the sliding time window, and taking the target outer-loop MCS value that can maximize the sum of the distribution probabilities of the outer-loop MCS values ​​corresponding to the current interval of N measurement parameters, a more appropriate initial MCS can be selected, thereby achieving the purpose of accelerating the UE scheduling MCS convergence speed and improving the system spectrum efficiency.

[0046] When N is equal to 1, the target outer ring MCS value corresponding to the element with the largest probability value in the probability matrix of the unique measurement parameter distribution is directly used as the initial outer ring MCS value. The matrix is ​​summed to obtain the summed matrix Then, the target outer loop MCS value corresponding to the element with the largest value in the summed matrix is ​​used as the initial outer loop MCS value. Let u represent the UE index, Indicates the interval where the measurement parameter i of the UEuMCS value is located at the current moment. At time t, the initial outer loop of UEu is calculated in real time. in represents the weight assigned to the MCS value measurement parameter i of the UE identified as u at time t. In addition, The value of can be manually adjusted through the parameter interface, or it can be automatically calculated according to certain rules. or

[0047] Taking CQI as the only MCS value measurement parameter as an example, assuming that the CQI of the UE with ID 0 at time t is 10, that is, Then make That is, let the initial outer loop MCS of UE 0 be -3, and the calculated inner loop MCS of UE 0 is 15, so the initial MCS of UE 0 is 12. Assume that UE 1 is at time tCQI=14, that is That is, assuming that the initial outer loop MCS of UE 1 is -1, the calculated inner loop MCS of UE 1 is 24, so the initial MCS of UE 1 is 23.

[0048] Taking the measurement parameters including: CQI and SRS_SINR as an example, assuming that the UE with identification 0 is at time t CQI = 10, that is SRS_SINR = 16dB, that is make but That is, if the initial outer loop MCS of the UE with ID 0 is -2, the calculated inner loop MCS of the UE with ID 0 is 15, so the initial MCS of the UE with ID 0 is 13. Assume that the UE with ID 1 has an initial MCS of 14 at time tCQI, that is SRS-SINR = 19dB, that is at this time in That is, assuming that the initial outer loop MCS of UE 1 is -2, the calculated inner loop MCS of UE identified as 1 is 24, so the initial MCS value of UE identified as 1 is 22.

[0049] Step 104: Determine the initial MCS value of the terminal according to the initial outer loop MCS value and the inner loop MCS value of the terminal.

[0050] Specifically, the initial MCS value of the user UE is the sum of the inner loop MCS value and the initial outer loop MCS value. That is, the initial MCS of the UE identified as u = inner loop MCS + initial outer loop MCS. Among them, the inner loop MCS value is determined by the real-time channel quality of the UE, and the initial outer loop MCS value is given based on experience and is often a fixed value. During the real-time scheduling process, the UE scheduling MCS value is the sum of the inner loop MCS value and the outer loop MCS value. Among them, the inner loop MCS value is still determined by the real-time channel quality of the UE, while the outer loop MCS value is gradually adjusted based on the initial outer loop MCS according to the BLER (Block Error Ratio) of several data transmissions of the UE. This embodiment only provides a method for obtaining the initial outer loop MCS to accelerate the process of the initial outer loop MCS converging to the outer loop MCS. Compared with the prior art, this embodiment pre-statistics the distribution probability of different outer loop values ​​of N measurement parameters in each interval, and calculates a more appropriate initial MCS outer loop value in real time according to the distribution probability and the current interval of the current N measurement parameters, so that the initial MCS value can quickly converge to a UE scheduling MCS value with a lower bit error rate BLER.

[0051] The second embodiment of the present invention relates to a method for determining an initial MCS value. This embodiment is substantially the same as the first embodiment, except that, in this embodiment, before obtaining a target outer-loop MCS value that can maximize the sum of the distribution probabilities of the outer-loop MCS values ​​corresponding to the interval in which the N measurement parameters are currently located, a weighting coefficient of each measurement parameter is obtained.

[0052] The method for determining the initial MCS value in this embodiment is as follows: Figure 3 As shown, specifically including:

[0053] Step 301: determine the interval in which N measurement parameters of the terminal that affect the modulation and coding scheme MCS value are currently located.

[0054] Step 302: Determine the distribution probability of different outer loop MCS values ​​corresponding to the interval where the N measurement parameters of the terminal are currently located according to the statistical distribution probability of different outer loop MCS values ​​of the N measurement parameters in each interval.

[0055] Step 301 and step 302 are similar to step 101 and step 102 in the first embodiment of the present invention, and the implementation details have been specifically described in the first embodiment of the present invention, which will not be repeated here.

[0056] Step 303: Obtain the weighting coefficient of each measurement parameter.

[0057] Step 304: Obtain a target outer loop MCS value that can maximize the weighted sum of the outer loop value distribution probabilities of the current interval of the N measurement parameters.

[0058] Specifically, the default weighting coefficient of each measurement parameter is 1 / N. The weighting coefficient corresponding to the measurement parameter in this embodiment is Determined according to the number of samples in the interval where the measurement parameter is currently located and the total number of samples in the interval where the N measurement parameters are currently located, where That is to say, the weighting coefficient is equal to the number of samples in the interval where the measurement parameter of any specified MCS value of the UE is located divided by the number of samples in the interval where all MCS value-related measurement parameters of the UE are located divided by the total number of samples in the interval where all MCS value measurement parameters of the UE are located. Through such a weighting coefficient, the calculated initial outer loop MCS value can be more consistent with the scheduling sample, avoiding the statistical error caused by too few samples of a certain measurement parameter, thereby obtaining an initial outer loop MCS value with a slower convergence speed.

[0059] In one example, the target outer loop MCS value is determined by the following formula:

[0060]

[0061] In addition, the weighting coefficients are adjusted in real time through the parameter interface.

[0062] Step 305: Determine the initial MCS value of the terminal according to the initial outer loop MCS value and the inner loop MCS value of the terminal.

[0063] It should be noted that the above examples in this embodiment are all illustrative for easy understanding and do not constitute a limitation on the technical solution of the present invention.

[0064] The step division of the above methods is only for the purpose of clear description. When implemented, they can be combined into one step or some steps can be split and decomposed into multiple steps. As long as they include the same logical relationship, they are all within the scope of protection of this patent; adding insignificant modifications to the algorithm or process or introducing insignificant designs without changing the core design of the algorithm and process are all within the scope of protection of this patent.

[0065] A third embodiment of the present invention relates to an electronic device, such as Figure 4 As shown, including:

[0066] At least one processor 401; and, a memory 402 communicatively connected to the at least one processor 401; wherein the memory 402 stores instructions executable by the at least one processor 401, and the instructions are executed by the at least one processor 402 so that the at least one processor 401 can execute the initial MCS determination method as described in the first and second embodiments of the present invention.

[0067] Among them, the memory and the processor are connected in a bus manner, and the bus may include any number of interconnected buses and bridges, and the bus connects various circuits of one or more processors and memories together. The bus can also connect various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and are therefore not further described herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be one element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices on a transmission medium. The data processed by the processor is transmitted on a wireless medium via an antenna, and further, the antenna also receives data and transmits the data to the processor.

[0068] The processor is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. Memory can be used to store data used by the processor when performing operations.

[0069] A fourth embodiment of the present invention relates to a computer-readable storage medium storing a computer program, which implements the above method embodiment when executed by a processor.

[0070] That is, those skilled in the art can understand that all or part of the steps in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a program, and the program is stored in a storage medium, including several instructions to enable a device (which can be a single-chip microcomputer, chip, etc.) or a processor to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0071] Those skilled in the art will appreciate that the above-mentioned embodiments are specific examples for implementing the present invention, and in actual applications, various changes may be made thereto in form and detail without departing from the spirit and scope of the present invention.

Claims

1. A method for determining an initial MCS value, It is characterized in that include: Determine the current interval of N measurement parameters of the terminal that affect the modulation and coding scheme MCS value; wherein the interval of each measurement parameter is obtained by pre-dividing the possible value range of the measurement parameter into intervals; and N is a natural number greater than 0; Determine the distribution probability of different outer loop MCS values ​​corresponding to the interval in which the N measurement parameters of the terminal are currently located according to the statistically obtained distribution probability of different outer loop MCS values ​​in each interval; Obtain a target outer ring MCS value that can maximize the sum of the distribution probabilities of the outer ring MCS values ​​corresponding to the intervals in which the N measurement parameters are currently located; Using the target outer loop MCS value as the initial outer loop MCS value of the terminal; An initial MCS value of the terminal is determined according to the initial outer loop MCS value and the inner loop MCS value of the terminal.

2. The method for determining the initial MCS value according to claim 1, It is characterized in that The distribution probability of different outer ring MCS values ​​of the N measurement parameters in each interval is obtained by the following statistical method: In a sliding time window of a preset length, the intervals where the measurement parameters are located and the corresponding outer loop MCS values ​​are counted for all terminals during each scheduling, and the probability that the outer loop MCS value is any value when the measurement parameter belongs to any interval is obtained.

3. The method for determining the initial MCS value according to claim 1, It is characterized in that The N measurement parameters respectively correspond to a weighting coefficient; The obtaining of a target outer ring MCS value that can maximize the sum of the distribution probabilities of the outer ring MCS values ​​corresponding to the intervals in which the N measurement parameters are currently located specifically includes: Obtain a target outer loop MCS value that can maximize the weighted sum of the outer loop MCS value distribution probabilities corresponding to the interval in which the N measurement parameters are currently located.

4. The method for determining the initial MCS value according to claim 3, It is characterized in that The weighting coefficient is adjusted in real time through a parameter interface.

5. The method for determining the initial MCS value according to claim 3, It is characterized in that The weighting coefficients corresponding to the measurement parameters are all 1 / N; or, the weighting coefficients corresponding to the measurement parameters are determined according to the number of samples in the interval where the measurement parameters are currently located and the total number of samples in the interval where the N measurement parameters are currently located.

6. The method for determining the initial MCS value according to any one of claims 1 to 5, It is characterized in that The N measurement parameters include one of the following or any combination thereof: Channel quality indication, sounding reference signal, signal-to-interference-and-noise ratio, or beamforming gain.

7. The method for determining the initial MCS value according to any one of claims 1 to 5, It is characterized in that The determining, according to the initial outer loop MCS value and the inner loop MCS value of the terminal, an initial MCS value of the terminal includes: The initial outer loop MCS value and the inner loop MCS value of the terminal are summed to obtain an initial MCS value of the terminal; wherein the inner loop MCS value is determined according to the real-time channel quality of the terminal.

8. An electronic device, It is characterized in that include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method for determining an initial MCS value as claimed in any one of claims 1 to 7.

9. A computer-readable storage medium storing a computer program, It is characterized in that When the computer program is executed by a processor, the method for determining an initial MCS value according to any one of claims 1 to 7 is implemented.

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