Method and device for adjusting inner loop value, storage medium and electronic device

Abstract

The embodiment of the present application provides a kind of inner loop value adjustment method and device, storage medium and electronic device, the above method includes: the following steps are cyclically executed, wherein the historical inner loop adjustment factor of each time domain scheduling unit in wireless frame is initialized as the initial inner loop adjustment factor of each time domain scheduling unit: according to the ACK / NACK information corresponding to each time domain scheduling unit, the block error rate corresponding to each time domain scheduling unit is determined, wherein wireless frame includes N time domain scheduling units, N is positive integer;According to the block error rate corresponding to each time domain scheduling unit and the historical inner loop adjustment factor of each time domain scheduling unit, the current inner loop adjustment factor of each time domain scheduling unit is determined;According to the current inner loop adjustment factor of each time domain scheduling unit, the inner loop value corresponding to each time domain scheduling unit is adjusted. By the present application, the technical problem that the demodulation difference between time domain scheduling units in the related art cannot be quickly compensated by user-level AMC is solved.

Description

Technical Field

[0001] The present invention relates to the field of communications, and more specifically, to a method and apparatus for adjusting an inner loop value, a storage medium, and an electronic device. Background Technology

[0002] With the development of mobile communication technology, users' communication needs are gradually increasing. Communication needs have evolved from voice-based to data-based, and these needs are still growing, such as the need to watch high-definition live broadcasts in real time with higher service speeds. To meet these needs, fifth-generation (5G) mobile communication technology has emerged.

[0003] In 5G standard protocols, the reference signals configured in different time slots differ, resulting in variations in the amount of valid information transmitted through the same number of resource blocks (RBs). This leads to differences in the bit rate for users across different time slots, which in turn causes differences in demodulation performance. Furthermore, the impact of uplink / downlink switching on the radio frequency end also contributes to differences in demodulation performance between time slots, as demonstrated by current network testing.

[0004] Traditional adaptive modulation and coding (AMC) techniques are user-level and can only compensate for differences at the user level. Differences between time slots cannot be quickly compensated for by user-level AMC. Therefore, when a user's demodulation performance varies significantly between time slots, the Block Error Rate (BLER) appears convergent from the user's perspective, but large differences in BLER occur across different time slots; some time slots have very high BLERs, while others have very low BLERs, resulting in insufficient improvement in spectral efficiency. This problem can be addressed through inter-time slot AMC. However, inter-time slot AMC introduces a time slot dimension, reducing the number of samples available for AMC learning in each time slot, thus further exacerbating the non-convergence problem for users with small packet scheduling.

[0005] There is no effective technical solution yet to address the technical problem that demodulation differences between time-domain scheduling units cannot be quickly compensated by user-level AMC. Summary of the Invention

[0006] This invention provides a method and apparatus for adjusting the inner loop value, a storage medium, and an electronic device to at least solve the technical problem in related technologies that demodulation differences between time-domain scheduling units cannot be quickly compensated by user-level AMC.

[0007] According to an embodiment of the present invention, a method for adjusting the inner loop value is provided, comprising: cyclically executing the following steps, wherein the historical inner loop adjustment factor of each time-domain scheduling unit in a radio frame is initialized as the initial inner loop adjustment factor of each time-domain scheduling unit; determining the block error rate corresponding to each time-domain scheduling unit based on the ACK / NACK information corresponding to each time-domain scheduling unit, wherein the radio frame includes N time-domain scheduling units, and N is a positive integer; determining the current inner loop adjustment factor of each time-domain scheduling unit based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit; and adjusting the inner loop value corresponding to each time-domain scheduling unit based on the current inner loop adjustment factor of each time-domain scheduling unit.

[0008] In an exemplary embodiment, determining the current inner loop adjustment factor of each time-domain scheduling unit based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit includes: when the range of the block error rates corresponding to the N time-domain scheduling units is greater than or equal to a preset threshold, determining the current inner loop adjustment factor T_factor of time-domain scheduling unit i according to the following formula. i :T_factor i = (1-α)*T'_factor i +α*factor i Where 1≤i≤N, α is the filter factor, 0≤α≤1, and T'_factor i The historical inner loop adjustment factor of the time-domain scheduling unit i is factor. i =(BLER_tar-BLER) i )*step, BLER_tar is the preset target value for block error rate, BLER i Let be the block error rate corresponding to the time-domain scheduling unit i, and step be the adjustment step size, where step is greater than 0.

[0009] In an exemplary embodiment, determining the current inner loop adjustment factor of each time-domain scheduling unit based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit includes: when the range of the block error rates corresponding to the N time-domain scheduling units is greater than or equal to a preset threshold, dividing the N time-domain scheduling units into M subsets based on the block error rates corresponding to each time-domain scheduling unit, wherein the range of the block error rates corresponding to the time-domain scheduling units in each of the M subsets is less than the preset threshold, M is a positive integer, and M is less than N; determining the inner loop adjustment factor corresponding to each subset based on the block error rate corresponding to the time-domain scheduling units in each subset; and determining the current inner loop adjustment factor of each time-domain scheduling unit based on the inner loop adjustment factor corresponding to each subset and the historical inner loop adjustment factor of each time-domain scheduling unit.

[0010] In an exemplary embodiment, determining the inner loop adjustment factor corresponding to each subset based on the block error rate corresponding to the time-domain scheduling unit of each subset includes: determining the inner loop adjustment factor (factor) corresponding to each subset according to the following formula. k :factor k =(BLER_tar-BLERA k )*step, where 1≤k≤M, BLER_tar is the preset target value for block error rate, BLERA k is the average block error rate corresponding to the time-domain scheduling unit in subset k, and step is the adjustment step size, and step is greater than 0.

[0011] In an exemplary embodiment, determining the current inner loop adjustment factor of each time-domain scheduling unit based on the inner loop adjustment factor corresponding to each subset and the historical inner loop adjustment factor of each time-domain scheduling unit includes: determining the current inner loop adjustment factor T_factor of time-domain scheduling unit i according to the following formula. i :T_factor i = (1-α)*T'_factor i +α*factor k Wherein, the time-domain scheduling unit i belongs to the k-th subset of the M subsets, 1≤i≤N, α is the filtering factor, 0≤α≤1, and T'_factor i is the historical inner loop adjustment factor of the time-domain scheduling unit i.

[0012] In an exemplary embodiment, dividing the N time-domain scheduling units into M subsets based on the block error rate corresponding to each time-domain scheduling unit includes: constructing an N×N absolute difference matrix A based on the block error rate set corresponding to the N time-domain scheduling units, wherein each block error rate in the block error rate set corresponds one-to-one with each time-domain scheduling unit in the N time-domain scheduling units; repeating the following steps until the value c equals 1, wherein the current matrix is ​​initialized to the matrix A, the current time-domain scheduling unit set is initialized to the set composed of the N time-domain scheduling units, and the value c is initialized to N; searching for a c×c target submatrix in the current matrix, wherein each element in the target submatrix is ​​less than the preset threshold; if the target submatrix is ​​found in the current matrix, the elements in the target submatrix are... The set of time-domain scheduling units corresponding to each row is determined as a subset; the subset is deleted from the current time-domain scheduling unit set, and the current time-domain scheduling unit set after deleting the subset is determined as the current time-domain scheduling unit set; the absolute value matrix of the difference of (Nc)×(Nc) constructed according to the block error rate set corresponding to the current time-domain scheduling unit set is determined as the current matrix, wherein each block error rate in the block error rate set corresponding to the current time-domain scheduling unit set corresponds one-to-one with each time-domain scheduling unit in the current time-domain scheduling unit set; if the target submatrix is ​​not found in the current matrix, the difference obtained by subtracting 1 from the value c is determined as the value c; wherein, if the value c equals 1, the time-domain scheduling unit corresponding to each row in the current matrix is ​​determined as a subset.

[0013] In an exemplary embodiment, the step of dividing the N time-domain scheduling units into M subsets according to the block error rate corresponding to each time-domain scheduling unit includes: dividing the N block error rates corresponding to the N time-domain scheduling units into M consecutive intervals, wherein each of the M intervals includes at least one block error rate, and the range of the block error rates within each interval is less than the preset threshold; dividing the time-domain scheduling units among the N time-domain scheduling units that correspond to the block error rates included in interval k of the M intervals into subset k, resulting in a total of M subsets, where 1≤k≤M.

[0014] In an exemplary embodiment, determining the current inner loop adjustment factor of each time-domain scheduling unit based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit includes: when the range of the block error rates corresponding to the N time-domain scheduling units is less than a preset threshold, determining the current inner loop adjustment factor of each time-domain scheduling unit as the historical inner loop adjustment factor of each time-domain scheduling unit.

[0015] In an exemplary embodiment, after determining the current inner loop adjustment factor of each time-domain scheduling unit based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit, the method further includes: if the range of the block error rates corresponding to the N time-domain scheduling units is greater than or equal to a preset threshold, updating the historical inner loop adjustment factor of each time-domain scheduling unit to the current inner loop adjustment factor of each time-domain scheduling unit.

[0016] In an exemplary embodiment, adjusting the inner loop value corresponding to each time-domain scheduling unit based on the current inner loop adjustment factor of each time-domain scheduling unit includes: determining the inner loop value d of the user corresponding to time-domain scheduling unit i. i The current inner loop adjustment factor T_factor of the time-domain scheduling unit i i The sum; the inner ring value d i With the current inner loop adjustment factor T_factor i The sum of these values ​​is determined as the inner loop value adjusted by the user in the time-domain scheduling unit i.

[0017] In an exemplary embodiment, when the wireless frame is a wireless frame in a 4G communication system, each time-domain scheduling unit in the wireless frame corresponds one-to-one with each subframe in the wireless frame, where N is the number of subframes in the wireless frame; when the wireless frame is a wireless frame in a 5G communication system, each time-domain scheduling unit in the wireless frame corresponds one-to-one with each time slot in the wireless frame, where N is the number of time slots in the wireless frame.

[0018] According to another embodiment of the present invention, an inner loop value adjustment device is provided, comprising: a processing module, wherein the processing module is configured to cyclically execute the following steps, wherein the historical inner loop adjustment factor of each time-domain scheduling unit in a radio frame is initialized to the initial inner loop adjustment factor of each time-domain scheduling unit; the block error rate corresponding to each time-domain scheduling unit is determined according to the ACK / NACK information corresponding to each time-domain scheduling unit, wherein the radio frame includes N time-domain scheduling units, and N is a positive integer; the current inner loop adjustment factor of each time-domain scheduling unit is determined according to the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit; and the inner loop value corresponding to each time-domain scheduling unit is adjusted according to the current inner loop adjustment factor of each time-domain scheduling unit.

[0019] According to yet another embodiment of the present invention, a computer-readable storage medium is also provided, wherein a computer program is stored therein, wherein the computer program is configured to perform the steps in any of the above method embodiments when executed.

[0020] According to yet another embodiment of the present invention, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0021] By means of this invention, the following steps are executed cyclically, wherein the historical inner loop adjustment factor of each time-domain scheduling unit in the radio frame is initialized to the initial inner loop adjustment factor of each time-domain scheduling unit: the block error rate corresponding to each time-domain scheduling unit is determined according to the ACK / NACK information corresponding to each time-domain scheduling unit, wherein the radio frame includes N time-domain scheduling units, where N is a positive integer; the current inner loop adjustment factor of each time-domain scheduling unit is determined according to the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit; and the inner loop value corresponding to each time-domain scheduling unit is adjusted according to the current inner loop adjustment factor of each time-domain scheduling unit. Since the current inner loop adjustment factor of each time-domain scheduling unit is determined based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit, and the inner loop value corresponding to each time-domain scheduling unit is adjusted based on the current inner loop adjustment factor of each time-domain scheduling unit, the technical problem that demodulation differences between time-domain scheduling units cannot be quickly compensated by user-level AMC in related technologies can be solved. This achieves the technical effect of quickly compensating for demodulation differences between time slots and differentiating user scheduling based on demodulation performance differences in different time-domain scheduling units. Attached Figure Description

[0022] Figure 1 This is a hardware structure block diagram of an optional electronic device according to an embodiment of the present invention;

[0023] Figure 2 This is a flowchart of a method for adjusting the inner loop value according to an embodiment of the present invention;

[0024] Figure 3 This is a schematic diagram of constructing the difference absolute value matrix using the inner loop value adjustment method according to an embodiment of the present invention;

[0025] Figure 4 This is a flowchart of a method for adjusting the inner loop value according to another embodiment of the present invention;

[0026] Figure 5This is a flowchart of the data collection phase of an inner loop value adjustment method according to another embodiment of the present invention;

[0027] Figure 6 This is a flowchart of the data processing stage of the inner loop value adjustment method according to another embodiment of the present invention;

[0028] Figure 7 This is a flowchart of the feature extraction and calculation stage of the inner loop value adjustment method according to another embodiment of the present invention;

[0029] Figure 8 This is a flowchart of the model learning phase of an inner loop value adjustment method according to another embodiment of the present invention;

[0030] Figure 9 This is a flowchart of the model application stage of the inner loop value adjustment method according to another embodiment of the present invention;

[0031] Figure 10 This is a structural block diagram of an inner loop value adjustment device according to an embodiment of the present invention. Detailed Implementation

[0032] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings and examples.

[0033] It should be noted that the terms "first," "second," etc., in the specification, claims, and drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0034] The methods and embodiments provided in this application can be executed in mobile terminals, base stations, computer terminals, servers, or similar computing devices. Taking operation on an electronic device as an example, Figure 1 This is a hardware structure block diagram of an optional electronic device according to an embodiment of the present invention. For example... Figure 1 As shown, an electronic device may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The electronic device may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the electronic device described above. For example, the electronic device may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0035] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the inner loop value adjustment method in this embodiment of the invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to electronic devices via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0036] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network or a wired network. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can be connected to other network devices to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module used for wireless communication with the Internet.

[0037] This embodiment provides a method for adjusting the inner loop value. Figure 2 This is a flowchart of the method for adjusting the inner loop value according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps: Steps S202 to S206 are executed cyclically, wherein the historical inner loop adjustment factor of each time-domain scheduling unit in the radio frame is initialized to the initial inner loop adjustment factor of each time-domain scheduling unit:

[0038] Step S202: Determine the block error rate corresponding to each time-domain scheduling unit based on the ACK / NACK information corresponding to each time-domain scheduling unit, wherein the radio frame includes N time-domain scheduling units, and N is a positive integer;

[0039] Step S204: Determine the current inner loop adjustment factor of each time-domain scheduling unit based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit;

[0040] Step S206: Adjust the inner loop value corresponding to each time-domain scheduling unit according to the current inner loop adjustment factor of each time-domain scheduling unit.

[0041] By means of this invention, the following steps are executed cyclically, wherein the historical inner loop adjustment factor of each time-domain scheduling unit in the radio frame is initialized to the initial inner loop adjustment factor of each time-domain scheduling unit: the block error rate corresponding to each time-domain scheduling unit is determined according to the ACK / NACK information corresponding to each time-domain scheduling unit, wherein the radio frame includes N time-domain scheduling units, where N is a positive integer; the current inner loop adjustment factor of each time-domain scheduling unit is determined according to the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit; and the inner loop value corresponding to each time-domain scheduling unit is adjusted according to the current inner loop adjustment factor of each time-domain scheduling unit. Since the current inner loop adjustment factor of each time-domain scheduling unit is determined based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit, and the inner loop value corresponding to each time-domain scheduling unit is adjusted based on the current inner loop adjustment factor of each time-domain scheduling unit, the technical problem that demodulation differences between time-domain scheduling units cannot be quickly compensated by user-level AMC in related technologies can be solved. This achieves the technical effect of quickly compensating for demodulation differences between time slots and differentiating user scheduling based on demodulation performance differences in different time-domain scheduling units.

[0042] It should be noted that, in the above embodiments, determining the block error rate corresponding to each time-domain scheduling unit based on the ACK / NACK information corresponding to each time-domain scheduling unit includes: collecting the ACK / NACK information corresponding to each time-domain scheduling unit, and determining the block error rate corresponding to each time-domain scheduling unit based on the ACK / NACK information corresponding to each time-domain scheduling unit.

[0043] In the above embodiments, the block error rate (BLER) corresponding to each time-domain scheduling unit can be determined, ACK / NACK information (excluding conservative scheduling) can be collected for each time-domain scheduling unit, and ACK / NACK can be counted separately for each time-domain scheduling unit. Optionally, the block error rate (BLER) corresponding to each time-domain scheduling unit can be determined according to the following formula. i :

[0044]

[0045] Where i = 1, 2, ... N, ni1 is the number of NACKs corresponding to time-domain scheduling unit i, and ni2 is the number of ACKs corresponding to time-domain scheduling unit i.

[0046] In an exemplary embodiment, determining the current inner loop adjustment factor of each time-domain scheduling unit based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit includes: when the range of the block error rates corresponding to the N time-domain scheduling units is greater than or equal to a preset threshold, determining the current inner loop adjustment factor T_factor of time-domain scheduling unit i according to the following formula. i :T_factor i = (1-α)*T'_factor i +α*factor i Where 1≤i≤N, α is the filter factor, 0≤α≤1, and T'_factor i The historical inner loop adjustment factor of the time-domain scheduling unit i is factor. i =(BLER_tar-BLER) i )*step, BLER_tar is the preset target value for block error rate, BLER i Let be the block error rate corresponding to the time-domain scheduling unit i, and step be the adjustment step size, where step is greater than 0.

[0047] In an exemplary embodiment, determining the current inner loop adjustment factor of each time-domain scheduling unit based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit includes: when the range of the block error rates corresponding to the N time-domain scheduling units is greater than or equal to a preset threshold, dividing the N time-domain scheduling units into M subsets based on the block error rates corresponding to each time-domain scheduling unit, wherein the range of the block error rates corresponding to the time-domain scheduling units in each of the M subsets is less than the preset threshold, M is a positive integer, and M is less than N; determining the inner loop adjustment factor corresponding to each subset based on the block error rate corresponding to the time-domain scheduling units in each subset; and determining the current inner loop adjustment factor of each time-domain scheduling unit based on the inner loop adjustment factor corresponding to each subset and the historical inner loop adjustment factor of each time-domain scheduling unit.

[0048] In an exemplary embodiment, determining the inner loop adjustment factor corresponding to each subset based on the block error rate corresponding to the time-domain scheduling unit of each subset includes: determining the inner loop adjustment factor (factor) corresponding to each subset according to the following formula. k :factor k =(BLER_tar-BLERA k )*step, where 1≤k≤M, BLER_tar is the preset target value for block error rate, BLERA kis the average block error rate corresponding to the time-domain scheduling unit in subset k, and step is the adjustment step size, and step is greater than 0.

[0049] In an exemplary embodiment, determining the current inner loop adjustment factor of each time-domain scheduling unit based on the inner loop adjustment factor corresponding to each subset and the historical inner loop adjustment factor of each time-domain scheduling unit includes: determining the current inner loop adjustment factor T_factor of time-domain scheduling unit i according to the following formula. i :T_factor i = (1-α)*T'_factor i +α*factor k Wherein, the time-domain scheduling unit i belongs to the k-th subset of the M subsets, 1≤i≤N, α is the filtering factor, 0≤α≤1, and T'_factor i is the historical inner loop adjustment factor of the time-domain scheduling unit i.

[0050] In an exemplary embodiment, dividing the N time-domain scheduling units into M subsets based on the block error rate corresponding to each time-domain scheduling unit includes: constructing an N×N absolute difference matrix A based on the block error rate set corresponding to the N time-domain scheduling units, wherein each block error rate in the block error rate set corresponds one-to-one with each time-domain scheduling unit in the N time-domain scheduling units; repeating the following steps until the value c equals 1, wherein the current matrix is ​​initialized to the matrix A, the current time-domain scheduling unit set is initialized to the set composed of the N time-domain scheduling units, and the value c is initialized to N; searching for a c×c target submatrix in the current matrix, wherein each element in the target submatrix is ​​less than the preset threshold; if the target submatrix is ​​found in the current matrix, the elements in the target submatrix are... The set of time-domain scheduling units corresponding to each row is determined as a subset; the subset is deleted from the current time-domain scheduling unit set, and the current time-domain scheduling unit set after deleting the subset is determined as the current time-domain scheduling unit set; the absolute value matrix of the difference of (Nc)×(Nc) constructed according to the block error rate set corresponding to the current time-domain scheduling unit set is determined as the current matrix, wherein each block error rate in the block error rate set corresponding to the current time-domain scheduling unit set corresponds one-to-one with each time-domain scheduling unit in the current time-domain scheduling unit set; if the target submatrix is ​​not found in the current matrix, the difference obtained by subtracting 1 from the value c is determined as the value c; wherein, if the value c equals 1, the time-domain scheduling unit corresponding to each row in the current matrix is ​​determined as a subset.

[0051] Optionally, such as Figure 3 As shown, based on the set of block error rates corresponding to the N time-domain scheduling units, an N×N difference absolute value matrix A is constructed: Each row and column in matrix A corresponds one-to-one with a time-domain scheduling unit, and the elements A in matrix A are... ij =|BLER i -BLER j |, j=1,2,…N.

[0052] In an exemplary embodiment, the step of dividing the N time-domain scheduling units into M subsets according to the block error rate corresponding to each time-domain scheduling unit includes: dividing the N block error rates corresponding to the N time-domain scheduling units into M consecutive intervals, wherein each of the M intervals includes at least one block error rate, and the range of the block error rates within each interval is less than the preset threshold; dividing the time-domain scheduling units among the N time-domain scheduling units that correspond to the block error rates included in interval k of the M intervals into subset k, resulting in a total of M subsets, where 1≤k≤M.

[0053] In the above embodiments, when a certain block error rate is the boundary value of two intervals, the time-domain scheduling unit corresponding to the block error rate is divided into the interval with the smaller initial block error rate value.

[0054] In an exemplary embodiment, determining the current inner loop adjustment factor of each time-domain scheduling unit based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit includes: when the range of the block error rates corresponding to the N time-domain scheduling units is less than a preset threshold, determining the current inner loop adjustment factor of each time-domain scheduling unit as the historical inner loop adjustment factor of each time-domain scheduling unit.

[0055] It should be noted that in the above embodiments, when the range of the block error rates corresponding to the N time-domain scheduling units is less than a preset threshold, the historical inner loop adjustment factor of each time-domain scheduling unit is reused. That is, after determining the current inner loop adjustment factor of each time-domain scheduling unit, the historical inner loop adjustment factor of each time-domain scheduling unit remains unchanged.

[0056] In an exemplary embodiment, after determining the current inner loop adjustment factor of each time-domain scheduling unit based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit, the method further includes: if the range of the block error rates corresponding to the N time-domain scheduling units is greater than or equal to a preset threshold, updating the historical inner loop adjustment factor of each time-domain scheduling unit to the current inner loop adjustment factor of each time-domain scheduling unit.

[0057] In an exemplary embodiment, adjusting the inner loop value corresponding to each time-domain scheduling unit based on the current inner loop adjustment factor of each time-domain scheduling unit includes: determining the inner loop value d of the user corresponding to time-domain scheduling unit i. i The current inner loop adjustment factor T_factor of the time-domain scheduling unit i i The sum; the inner ring value d i With the current inner loop adjustment factor T_factor i The sum of these values ​​is determined as the inner loop value adjusted by the user in the time-domain scheduling unit i.

[0058] In an exemplary embodiment, when the wireless frame is a wireless frame in a 4G communication system, each time-domain scheduling unit in the wireless frame corresponds one-to-one with each subframe in the wireless frame, where N is the number of subframes in the wireless frame; when the wireless frame is a wireless frame in a 5G communication system, each time-domain scheduling unit in the wireless frame corresponds one-to-one with each time slot in the wireless frame, where N is the number of time slots in the wireless frame.

[0059] It should be noted that in the above embodiments, the inner loop value is the channel measurement value of the base station for the user. Therefore, in the above embodiments, the inner loop value adjusted by the time domain scheduling unit can be used to determine the scheduling strategy of the corresponding time domain scheduling unit. That is, in the above embodiments, the scheduling strategy corresponding to each time domain scheduling unit can be determined according to the inner loop value adjusted by each time domain scheduling unit, thereby realizing differentiated scheduling of each time domain scheduling unit according to the demodulation performance difference of the user in each time domain unit.

[0060] It should be noted that, in the above embodiments, the range of the block error rates corresponding to the N time-domain scheduling units is the difference between the maximum value and the minimum value of the block error rates corresponding to the N time-domain scheduling units.

[0061] The following example illustrates the method for adjusting the inner loop value in the above embodiments, but it is not intended to limit the technical solutions of the embodiments of the present invention.

[0062] In one exemplary embodiment, a method for adjusting the inner loop value is provided, such as Figure 4 As shown, the method includes the following stages:

[0063] Phase 1, Data Collection: Phase 1 includes the following steps:

[0064] Step 1: For 4G systems, initialize the inner loop conversion value of each subframe in the radio frame; for 5G systems, initialize the inner loop conversion factor of each time slot in the radio frame.

[0065] It should be noted that, in the embodiments of the present invention, both subframes and time slots can be referred to as time-domain scheduling units (or time-domain scheduling units) in a radio frame;

[0066] Step 2: Collect ACK / NACK information (excluding conservative scheduling) from each time-domain scheduling unit and count it separately in each time-domain scheduling unit.

[0067] Step 3: Determine whether the number of samples collected on each time-domain scheduling unit has reached the minimum threshold. If not, return to step 2 and continue the statistics; otherwise, calculate the BLER corresponding to each time-domain scheduling unit based on the ACK / NACK information collected on each time-domain scheduling unit, and obtain the BLER information set corresponding to each time-domain scheduling unit in the radio frame.

[0068] Phase 2, Data Processing;

[0069] Phase 3, Feature Extraction and Calculation; Phase 3 includes the following steps:

[0070] Step 4: Calculate the statistics reflecting the degree of divergence of the BLER information set based on the BLER information set corresponding to each time-domain scheduling unit in the radio frame.

[0071] Step 5: Determine whether the divergence of the corresponding BLER information set in each time-domain scheduling unit in the wireless frame is greater than a given threshold based on the statistics. If it is greater than the given threshold, perform differential conversion between time-domain scheduling units and proceed to Step 6. Otherwise, reuse the conversion factor corresponding to each current time-domain scheduling unit, apply this conversion factor to perform inner-loop conversion for the user in the corresponding time-domain scheduling unit, and proceed to Step 2, and clear the historical data of the last statistics (i.e., the ACK / NACK information collected last time).

[0072] Phase 4, Model Learning: Phase 4 includes the following steps:

[0073] Step 6: Classify each time-domain scheduling unit in the wireless frame so that the divergence of the BLER information corresponding to each time-domain scheduling unit in each class is less than a given threshold.

[0074] Step 7: Calculate the average BLER information for each category;

[0075] Step 8: Calculate the inner loop reduction factor for the corresponding class based on the target BLER information set by the system and the average BLER information calculated for each class;

[0076] Step 9: Based on the maintained historical inner loop conversion factor of the time-domain scheduling unit, the set to which the time-domain scheduling unit belongs, and the conversion factor corresponding to that set, update the inner loop conversion factor of each time-domain scheduling unit, thereby obtaining the inner loop conversion factor of each time-domain scheduling unit in the radio frame.

[0077] Phase 5, Model Application; Phase 5 includes the following steps:

[0078] Step 10: Output the inner loop conversion factor for each time-domain scheduling unit, and apply this factor to perform inner loop conversion for the user in the corresponding time-domain scheduling unit.

[0079] Step 11: Proceed to Step 2, clear the statistical information from the previous round, and begin the next round of learning.

[0080] In one exemplary embodiment, such as Figure 5 As shown, the data collection phase (i.e., the process of counting ACK / NACK numbers) specifically includes the following steps:

[0081] Step S501: Clear cached data;

[0082] Step S502: Determine whether the corresponding adjustment is a conservative scheduling; if yes, proceed to step S503; otherwise, proceed to step S504.

[0083] Step S503: Discard the data and proceed to step S505;

[0084] Step S504: Collect the corresponding ACK / NACK information for uplink and downlink separately according to time slots;

[0085] Step S505: Determine whether the sample size meets the requirements; if yes, proceed to stage 2 for data processing; otherwise, return to step S502.

[0086] In one exemplary embodiment, such as Figure 6 As shown, the data processing stage includes the following steps:

[0087] Step S601: Determine whether to perform model learning (i.e., determine whether to perform inter-frame differential conversion); if yes, proceed to step S603; otherwise, proceed to step S602.

[0088] Step S602: Obtain the A / N sample data corresponding to each time slot based on the collected data, and end the current data processing stage;

[0089] Step S603: Aggregate the statistical ACK / NACK information by user ID;

[0090] Step S604: Calculate the BLER for each user;

[0091] Step S605: Determine whether the BLER corresponding to each user is within the corresponding convergence interval. If yes, proceed to step S607; otherwise, proceed to step S606.

[0092] Step S606: Discard the data;

[0093] Step S607: Deliver the ACK / NACK data corresponding to each user to the set corresponding to the subframe to which the ACK / NACK belongs;

[0094] Step S608: Obtain ACK / NACK sample data corresponding to each time slot.

[0095] In one exemplary embodiment, such as Figure 7 As shown, the feature extraction and calculation stage includes the following steps:

[0096] Step S701: Obtain the A / N sample data corresponding to each time slot;

[0097] Step S702: Calculate the BLER corresponding to each time slot to obtain the set BLER_SET;

[0098] Step S703: Calculate the range of the set BLER_SET;

[0099] Step S704: Determine whether the range is greater than the given threshold TH; if yes, proceed to step S706; otherwise, proceed to step S705.

[0100] Step S705: Continue collecting data, and instead of modifying the existing model, use the existing model.

[0101] Step S706: Learn and correct the model.

[0102] In one exemplary embodiment, such as Figure 8 As shown, the model learning phase includes the following steps:

[0103] Step S801: Obtain the BLER corresponding to each time slot;

[0104] Step S802: Classify the time slots;

[0105] The following classification rules apply to the classification process:

[0106] The range within each class must be less than the threshold; the range of the union of any two classes must be greater than the threshold; there must be no intersection between the time-domain scheduling units (e.g., time slots) in any two classes; the union of all classes is the set of all time slots.

[0107] Step S803: Calculate the average BLER for each class;

[0108] Step S804: Calculate the correction value for each class; specifically, calculate the inner loop adjustment factor for each class based on the target BLER, the average BLER of each class, and the adjustment step size.

[0109] Step S805: Correct the model; specifically, calculate the inner loop adjustment factor for each time slot.

[0110] In one exemplary embodiment, such as Figure 9 As shown, the model application phase includes the following steps:

[0111] Step S901: Based on the model correction results, obtain the correction value corresponding to each time slot;

[0112] Step S902: Determine the time slot corresponding to the user scheduling (including but not limited to the corresponding air interface index);

[0113] Step S903: Determine the inner loop correction value corresponding to the time slot; wherein, the inner loop correction value is determined according to the index position, and inner loop correction is performed;

[0114] Step S904: Determine the user's scheduling based on the corrected inner and outer loops.

[0115] In an exemplary embodiment, a method for adjusting the inner loop value is provided. This method can be applied to a Long Term Evolution (LTE) system. Taking the time-domain scheduling unit in the above embodiment as a subframe in a radio frame of an LTE system as an example, the method includes the following steps:

[0116] Step 1: Initialize the inner loop conversion factor (i.e., the inner loop adjustment factor in the above embodiment) of each subframe of the radio frame as follows:

[0117] sf_factor i =0, i=1,2,…N,

[0118] Where sf_factor i The inner loop conversion factor corresponding to the i-th subframe is represented by N, and N represents the number of subframes included in a radio frame.

[0119] Step 2: Count the number of ACK / NACKs for each subframe, excluding conservative scheduling. The number of ACK / NACKs is maintained according to the subframe to which the ACK / NACK corresponds. For example, each ACK / NACK information (or sample) is maintained in the following format: User ID information carried in the ACK / NACK: Subframe to which the ACK / NACK belongs.

[0120] Step 3: Determine whether the number of ACK / NACK samples collected for each subframe has reached the sample count threshold. If not, return to Step 2 to continue counting; otherwise, proceed to the following steps:

[0121] Step 3.1: Aggregate the statistical ACK / NACK information by user ID and calculate the BLER for each user;

[0122] Step 3.2: Determine whether the BLER corresponding to each user is within the corresponding convergence interval (the convergence interval is a preset range, such as from 0.08 to 0.12); if it is, deliver the ACK / NACK data corresponding to each user to the set corresponding to the subframe to which the ACK / NACK belongs, and execute step 3.3; if it is not, discard the data of this user.

[0123] Step 3.3: Calculate the BLER corresponding to each subframe and collect the BLER information for each subframe to obtain the BLER set (BLER_SET):

[0124] BLER_SET = {BLER i |i=1,2,…N},

[0125] Among them, BLER i This represents the block error rate corresponding to the i-th subframe;

[0126] Step 4: Calculate the range D of the set BLER_SET:

[0127] D = max{BLER i |i=1,2,…N}-min{BLER i |i=1,2,…N};

[0128] The max{} function represents the maximum value, and the min{} function represents the minimum value.

[0129] Step 5: Determine if the range is greater than the given threshold TH (i.e., the preset threshold in the above embodiment); if D≥TH, determine to perform inter-frame differential conversion and proceed to step 6; otherwise, reuse the current subframe conversion factor sf_factor. i ,i=1,2,…N, and go to step 2, and clear the historical data of the last statistics;

[0130] Step 6: Divide the BLER_SET set into N subsets {set k |k=1,2,…N}, where set k For the i-th subframe out of N subframes, k = i;

[0131] Step 7: Calculate the average BLER for each of the N subsets. k In this embodiment,

[0132] BLERA k =BLER k k = 1, 2, ... N

[0133] Step 8: Calculate the inner loop reduction factor for each subset. k :

[0134] factor k =(BLER_tar-BLERA k *step,

[0135] Where BLER_tar is the preset target value for block error rate, and step is the preset value;

[0136] Step 9: Calculate the inner loop reduction factor for each subframe:

[0137] sf_factor i = (1-α)*sf'_factor i +α*factor k ,

[0138] Where α is the filtering factor and sf'_factor is the historical inner loop reduction factor;

[0139] Step 10: Output the inner loop conversion factor sf_factor for each subframe. i i = 1, 2, ... N, and apply the inner ring conversion factor of each subframe to convert the inner ring value of the corresponding subframe;

[0140] Step 11: Proceed to Step 2, clear the statistical information from the previous round, and proceed to the next round of learning.

[0141] In an exemplary embodiment, a method for adjusting the inner loop value is provided. This method can be applied to a 5G NR system. Taking the time-domain scheduling unit in the above embodiment as a time slot in a radio frame of a 5G NR system as an example, the method includes the following steps, wherein, when the time-domain scheduling unit is a time slot in a radio frame of a 5G NR system, the block error rate corresponding to each time-domain scheduling unit is actually the slot error rate corresponding to each time slot:

[0142] Step 1: Initialize the inner loop conversion factor for each time slot in the radio frame:

[0143] slot_factor i =0, i=1,2,…N

[0144] Among them, slot_factor i represents the conversion factor corresponding to the i-th time slot, and N represents the number of time slots in a radio frame;

[0145] Step 2: Count the number of ACK / NACK for each time slot except for conservative scheduling, and maintain the collected ACK / NACK data (or samples) by time slot, with each time slot counted separately;

[0146] Step 3: Determine if the number of ACK / NACK samples collected for each time slot has reached the minimum threshold (the minimum threshold can be 100,000, meaning that the number of ACK / NACK samples collected for each time slot needs to reach 100,000). If not, return to Step 2 to continue the statistics; otherwise, calculate the BLER corresponding to each time slot and collect the BLER information for each time slot to obtain the BLER set (BLER_SET).

[0147] BLER_SET = {BLER i |i=1,2,…N},

[0148] Among them, BLER i This represents the error rate of the i-th time slot;

[0149] Step 4: Calculate the range D of the set BLER_SET:

[0150] D = max{BLER i |i=1,2,…N}-min{BLER i |i=1,2,…N}

[0151] Step 5: Determine if the range is greater than the given threshold TH; if D≥TH, determine to perform inter-slot differential conversion and proceed to step 6; otherwise, reuse the current slot conversion factor slot_factor. i ,i=1,2,…N, and go to step 2, and clear the previous step 6 statistics, calculate the historical data of BLER_SE; divide the set into M subsets {set k The specific partitioning method is as follows: the time slot set St is initialized as a set of N time slots;

[0152] Step 6.1: Construct an N×N matrix A of absolute values ​​of BLER differences between time slots based on BLER_SET;

[0153] Step 6.2: Based on the constructed difference absolute value matrix A, starting from N, perform a dimension reduction search for submatrices, where each submatrix satisfies the following condition: each element is less than the threshold TH, and adding another dimension no longer satisfies the condition that each element in the submatrix is ​​less than the threshold TH; if there are multiple submatrices of the same dimension that satisfy this condition, select the submatrix with the smallest average value of all elements in the submatrix, and denote the selected submatrix as matrix B.

[0154] Step 6.3: Determine the time slot numbers corresponding to the rows of matrix B and form a subset set;

[0155] Step 6.4: Remove the time slots included in the subset set from the time slot set St to obtain the time slot set St. Construct matrix C based on the time slot error rate set corresponding to the time slot set St, and assign matrix C to A.

[0156] Step 6.5: Repeat steps 6.2 to 6.4 to finally obtain {set} k |k=1,2,…M};

[0157] Step 7: Calculate the average BLER for each of the M subsets:

[0158]

[0159] Among them, |set k | represents a set k The number of elements in;

[0160] Step 8: Calculate the inner loop reduction factor for each subset.

[0161] factor k =(BLER_tar-BLERA k *step;

[0162] Step 9: Calculate the inner loop reduction factor for each time slot, where, for time slot i, if i∈set k (i.e., the set to which slot i belongs is i∈set) k Update the inner loop reduction factor corresponding to the subframe according to the following formula:

[0163] slot_factor i = (1-α)*slot'_factor i +α*factor k

[0164] Where α is the filter factor, slot'_factor i Historical inner-loop conversion factor;

[0165] Step 10: Output the inner loop reduction factor (slot_factor) for each time slot. i i = 1, 2, ... N, and apply the factors of each subframe to perform inner loop conversion for the user in the corresponding time slot.

[0166] Step 11: Proceed to Step 2, clear the statistical information from the previous round, and begin the next round of learning.

[0167] In an exemplary embodiment, a method for adjusting the inner loop value is provided. This method can be applied to a 5G NR system. Taking the time-domain scheduling unit in the above embodiment as a time slot in a radio frame of a 5G NR system as an example, the method includes the following steps, wherein, when the time-domain scheduling unit is a time slot in a radio frame of a 5G NR system, the block error rate corresponding to each time-domain scheduling unit is actually the slot error rate corresponding to each time slot:

[0168] Step 1: Initialize the inner loop conversion factor for each time slot in the radio frame:

[0169] slot_factor i =0, i=1,2,…N,

[0170] Among them, slot_factor i The inner loop conversion factor corresponding to the i-th time slot is represented by N, and N represents the number of time slots in a radio frame.

[0171] Step 2: Count the number of ACK / NACK in each time slot. ACK / NACK in conservative scheduling is not counted, nor are NACK in the lowest-order scheduling or ACK in the highest-order scheduling. That is, the ACK / NACK count for each time slot does not include ACK / NACK in conservative scheduling, NACK in the lowest-order scheduling, or ACK in the highest-order scheduling. Maintain the collected ACK / NACK data by time slot, with ACK / NACK in each time slot counted separately.

[0172] Step 3: Determine if the number of ACK / NACK samples collected for each time slot has reached the minimum threshold (the minimum threshold can be 100,000, meaning that the number of ACK / NACK samples collected for each time slot needs to reach 100,000). If not, return to Step 2 to continue the statistics; otherwise, calculate the BLER corresponding to each time slot and collect the BLER set (BLER_SET) for each time slot.

[0173] BLER_SET = {BLER i |i=1,2,…N},

[0174] Among them, BLER iThis represents the error rate of the i-th time slot;

[0175] Step 4: Calculate the range D of the set BLER_SET:

[0176] D = max{BLER i |i=1,2,…N}-min{BLER i |i=1,2,…N};

[0177] Step 5: Determine if the range is greater than the given threshold; if D≥TH, determine to perform inter-slot differential conversion and proceed to step 6; otherwise, reuse the current slot conversion factor (slot_factor). i ,i=1,2,…N, and go to step 2, and clear the historical data of the last statistics;

[0178] Step 6: Divide the BLER_SET set into M subsets {set k The specific partitioning method for |k=1,2,…M} is as follows:

[0179] Step 6.1: Sort the time slot indices (e.g., time slot numbers) in ascending order of the BLER corresponding to all time slots;

[0180] Step 6.2: Starting from the smallest BLER among all BLERs corresponding to all time slots, and ending at the largest BLER + 0.1, divide all sorted BLERs into several intervals with a preset block error rate interval as the step size (the length of the last interval may be less than the fixed preset block error rate interval).

[0181] Step 6.3: Based on the several intervals obtained in Step 6.2, select several intervals that are left-closed and right-open, and classify the corresponding time slots according to the interval to which their corresponding BLER belongs, thereby obtaining the subset partition {set k |k=1,2,…M};

[0182] Step 7: Calculate the average BLER for each of the M subsets:

[0183]

[0184] Among them, |set k | represents a set k The number of elements in;

[0185] Step 8: Calculate the inner loop reduction factor for each subset:

[0186] factor k =(BLER_tar-BLERA k *step;

[0187] Step 9: Calculate the inner loop reduction factor for each time slot: where, for time slot i, if i∈set k (i.e., the set to which slot i belongs is i∈set) k Update the inner loop reduction factor corresponding to the subframe according to the following formula:

[0188] slot_factor i = (1-α)*slot'_factor i +α*factor k

[0189] Where α is the filter factor, slot'_factor i Historical inner-loop conversion factor;

[0190] Step 10: Output the inner loop reduction factor (slot_factor) for each time slot. i i = 1, 2, ... N, and apply the factors of each subframe to perform inner loop calculation for the user in the corresponding time slot;

[0191] Step 11: Proceed to Step 2, clear the statistical information from the previous round, and begin the next round of learning.

[0192] It should be noted that, in the above embodiments, the inner loop value adjustment method described in the above embodiments can be repeated multiple times. Specifically, when the range of block error rates corresponding to all time-domain scheduling units in the radio frame is less than a preset threshold, the current inner loop adjustment factor of each time-domain scheduling unit is determined to be the historical inner loop adjustment factor of each time-domain scheduling unit (optionally, the historical inner loop adjustment factor of each time-domain scheduling unit is kept unchanged, or the historical inner loop adjustment factor of each time-domain scheduling unit is updated to the current inner loop adjustment factor of each time-domain scheduling unit), and the previously collected ACK / NACK information is cleared, and the step of collecting ACK / NACK information corresponding to each time-domain scheduling unit and determining the block error rate corresponding to each time-domain scheduling unit is re-executed; when the range of block error rates corresponding to all time-domain scheduling units in the radio frame is greater than or equal to the preset threshold, after determining the current inner loop adjustment factor of each time-domain scheduling unit based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit, the historical inner loop adjustment factor of each time-domain scheduling unit is updated to the current inner loop adjustment factor of each time-domain scheduling unit.

[0193] Through the above embodiments, historical data in the network (i.e., ACK / NACK data corresponding to each time-domain scheduling unit) is used. This historical data can be converged data from the user's past history (excluding conservative scheduling data) or all historical data (regardless of convergence or non-convergence, but excluding conservative scheduling data). The BLER of each time slot is statistically analyzed; the range of BLER across all time slots is calculated; and the BLER difference between time slots is then determined to be greater than a certain threshold. If it is less, the existing conversion model (i.e., the inner-loop conversion factor corresponding to each time-domain scheduling unit) is used; otherwise, the conversion amount of each time slot is learned based on historical data, and the conversion model is corrected. Specifically, when correcting the conversion model, the BLER distribution of each time slot is analyzed, and the conversion factor is adjusted for all time slots. The time slots are grouped according to certain rules (i.e., subsets). For example, the range within each group must be less than a threshold, and the range of any two combined groups must be greater than the threshold. There is no intersection between the time-domain scheduling units (e.g., time slots) in any two groups, and the union of all groups is the set of all time slots. Then, the average BLER of each subset is calculated. Based on the calculated BLER, the set target BLER, and the corresponding adjustment step size, the inner loop conversion factor for each time slot is calculated. This inner loop conversion factor is then filtered with the historical inner loop conversion factors of each time-domain scheduling unit to obtain a new inner loop correction model (i.e., inner loop conversion factor) for each time-domain scheduling unit. This model is then applied to continue collecting historical data and continuously revising the model, ultimately achieving the best possible adaptation between the user's scheduling and the channel experienced by the user's time slot.

[0194] Based on the above embodiments, the technical problems in related technologies can be solved, such as differences in reference signals contained in different time slots or differences in demodulation performance of the same user in different uplink time slots due to factors such as uplink / downlink switching. Furthermore, it can solve the technical problem in traditional AMC technology where, because it is user-level, the difference in demodulation performance between different time slots cannot be quickly reflected, thus leading to reduced spectral efficiency. It can also solve the problem in inter-slot AMC technology where, due to the further discrete AMC learning sample data, it is difficult for small packet scheduling users to converge and for new AMCs to converge.

[0195] The above embodiments involve learning and correcting demodulation performance differences when there are differences in transmission / reception between time slots. Specifically, the differences in demodulation performance of users in different time slots are learned based on historical data, and the inner loop values ​​of different time slots are converted according to the learning results. This allows users to be scheduled differently in different time slots due to differences in demodulation performance, thereby improving spectrum efficiency.

[0196] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0197] This embodiment also provides an inner loop value adjustment device for implementing the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, hardware implementations, or a combination of software and hardware, are also possible and contemplated.

[0198] Figure 10 This is a structural block diagram of the inner loop value adjustment device according to an embodiment of the present invention, as shown below. Figure 10 As shown, the device includes a processing module 1002, wherein the processing module is configured to cyclically execute the following steps, wherein the historical inner loop adjustment factor of each time-domain scheduling unit in the radio frame is initialized to the initial inner loop adjustment factor of each time-domain scheduling unit:

[0199] Based on the ACK / NACK information corresponding to each time-domain scheduling unit, the block error rate corresponding to each time-domain scheduling unit is determined, wherein the radio frame includes N time-domain scheduling units, and N is a positive integer;

[0200] The current inner loop adjustment factor of each time-domain scheduling unit is determined based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit.

[0201] The inner loop value corresponding to each time-domain scheduling unit is adjusted based on the current inner loop adjustment factor of each time-domain scheduling unit.

[0202] By means of this invention, the following steps are executed cyclically, wherein the historical inner loop adjustment factor of each time-domain scheduling unit in the radio frame is initialized to the initial inner loop adjustment factor of each time-domain scheduling unit: the block error rate corresponding to each time-domain scheduling unit is determined according to the ACK / NACK information corresponding to each time-domain scheduling unit, wherein the radio frame includes N time-domain scheduling units, where N is a positive integer; the current inner loop adjustment factor of each time-domain scheduling unit is determined according to the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit; and the inner loop value corresponding to each time-domain scheduling unit is adjusted according to the current inner loop adjustment factor of each time-domain scheduling unit. Since the current inner loop adjustment factor of each time-domain scheduling unit is determined based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit, and the inner loop value corresponding to each time-domain scheduling unit is adjusted based on the current inner loop adjustment factor of each time-domain scheduling unit, the technical problem that demodulation differences between time-domain scheduling units cannot be quickly compensated by user-level AMC in related technologies can be solved. This achieves the technical effect of quickly compensating for demodulation differences between time slots and differentiating user scheduling based on demodulation performance differences in different time-domain scheduling units.

[0203] In an exemplary embodiment, the processing module is further configured to: determine the current inner loop adjustment factor T_factor of time-domain scheduling unit i according to the following formula when the range of the block error rates corresponding to the N time-domain scheduling units is greater than or equal to a preset threshold. i :T_factor i = (1-α)*T'_factor i +α*factor i Where 1≤i≤N, α is the filter factor, 0≤α≤1, and T'_factor i The historical inner loop adjustment factor of the time-domain scheduling unit i is factor. i =(BLER_tar-BLER) i )*step, BLER_tar is the preset target value for block error rate, BLER i Let be the block error rate corresponding to the time-domain scheduling unit i, and step be the adjustment step size, where step is greater than 0.

[0204] In an exemplary embodiment, the processing module is further configured to: when the range of the block error rates corresponding to the N time-domain scheduling units is greater than or equal to a preset threshold, divide the N time-domain scheduling units into M subsets according to the block error rate corresponding to each time-domain scheduling unit, wherein the range of the block error rates corresponding to the time-domain scheduling units in each of the M subsets is less than the preset threshold, M is a positive integer, and M is less than N; determine the inner loop adjustment factor corresponding to each subset according to the block error rate corresponding to the time-domain scheduling units in each subset; and determine the current inner loop adjustment factor of each time-domain scheduling unit according to the inner loop adjustment factor corresponding to each subset and the historical inner loop adjustment factor of each time-domain scheduling unit.

[0205] In an exemplary embodiment, determining the inner loop adjustment factor corresponding to each subset based on the block error rate corresponding to the time-domain scheduling unit of each subset includes: determining the inner loop adjustment factor (factor) corresponding to each subset according to the following formula. k :factor k =(BLER_tar-BLERA k )*step, where 1≤k≤M, BLER_tar is the preset target value for block error rate, BLERA k is the average block error rate corresponding to the time-domain scheduling unit in subset k, and step is the adjustment step size, and step is greater than 0.

[0206] In an exemplary embodiment, the processing module is further configured to: determine the current inner loop adjustment factor T_factor of the time-domain scheduling unit i according to the following formula. i :T_factor i = (1-α)*T'_factor i +α*factor k Wherein, the time-domain scheduling unit i belongs to the k-th subset of the M subsets, 1≤i≤N, α is the filtering factor, 0≤α≤1, and T'_factor i is the historical inner loop adjustment factor of the time-domain scheduling unit i.

[0207] In an exemplary embodiment, the processing module is further configured to: construct an N×N absolute difference matrix A based on the block error rate set corresponding to the N time-domain scheduling units, wherein each block error rate in the block error rate set corresponds one-to-one with each time-domain scheduling unit in the N time-domain scheduling units; repeat the following steps until the value c equals 1, wherein the current matrix is ​​initialized to the matrix A, the current time-domain scheduling unit set is initialized to the set composed of the N time-domain scheduling units, and the value c is initialized to N; search for a c×c target submatrix in the current matrix, wherein each element in the target submatrix is ​​less than the preset threshold; if the target submatrix is ​​found in the current matrix, set the time-domain scheduling units corresponding to each row of the target submatrix... The set of time-domain scheduling units is determined as a subset; the subset is deleted from the current time-domain scheduling unit set, and the current time-domain scheduling unit set after deleting the subset is determined as the current time-domain scheduling unit set; the absolute value matrix of the difference of (Nc)×(Nc) constructed according to the block error rate set corresponding to the current time-domain scheduling unit set is determined as the current matrix, wherein each block error rate in the block error rate set corresponding to the current time-domain scheduling unit set corresponds one-to-one with each time-domain scheduling unit in the current time-domain scheduling unit set; if the target submatrix is ​​not found in the current matrix, the difference obtained by subtracting 1 from the value c is determined as the value c; wherein, if the value c equals 1, the time-domain scheduling unit corresponding to each row in the current matrix is ​​determined as a subset.

[0208] In an exemplary embodiment, the processing module is further configured to: divide the N block error rates corresponding to the N time-domain scheduling units into M consecutive intervals, wherein each of the M intervals includes at least one block error rate, and the range of the block error rates in each interval is less than the preset threshold; divide the time-domain scheduling units among the N time-domain scheduling units that correspond to the block error rates included in interval k of the M intervals into subset k, thereby obtaining a total of M subsets, wherein 1≤k≤M.

[0209] In an exemplary embodiment, the processing module is further configured to: determine the current inner loop adjustment factor of each time-domain scheduling unit as the historical inner loop adjustment factor of each time-domain scheduling unit when the range of the error block rates corresponding to the N time-domain scheduling units is less than a preset threshold.

[0210] In an exemplary embodiment, the processing module is further configured to: after determining the current inner loop adjustment factor of each time-domain scheduling unit based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit, update the historical inner loop adjustment factor of each time-domain scheduling unit to the current inner loop adjustment factor of each time-domain scheduling unit if the range of the block error rates corresponding to the N time-domain scheduling units is greater than or equal to a preset threshold.

[0211] In one exemplary embodiment, the processing module is further configured to: determine the inner loop value d corresponding to the user in the time-domain scheduling unit i. i The current inner loop adjustment factor T_factor of the time-domain scheduling unit i i The sum; the inner ring value d i With the current inner loop adjustment factor T_factor i The sum of these values ​​is determined as the inner loop value adjusted by the user in the time-domain scheduling unit i.

[0212] In an exemplary embodiment, when the wireless frame is a wireless frame in a 4G communication system, each time-domain scheduling unit in the wireless frame corresponds one-to-one with each subframe in the wireless frame, where N is the number of subframes in the wireless frame; when the wireless frame is a wireless frame in a 5G communication system, each time-domain scheduling unit in the wireless frame corresponds one-to-one with each time slot in the wireless frame, where N is the number of time slots in the wireless frame.

[0213] It should be noted that the above modules can be implemented by software or hardware. For the latter, they can be implemented in the following ways, but are not limited to: all the above modules are located in the same processor; or, the above modules are located in different processors in any combination.

[0214] Embodiments of the present invention also provide a computer-readable storage medium storing a computer program, wherein the computer program is configured to perform the steps in any of the above method embodiments when executed.

[0215] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0216] Embodiments of the present invention also provide an electronic device including a memory and a processor, the memory storing a computer program and the processor being configured to run the computer program to perform the steps in any of the above method embodiments.

[0217] In one exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0218] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0219] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those described herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0220] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for adjusting the inner loop value, characterized in that, include: The following steps are executed cyclically, wherein the historical inner loop adjustment factor of each time-domain scheduling unit in the radio frame is initialized to the initial inner loop adjustment factor of each time-domain scheduling unit: Based on the ACK / NACK information corresponding to each time-domain scheduling unit, the block error rate corresponding to each time-domain scheduling unit is determined, wherein the radio frame includes N time-domain scheduling units, and N is a positive integer; The current inner loop adjustment factor of each time-domain scheduling unit is determined based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit. This includes: when the range of the block error rates corresponding to the N time-domain scheduling units is greater than or equal to a preset threshold, dividing the N time-domain scheduling units into M subsets based on the block error rates corresponding to each time-domain scheduling unit, wherein the range of the block error rates corresponding to the time-domain scheduling units in each of the M subsets is less than the preset threshold, and M is a positive integer, M less than N; determining the inner loop adjustment factor corresponding to each subset based on the block error rate corresponding to the time-domain scheduling units in each subset; and determining the current inner loop adjustment factor of each time-domain scheduling unit based on the inner loop adjustment factor corresponding to each subset and the historical inner loop adjustment factor of each time-domain scheduling unit. The inner loop value corresponding to each time-domain scheduling unit is adjusted based on the current inner loop adjustment factor of each time-domain scheduling unit.

2. The method according to claim 1, characterized in that, The step of determining the current inner loop adjustment factor of each time-domain scheduling unit based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit includes: If the range of the block error rates corresponding to the N time-domain scheduling units is greater than or equal to a preset threshold, the current inner loop adjustment factor of time-domain scheduling unit i is determined according to the following formula. : ， in, , For the filter factor, , For the time-domain scheduling unit Historical inner-loop adjustment factor , To preset the target value for the block error rate, The block error rate corresponding to the time-domain scheduling unit i. To adjust the step size, and Greater than 0.

3. The method according to claim 1, characterized in that, The step of determining the inner loop adjustment factor corresponding to each subset based on the block error rate corresponding to the time-domain scheduling unit of each subset includes: The inner loop adjustment factor for each subset is determined according to the following formula. : ， in, , To preset the target value for the block error rate, Let be the average block error rate corresponding to the time-domain scheduling units in subset k. To adjust the step size, and Greater than 0.

4. The method according to claim 3, characterized in that, The step of determining the current inner loop adjustment factor of each time-domain scheduling unit based on the inner loop adjustment factor corresponding to each subset and the historical inner loop adjustment factor of each time-domain scheduling unit includes: The current inner loop adjustment factor of time-domain scheduling unit i is determined according to the following formula. : ， Among them, the time-domain scheduling unit It belongs to the k-th subset of the M subsets. , For the filter factor, , For the time-domain scheduling unit Historical inner-loop adjustment factor.

5. The method according to claim 1, characterized in that, The step of dividing the N time-domain scheduling units into M subsets based on the block error rate corresponding to each time-domain scheduling unit includes: Based on the set of error rates corresponding to the N time-domain scheduling units, construct... The absolute value matrix A of the differences, wherein each block error rate in the block error rate set corresponds one-to-one with each of the N time-domain scheduling units; Repeat the following steps until the value c equals 1, wherein the current matrix is ​​initialized to matrix A, the current set of time-domain scheduling units is initialized to the set of the N time-domain scheduling units, and the value c is initialized to N: Search in the current matrix The target submatrix, wherein each element in the target submatrix is ​​less than the preset threshold; If the target submatrix is ​​found from the current matrix, the set of time-domain scheduling units corresponding to each row of the target submatrix is ​​determined as a subset; Remove the subset from the current time-domain scheduling unit set, and determine the current time-domain scheduling unit set after removing the subset as the current time-domain scheduling unit set; The set of block error rates corresponding to the current set of time-domain scheduling units will be constructed. The absolute value matrix of the difference is determined as the current matrix, wherein each block error rate in the block error rate set corresponding to the current time domain scheduling unit set corresponds one-to-one with each time domain scheduling unit in the current time domain scheduling unit set; If the target submatrix is ​​not found in the current matrix, the difference obtained by subtracting 1 from the value c is determined as the value c. Specifically, when the value c equals 1, the time-domain scheduling unit corresponding to each row in the current matrix is ​​determined as a subset.

6. The method according to claim 1, characterized in that, The step of dividing the N time-domain scheduling units into M subsets based on the block error rate corresponding to each time-domain scheduling unit includes: The N block error rates corresponding to the N time-domain scheduling units are divided into M consecutive intervals, wherein each of the M intervals includes at least one block error rate, and the range of the block error rates in each interval is less than the preset threshold. The time-domain scheduling units among the N time-domain scheduling units, those corresponding to the block error rates of interval k in the M intervals, are divided into subset k, resulting in a total of M subsets. .

7. The method according to claim 1, characterized in that, The step of determining the current inner loop adjustment factor of each time-domain scheduling unit based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit includes: If the range of the block error rates corresponding to the N time-domain scheduling units is less than a preset threshold, the current inner loop adjustment factor of each time-domain scheduling unit is determined as the historical inner loop adjustment factor of each time-domain scheduling unit.

8. The method according to claim 1, characterized in that, After determining the current inner loop adjustment factor of each time-domain scheduling unit based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit, the method further includes: If the range of the error rates corresponding to the N time-domain scheduling units is greater than or equal to a preset threshold, the historical inner loop adjustment factor of each time-domain scheduling unit is updated to the current inner loop adjustment factor of each time-domain scheduling unit.

9. The method according to claim 1, characterized in that, The step of adjusting the inner loop value corresponding to each time-domain scheduling unit based on the current inner loop adjustment factor of each time-domain scheduling unit includes: Determine the user in the time-domain scheduling unit Corresponding inner ring value With the time-domain scheduling unit Current inner-loop adjustment factor The sum of; The inner ring value With the current inner loop adjustment factor The sum of these values ​​is determined to be the sum of the values ​​of the user in the time-domain scheduling unit. Adjusted inner ring value.

10. The method according to any one of claims 1 to 9, characterized in that, When the wireless frame is a wireless frame in a 4G communication system, each time-domain scheduling unit in the wireless frame corresponds one-to-one with each subframe in the wireless frame, where N is the number of subframes in the wireless frame; when the wireless frame is a wireless frame in a 5G communication system, each time-domain scheduling unit in the wireless frame corresponds one-to-one with each time slot in the wireless frame, where N is the number of time slots in the wireless frame.

11. A device for adjusting the inner loop value, characterized in that, include: The processing module is configured to cyclically execute the following steps, wherein the historical inner loop adjustment factor of each time-domain scheduling unit in the radio frame is initialized to the initial inner loop adjustment factor of each time-domain scheduling unit: Based on the ACK / NACK information corresponding to each time-domain scheduling unit, the block error rate corresponding to each time-domain scheduling unit is determined, wherein the radio frame includes N time-domain scheduling units, and N is a positive integer; The current inner loop adjustment factor of each time-domain scheduling unit is determined based on the block error rate corresponding to each time-domain scheduling unit and the historical inner loop adjustment factor of each time-domain scheduling unit. This includes: when the range of the block error rates corresponding to the N time-domain scheduling units is greater than or equal to a preset threshold, dividing the N time-domain scheduling units into M subsets based on the block error rates corresponding to each time-domain scheduling unit, wherein the range of the block error rates corresponding to the time-domain scheduling units in each of the M subsets is less than the preset threshold, and M is a positive integer, M less than N; determining the inner loop adjustment factor corresponding to each subset based on the block error rate corresponding to the time-domain scheduling units in each subset; and determining the current inner loop adjustment factor of each time-domain scheduling unit based on the inner loop adjustment factor corresponding to each subset and the historical inner loop adjustment factor of each time-domain scheduling unit. The inner loop value corresponding to each time-domain scheduling unit is adjusted based on the current inner loop adjustment factor of each time-domain scheduling unit.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program is configured to perform the method described in any one of claims 1 to 10 when executed.

13. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to run the computer program to perform the method as described in any one of claims 1 to 10.

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