A 5G system scheduling method, device and equipment based on early warning coefficient

Abstract

The present application discloses a 5G system scheduling method based on an early warning coefficient, which obtains an evaluation of the quality of the business environment and whether the system resources are tight by setting an early warning coefficient in each business indicator. When negative indicators such as service delay and packet loss rate are higher than the corresponding early warning threshold or positive indicators such as throughput are lower than the corresponding early warning threshold, additional system resources are added. During the resource scheduling process, the system will automatically pay attention to the services that have repeatedly alarmed, and increase the scheduling level when appropriate, so as to ensure the fairness of each service. Thereby, the needs of typical scenario services such as eMMB, uRLLC and mMTC can be better met under the premise of multiple services being online, and matching is performed according to the service attributes of the services on the premise of ensuring the fairness of the scheduling algorithm to ensure the fairness of the entire scheduling scheme. In addition, the present application also provides a 5G system scheduling device and equipment based on an early warning coefficient, and its technical effects correspond to the technical effects of the above method.

Description

Technical Field

[0001] The present application relates to the field of mobile communication technology, and in particular to a 5G system scheduling method, device and equipment based on early warning coefficient. Background Art

[0002] Wireless resources in mobile communication systems are scarce, and 5G is no exception. To support the interconnection of everything, 5G provides three major application scenarios, including eMBB (Enhanced Mobile Broadband), uRLLC (Ultra Reliable and Low Latency Communication), and mMTC (Massive Machine Type Communication), which increasingly meet the needs of various differentiated services, from conventional communications to unmanned driving, AR / VR, etc.

[0003] As a key technology in 5G systems, resource scheduling can provide different levels of services based on the different granularity of service requirements of different users. Unlike 4G systems, 5G system scheduling needs to pay more attention to indicators such as throughput, latency, and reliability involved in the above scenarios. The current resource scheduling scheme does not fully meet the requirements for automatic matching of multiple key indicators such as throughput and latency in 5G hybrid scenarios, or affects uRLLC or mMTC services due to the high bandwidth occupancy required by eMBB scenarios. Summary of the invention

[0004] The purpose of this application is to provide a 5G system scheduling method, device and equipment based on early warning coefficient to solve the problem that the current resource scheduling scheme cannot guarantee fairness in the 5G system. The specific scheme is as follows:

[0005] In a first aspect, the present application provides a 5G system scheduling method based on an early warning coefficient, including:

[0006] For each user, the delay weight of each service of the user is calculated; based on the delay weights of all services of the user, the comprehensive delay weight of the user is calculated;

[0007] For each user, the packet loss weight of each service of the user is calculated; based on the packet loss weights of all services of the user, the comprehensive packet loss weight of the user is calculated;

[0008] Calculate the mathematical expectation of the application rate of all users; calculate the application rate weight of each user based on the current application rate of each user and the mathematical expectation of the application rate of all users:

[0009] The comprehensive weight of each user is calculated based on the comprehensive weight of delay, comprehensive weight of packet loss, and weight of application rate:

[0010] According to the number of delay warnings, packet loss warnings and application rate warnings of each user, the total number of warnings for the user is calculated; the comprehensive weight of the users whose total number of warnings is greater than or equal to the warning threshold is updated to 1;

[0011] The 5G scheduler is used to schedule users according to their comprehensive weights.

[0012] Optionally, calculating, for each user, a delay weight of each service of the user includes:

[0013] For each user, the delay weight of each service of the user is calculated according to the first formula, which is as follows:

[0014]

[0015] in, is the delay weight of the jth service of the i-th user, Dly i，j is the current waiting delay of the jth service of the i-th user, Wn_dly i，j is the delay warning coefficient of the jth service of the i-th user, Max_dly i，j is the maximum delay tolerance of the jth service of the ith user.

[0016] Optionally, calculating the comprehensive delay weight of the user according to the delay weights of all services of the user includes:

[0017] According to the delay weights of all services of the user, the comprehensive delay weight of the user is calculated according to the second formula, and the second formula is as follows:

[0018]

[0019] in, is the comprehensive delay weight of the i-th user, i m is the total number of transactions of the ith user, is the delay weight of the j-th service of the ith user.

[0020] Optionally, calculating, for each user, a packet loss weight of each service of the user includes:

[0021] For each user, the packet loss weight of each service of the user is calculated according to the third formula, which is as follows:

[0022]

[0023] in, is the packet loss weight of the jth service of the i-th user, Wn_drp i，j is the packet loss warning coefficient of the jth service of the i-th user, Max_drp i，j is the maximum packet loss tolerance of the jth service of the i-th user, Drp i，j is the current packet loss rate of the jth service of the ith user.

[0024] Optionally, calculating the comprehensive packet loss weight of the user according to the packet loss weights of all services of the user includes:

[0025] According to the packet loss weights of all services of the user, the comprehensive packet loss weight of the user is calculated according to the fourth formula, and the fourth formula is as follows:

[0026]

[0027] in, is the comprehensive weight of packet loss of the i-th user, i m is the total number of transactions of the ith user, is the packet loss weight of the j-th service of the ith user.

[0028] Optionally, calculating the mathematical expectation of the application rates of all users includes:

[0029] The mathematical expectation of the application rate of all users is calculated according to the fifth formula, which is as follows:

[0030]

[0031] Among them, Men Vlc is the mathematical expectation of the application rate of all users, n is the total number of users, Vlc i is the current application rate of the i-th user.

[0032] Optionally, the calculation of the application rate weight of each user according to the current application rate of each user and the mathematical expectation value of the application rates of all users includes:

[0033] According to the current application rate of each user and the mathematical expectation of the application rates of all users, the application rate weight of each user is calculated according to the sixth formula, which is as follows:

[0034]

[0035] in, is the application rate weight of the ith user, Men Vlc Vlc is the mathematical expectation of the application rate of all users. i is the current application rate of the ith user, Wn_vlci is the application rate warning coefficient of the i-th user.

[0036] Optionally, the calculating of the comprehensive weight of each user according to the comprehensive weight of delay, the comprehensive weight of packet loss, and the weight of application rate includes:

[0037] The product of the delay comprehensive weight, packet loss comprehensive weight, and application rate weight is calculated as the comprehensive weight of each user.

[0038] In a second aspect, the present application provides a 5G system scheduling device based on an early warning coefficient, comprising:

[0039] The delay comprehensive weight calculation module is used to calculate the delay weight of each service of each user for each user; and calculate the delay comprehensive weight of the user according to the delay weight of all services of the user;

[0040] The packet loss comprehensive weight calculation module is used to calculate the packet loss weight of each service of each user for each user; and calculate the packet loss comprehensive weight of the user according to the packet loss weights of all services of the user;

[0041] The application rate weight calculation module is used to calculate the mathematical expectation of the application rates of all users; the application rate weight of each user is calculated according to the current application rate of each user and the mathematical expectation of the application rates of all users;

[0042] A comprehensive weight calculation module is used to calculate the comprehensive weight of each user based on the delay comprehensive weight, packet loss comprehensive weight, and application rate weight;

[0043] The comprehensive weight update module is used to calculate the total number of warnings for each user based on the number of delay warnings, packet loss warnings and application rate warnings of each user; the comprehensive weight of the user whose total number of warnings is greater than or equal to the warning threshold is updated to 1;

[0044] The scheduling module is used to schedule users according to their comprehensive weights using the 5G scheduler.

[0045] In a third aspect, the present application provides a 5G system scheduling device based on an early warning coefficient, including:

[0046] Memory for storing computer programs;

[0047] A processor is used to execute the computer program to implement the 5G system scheduling method based on the early warning coefficient as described above.

[0048] The present application provides a 5G system scheduling method based on warning coefficient, including: for each user, calculating the delay weight of each service of the user, and calculating the comprehensive delay weight of the user according to the delay weight of all services of the user; for each user, calculating the packet loss weight of each service of the user, and calculating the comprehensive packet loss weight of the user according to the packet loss weight of all services of the user; calculating the mathematical expectation of the application rate of all users, and calculating the application rate weight of each user according to the current application rate of each user and the mathematical expectation of the application rate of all users; calculating the comprehensive weight of each user according to the delay comprehensive weight, the packet loss comprehensive weight, and the application rate weight; calculating the total number of warnings of the user according to the number of delay warnings, the number of packet loss warnings, and the number of application rate warnings of each user, and updating the comprehensive weight of users whose total number of warnings is greater than or equal to the warning threshold to 1; and scheduling users according to their comprehensive weights by using a 5G scheduler.

[0049] It can be seen that this method obtains an evaluation of the quality of the business environment and whether the system resources are tight by setting up early warning coefficients in each business indicator. When negative indicators such as service delay and packet loss rate are higher than the corresponding early warning threshold or positive indicators such as throughput are lower than the corresponding early warning threshold, additional system resources are added. During the resource scheduling process, the system will automatically pay attention to the services that have repeatedly issued alarms, and increase the scheduling level when appropriate to ensure the fairness of each service. It can better meet the needs of typical scenario services such as eMBB, uRLLC and mMTC under the premise of multiple services online, and match them according to the service attributes of the services on the premise of ensuring the fairness of the scheduling algorithm to ensure the fairness of the entire scheduling plan.

[0050] In addition, the present application also provides a 5G system scheduling device and equipment based on the early warning coefficient, and its technical effects correspond to the technical effects of the above-mentioned method, which will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present application or the technical solutions of the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0052] Figure 1 This is a flowchart of Embodiment 1 of the 5G system scheduling method based on the early warning coefficient provided in this application;

[0053] Figure 2 This is a flowchart of Embodiment 2 of the 5G system scheduling method based on the early warning coefficient provided in this application;

[0054] Figure 3 A throughput comparison chart of the 5G system scheduling method based on early warning coefficient provided in this application and other algorithms;

[0055] Figure 4 This is a comparison chart of the packet loss rate between the 5G system scheduling method based on the early warning coefficient provided by this application and other algorithms;

[0056] Figure 5 This is a comparison chart of the scheduling fairness of the 5G system scheduling method based on the early warning coefficient provided by this application and other algorithms;

[0057] Figure 6 This is a schematic diagram of an embodiment of a 5G system scheduling device based on early warning coefficient provided in this application. DETAILED DESCRIPTION

[0058] In order to enable those skilled in the art to better understand the present application, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0059] The following is an introduction to the first embodiment of the 5G system scheduling method based on the early warning coefficient provided by the present application. Figure 1 , Embodiment 1 includes:

[0060] S11. For each user, calculate the delay weight of each service of the user; calculate the comprehensive delay weight of the user according to the delay weights of all services of the user;

[0061] Specifically, for each user, the delay weight of each service of the user is calculated according to the first formula, and the first formula is as follows:

[0062]

[0063] in, is the delay weight of the jth service of the i-th user, Dly i，j is the current waiting delay of the jth service of the i-th user, Wn_dly i，j is the delay warning coefficient of the jth service of the i-th user, Max_dly i，j is the maximum delay tolerance of the jth service of the ith user.

[0064] Afterwards, according to the delay weights of all services of the user, the comprehensive delay weight of the user is calculated according to the second formula, and the second formula is as follows:

[0065]

[0066] in, is the comprehensive delay weight of the i-th user, i m is the total number of transactions of the ith user, is the delay weight of the j-th service of the ith user.

[0067] S12. For each user, calculate the packet loss weight of each service of the user; and calculate the comprehensive packet loss weight of the user according to the packet loss weights of all services of the user;

[0068] Specifically, for each user, the packet loss weight of each service of the user is calculated according to the third formula, and the third formula is as follows:

[0069]

[0070] in, is the packet loss weight of the jth service of the i-th user, Wn_drp i，j is the packet loss warning coefficient of the jth service of the i-th user, Max_drp i，j is the maximum packet loss tolerance of the jth service of the i-th user, Drp i，j is the current packet loss rate of the jth service of the ith user.

[0071] Afterwards, according to the packet loss weights of all services of the user, the comprehensive packet loss weight of the user is calculated according to the fourth formula, and the fourth formula is as follows:

[0072]

[0073] in, is the comprehensive weight of packet loss of the i-th user, i m is the total number of transactions of the ith user, is the packet loss weight of the j-th service of the ith user.

[0074] S13, calculating the mathematical expectation of the application rates of all users; calculating the application rate weight of each user according to the current application rate of each user and the mathematical expectation of the application rates of all users;

[0075] Specifically, the mathematical expectation value of the application rate of all users is calculated according to the fifth formula, and the fifth formula is as follows:

[0076]

[0077] Among them, Men Vlc is the mathematical expectation of the application rate of all users, n is the total number of users, Vlc i is the current application rate of the i-th user.

[0078] Afterwards, the application rate weight of each user is calculated according to the sixth formula based on the current application rate of each user and the mathematical expectation value of the application rates of all users. The sixth formula is as follows:

[0079]

[0080] in, is the application rate weight of the ith user, Men Vlc Vlc is the mathematical expectation of the application rate of all users. i is the current application rate of the ith user, Wn_vlc i is the application rate warning coefficient of the i-th user.

[0081] S14. Calculate the comprehensive weight of each user according to the comprehensive weight of delay, the comprehensive weight of packet loss, and the weight of application rate;

[0082] As a specific implementation method, the product of the delay comprehensive weight, the packet loss comprehensive weight, and the application rate weight is calculated as the comprehensive weight of each user.

[0083] S15, calculating the total number of warnings for each user based on the number of delay warnings, packet loss warnings, and application rate warnings; updating the comprehensive weight of users whose total number of warnings is greater than or equal to the warning threshold to 1;

[0084] S16. Use the 5G scheduler to schedule users according to their comprehensive weights.

[0085] The following is a detailed introduction to Example 2 of the 5G system scheduling method based on the early warning coefficient provided in this application.

[0086] In the second embodiment, the 5G system includes n users Usr total = {Usr1, Usr2, ..., Usr n}, each user Usr i ∈Usr t。tal Run on m Business, Svr i，j is the jth service of the i-th user,

[0087] Based on the 5G system described above, the resource scheduling process of the second embodiment mainly includes five steps, namely, delay attention, packet loss rate calculation, rate marking, early warning monitoring, and scheduling implementation. The overall implementation process is as follows: Figure 2 As shown, each step is introduced below.

[0088] S21, delayed attention;

[0089] S21-1, set the first basic table, the first basic table includes typical applications, delay, packet loss rate; for each service Svr of each user at the current moment i，j , set its delay warning coefficient Wn_dly i，j , Maximum delay tolerance Max_dly i，j And the current queue waiting delay Dly i，j ;

[0090] S21-2. Calculate service delay weight For User Usr i , calculate its delay comprehensive weight

[0091] S22, packet loss rate calculation;

[0092] S22-1. For each service Svr of each user at the current moment i，j , set its packet loss warning coefficient Wn_drp i，j , Maximum packet loss tolerance Max_drp i，j And the current packet loss rate Drp i，j ;

[0093] S22-2. Calculate the service packet loss weight For User Usr i , calculate the comprehensive weight of packet loss

[0094] S23, applying for rate mark;

[0095] S23-1. For each user at the current moment, set its rate warning coefficient Wn_vlc i , the current requested rate Vlc i ; Calculate the mathematical expectation of the application rate of all current users

[0096] S23-2. For user Usr i , calculate its current application rate weight

[0097] S24, early warning monitoring;

[0098] S24-1. Calculate Usr per user according to the following formula i The comprehensive weight of:

[0099] , then δ i Arrange in descending order to obtain a new user set Sch = {Usr k , k=1, 2...n};

[0100] S24-2. Set the system's warning threshold For each user in the user set Sch, set the delay warning times τ_dly k ,,Packet loss warning times τ_drp k And the number of application rate warnings τ_vlc k , calculate the total number of warnings for this user τ k =τ_dly k +τ_drp k +τ_vlc k ; will satisfy The user comprehensive weight δ k Set to 1.

[0101] S25, scheduling implementation;

[0102] For the set Sch, according to the updated δ k Rearrange in descending order; at the current moment, press δ k The scheduling priority sends each user to the 5G scheduler for scheduling.

[0103] The implementation process of this embodiment is specifically described below by taking n=5 as an example. The 5G typical service indicators are shown in the first basic table of Table 1:

[0104] Table 1

[0105]

[0106]

[0107] The services provided by each user are shown in Table 2:

[0108] Table 2

[0109]

[0110] The basic data are shown in Table 3:

[0111] Table 3

[0112] project data Operating frequency (GHz) 2.6 Operating bandwidth (MHz) 100 Total number of cell RBs 273 Warning threshold 5 Delay warning coefficient 0.6 Packet loss warning coefficient 0.7 Rate warning factor 0.8

[0113] This embodiment specifically includes the following steps:

[0114] Step 1: Delayed attention;

[0115] Calculate the service delay weight according to service table 2 and basic data table 3 For User Usr i , calculate its delay comprehensive weight

[0116] Step 2: Calculate the packet loss rate;

[0117] Calculate the service packet loss weight For User Usr i , calculate the comprehensive weight of packet loss

[0118] Step 3: rate marking;

[0119] Calculate the mathematical expectation of the application rate of all current usersMen Vlc =12.2Mbps; for user Usr i , calculate its current application rate weight

[0120] Step 4: Early warning monitoring;

[0121] Calculate Usr per user i The comprehensive weight δ i ={0.78, 0.5, 0.37, 0.45, 0.23}; change δ i Arrange in descending order to obtain a new user set Sch = {Usr k , k=1,2...n}; According to Table 2, it satisfies The user set is {Usr5}, and its comprehensive weight δ5 is changed from the original 0.23 to 1.

[0122] Step 5: Scheduling implementation;

[0123] The set Sch is based on the updated δ k Rearrange in descending order to obtain {1.0, 0.78, 0.5, 0.45, 0.37}, and the corresponding user set is {Usr5, Usr1, Usr2, Usr4, Usr3}. Each user is sent to the 5G scheduler for scheduling in this order.

[0124] The resource scheduling method of this embodiment is simulated on the MATLAB platform. A certain number of users are randomly added and random service configuration is performed. The overall load of the 5G base station gNB is kept at about 50%. One of the users is forced to issue an over-threshold warning. The obtained throughput, packet loss rate and fairness are shown in the attached figure. Figures 3 to 5 shown.

[0125] like Figure 3 As shown, the resource scheduling method of this embodiment will increase the scheduling probability of users whose application rate is lower than the warning coefficient, and generally increase the total throughput of users. The maximum weight delay priority algorithm modified by M-LWDF is a real-time algorithm. It can be seen from the simulation that the throughput of the resource scheduling method of this embodiment is slightly higher than that of M-LWDF.

[0126] like Figure 4As shown, the packet loss rate of the resource scheduling method of this embodiment is between RR and M-LWDF, and the reason is that there is an early warning of the packet loss rate; SJF prioritizes scheduling short jobs, so the packet loss rate remains high; delay and packet loss rate are both negative indicators, and the performance comparison of several target algorithms is similar, which is not listed in detail here.

[0127] like Figure 5 As shown, the fairness of several algorithms is still better than RR, followed by the resource scheduling method of this embodiment, followed by M-LWDF and SJF. This shows that the resource scheduling method of this embodiment is more fair to each user as a whole, ensuring fair distribution of system resources among each user.

[0128] The following is an introduction to the 5G system scheduling method based on the warning coefficient provided in an embodiment of the present application. The 5G system scheduling device based on the warning coefficient described below and the 5G system scheduling method based on the warning coefficient described above can be referenced to each other.

[0129] like Figure 6 As shown, the 5G system scheduling device based on the early warning coefficient of this embodiment includes:

[0130] The delay comprehensive weight calculation module 61 is used to calculate the delay weight of each service of each user for each user; and calculate the delay comprehensive weight of the user according to the delay weights of all services of the user;

[0131] The packet loss comprehensive weight calculation module 62 is used to calculate the packet loss weight of each service of each user for each user; and calculate the packet loss comprehensive weight of the user according to the packet loss weights of all services of the user;

[0132] The application rate weight calculation module 63 is used to calculate the mathematical expectation of the application rates of all users; the application rate weight of each user is calculated according to the current application rate of each user and the mathematical expectation of the application rates of all users;

[0133] A comprehensive weight calculation module 64 is used to calculate the comprehensive weight of each user according to the delay comprehensive weight, the packet loss comprehensive weight and the application rate weight;

[0134] The comprehensive weight updating module 65 is used to calculate the total number of warnings for each user according to the number of delay warnings, packet loss warnings and application rate warnings of the user; and update the comprehensive weight of the user whose total number of warnings is greater than or equal to the warning threshold to 1;

[0135] The scheduling module 66 is used to schedule users according to their comprehensive weights using the 5G scheduler.

[0136] The 5G system scheduling device based on the warning coefficient of this embodiment is used to implement the aforementioned 5G system scheduling method based on the warning coefficient. Therefore, the specific implementation method of the device can be seen in the implementation example part of the 5G system scheduling method based on the warning coefficient in the previous text, and will not be elaborated here.

[0137] In addition, the present application also provides a 5G system scheduling device based on early warning coefficient, including:

[0138] Memory for storing computer programs;

[0139] A processor is used to execute the computer program to implement the 5G system scheduling method based on the early warning coefficient as described above.

[0140] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0141] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0142] The above is a detailed introduction to the scheme provided by the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A 5G system scheduling method based on early warning coefficient, characterized in that: include: For each user, calculate the delay weight of each service of the user; Calculate the comprehensive delay weight of the user according to the delay weights of all services of the user; For each user, the packet loss weight of each service of the user is calculated; based on the packet loss weights of all services of the user, the comprehensive packet loss weight of the user is calculated; Calculate the mathematical expectation of the application rates of all users; calculate the application rate weight of each user based on the current application rate of each user and the mathematical expectation of the application rates of all users; Calculate the comprehensive weight of each user based on the comprehensive weight of delay, comprehensive weight of packet loss, and weight of application rate; Calculate the total number of warnings for each user based on the number of delay warnings, packet loss warnings, and application rate warnings. Update the comprehensive weight of users whose total number of warnings is greater than or equal to the warning threshold to 1; Use the 5G scheduler to schedule users according to their comprehensive weights; The step of calculating the delay weight of each service of each user includes: For each user, the delay weight of each service of the user is calculated according to the first formula, which is as follows: in, is the delay weight of the jth service of the i-th user, Dly i，j is the current waiting delay of the jth service of the i-th user, Wn_dly i，j is the delay warning coefficient of the jth service of the i-th user, Max_dly i，j is the maximum delay tolerance of the jth service of the ith user.

2. The method according to claim 1, characterized in that The calculating the delay comprehensive weight of the user according to the delay weights of all services of the user includes: According to the delay weights of all services of the user, the comprehensive delay weight of the user is calculated according to the second formula, and the second formula is as follows: in, is the comprehensive delay weight of the i-th user, i m is the total number of transactions of the ith user, is the delay weight of the j-th service of the ith user.

3. The method according to claim 1, characterized in that The step of calculating the packet loss weight of each service of each user includes: For each user, the packet loss weight of each service of the user is calculated according to the third formula, which is as follows: in, is the packet loss weight of the jth service of the i-th user, Wn_drp i，j is the packet loss warning coefficient of the jth service of the i-th user, Max_drp i，j is the maximum packet loss tolerance of the jth service of the i-th user, Drp i，j is the current packet loss rate of the jth service of the ith user.

4. The method according to claim 3, characterized in that The calculating the comprehensive packet loss weight of the user according to the packet loss weights of all services of the user includes: According to the packet loss weights of all services of the user, the comprehensive packet loss weight of the user is calculated according to the fourth formula, and the fourth formula is as follows: in, is the comprehensive weight of packet loss of the i-th user, i m is the total number of transactions of the ith user, is the packet loss weight of the j-th service of the ith user.

5. The method according to claim 1, characterized in that The calculating of the mathematical expectation of the application rates of all users includes: The mathematical expectation of the application rate of all users is calculated according to the fifth formula, which is as follows: Among them, Men Vlc is the mathematical expectation of the application rate of all users, n is the total number of users, Vlc i is the current application rate of the i-th user.

6. The method according to claim 5, characterized in that The step of calculating the application rate weight of each user according to the current application rate of each user and the mathematical expectation of the application rates of all users includes: According to the current application rate of each user and the mathematical expectation of the application rates of all users, the application rate weight of each user is calculated according to the sixth formula, which is as follows: in, is the application rate weight of the ith user, Men Vlc Vlc is the mathematical expectation of the application rate of all users. i is the current application rate of the ith user, Wn_vlc i is the application rate warning coefficient of the i-th user.

7. The method according to any one of claims 1 to 6, characterized in that: The method of calculating the comprehensive weight of each user according to the comprehensive weight of delay, the comprehensive weight of packet loss and the weight of application rate includes: The product of the delay comprehensive weight, packet loss comprehensive weight, and application rate weight is calculated as the comprehensive weight of each user.

8. A 5G system scheduling device based on early warning coefficient, characterized in that: include: A delay comprehensive weight calculation module is used to calculate the delay weight of each service of each user for each user; Calculate the comprehensive delay weight of the user according to the delay weights of all services of the user; The packet loss comprehensive weight calculation module is used to calculate the packet loss weight of each service of each user for each user; and calculate the packet loss comprehensive weight of the user according to the packet loss weights of all services of the user; The application rate weight calculation module is used to calculate the mathematical expectation of the application rates of all users; the application rate weight of each user is calculated according to the current application rate of each user and the mathematical expectation of the application rates of all users; A comprehensive weight calculation module is used to calculate the comprehensive weight of each user based on the delay comprehensive weight, packet loss comprehensive weight, and application rate weight; A comprehensive weight update module is used to calculate the total number of warnings for each user based on the number of delay warnings, packet loss warnings and application rate warnings for each user; Update the comprehensive weight of users whose total number of warnings is greater than or equal to the warning threshold to 1; A scheduling module, used to schedule users according to their comprehensive weights using a 5G scheduler; The step of calculating the delay weight of each service of each user includes: For each user, the delay weight of each service of the user is calculated according to the first formula, which is as follows: in, is the delay weight of the jth service of the i-th user, Dly i，j is the current waiting delay of the jth service of the i-th user, Wn_dly i，j is the delay warning coefficient of the jth service of the i-th user, Max_dly i，j is the maximum delay tolerance of the jth service of the ith user.

9. A 5G system scheduling device based on early warning coefficient, characterized in that: include: Memory for storing computer programs; A processor, configured to execute the computer program to implement the 5G system scheduling method based on the early warning coefficient as described in any one of claims 1 to 7.

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