Cell congestion state determination method and apparatus, storage medium, and electronic device

Abstract

The present disclosure relates to the technical field of mobile communications, and relates to a cell congestion state determination method and apparatus, a storage medium, and an electronic device. The method comprises: counting the number of first active users in an RRC connected state and the number of second active users in an RRC inactive state in a target cell; and determining the congestion state of the target cell on the basis of the number of first active users and the number of second active users. The present disclosure improves the accuracy of a congestion state determination result of a target cell.

Description

Cell congestion state determination method and device, storage medium, and electronic device

[0001] Cross-reference to Related Applications

[0002] The present disclosure claims priority to the application file with the application number of 202411067313.9, the application date of 2024-08-05, and the application name of Cell congestion state determination method and device, storage medium, and electronic device, the entire content of which is incorporated herein by reference. TECHNICAL FIELD

[0003] Embodiments of the present disclosure relate to the field of mobile communication technology, in particular to a cell congestion state determination method, a cell congestion state determination device, a computer readable storage medium, and an electronic device. BACKGROUND

[0004] Currently, the method for determining cell congestion in network optimization is usually to monitor the number of active users in the cell and the throughput of the users to evaluate the congestion degree of the cell, and when the number of active users exceeds a certain number, the cell is determined to be a service congestion cell.

[0005] However, this method does not take into account non-activated small data transmission, which results in low accuracy of the determination result of the congestion state.

[0006] It should be noted that the information disclosed in the above background section is only used to strengthen the understanding of the background of the present disclosure, and therefore can include information that does not constitute related art known to those of ordinary skill in the art. SUMMARY

[0007] The purpose of the present disclosure is to provide a cell congestion state determination method, a cell congestion state determination device, a computer readable storage medium, and an electronic device, thereby at least partially overcoming the problem of low accuracy of the determination result of the congestion state caused by the limitations and defects of the related art.

[0008] According to one aspect of the present disclosure, a cell congestion state determination method is provided, comprising:

[0009] counting the number of first active users in an RRC connected state and the number of second active users in an RRC inactive state in a target cell;

[0010] determining the congestion state of the target cell according to the number of first active users and the number of second active users.

[0011] In an example embodiment of the present disclosure, the second number of active users has less influence on the congestion state of the target cell than the first number of active users.

[0012] In an example embodiment of the present disclosure, determining the congestion state of the target cell according to the first number of active users and the second number of active users comprises:

[0013] increasing a first weighting factor of the first number of active users and decreasing a second weighting factor of the second number of active users;

[0014] performing weighted summation on the first number of active users and the first weighting factor, and the second number of active users and the second weighting factor, and determining the congestion state of the target cell according to a result of the weighted summation.

[0015] In an example embodiment of the present disclosure, the sum of the first weighting factor and the second weighting factor is 1, and the first weighting factor is greater than the second weighting factor.

[0016] In an example embodiment of the present disclosure, the first weighting factor and the second weighting factor are obtained by:

[0017] obtaining a first original weighting coefficient of the RRC connected state and a second original weighting coefficient of the RRC inactive state;

[0018] using the first original weighting coefficient as the first weighting factor of the RRC connected state, and using the second original weighting coefficient as the second weighting factor of the RRC inactive state; or

[0019] performing adaptive adjustment on the first original weighting coefficient and the second original weighting coefficient to obtain the first weighting factor and the second weighting factor.

[0020] In an example embodiment of the present disclosure, performing adaptive adjustment on the first original weighting coefficient and the second original weighting coefficient to obtain the first weighting factor and the second weighting factor comprises:

[0021] obtaining other network performance parameters of the target cell, and determining a first weight adjustment reference coefficient and a second weight adjustment reference coefficient according to the other network performance parameters;

[0022] performing adaptive adjustment on the first original weighting coefficient according to the first weight adjustment reference coefficient to obtain the first weighting factor;

[0023] performing adaptive adjustment on the second original weighting coefficient according to the second weight adjustment reference coefficient to obtain the second weighting factor.

[0024] In an example embodiment of the present disclosure, the other network performance parameters include uplink throughput and downlink throughput; or uplink PRB utilization and downlink PRB utilization; or uplink throughput, downlink throughput, uplink PRB utilization and downlink PRB utilization.

[0025] The uplink throughput includes a first uplink throughput in an RRC connected state and a second uplink throughput in an RRC inactive state.

[0026] The downlink throughput includes a first downlink throughput in an RRC connected state and a second downlink throughput in an RRC inactive state.

[0027] The uplink PRB utilization includes a first uplink PRB utilization in an RRC connected state and a second uplink PRB utilization in an RRC inactive state.

[0028] The downlink PRB utilization includes a first downlink PRB utilization in an RRC connected state and a second downlink PRB utilization in an RRC inactive state.

[0029] In an example embodiment of the present disclosure, determining the first weight adjustment reference coefficient according to the other network performance parameters includes:

[0030] determining the first weight adjustment reference coefficient according to the first uplink throughput and the first downlink throughput; or

[0031] determining the first weight adjustment reference coefficient according to the first uplink PRB utilization and the first downlink PRB utilization; or

[0032] determining the first weight adjustment reference coefficient according to the first uplink throughput, the first downlink throughput, the first uplink PRB utilization and the first downlink PRB utilization.

[0033] In an example embodiment of the present disclosure, determining the first weight adjustment reference coefficient according to the first uplink throughput, the first downlink throughput, the first uplink PRB utilization and the first downlink PRB utilization includes:

[0034] configuring the first uplink throughput, the first downlink throughput, the first uplink PRB utilization and the first downlink PRB utilization with a first uplink throughput weight, a first downlink throughput weight, a first uplink PRB utilization weight and a first downlink PRB utilization weight;

[0035] weighting and summing the first uplink throughput and the first uplink throughput weight, the first downlink throughput and the first downlink throughput weight, the first uplink PRB utilization and the first uplink PRB utilization weight, and the first downlink PRB utilization and the first downlink PRB utilization weight, to obtain the first weight adjustment reference coefficient.

[0036] In an exemplary embodiment of the present disclosure, determining the second weight adjustment reference coefficient according to the other network performance parameters comprises:

[0037] determining the second weight adjustment reference coefficient according to the second uplink throughput and the second downlink throughput; or

[0038] determining the second weight adjustment reference coefficient according to the second uplink PRB utilization and the second downlink PRB utilization; or

[0039] determining the second weight adjustment reference coefficient according to the second uplink throughput, the second downlink throughput, the second uplink PRB utilization and the second downlink PRB utilization.

[0040] In an exemplary embodiment of the present disclosure, determining the second weight adjustment reference coefficient according to the second uplink throughput, the second downlink throughput, the second uplink PRB utilization and the second downlink PRB utilization comprises:

[0041] configuring the second uplink throughput, the second downlink throughput, the second uplink PRB utilization and the second downlink PRB utilization with a second uplink throughput weight, a second downlink throughput weight, a second uplink PRB utilization weight and a second downlink PRB utilization weight;

[0042] weighting and summing the second uplink throughput and the second uplink throughput weight, the second downlink throughput and the second downlink throughput weight, the second uplink PRB utilization and the second uplink PRB utilization weight, and the second downlink PRB utilization and the second downlink PRB utilization weight, to obtain the second weight adjustment reference coefficient.

[0043] In an exemplary embodiment of the present disclosure, determining the congestion state of the target cell according to the weighting and summing result comprises:

[0044] determining whether the weighting and summing result is greater than a preset congestion threshold value;

[0045] determining that the target cell is in a congestion state when it is determined that the weighting and summing result is greater than the preset congestion threshold value;

[0046] determining that the target cell is in a normal communication state when it is determined that the weighting and summing result is less than or equal to the preset congestion threshold value.

[0047] In an example embodiment of the present disclosure, the method for determining the cell congestion state further comprises:

[0048] When it is determined that the target cell is in a congestion state, generating congestion alarm information according to the target active user number.

[0049] According to an aspect of the present disclosure, there is provided a device for determining a cell congestion state, comprising:

[0050] an active user number counting module configured to count a first active user number in an RRC connected state and a second active user number in an RRC inactive state in a target cell;

[0051] a congestion state determining module configured to determine a congestion state of the target cell according to the first active user number and the second active user number.

[0052] According to an aspect of the present disclosure, there is provided a computer readable storage medium having stored thereon a computer program, which, when executed by a processor, implements the method for determining a cell congestion state according to any one of the preceding embodiments.

[0053] According to an aspect of the present disclosure, there is provided an electronic device, comprising:

[0054] a processor; and

[0055] a memory configured to store executable instructions of the processor;

[0056] wherein the processor is configured to implement the method for determining a cell congestion state according to any one of the preceding embodiments by executing the executable instructions.

[0057] The method for determining a cell congestion state provided by the embodiments of the present disclosure counts a first active user number in an RRC connected state and a second active user number in an RRC inactive state in a target cell, and then determines a congestion state of the target cell according to the first active user number and the second active user number. In the process of determining the congestion state of the target cell, not only the first active user number in the RRC connected state is considered, but also the second active user number in the RRC inactive state is considered. Thus, the problem that the accuracy of the determination result of the congestion state is low due to the fact that the small data transmission in the inactive state is not considered in the related art is solved, and the accuracy of the determination result of the congestion state of the target cell is improved.

[0058] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and are not limiting to the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0059] The accompanying drawings, which are incorporated herein and form a part of the specification, illustrate embodiments consistent with the present disclosure and, together with the description, further serve to explain the principles of the present disclosure. It is to be understood that the drawings are designed solely for purposes of illustration to be used in conjunction with the description. It is to be understood that the drawings are designed solely for purposes of illustration and to aid in the understanding of the present disclosure, and are, therefore, not to scale. In the drawings:

[0060] FIG. 1 schematically shows a flowchart of a method for determining a cell congestion state according to an example embodiment of the present disclosure.

[0061] FIG. 2 schematically shows an example diagram of a system for determining a cell congestion state according to an example embodiment of the present disclosure.

[0062] FIG. 3 schematically shows an example diagram of a scenario of a target cell and a base station according to an example embodiment of the present disclosure.

[0063] FIG. 4 schematically shows a flowchart of a method for adaptively adjusting a first original weighting factor and a second original weighting factor to obtain a first weighting factor and a second weighting factor according to an example embodiment of the present disclosure.

[0064] FIG. 5 schematically shows an example diagram of other network performance parameters according to an example embodiment of the present disclosure.

[0065] FIG. 6 schematically shows an example diagram of weights of other network performance parameters according to an example embodiment of the present disclosure.

[0066] FIG. 7 schematically shows a block diagram of a device for determining a cell congestion state according to an example embodiment of the present disclosure.

[0067] FIG. 8 schematically shows an electronic device for implementing a method for determining a cell congestion state according to an example embodiment of the present disclosure. DETAILED DESCRIPTION

[0068] Example implementations are now described with reference to the drawings; it being understood that the following description is by way of example only and is not intended to limit the application as set forth in the claims. With reference to the drawings, like or similar elements are referred to using the same reference numbers. The example implementations are described with reference to the following acts, but the example implementations are not limited by the acts. The acts can be performed in the order listed, in a different order, or concurrently.

[0069] Further, the accompanying drawings are included to provide a thorough understanding of the present disclosure and are not intended to be in any way limiting of the disclosure. The same reference numerals in different drawings identify the same or similar elements.

[0070] At present, the method for determining cell congestion in network optimization is usually to monitor the number of active users in the cell and the throughput of the users to evaluate the congestion degree of the cell, and when the number of active users exceeds a certain number, the cell is determined to be congested.

[0071] Further, the mobile Internet and the Internet of Things application will generate a large amount of intermittent small data. In order to more efficiently support the transmission of such data, the 5G R17 version introduces a small data transmission (SDT, Small Data Transmission) mechanism in the RRC_INACTIVE state. This means that if most of the active users in the cell are transmitting data in the RRC_INACTIVE state, although the number of active users is large, the throughput is not large, and at this time, only relying on the number of active users to determine the congestion degree of the cell may trigger false alarm of cell congestion.

[0072] For example, when monitoring the congested cell, assuming that the active user number alarm threshold of a certain cell is 10,000 UEs (User Equipment), if all the active user numbers are sending large data packets, the threshold is applicable; however, if 8,000 of the 10,000 users are only transmitting small data packets in the inactive state, the previous determination threshold for the congested cell is not applicable; at this time, the threshold needs to be set according to the proportion of users in different states to more accurately determine whether the cell is congested.

[0073] Based on this, in the example embodiment, a cell congestion state determination method is first provided, which can run on a server, a server cluster, or a cloud server, etc. at the network side. Of course, those skilled in the art can also run the method of the present disclosure on other platforms according to the needs, which is not specially limited in the example embodiment. Specifically, referring to FIG. 1, the cell congestion state determination method can include the following steps:

[0074] Step S110. Statistics of the first active user number in the RRC connected state and the second active user number in the RRC inactive state in the target cell are obtained.

[0075] Step S120. Determine the congestion state of the target cell according to the first active user number and the second active user number.

[0076] In the above method for determining the cell congestion state, the first active user number in the RRC connected state and the second active user number in the RRC inactive state in the target cell are counted, and then the congestion state of the target cell is determined according to the first active user number and the second active user number. Since the first active user number in the RRC connected state and the second active user number in the RRC inactive state are considered in the process of determining the congestion state of the target cell, the problem that the accuracy of the determination result of the congestion state is low due to the failure to consider the small data transmission in the inactive state in the related art is solved, and the accuracy of the determination result of the congestion state of the target cell is improved.

[0077] In the following, the method for determining the cell congestion state according to the example embodiments of the present disclosure will be explained and described in detail with reference to the accompanying drawings.

[0078] First, the technical implementation principle of the example embodiments of the present disclosure will be explained and described. Specifically, the method for determining the cell congestion state according to the example embodiments of the present disclosure is a cell congestion degree determination method that comprehensively considers the state of user data transmission and user behavior and other factors. Based on the method according to the example embodiments of the present disclosure, the user number of the cell is counted by distinguishing different RRC (Radio Resource Control) states, and the weight is adjusted to improve the accuracy of the congestion cell determination standard, so that the network status of the cell can be more accurately reflected, thereby achieving the purpose of improving the accuracy of the determination result of the congestion state of the cell.

[0079] Secondly, the communication system related to the example embodiments of the present disclosure will be explained and described. Specifically, as shown in FIG. 2, the communication system can include a user equipment 210, a base station 220 and a network side server 230. The user equipment and the network side server are in communication connection with the base station. In actual application, the user equipment is configured to report the current network performance data to the base station. The base station is configured to transmit the received network performance data to the network side server. The network side server is configured to implement the method for determining the cell congestion state according to the example embodiments of the present disclosure.

[0080] In an example embodiment, the user equipment described herein can be used to refer to the user equipment in the target cell, and the base station can be used to refer to the base station associated with the target cell; wherein, a specific scenario example diagram can be referred to as shown in FIG. 3; further, in the scenario example diagram shown in FIG. 3, the base station can include one or more, which can be determined according to the area of the target cell and the total number of users; the user equipment can include multiple.

[0081] Further, the cell congestion state determination method shown in FIG. 1 is further explained and described in combination with FIG. 2 and FIG. 3. Specifically:

[0082] In step S110, the first active user number in the RRC connected state and the second active user number in the RRC inactive state in the target cell are counted.

[0083] Specifically, the network side can actively receive the network performance data reported by the target cell, and then count the first active user number in the RRC connected state and the second active user number in the RRC inactive state from the network performance data corresponding to the target cell; wherein, the RRC described herein refers to Radio Resource Control, wireless resource control; RRC connected state is used to refer to RRC CONNECT; RRC inactive state is used to refer to RRC INACTIVE. Further, in the process of counting the first active user number in the RRC connected state and the second active user number in the RRC inactive state, each user equipment included in the network performance data can be extracted according to the current connection state; for example, the user equipment with the state marked as RRC CONNECT is counted as the first active user number; the user equipment with the state marked as RRC INACTIVE is counted as the second active user number.

[0084] In step S120, the congestion state of the target cell is determined according to the first active user number and the second active user number.

[0085] Specifically, in the actual application process, the first active user number and the second active user number can be directly summed, and the congestion state of the target cell is determined according to the sum operation result; however, since the influence degree of the second active user number on the congestion state of the target cell is less than the influence degree of the first active user number on the congestion state of the target cell; therefore, in order to further improve the accuracy of the discrimination result of the congestion state of the target cell, the first weighting factor of the first active user number can be increased, and the second weighting factor of the second active user number can be reduced. Under this premise, the specific discrimination process of the congestion state of the target cell can be realized by the following way: increasing the first weighting factor of the first active user number and reducing the second weighting factor of the second active user number; weighting and summing the first active user number and the first weighting factor, the second active user number and the second weighting factor, and determining the congestion state of the target cell according to the weighted sum result; wherein the sum of the first weighting factor and the second weighting factor recorded here is 1, and the first weighting factor is greater than the second weighting factor.

[0086] In an example embodiment, the first weighting factor and the second weighting factor recorded above are obtained by the following way: obtaining the first original weighting coefficient of the RRC connected state and the second original weighting coefficient of the RRC inactive state; taking the first original weighting coefficient as the first weighting factor of the RRC connected state and taking the second original weighting coefficient as the second weighting factor of the RRC inactive state; further, the first weighting factor and the second weighting factor can also be obtained by the following way: adaptively adjusting the first original weighting coefficient and the second original weighting coefficient to obtain the first weighting factor and the second weighting factor. That is, in the actual application process, the first weighting factor and the second weighting factor can be completely consistent with the first original weighting coefficient and the second original weighting coefficient, or can be obtained by adaptively adjusting the first original weighting coefficient and the second original weighting coefficient. At the same time, in the case that the first weighting factor and the second weighting factor can be completely consistent with the first original weighting coefficient and the second original weighting coefficient, the first original weighting coefficient and the second original weighting coefficient recorded here can be set by historical experience, or can be predicted by a neural network model; at the same time, the neural network model recorded here can include a decision tree model or a deep neural network model, etc., which is not specially limited in the present example; further, in the process of training the neural network model, the historical congestion state of the target cell and the historical first active user number and second active user number can be used for training.

[0087] In an example embodiment, the first active user number and the first weighting factor, the second active user number and the second weighting factor are weighted and summed, and the congestion state of the target cell is determined according to the weighted sum result, which can be achieved by: multiplying the first active user number and the first weighting factor to obtain a first calculation result; multiplying the second active user number and the second weighting factor to obtain a second calculation result; summing the first calculation result and the second calculation result to obtain a weighted sum result, and determining the congestion state of the target cell according to the weighted sum result. The specific calculation process of the weighted sum result can be shown in the following formula (1):

[0088] wherein, τ i is the weighting factor of different RRC states, which can be a preset value or a preset value obtained by adaptive adjustment according to other performance statistical parameters; c i is the active user number of different RRC states; N is the number of RRC states; further, in the example embodiment of the present disclosure, the above formula (1) can be simplified as the following formula (2):

[0089] wherein, is the first active user number, is the second active user number, is the first weighting factor, is the second weighting factor.

[0090] In an example embodiment, the congestion state of the target cell is determined according to the weighted sum result, which can be achieved by: judging whether the weighted sum result is greater than a preset congestion threshold value; determining that the target cell is in a congestion state when it is determined that the weighted sum result is greater than the preset congestion threshold value; determining that the target cell is in a normal communication state when it is determined that the weighted sum result is less than or equal to the preset congestion threshold value. The specific discrimination process of the congestion state of the target cell can be achieved by the following formula (3):

[0091] wherein, TG congestion is a preset congestion threshold value; wherein, the preset congestion threshold value can be set according to the number of base stations corresponding to the target cell, the total number of users in the cell, the area of the cell and other different network resources; for example, it can be obtained by prediction based on a corresponding congestion threshold value prediction model, or it can be set by an empirical value, and the present example does not make special limitation. Further, in the example embodiment of the present disclosure, the above formula (3) can be simplified as the following formula (4):

[0092] Meanwhile, if the target active user number is greater than a preset congestion threshold value TG congestion , it is determined that the target cell is in a congestion state; further, if the target active user number is less than or equal to the preset congestion threshold value TG congestion , it is determined that the target cell is in a normal communication state, i.e., in a non-congestion state.

[0093] Further, the method for determining the cell congestion state further comprises: when it is determined that the target cell is in a congestion state, generating congestion alarm information according to the target active user number. That is, if the target cell is in a congestion state, corresponding congestion alarm information needs to be generated, so that the network resources of the target cell can be adjusted by the operation and maintenance personnel or the supplier based on the target active user number and / or the preset congestion threshold value in the congestion alarm information, so that the users of the target cell can smoothly access the network.

[0094] FIG. 4 schematically shows a method flowchart for adaptively adjusting the first original weighting coefficient and the second original weighting coefficient to obtain the first weighting factor and the second weighting factor. Specifically, referring to FIG. 4, the specific determination process of the first weighting factor and the second weighting factor can include the following steps:

[0095] Step S410: obtaining other network performance parameters of the target cell, and determining a first weight adjustment reference coefficient and a second weight adjustment reference coefficient according to the other network performance parameters.

[0096] Specifically, in actual application, if other network performance parameters except the active user number are needed as influencing factors, first, the above formula (1) can be modified as shown in the following formula (5):

[0097] Target active user number = [τ1, τ2,..., τN] N ][c1, c2,..., cN] N T ; Formula (5)

[0098] Wherein, N is the number of RRC states, and T is the transpose of the matrix.

[0099] Further, if the influencing factors are increased, the above formula (5) can be converted into the following formula (6):

[0100] Wherein, λ i is the weight adjustment reference coefficient.

[0101] ​Further, the other network performance parameters described above can include the following three cases: the first case is that the other network performance parameters can include uplink throughput and downlink throughput; the second case is that the other network performance parameters can include uplink PRB utilization and downlink PRB utilization; the third case is that the other network performance parameters can include uplink throughput, downlink throughput, uplink PRB utilization and downlink PRB utilization; wherein the uplink throughput, the downlink throughput, the uplink PRB utilization and the downlink PRB utilization can be obtained from the network performance parameters reported by the user equipment. Meanwhile, the uplink throughput described herein includes a first uplink throughput υ 11 in the RRC connected state and a second uplink throughput υ 21 in the RRC inactive state; the downlink throughput includes a first downlink throughput υ 12 in the RRC connected state and a second downlink throughput υ 22 in the RRC inactive state; the uplink PRB utilization includes a first uplink PRB utilization υ 31 in the RRC connected state and a second uplink PRB utilization υ 32 in the RRC inactive state; the downlink PRB utilization includes a first downlink PRB utilization υ 41 in the RRC connected state and a second downlink PRB utilization υ 42 in the RRC inactive state. Wherein, the specific example diagram of the other network performance parameters can refer to the diagram 5 shown in the figure.

[0102] Secondly, after obtaining the other network performance parameters, the first weight adjustment reference coefficient and the second weight adjustment reference coefficient can be determined according to the other network performance parameters; specifically, the specific calculation process of the weight adjustment reference coefficient can be shown in the following formula (7): λ i =[ρ i1 ,ρ i2 ,...,ρ iM ][υ i1 ,υ i2 ,...,υ iM ] T ; Formula (7)

[0103] Wherein, M is the number of the other network performance parameters; υ ij is the specific value of the jth other network performance parameter in the ith RRC state; ρ ij is the weight of the jth other network performance parameter in the ith RRC state; further, ρ ijThe value of the first weight adjustment reference coefficient can be determined according to actual work experience or predicted based on a corresponding weight prediction model, and the present example does not make special limitations thereto.

[0104] It should be noted that in actual application, other network performance parameters can be selected according to actual needs, and the selection of throughput and PRB utilization here is only for exemplary illustration, and has no other limiting effect.

[0105] On the premise of the above-mentioned content, the first weight adjustment reference coefficient can be determined according to other network performance parameters, which can be realized in the following three ways: the first implementation way is to determine the first weight adjustment reference coefficient according to the first uplink throughput and the first downlink throughput; the second implementation way is to determine the first weight adjustment reference coefficient according to the first uplink PRB utilization and the first downlink PRB utilization; and the third implementation way is to determine the first weight adjustment reference coefficient according to the first uplink throughput, the first downlink throughput, the first uplink PRB utilization and the first downlink PRB utilization.

[0106] Further, the second weight adjustment reference coefficient can be determined according to other network performance parameters, which can be realized in the following three ways: the first implementation way is to determine the second weight adjustment reference coefficient according to the second uplink throughput and the second downlink throughput; the second implementation way is to determine the second weight adjustment reference coefficient according to the second uplink PRB utilization and the second downlink PRB utilization; and the third implementation way is to determine the second weight adjustment reference coefficient according to the second uplink throughput, the second downlink throughput, the second uplink PRB utilization and the second downlink PRB utilization.

[0107] In an example embodiment, the first weight adjustment reference coefficient can be determined according to the first uplink throughput and the first downlink throughput in the following way: the first uplink throughput and the first downlink throughput are configured with a first uplink throughput weight and a first downlink throughput weight; and the first uplink throughput and the first uplink throughput weight, and the first downlink throughput and the first downlink throughput weight are weighted and summed to obtain the first weight adjustment reference coefficient.

[0108] In an example embodiment, the first weight adjustment reference factor is determined according to the first uplink PRB utilization and the first downlink PRB utilization, which can be achieved by: configuring a first uplink PRB utilization weight and a first downlink PRB utilization weight for the first uplink PRB utilization and the first downlink PRB utilization; and performing weighted summation on the first uplink PRB utilization and the first uplink PRB utilization weight, and the first downlink PRB utilization and the first downlink PRB utilization weight, to obtain the first weight adjustment reference factor.

[0109] In an example embodiment, the first weight adjustment reference factor is determined according to the first uplink throughput, the first downlink throughput, the first uplink PRB utilization and the first downlink PRB utilization, which can be achieved by: configuring a first uplink throughput weight, a first downlink throughput weight, a first uplink PRB utilization weight and a first downlink PRB utilization weight for the first uplink throughput, the first downlink throughput, the first uplink PRB utilization and the first downlink PRB utilization; and performing weighted summation on the first uplink throughput and the first uplink throughput weight, the first downlink throughput and the first downlink throughput weight, the first uplink PRB utilization and the first uplink PRB utilization weight, and the first downlink PRB utilization and the first downlink PRB utilization weight, to obtain the first weight adjustment reference factor.

[0110] In an example embodiment, the second weight adjustment reference factor is determined according to the second uplink throughput and the second downlink throughput, which can be achieved by: configuring a second uplink throughput weight and a second downlink throughput weight for the second uplink throughput and the second downlink throughput; and performing weighted summation on the second uplink throughput and the second uplink throughput weight, and the second downlink throughput and the second downlink throughput weight, to obtain the second weight adjustment reference factor.

[0111] In an example embodiment, the second weight adjustment reference factor is determined according to the second uplink PRB utilization and the second downlink PRB utilization, which can be achieved by: configuring a second uplink PRB utilization weight and a second downlink PRB utilization weight for the second uplink PRB utilization and the second downlink PRB utilization; and performing weighted summation on the second uplink PRB utilization and the second uplink PRB utilization weight, and the second downlink PRB utilization and the second downlink PRB utilization weight, to obtain the second weight adjustment reference factor.

[0112] In an example embodiment, the second weight adjustment reference coefficient is determined according to the second uplink throughput, the second downlink throughput, the second uplink PRB utilization and the second downlink PRB utilization, which can be achieved by: configuring a second uplink throughput weight, a second downlink throughput weight, a second uplink PRB utilization weight and a second downlink PRB utilization weight for the second uplink throughput, the second downlink throughput, the second uplink PRB utilization and the second downlink PRB utilization; and performing weighted summation on the second uplink throughput and the second uplink throughput weight, the second downlink throughput and the second downlink throughput weight, the second uplink PRB utilization and the second uplink PRB utilization weight, and the second downlink PRB utilization and the second downlink PRB utilization weight, to obtain the second weight adjustment reference coefficient.

[0113] Further, the first uplink throughput weight, the first downlink throughput weight, the first uplink PRB utilization weight, the first downlink PRB utilization weight, the second uplink throughput weight, the second downlink throughput weight, the second uplink PRB utilization weight and the second downlink PRB utilization weight described above can refer to FIG. 6. On the premise of the above description, the specific calculation formula of the first weight adjustment reference coefficient and the second weight adjustment reference coefficient can be respectively shown in the following formula (8) to formula (13): 11 ,ρ 12 ][υ 11 ,υ 12 ] T =ρ 11 *υ 11 +ρ 12 *υ 12 ; formula (8)

[0114] or λ1= [ρ 13 ,ρ 14 ][υ 13 ,υ 14 ] T =ρ 13 *υ 13 +ρ 14 *υ 14 ; formula (9)

[0115] or λ1= [ρ 11 ,ρ 12 ,ρ 13 ,ρ 14 ][υ 11 ,υ 12 ,υ 13 ,υ14 ] T = p 11 * u 11 + p 12 * u 12 + p 13 * u 13 + p 14 * u 14 ; Formula (10) λ2= [p 21 , p 22 ] [u 21 , u 22 ] T = p 21 * u 21 + p 22 * u 22 ; Formula (11)

[0116] or λ2= [p 23 , p 24 ] [u 23 , u 24 ] T = p 23 * u 23 + p 24 * u 24 ; Formula (12)

[0117] or λ2= [p 21 , p 22 , p 23 , p 24 ] [u 21 , u 22 , u 23 , u 24 ] T = p 21 * u 21 + p 22 * u 22 + p 23 * u 23 + p 24 * u 24 ; Formula (13)

[0118] where p 11 , p 12 , p 13 , p 14respectively are the first uplink throughput weight, the first downlink throughput weight, the first uplink PRB utilization weight and the first downlink PRB utilization weight of the uplink throughput and the downlink throughput in the RRC CONNECT state; υ 11 ,υ 12 ,υ 13 ,υ 14 respectively are the specific values of the first uplink throughput, the first downlink throughput, the first uplink PRB utilization and the first downlink PRB utilization in the RRC CONNECT state. 21 ,ρ 22 ,ρ 23 ,ρ 24 respectively are the second uplink throughput weight, the second downlink throughput weight, the second uplink PRB utilization weight and the second downlink PRB utilization weight of the uplink throughput and the downlink throughput in the RRC INACTIVE state; υ 21 ,υ 22 ,υ 23 ,υ 24 respectively are the specific values of the second uplink throughput, the second downlink throughput, the second uplink PRB utilization and the second downlink PRB utilization in the RRC INACTIVE state.

[0119] Step S420, the first original weighting coefficient is adaptively adjusted according to the first weight adjustment reference coefficient, to obtain a first weighting factor.

[0120] Wherein, the specific calculation process of the first weighting factor can be shown in the following formula (14): First weighting factor = λ1*τ1; Formula (14)

[0121] Step S430, the second original weighting coefficient is adaptively adjusted according to the second weight adjustment reference coefficient, to obtain a second weighting factor.

[0122] Wherein, the specific calculation process of the second weighting factor can be shown in the following formula (15): Second weighting factor = λ2*τ2; Formula (15)

[0123] Finally, the specific discrimination process of the congestion state of the target cell can be simplified as shown in the following formula (16):

[0124] Specifically, if the weighted sum result is greater than the threshold value, the determination result is that the target cell is in a congestion state and a congestion alarm is triggered; if the weighted sum result is less than or equal to the threshold value, the determination result is that the target cell is in a normal communication state.

[0125] At this point, the cell congestion state determination method described in the example embodiments of the present disclosure has been fully implemented. Based on the foregoing, it can be known that the cell congestion state determination method described in the example embodiments of the present disclosure has at least the following advantages: on the one hand, distinguishing between RRC CONNECT and RRC INACTIVE reporting active user numbers solves the problem of misjudgment of cell congestion caused by small data transmission user numbers in the RRC INACTIVE state; on the other hand, by setting or adjusting the weight of active user numbers in different RRC states, the accuracy of cell congestion degree determination is improved; on the other hand, the cell congestion evaluation standard can also be considered by comprehensively considering the state of user transmission data and other network performance parameters of the cell and the like, the accuracy of evaluating network quality is improved, and the network does not need to be modified.

[0126] The following is an apparatus embodiment of the present disclosure, which can be used to execute the method embodiments of the present disclosure. For details not disclosed in the apparatus embodiments of the present disclosure, please refer to the method embodiments of the present disclosure.

[0127] The example embodiments of the present disclosure also provide a cell congestion state determination device. Specifically, referring to FIG. 7, the cell congestion state determination device can include an active user number statistical module 710 and a congestion state determination module 720. Wherein:

[0128] The active user number statistical module 710 can be used to count the first active user number in the RRC connected state and the second active user number in the RRC inactive state in the target cell;

[0129] The congestion state determination module 720 can be used to determine the congestion state of the target cell according to the first active user number and the second active user number.

[0130] In an example embodiment of the present disclosure, the influence degree of the second active user number on the congestion state of the target cell is less than the influence degree of the first active user number on the congestion state of the target cell.

[0131] In an example embodiment of the present disclosure, determining the congestion state of the target cell according to the first active user number and the second active user number includes:

[0132] Increasing the first weighting factor of the first active user number and decreasing the second weighting factor of the second active user number;

[0133] The first and second activated user numbers and the first and second weighting factors are weighted and summed, and a congestion state of the target cell is determined according to a result of the weighted and summed.

[0134] In an exemplary embodiment of the present disclosure, the sum of the first and second weighting factors is 1, and the first weighting factor is greater than the second weighting factor.

[0135] In an exemplary embodiment of the present disclosure, the first and second weighting factors are obtained in the following manner:

[0136] A first original weighting coefficient of the RRC connected state and a second original weighting coefficient of the RRC inactive state are obtained.

[0137] The first original weighting coefficient is taken as the first weighting factor of the RRC connected state, and the second original weighting coefficient is taken as the second weighting factor of the RRC inactive state; or

[0138] The first and second original weighting coefficients are adaptively adjusted to obtain the first and second weighting factors.

[0139] In an exemplary embodiment of the present disclosure, the first and second original weighting coefficients are adaptively adjusted to obtain the first and second weighting factors, including:

[0140] Other network performance parameters of the target cell are obtained, and first and second weight adjustment reference coefficients are determined according to the other network performance parameters.

[0141] The first original weighting coefficient is adaptively adjusted according to the first weight adjustment reference coefficient to obtain the first weighting factor.

[0142] The second original weighting coefficient is adaptively adjusted according to the second weight adjustment reference coefficient to obtain the second weighting factor.

[0143] In an exemplary embodiment of the present disclosure, the other network performance parameters include uplink and downlink throughputs, or uplink and downlink PRB utilization rates, or uplink and downlink throughputs and uplink and downlink PRB utilization rates.

[0144] The uplink throughput includes a first uplink throughput in the RRC connected state and a second uplink throughput in the RRC inactive state.

[0145] The downlink throughput includes a first downlink throughput in an RRC connected state and a second downlink throughput in an RRC inactive state.

[0146] The uplink PRB utilization includes a first uplink PRB utilization in an RRC connected state and a second uplink PRB utilization in an RRC inactive state.

[0147] The downlink PRB utilization includes a first downlink PRB utilization in an RRC connected state and a second downlink PRB utilization in an RRC inactive state.

[0148] In an example embodiment of the present disclosure, determining the first weight adjustment reference coefficient according to the other network performance parameters includes:

[0149] determining the first weight adjustment reference coefficient according to the first uplink throughput and the first downlink throughput; or

[0150] determining the first weight adjustment reference coefficient according to the first uplink PRB utilization and the first downlink PRB utilization; or

[0151] determining the first weight adjustment reference coefficient according to the first uplink throughput, the first downlink throughput, the first uplink PRB utilization and the first downlink PRB utilization.

[0152] In an example embodiment of the present disclosure, determining the first weight adjustment reference coefficient according to the first uplink throughput, the first downlink throughput, the first uplink PRB utilization and the first downlink PRB utilization includes:

[0153] configuring the first uplink throughput, the first downlink throughput, the first uplink PRB utilization and the first downlink PRB utilization with a first uplink throughput weight, a first downlink throughput weight, a first uplink PRB utilization weight and a first downlink PRB utilization weight;

[0154] performing weighted summation on the first uplink throughput and the first uplink throughput weight, the first downlink throughput and the first downlink throughput weight, the first uplink PRB utilization and the first uplink PRB utilization weight, the first downlink PRB utilization and the first downlink PRB utilization weight to obtain the first weight adjustment reference coefficient.

[0155] In an example embodiment of the present disclosure, determining the second weight adjustment reference coefficient according to the other network performance parameters includes:

[0156] determining the second weight adjustment reference coefficient according to the second uplink throughput and the second downlink throughput; or

[0157] determine the second weight adjustment reference coefficient according to the second uplink PRB utilization rate and the second downlink PRB utilization rate; or

[0158] determine the second weight adjustment reference coefficient according to the second uplink throughput, the second downlink throughput, the second uplink PRB utilization rate and the second downlink PRB utilization rate.

[0159] In an exemplary embodiment of the present disclosure, determining the second weight adjustment reference coefficient according to the second uplink throughput, the second downlink throughput, the second uplink PRB utilization rate and the second downlink PRB utilization rate comprises:

[0160] configuring a second uplink throughput weight, a second downlink throughput weight, a second uplink PRB utilization rate weight and a second downlink PRB utilization rate weight for the second uplink throughput, the second downlink throughput, the second uplink PRB utilization rate and the second downlink PRB utilization rate;

[0161] performing weighted summation on the second uplink throughput and the second uplink throughput weight, the second downlink throughput and the second downlink throughput weight, the second uplink PRB utilization rate and the second uplink PRB utilization rate weight, and the second downlink PRB utilization rate and the second downlink PRB utilization rate weight to obtain the second weight adjustment reference coefficient.

[0162] In an exemplary embodiment of the present disclosure, determining the congestion state of the target cell according to the weighted summation result comprises:

[0163] determining whether the weighted summation result is greater than a preset congestion threshold value;

[0164] determining that the target cell is in a congestion state when it is determined that the weighted summation result is greater than the preset congestion threshold value;

[0165] determining that the target cell is in a normal communication state when it is determined that the weighted summation result is less than or equal to the preset congestion threshold value.

[0166] In an exemplary embodiment of the present disclosure, the cell congestion state discrimination apparatus further comprises:

[0167] a congestion alarm information generation module, which can be used to generate congestion alarm information according to the target active user number when it is determined that the target cell is in a congestion state.

[0168] The specific details of each module in the above cell congestion state discrimination apparatus have been described in detail in the corresponding cell congestion state discrimination method, and thus will not be described here again.

[0169] It should be noted that although several modules or units of the devices for action execution are mentioned in the above detailed description, such division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into multiple modules or units for embodiment.

[0170] In addition, although the various steps of the methods in the present disclosure are described in a particular order in the accompanying drawings, this is not required or implied that the steps must be performed in this particular order, or that all the steps shown must be performed to achieve the desired result. Additionally or alternatively, certain steps can be omitted, multiple steps can be combined into one step, and / or one step can be divided into multiple steps, etc.

[0171] In the exemplary embodiments of the present disclosure, an electronic device capable of implementing the above method is also provided.

[0172] Those skilled in the art can understand that various aspects of the present disclosure can be implemented as a system, a method or a program product. Therefore, various aspects of the present disclosure can be embodied as a complete hardware embodiment, a complete software embodiment (including firmware, microcode, etc.), or an embodiment combining hardware and software aspects, which can be collectively referred to as "circuitry", "module" or "system" herein.

[0173] The electronic device 800 according to such an embodiment of the present disclosure will be described below with reference to FIG. 8. FIG. 8 shows the electronic device 800 only as an example, and should not bring any limitation to the functions and use range of the embodiments of the present disclosure.

[0174] As shown in FIG. 8, the electronic device 800 is in the form of a general computing device. The components of the electronic device 800 can include, but are not limited to, the at least one processing unit 810 described above, the at least one storage unit 820 described above, a bus 830 connecting different system components (including the storage unit 820 and the processing unit 810), and a display unit 840.

[0175] The storage unit stores program codes which can be executed by the processing unit 810, so that the processing unit 810 performs the steps according to various exemplary embodiments of the present disclosure described in the "Exemplary Method" section of the present specification. For example, the processing unit 810 can perform the steps S110 of counting the first active user number in the RRC connected state and the second active user number in the RRC inactive state in the target cell as shown in FIG. 1, and the step S120 of determining the congestion state of the target cell according to the first active user number and the second active user number.

[0176] Storage 820 can include a readable medium that can be in the form of volatile memory, such as random access memory (RAM) 8201 and / or cache memory 8202, and can further include read only memory (ROM) 8203.

[0177] Storage 820 can also include a program / utility 8204 having a set of program modules 8205 such as an operating system, one or more application programs, other program modules, and program data, each of which can give the electronic device 800 its functionality, at least in part. Each of the operating system, one or more application programs, other program modules, and program data can include an implementation of a networking environment.

[0178] Bus 830 can represent one or more of several types of bus structures, including a storage bus or bus controller, peripheral bus, graphics bus, processor or local bus using any of a variety of bus architectures.

[0179] Electronic device 800 can also communicate with one or more external devices 900 such as a keyboard or pointing device, using one or more communication ports 850. Communication port 850 can also enable electronic device 800 to communicate with one or more devices that enable user interaction with electronic device 800 (for example, remote control or weaponry targeting device) and / or one or more devices that enable electronic device 800 to communicate with one or more other computing devices. Such communication can be facilitated by an input / output (I / O) interface 850. Electronic device 800 can also communicate with one or more networks (for example, a local area network (LAN), a wide area network (WAN), and / or the Internet) through a network adapter 860. As illustrated, network adapter 860 can communicate with the other components of electronic device 800 through bus 830. It should be understood that although not shown, other hardware and / or software components could be used in conjunction with electronic device 800. These include, but are not limited to, microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival storage systems, etc.

[0180] Those skilled in the art will readily understand that the example embodiments described herein can be implemented by software and / or by hardware coupled with software, as described above. As such, the technical solutions according to the embodiments of the present disclosure can be embodied in the form of a software product. The software product can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash disk, a mobile hard disk, or the like) or a network, and includes a number of instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to perform the methods according to the embodiments of the present disclosure.

[0181] In exemplary embodiments of the present disclosure, a computer readable storage medium having stored thereon a program product capable of implementing the above-described methods of the present specification is also provided. In some possible implementations, various aspects of the present disclosure can also be implemented in the form of a program product including a program code that, when run on a terminal device, causes the terminal device to perform the steps described in the above "Exemplary Methods" section according to various exemplary embodiments of the present disclosure.

[0182] A program product for implementing the above-described methods according to embodiments of the present disclosure can take the form of a portable compact disc read-only memory (CD-ROM) and include a program code, and can be run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto, and in the present document, a readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0183] The program product can take any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium, for example, can be, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of the readable storage medium include an electrical connection having one or more wires, a portable disc, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0184] The computer readable signal medium can include a data signal propagated in baseband or propagated as a carrier wave in a propagated data signal, in which the readable program code is embodied. Such propagated data signal can take multiple forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination thereof. The readable signal medium can also be any readable medium that is not a readable storage medium and that can transmit, propagate, or transport the program for use by or in connection with an instruction execution system, apparatus, or device.

[0185] The program code contained on the readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, and the like, or any suitable combination thereof.

[0186] The program code may be executed by one or more programmable processing devices, which can include processors, microprocessor, microcomputer or microcontrollers, as well as other electronic circuits that include elements that can execute a program of instructions written in any one of a variety of programming languages, including an object oriented programming language such as Java, C++, or the like, as well as conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's computing device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device or entirely on the remote computing device or server. In the latter scenario, the remote computing device can be connected to the user's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computing device, such as through the Internet using an Internet Service Provider (ISP).

[0187] In addition, the above-described flowcharts are merely illustrative of the processes included in the method according to the exemplary embodiments of the present disclosure, and are not intended to limit the purpose. It is easily understood that the processes shown in the above-described flowcharts do not indicate or limit the time sequence of the processes. In addition, it is also easily understood that the processes can be executed synchronously or asynchronously, for example, in a plurality of modules.

[0188] Other embodiments of the present disclosure will be readily apparent to those skilled in the art upon considering the specification and practice of the invention disclosed herein. The present application is intended to cover any variations, uses or adaptive changes of the present disclosure following the general principles thereof and including the general principles of the present disclosure and including those expressly stated or implied herein. The specification and examples are to be regarded as exemplary only, and the true scope and spirit of the present disclosure are indicated by the claims.

Claims

1. A method for determining a congestion state of a cell, comprising: counting a first number of active users in a RRC connected state and a second number of active users in a RRC inactive state in a target cell; determining the congestion state of the target cell according to the first number of active users and the second number of active users.

2. The method of claim 1, wherein the cell congestion state is determined based on the number of the cells in the cell congestion state. The second number of active users has a smaller impact on the congestion state of the target cell than the first number of active users.

3. The method of claim 1 or 2, wherein, A second weighting factor is used to reduce the second number of active users.

4. The method of claim 3, wherein the cell congestion state is determined based on the number of the cells in the cell congestion state. The determination of the congestion state of the target cell according to the first number of active users and the second number of active users comprises: a first weighting factor is used to increase the first number of active users; a weighted sum of the first number of active users and the first weighting factor, and the second number of active users and the second weighting factor is calculated, and the congestion state of the target cell is determined according to the weighted sum.

5. The method of claim 4, wherein the cell congestion state is determined based on the number of the cells in the cell congestion state. The sum of the first weighting factor and the second weighting factor is 1, and the first weighting factor is greater than the second weighting factor. 6.The method according to claim 4, wherein the first weighting factor and the second weighting factor are obtained by: obtaining a first original weighting coefficient of the RRC connected state and a second original weighting coefficient of the RRC inactive state; using the first original weighting coefficient as the first weighting factor of the RRC connected state, and using the second original weighting coefficient as the second weighting factor of the RRC inactive state; or adaptively adjusting the first original weighting coefficient and the second original weighting coefficient to obtain the first weighting factor and the second weighting factor.

7. The method of claim 6, wherein the cell congestion state is determined based on the number of the cells in the cell congestion state. The adaptively adjusting the first original weighting coefficient and the second original weighting coefficient to obtain the first weighting factor and the second weighting factor comprises: obtaining other network performance parameters of the target cell, and determining a first weight adjustment reference coefficient and a second weight adjustment reference coefficient according to the other network performance parameters; adaptively adjusting the first original weighting coefficient according to the first weight adjustment reference coefficient to obtain the first weighting factor; adaptively adjusting the second original weighting coefficient according to the second weight adjustment reference coefficient to obtain the second weighting factor.

8. The method of claim 7, wherein the cell congestion state is determined based on the number of the cells in the cell congestion state. The other network performance parameters comprise uplink throughput and downlink throughput, or uplink PRB utilization and downlink PRB utilization; or uplink throughput, downlink throughput, uplink PRB utilization and downlink PRB utilization. The uplink throughput comprises a first uplink throughput in the RRC connected state and a second uplink throughput in the RRC inactive state. The downlink throughput comprises a first downlink throughput in the RRC connected state and a second downlink throughput in the RRC inactive state. The uplink PRB utilization comprises a first uplink PRB utilization in the RRC connected state and a second uplink PRB utilization in the RRC inactive state. The downlink PRB utilization rate includes a first downlink PRB utilization rate in an RRC connected state and a second downlink PRB utilization rate in an RRC inactive state.

9. The method of claim 8, wherein the cell congestion state is determined based on the number of the cells in the cell congestion state. The first weight adjustment reference coefficient is determined according to the other network performance parameters, including: The first weight adjustment reference coefficient is determined according to the first uplink throughput and the first downlink throughput; or The first weight adjustment reference coefficient is determined according to the first uplink PRB utilization rate and the first downlink PRB utilization rate; or The first weight adjustment reference coefficient is determined according to the first uplink throughput, the first downlink throughput, the first uplink PRB utilization rate and the first downlink PRB utilization rate.

10. The method of claim 9, wherein the cell congestion state is determined based on the number of the cells in the cell congestion state. The first weight adjustment reference coefficient is determined according to the first uplink throughput, the first downlink throughput, the first uplink PRB utilization rate and the first downlink PRB utilization rate, including: The first uplink throughput, the first downlink throughput, the first uplink PRB utilization rate and the first downlink PRB utilization rate are configured with a first uplink throughput weight, a first downlink throughput weight, a first uplink PRB utilization rate weight and a first downlink PRB utilization rate weight; The first uplink throughput and the first uplink throughput weight, the first downlink throughput and the first downlink throughput weight, the first uplink PRB utilization rate and the first uplink PRB utilization rate weight, and the first downlink PRB utilization rate and the first downlink PRB utilization rate weight are weighted and summed to obtain the first weight adjustment reference coefficient.

11. The method of claim 8, wherein the cell congestion state is determined based on the number of the cells in the cell congestion state. The second weight adjustment reference coefficient is determined according to the other network performance parameters, including: The second weight adjustment reference coefficient is determined according to the second uplink throughput and the second downlink throughput; or The second weight adjustment reference coefficient is determined according to the second uplink PRB utilization rate and the second downlink PRB utilization rate; or The second weight adjustment reference coefficient is determined according to the second uplink throughput, the second downlink throughput, the second uplink PRB utilization rate and the second downlink PRB utilization rate.

12. The method of claim 11, wherein the cell congestion state is determined based on the number of the cells in the cell congestion state. The second weight adjustment reference coefficient is determined according to the second uplink throughput, the second downlink throughput, the second uplink PRB utilization rate and the second downlink PRB utilization rate, including: The second uplink throughput, the second downlink throughput, the second uplink PRB utilization rate and the second downlink PRB utilization rate are configured with a second uplink throughput weight, a second downlink throughput weight, a second uplink PRB utilization rate weight and a second downlink PRB utilization rate weight; The second uplink throughput and the second uplink throughput weight, the second downlink throughput and the second downlink throughput weight, the second uplink PRB utilization rate and the second uplink PRB utilization rate weight, and the second downlink PRB utilization rate and the second downlink PRB utilization rate weight are weighted and summed to obtain the second weight adjustment reference coefficient.

13. The method of claim 5, wherein the cell congestion state is determined based on the number of the cells in the cell congestion state. The congestion state of the target cell is determined according to the weighted sum result, including: It is judged whether the weighted sum result is greater than a preset congestion threshold value; When it is determined that the weighted sum result is greater than the preset congestion threshold value, it is determined that the target cell is in a congestion state; determining that the target cell is in a normal communication state when the weighted sum result is less than or equal to the preset congestion threshold value.

14. The method of claim 13, wherein the cell congestion state is determined based on the number of the cells in the cell congestion state. The method for determining the cell congestion state further comprises: generating congestion alarm information according to the target active user number when it is determined that the target cell is in a congestion state.

15. A device for determining a cell congestion state, comprising: an active user number counting module configured to count a first active user number in an RRC connected state and a second active user number in an RRC inactive state in a target cell; a congestion state determining module configured to determine a congestion state of the target cell according to the first active user number and the second active user number.

16. A computer readable storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the method for determining a cell congestion state according to any one of claims 1-14.

17. An electronic device, comprising: a processor; and a memory configured to store executable instructions of the processor; wherein the processor is configured to implement the method for determining a cell congestion state according to any one of claims 1-14 by executing the executable instructions.

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