4G high-load optimization scheme automatic output method

Abstract

The invention discloses an automatic output method for a 4G high-load optimization scheme, relates to the technical field of 4G communication network optimization, and solves the technical problems of high output cost and low efficiency caused by dependence on manual output of a traditional 4G high-load optimization scheme. According to the method, 4G cell data are extracted according to 4G cell high-load evaluation indexes, and high-load cells are determined and counted; counting and outputting an outdoor frequency band, an outdoor high-load frequency band, a physical direction flow and a physical direction design capacity according to the 4G high-load cell obtained by counting and in combination with a physical site name and an azimuth angle; outputting a 4G high-load cell optimization scheme according to the information in the basic information table, the outdoor frequency band, the outdoor high-load frequency band, the physical direction flow, the physical direction design capacity and the cell property; an accurate and high-efficiency 4G high-load optimization scheme automatic output mode is provided, and the network service quality is effectively improved.

Description

Technical Field

[0001] The present invention belongs to the field of 4G communication network optimization, and specifically is a method for automatically outputting a 4G high-load optimization solution. Background Art

[0002] With the gradual increase of 4G users, the load of cells in hot spots is also gradually increasing. The uneven distribution of users has led to high loads in some cells. Uniform coverage of cells in hot spots and single carriers can no longer meet the needs of users. Inter-cell coverage expansion and dual-carrier deployment are becoming increasingly important. In the actual network environment, when the load of a cell reaches a certain level, its access, throughput and other indicators will deteriorate. Therefore, it is particularly important to balance the load between cells and frequencies, balance the performance of the entire system, and improve the stability of the system.

[0003] The existing 4G base stations are densely distributed base stations, and there are multiple carrier frequencies. The traditional 4G high-load optimization solution output is generally manual. As the network scale becomes larger and larger, the statistics of 4G high-load cells and the output of optimization solutions require operators to pay more manpower and financial resources, and the manual method has the problems of high cost and low efficiency. Therefore, the present invention provides a method for automatically outputting a 4G high-load optimization solution. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes a 4G high-load optimization solution automatic output method, which is used to solve the technical problem that the traditional 4G high-load optimization solution relies on manual output, resulting in high output cost and low efficiency.

[0005] To achieve the above object, a first aspect of the present invention provides a method for automatically outputting a 4G high-load optimization solution, comprising the following steps:

[0006] Step 1: Select characteristic information of the cell base station from the engineering parameter table based on clustering adaptive selection algorithm to establish a basic information table; wherein the characteristic information of the cell base station includes base station service information and base station location information;

[0007] Base station service information includes cell name, type (indoor / outdoor), frequency band, bandwidth, district, county, manufacturer, etc.

[0008] The base station location information includes the physical site name, longitude, latitude, azimuth type (indoor / outdoor), physical site name_azimuth, etc.

[0009] Step 2: Extract 4G cell data according to the 4G cell high load evaluation index, and determine and count the 4G high load cells;

[0010] Step 3: Based on the statistically obtained 4G high-load cells, the outdoor frequency band, outdoor high-load frequency band, physical direction traffic, and physical direction design capacity are statistically output in combination with the physical site name and azimuth;

[0011] Step 4: Output the 4G high-load cell optimization plan based on the information in the basic information table, outdoor frequency band, outdoor high-load frequency band, physical direction traffic and physical direction design capacity, and cell nature; the cell nature includes high-load cell and non-high-load cell.

[0012] Preferably, extracting 4G cell data according to the 4G cell high load definition index and determining the high load cell includes:

[0013] According to the extracted 4G cell data, the frequency band and bandwidth are extracted from the sorted basic information table, and the 4G high-load cell is determined in combination with the high-load cell evaluation indicators.

[0014] Preferably, the 4G cell data includes existing network indicator traffic, PRB utilization and number of RRC users; the existing network indicator traffic includes PDCP layer downlink traffic and PDCP layer uplink traffic.

[0015] Preferably, outdoor frequency band: through the cell name, frequency band, physical site name, azimuth, the outdoor frequency band of the corresponding physical direction is obtained by counting the physical site name_azimuth;

[0016] Outdoor high-load frequency band: According to the cell name, the frequency band of the high-load cell, the physical site name, and the azimuth, the outdoor high-load frequency band of the corresponding physical direction is obtained by counting the physical site name_azimuth;

[0017] Physical direction traffic: The physical direction traffic of the corresponding physical direction is obtained by counting the cell name, 5.3 PDCP layer downlink traffic (MB), physical site name, and azimuth according to the physical site name_azimuth.

[0018] Physical direction design capacity: The physical direction design capacity of the corresponding physical direction is obtained by counting the cell name, frequency band, bandwidth, downlink traffic threshold, physical site name, and azimuth, and using the physical site name_azimuth statistics.

[0019] Preferably, the output of the 4G high-load cell optimization solution according to the information in the basic information table, the outdoor frequency band, the outdoor high-load frequency band, the physical direction flow and the physical direction design capacity, and the cell properties includes:

[0020] Passive / indoor optimization solution:

[0021] Output optimization solutions based on cell type, cell frequency band, bandwidth, and cell nature;

[0022] Outdoor optimization solution:

[0023] Design capacity based on cell type, outdoor frequency band, outdoor high-load frequency band, physical direction traffic, and physical direction, while taking 200MB of redundant traffic into account as a balancing space and outputting an optimization plan.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] 1. The 4G base station of the present invention is a densely distributed base station. Coupled with the coexistence of 4G multiple frequency bands, a complex and multi-frequency communication network has been formed, which increases the difficulty and workload of network optimization. The present invention firstly outputs 4G high-load cells based on 4G high-load definition statistics. Secondly, it outputs outdoor frequency bands in the direction of physical sites and outdoor high-load frequency bands through algorithms such as high-load same-direction traffic, capacity, and frequency bands. Finally, it outputs 4G high-load cell optimization solutions through 4G high-load optimization solution algorithms. It provides a more accurate and efficient automatic output of 4G high-load optimization solutions, which, on the one hand, replaces manual statistical analysis and reduces network operation and maintenance costs. On the other hand, it accurately outputs optimization solutions for each high-load cell and quickly locates network problems. It effectively improves the service quality of 4G networks, improves users' 4G business perception, supports innovation in the network optimization industry, and improves the project delivery capabilities of enterprises.

[0026] 2. The present invention selects characteristic information of cell base stations from the engineering parameter table based on a clustering-based adaptive selection algorithm to establish a basic information table; extracts 4G cell data according to 4G cell high load evaluation indicators, and determines and counts high load cells; outputs outdoor frequency bands, outdoor high load frequency bands, physical direction traffic and physical direction design capacity according to the statistically obtained 4G high load cells, combined with physical site names and azimuth statistics; outputs 4G high load cell optimization plans based on the information in the basic information table, as well as outdoor frequency bands, outdoor high load frequency bands, physical direction traffic and physical direction design capacity, and cell properties; formulates optimization plans for high load cells, optimizes network structure and resource allocation, alleviates network congestion, and improves users' network experience, while reducing operators' operating costs and improving operating efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in 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 invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0028] Figure 1 It is a schematic diagram of the process of the present invention;

[0029] Figure 2Schematic diagram of the system structure of the present invention. DETAILED DESCRIPTION

[0030] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] See also Figure 1 The first aspect of the present invention provides a method for automatically outputting a 4G high-load optimization solution, comprising the following steps:

[0032] Step 1: Create a basic information table;

[0033] Specifically, the cell name, frequency band, bandwidth, district, county, manufacturer, physical site name, longitude, latitude, azimuth, type (indoor / outdoor), physical site name_azimuth, etc. in the engineering parameter table are extracted through the clustering adaptive selection algorithm to complete the output of the basic information table, as shown in Table 1 Basic Information Table:

[0034] Table 1 Basic information table

[0035] Community Name Districts and counties factory Physical site name longitude latitude Azimuth Type (indoor / outdoor) Frequency band bandwidth Physical site name_azimuth

[0036] Step 2: Count high-load cells;

[0037] Step S1: Determine the definition of 4G cell high load according to the operator, that is, determine relevant indicators, threshold values, etc.;

[0038] Step S2: extract 4G cell data;

[0039] Specifically, according to the definition of high-load cells, the cell name of the 4G cell during the busy hour of the existing network element is extracted, 5.3 PDCP layer downlink traffic (MB), 5.1 PDCP layer uplink traffic (MB), 1.1 downlink PRB average utilization (%), 1.9 uplink PRB average utilization (%), 1.16 average number of RRC connected users, [5.13] user experience uplink average rate (Mbps), [5.14] user experience downlink average rate (Mbps), and the 4G cell data is sorted; as shown in Table 2 below;

[0040] Table 2 4G cell data

[0041]

[0042] Step S3: Output statistics of 4G high-load cells

[0043] Specifically, the decision tree algorithm is used to extract the frequency band and bandwidth from the basic information table based on the extracted 4G cell data, and the 4G high-load cell is determined in combination with the high-load cell evaluation criteria. For example, the evaluation criteria of the telecom operator for the 4G high-load cell are as follows:

[0044] (1) Monthly granularity index (10 days in a month are high load);

[0045] (2) High-load cell = high-traffic load cell + high-connection load cell (deduplication);

[0046] (3) High-traffic load cells: Typical PRB utilization during 4G busy hours>=50% and downlink PDCP traffic>=7.6G or uplink PDCP traffic>=3.8GB (1.8C / 2.1G, 20M bandwidth) and the number of RRC connected users>=10; Typical PRB utilization during 4G busy hours>=50% and downlink PDCP traffic>=5.7G or uplink PDCP traffic>=2.8GB (1.8G, 15M bandwidth) and the number of RRC connected users>=10; Typical RB utilization during 4C busy hours>=50% and downlink PDCP traffic>=1.9C or uplink PDCP traffic>=0.9GB (800M) and the number of RRC connected users>=3;

[0047] (4) Connecting to high-load cells: Typical PRB utilization during 4G busy hours>=50% and number of RRC connected users>=200 (1.8G / 2.1G, 20M bandwidth); Typical PRB utilization during 4G busy hours>=50% and number of RRC connected users>=150 (1.8C, 15M bandwidth); Typical PRB utilization during 4G busy hours>=50% and number of RRC connected users>=50 (800M);

[0048] Step 3: Based on the statistically obtained 4G high-load cells, the outdoor frequency band, outdoor high-load frequency band, physical direction traffic, and physical direction design capacity are statistically output in combination with the physical site name and azimuth;

[0049] Specifically, based on the statistically obtained 4G high-load cells combined with the physical site name + azimuth, the following is obtained:

[0050] (1) Outdoor frequency band: Based on the cell name, frequency band, physical site name, and azimuth, the outdoor frequency band of the physical direction is output according to the statistics of physical site name_azimuth, such as 1.8G, 1.8G2.1G, 1.8G2.1G800M, etc.

[0051] (2) Outdoor high-load frequency band: Based on the cell name, frequency band of the high-load cell, physical site name, and azimuth, the outdoor high-load frequency band in the physical direction is statistically output according to the physical site name_azimuth, such as 1.8G, 1.8G2.1G, 1.8G2.1G800M, etc.

[0052] (3) Physical direction traffic: Based on the cell name, 5.3 PDCP layer downlink traffic (MB), physical site name, and azimuth, the physical direction traffic of the physical direction is output according to the statistics of physical site name_azimuth.

[0053] (4) Physical direction design capacity: Based on the cell name, frequency band, bandwidth, downlink traffic threshold, physical site name, and azimuth, the physical direction design capacity of the physical direction is output according to the statistics of physical site name_azimuth.

[0054] For example, as shown in Table 3 below, the physical direction and flow threshold algorithm and Table 4, the downlink flow threshold table:

[0055] Table 3 Physical direction and flow threshold algorithm

[0056]

[0057] Table 4 Downstream flow threshold

[0058] Frequency band bandwidth Downstream traffic threshold GB 1.8G or 2.1G 20M 7.6 1.8G or 2.1G 15M or 10M 5.7 800M 10M or 5M 1.9

[0059] Step 4: Output 4G high load optimization solution;

[0060] According to the physical site name_azimuth, frequency band, bandwidth, outdoor frequency band, outdoor high-load frequency band, physical direction traffic, physical direction design capacity, and whether it is a high-load cell, the 4G high-load cell optimization plan is automatically output according to the following algorithm; the details are as follows:

[0061] 1. Passive indoor distribution optimization solution

[0062] According to the cell type, cell frequency band, bandwidth, and whether it is a high-load cell, an optimization plan is output, as shown in Table 5 Passive indoor 4G high-load cell optimization plan algorithm;

[0063] Table 5 Passive indoor 4G high-load cell optimization algorithm

[0064] Serial number type Frequency band bandwidth Optimization plan 1 Room 800M 10M Replace 1.8G or 2.1G 2 Room 800M 5M Replace 1.8G or 2.1G 3 Room 1.8G 15M Replace 1.8G (20M) or 2.1G 4 Room 1.8G 10M Replace 1.8G (20M) or 2.1G 5 Room 2.1G 20M Need to expand 1.8G 6 Room 1.8G 20M Need to expand 2.1G

[0065] (1) The cell frequency band is 800 MHz, the bandwidth is 10 MHz, and the output optimization solution is to replace 1.8 GHz or 2.1 GHz;

[0066] (2) The cell frequency band is 800 MHz and the bandwidth is 5 MHz. Output optimization solution: replace 1.8 GHz or 2.1 GHz.

[0067] (3) The cell frequency band is 1.8G and the bandwidth is 10M. Output optimization solution: replace 1.8G (20M) or 2.1G;

[0068] (4) The cell frequency band is 1.8G and the bandwidth is 15M. Output optimization solution: replace 1.8G (20M) or 2.1G;

[0069] (5) The cell frequency band is 1.8G, the bandwidth is 20M, and the output optimization solution is to expand to 2.1G;

[0070] (6) The cell frequency band is 2.1G and the bandwidth is 20M. The output optimization solution is to expand to 1.8G.

[0071] 2. Active indoor optimization solution

[0072] Output the optimization plan according to the cell type, frequency band, bandwidth, and whether it is a high-load cell; as shown in Table 6, the optimization plan algorithm for active indoor 4G high-load cells;

[0073] Table 6 Active indoor 4G high-load cell optimization algorithm

[0074] Serial number type Frequency band bandwidth Optimization plan 1 Active room division 1.8G 20M Active chamber splitting 2 Active room division 2.1G 20M Active chamber splitting 3 Active room division 800M 20M Active chamber splitting

[0075] (1) The cell frequency band is 800M, the bandwidth is 20M, and the output optimization solution is active room splitting;

[0076] (2) The cell frequency band is 1.8G, the bandwidth is 20M, and the output optimization solution is active room splitting;

[0077] (3) The cell frequency band is 2.1G, the bandwidth is 10M, and the output optimization solution is active indoor splitting.

[0078] 3. Outdoor optimization solution

[0079] According to the cell type, outdoor frequency band, outdoor high-load frequency band, physical direction traffic, physical direction design capacity, and considering 200MB of redundant traffic as a balancing space, an optimization plan is output; as shown in Table 7, the outdoor 4G high-load cell optimization plan algorithm;

[0080] Table 7 Outdoor 4G high-load cell optimization algorithm

[0081]

[0082]

[0083]

[0084] It should be noted that the blank part in Table 7 is automatically generated by the system.

[0085] (1) The outdoor frequency band is 1.8G, and the outdoor high-load frequency band is 1.8G. Output optimization solution: 2.1G needs to be expanded;

[0086] (2) The outdoor frequency band is 1.8G2.1G, the outdoor high-load frequency band is 1.8G, the physical direction design capacity - physical direction traffic > 200MB, output optimization solution: load balancing;

[0087] (3) The outdoor frequency band is 1.8G2.1G, the outdoor high-load frequency band is 1.8G, the physical direction design capacity - physical direction traffic ≤ 200MB, and the output optimization solution: sector splitting;

[0088] (4) The outdoor frequency band is 1.8G2.1G, and the outdoor high-load frequency band is 1.8G2.1G. The output optimization solution is sector splitting.

[0089] (5) The outdoor frequency band is 1.8G2.1G, the outdoor high-load frequency band is 2.1G, the physical direction design capacity - physical direction traffic> 200MB, output optimization solution: load balancing;

[0090] (6) The outdoor frequency band is 1.8G2.1G, the outdoor high-load frequency band is 2.1G, the physical direction design capacity - physical direction traffic ≤ 200MB, output optimization solution: sector splitting;

[0091] (7) The outdoor frequency band is 1.8G2.1G800M, the outdoor high-load frequency band is 1.8G, the physical direction design capacity - physical direction traffic> 200MB, output optimization solution: load balancing;

[0092] (8) The outdoor frequency band is 1.8G2.1G800M, the outdoor high-load frequency band is 1.8G, the physical direction design capacity - physical direction traffic ≤ 200MB, and the output optimization solution: sector splitting;

[0093] (9) The outdoor frequency band is 1.8G2.1G800M, the outdoor high-load frequency band is 1.8G2.1G, the physical direction design capacity - physical direction traffic> 200MB, output optimization solution: load balancing;

[0094] (10) The outdoor frequency band is 1.8G2.1G800M, the outdoor high-load frequency band is 1.8G2.1G, the physical direction design capacity - physical direction traffic ≤ 200MB, output optimization solution: sector splitting;

[0095] (11) The outdoor frequency band is 1.8G2.1G800M, and the outdoor high-load frequency band is 1.8G2.1G800M. The output optimization solution is sector splitting.

[0096] (12) The outdoor frequency band is 1.8G2.1G800M, the outdoor high-load frequency band is 1.8G800M, the physical direction design capacity - physical direction traffic> 200MB, output optimization solution: load balancing;

[0097] (13) The outdoor frequency band is 1.8G2.1G800M, the outdoor high-load frequency band is 1.8G800M, the physical direction design capacity - physical direction traffic ≤ 200MB, output optimization solution: sector splitting;

[0098] (14) The outdoor frequency band is 1.8G2.1G800M, the outdoor high-load frequency band is 2.1G, the physical direction design capacity - physical direction traffic> 200MB, output optimization solution: load balancing;

[0099] (15) The outdoor frequency band is 1.8G2.1G800M, the outdoor high-load frequency band is 2.1G, the physical direction design capacity - physical direction traffic ≤ 200MB, output optimization solution: sector splitting;

[0100] (16) The outdoor frequency band is 1.8G2.1G800M, the outdoor high-load frequency band is 2.1G800M, the physical direction design capacity - physical direction traffic> 200MB, output optimization solution: load balancing;

[0101] (17) The outdoor frequency band is 1.8G2.1G800M, the outdoor high-load frequency band is 2.1G800M, the physical direction design capacity - physical direction traffic ≤ 200MB, output optimization solution: sector splitting;

[0102] (18) The outdoor frequency band is 1.8G2.1G800M, the outdoor high-load frequency band is 800M, the physical direction design capacity - physical direction traffic> 200MB, output optimization solution: load balancing;

[0103] (19) The outdoor frequency band is 1.8G2.1G800M, the outdoor high-load frequency band is 800M, the physical direction design capacity - physical direction traffic ≤ 200MB, output optimization solution: sector splitting;

[0104] (20) The outdoor frequency band is 1.8GG800M, the outdoor high-load frequency band is 1.8G, the physical direction design capacity - physical direction traffic> 200MB, output optimization solution: load balancing;

[0105] (21) The outdoor frequency band is 1.8G800M, the outdoor high-load frequency band is 1.8G, the physical direction design capacity - physical direction traffic ≤ 200MB, the output optimization plan: need to expand 2.1G;

[0106] (22) The outdoor frequency band is 1.8GG800M, and the outdoor high-load frequency band is 1.8G800M. The output optimization solution: 2.1G needs to be expanded;

[0107] (23) The outdoor frequency band is 1.8GG800M, the outdoor high-load frequency band is 800M, the physical direction design capacity - physical direction traffic> 200MB, output optimization solution: load balancing;

[0108] (24) The outdoor frequency band is 1.8G800M, the outdoor high-load frequency band is 800M, the physical direction design capacity - physical direction traffic ≤ 200MB, output optimization plan: need to expand 2.1G;

[0109] (25) The outdoor frequency band is 2.1G, and the outdoor high-load frequency band is 2.1G. Output optimization solution: 1.8G needs to be expanded;

[0110] (26) The outdoor frequency band is 2.1GG800M, the outdoor high-load frequency band is 2.1G, the physical direction design capacity - physical direction traffic> 200MB, output optimization solution: load balancing;

[0111] (27) The outdoor frequency band is 2.1G800M, the outdoor high-load frequency band is 2.1G, the physical direction design capacity - physical direction traffic ≤ 200MB, output optimization plan: need to expand 1.8G;

[0112] (28) The outdoor frequency band is 2.1G800M, the outdoor high-load frequency band is 2.1G800M, the physical direction design capacity - physical direction traffic ≤ 200MB, output optimization plan: need to expand 1.8G;

[0113] (29) The outdoor frequency band is 2.1G800M, the outdoor high-load frequency band is 800M, the physical direction design capacity - physical direction traffic> 200MB, output optimization solution: load balancing;

[0114] (30) The outdoor frequency band is 2.1G800M, the outdoor high-load frequency band is 800M, the physical direction design capacity - physical direction traffic ≤ 200MB, output optimization plan: need to expand 1.8G;

[0115] (31) The outdoor frequency band is 800M, and the outdoor high-load frequency band is 800M. The output optimization solution: 1.8G needs to be expanded.

[0116] See also Figure 2 , the second aspect of the present invention proposes an automatic output system based on 4G high-load optimization scheme, including an adaptive selection algorithm module, a decision tree construction algorithm module, an edge computing module and an execution module;

[0117] The adaptive selection algorithm module automatically extracts the basic information table and sends it to the decision tree algorithm module;

[0118] Specifically, the clustering-based adaptive selection algorithm uses clustering methods to automatically select the best set of features for analysis. The algorithm can adaptively adjust parameters according to the characteristics of different data sets, including the number of clusters, distance measurement, etc., to obtain better analysis results. At the same time, the algorithm can also solve the problem of feature selection in traditional classification algorithms, improving the accuracy and efficiency of classification. The algorithm is used to automatically propose the cell name, frequency band, bandwidth and other information of the engineering parameter table, and output the basic information table.

[0119] The decision tree algorithm module is constructed to automatically output 4G high-load cells and send the evaluation results to the edge computing module and the execution module;

[0120] Specifically, according to the set conditions, the extracted cell data table is subjected to multi-layer screening according to the characteristics such as the frequency band and bandwidth in the basic information table; the data set is divided into multiple subsets according to the selected characteristics; and then the 4G high-load cells are output according to the frequency band and bandwidth according to the definition of high-load cells.

[0121] In addition, it automatically outputs the same-direction traffic, capacity, frequency band, etc. of the 4G high-load cell, and sends the evaluation results to the edge computing module and execution module.

[0122] Specifically, the selection is made based on the characteristics such as the special site name, downlink traffic, downlink traffic threshold, frequency band, bandwidth, etc.; the data set is divided, and the frequency band, traffic, and capacity (calculated according to bandwidth) are calculated according to the physical site + azimuth of the 4G high-load cell (that is, for multi-band cells with the same coverage direction of the co-site), and the "outdoor frequency band, outdoor high-load frequency band, physical direction traffic, and physical direction design capacity" of the 4G high-load cell co-site are output as the basis for the 4G high-load cell optimization plan.

[0123] The edge computing module and execution module automatically output 4G high-load optimization solutions.

[0124] Specifically, according to the decision tree algorithm module, the physical site name, azimuth, frequency band, bandwidth, outdoor frequency band, outdoor high-load frequency band, physical direction traffic, physical direction design capacity, and whether it is a high-load cell are output according to the set algorithm, and the 4G high-load cell optimization plan is automatically output.

[0125] Among them, the edge computing module can realize low latency, high reliability, and low bandwidth requirements for real-time transmission of the optimal solution. The execution module automatically debugs the 4G high-load optimization solution according to the optimal solution to improve the flexibility and wide application of the system.

[0126] In this embodiment, the automatic output of the 4G high-load cell optimization plan adopts an adaptive selection algorithm module to construct a decision tree algorithm module, an edge computing module and an execution module. The 4G high-load cell optimization plan is automatically output according to the following algorithm based on the physical site name_azimuth, frequency band, bandwidth, outdoor frequency band, outdoor high-load frequency band, physical direction traffic, physical direction design capacity, and whether it is a high-load cell.

[0127] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A method for automatically outputting a 4G high-load optimization solution, characterized in that: The following steps are involved: Step 1: Select characteristic information of the cell base station from the engineering parameter table based on clustering adaptive selection algorithm to establish a basic information table; wherein the characteristic information of the cell base station includes base station service information and base station location information; Step 2: Extract 4G cell data according to the 4G cell high load evaluation index, and determine and count the 4G high load cells; Step 3: Based on the statistically obtained 4G high-load cells, the outdoor frequency band, outdoor high-load frequency band, physical direction traffic, and physical direction design capacity are statistically output in combination with the physical site name and azimuth; Step 4: Output the 4G high-load cell optimization plan based on the information in the basic information table, outdoor frequency band, outdoor high-load frequency band, physical direction traffic and physical direction design capacity, and cell nature; the cell nature includes high-load cell and non-high-load cell.

2. The method for automatically outputting a 4G high-load optimization solution according to claim 1, characterized in that: The extracting 4G cell data according to the 4G cell high load definition index and determining the high load cell includes: According to the extracted 4G cell data, the frequency band and bandwidth are extracted from the sorted basic information table, and the 4G high-load cell is determined in combination with the high-load cell evaluation indicators.

3. The method for automatically outputting a 4G high-load optimization solution according to claim 2, characterized in that: 4G cell data includes existing network indicator traffic, PRB utilization and number of RRC users; existing network indicator traffic includes PDCP layer downlink traffic and PDCP layer uplink traffic.

4. The method for automatically outputting a 4G high-load optimization solution according to claim 1, characterized in that: Outdoor frequency band: Through the cell name, frequency band, physical site name, azimuth, and physical site name_azimuth statistics, the outdoor frequency band of the corresponding physical direction is obtained; Outdoor high-load frequency band: According to the cell name, the frequency band of the high-load cell, the physical site name, and the azimuth, the outdoor high-load frequency band of the corresponding physical direction is obtained by counting the physical site name_azimuth; Physical direction traffic: The physical direction traffic of the corresponding physical direction is obtained by counting the cell name, 5.3 PDCP layer downlink traffic (MB), physical site name, and azimuth according to the physical site name_azimuth. Physical direction design capacity: The physical direction design capacity of the corresponding physical direction is obtained by counting the cell name, frequency band, bandwidth, downlink traffic threshold, physical site name, and azimuth, and using the physical site name_azimuth statistics.

5. The method for automatically outputting a 4G high-load optimization solution according to claim 1, characterized in that: According to the information in the basic information table, as well as the outdoor frequency band, outdoor high-load frequency band, physical direction traffic and physical direction design capacity, the cell nature outputs the 4G high-load cell optimization plan, including: Passive / indoor optimization solution: Output optimization solutions based on cell type, cell frequency band, bandwidth, and cell nature; Outdoor optimization solution: Design capacity based on cell type, outdoor frequency band, outdoor high-load frequency band, physical direction traffic, and physical direction, while taking 200MB of redundant traffic into account as a balancing space and outputting an optimization plan.

Images