WO2021012835A1 - Procédé et appareil d'optimisation de paramètres d'alimentation d'antenne, dispositif de réseau, et support de stockage - Google Patents

Procédé et appareil d'optimisation de paramètres d'alimentation d'antenne, dispositif de réseau, et support de stockage Download PDF

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WO2021012835A1
WO2021012835A1 PCT/CN2020/096206 CN2020096206W WO2021012835A1 WO 2021012835 A1 WO2021012835 A1 WO 2021012835A1 CN 2020096206 W CN2020096206 W CN 2020096206W WO 2021012835 A1 WO2021012835 A1 WO 2021012835A1
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cell
adjustment
cells
adjusted
evaluation
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PCT/CN2020/096206
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English (en)
Chinese (zh)
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胡丹
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中兴通讯股份有限公司
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/04—Arrangements for maintaining operational condition

Definitions

  • the present invention relates to the field of communications, in particular to a method, device, network equipment and storage medium for optimizing antenna feeder parameters.
  • VoLTE Voice over Long-Term Evolution
  • LTE networks under all-IP conditions. It is the foundation of rich media converged communications and the key to high-quality voice services in the LTE era. VoLTE can bring business value to operators such as reducing network costs and improving user perception.
  • VoLTE has different characteristics from LTE. Therefore, if traditional manual solutions to solve LTE wireless side problems are used to solve VoLTE wireless side problems, new problems may arise. More importantly, traditional manual solutions rely on manual troubleshooting, problem solving, etc., so the problem solving efficiency is low. Once a problem occurs, it will affect the user's VoLTE voice service experience for a long time, and the traditional manual solution has high operation and maintenance costs. , Is not conducive to the optimal allocation of resources.
  • the antenna feeder parameter optimization method, device, network equipment, and storage medium provided by the embodiments of the present invention mainly solve the technical problems of using manual solutions for VOLTE voice services in related technologies, such as low efficiency and high operation and maintenance costs.
  • an embodiment of the present invention provides a method for optimizing antenna feeder parameters, including: determining the reason for the poor quality of the VoLTE (voice service based on the IP multimedia subsystem) cell to be optimized as one of the preset reasons; Determine the adjusted cell for this optimization in the cell, and the adjusted cell has a non-strong neighbor relationship with other adjusted cells in this adjustment period; determine the target antenna feeder parameter of the adjusted cell, and compare all the parameters according to the target antenna feeder parameter.
  • the antenna feeder parameters of the adjusted cell are adjusted; the effect of this adjustment is evaluated, and if the evaluation result indicates that the adjustment of the adjusted cell is effective, the adjustment of the adjusted cell is maintained.
  • the embodiment of the present invention also provides an antenna feeder parameter optimization device, which includes: a problem location module configured to determine the reason for the poor VoLTE quality of the cell to be optimized as one of the preset reasons; the cell selection module configured to determine from the cell to be optimized The optimized adjusted cell this time, the adjusted cell has a non-strong neighbor relationship with other adjusted cells in this adjustment period; the parameter optimization module is set to determine the target antenna feeder parameters of the adjusted cell, and based on the target antenna feeder The parameters adjust the antenna feeder parameters of the adjusted cell; the effect evaluation module is set to evaluate the effect of this adjustment, and if the evaluation result indicates that the adjustment of the adjusted cell is effective, the adjustment of the adjusted cell is maintained .
  • a problem location module configured to determine the reason for the poor VoLTE quality of the cell to be optimized as one of the preset reasons
  • the cell selection module configured to determine from the cell to be optimized The optimized adjusted cell this time, the adjusted cell has a non-strong neighbor relationship with other adjusted cells in this adjustment period
  • the parameter optimization module is set to determine the target antenna
  • the embodiment of the present invention also provides a network device, the network device includes a processor, a memory, and a communication bus; the communication bus is configured to realize connection and communication between the processor and the memory;
  • the processor is configured to execute one or more programs stored in the memory to implement the steps of the antenna feed parameter optimization method described above.
  • the embodiment of the present invention also provides a computer storage medium, and the storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps of the antenna feed parameter optimization method.
  • the antenna feeder parameter optimization method, device, network equipment, and storage medium provided in the embodiments of the present invention determine that the reason for the poor VoLTE quality of the cell to be optimized is one of the preset reasons, and then select from the cell to be optimized Determine the optimized adjustment cell this time, determine the target antenna feeder parameters of the adjusted cell, and adjust the antenna feeder parameters of the adjusted cell according to the target antenna feeder parameters, and then evaluate the effect of this adjustment, if the evaluation result characterizes this adjustment If it is valid, the adjustment will be maintained, otherwise the adjustment will be rolled back.
  • the adjustment cell is selected, and then the target antenna feeder parameters for the adjusted cell are automatically determined and based on the target antenna feeder parameters Adjust the antenna feeder parameters of the adjusted cell. After the adjustment, the adjustment effect will be further evaluated to avoid the negative impact of improper adjustment on VoLTE.
  • the process of problem location, problem optimization, and optimization evaluation is fully automated without manual participation, which is conducive to reducing network operation and maintenance costs.
  • the automated antenna feeder parameter optimization solution has high optimization efficiency and can be solved in time after VoLTE problems occur, reducing the impact of VoLTE problems on users' voice services, and improving user experience.
  • FIG. 1 is a flowchart of a method for optimizing antenna feeder parameters provided in Embodiment 1 of the present invention
  • FIG. 2 is a flowchart of a network device in the first embodiment of the present invention for determining and adjusting a cell
  • FIG. 3 is a flow chart of the network device in the first embodiment of the present invention determining an adjustment cell set from the cells to be optimized;
  • FIG. 5 is a flow chart for evaluating the evaluation effect of the adjusted cell by the network equipment provided in the second embodiment of the present invention.
  • FIG. 6 is a flow chart of the network device in the second embodiment of the present invention determining and adjusting the evaluation area of the cell;
  • FIG. 7 is a schematic structural diagram of an antenna feeder parameter optimization device provided in Embodiment 3 of the present invention.
  • FIG. 8 is another schematic structural diagram of the antenna feeder parameter optimization device provided in Embodiment 3 of the present invention.
  • FIG. 9 is a schematic diagram of a hardware structure of a network device provided in Embodiment 5 of the present invention.
  • this embodiment provides an antenna feeder parameter For the optimization method, please refer to a flow chart of the antenna feeder parameter optimization method shown in Figure 1:
  • S102 Determine whether the reason for the poor VoLTE quality of the cell to be optimized is one of the preset reasons.
  • the so-called cell to be optimized refers to the cell with poor VoLTE quality and the cell that needs to be optimized.
  • the cells to be optimized are automatically selected by the network equipment.
  • the network equipment can evaluate the VoLTE quality of each cell in a predetermined area to select those voice service qualities.
  • the poorer cell is regarded as the cell to be optimized.
  • the network device may determine the MOS value of each cell in the predetermined area, and then determine the cell to be optimized according to the MOS value of each cell.
  • the network device may obtain VoLTE data and MR data of all cells in a predetermined area, and then associate the VoLTE data and MR data of a cell to calculate the MOS value of the slice level (5 seconds is a slice).
  • the network equipment determines whether the MOS value of each slice is poor quality, and determines the MOS quality poor ratio of each cell (that is, the number of poor quality slice MOS values in the cell/the number of all slice MOS values in the cell ), the cell with the top 1/3 of the MOS poor quality ratio is determined as the cell to be optimized. Assuming that there are six cells a, b, c, d, e, and f in the predetermined area, when the network device selects the cell to be optimized, it will select 1/3 of the six cells, that is, two cells . If the first and second cells in the MOS quality ratio among the six cells are c and a respectively, then the cells to be optimized determined by the network equipment are a and c.
  • the cell to be optimized may be manually reported by other equipment or network administrators, because when the VoLTE quality of a cell is not good, the voice services of users in the cell will definitely be affected. Users can perceive.
  • the network administrator can designate the cell to be optimized to the network equipment according to user complaints.
  • the so-called preset reasons in this embodiment include, but are not limited to, coverage reasons, interference reasons, and capacity reasons. If the network equipment determines that the reason for the poor VoLTE quality of the cell to be optimized is one of the above three reasons, then The VoLTE quality optimization of the cell to be optimized can be achieved through this case. It is understandable that the reasons for the poor VoLTE quality of all cells to be optimized are not necessarily the same. For example, in an example of this embodiment, the cell to be optimized a The poor quality of VoLTE is due to coverage reasons, and the cells to be optimized c is because of interference problems.
  • S104 Determine the adjusted cell for this optimization from the cells to be optimized.
  • the network device may select the adjusted cell optimized this time from the cells to be optimized.
  • one or more adjustment cells in the cell to be optimized can be adjusted, and each adjustment cell in the same adjustment period can form an "adjustment cell set".
  • each adjustment cell in the same adjustment period can form an "adjustment cell set".
  • its strong neighboring cell refers to the neighboring cell that has a strong correlation with the cell:
  • the judgment can be made based on the MR of the cell to determine the frequency of the neighboring cell in the MR of the cell Is it high enough? If it is, it is its strong neighbor; otherwise, it is not its strong neighbor. In an example of this embodiment, only when the proportion of a neighboring cell appearing in the MR of a cell reaches the preset strong neighboring cell ratio, will the neighboring cell be determined as the strong neighboring cell of the corresponding cell.
  • the proportion of strong neighbors of a cell a in the MR of a cell a must reach 5%. If the terminals in cell a report a total of 100 MRs, then if a cell is the MR of cell a Strong neighbor cell, the cell appears in the MR in cell a at least 5 times.
  • the proportion of all neighboring cells of the cell in the MR of the cell can be determined, and then the top k neighbors can be selected. District as a strong neighbor. For example, if a cell b has 80 neighboring cells, 10 of which will be determined as strong neighbors, you can determine the frequency or proportion of these 80 neighboring cells in the MR of cell b, and then select the frequency or proportion The top 10 neighboring cells with a higher ranking are regarded as strong neighbors of cell b.
  • the network device when the network device determines the adjusted cell in this adjustment from the optimized cell, it may first determine the adjusted cell set. Please refer to Figure 2 for a process for the network device to determine the adjusted cell. Picture:
  • S202 Determine a set of adjustment cells to be optimized in this adjustment period from the cells to be optimized.
  • the network device when the network device determines the adjusted cell set corresponding to this adjustment period from the cells to be optimized, it only needs to ensure that there is no strong neighbor relationship between the cells in the adjusted cell set. In this case Next, the network device can determine the set of cells to be adjusted according to the flowchart shown in Figure 3:
  • the network equipment may first randomly select a cell from the cells to be optimized to join the adjusted cell set.
  • S304 Select a cell with a non-strong neighbor relationship with the adjusted cell set from the remaining cells to be optimized to join the adjusted cell set;
  • S306 Determine whether there are still cells in the cell to be optimized that do not have a strong neighbor relationship with each cell in the adjusted cell set;
  • the network device can also limit the selection of the adjusted cell set by the number. For example, if the number of cells in the adjusted cell set cannot exceed 6, the network device selects according to the process shown in FIG. 3 When adjusting the cell, although there are still other qualified cells in the cell to be optimized, it is not because the number of cells in the current adjusted cell set has reached 6, the network device will not continue to select.
  • the concentration of adjusted cells selected by the network device not only requires that there is no strong neighbor relationship between the cells, but also considers the impact of the selected adjusted cells if they are adjusted.
  • the network device may preferentially select a cell with a large number of users among the cells to be optimized. For example, in an example of this embodiment, the network device may select the first n cells with a larger number of reported MRs or cells with a reported MR number greater than m to form the set of adjusted cells corresponding to this adjustment period.
  • the network device has a priority when determining to adjust the cell set.
  • a cell with a low average cell MOS for example, a network device selects a cell with an average cell MOS lower than a preset average to form an adjusted cell set corresponding to this adjustment period.
  • the average cell MOS mentioned here refers to the average MOS determined based on at least two MOS values of a cell.
  • the network equipment can also combine the above two principles to select those cells with a larger coverage area and poor VoLTE quality to form an adjusted cell set.
  • the network equipment can First select the first n cells with a larger reported MR number or cells with a reported MR number greater than m from the cells to be optimized to form the first cell set, and then select the cells with the average MOS lower than the preset average from the first cell set. The adjusted cell set corresponding to this adjustment period.
  • the network device may first select cells with a cell MOS average value lower than the preset average value from the cells to be optimized to form a second cell set, and then select and report a larger MR number from the second cell set.
  • the first n cells or the cells whose reported MR number is greater than m constitute the adjusted cell set corresponding to this adjustment period.
  • the network device may also select the first cell set and the second cell set at the same time, and then determine that the intersecting cells of the first cell set and the second cell set constitute an adjusted cell set.
  • the network device After determining the adjusted cell set, when determining the adjusted cell from the adjusted cell set, the network device randomly selects a cell that has not yet been adjusted.
  • the network equipment can adjust the antenna feeder parameters for only one adjustment cell during each adjustment process, but because each adjustment process of the network equipment needs to interact with the base station, if each adjustment process only adjusts If an adjustment cell in the cell set is adjusted, when the adjustment cell set includes multiple adjustment cells, the network device needs to interact with the base station multiple times. Therefore, in some examples of this embodiment, the network device performs each adjustment process Two or more adjustment cells can be selected from the adjustment cell set. For example, in an example of this embodiment, the network device can adjust all adjustment cells in the adjustment cell set in one adjustment process.
  • the network device will first determine the adjusted cell set from the cells to be optimized, and then select the adjusted cell set for this adjustment from the adjusted cell set.
  • the network device may directly select an adjustment cell from the cells to be optimized without first determining an adjustment cell set.
  • the network device also needs to ensure that there is no strong neighbor relationship between the adjusted cells selected in the same adjustment period. For example, if during a certain adjustment process, the network equipment selects two cells from the cells to be optimized as adjustment cells, on the one hand, the network equipment needs to ensure that these two cells are different from those selected during other adjustment processes in this adjustment period. Strong neighbor relationship. On the other hand, the network equipment must ensure that the two cells selected this time are not in a strong neighbor relationship with each other.
  • S106 Determine the target antenna feeder parameter of the adjusted cell, and adjust the antenna feeder parameter of the adjusted cell according to the target antenna feeder parameter.
  • the network device can determine the target antenna feeder parameter of the adjusted cell.
  • the so-called target antenna feeder parameters are the antenna feeder parameters that are determined according to the relevant performance and attributes of the adjusted cell and can make VoLTE quality relatively ideal.
  • the network device may determine the target antenna feeder parameter of the adjusted cell according to at least one of the inherent attribute parameter and the performance index parameter of the adjusted cell.
  • the inherent attribute parameters mentioned here include but are not limited to adjusting the station height of the cell.
  • Performance index parameters include at least one of these types of parameters: RSRP (Reference Signal Received Power), TA (Timing Advance, timing advance), over coverage, and weak coverage.
  • RSRP Reference Signal Received Power
  • TA Timing Advance, timing advance
  • over coverage and weak coverage.
  • weak coverage weak coverage
  • the network equipment can adjust the antenna feeder parameters of the adjusted cell according to the target antenna feeder parameters.
  • the network equipment can send adjustment instructions to the base station, and the sent instructions include the target for adjusting the cell.
  • the antenna feeder parameter so that after the base station receives the adjustment instruction sent by the network device, it can adjust the antenna feeder parameter of the corresponding cell according to the target antenna feeder parameter therein.
  • the network equipment adjusts the antenna feeder parameters of the adjusted cell, it should first determine that the current antenna feeder parameters of the adjusted cell are inconsistent with the determined target antenna feeder parameters. Otherwise, if the current antenna feeder parameters of the adjusted cell are different from the determined target antenna feeder parameters. If the target antenna feeder parameters are consistent, the network device does not need to send adjustment instructions to the base station.
  • the network equipment After adjusting the antenna feeder parameters of the adjusted cell, the network equipment will also evaluate the effect of this adjustment. If the evaluation result indicates that the adjustment is effective, the network equipment will maintain this adjustment.
  • the effective adjustment mentioned here means that the VoLTE quality of the adjusted cell is improved after adjustment. In some other examples of this embodiment, the so-called effective adjustment not only requires the VoLTE quality to be improved after the adjusted cell is adjusted, but also requires the degree of improvement.
  • the network device determines that its adjustment to a certain adjusted cell is effective, the network device will not optimize and adjust the adjusted cell during this adjustment period and other subsequent adjustment periods. Therefore, the network device can The adjusted cell is deleted from the cell to be optimized.
  • the network device determines that this adjustment is invalid after evaluation, it can consider rolling back this adjustment, that is, returning the antenna feeder parameters of the adjusted cell to the state before the adjustment. In some other examples of this embodiment, the network device will not roll back this adjustment. However, in either case, the network device will not allow the adjusted cell whose adjustment is invalid to remain in the cell to be optimized, so that Continue to optimize and adjust the cell in the subsequent process.
  • the antenna feeder parameter optimization method provided in this embodiment can determine the cell to be optimized according to the MOS value of each cell in the predetermined area, and then select the adjusted cell that needs to be optimized and adjusted this time from the cell to be optimized, and then select the adjusted cell that needs to be optimized and adjusted according to the At least one of the inherent attribute parameter and the performance index parameter is used to determine the target antenna feeder parameter of the adjusted cell. If the network device determines that the current antenna feeder parameter of the adjusted cell is inconsistent with the target antenna feeder parameter, it sends an adjustment instruction to the base station to allow the base station to adjust the antenna feeder parameter of the corresponding cell. Moreover, after the adjustment, the network equipment will also evaluate the evaluation effect, and determine whether to maintain the adjustment or roll back the adjustment according to the adjustment effect of the adjusted cell. Network equipment can automatically perform problem discovery, problem analysis, cause location, problem resolution, and effect evaluation on the VoLTE wireless side, reducing the manual intervention process and improving the efficiency of wireless network optimization.
  • This embodiment will introduce the effect evaluation process in the antenna feeder parameter optimization method based on the first embodiment.
  • S402 Determine the cell to be optimized according to the MOS value of each cell in the predetermined area.
  • the network device can determine the MOS value of each cell in the predetermined area, and then determine the cell to be optimized according to the MOS value of each cell. For example, the network device may calculate the slice level MOS value, and then select a cell with a MOS value lower than a preset MOS threshold as the cell to be optimized, or select a certain proportion of cells as the cell to be optimized in the order of MOS value from low to high. In some examples of this embodiment, the cell to be optimized may also be manually designated.
  • S404 Screen out cells whose reasons for the poor VoLTE quality in the cells to be optimized do not belong to the preset reasons.
  • the network equipment analyzes and locates the cause of the poor VoLTE quality of the cell to be optimized on the radio side, it does not analyze all the cells in the cell to be optimized as a whole at the same time, but analyzes the cells separately.
  • the cells to be optimized there may be some cells whose VoLTE quality is poor due to one of the preset reasons, but there may also be other cells where the poor VoLTE quality is not due to the preset reasons.
  • the problem of poor VoLTE quality in some cells to be optimized cannot be resolved through subsequent procedures, but the problem of poor VoLTE quality in some cells to be optimized can be resolved through subsequent procedures.
  • S406 Determine an adjustment cell set of the adjustment period from the cells to be optimized.
  • the network device can determine the set of adjustment cells corresponding to the adjustment period from the cells to be optimized.
  • the network device selects each adjustment cell in the adjustment period from the cells to be optimized, it will not only guarantee the selected adjustment cells The small area is not a strong neighbor, and it will try to choose which cells have a larger coverage area and relatively poor VoLTE quality.
  • the foregoing embodiment has already made a detailed introduction, and will not be repeated here.
  • those skilled in the art can understand that when the network device selects the cells that constitute the adjusted cell set, it may also refer to other principles for selection.
  • S408 For each adjustment cell in the adjustment cell set, determine the target antenna feeder parameter according to the inherent attribute parameter and performance index parameter of the adjustment cell.
  • the network device after the network device selects all adjustment cells in an adjustment period, it can adjust these adjustment cells together. That is, for each adjusted cell in the same adjustment period, the network device no longer determines the target antenna feeder parameters in stages. Therefore, after determining the set of adjustment cells, the network equipment determines the corresponding target antenna feeder parameters according to the inherent attribute parameters and performance index parameters of each adjustment cell.
  • the network equipment After the network equipment determines the target antenna feeder parameters corresponding to each adjusted cell, it sends these target antenna feeder parameters to the base station through an adjustment instruction, so that the base station can obtain the target antenna feeder parameters of each adjusted cell in the adjusted cell set according to the adjustment instruction. , And complete the adjustment of these adjusted cells according to the target antenna feeder parameters.
  • the network device when evaluating the adjustment effect of the adjusted cell, may only evaluate the evaluation indicators that reflect the quality of VoLTE before and after the adjustment of the adjusted cell, and then compare the adjusted results Is the evaluation index better than the evaluation index before the adjustment, so as to judge whether the adjustment is effective.
  • VoLTE Cell Quality Indicator 1 or 2
  • QCI Channel Quality Indicator
  • the evaluation of the network equipment involves not only the evaluation indicators related to VoLTE quality, but also the evaluation indicators affecting the quality of data traffic services.
  • the evaluation range of network equipment is not limited to adjusting the cell itself, but involves adjusting the neighboring cells of the cell or adjusting the strong neighbors of the cell. The following describes the process of evaluating the evaluation effect of the adjusted cell by the network equipment provided in this embodiment in conjunction with the flowchart shown in FIG. 5:
  • S502 Determine an evaluation area corresponding to the adjusted cell.
  • the evaluation area of an adjusted cell includes not only itself but also its neighboring cells.
  • the network device may refer to the flowchart shown in FIG. 6 to determine the evaluation area of the adjustment cell:
  • S602 Determine the neighboring cell of the adjusted cell according to the MR data of the adjusted cell.
  • the MR reported by users in a cell contains information about the neighboring cells of the cell.
  • the neighboring cells measured by users in different locations may be different, and there are many users in a cell. Therefore, the MR data reported by these many users can basically Determine all neighboring cells of the cell.
  • the network device may obtain the MR data reported by each user in the cell, and then determine the neighboring cell of the adjusted cell based on the MR data.
  • the network equipment will also determine the number of times each neighboring cell appears in the MR data according to the MR data of the adjusted cell. Of course, in some examples of this embodiment, the network equipment may also determine that each neighboring cell appears in the MR data of the adjusted cell. proportion. However, it should be understood that the amount of MR data acquired by the network device is certain, so whether it is to determine the number of occurrences of each neighboring cell in the MR data or the proportion of occurrences, the effect is the same.
  • S606 Select the first m cells with a higher number of occurrences as strong neighbors and the adjusted cells to form an evaluation area of the adjusted cells.
  • the network equipment selects the neighboring cell with a higher frequency of occurrence from these neighboring cells, that is, the strong neighboring cell, and the adjustment cell forms the adjustment cell.
  • the evaluation area of the evaluation For example, in an example of this embodiment, the network device may select the first m cells with a higher number of occurrences in the neighboring cells to form the evaluation area together with the adjusted cells. In some other examples of this embodiment, the network device may select the top q% of these neighboring cells, which has a higher proportion, and adjust the cell to form an evaluation area.
  • the network equipment After determining the evaluation area, the network equipment will calculate the current evaluation indicators in the evaluation area. It is understandable that the current evaluation indicators in the evaluation area represent the VoLTE quality and data flow service quality of the evaluation area after the adjustment cell is adjusted. These qualities need to be compared with the quality before the adjustment. Therefore, in the adjustment cell Before making adjustments, network equipment should determine the corresponding evaluation indicators for the evaluation area.
  • the evaluation index includes an index representing the RSRP of the evaluation area, an index representing the CQI of the evaluation area, and an index representing the MOS value of the evaluation area.
  • the indicators that characterize the RSRP of the evaluation area include the average RSRP value of the area and/or the ratio of RSRP ⁇ -110 of the cells in the evaluation area.
  • the average RSRP value here refers to the sum of the RSRP values of each cell in the evaluation area and the number of cells in the evaluation area. Ratio. For example, assuming that there are three cells a, b, and c in the evaluation area, and the RSRP values of these three cells are x1, x2, and x3, the average RSRP value of the evaluation area is (x1+x2+x3)/3 .
  • the indicators that characterize the MOS value of the evaluation area include at least one of the area MOS average value and the area poor quality ratio.
  • the meaning of the area MOS average value is similar to the meaning of the area RSRP average value. It refers to the sum of the MOS values of each cell in the evaluation area and the evaluation area
  • the ratio of the number of cells in the middle for example, for an evaluation area composed of three cells a, b, and c, if the MOS values of the three cells are y1, y2, and y3, then the average MOS value of the evaluation area is (y1 +y2+y3)/3.
  • the so-called regional poor quality ratio refers to the ratio of the number of cells in the evaluation area whose MOS value is lower than the preset threshold to the total number of cells in the evaluation area.
  • the evaluation indicators also include RSRQ (Reference Signal Received Quality, reference signal reception quality) indicators that characterize the assessment area, indicators that characterize the downlink throughput rate of the assessment area, and PRB (Physical Resource Block, At least one of the indicators of physical resource block utilization and indicators that characterize the number of active users in the evaluation area.
  • RSRQ Reference Signal Received Quality, reference signal reception quality
  • PRB Physical Resource Block
  • S506 Calculate the first evaluation score before adjustment and the second evaluation score after adjustment of the evaluation area respectively.
  • i denotes the i-th evaluation index
  • n is the total number of evaluation index
  • w i denotes the i th evaluation index corresponding weight. It is understandable that in some cases, the measurement of multiple evaluation indicators may be different, and some evaluation indicators are "positive indicators", the larger the value, the better the communication quality, while some evaluation indicators may be "negative indicators" , The smaller the value, the better the communication quality.
  • the network device may normalize the evaluation indexes with inconsistent weights and measures, uniformly convert the negative indexes into positive indexes, or convert the positive indexes into negative indexes at the same time, and then calculate the evaluation scores.
  • S508 Determine the difference between the second evaluation score and the first evaluation score.
  • the network device calculates the difference between the two. Assuming that all evaluation indicators are positive through the conversion of the network device, the final evaluation score should also be the larger the better. Therefore, The network device calculates the difference between the second evaluation score and the first evaluation score.
  • the network device After the network device calculates the difference between the second evaluation score and the first evaluation score, as long as the second evaluation score is greater than the first evaluation score Score, the network device will determine that this adjustment is valid. However, in some other examples of this embodiment, if the network device needs to determine that the difference between the second evaluation score and the first evaluation score reaches a certain threshold, the adjustment will be determined to be effective, otherwise, even the second evaluation score If the score is greater than the first evaluation score, the network industry equipment will also determine that this adjustment is invalid.
  • the network equipment determines that the adjustment to a certain adjusted cell is valid, it can remove the adjusted cell from the cell to be optimized. If the network equipment determines that the adjustment to a certain adjusted cell is invalid, it will not remove the adjusted cell from Move out of the cell to be optimized and adjusted so that the adjusted cell can get a chance to be adjusted again in other adjustment periods.
  • the antenna feeder parameter optimization method provided in this embodiment not only evaluates the adjustment effect after adjusting an adjustment cell, so as to remedy the effect of the adjustment cell with poor adjustment effect in time.
  • this embodiment will expand the evaluation during the evaluation Scope, while taking into account the evaluation indicators of data traffic services, to ensure that the signal strength of data traffic services is guaranteed while improving the quality of VoLTE.
  • This embodiment provides an antenna feeder parameter optimization device. Please refer to the schematic structural diagram of the antenna feeder parameter optimization device 70 shown in FIG. 7:
  • the antenna feeder parameter optimization device 70 includes a problem location module 702, a cell selection module 704, a parameter optimization module 706, and an effect evaluation module 708.
  • the problem location module 702 is configured to determine the reason for the poor VoLTE quality of the cell to be optimized as one of the preset causes ;
  • the cell selection module 704 is set to determine the optimized adjusted cell from the cells to be optimized, and the adjusted cell has a non-strong neighbor relationship with other adjusted cells in the adjustment period;
  • the parameter optimization module 706 is set to determine the target antenna feeder for the adjusted cell And adjust the antenna feeder parameters of the adjusted cell according to the target antenna feeder parameters;
  • the effect evaluation module 708 is set to evaluate the effect of this adjustment. If the evaluation result indicates that the adjustment of the adjusted cell is effective, the adjustment of the adjusted cell is maintained Adjustment.
  • the problem location module 702 determines whether the reason for the poor VoLTE quality of the cell to be optimized is one of the preset reasons. If the judgment result is yes, that is, the reason for the poor VoLTE quality of the cell to be optimized is one of the preset reasons, the cell selection module 704 and the parameter optimization module 706 can optimize the antenna feeder parameters; otherwise, this implementation is not suitable
  • the antenna feeder parameter optimization solution provided in the example solves the problem.
  • the so-called cell to be optimized refers to the cell with poor VoLTE quality and the cell that needs to be optimized.
  • the cell to be optimized is automatically selected by the antenna feeder parameter optimization device 70.
  • the antenna feeder parameter optimization device 70 can evaluate the VoLTE quality of each cell in a predetermined area. , Thus selecting those cells with poor voice service quality as the cells to be optimized.
  • the antenna feeder parameter optimization device 70 provided in FIG. 8 also includes a problem finding module 700.
  • the problem finding module 700 can determine the MOS value of each cell in a predetermined area, and then determine the cell to be optimized based on the MOS value of each cell.
  • the problem discovery module 700 can obtain VoLTE data and MR data of all cells in a predetermined area, and then correlate the VoLTE data and MR data of a cell to calculate the MOS value of the slice level (5 seconds is a slice) . After calculating the MOS of each cell, the problem discovery module 700 determines whether the MOS value of each slice is poor quality, and determines the MOS quality poor ratio of each cell (that is, the number of poor quality slice MOS values in the cell/all slice MOS values in the cell). Value), and the cell with the top 1/3 of the MOS poor quality ratio is determined as the cell to be optimized.
  • the problem discovery module 700 selects the cell to be optimized, it will select 1/3 of the six cells, that is, two cells. A cell. If the cells with the first and second MOS quality ratios among the six cells are c and a respectively, then the cells to be optimized determined by the problem discovery module 700 are a and c.
  • the cell to be optimized may be manually reported by other equipment or network administrators, because when the VoLTE quality of a cell is not good, the voice services of users in the cell will definitely be affected. Users can perceive.
  • the network administrator can specify the cell to be optimized to the antenna feeder parameter optimization device 70 according to the user's complaint.
  • the so-called preset reasons in this embodiment include, but are not limited to, coverage reasons, interference reasons, and capacity reasons. If the problem location module 702 determines that the reason for the poor VoLTE quality of the cell to be optimized is one of the above three reasons , Then the VoLTE quality optimization of the cell to be optimized can be achieved through this case. It is understandable that the reasons for the poor VoLTE quality of all cells to be optimized are not necessarily the same. For example, in an example of this embodiment, the cell to be optimized a The poor quality of VoLTE is due to coverage reasons, and the cells to be optimized c is because of interference problems.
  • the cell selection module 704 may select the adjusted cell optimized this time from the cells to be optimized.
  • the cell to be optimized can be adjusted, and each adjustment cell in the same adjustment period can form an "adjustment cell set".
  • the cell selection module 704 may select the adjusted cell optimized this time from the cells to be optimized.
  • one or more adjustment cells in the cell to be optimized can be adjusted, and each adjustment cell in the same adjustment period can form an "adjustment cell set".
  • its strong neighboring cell refers to the neighboring cell that has a strong correlation with the cell:
  • the cell selection module 704 determines whether the neighboring cell of a certain cell is a strong neighbor of the cell, the determination can be made based on the MR of the cell to determine the MR of the neighboring cell in the cell. Whether the frequency that appears in the cell is high enough, if so, the cell selection module 704 determines that the neighboring cell is a strong neighboring cell of the cell, otherwise, it is not its strong neighboring cell. In an example of this embodiment, only when the proportion of a neighboring cell appearing in the MR of a cell reaches the preset strong neighboring cell ratio, will the neighboring cell be determined as the strong neighboring cell of the corresponding cell.
  • the proportion of strong neighbors of a cell a in the MR of a cell a must reach 5%. If the terminals in cell a report a total of 100 MRs, then if a cell is the MR of cell a Strong neighbor cell, the cell appears in the MR in cell a at least 5 times.
  • the cell selection module 704 when the cell selection module 704 judges whether the neighboring cells of a certain cell are strong neighbors of the cell, it can determine the proportion of all neighboring cells of the cell in the MR of the cell, and then select The first k neighbors are regarded as strong neighbors. For example, if a cell b has 80 neighboring cells, 10 of which will be determined as strong neighbors, you can determine the frequency or proportion of these 80 neighboring cells in the MR of cell b, and then select the frequency or proportion The top 10 neighboring cells with a higher ranking are regarded as strong neighbors of cell b.
  • the cell selection module 704 when the cell selection module 704 determines the adjusted cell in this adjustment from the optimized cells, it may first determine the adjusted cell set:
  • the cell selection module 704 determines the adjusted cell set corresponding to the adjustment period from the cells to be optimized, it only needs to ensure that there is no strong neighbor relationship between the cells in the adjusted cell set. In this case, the cell selection module 704 can first randomly select a cell from the cells to be optimized to join the adjusted cell set, and then select and adjust a cell that has a non-strong neighbor relationship from the remaining cells to be optimized. Adjust the cell set.
  • the cell selection module 704 determines whether there are still cells in the cell to be optimized that do not have a strong neighbor relationship with each cell in the adjusted cell set; if the judgment result is yes, the cell selection module 704 continues to select and adjust cells from the cells to be optimized to join the adjustment Cell set, otherwise, it means that the adjustment cell set of this adjustment period has been selected. Therefore, the cell selection module 704 stops the selection.
  • the cell selection module 704 can also limit the selection determination of the adjusted cell set by number. For example, if the number of cells in the adjusted cell set cannot exceed 6, the cell selection module 704 selects according to the above method. When adjusting the cell, although there are still other qualified cells in the cell to be optimized, it is not because the number of cells in the current adjusted cell set has reached six, the cell selection module 704 will not continue to select.
  • the concentration of adjusted cells selected by the cell selection module 704 not only requires that there is no strong neighbor relationship between the cells, but also considers the impact of the selected adjusted cells if they are adjusted. Generally, if the number of users in a cell is large, when the VoLTE quality of this cell is poor, it will cause a huge number of users to have a bad voice service experience. Therefore, the cell selection module 704 should try to give priority to ensuring that the number of such users is large. VoLTE quality in a cell with a wide coverage. Therefore, in some examples of this embodiment, when determining to adjust the cell set, the cell selection module 704 may preferentially select a cell with a large number of users among the cells to be optimized. For example, in an example of this embodiment, the cell selection module 704 may select the first n cells with a larger number of reported MRs or cells with a reported MR number greater than m to form the adjusted cell set corresponding to this adjustment period.
  • the cell selection module 704 determines to adjust the cell set.
  • the cell with a lower average cell MOS is preferentially selected.
  • the cell selection module 704 selects a cell with an average cell MOS lower than the preset average to form an adjusted cell set corresponding to this adjustment period.
  • the average cell MOS mentioned here refers to the average MOS determined based on at least two MOS values of a cell.
  • the cell selection module 704 can also combine the above two principles to select those cells with a larger coverage area and poor VoLTE quality to form an adjusted cell set.
  • the cell The selection module 704 may first select the first n cells with a larger reported MR number or cells with a reported MR number greater than m from the cells to be optimized to form the first cell set, and then select cells from the first cell set with an average MOS value lower than the preset The average cell constitutes the set of adjusted cells corresponding to this adjustment period.
  • the cell selection module 704 may first select cells with a cell MOS average value lower than the preset average value from the cells to be optimized to form the second cell set, and then select and report the MR number from the second cell set. The larger first n cells or the cells with the reported MR number greater than m constitute the adjusted cell set corresponding to this adjustment period.
  • the cell selection module 704 can also simultaneously select the first cell set and the second cell set, and then determine that the intersection of the first cell set and the second cell set constitutes an adjusted cell set.
  • the cell selection module 704 randomly selects a cell that has not yet been adjusted.
  • the parameter optimization module 706 can adjust the antenna feeder parameters of only one adjustment cell during each adjustment process, but because the parameter optimization module 706 needs to interact with the base station during each adjustment process, if each adjustment process is The process only adjusts one adjustment cell in the adjustment cell set.
  • the adjustment cell set includes multiple adjustment cells, the parameter optimization module 706 needs to interact with the base station multiple times. Therefore, in some examples of this embodiment, the cell selection The module 704 can select two or more adjustment cells from the adjustment cell set during each adjustment process. For example, in an example of this embodiment, the parameter optimization module 706 can select the adjustment cells in the adjustment process. All adjusted cells have been adjusted.
  • the cell selection module 704 will first determine the adjusted cell set from the cells to be optimized, and then select the adjusted cell set for this adjustment from the adjusted cell set.
  • the cell selection module 704 can directly select an adjustment cell from the cells to be optimized without first determining an adjustment cell set.
  • the cell selection module 704 also needs to ensure that there is no strong neighbor relationship between the adjusted cells selected in the same adjustment period. For example, if in a certain adjustment process, the cell selection module 704 selects two cells from the cells to be optimized as the adjustment cells, the cell selection module 704 needs to ensure that these two cells are different from other adjustment processes in the adjustment period. The selected and adjusted cell is a non-strong neighbor relationship. On the other hand, the cell selection module 704 also needs to ensure that the two cells selected this time are not in a strong neighbor relationship with each other.
  • the parameter optimization module 706 may determine the target antenna feeder parameter of the adjusted cell.
  • the so-called target antenna feeder parameters are the antenna feeder parameters that are determined according to the relevant performance and attributes of the adjusted cell and can make VoLTE quality relatively ideal.
  • the parameter optimization module 706 may determine the target antenna feed parameter of the adjusted cell according to at least one of the inherent attribute parameter and the performance index parameter of the adjusted cell.
  • the inherent attribute parameters mentioned here include but are not limited to adjusting the station height of the cell.
  • the performance index parameters include at least one of these types of parameters: RSRP, TA, over coverage, and weak coverage. Of course, those skilled in the art can understand that the performance index parameters may also be other parameters.
  • the parameter optimization module 706 can adjust the antenna feeder parameters of the adjusted cell according to the target antenna feeder parameters.
  • the parameter optimization module 706 can send an adjustment instruction to the base station, and the sent instructions include The target antenna feeder parameter of the cell is adjusted, so that after the base station receives the adjustment instruction sent by the parameter optimization module 706, the antenna feeder parameter of the corresponding cell can be adjusted according to the target antenna feeder parameter therein.
  • the parameter optimization module 706 adjusts the antenna feeder parameters of the adjusted cell, it should first determine that the current antenna feeder parameters of the adjusted cell are inconsistent with the determined target antenna feeder parameters. Otherwise, if the current antenna feeder parameters of the adjusted cell are adjusted If the parameters are consistent with the target antenna feeder parameters, the parameter optimization module 706 does not need to send adjustment instructions to the base station.
  • the effect evaluation module 708 will also evaluate the effect of this adjustment. If the evaluation result indicates that the adjustment is effective, the effect evaluation module 708 will maintain the adjustment .
  • the effective adjustment mentioned here means that the VoLTE quality of the adjusted cell is improved after adjustment. In some other examples of this embodiment, the so-called effective adjustment not only requires the VoLTE quality to be improved after the adjusted cell is adjusted, but also requires the degree of improvement.
  • the effect evaluation module 708 determines that the adjustment of a certain adjusted cell is effective, the parameter optimization module 706 will not optimize and adjust the adjusted cell during this adjustment period and other subsequent adjustment periods. Therefore, , The effect evaluation module 708 can delete the adjusted cell from the cell to be optimized.
  • the effect evaluation module 708 determines that this adjustment is invalid after evaluation, it may consider rolling back this adjustment, that is, returning the antenna feeder parameters of the adjusted cell to the state before the adjustment. In some other examples of this embodiment, the effect evaluation module 708 will not roll back this adjustment. However, in either case, the effect evaluation module 708 will not allow the adjusted cell whose adjustment is invalid to remain in the cell to be optimized. In order to continue to optimize and adjust the cell in the subsequent process.
  • the antenna feeder parameter optimization device provided in this embodiment can determine the cell to be optimized according to the MOS value of each cell in the predetermined area, and then select the adjusted cell that needs to be optimized and adjusted this time from the cell to be optimized, and then according to the adjustment At least one of the inherent attribute parameter and the performance index parameter is used to determine the target antenna feeder parameter of the adjusted cell. If the antenna feeder parameter optimization device determines that the current antenna feeder parameters of the adjusted cell are inconsistent with the target antenna feeder parameters, it sends an adjustment instruction to the base station to allow the base station to adjust the antenna feeder parameters of the corresponding cell. Moreover, after the adjustment, the antenna feeder parameter optimization device will also evaluate the evaluation effect, and determine whether to maintain the adjustment or roll back the adjustment according to the adjustment effect of the adjusted cell.
  • the antenna feeder parameter optimization device can automatically perform problem discovery, problem analysis, cause location, problem resolution, and effect evaluation on the VoLTE wireless side, reducing the manual intervention process and improving the efficiency of wireless network optimization.
  • the problem discovery module 700 may determine the MOS value of each cell in the predetermined area, and then determine the cell to be optimized according to the MOS value of each cell. For example, the problem discovery module 700 may calculate the slice level MOS value, and then select the cell with the MOS value lower than the preset MOS threshold as the cell to be optimized, or select a certain proportion of the cells as the cell to be optimized in the order of MOS value from low to high . In some examples of this embodiment, the cell to be optimized may also be manually designated.
  • the problem location module 702 in the antenna feeder parameter optimization device 70 does not analyze all the cells in the cell to be optimized at the same time as a whole when analyzing and positioning the wireless side cause of the poor VoLTE quality of the cell to be optimized. Instead, analyze the cells separately. For example, for the cells to be optimized, there may be some cells with poor VoLTE quality due to one of the preset reasons, but there may also be other cells where the poor VoLTE quality is not due to the preset reasons. In this case, the problem of poor VoLTE quality in some cells to be optimized cannot be resolved through subsequent procedures, but the problem of poor VoLTE quality in some cells to be optimized can be resolved through subsequent procedures.
  • the cell selection module 704 can determine the set of adjusted cells corresponding to the adjustment period from the cells to be optimized.
  • the cell selection module 704 selects each adjustment cell in the adjustment period from the cells to be optimized, it will not only guarantee the selection
  • the adjusted cells are not strong neighboring cells, and will try to choose which ones have larger coverage areas and relatively poor VoLTE quality.
  • the foregoing embodiment has already made a detailed introduction, and will not be repeated here.
  • those skilled in the art can understand that when the cell selection module 704 selects the cells that constitute the adjusted cell set, it can also select other principles with reference to it.
  • the parameter optimization module 706 can adjust these adjusted cells together. That is, for each adjusted cell in the same adjustment period, the parameter optimization module 706 no longer determines the target antenna feeder parameters in stages. Therefore, after determining the adjusted cell set, the parameter optimization module 706 determines the corresponding target antenna feeder parameters according to the inherent attribute parameters and performance index parameters of each adjusted cell.
  • the parameter optimization module 706 determines the target antenna feeder parameters corresponding to each adjusted cell, it sends these target antenna feeder parameters to the base station through an adjustment instruction, so that the base station can obtain the target antenna for each adjusted cell in the adjusted cell set according to this adjustment instruction. Feed parameters, and complete the adjustment of these adjusted cells according to the target antenna feed parameters.
  • the effect evaluation module 708 may only evaluate the evaluation indicators that reflect the quality of VoLTE before and after the adjustment of the adjusted cell, and then compare Whether the adjusted evaluation index is better than the evaluation index before adjustment, so as to judge whether the adjustment is effective.
  • the evaluation by the effect evaluation module 708 not only involves evaluation indicators related to VoLTE quality, but also involves evaluation indicators affecting the quality of data traffic services.
  • the evaluation scope of the effect evaluation module 708 is not limited to adjusting the cell itself, but involves adjusting the strong neighbors of the cell.
  • the evaluation area of an adjusted cell includes not only itself but also its neighboring cells.
  • the effect evaluation module 708 can determine the neighboring cell of the adjusted cell according to the MR data of the adjusted cell: the MR reported by the user in a cell contains information about the neighboring cell of the cell, and the neighboring cells measured by the users in different positions Areas may be different, and there are many users in a cell. Therefore, through the MR data reported by these many users, all neighboring cells of the cell can be basically determined. For an adjusted cell, the effect evaluation module 708 can obtain the MR data reported by each user in the cell, and then determine the neighboring cell of the adjusted cell based on the MR data.
  • the effect evaluation module 708 counts the number of times each neighboring cell appears in the MR data of the adjusted cell.
  • the effect evaluation module 708 also determines the number of times each neighboring cell appears in the MR data according to the MR data of the adjusted cell.
  • the effect evaluation module 708 can also determine that each neighboring cell is in the adjusted cell.
  • the ratio that appears in the MR data it should be understood that the amount of MR data acquired by the effect evaluation module 708 is certain, so whether it is to determine the number of occurrences of each neighboring area in the MR data or the proportion of occurrences, the effect is consistent.
  • the effect evaluation module 708 selects the first m cells with higher occurrence times and the adjusted cells to form an evaluation area of the adjusted cells.
  • the effect evaluation module 708 selects neighboring cells with a higher frequency of occurrence from these neighboring cells, that is, selecting strong neighboring cells and forming a pair with the adjusted cell.
  • the effect evaluation module 708 may select the first m cells with a higher number of occurrences in the MR to form the evaluation area together with the adjusted cells.
  • the effect evaluation module 708 may select the top q% of these neighboring cells with a higher proportion and the adjusted cells to form the evaluation area.
  • the effect evaluation module 708 will calculate the current evaluation indicators in the evaluation area. It is understandable that the current evaluation indicators in the evaluation area represent the VoLTE quality and data flow service quality of the evaluation area after the adjustment cell is adjusted. These qualities need to be compared with the quality before the adjustment. Therefore, in the adjustment cell Before making adjustments, the effect evaluation module 708 should determine the corresponding evaluation index of the evaluation area.
  • the evaluation index includes an index representing the RSRP of the evaluation area, an index representing the CQI of the evaluation area, and an index representing the MOS value of the evaluation area.
  • the indicators that characterize the RSRP of the evaluation area include the average RSRP value of the area and/or the ratio of RSRP ⁇ -110 of the cells in the evaluation area.
  • the average RSRP value here refers to the sum of the RSRP values of each cell in the evaluation area and the number of cells in the evaluation area. Ratio. For example, assuming that there are three cells a, b, and c in the evaluation area, and the RSRP values of these three cells are x1, x2, and x3, the average RSRP value of the evaluation area is (x1+x2+x3)/3 .
  • the indicators that characterize the MOS value of the evaluation area include at least one of the area MOS average value and the area poor quality ratio.
  • the meaning of the area MOS average value is similar to the meaning of the area RSRP average value. It refers to the sum of the MOS values of each cell in the evaluation area and the evaluation area
  • the ratio of the number of cells in the middle for example, for an evaluation area composed of three cells a, b, and c, if the MOS values of the three cells are y1, y2, and y3, then the average MOS value of the evaluation area is (y1 +y2+y3)/3.
  • the so-called regional poor quality ratio refers to the ratio of the number of cells in the evaluation area whose MOS value is lower than the preset threshold to the total number of cells in the evaluation area.
  • the evaluation indicators also include indicators that characterize the RSRQ of the assessment area, indicators that characterize the downlink throughput rate of the assessment area, indicators that characterize the PRB utilization rate of the assessment area, and indicators that characterize the number of active users in the assessment area. At least one of.
  • the effect evaluation module 708 respectively calculates the first evaluation score before adjustment and the second evaluation score after adjustment of the evaluation area.
  • i denotes the i-th evaluation index
  • w i represents the weight of the i th evaluation index corresponding to a weight. It is understandable that in some cases, the measurement of multiple evaluation indicators may be different, and some evaluation indicators are "positive indicators", the larger the value, the better the communication quality, while some evaluation indicators may be "negative indicators” , The smaller the value, the better the communication quality.
  • the effect evaluation module 708 may normalize the evaluation indexes with inconsistent weights and measures, uniformly convert the negative indexes into positive indexes, or convert the positive indexes into negative indexes at the same time, and then calculate the evaluation score.
  • the effect evaluation module 708 calculates the difference between the two. Assuming that through the conversion of the effect evaluation module 708, all evaluation indicators are positive indicators, the final evaluation score should also be greater OK, therefore, the effect evaluation module 708 calculates the difference between the second evaluation score and the first evaluation score. Next, the effect evaluation module 708 determines whether the adjustment is effective. If the judgment result is yes, the effect evaluation module 708 deletes the adjusted cell from the cell to be optimized. If the judgment result is no, when the new adjustment period arrives, the effect evaluation module 708 judges whether there is a cell in the cell to be optimized. If it exists, continue to select and adjust the cell set for adjustment.
  • the effect evaluation module 708 calculates the difference between the second evaluation score and the first evaluation score, as long as the second evaluation score is greater than the first evaluation score Once the score is evaluated, the effect evaluation module 708 will determine that this adjustment is effective. However, in some other examples of this embodiment, if the effect evaluation module 708 needs to determine that the difference between the second evaluation score and the first evaluation score reaches a certain threshold, the adjustment will be determined to be effective, otherwise, even the second If the evaluation score is greater than the first evaluation score, the network industry equipment will also determine that this adjustment is invalid.
  • the effect evaluation module 708 determines that the adjustment to a certain adjusted cell is valid, it can remove the adjusted cell from the cell to be optimized. If the effect evaluation module 708 determines that the adjustment for a certain adjusted cell is invalid, it will not The adjusted cell is removed from the cell to be optimized and adjusted, so that the adjusted cell can get a chance to be adjusted again in other adjustment periods.
  • the effect evaluation module 708 continues to select the set of adjusted cells for adjustment, otherwise the process ends.
  • the antenna feeder parameter optimization device 70 can be deployed on a network device, for example, on a server.
  • Functions of the problem discovery module 700, problem location module 702, cell selection module 704, parameter optimization module 706, and effect evaluation module 708 can be implemented by the processor of the network device.
  • the antenna feeder parameter optimization device provided in this embodiment not only evaluates the adjustment effect after adjusting an adjustment cell, so as to remedy the effect of the adjustment cell with poor adjustment effect in time.
  • this embodiment will expand the evaluation during the evaluation Scope, while taking into account the evaluation indicators of data traffic services, to ensure that the signal strength of data traffic services is guaranteed while improving the quality of VoLTE.
  • This embodiment provides a storage medium that can store one or more computer programs that can be read, compiled, and executed by one or more processors.
  • the storage medium can store
  • the antenna feeder parameter optimization program can be used by one or more processors to execute the process of implementing any one of the antenna feeder parameter optimization methods introduced in the foregoing embodiments.
  • the network device 90 includes a processor 91, a memory 92, and a communication bus 93 configured to connect the processor 91 and the memory 92, where the memory 92 may be the aforementioned storage Storage medium of antenna feeder parameter optimization program.
  • the processor 91 may read the antenna feeder parameter optimization program, compile and execute the process of implementing the antenna feeder parameter optimization method introduced in the foregoing embodiment:
  • the processor 91 determines that the reason for the poor VoLTE quality of the cell to be optimized is one of the preset reasons; then determines the optimized adjusted cell from the cells to be optimized, and adjusts the cell to have a non-strong neighbor relationship with other adjusted cells in the adjustment period ; Subsequently, the processor 91 determines the target antenna feeder parameters of the adjusted cell, and adjusts the antenna feeder parameters of the adjusted cell according to the target antenna feeder parameters; the processor 91 evaluates the effect of this adjustment, and if the evaluation result characterizes the adjustment cell If the adjustment is effective, the adjustment to the adjusted cell is maintained.
  • its strong neighboring cell refers to the neighboring cell that has a strong correlation with the cell:
  • the processor 91 when the processor 91 determines whether a neighboring cell of a certain cell is a strong neighbor of the cell, it can make a determination based on the MR of the cell, and determine that the neighboring cell is in the MR of the cell. Whether the frequency of occurrence is high enough, if so, the processor 91 determines that the neighboring cell is a strong neighboring cell of the cell, otherwise, it is not its strong neighboring cell. For example, in an example of this embodiment, only when the proportion of a neighboring cell appearing in the MR of a cell reaches the preset strong neighboring cell ratio, will the neighboring cell be determined as the strong neighboring cell of the corresponding cell.
  • the proportion of strong neighbors of a cell a in the MR of a cell a must reach 5%. If the terminals in cell a report a total of 100 MRs, then if a cell is the MR of cell a Strong neighbor cell, the cell appears in the MR in cell a at least 5 times.
  • the processor 91 when the processor 91 judges whether the neighboring cells of a certain cell are strong neighbors of the cell, it can determine the proportion of all neighboring cells of the cell in the MR of the cell, and then select the previous The k neighboring areas are regarded as strong neighboring areas. For example, if a cell b has 80 neighboring cells, 10 of which will be determined as strong neighbors, the processor 91 can respectively determine the frequency or proportion of these 80 neighboring cells in the MR of cell b, and then choose to appear The top 10 neighboring cells ranked higher in frequency or proportion are regarded as strong neighbors of cell b.
  • the processor 91 Before determining that the reason for the poor VoLTE quality of the cell to be optimized is one of the preset causes, the processor 91 first determines the MOS value of each cell in the predetermined area, and then determines the cell to be optimized according to the MOS value of each cell.
  • the processor 91 determines the MOS value of each cell in the predetermined area, for any cell in the predetermined area, obtain the VoLTE data and measurement report MR data of the cell; and then associate the VoLTE data and MR data of the cell according to the VoLTE data.
  • the data and MR data determine the MOS value of the cell.
  • the preset reasons include coverage reasons, interference reasons, and capacity reasons.
  • the processor 91 may determine the set of adjusted cells to be optimized in the adjustment period from the cells to be optimized, and there is no strong neighbor relationship in the adjusted cell set. Then, determine the optimized adjusted cell from the adjusted cell set.
  • the processor 91 may determine the set of adjustment cells to be optimized in the adjustment period according to at least one of the coverage of each cell in the cells to be optimized and the VoLTE quality.
  • the adjusted cell set may be determined according to at least one of the coverage of each cell in the cells to be optimized and the VoLTE quality.
  • the way for the processor 91 to determine the set of adjustment cells to be optimized in the adjustment period according to at least one of the coverage of each cell in the cells to be optimized and the VoLTE quality includes any one of the following two:
  • the cell MOS average value is an MOS average value determined according to at least two MOS values of a cell
  • the first n cells with a larger number of reported MRs or cells with a number of reported MRs greater than m are selected from the second cell set to form an adjusted cell set corresponding to this adjustment period.
  • the processor 91 may determine the target antenna feeder parameter of the adjusted cell according to the inherent attribute parameter of the adjusted cell and/or the performance index parameter of the adjusted cell.
  • the above-mentioned inherent attribute parameters include: adjusting the station height of the cell; the performance index parameters include adjusting at least one of the following parameters of the cell: reference signal received power RSRP, timing advance TA, over-coverage, and weak-coverage.
  • the processor 91 when it evaluates the effect of this adjustment, it can first determine the evaluation area corresponding to the adjusted cell; then determine the evaluation index of the evaluation area.
  • the processor 91 may first determine the neighboring cells of the adjusted cell according to the MR data of the adjusted cell, and then count the number of times each neighboring cell appears in the MR data of the adjusted cell, and then select the higher number of occurrences
  • the first m cells, that is, strong neighbor cells, together with the adjusted cells constitute the evaluation area of the adjusted cells.
  • the indicators that characterize the MOS value of the evaluation area include at least one of the area MOS average value and the area poor quality ratio, and the area MOS average value is the sum of the MOS values of each cell in the evaluation area and the number of cells in the evaluation area.
  • the ratio of regional quality is the ratio of the number of cells in the evaluation area whose MOS value is lower than the preset threshold to the total number of cells in the evaluation area.
  • the indicators that characterize the RSRP of the evaluation area include the average RSRP value of the area and/or the ratio of RSRP ⁇ -110 of the cells in the evaluation area.
  • the average RSRP value of the area is the sum of the RSRP values of the cells in the evaluation area and The ratio of the number of cells.
  • the evaluation index further includes an index that characterizes the reference signal reception quality of the evaluation area, RSRQ, an index that characterizes the downlink throughput rate of the evaluation area, an index that characterizes the PRB utilization rate of the physical resource block in the evaluation area, and an index that characterizes the evaluation area. At least one of several indicators of the number of active users.
  • the network device provided in this embodiment can automatically perform problem discovery, location, problem solving, and effect evaluation, thereby improving problem solving efficiency and reducing dependence and requirements on human resources.
  • After adjusting an adjusted cell not only the adjustment effect will be evaluated, so that the adjusted cell with poor adjustment effect can be remedied in time.
  • this embodiment when evaluating the adjustment effect, in order to avoid only considering the effect of VoLTE and causing cell edge users to have poor signal or even coverage holes when using data traffic services, this embodiment will expand the evaluation during the evaluation Scope, while taking into account the evaluation indicators of data traffic services, to ensure that the signal strength of data traffic services is guaranteed while improving the quality of VoLTE.
  • Embodiment 6 is a diagrammatic representation of Embodiment 6
  • Step 1 The network device obtains the VoLTE data and MR data of all cells in the predetermined area, then associates the VoLTE data with the MR data, and calculates the MOS value of the slice level (5 seconds is a slice). Subsequently, the network device determines whether the MOS value of each slice is poor quality, and determines the MOS quality poor ratio of each cell respectively, and then ranks the MOS quality poor ratios of all cells in the predetermined area, and determines the top 1/3 of the cells For the cell to be optimized, it is assumed that cells a, b, and c are judged to be cells to be optimized.
  • Step 2 The network equipment locates the problem of the cell to be optimized. It can use the historical fingerprint data to determine the cause of the poor VoLTE quality of the cell to be optimized. For example, the network equipment detects that cells a and b are coverage problems and cell c is an interference problem.
  • Step 3 The network equipment selects each adjustment cell in the adjustment period from the cells to be optimized.
  • the network equipment will not only ensure that the selected adjusted cells are not in strong neighbor relationships, but will also try to select cells with larger coverage areas and relatively poor VoLTE quality.
  • Step 4 The network equipment separately calculates the optimal antenna feeder angle of each adjusted cell in the adjusted cell set, and sets the target antenna feeder parameters. If the optimal antenna feed angle is consistent with the current angle of the adjusted cell, the network device calculates the next one; if not, the network device adjusts the antenna feed angle of the adjusted cell to the optimal antenna feed angle.
  • Step 5 The network equipment calculates and adjusts the evaluation area of the cell.
  • the network equipment screens out all neighboring cells of the adjusted cell from the MR data of the adjusted cell, and counts the proportion of each neighboring cell in the adjusted cell MR, and then uses the set of strong neighbors and adjusted cells as the evaluation area.
  • the number of occurrences of each neighboring cell in the adjusted cell MR is sorted from high to low, and the neighboring cell with the top 2/3 is the strong neighbor of the adjusted cell.
  • Step 6 The network device calculates the MOS value of the cell slice level in the evaluation area, calculates the average MOS value of the evaluation area through the slice level MOS value, and determines whether each MOS slice is of poor quality, and calculates the ratio of MOS quality in the evaluation area, as shown in the following formula :
  • MOS value is the mean value of regional MOS, where MOS value is the MOS value of each slice, Num all is the number of MOS slices in the evaluation area, MOS ratio is the ratio of regional quality to poor, Num bad is the number of poor quality slices.
  • the network device also obtains the MR data of all cells in the evaluation area, and calculates the average RSRQ value, the average CQI value, the average RSRP value, and the ratio of RSRP ⁇ -110 in the evaluation area through a similar process as described above.
  • Step 7 The network device calculates the evaluation score of the evaluation area according to the following formula, including the first evaluation score before adjustment and the second evaluation score after adjustment:
  • i denotes the i-th evaluation index
  • n is the total number of evaluation index
  • w i denotes the i th evaluation index corresponding weight.
  • Step 8 The network equipment judges the effect of the evaluation index change in the evaluation area due to the adjustment of the adjusted cell. If the effect becomes better, the corresponding adjusted cell will be deleted from the set of cells to be optimized; if it becomes worse, the issued optimal day will be rolled back. Feed angle.
  • Step 1 The network device obtains the VoLTE data and MR data of all cells in the predetermined area, then associates the VoLTE data with the MR data, and calculates the MOS value of the slice level (5 seconds is a slice). Subsequently, the network device determines whether the MOS value of each slice is poor quality, and determines the MOS quality poor ratio of each cell respectively, and then ranks the MOS quality poor ratios of all cells in the predetermined area, and determines the top 1/3 of the cells For the cell to be optimized, it is assumed that cells a, b, and c are judged to be cells to be optimized.
  • Step 2 The network equipment locates the problem of the cell to be optimized. It can use the historical fingerprint data to determine the cause of the poor VoLTE quality of the cell to be optimized. For example, the network equipment detects that cells a and b are coverage problems and cell c is an interference problem.
  • Step 3 The network equipment selects each adjustment cell in the adjustment period from the cells to be optimized.
  • the network equipment will not only ensure that the selected adjusted cells are not in strong neighbor relationships, but will also try to select cells with larger coverage areas and relatively poor VoLTE quality.
  • Step 4 The network equipment separately calculates the optimal antenna feeder angle of each adjusted cell in the adjusted cell set, and sets the target antenna feeder parameters. If the optimal antenna feed angle is consistent with the current angle of the adjusted cell, the network device calculates the next one; if not, the network device adjusts the antenna feed angle of the adjusted cell to the optimal antenna feed angle.
  • Step 5 The network equipment calculates and adjusts the evaluation area of the cell.
  • the network equipment screens out all neighboring cells of the adjusted cell from the MR data of the adjusted cell, and counts the proportion of each neighboring cell in the adjusted cell MR, and then evaluates the top 2/3 neighboring cells and the set of adjusted cells area.
  • Step 6 The network device calculates the MOS value of the cell slice level in the evaluation area, calculates the average MOS value of the evaluation area through the slice level MOS value, and determines whether each MOS slice is of poor quality, and calculates the ratio of MOS quality in the evaluation area, as shown in the following formula :
  • MOS value is the mean value of regional MOS, where MOS value is the MOS value of each slice, Num all is the number of MOS slices in the evaluation area, MOS ratio is the ratio of regional quality to poor, Num bad is the number of poor quality slices.
  • the network device also obtains the MR data of all cells in the evaluation area, and calculates the average RSRQ value, the average CQI value, the average RSRP value, and the ratio of RSRP ⁇ -110 in the evaluation area through a similar process as described above.
  • Step 7 The network equipment can calculate the downlink throughput rate, PRB utilization rate, and the number of active users in a different evaluation area.
  • Step 8 The network device calculates the evaluation score of the evaluation area according to the following formula, including the first evaluation score before adjustment and the second evaluation score after adjustment:
  • thr is the parameter to determine the current load of the cell according to the adjustment of the cell's geographic location and service capability
  • w i and w j are the weights of the selected variables when the number of active users is different
  • i represents the i-th evaluation index
  • n is the total number of evaluation index, v i i-th feature value of the evaluation index.
  • the network device may set the weight value of the RSRQ and CQI to be greater than the weight of the RSRP, so as to focus on improving the channel quality for evaluation.
  • Step 9 The network equipment judges the effect of the evaluation index change of the evaluation area after the adjustment of the cell. If the effect becomes better, the adjusted cell is deleted from the cell to be optimized; if it becomes worse, the issued optimal antenna feed angle is rolled back.
  • the functional modules/units in the system, and the device can be implemented as software (which can be implemented by program code executable by a computing device) , Firmware, hardware and their appropriate combination.
  • the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may consist of several physical components. The components are executed cooperatively.
  • Some physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit .
  • the computer-readable medium may include computer storage Medium (or non-transitory medium) and communication medium (or temporary medium).
  • computer storage medium includes volatile and non-volatile memory implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data).
  • flexible, removable and non-removable media are examples of flexible, removable and non-removable media.
  • Computer storage media include but are not limited to RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cassette, tape, magnetic disk storage or other magnetic storage devices, or Any other medium used to store desired information and that can be accessed by a computer.
  • communication media usually contain computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as carrier waves or other transmission mechanisms, and may include any information delivery media . Therefore, the present invention is not limited to any specific combination of hardware and software.
  • the technical solution provided by the embodiment of the present invention determines the reason for the poor VoLTE quality of the cell to be optimized as one of the preset reasons, then determines the optimized adjustment cell from the cells to be optimized, determines the target antenna feeder parameters of the adjusted cell, and Adjust the antenna feeder parameters of the adjusted cell according to the target antenna feeder parameters, and then evaluate the effect of this adjustment. If the evaluation result indicates that the adjustment is effective, the adjustment is maintained, otherwise the adjustment is rolled back.
  • the adjustment cell is selected, and then the target antenna feeder parameters for the adjusted cell are automatically determined and based on the target antenna feeder parameters Adjust the antenna feeder parameters of the adjusted cell.
  • the adjustment effect will be further evaluated to avoid the negative impact of improper adjustment on VoLTE.
  • the process of problem location, problem optimization, and optimization evaluation is fully automated without manual participation, which is conducive to reducing network operation and maintenance costs.
  • the automated antenna feeder parameter optimization solution has high optimization efficiency and can be solved in time after VoLTE problems occur, reducing the impact of VoLTE problems on users' voice services and improving user experience.

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

Certains modes de réalisation de la présente invention concernent un procédé et un appareil d'optimisation de paramètres d'alimentation d'antenne, un dispositif de réseau, et un support de stockage. La solution d'optimisation de paramètres d'alimentation d'antenne comporte les étapes consistant: après avoir déterminé que la raison de la mauvaise qualité de VoLTE d'une cellule à optimiser est une raison parmi des raisons prédéfinies, à sélectionner une cellule à ajuster; puis à déterminer automatiquement des paramètres cibles d'alimentation d'antenne pour la cellule à ajuster, et à ajuster, selon les paramètres cibles d'alimentation d'antenne, des paramètres d'alimentation d'antenne de la cellule à ajuster. Après l'ajustement, l'effet de l'ajustement doit en outre être évalué pour éviter un impact négatif causé par un ajustement incorrect sur la VoLTE. Les processus de localisation de problèmes, d'optimisation de problèmes, et d'évaluation d'optimisation sont mis en œuvre de façon entièrement automatique sans intervention manuelle, ce qui réduit les coûts d'exploitation et de maintenance du réseau. De plus, la solution d'optimisation automatique de paramètres d'alimentation d'antenne présente un haut rendement d'optimisation, et peut résoudre en temps opportun un problème de VoLTE après l'apparition du problème de VoLTE, ce qui réduit les influences du problème de VoLTE sur un service vocal d'utilisateur, et améliore l'agrément d'utilisation.
PCT/CN2020/096206 2019-07-19 2020-06-15 Procédé et appareil d'optimisation de paramètres d'alimentation d'antenne, dispositif de réseau, et support de stockage WO2021012835A1 (fr)

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