CN104768171A - Network optimization method and device - Google Patents
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Abstract
The invention discloses a network optimization method and device. The method comprises that a polling period is determined according to the communication load; rolling sampling is carried out on all preset communication support cells according to the polling period to obtain the instantaneity index of each the communication support cell; and congestion of each communication support cell is predicted according to the obtained instantaneity index as well as historical performance index under the same communication support scene; and optimization adjustment is carried out according to the congestion prediction result of each communication support cell.
Description
Technical Field
The present invention relates to the field of mobile communication network management, and in particular, to a network optimization method and apparatus.
Background
With the increase of communication users and the development of communication terminals, each communication network has been changed greatly. In daily life, activities gathered by users such as concerts, large conferences and holiday activities often occur in many areas, and operators often cannot find the activities in time due to message lag, overlarge network, slow index extraction and the like, and furthermore, in communication guarantee, even if monitoring is performed on such cells, data with granularity of only 15 minutes can be extracted by a network manager, so that cell congestion is found late, and finally, the communication guarantee effect is poor.
In the prior art, network optimization realized by an operator is mainly solved by adopting methods such as network management index extraction, Man Machine Language (MML) sampling, resource release before guarantee and the like, and the methods have the following defects: firstly, the sudden user aggregation behavior cannot be known in advance, and the optimal adjustment time is often missed; secondly, the traditional network management index extraction is used for guaranteeing that the data extraction period is too long, and the congestion caused by the communication behavior of part of emergent user aggregation cannot be timely dealt with; thirdly, the sampling result of the single base station occupation condition is used for analysis, and the communication behavior of the sudden user aggregation cannot be responded in time due to long period, random single sampling and low accuracy; fourthly, network resources of voice and data are fixed in advance, different requirements of the voice and the data cannot be accurately evaluated in busy hours, a method for dynamically adjusting base station resources is lacked, and the resources cannot be released in time in idle hours to improve user perception.
At present, no mature network optimization method is available for rapidly coping with user communication behaviors in various different security scenes; to cope with these bursty activities, the communication network needs to have a discovery mechanism and adjustment countermeasures fast enough to accommodate such changes.
Disclosure of Invention
In view of this, embodiments of the present invention are expected to provide a method and an apparatus for network optimization, which enable a communication network to quickly discover bursty aggregated communication behaviors and adjust countermeasures, so as to quickly cope with user communication behaviors in various different security scenarios.
In order to achieve the above purpose, the technical solution of the embodiment of the present invention is realized as follows:
the embodiment of the invention provides a network optimization method, which comprises the following steps: determining a polling period according to the communication load; polling and sampling each preset communication guarantee cell according to the polling period to obtain the real-time performance index of each communication guarantee cell; for each communication guarantee cell, carrying out congestion prediction according to the acquired real-time performance index and historical performance index under the similar communication guarantee scene; and carrying out optimization adjustment according to the congestion prediction result of each communication guarantee cell.
In the foregoing solution, before determining the polling period according to the communication load, the method further includes: setting a communication guarantee cell and communication guarantee duration according to a communication guarantee scene; the communication guarantee scene comprises a normal network monitoring scene and an emergency communication guarantee scene.
In the foregoing solution, the determining a polling cycle according to a communication load includes: and respectively calculating a sampling period according to the extracted load of an Operation Manager (OMU) of a communication guarantee cell home Base Station Controller (BSC) and the load of a data processing server, and determining the larger value of the two as a polling period.
In the above scheme, the predicting congestion according to the obtained real-time performance index and the historical performance index in the similar communication guarantee scene includes: calculating a predicted performance index according to the real-time performance index obtained by sampling and the historical performance index of the same time period under the same type of communication guarantee scene; and determining the congestion state of the communication guarantee cell according to the predicted performance index.
In the above scheme, the calculating a predicted performance index according to the real-time performance index obtained by sampling and the historical performance index of the same period in the same type of communication guarantee scene, and determining the congestion state of the communication guarantee cell according to the predicted performance index includes: obtaining real-time telephone traffic of a communication guarantee cell through real-time performance indexes obtained by sampling, calculating the trial call number of a predicted voice channel of the communication guarantee cell according to the real-time telephone traffic, the historical telephone traffic of the same time period in the same scene and the historical voice trial call number of the same time period in the same scene, and further obtaining the single trial call occurrence interval of the predicted voice channel; when the duration with the voice channel occupancy rate of 100% exceeds the single call trial occurrence interval, determining the communication guarantee cell as a congestion cell; obtaining the real-time telephone traffic through real-time performance indexes for at least six times; the real-time performance indicators include: the number of time slots occupied by the voice channel and the idle time slots of the voice channel.
In the foregoing solution, the performing optimization adjustment according to the congestion prediction result of each communication guarantee cell includes: calculating a congestion rate and/or a congestion duration through the determined duration of each recorded congestion of the congested cell, the recorded times of the congestion and the monitoring duration; and sequencing according to the congestion rates and/or the congestion time lengths of all the determined congestion cells, and preferentially processing the congestion cells with high congestion rates and/or long congestion time lengths.
The embodiment of the invention also provides a device for network optimization, which comprises: a polling cycle determining unit, a sampling unit, a congestion predicting unit and an adjusting unit; wherein, the cycle determining unit is used for determining a polling cycle according to the communication load; the sampling unit is used for performing polling sampling on each preset communication guarantee cell according to the polling period to acquire the real-time performance index of each communication guarantee cell; the congestion prediction unit is used for predicting congestion according to the acquired real-time performance index and historical performance index under the similar communication guarantee scene aiming at each communication guarantee cell; and the adjusting unit is used for carrying out optimization adjustment according to the congestion prediction result of each communication guarantee cell.
In the above scheme, the device further comprises a setting unit; the setting unit is used for setting a communication guarantee cell and communication guarantee duration according to a communication guarantee scene; the communication guarantee scene comprises a normal network monitoring scene and an emergency communication guarantee scene.
In the foregoing solution, the period determining unit is specifically configured to: and respectively calculating a sampling period according to the extracted OMU load of the BSC to which the communication guarantee cell belongs and the load of the data processing server, and determining the larger value of the two as a polling period.
In the foregoing solution, the congestion prediction unit further includes: an analysis unit and a prediction unit; the analysis unit is used for calculating a predicted performance index according to a real-time performance index obtained by sampling and a historical performance index of the same time period under the same type of communication guarantee scene; and the prediction unit is used for determining the congestion state of the communication guarantee cell according to the predicted performance index.
In the foregoing solution, the analysis unit is specifically configured to: obtaining real-time telephone traffic of a communication guarantee cell through real-time performance indexes obtained by sampling, calculating the trial call number of a predicted voice channel of the communication guarantee cell according to the real-time telephone traffic, the historical telephone traffic of the same time period in the same scene and the historical voice trial call number of the same time period in the same scene, and further obtaining the single trial call occurrence interval of the predicted voice channel; accordingly, the prediction unit is specifically configured to: and when the duration with the voice channel occupancy rate of 100% exceeds the single call trial occurrence interval, determining the communication guarantee cell as a congestion cell.
In the foregoing solution, the adjusting unit is specifically configured to: calculating a congestion rate and/or a congestion duration through the determined duration of each recorded congestion of the congested cell, the recorded times of the congestion and the monitoring duration; and sequencing according to the congestion rates and/or the congestion time lengths of all the determined congestion cells, and preferentially processing the congestion cells with high congestion rates and/or long congestion time lengths.
Therefore, the network optimization method and the network optimization device provided by the embodiment of the invention perform polling sampling on the communication guarantee cells according to the polling period determined by the communication load, and acquire the real-time performance index of each communication guarantee cell; for each communication guarantee cell, carrying out congestion prediction on the communication guarantee cell according to the acquired real-time performance index and historical performance index under the similar communication guarantee scene, and carrying out optimization adjustment according to a congestion prediction result; therefore, under the condition of utilizing the processing capacity of the network management to the maximum extent, the sudden aggregation communication behavior can be quickly discovered and the countermeasures can be adjusted, so that the user communication behavior under various different security scenes can be quickly responded. The embodiment of the invention can provide a reliable congestion evaluation analysis solution for emergency communication guarantee, and also can provide a solution for early warning and timely discovery for daily network operation; the method can provide more efficient and reliable information technology means for operators in network quality improvement and emergency treatment, and is simple to implement and easy to popularize.
Drawings
Fig. 1 is a schematic flow chart of an implementation of a network optimization method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram illustrating a network optimization method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an implementation flow of a daily network monitoring scene network optimization method according to an embodiment of the present invention;
FIG. 4 is a schematic diagram illustrating an implementation flow of a method for network optimization of an emergency communication guarantee scene according to an embodiment of the present invention;
FIG. 5 is a flowchart illustrating an implementation of an emergency communication assurance adjustment process according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of a network optimization apparatus according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a network optimization apparatus according to another embodiment of the present invention.
Detailed Description
In the embodiment of the invention, a polling period is determined according to communication load, and polling sampling is carried out on each preset communication guarantee cell according to the polling period to obtain the real-time performance index of each communication guarantee cell; for each communication guarantee cell, carrying out congestion prediction according to the acquired real-time performance index and the historical performance index under the similar communication guarantee scene; and carrying out optimization adjustment according to the congestion prediction result of each communication guarantee cell.
Here, the determining a polling period according to the communication load includes: calculating a sampling period according to the extracted Operation Manager Unit (OMU) load of a Base Station Controller (BSC) of the communication guarantee cell and the load of the data processing server, and determining the larger value of the two as a polling period.
The performing congestion prediction comprises: and calculating a predicted performance index through the real-time performance index obtained by sampling and the historical performance index of the same time period in the same type scene, and determining the congestion state of the communication guarantee cell according to the predicted performance index.
Specifically, for the optimization adjustment, according to the difference in the scene setting of the communication guarantee, the specific processing of the optimization adjustment is different, including: triggering a sudden congestion warning when the scene is set to be monitored in a daily network; and when the scene is set as emergency communication guarantee, triggering emergency situation warning and executing an emergency communication guarantee adjusting process.
Wherein the real-time performance indicators include, but are not limited to, channel occupancy, idle conditions; the historical performance indexes include, but are not limited to, historical traffic volume and historical voice call trial number; the predicted performance index includes, but is not limited to, a predicted number of pilot calls of the voice channel, and a predicted occurrence interval of single pilot call of the voice channel.
The invention is further described in detail below with reference to the drawings and the specific embodiments.
Fig. 1 is a schematic view of an implementation flow of a network optimization method according to an embodiment of the present invention, and as shown in fig. 1, the network optimization method includes the following steps:
step 101: determining a polling period according to the communication load;
before determining the polling period, the embodiment of the present invention further includes: and extracting the OMU load of the BSC to which the preset communication guarantee cell belongs, and acquiring the real-time occupation condition of the base station according to the extracted OMU load of the BSC so as to ensure that the OMU of the BSC normally executes all instructions of the BSC during the communication guarantee period.
After obtaining the load of the OMU of the BSC, respectively calculating a sampling period according to the load of the OMU of the extracted communication guarantee cell home BSC, calculating the sampling period according to the load of the data processing server, and determining the larger value of the sampling period and the sampling period as a polling period.
The polling cycle is restricted by the load of the OMU of the BSC and the load of the data processing server, and based on the limit, the sampling cycle is calculated according to the extracted load of the OMU of the BSC to which the communication guarantee cell belongs and the load of the data processing server, and the proper polling cycle needs to be selected through calculation; the polling period is determined by the side with a larger load, namely the polling period T is as follows:
T=max{TO,TS}
wherein, TOFor a polling period calculated from the OMU load, TSIs a polling period calculated from the load of the data processing server.
Specifically, the process of calculating the polling period according to the OMU load includes:
the MML instruction sent out during polling is processed by the OMU and the result is output, so the load of the OMU comes from the processing of the instruction; one instruction increases the load of the OMU by 19.8% per unit time. In order to ensure that other instructions except the polling instruction can be normally executed in the guarantee period, 50% of load capacity needs to be reserved for the OMU; based on this, the sampling period based on the OMU load is:
to obtain
Wherein N isbscFor communication protection under current BSCThe number of the obstacle cells; assuming that the number of cells under a certain BSC is 200, if all cells under the BSC participate in the guarantee, the polling period T isOAbout 79.2S; if the number of the cells needing communication guarantee under the BSC is only 30, the polling period T isOAbout 11.8S.
The process of calculating the polling period from the data processing server includes:
the acquired sampling data is summarized and calculated by the data processing server, therefore, the performance of the data processing server is an important factor for restricting the sampling frequency, and according to the fact that the processing capacity of the current mainstream data processing server is about 100000 pieces/S at 90% load, the data processing server has a relationship with the polling cycle:
wherein S is the total data processing amount, E is the processing capacity, TlGuarantee duration for communication, NcellGuaranteeing the total number of cells for communication; at this time, it is not necessary to divide blocks by BSC, NkptSampling the number of indexes in the communication guarantee process; wherein, the sampling index is the real-time cell occupation condition provided by the BSC; the sampling index comprises parameters such as the number of occupied full-rate voice channels, the number of idle full-rate voice channels, the number of occupied half-rate voice channels, the number of idle half-rate voice channels, the number of occupied data service channels, the number of locked channels, the number of occupied SDCCH channels, the number of idle SDCCH channels, cell ID, and the number in a cell network element.
The sampling period based on the load of the data processing server is as follows:
assuming that the number of the current collection indexes is 10, when the communication guarantee duration T is longerlIs 1 second, TSThe calculation of (a) can be simplified as:
in practical applications, the embodiment of the present invention does not exclude an implementation method in which the data processing server and the acquisition server for sampling are the same object; according to the current MML operation method, the acquisition server is mainly implemented based on telnet.
Before calculating the sampling period according to the OMU load and the data processing server load of the BSC, respectively, and determining the polling period, the method may further include: setting a communication guarantee cell and communication guarantee duration according to the communication requirement of the current network or according to the communication condition of a certain area, namely according to a guarantee scene;
for example, in a mall or square in a downtown area, the probability of occurrence of an aggregated communication behavior is high, and a communication security cell may be set to cover security areas of the mall or square; at night time, the probability of sudden aggregate communication behavior is small, and the communication guarantee duration can be set to nine early to nine late.
Furthermore, different communication guarantee areas and communication guarantee durations can be selected according to different communication guarantee scenes; the communication guarantee scene can be daily network monitoring, emergency communication guarantee and the like; the daily network monitoring is a monitoring communication guarantee, and the communication guarantee area and the communication guarantee duration of the daily network monitoring can be selected to be monitored in the whole day and the whole network; the emergency communication guarantee is a deterministic communication guarantee, and a special communication guarantee area and time can be generally selected.
Step 102: polling and sampling each preset communication guarantee cell according to the polling period to obtain the real-time performance index of each communication guarantee cell;
specifically, a sampling instruction is repeatedly sent to each preset communication support cell according to a determined polling period, the real-time performance index of the communication support cell is obtained, and the real-time sampling of the cell service channel is realized; the real-time performance index is index data sampled and counted according to a polling period, and includes but is not limited to: channel occupancy, idle conditions; here, the sampling instruction transmitted to each communication guarantee cell may be an MML instruction.
Step 103: for each communication guarantee cell, carrying out congestion prediction according to the acquired real-time performance index and historical performance index under the similar communication guarantee scene;
specifically, for each communication guarantee cell, according to a real-time performance index obtained by sampling and a historical performance index of the same time period in the same scene, a predicted performance index is calculated, and the congestion state of the communication guarantee cell is determined according to the predicted performance index;
more specifically, the real-time performance index obtained by sampling is used for obtaining the real-time telephone traffic of the communication guarantee cell, the predicted voice channel trial call number of the communication guarantee cell is calculated according to the real-time telephone traffic, the historical telephone traffic in the same time period in the same scene and the historical voice trial call number in the same time period in the same scene, and the single trial call occurrence interval of the predicted voice channel is further obtained; when the duration with the voice channel occupancy rate of 100% exceeds a single trial call occurrence interval of a voice channel, determining the communication guarantee cell as a congestion cell; obtaining the real-time telephone traffic through real-time performance indexes for at least six times; the real-time performance indicators include: the number of time slots occupied by the voice channel, the idle time slots of the voice channel and other performance indexes.
The historical performance index is extracted from each cell needing communication guarantee in the same scene before communication guarantee in a relevant time period; the historical performance index specifically includes: performance indexes such as historical telephone traffic, historical voice call trial number and the like; the similar scene is under a daily network monitoring scene or an emergency communication guarantee scene; the related period can be one or more of yesterday synchronization, last cycle synchronization and last month synchronization, and the rule use weight can be automatically established, such as: 1.0 × last month synchronization, 1.0 × last week synchronization, 1.0 × yesterday synchronization, 0.4 × last month synchronization +0.2 × last week synchronization +0.4 × yesterday synchronization.
In practical application, because sampling is random, multiple results are needed to comprehensively judge the real-time performance index to obtain the real-time telephone traffic, so that the obtained operation result of the real-time telephone traffic is more reasonable and more in line with the network condition.
In the communication guarantee process, aiming at each communication guarantee cell, the real-time telephone traffic of the communication guarantee cell is obtained according to the multiple real-time performance indexes, and a prediction coefficient is further obtained; and acquiring the prediction performance index of the communication guarantee cell according to the obtained prediction coefficient and the historical voice channel call trial number, and predicting the congestion condition of the communication guarantee cell according to the acquired prediction performance index. The prediction performance index is the prediction of the number of the pilot calls of the voice channel and the prediction of the occurrence interval of the single pilot call of the voice channel.
Taking a communication security cell as an example, the congestion prediction process of the communication security cell specifically includes:
obtaining real-time telephone traffic of the communication guarantee cell by using the real-time performance indexes of the last 6 times; here, the real-time performance index includes the number of occupied time slots of the voice channel and the idle time slots of the voice channel.
Wherein KPIHistorical trafficFor the traffic volume, KPI, of the relevant time interval under the same kind of sceneReal-time trafficFor the real-time traffic of the cell, FRNumber of occupied time slotsNumber of occupied time slots, FR, for cell full-rate channelsNumber of free time slotsNumber of idle slots, HR, for a cell full rate channelNumber of occupied time slotsNumber of occupied time slots, HR, for cell half rate channelNumber of free time slotsThe number of idle time slots of a cell half-rate channel;
obtaining a prediction coefficient Kerl：
By predicting the coefficient KerlAnd calculating the predicted voice channel call test number of the communication guarantee cell, and further calculating the single call test occurrence interval of the predicted voice channel.
Predicting the number of pilot calls of the voice channel can be used as a reference for judging the congestion condition of the communication guarantee cell, and predicting the number of pilot calls of the voice channel KPIPredicting number of pilot calls of voice channelComprises the following steps:
wherein KPINumber of pilot calls of historical voice channelThe number of times of trying calling of the voice channel in one hour of the relevant time period under the same scene.
Average period T of occurrence of pilot callsMean period of pilot callsComprises the following steps:
the average period of the test call is the single test call occurrence interval of the predicted voice channel, and the unit time is second.
And when the time length with the voice channel occupancy rate of 100% in the sampling result exceeds the single trial call occurrence interval, determining the voice channel occupancy rate as a congestion state, recording the congestion once, and recording the information such as the duration time of the congestion and the like.
Specifically, congestion judgment is carried out according to the duration of 100% of the occupancy rate of the voice channel continuously appearing in the real-time sampling result, and cell congestion indicates that all the voice channels of the cell are occupied; when the duration exceeds the single trial call occurrence interval, determining that congestion occurs, recording the congestion once, and recording the duration of the congestion in unit of second; when the duration does not exceed the occurrence interval of the single call attempt or is equal to the occurrence interval of the single call attempt, the congestion is not recorded;
here, after determining that the current communication guarantee cell is in a congestion state, a congestion reminder may be sent.
Step 104: and carrying out optimization adjustment according to the congestion prediction result of each communication guarantee cell.
Specifically, the congestion rate and/or the congestion duration are calculated through the determined duration of congestion recorded each time in the congested cell, the recorded times of congestion and the monitoring duration; and sorting according to the congestion rates and/or the congestion duration of all the determined congestion cells, and preferentially processing the congestion cells with high congestion rates and/or long congestion durations.
Calculating the congestion rate and/or congestion duration through the duration of congestion recorded each time, the recorded times of congestion and the monitoring duration of a congested cell; sorting according to the congestion rates and/or the congestion duration of all the determined congestion cells, and preferentially processing the congestion cells with high congestion rates and/or long congestion durations; the congested cell is the communication guarantee cell determined as congested in step 103, and the monitoring duration is a period of time from the start of communication guarantee to the present.
The duration of the nth congestion recorded in step 103 is tnUnit of second, the time T of congestion occurring in the monitored timeDuration of congestionComprises the following steps:
wherein k is the total number of times of congestion occurrence recorded within the monitoring time.
Congestion rate of congested cell:
here, the specific processing of the optimization adjustment is different according to different communication guarantee scene settings; the specific treatment comprises the following steps: triggering a sudden congestion warning when the scene is set to be monitored in a daily network; and when the scene is set as emergency communication guarantee, triggering emergency situation warning and executing an emergency communication guarantee adjusting process.
Wherein, emergent communication guarantee adjustment process specifically includes: adjusting the half rate threshold of the cell, and/or adjusting other types of channel resource occupation ratios except for a voice channel, and/or adjusting the adjacent cell level parameters of the cell and the adjacent cell, and/or performing manual processing.
By the embodiment, the congested cell can be quickly found and processed under quick polling; and (3) according to the prediction result, making a corresponding communication guarantee solution: sequencing according to the congestion rate and/or congestion duration, and automatically outputting corresponding resource release MML instructions, including closing data services and releasing more voice channel resources to ensure the normal access of voice services; in a plurality of continuous judging periods, if the service of the base station is found to be reduced, the original resource allocation is recovered as required so as to improve the service quality of the user.
In the daily practical application process, a sampling task of continuously issuing the MML instruction twice every 20 minutes can be established; before optimizing and adjusting the process, the analyzed burst service base station can be automatically exported, mail warning is provided, and information technology support is provided for part of communication guarantee which cannot be predicted.
In the practical application process, the system for completing the method can be a single system, and can also be a logic unit for completing different functions added in the existing core network.
Fig. 2 is a schematic flow chart of an implementation of the network optimization method according to an embodiment of the present invention, and as shown in fig. 2, the network optimization method includes the following specific steps:
step 201: setting a communication guarantee cell and communication guarantee duration;
here, the cell for setting the communication guarantee may be one cell or a plurality of cells, may be under the same BSC, or may be under a plurality of BSCs; and after the communication guarantee cell and the communication guarantee duration are set, processing is carried out by taking the set communication guarantee cell attribution BSC as a reference, and the polling periods of the communication guarantee cells attributing to the same BSC are the same.
Step 202: extracting OMU load of a communication guarantee cell home BSC;
step 203: determining a polling period according to the obtained OMU load;
specifically, the sampling period based on the extracted OMU load of the BSC and the sampling period based on the data processing server are calculated at the same time, and the larger value is determined to be the polling period.
Step 204: judging whether the communication guarantee duration is finished or not; when the communication guarantee duration is not over, the current communication guarantee duration is within the communication guarantee period, and step 204 is executed; when the communication guarantee duration is over, step 208 is executed to exit the communication guarantee process.
Step 205: sending a sampling instruction to obtain a real-time performance index;
specifically, a sampling instruction is sent to each communication guarantee cell according to the polling period determined in step 203, polling sampling is performed, and a real-time performance index is obtained; the sampling instruction sent to each communication guarantee cell may be an MML instruction.
Step 206: carrying out congestion prediction and reminding according to the obtained real-time performance index;
specifically, congestion prediction analysis is performed according to the real-time performance index obtained in step 205, and when it is determined that a certain cell is congested, congestion is recorded once, information such as duration of the congestion at this time is recorded, and a congestion prompt is sent at the same time.
Step 207: optimizing and adjusting the congested cell according to the congestion prediction record;
specifically, the average congestion duration of the congested cell is determined according to the congestion prediction record in step 206, the congestion rate and/or the congestion duration of the congested cell is further determined, all the congested cells are sorted according to the determined congestion rate and/or congestion duration of each congested cell, and the congested cells with high congestion rates and/or long congestion durations are preferentially processed.
Performing corresponding reminding operation or adjusting operation according to the communication guarantee scene setting; specifically, when a communication guarantee scene is set as daily network monitoring, burst congestion warning is triggered; and when the communication guarantee scene is set as emergency communication guarantee, triggering emergency situation warning and executing an emergency communication guarantee adjusting process.
Fig. 3 is a schematic flow chart illustrating an implementation process of a network optimization method in a daily network monitoring scenario according to an embodiment of the present invention, and as shown in fig. 3, the network optimization method in the daily network monitoring scenario specifically includes the following steps:
step 301: determining a communication guarantee area and communication guarantee time;
specifically, according to the communication guarantee field situation, the area and the communication guarantee time needing emergency communication guarantee are confirmed. Under the daily network monitoring scene, the whole network daily optimization monitoring can be selected, the monitoring guarantee is realized, and the communication guarantee cell needing communication guarantee is determined according to the determined guarantee area.
Step 302: determining a polling period;
specifically, according to a communication support cell polling period algorithm, a minimum allowable period is calculated by combining the load of an OMU (operation management unit) for processing an MML (multimedia messaging service) instruction, and a proper polling period value is determined by comprehensively considering according to possible behaviors of field users, experience values of the same type of communication support and the efficiency of a data processing server.
The determined polling period is larger than the OMU load minimum allowable period, and the load of the data processing server is comprehensively considered, and a larger polling period is selected.
Step 303: calculating the traffic of the current time period through a real-time sampling result;
here, the communication guarantee cell is polled at a high speed to obtain a real-time performance index, and the current real-time telephone traffic is calculated through a short-term real-time sampling result, wherein the calculation formula is as follows:
step 304: calculating K according to the current time interval and the synchronous telephone trafficerlA value;
specifically, the telephone traffic condition of the same period (yesterday same period, last cycle same period and/or last month same period) is analyzed to generate historical telephone traffic, and a corresponding prediction coefficient K is calculated according to the real-time telephone trafficerlA value of (d);
here, the prediction coefficient K may be calculated using the following formulaerlThe value of (c):
step 305: calculating and predicting the number of the voice channel attempted calls;
specifically, the number of test calls of the voice channel in the same period (yesterday, last week and last month) is analyzed, and the test calls are carried out according to KerlCalculating and predicting the number of the voice channel test calls;
here, the predicted number of voice channel calls can be calculated using the following formula:
step 306: calculating the occurrence interval of single call trial, and judging the congestion of the current communication guarantee cell;
specifically, according to the calculated trial call number and polling period of the voice channel, calculating the occurrence interval of single trial call; and judging congestion according to the duration of the voice channel occupancy rate of 100% continuously appearing in the real-time sampling result, recording congestion once when the duration of the voice channel occupancy rate of 100% exceeds the single trial call occurrence interval, and recording the duration of the current congestion of the congested cell and other related information.
Step 307: calculating the congestion rate and/or congestion duration, and performing congestion processing;
specifically, the congestion rate and/or congestion duration are calculated according to the obtained congestion times, the whole network condition is calculated by using the same method, and whether the peripheral cells are congested or not is judged; according to the average congestion rate and/or the congestion duration, all the determined congestion cells are sorted in a descending order, the priority of the congestion cell with the high congestion rate and/or the congestion duration is determined, and a sudden congestion warning is prompted for the congestion cell with the high priority by combining the congestion conditions of the adjacent cells; wherein, the following condition is satisfied to prompt the burst congestion warning: when the congestion priority of the congested cell is high, the congested neighbor cell accounts for more than 40% of all neighbor cells.
Fig. 4 is a schematic view of an implementation flow of a network optimization method in an emergency communication security scenario according to an embodiment of the present invention, and as shown in fig. 4, the network optimization method in the emergency communication security scenario includes the specific steps of:
step 401: determining a communication guarantee area and communication guarantee time;
specifically, according to the communication guarantee field situation, the area and the communication guarantee time needing emergency communication guarantee are confirmed. In an emergency communication guarantee scene, a special communication guarantee area and time can be selected to realize deterministic guarantee, and a communication guarantee cell needing communication guarantee is determined according to the determined guarantee area.
Step 402: determining a polling period;
specifically, according to a communication support cell polling period algorithm, a minimum allowable period is calculated by combining the load of an OMU (operation management unit) for processing an MML (multimedia messaging service) instruction, and a proper polling period value is determined by comprehensively considering according to possible behaviors of field users, experience values of the same type of communication support and the efficiency of a data processing server.
The determined polling period is larger than the OMU load minimum allowable period, and the load of the data processing server is comprehensively considered, and a larger polling period is selected.
Step 403: calculating the traffic of the current time period through a real-time sampling result;
here, the communication guarantee cell is polled at a high speed to obtain a real-time performance index, and the current real-time telephone traffic is calculated through a short-term real-time sampling result, wherein the calculation formula is as follows:
step 404: calculating K according to the current time interval and the synchronous telephone trafficerlA value;
specifically, the telephone traffic condition of the same period (yesterday same period, last cycle same period and/or last month same period) is analyzed to generate historical telephone traffic, and a corresponding prediction coefficient K is calculated according to the real-time telephone trafficerlA value of (d);
here, the prediction coefficient K may be calculated using the following formulaerlThe value of (c):
step 405: calculating and predicting the number of the voice channel attempted calls;
specifically, the number of test calls of the voice channel in the same period (yesterday, last week and last month) is analyzed, and the test calls are carried out according to KerlCalculating the value to predict the number of the voice channel test calls;
here, the predicted number of voice channel calls can be calculated using the following formula:
step 406: calculating the occurrence interval of single call trial, and judging the congestion of the current communication guarantee cell;
specifically, according to the calculated voice channel call trial number and polling period, calculating a single call trial occurrence interval, and performing congestion judgment of the current communication guarantee cell; and judging congestion according to the duration of the voice channel occupancy rate of 100% continuously appearing in the real-time sampling result, recording congestion once when the duration of the voice channel occupancy rate of 100% exceeds the single trial call occurrence interval, and recording the duration of the current congestion of the congested cell and other related information.
Step 407-: calculating the congestion rate and/or congestion duration, and performing congestion processing;
specifically, the congestion rate and/or the congestion duration are calculated according to the obtained congestion times, all the determined congestion cells are sorted in a descending order according to the average congestion rate and/or the average congestion duration, the priority of the congestion cell with the high congestion rate and/or the average congestion duration is determined to be high, an emergency situation warning is triggered for the congestion cell with the high priority, and the emergency communication guarantee adjustment process in step 408 is executed.
Fig. 5 is a flowchart illustrating an implementation of an emergency communication security adjustment process according to an embodiment of the present invention, and as shown in fig. 5, the emergency communication security adjustment process for each congested cell specifically includes the following steps:
step 4081: judging whether the half rate threshold of the congested cell is set to be maximum or not, if the half rate threshold of the congested cell is not set to be maximum, executing step 4081 a: adjusting a half rate threshold of the cell; if so, i.e., the half rate threshold of the congested cell is set to the maximum, step 4082 is performed.
Step 4082: judging whether the channel resources of other types except the voice channel of the congested cell are congested, if the channel resources of other types except the voice channel of the congested cell are not congested, executing step 4082 a: adjusting the voice channel resource occupation ratio of the congested cell, and releasing part of other types of channel resources for relieving voice congestion; if so, step 4083 is performed.
Step 4083: judging whether the adjacent cell of the congested cell has the congestion condition, if the adjacent cell of the cell has no congestion condition, executing step 4083 a: adjusting parameters of a neighboring cell and parameters of neighboring cell level of the cell, changing the cell occupied by the user at the edge of the cell coverage, and adjusting the user at the edge of the cell coverage to the neighboring cell; if there is also a congestion situation in the neighbor cells of this cell, step 4084 is performed.
Step 4084: judging whether the congestion of the congested cell is serious;
under the condition that the congestion rate is more than 5%, the congestion of the cell can be judged to be very serious; if the very serious criteria are not met, the person in charge is notified, step 4084a is performed: directly entering a manual processing link and requiring manual adjustment by workers; if it is a very serious condition, step 4085 is performed: and requesting to reduce the cell transmitting power and informing a responsible person to check.
In practical application, the emergency communication guarantee adjustment process is realized by adopting an MML language.
To implement the above method, the present invention further provides a network optimization apparatus, as shown in fig. 6 and 7, which are an apparatus for network optimization according to an embodiment of the present invention and an apparatus for network optimization according to another embodiment of the present invention, and the apparatus mainly includes: a cycle determination unit 601, a sampling unit 602, a congestion prediction unit 603, and an adjustment unit 604; wherein,
a period determining unit 601, configured to determine a polling period according to a communication load, and send the determined polling period to the sampling unit 602;
a sampling unit 602, configured to perform polling sampling on each preset communication guarantee cell according to the polling period determined by the period determining unit 601, obtain a real-time performance index of each communication guarantee cell, and send the obtained real-time performance index to the congestion prediction unit 603;
a congestion prediction unit 603, configured to perform congestion prediction for each communication guarantee cell according to the acquired real-time performance index and historical performance index in the similar communication guarantee scenario, and send a congestion prediction result to the adjustment unit 604;
an adjusting unit 604, configured to perform optimization adjustment according to the congestion prediction result of each communication guarantee cell sent by the congestion predicting unit 603.
The apparatus may further include a setting unit 605 configured to set a communication security cell and a communication security duration according to the communication security scenario; the communication guarantee scene comprises a normal network monitoring scene and an emergency communication guarantee scene.
Specifically, the period determining unit 601 calculates a sampling period according to the extracted OMU load of the BSC to which the communication guarantee cell belongs and the load of the data processing server, and determines the larger value of the two as the polling period.
The congestion prediction unit 603 may further include: an analysis unit 631 and a prediction unit 632; wherein,
the analysis unit 631 is configured to calculate a predicted performance index according to the real-time performance index obtained through sampling and a historical performance index of the same period in the same communication guarantee scene;
specifically, the analysis unit 631 obtains the real-time traffic volume of the communication security cell through the real-time performance index obtained by sampling, calculates the predicted voice channel call trial number of the communication security cell according to the real-time traffic volume, the historical traffic volume at the same time interval in the same type of scene, and the historical voice call trial number at the same time interval in the same type of scene, further obtains the predicted voice channel single call trial occurrence interval, and sends the calculated predicted channel single call trial occurrence interval to the prediction unit 632;
a predicting unit 632, configured to determine a congestion state of the communication assurance cell according to the predicted performance index;
specifically, when the duration in which the voice channel occupancy is 100% exceeds the predicted channel single-call occurrence interval received from the analysis unit 631, the communication guarantee cell is determined to be a congested cell.
The adjusting unit 604 is specifically configured to: calculating a congestion rate and/or a congestion duration through the determined duration of each recorded congestion of the congested cell, the recorded times of the congestion and the monitoring duration; and sequencing according to the congestion rates and/or the congestion time lengths of all the determined congestion cells, and preferentially processing the congestion cells with high congestion rates and/or long congestion time lengths.
When the communication assurance scenario is set for daily network monitoring, the adjusting unit 604 triggers a burst congestion warning accordingly;
specifically, burst congestion warning is triggered according to the congestion rate and/or congestion duration of each congested cell and the congestion situation of the surrounding cells.
When the communication assurance scene is set as emergency communication assurance, accordingly, the adjustment unit 604 triggers an emergency situation warning and executes an emergency communication assurance adjustment process.
The adjusting unit further includes an emergency communication adjusting unit 641 configured to adjust a half rate threshold of the congested cell, and/or adjust other types of channel resource ratios other than the voice channel, and/or adjust neighboring cell level parameters of the congested cell and neighboring cells thereof, and/or notify human handling.
In practical application, the device can be used as a single system, and can also be a logic unit which is added in the existing base station and completes different functions.
When a logic unit is added to the base station, the period determination unit 601, the sampling unit 602, the congestion prediction unit 603, the adjustment unit 604, the setting unit 605, the analysis unit 631, the prediction unit 632, and the emergency communication adjustment unit 641 may be implemented by a Central Processing Unit (CPU), a Digital Signal Processor (DSP), or a Programmable Gate Array (FPGA) located in the base station.
The above description is only exemplary of the present invention and should not be taken as limiting the scope of the present invention, and any modifications, equivalents, improvements, etc. that are within the spirit and principle of the present invention should be included in the present invention.
Claims (12)
1. A method for network optimization, comprising:
determining a polling period according to the communication load;
polling and sampling each preset communication guarantee cell according to the polling period to obtain the real-time performance index of each communication guarantee cell;
for each communication guarantee cell, carrying out congestion prediction according to the acquired real-time performance index and historical performance index under the similar communication guarantee scene;
and carrying out optimization adjustment according to the congestion prediction result of each communication guarantee cell.
2. The method of claim 1, wherein prior to determining the polling period based on the traffic load, the method further comprises: setting a communication guarantee cell and communication guarantee duration according to a communication guarantee scene;
the communication guarantee scene comprises a normal network monitoring scene and an emergency communication guarantee scene.
3. The method of claim 1, wherein determining a polling period based on communication load comprises:
and respectively calculating a sampling period according to the extracted load of an Operation Manager (OMU) of a communication guarantee cell home Base Station Controller (BSC) and the load of a data processing server, and determining the larger value of the two as a polling period.
4. The method according to claim 1 or 2, wherein the predicting congestion according to the obtained real-time performance index and historical performance index under the similar communication guarantee scenario comprises:
calculating a predicted performance index according to the real-time performance index obtained by sampling and the historical performance index of the same time period under the same type of communication guarantee scene; and determining the congestion state of the communication guarantee cell according to the predicted performance index.
5. The method of claim 4, wherein the calculating the predicted performance index according to the sampled real-time performance index and the historical performance index of the same time period in the same type of communication guarantee scene, and the determining the congestion state of the communication guarantee cell according to the predicted performance index comprises:
obtaining real-time telephone traffic of a communication guarantee cell through real-time performance indexes obtained by sampling, calculating the trial call number of a predicted voice channel of the communication guarantee cell according to the real-time telephone traffic, the historical telephone traffic of the same time period in the same scene and the historical voice trial call number of the same time period in the same scene, and further obtaining the single trial call occurrence interval of the predicted voice channel;
when the duration with the voice channel occupancy rate of 100% exceeds the single call trial occurrence interval, determining the communication guarantee cell as a congestion cell;
obtaining the real-time telephone traffic through real-time performance indexes for at least six times;
the real-time performance indicators include: the number of time slots occupied by the voice channel and the idle time slots of the voice channel.
6. The method of claim 5, wherein the optimally adjusting according to the congestion prediction result of each communication assurance cell comprises:
calculating a congestion rate and/or a congestion duration through the determined duration of each recorded congestion of the congested cell, the recorded times of the congestion and the monitoring duration; and sequencing according to the congestion rates and/or the congestion time lengths of all the determined congestion cells, and preferentially processing the congestion cells with high congestion rates and/or long congestion time lengths.
7. An apparatus for network optimization, the apparatus comprising: a polling cycle determining unit, a sampling unit, a congestion predicting unit and an adjusting unit; wherein,
a cycle determination unit configured to determine a polling cycle according to a communication load;
the sampling unit is used for performing polling sampling on each preset communication guarantee cell according to the polling period to acquire the real-time performance index of each communication guarantee cell;
the congestion prediction unit is used for predicting congestion according to the acquired real-time performance index and historical performance index under the similar communication guarantee scene aiming at each communication guarantee cell;
and the adjusting unit is used for carrying out optimization adjustment according to the congestion prediction result of each communication guarantee cell.
8. The apparatus of claim 7, further comprising a setting unit; the setting unit is used for setting a communication guarantee cell and communication guarantee duration according to a communication guarantee scene; wherein,
the communication guarantee scene comprises a normal network monitoring scene and an emergency communication guarantee scene.
9. The apparatus according to claim 7, wherein the period determining unit is specifically configured to: and respectively calculating a sampling period according to the extracted OMU load of the BSC to which the communication guarantee cell belongs and the load of the data processing server, and determining the larger value of the two as a polling period.
10. The apparatus according to claim 7 or 8, wherein the congestion prediction unit further comprises: an analysis unit and a prediction unit; wherein,
the analysis unit is used for calculating a predicted performance index according to the real-time performance index obtained by sampling and the historical performance index of the same time period under the similar communication guarantee scene;
and the prediction unit is used for determining the congestion state of the communication guarantee cell according to the predicted performance index.
11. The apparatus according to claim 10, wherein the analysis unit is specifically configured to:
obtaining real-time telephone traffic of a communication guarantee cell through real-time performance indexes obtained by sampling, calculating the trial call number of a predicted voice channel of the communication guarantee cell according to the real-time telephone traffic, the historical telephone traffic of the same time period in the same scene and the historical voice trial call number of the same time period in the same scene, and further obtaining the single trial call occurrence interval of the predicted voice channel; accordingly, the number of the first and second electrodes,
the prediction unit is specifically configured to: and when the duration with the voice channel occupancy rate of 100% exceeds the single call trial occurrence interval, determining the communication guarantee cell as a congestion cell.
12. The apparatus according to claim 11, wherein the adjusting unit is specifically configured to:
calculating a congestion rate and/or a congestion duration through the determined duration of each recorded congestion of the congested cell, the recorded times of the congestion and the monitoring duration; and sequencing according to the congestion rates and/or the congestion time lengths of all the determined congestion cells, and preferentially processing the congestion cells with high congestion rates and/or long congestion time lengths.
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