WO2017054422A1

WO2017054422A1 - Method and device for managing cell peak time segment and self-organizing network cell

Info

Publication number: WO2017054422A1
Application number: PCT/CN2016/076875
Authority: WO
Inventors: 刘芙蕾
Original assignee: 中兴通讯股份有限公司
Priority date: 2015-09-28
Filing date: 2016-03-21
Publication date: 2017-04-06
Also published as: CN106559828B; CN106559828A

Abstract

Disclosed are a method and device for managing a cell peak time segment, and a self-organizing network cell. A process of identifying a cell peak time segment comprises: acquiring network performance parameter values of a cell at N time segments within a measurement period, wherein N is greater than or equal to 1; and comparing the network performance parameter values acquired at respective time segments with a first preset network performance parameter threshold, and if a comparison result between one of the network performance parameter values and the first preset network performance parameter threshold satisfies a preset condition, determining the time segment corresponding to said network performance parameter value to be a peak time segment of the cell. The above measurement process enables a peak time segment, namely a high-load time segment, of a cell to be identified accurately, thereby providing a reliable basis for optimizing a radio network load. (FIG. 1)

Description

Cell busy period management method, device and self-organizing network element

Technical field

The present invention relates to the field of communications, and in particular, to a cell busy period management method and apparatus, and an ad hoc network element.

Background technique

The current wireless network, such as GSM (Global System for Mobile Communication), UMTS (Universal Mobile Telecommunications System)/TD-SCDMA (Time Division-Synchronous Code Division Multiple Access), LTE (Long Term Evolution), has been widely used, network optimization. The method, in addition to manual optimization, is also automatically optimized. Auto-optimization is one of the self-organizing network functions by automatically monitoring network metrics (for example, counters or key performance indicators) to adjust for deteriorating metrics when network performance deteriorates. Corresponding wireless parameter values improve network performance. The goals of network optimization in self-organizing networks are network coverage, network capacity, network load, and so on. In the network load optimization, it is first necessary to identify the high load time of the wireless network. Due to the difference in user distribution and user behavior, the time of occurrence of high load in different areas of the network may be inconsistent. For example, the high load time of the business area occurs during daytime work hours. The high load time in residential areas occurs during nighttime breaks. Therefore, it is very important to be able to identify the high load time (ie, busy time) of each area of the wireless network, and it is also an important prerequisite for optimizing the no-network load.

Summary of the invention

The main technical problem to be solved by the present invention is to provide a cell busy period management method and device, and an ad hoc network element, which solves the problem of how to implement the busy period of each cell of the wireless network.

To solve the above technical problem, the present invention provides a cell busy period management method, including:

Obtaining a network performance parameter value of the cell in the N period of the statistical period, where the N is greater than or equal to 1;

The obtained network performance parameter values of the time periods are respectively compared with the first preset network performance parameter thresholds, and the corresponding time period in which the comparison result meets the preset condition is determined as the busy time period of the cell.

In an embodiment of the present invention, the network performance parameter value includes an average power value, and the first preset network performance parameter threshold includes a first average power threshold, and the preset condition is that the average power value is greater than or equal to Describe a first average power threshold;

Or the network performance parameter value includes an average number of users, and the first preset network performance parameter threshold includes a first average user number threshold, where the preset condition is that the average number of users is greater than or equal to the first average user number threshold. ;

Or the network performance parameter value includes an average power value and an average number of users, where the first preset network performance parameter threshold includes a first average power threshold and a first average user number threshold, and the preset condition is an average power value. And greater than or equal to the first average power threshold, and the average number of users is greater than or equal to the first average number of users threshold.

In an embodiment of the present invention, the method further includes: performing a merge process on the determined busy periods.

In an embodiment of the present invention, the merging processing for the determined busy periods includes:

Determining whether the time interval between the busy periods is less than or equal to a preset time interval threshold in the busy periods determined, and if present, combining the busy periods into one time period;

And/or determining whether the determined number of busy periods is greater than a busy period number threshold of the cell, and if yes, combining two busy periods with a minimum time interval between busy periods into one, and then determining the merged Whether the number of busy periods is greater than the number of busy periods of the cell until the number of busy periods after the combination is less than or equal to the number of busy periods of the cell.

In an embodiment of the present invention, the method further includes configuring the cell to be a high load configuration during the busy periods.

In an embodiment of the present invention, the method further includes:

And determining, in a new statistical period, whether the network performance parameter value of each busy period is less than a second preset network performance parameter threshold, and if yes, determining that the corresponding busy period is converted to an idle period; and the second preset network performance parameter The threshold is less than the first preset network performance parameter threshold.

In an embodiment of the present invention, the method further includes configuring the cell to be a normal load configuration during the idle period.

In order to solve the above problem, the present invention further provides a cell busy period management apparatus, including:

a statistics module, configured to acquire a network performance parameter value of a cell in a period of N in a statistical period, where the N is greater than or equal to 1;

The processing module is configured to compare the acquired network performance parameter values of the time periods with the first preset network performance parameter thresholds, and determine a corresponding time period in which the comparison result meets the preset condition as a busy period of the cell.

In an embodiment of the present invention, the network performance parameter value includes an average power value, and the first preset network performance parameter threshold includes a first average power threshold, and the preset condition is that the average power value is greater than or equal to The first average power threshold, the statistic module includes a first statistic sub-module, the processing module includes a first processing sub-module, and the first statistic sub-module is configured to obtain an average power of N time periods in the statistical period And the first processing sub-module is configured to compare the average power value of the N time periods with the first average power threshold, respectively, to determine whether the preset condition is met;

Or the network performance parameter value includes an average number of users, and the first preset network performance parameter threshold includes a first average user number threshold, where the preset condition is that the average number of users is greater than or equal to the first average user number threshold. The statistic module includes a second statistic sub-module, where the processing module includes a second processing sub-module, and the second statistic sub-module is configured to obtain an average number of users of N time periods in the statistical period, the second The processing sub-module is configured to compare the average number of users of the N time periods with the first average user number threshold, and determine whether the preset condition is met;

Or the network performance parameter value includes an average power value and an average number of users, the first preset network performance The parameter threshold includes a first average power threshold and a first average user number threshold, where the preset condition is that the average power value is greater than or equal to the first average power threshold, and the average number of users is greater than or equal to the first average number of users threshold, The statistic module includes a first statistic sub-module and a second statistic sub-module, where the processing module includes a first processing sub-module and a second processing sub-module; the first statistic sub-module and the second statistic sub-module respectively And an average power value and an average number of users for acquiring N time periods in the statistical period, where the first processing submodule and the second processing submodule are respectively configured to use an average power value of the N time periods and the first An average power threshold is compared and the average number of users of the N time periods is compared with the first average number of users threshold to determine whether the preset condition is met.

In an embodiment of the present invention, the first merge management module and/or the second merge management module are further included.

The first merge management module is configured to determine whether the time interval between the busy periods is less than or equal to a preset time interval threshold in the determined busy periods, and if yes, combine the busy periods into one time period;

The second merge management module is configured to determine whether the determined number of busy periods is greater than a busy period threshold of the cell, and if yes, combine two busy periods with a minimum interval between busy periods into one Then, it is determined whether the number of the busy periods after the combination is greater than the number of busy periods of the cell, until the number of busy periods after the combination is less than or equal to the number of busy periods of the cell.

In an embodiment of the present invention, the method further includes: a conversion management module, configured to determine, in a new statistical period, whether the network performance parameter value of each busy period is less than a second preset network performance parameter threshold, and if so, determine The corresponding busy period is converted to the idle period; the second preset network performance parameter threshold is smaller than the first preset network performance parameter threshold.

In order to solve the above problems, the present invention also provides an ad hoc network element, including the cell busy period management apparatus as described above.

The beneficial effects of the invention are:

The method for the cell busy period management and the self-organizing network element provided by the present invention, the process of identifying the busy period of the cell includes: acquiring the network performance parameter value of the N time period of the cell in the statistical period, where N is greater than or equal to 1; The network performance parameter values of each time period are compared with the first preset network performance parameter thresholds, and the corresponding time period in which the comparison result meets the preset condition is determined as the busy time period of the cell. Through the above-mentioned acquisition statistics process, the busy period of the cell, that is, the high load period, can be accurately identified, which provides a reliable basis for wireless network load optimization.

In addition, the present invention also proposes to perform the merging process on the identified multiple busy periods, which can avoid frequent changes in the busy period and cause the corresponding high-load configuration to be sent multiple times, thereby avoiding the increase of the configuration between the different devices. The amount of signaling interaction, while avoiding the unnecessary transmission of large amounts of data, occupies unnecessary system resources and improves system resource utilization. In this way, the network busy period can be more accurately identified; and the network busy hour load can be reduced if the system equipment load is minimized.

In addition, in the new statistical period, the present invention may also determine whether the previously calculated network performance parameter value of each busy period is smaller than the second preset network performance parameter threshold, and if so, determine that it is converted from the busy period to the idle period; It can identify that the busy period is changed to the idle period due to factors such as changes in the network traffic model, thereby stopping the high-load configuration delivery, reducing the system equipment burden, or avoiding the network indicator ping-pong change.

DRAWINGS

1 is a schematic flowchart of a cell busy period management method according to Embodiment 1 of the present invention;

2 is a schematic flowchart of a cell busy and idle time conversion identification process according to Embodiment 1 of the present invention;

3 is a schematic structural diagram 1 of a cell busy period management apparatus according to Embodiment 2 of the present invention;

4 is a schematic structural diagram 2 of a cell busy period management apparatus according to Embodiment 2 of the present invention;

FIG. 5 is a schematic structural diagram 3 of a cell busy period management apparatus according to Embodiment 2 of the present invention.

detailed description

When the cell busy period is identified, the network performance parameter values of the N time periods of the cell in the statistical period are obtained, and then the obtained network performance parameter values of each time period are respectively compared with the first preset network performance parameter threshold, and the comparison is performed. As a result, the corresponding period that satisfies the preset condition is determined as the busy period of the cell. Through the above-mentioned acquisition statistics process, the busy period of the cell, that is, the high load period, can be accurately identified, which provides a reliable basis for wireless network load optimization. After the multiple busy periods are identified, the merging process can be flexibly performed according to the requirements, so as to avoid frequent changes in the busy period, causing the corresponding high-load configuration to be sent multiple times, thereby avoiding the increase of different devices due to the constant change of configuration. The amount of signaling interaction, while avoiding the unnecessary transmission of large amounts of data, occupies unnecessary system resources, improves system resource utilization; can more accurately identify the network busy time; and can reduce the system equipment load minimum The network is busy when it is loaded. At the same time, the present invention can also judge whether the previously calculated busy periods are converted into idle periods in the subsequent statistical period, so that the busy period can be identified as being changed due to factors such as changes in the network traffic model. The time period, thereby stopping the high-load configuration delivery, reducing the burden on the system equipment, or avoiding the ping-pong change of the network indicator. The present invention will be further described in detail below with reference to the accompanying drawings.

Embodiment 1:

Referring to FIG. 1 , a method for managing a busy period of a cell, including a process for identifying a busy period, is shown in FIG. 1 and includes:

Step 101: Acquire a network performance parameter value of the N time period of the cell in the statistical period, where N is greater than or equal to 1;

Step 102: Compare the obtained network performance parameter values of each time period with the first preset network performance parameter threshold, and determine a corresponding time period in which the comparison result meets the preset condition as the busy time period of the cell.

It should be understood that the specific value of the statistical period P in the above step 101 may be flexibly set according to factors such as actual situation requirements, for example, may be set to be in days, for example, 1 day; or may be set to be in units of months and years. For example, 1 month, 1 year, etc., fine control can also be set to hours or less time units;

In this embodiment, the time division manner of the statistical period can be flexibly selected; the multiple time periods obtained after the division can be equal or unequal; for example, if the statistical period P is 1 day, the duration of the time period is 1 hour and rounded off. The way the points are divided is divided into 24 time periods, each time period is 1 hour, and 0:00-1:00, 1:00-2:00, ..., 23:00-0:00 Time period. For another example, if the statistical period P>1 day, the period is first divided into 0:00-1; 00, 1:00-2:00, ..., 23 in the above manner in the above-mentioned manner. There are 24 time slots of :00-0:00. These 24 time periods are multiple time periods of the statistical period P, and then the network performance data of the same time period in each day of the statistical period is averaged to obtain the network performance parameter values of each time period. If the statistical period is P=3 days, the relevant network performance parameter values of 3 9:00-10:00 will be counted, and then the 3 values will be averaged to obtain the network performance of 9:00-10:00. Parameter value; if the period is 7 days, there will be 7 relevant network performance parameter values of 9:00-10:00, and then average these 7 values to get the network performance parameters of this period from 9:00-10:00 value. And so on. It should be understood that the manner of dividing the time period of the statistical period in this embodiment is not limited to the above exemplary manner, and may be, for example, divided into 12 time periods, 8 time periods, and the like. The value of N in the above step 101 may be greater than or equal to 1, which is less than or equal to the number of time slots divided in the statistical period. In order to prevent leakage statistics, in this embodiment, it is preferable that N is equal to the number of time slots divided in the statistical period.

The network performance parameter value in this embodiment may be any parameter value that can represent the network load condition. The following only uses several parameters as an example for description.

Example 1: The network performance parameter value includes an average power value, and the corresponding first preset network performance parameter threshold includes a first average power threshold, and the preset condition is that the average power value is greater than or equal to the first average power threshold; The average power value of each time period is compared with the first average power threshold, and is greater than or equal to the first average power threshold, and the time period is determined to be a busy period.

Example 2: The network performance parameter value includes an average number of users, and the corresponding first preset network performance parameter threshold includes a first average user number threshold, and the preset condition is that the average number of users is greater than or equal to the first average user number threshold; The statistical average number of users in each time period is compared with the first average user number threshold, and is greater than or equal to the first average user number threshold, and the time period is determined as a busy period.

Example 3: The network performance parameter value includes an average power value and an average number of users, and the corresponding first preset network performance parameter threshold includes a first average power threshold and a first average user number threshold, and the preset condition is that the average power value is greater than or equal to the first An average power threshold, and the average number of users is greater than or equal to the first average number of users threshold. At this time, the average power value and the average number of users in each period are compared with the first average user number threshold, and the average power value of the comparison result is greater than or equal to the first average power threshold and the average number of users is greater than or equal to the first average user. For a threshold, the corresponding time period is a busy period.

After the busy period in the cell is identified by the above process, when the busy period comes, the cell is configured as a high load configuration.

In this embodiment, after the busy period in the cell is identified through the foregoing process, the determined busy periods may also be combined. The merging process can make the management of the busy period of the cell simpler and more efficient, and can reduce the amount of data interaction and improve system resource utilization. The scheme for merging busy periods in this embodiment may be based on specific Flexible settings with scenes. The following is a brief description of only a few examples.

Example 1: determining whether the time interval between busy periods is less than or equal to a preset time interval threshold in each busy period determined, and if present, combining the busy periods into one time period; for example, when the determined busy periods are respectively 07:00-08:00, 11:00-12:00, 13:00-14:00, 18:00-19:00, the preset time interval threshold is 1 hour, due to the third busy period The interval between the start time and the end time of the second busy period = <preset time interval threshold (1 hour), so the busy period after the merge is: 07:00-08:00, 11:00-14: 00, 18:00-19:00.

Example 2: determining whether the determined number of busy periods is greater than a busy period threshold of the cell, and if so, combining two busy periods with the smallest interval between busy periods into one, and then determining the merged busy periods Whether the number is greater than the busy period number threshold of the cell until the number of merged busy periods is less than or equal to the busy period number threshold of the cell. For example, when the determined busy periods are 07:00-08:00, 11:00-12:00, 13:00-14:00, 18:00-19:00, respectively; the number of busy hours of the cell The threshold is three, and since the determined number of busy periods is greater than three, and the time interval between the third busy period and the second busy period is the smallest, the busy period after the merge is: 07:00- 08:00, 11:00-14:00, 18:00-19:00.

Example 3: determining whether the time interval between busy periods is less than or equal to a preset time interval threshold in each busy period determined, and if present, combining the busy periods into one time period; and then determining the determination (that is, the merged Whether the number of busy periods is greater than the busy period number threshold of the cell, and if so, the two busy periods with the smallest interval between busy periods are combined into one, and then it is determined whether the number of merged busy periods is greater than The number of busy periods of the cell is determined until the number of busy periods after the combination is less than or equal to the number of busy periods of the cell. For example, when the determined busy periods are 02:00-03:00, 07:00-08:00, 11:00-12:00, 13:00-14:00, 18:00-19:00, The preset time interval threshold is 1 hour, and the number of busy periods of the cell is three; then the interval between the start time of the fourth busy period and the end time of the third busy period = < preset time interval threshold (1 hour), so the busy time after the first merger is: 02:00-03:00, 07:00-08:00, 11:00-14:00, 18:00-19:00; then judge The busy period determined after the merge processing is four, which is greater than the busy period number threshold of the cell, and the time interval between the third busy period and the second busy period is the smallest, so the busy period after the second merge is: 02:00-03:00, 07:00-14:00, 18:00-19:00.

Through the above-mentioned merging process, it is possible to avoid the frequent change of the busy period and the corresponding high-load configuration to be repeatedly sent, thereby avoiding the increase of the signaling interaction between different devices due to the continuous change of the configuration, and avoiding the occupation due to the continuous transmission of large amounts of data. The necessary system resources to improve system resource utilization. In this way, the network busy time can be more accurately identified; and the network busy hour load can be reduced if the system equipment load is minimized.

In this embodiment, the cell load is degraded due to a change in the traffic model, or the cell load is degraded due to the use of the busy configuration during the busy period. If the cell load decreases due to the change of the traffic model, the busy period needs to be changed to the idle period, the high load configuration is stopped, and the normal load configuration is used. If the cell load is degraded due to the use of the high-load configuration during the busy period, the high-load configuration is still required during the period of the subsequent period, so that the normal configuration is not used in the period of the subsequent period without using the high-load configuration, and the network load cannot be used. Drop Low, causing the network load to rebound. When the cell load is degraded due to the change of the traffic model, and the busy period is changed to the idle period, the time period after the transition needs to be identified, and the corresponding high load configuration is switched to the normal load configuration. The process is shown in Figure 2 and includes:

Step 201: Statistics of network performance parameters of each time period in a new statistical period;

Step 202: Determine whether the network performance parameter value of each busy period determined in the previous statistical period is less than the second preset network performance parameter threshold, and if yes, go to step 203; otherwise, go to step 205;

Step 203: Determine that the corresponding busy period is converted into an idle period;

Step 204: Configure the cell as a normal load configuration when the idle time comes.

Step 205: the busy period is unchanged;

Step 206: Configure the cell to be in a high load configuration when the busy period arrives.

In the foregoing step, the second preset network performance parameter threshold is smaller than the first preset network performance parameter threshold, and the specific value may be obtained by subtracting a compensation value from the first preset network performance parameter threshold, and the specific value of the compensation value may be flexibly set. .

Through the above process, it can be recognized that the busy period is changed to the idle period due to factors such as changes in the network traffic model, thereby stopping the high-load configuration from being delivered, reducing the system equipment burden, or avoiding the network indicator ping-pong change.

Embodiment 2:

Referring to FIG. 3, the embodiment provides a cell busy period management apparatus, including:

The statistic module 1 is configured to obtain a network performance parameter value of the N time period of the cell in the statistical period P, where N is greater than or equal to 1; the specific value of the statistical period P can be flexibly set according to factors such as actual situation requirements, for example, it can be set to The unit, for example, one day; can also be set in units of months and years, for example, one month, one year, etc., and the time unit of hours or less can also be set in the fine control.

In addition, the time division manner of the statistical period in the embodiment may be flexibly selected; the multiple time periods obtained after the division may be equal or different; for example, if the statistical period P is 1 day, the duration of the time period is 1 hour and The division of the whole point is divided into 24 time periods, each time period is 1 hour, and 0:00-1:00, 1:00-2:00, ..., 23:00-0:00 These 24 time periods. For another example, if the statistical period P>1 day, the daily period is first divided into 0:00-1:00, 1:00-2:00,...,23 according to the above manner. There are 24 time slots of :00-0:00. These 24 time periods are multiple time periods of the statistical period P, and then the network performance data of the same time period in each day of the statistical period is averaged to obtain the network performance parameter values of each time period. If the false statistical period is P=3 days, the relevant network performance parameter values of 3 9:00-10:00 will be counted, and then the 3 values will be averaged to obtain the network from 9:00-10:00. Performance parameter value; if the period is 7 days, there will be 7 relevant network performance parameter values of 9:00-10:00, and then average these 7 values to get the network performance of this period from 9:00-10:00 Parameter value. And so on. It should be understood that the manner of dividing the time period of the statistical period in this embodiment is not limited to the above exemplary manner, and may be, for example, divided into 12 time periods, 8 time periods, and the like. This implementation In the example, the value of N may be greater than or equal to 1, less than or equal to the number of time slots divided in the statistical period. In order to prevent leakage statistics, N is preferably equal to the number of time slots divided in the statistical period.

The processing module 2 is configured to compare the obtained network performance parameter values of each time period with the first preset network performance parameter threshold, and determine a corresponding time period in which the comparison result meets the preset condition as the busy time period of the cell.

Example 1: The network performance parameter value includes an average power value, the first preset network performance parameter threshold includes a first average power threshold, and the preset condition is that the average power value is greater than or equal to the first average power threshold, and the statistics module 1 includes the first a statistic sub-module, the processing module 2 includes a first processing sub-module; the first statistic sub-module is configured to obtain an average power value of N time periods in a statistical period according to the foregoing manner, and the first processing sub-module is configured to average power of N time periods The values are respectively compared with the first average power threshold to determine whether the preset condition is met;

Example 2: The network performance parameter value includes an average number of users, and the first preset network performance parameter threshold includes a first average number of users threshold, and the preset condition is that the average number of users is greater than or equal to the first average number of users, and the statistics module 1 includes a second statistic sub-module, the processing module 2 includes a second processing sub-module; the second statistic sub-module is configured to obtain an average number of users of N time periods in the statistical period according to the foregoing manner, and the second processing sub-module is configured to use N time periods The average number of users is compared with the first average number of users threshold to determine whether the preset condition is met;

Example 3: The network performance parameter value includes an average power value and an average number of users, and the first preset network performance parameter threshold includes a first average power threshold and a first average user number threshold, and the preset condition is that the average power value is greater than or equal to the first The statistic module 1 includes a first statistic sub-module and a second statistic sub-module, and the processing module 2 includes a first processing sub-module and a second processing sub-module, and the average user number is greater than or equal to the first average user number threshold. The first statistical sub-module and the second statistical sub-module are respectively used to obtain the average power value and the average user number of the N time periods in the statistical period according to the foregoing manner, and the first processing sub-module and the second processing sub-module are respectively used for Comparing the average power value of the N time periods with the first average power threshold and comparing the average number of users of the N time periods with the first average number of users threshold to determine whether the preset condition is met.

In this embodiment, after the busy period in the cell is identified through the foregoing process, the determined busy periods may also be combined. The merging process can make the management of the busy period of the cell simpler and more efficient, and can reduce the amount of data interaction and improve system resource utilization. Referring to FIG. 4, the cell busy period management apparatus further includes a first merge management module 3 and/or a second merge management module 4,

When the cell busy period management apparatus includes the first merge management module 3, the first merge management module 3 is configured to determine whether the time interval between the busy periods is less than or equal to the preset time interval threshold, if any, Combine these busy periods into one time period; for example, when the determined busy periods are 07:00-08:00, 11:00-12:00, 13:00-14:00, 18:00-19:00 The preset time interval threshold is 1 hour, because the time interval between the start time of the third busy period and the end time of the second busy period = < preset time interval threshold (1 Hours), so the busy hours after the merger are: 07:00-08:00, 11:00-14:00, 18:00-19:00.

When the cell busy period management apparatus includes the second merge management module 4, the second merge management module 4 is configured to determine whether the determined number of busy periods is greater than a busy period number threshold of the cell, and if so, the time interval between busy periods The minimum two busy periods are combined into one, and then it is determined whether the number of merged busy periods is greater than the busy period number threshold of the cell, until the number of merged busy periods is less than or equal to the busy period number threshold of the cell. For example, when the determined busy periods are 07:00-08:00, 11:00-12:00, 13:00-14:00, 18:00-19:00, respectively; the number of busy hours of the cell The threshold is three, and since the determined number of busy periods is greater than three, and the time interval between the third busy period and the second busy period is the smallest, the busy period after the merge is: 07:00- 08:00, 11:00-14:00, 18:00-19:00.

When the cell busy period management apparatus includes the first merge management module 3 and the second merge management module 4, the first merge management module 3 is configured to determine whether the time interval between the busy periods is less than or equal to the preset in each determined busy period. The time interval threshold, if present, merges the busy periods into one time period; the second merge management module 4 is configured to re-determine whether the number of busy periods determined (ie, merged) is greater than a busy period number threshold of the cell If yes, combine the two busy periods with the smallest interval between busy periods into one, and then determine whether the number of merged busy periods is greater than the number of busy periods of the cell until the number of busy periods after the merge Less than or equal to the number of busy periods of the cell. For example, when the determined busy periods are 02:00-03:00, 07:00-08:00, 11:00-12:00, 13:00-14:00, 18:00-19:00, The preset time interval threshold is 1 hour, and the number of busy periods of the cell is three; then; the first merge management module 3 determines the start time of the fourth busy period and the end time of the third busy period. Interval = <preset interval threshold (1 hour), so the busy period after the first merge is: 02:00-03:00, 07:00-08:00, 11:00-14:00, 18: 00-19:00; then the second merge management module 4 determines that the busy period determined after the merge processing is four, greater than the busy period number threshold of the cell, and the time between the third busy period and the second busy period The interval is the smallest, so the busy period after the second merge is: 02:00-03:00, 07:00-14:00, 18:00-19:00.

Through the above-mentioned merging process, it is possible to avoid the frequent change of the busy period and the corresponding high-load configuration to be repeatedly sent, thereby avoiding the increase of the signaling interaction between different devices due to the continuous change of the configuration, and avoiding the occupation due to the continuous transmission of large amounts of data. The necessary system resources to improve system resource utilization. In this way, the network busy period can be more accurately identified; and the network busy hour load can be reduced if the system equipment load is minimized.

In this embodiment, the cell load is degraded due to a change in the traffic model, or the cell load is degraded due to the use of the busy configuration when busy. If the cell load decreases due to the change of the traffic model, the busy period needs to be changed to the idle period, the high load configuration is stopped, and the normal load configuration is used. If the cell load is degraded due to the use of the high-load configuration during the busy period, the high-load configuration is still required during the period of the subsequent period, so that the normal configuration is not used in the period of the subsequent period without using the high-load configuration, and the network load cannot be used. Lower, causing the network load to rebound. When the cell load is degraded due to the change of the traffic model, and the busy period is changed to the idle period, the period after the transition is required to be identified, and the corresponding high load configuration is switched to the normal load configuration. Referring to FIG. 5, the cell busy period management apparatus further includes a conversion management module 5 for using the new During the statistical period, it is determined whether the network performance parameter value of each busy period is less than the second preset network performance parameter threshold. If yes, it is determined that the corresponding busy period is converted into the idle period, and then the cell is configured as a normal load configuration when the idle period arrives. .

The second preset network performance parameter threshold is smaller than the first preset network performance parameter threshold. The specific value can be obtained by subtracting a compensation value from the threshold of the first preset network performance parameter, and the specific value of the compensation value can be flexibly set.

It should be understood that the foregoing cell busy period management device in this embodiment may be a single device, or may be integrated in a self-organizing network (SON: self-organization network) network element.

The above cell busy period management apparatus is configured to perform the above-described cell busy period management method. The cell busy period management device may include at least one of a processing component, a memory, a power component, an input and output interface, and a communication component.

The processing component can perform all operations of the cell busy period management device, such as data communication, data comparison, recording operations, and the like. Processing components may include one or more processors for executing instructions to implement all or a portion of the steps above. Moreover, the processing component can include one or more modules that facilitate interaction between the processing component and other components.

The memory is configured to store various types of data to support operation of the cell busy period management device. Examples of such data include instructions, messages, etc. of any application or method running on a cell busy time management device. The memory can be implemented using any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read only memory (EEPROM), erasable programmable Read Only Memory (EPROM), Programmable Read Only Memory (PROM), Read Only Memory (ROM), Magnetic Memory, Flash Memory, Disk or Optical Disk.

The power component provides power to various components of the cell busy time management device.

The input/output interface provides an interface between the processing component and the peripheral interface module, and the peripheral interface module may be a keyboard, a click wheel, a button, or the like.

The communication component is configured to facilitate wired or wireless communication between the cell busy time management device and other devices to enable transmission and reception of related data and/or information and the like.

In an exemplary embodiment, there is also provided a non-transitory computer readable storage medium comprising instructions, such as a memory comprising instructions executable by a processor of a cell busy time management device to perform the above method. For example, the non-transitory computer readable storage medium described above may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device.

Embodiment 3:

In this embodiment, some cells to be optimized are selected in the wireless network, and an ad hoc network task is created. The main purpose of the task is to identify the busy period of the selected cell to be optimized, and to use the high load configuration during the busy period and the normal load configuration during the idle period. The specific control process is as follows:

The initial setting: the statistical period P=1 days, the duration of the time period is 1 hour and the division of the whole point is divided into 24 time periods, and the wireless performance data D is the average power of the monitoring, and the preset threshold of the average power. (ie, the first average power threshold) Q=40%; the preset time interval threshold N=1 between busy periods; the busy period number threshold M=3; the compensation value delta=10%, that is, the second average power threshold Equal to Q-delta=30%, the initial use of the cell is a common configuration.

2) Data collection: Take the cell A of the cell to be optimized as an example, and collect the data of the 24 hours of the cell A, that is, the data of the acquisition period P1 (00:00-24:00), and perform the following processing.

3) Data processing: If the average power collection granularity in the system is 15 minutes, it needs to be combined according to the granularity of 1 hour, and finally 24 sets of data corresponding to 24 hours of average power are obtained.

4) Busy time identification: The average power data is filtered. If the condition is satisfied: the average power of an hour is >=40%, the hour is the busy period of cellA. For example, the busy hours selected are: 07:00-08:00, 11:00-12:00, 13:00-14:00, 18:00-19:00.

5) Busy-time merge: Since the time interval between the start time of the third busy hour and the end time of the second busy time = <N (1 hour), the busy period of cellA is: 07:00-08: 00, 11:00-14:00 18:00-19:00.

6) Checking the number of busy periods: The number of busy periods of the merged cellA is 3, and if M=3 is satisfied, the busy period of the output of the cellA is 07:00-08:00, 11:00-14:00, 18 :00-19:00.

7) Configured during busy time: cellA changes to high load configuration at 07:00 of cycle P2, changes to normal configuration at 08:00, changes to high load configuration at 11:00, changes to normal configuration at 14:00, 18:00 Change to a high-load configuration and change to a normal configuration at 19:00.

8) Busy time and idle time change recognition: Perform steps 2)-4). Collect data for period P2 (00:00-24:00),

If the average power of 07:00-08:00 is <30%, it is considered that 07:00-08:00 becomes idle;

If the average power of 17:00-18:00 is >=40%, it is considered that 17:00-18:00 is busy;

Perform steps 5)-6) and the output is: 11:00-14:00, 17:00-19:00.

Perform steps 7)-8) until the task stops.

Embodiment 4:

Select some cells to be optimized in the wireless network, and create an ad hoc network task. The main purpose of the task is to identify the busy time of the selected cell to be optimized, and use the high load configuration when busy, and use the normal configuration when idle. . The specific settings and steps are as follows:

1) Initial setting: period P=3 days; divide the time period into 1 hour and divide the whole point into 24 time periods, wireless performance data D is the average power of monitoring, the preset power of average power Threshold (ie, first average power threshold) Q=40%; preset time interval threshold N=1 between busy periods; busy period number threshold M=3; compensation value delta=10%, ie second average power The threshold is equal to Q-delta=30%, the initial cell All are in common configuration.

2) Data collection: Take the cell A of the cell to be optimized as an example, and collect data of 3 days and 72 hours of the collection period P1 of the cell A, and perform the following processing.

3) Data processing: If the average power collection granularity in the system is 15 minutes, it needs to be combined according to the granularity of 1 hour. Firstly, the average power is corresponding to 3 days*24 hours of data; then, the same hour every day. The data is averaged, for example, three groups of data from 08:00 to 09:00 are averaged to obtain one set of data; finally, 24 sets of data are output.

4) Busy time period identification: The average power data is filtered. If the condition is satisfied: the average power of an hour is >=40%, the hour is the busy period of cellA. For example, the busy hours selected are: 07:00-08:00, 11:00-12:00, 13:00-14:00, 18:00-19:00, 21:00-22:00.

5) Busy time pooling: Since the time interval between the start time of the third busy hour and the end time of the second busy time = <N (1 hour), the busy period of cellA is: 07:00-08: 00, 11:00-14:00, 18:00-19:00, 21:00-22:00.

6) Checking the number of busy periods: the number of busy periods of the combined cell A is 4, and the number of busy periods is M=3. According to the principle: the two busy periods with the shortest interval are combined and processed in a loop until there are M busy periods. If the merger is performed between 18:00-19:00 and 21:00-22:00, the busy period of the output of cellA is 07:00-08:00, 11:00-14:00, 18:00-22:00. .

7) Busy and idle configuration: The following actions are repeated every day for 3 days of cycle P2: cellA changes to high load configuration at 07:00, change to normal configuration at 08:00, change to high load configuration at 11:00, 14:00 Change to normal configuration, change to high load configuration at 18:00, change to normal configuration at 22:00.

8) Busy time and idle time change recognition: Perform steps 2)-4). The data of the period P2 is collected, and the data of each hour of the three days is averaged separately.

Perform steps 5)-6) and the output is: 11:00-14:00, 18:00-22:00.

Perform steps 7)-8) until the task stops.

Embodiment 5:

1) Initial setting: period P=3 days, the duration of the period is 1 hour and the division of the whole point is divided into 24 periods; the wireless performance data D is the average power monitored and the average number of users, of which the average The preset threshold of power (ie, the first average power threshold) Q=40%; the preset time interval threshold between busy periods N=2; the busy period number threshold M=3; the compensation value delta=10%, also That is, the second average power threshold is equal to Q-delta=30%, the preset threshold of the average number of users (ie, the first user average threshold) Q2=20; delta2=5; that is, the second level The average user number threshold is equal to Q2-delta2=15; the initial use of the cell is a common configuration.

3) Data processing: If the average power and the average number of users in the system are 15 minutes, the data needs to be combined according to the granularity of 1 hour. First, the average power and the average number of users are corresponding to 3 days*24 hours. Data; then, the data of the same hour every day is averaged, for example, 3 groups of 08:00-09:00 data are averaged to obtain 1 set of data; finally, 24 sets of data of average power and 24 sets of data of average users are output.

4) Busy hour identification: The average power and the average number of users are filtered. If the condition is: the average power of an hour is >=40% and the average number of users is >=20, the hour is the busy period of cellA. For example, the busy hours selected are: 07:00-08:00, 11:00-12:00, 13:00-14:00, 18:00-19:00, 21:00-22:00.

5) Busy time pooling: Since the busy time interval is N=2, the busy period of cellA is: 07:00-08:00, 11:00-14:00, 18:00-22:00.

6) Checking the number of busy periods: The number of busy periods of the merged cellA is 3, and if M=3 is satisfied, the busy period of the output of the cellA is 07:00-08:00, 11:00-14:00, 18 :00-22:00.

8) The busy period and idle period change recognition steps 2)-4). The data of the period P2 is collected, and the data of each hour of the three days is averaged separately.

If the average power and average number of users of the three busy periods have been identified as satisfying the condition: average power <30% or average number of users <15, it is considered that the identified busy periods are still busy periods.

Perform steps 5)-8) until the task stops.

The above is a further detailed description of the present invention in connection with the specific embodiments, and the specific embodiments of the present invention are not limited to the description. It will be apparent to those skilled in the art that the present invention may be made without departing from the spirit and scope of the invention.

Industrial applicability

The invention is applicable to the field of communication and is used for realizing effective management of a busy period of a cell.

Claims

A cell busy period management method includes:

Obtaining a network performance parameter value of the cell in the N period of the statistical period, where the N is greater than or equal to 1;

The obtained network performance parameter values of the time periods are respectively compared with the first preset network performance parameter thresholds, and the corresponding time period in which the comparison result meets the preset condition is determined as the busy time period of the cell.
The cell busy period management method according to claim 1, wherein the network performance parameter value comprises an average power value, the first preset network performance parameter threshold comprises a first average power threshold, and the preset condition is an average The power value is greater than or equal to the first average power threshold;

Or the network performance parameter value includes an average number of users, and the first preset network performance parameter threshold includes a first average user number threshold, where the preset condition is that the average number of users is greater than or equal to the first average user number threshold. ;

Or the network performance parameter value includes an average power value and an average number of users, where the first preset network performance parameter threshold includes a first average power threshold and a first average user number threshold, and the preset condition is an average power value. And greater than or equal to the first average power threshold, and the average number of users is greater than or equal to the first average number of users threshold.
The cell busy period management method according to claim 1 or 2, further comprising: performing a merge process on the determined busy periods.
The cell busy period management method according to claim 3, wherein the merging processing for the determined busy periods comprises:

Determining whether the time interval between the busy periods is less than or equal to a preset time interval threshold in the busy periods determined, and if present, combining the busy periods into one time period;

And/or determining whether the determined number of busy periods is greater than a busy period number threshold of the cell, and if yes, combining two busy periods with a minimum time interval between busy periods into one, and then determining the merged Whether the number of busy periods is greater than the number of busy periods of the cell until the number of busy periods after the combination is less than or equal to the number of busy periods of the cell.
The cell busy period management method according to claim 1 or 2, further comprising configuring the cell to be a high load configuration during the busy periods.
The cell busy period management method according to claim 1 or 2, further comprising:

And determining, in a new statistical period, whether the network performance parameter value of each busy period is less than a second preset network performance parameter threshold, and if yes, determining that the corresponding busy period is converted to an idle period; and the second preset network performance parameter The threshold is less than the first preset network performance parameter threshold.
The cell busy period management method according to claim 6, further comprising configuring the cell to be a normal load configuration during the idle period.
A cell busy period management device includes:

a statistics module, configured to acquire a network performance parameter value of the N time period of the cell in the statistical period, where the N Greater than or equal to 1;

The processing module is configured to compare the acquired network performance parameter values of the time periods with the first preset network performance parameter thresholds, and determine a corresponding time period in which the comparison result meets the preset condition as a busy period of the cell.
The cell busy period management apparatus according to claim 8, wherein the network performance parameter value comprises an average power value, the first preset network performance parameter threshold comprises a first average power threshold, and the preset condition is an average The power module is greater than or equal to the first average power threshold, the statistic module includes a first statistic sub-module, and the processing module includes a first processing sub-module; the first statistic sub-module is configured to acquire the statistical period An average power value of the N time periods, where the first processing sub-module is configured to compare the average power values of the N time periods with the first average power threshold, respectively, to determine whether the preset condition is met;

Or the network performance parameter value includes an average number of users, and the first preset network performance parameter threshold includes a first average user number threshold, where the preset condition is that the average number of users is greater than or equal to the first average user number threshold. The statistic module includes a second statistic sub-module, where the processing module includes a second processing sub-module, and the second statistic sub-module is configured to obtain an average number of users of the N time periods in the statistical period, The second processing sub-module is configured to compare the average number of users of the N time periods with the first average user number threshold, and determine whether the preset condition is met;

Or the network performance parameter value includes an average power value and an average number of users, where the first preset network performance parameter threshold includes a first average power threshold and a first average user number threshold, and the preset condition is an average power value. The first statistic module includes a first statistic sub-module and a second statistic sub-module, and the processing module includes a first process, where the first average power threshold is greater than or equal to the first average user number threshold. a sub-module and a second processing sub-module; the first statistic sub-module and the second statistic sub-module are respectively configured to obtain an average power value and an average number of users in N time periods in the statistical period, the first processing The submodule and the second processing submodule are respectively configured to compare an average power value of the N time periods with the first average power threshold and to average the number of users of the N time periods with the first average The user number threshold is compared to determine whether the preset condition is met.
The cell busy period management apparatus according to claim 8 or 9, further comprising a first merge management module and/or a second merge management module,

The first merge management module is configured to determine whether the time interval between the busy periods is less than or equal to a preset time interval threshold in the determined busy periods, and if yes, combine the busy periods into one time period;

The second merge management module is configured to determine whether the determined number of busy periods is greater than a busy period number threshold of the cell, and if so, combine two busy periods with a minimum time interval between busy periods into one Then, it is determined whether the number of the busy periods after the combination is greater than the number of busy periods of the cell, until the number of busy periods after the combination is less than or equal to the number of busy periods of the cell.
The cell busy period management apparatus according to claim 8 or 9, further comprising a conversion management module, configured to determine, in a new statistical period, whether the network performance parameter value of each busy period is smaller than a second preset network The performance parameter threshold, if yes, determining that the corresponding busy period is converted to the idle period; the second preset network performance parameter threshold is smaller than the first preset network performance parameter threshold.
A self-organizing network element, comprising the cell busy period management apparatus according to any one of claims 8-11.