WO2012109936A1

WO2012109936A1 - Wireless parameter self-optimization method and system

Info

Publication number: WO2012109936A1
Application number: PCT/CN2011/083220
Authority: WO
Inventors: 董玥昕
Original assignee: 中兴通讯股份有限公司
Priority date: 2011-02-18
Filing date: 2011-11-30
Publication date: 2012-08-23
Also published as: CN102647737B; CN102647737A

Abstract

Disclosed are a wireless parameter self-optimization method and system. The method comprises: a first base station determines a wireless parameter to be optimized in a first cell that is managed by said first base station and requires wireless parameter self-optimization; the first base station selects the corresponding optimization policy according to the wireless parameter, and notifies an Operation, Administration and Maintenance (OAM) node of same for assessment, or the first base station advises the OAM node to select the corresponding optimization policy according to the wireless parameter and to conduct an assessment; and after the assessment is passed, the wireless parameter is optimized according to the optimization policy. By way of the present invention, the optimization of different wireless parameters can be handled flexibly, the reliability of parameter optimization can be significantly improved and, at the same time, the number of calculations by a single node is effectively decreased.

Description

Method and system for wireless parameter self-optimization

The present invention relates to the field of wireless communications, especially

System. Scenery technology

In the Long Term Evolution (LTE) system, the number of network parameters is large, the correlation is strong, and the complexity is high. In addition, the system requires that the new configuration and management of the base station require minimal manual intervention, which puts new demands on the operation and maintenance of the network.

In order to solve the above problems, a self-configuring and self-optimizing network (SON) has been proposed and considered to be the most effective means of reducing cost and operational complexity. The SON function requires self-configuration, self-optimization, and self-healing. The self-configuration process, that is, the newly deployed node learns the necessary basic system operation configuration through the "automatic installation process" to realize the automatic configuration; the self-optimization process, that is, the result measured by the user equipment (UE, User Equipment) automatically Adjustment; Self-healing process, which automatically detects and locates most problematic areas and solves problems through self-healing mechanisms.

SON can greatly reduce cost and operational complexity, so the 3GPP, 3rd Generation Partnership Project (3GPP, 3rd Generation Partnership Project) organization has been committed to introducing SON into the LTE standard and is receiving more and more attention. At present, 3GPP has decomposed the self-configuration and self-optimization in SON into multiple functions and detailed descriptions of each function, pointing out the goals to be achieved.

SON's self-optimization process usually consists of two parts, one is the identification of network faults, and the other is the optimization of network faults. The identification of the fault is generally based on the UE measurement result or the information exchanged between the base stations, and the fault of the network fault is optimized for the SON. Several functions that need to be implemented, such as Mobrility Robustness Optimization (MRO), Mobility Load Balancing (MLB), Inter-cell Interference Coordination (ICIC), etc. The optimization process involves the modification of the radio parameters of the cell. Among many wireless parameters, the revision of some parameters will only affect the wireless performance of the cell, and the revision of some parameters will affect the wireless performance of the cell and related neighbors. According to the influence surface of the parameters, the strategy for optimizing the wireless parameters should also adopt a differentiated optimization method.

At present, the strategy for parameter self-optimization is usually selected from the method of distributed wireless parameter self-optimization and the method of centralized wireless parameter self-optimization. Figure 1 shows the centralized parameter optimization diagram, and Figure 2 shows the distribution. Schematic diagram of parameter optimization.

In the distributed wireless parameter self-optimization method, the base station determines the parameters to be optimized and the result of parameter optimization. Such an optimization method can quickly optimize the radio parameters of the cell, but on the other hand, such a method needs to rely on the base station. The standard interface between the two interfaces can only be negotiated with neighboring base stations for parameters that affect multiple cells. However, no matter how rich the interface information is, it is impossible for a base station to know the information of the entire area or other base stations in the network. The optimization of parameters is often one-sided, and ultimately the basic wireless performance of the cell cannot be guaranteed.

The centralized wireless parameter optimization method can effectively overcome the shortcomings of the distributed, and can fully consider the impact of the parameters that need to be optimized on the overall performance of the network. However, in the existing network, the number of cells is large, and if all the cells are optimized, Focused on the OAM (Operation Administration and Maintenance) node processing, then this centralized node will bear a lot of load pressure, and this node also becomes a hidden danger of system security. Summary of the invention

In view of this, the main object of the present invention is to provide a wireless parameter self-optimization method and system for solving the purely centralized wireless parameter optimization method or the distributed wireless parameter optimization method. In order to achieve the above object, the technical solution of the present invention is achieved as follows:

The invention provides a method for wireless parameter self-optimization, the method comprising:

Determining, by the first base station, a radio parameter that needs to be optimized in the first cell that is required to perform radio parameter self-optimization;

The first base station selects a corresponding optimization policy according to the wireless parameter, and notifies the OAM node to perform evaluation; or the first base station notifies the OAM node to select a corresponding optimization policy according to the wireless parameter, and performs an evaluation;

After the evaluation is passed, the wireless parameters are optimized according to an optimization strategy.

The first base station selects a corresponding optimization policy according to the wireless parameter, and notifies the OAM node for evaluation, including:

After the first base station determines that the wireless parameter that needs to be optimized in the first cell that is in its own jurisdiction determines that the wireless parameter only affects the first cell, or the first base station determines that the When the wireless parameter affects the first cell and affects the second cell, and the first base station can obtain the basic information of the second cell, the first base station selects a corresponding optimization policy according to the wireless parameter, The optimization parameters, the wireless parameter configuration before and after the application of the optimization policy, and the cell wireless scenario are reported to the OAM node for evaluation.

The evaluating, by optimizing the wireless parameter according to the optimization policy, includes: when the wireless parameter only affects the first cell, after the evaluation is passed, the OAM node notifies the first base station according to the first base station Selecting an optimization policy to optimize the wireless parameter of the first cell;

The radio parameter not only affects the first cell but also affects the second cell, and when the first base station can acquire basic information of the second cell, after the evaluation is passed, the OAM node notifies the first base station And performing, by the first base station and the second base station to which the second cell belongs, the radio parameters of the first cell and the second cell according to an optimization policy selected by the first base station Optimization.

The first base station notifies the 0AM node to select and optimize the corresponding optimization policy according to the wireless parameter, including:

Determining, by the first base station, that the radio parameter has an impact on the first cell, and affecting the second cell, and the first base station cannot acquire the basic information of the second cell, the first base station notifies the OAM node Optimizing the radio parameters of the first cell and the second cell, the OAM node selects a corresponding optimization policy according to the radio parameter, and according to the optimization policy, the radio parameter configuration before and after the optimization policy application, and the cell The wireless scene is evaluated.

The evaluating, by optimizing the radio parameter according to the optimization policy, includes: the radio parameter not affecting the first cell, but also affecting the second cell, and the first base station cannot acquire the When the basic information of the two cells is passed, the OAM node notifies the first base station and the second base station to which the second cell belongs to the first cell and the second cell according to an optimization policy selected by the OAM node. The wireless parameters are optimized.

The evaluating the optimization strategy includes: evaluating the impact of the optimization strategy on network performance, and evaluating when the evaluation result conforms to the established network planning indicator; otherwise, the evaluation is not passed.

The invention also provides a wireless parameter self-optimizing system, the system comprising: an optimization decision module, an optimization evaluation module and an optimization strategy library, wherein:

The optimization strategy library is used to store an optimization strategy;

The optimization decision module of the first base station is configured to determine a radio parameter that needs to be optimized in a first cell that is required by the first base station to perform radio parameter self-optimization, and is further configured to use the radio parameter from the optimization policy. Selecting an optimization strategy in the library and reporting it to the OAM node; or informing the OAM node to select a corresponding optimization policy according to the wireless parameter;

The optimization decision module of the OAM node is configured to: after receiving the notification of the optimization decision module of the first base station, select a corresponding optimization from the optimization policy library according to the wireless parameter Strategy

The optimization evaluation module is located at the OAM node, and is used to evaluate an optimization strategy reported by the optimization decision module of the first base station; and is also used to evaluate an optimization strategy selected by the optimization decision module of the first base station;

The optimization decision module is further configured to optimize the wireless parameter by evaluating according to an optimization strategy.

The optimization decision module of the first base station is further configured to determine, after determining the radio parameter that needs to be optimized in the first cell that is managed by the first base station, that the radio parameter is generated only for the first cell. When in effect, or determining that the wireless parameter has an impact on the first cell, and affecting the second cell, and determining that the first base station can acquire basic information of the second cell, according to the wireless parameter Selecting a corresponding optimization strategy from the optimization strategy library; and also for reporting the optimization parameter, the wireless parameter configuration before and after the optimization policy application, and the cell wireless scenario to the optimization evaluation module located at the OAM node.

The optimization evaluation module of the OAM node is further configured to: when the wireless parameter only affects the first cell, and after the evaluation is passed, notify the optimization decision module located at the first base station according to an optimization strategy Determining the wireless parameters of the first cell;

The optimization evaluation module of the OAM node is further configured to: in addition to affecting the first cell, the radio parameter has an impact on the second cell, and the first base station can acquire basic information of the second cell. And after the evaluation is passed, notifying the first base station, the optimization decision module located at the first base station and the optimization decision module located at the second base station to which the second cell belongs, according to an optimization strategy, respectively The wireless parameters of a cell and the second cell are optimized.

The optimization decision module of the first base station is further configured to determine that the wireless parameter has an impact on the first cell, and further affects the second cell, and determines that the first base station cannot acquire the second cell. Notifying the OAM node to the first cell and the second when the basic information Optimizing the wireless parameters of the cell;

Correspondingly, the optimization decision module located at the OAM node is further configured to select a corresponding optimization policy from the optimization policy library according to the wireless parameter, and configure the optimized parameter, the wireless parameter configuration before and after the optimization policy is applied, and The cell radio scenario is input to the optimization evaluation module located at the OAM node.

The optimization evaluation module of the OAM node is further configured to: in addition to affecting the first cell, the radio parameter has an impact on the second cell, and the first base station cannot acquire basic information of the second cell. And after the evaluation is passed, notifying the optimization decision module located at the first base station and the optimization decision module located at the second base station to which the second cell belongs to each of the first cell and the second cell according to an optimization policy The wireless parameters are optimized.

The optimization evaluation module of the OAM node is further configured to: when evaluating the optimization strategy, evaluate an impact of the optimization strategy on network performance, and when the evaluation result meets the determined network planning indicator, the evaluation passes; otherwise, The assessment did not pass.

A wireless parameter self-optimization method and system according to the present invention, in the framework of an existing protocol standard, determines whether to optimize wireless parameters by itself according to the amount of information available to the base station, and determines an optimization strategy when optimizing by itself. The SON centralized control node, that is, the OAM node, is notified for evaluation and verification. After the evaluation and verification is passed, the base station can modify the radio parameters of one or more cells according to the optimization strategy. If the base station cannot make a decision, the basic information is reported to the OAM node. The OAM node performs subsequent steps such as optimization decision, evaluation and verification, and overcomes the unreliability of purely centralized or distributed parameter optimization, improves the efficiency and reliability of system wireless parameter optimization, and can flexibly respond to different Optimization of wireless parameters; The shared processing of parameter optimization by base station and OAM nodes can effectively reduce the computational complexity of the nodes, and can also significantly improve the reliability of parameter optimization. DRAWINGS

Figure 2 is a schematic diagram of distributed parameter optimization;

3 is a schematic structural diagram of a system for self-optimization of a hybrid mode wireless parameter according to the present invention; FIG. 4 is a schematic flowchart of a wireless parameter self-optimization according to the present invention;

FIG. 5 is a schematic diagram of an application scenario of wireless parameter self-optimization according to the present invention. detailed description

In order to solve the defects of the existing distributed wireless parameter self-optimization method and the centralized wireless parameter self-optimization method, the present invention proposes a hybrid mode wireless parameter self-optimization method, and the basic idea is: in the framework of the existing protocol standard In the following, according to the amount of information that the base station can obtain, it is determined whether the wireless parameter is optimized by itself, and when the optimization is determined by itself, the optimization strategy is notified to the SON centralized control node, that is, the OAM node for evaluation and verification, and after the evaluation and verification is passed, the base station The radio parameters of one or more cells may be revised according to the optimization strategy; if the base station cannot make a decision, the basic information is reported to the OAM node, and the OAM node performs subsequent steps such as optimization decision, evaluation of the insurance certificate, and the like.

FIG. 3 is a schematic diagram of a system structure of a hybrid mode wireless parameter self-optimization according to the present invention. The system includes: an optimization decision module, an optimization evaluation module, and an optimization strategy library, where: an optimization strategy library, configured to store an optimization strategy, includes A variety of optimization strategies for wireless parameters, including handover parameter adjustment strategy, power parameter adjustment strategy, and cell selection reselection parameter adjustment policy and improvement. The optimization strategy library can be deployed separately. At the same time, the optimization strategy library will be backed up on the OAM node, the proxy server of the OAM node, and the base station side. Once the policy database is updated, all backups will be updated in time, as shown by the dotted line in Figure 3. Show.

The optimization decision module is mainly used to optimize the strategy. It is deployed on the OAM node, the proxy server of the OAM node, and the base station side. Specifically:

An optimization decision module located at the first base station, configured to determine a radio parameter that needs to be optimized in the first cell that is required by the first base station to perform radio parameter self-optimization; and is further configured to use the radio parameter Selecting an optimization strategy from the optimization strategy database (preferably, the optimization strategy database refers to the backup of the optimization strategy database in the first base station), and reporting the corresponding optimization policy to the OAM node; or notifying the OAM node to select the corresponding according to the wireless parameter. Optimization Strategy;

The optimization decision module located at the OAM node is configured to receive the notification from the optimization decision module of the first base station, and then optimize the policy base according to the wireless parameter (preferably, the optimization strategy library herein refers to the optimization strategy library in the OAM node) Select the appropriate optimization strategy in Backup);

In addition, an optimization evaluation module is deployed on the OAM node device, which uses simulation to evaluate whether the optimization strategy is valid and correct. The inputs of the optimization evaluation module include: optimization strategy, optimization of wireless parameter configuration before and after application of the strategy, and cell wireless scene.

An optimization evaluation module at the OAM node is used to evaluate the optimization strategy reported by the optimization decision module of the first base station; and is also used to evaluate the optimization strategy selected by the optimization decision module of the first base station; when evaluating the optimization strategy, the evaluation is performed. The impact of the optimization strategy on the network performance. When the evaluation result is consistent with the established network planning indicators, the evaluation is passed; otherwise, the evaluation fails.

The optimization decision module is also used to optimize the wireless parameters in accordance with the optimization strategy. The optimization decision module located in the first base station is further configured to determine, after determining the wireless parameter that needs to be optimized in the first cell that is managed by the first base station, whether the wireless parameter affects only the first cell, or determine the wireless parameter. In addition to affecting the first cell, and affecting the second cell, and determining that the first base station can obtain basic information of the second cell, selecting a corresponding optimization strategy from the optimization policy base according to the wireless parameter; The policy, the wireless parameter configuration before and after the application of the optimization policy, and the cell wireless scenario are reported to the optimization evaluation module located at the OAM node.

Correspondingly, the optimization evaluation module at the OAM node is further configured to: when the wireless parameter only affects the first cell, and after the evaluation is passed, notify the optimization decision module located at the first base station to perform the wireless parameter of the first cell according to the optimization policy. Optimizing; also used to affect the second cell in addition to the wireless parameter, and the first base station can acquire the base of the second cell In the present information, and after the evaluation is passed, the first base station is notified, and the optimization decision module located at the first base station and the optimization decision module located at the second base station to which the second cell belongs are in accordance with the optimization policy, respectively, for the first cell and the second cell. The wireless parameters are optimized.

The optimization decision module of the first base station is further configured to determine that the radio parameter has an impact on the first cell, and also affects the second cell, and determines that the first base station cannot obtain the basic information of the second cell, and notifies the OAM node to The wireless parameters of the first cell and the second cell are optimized; correspondingly, the optimization decision module located at the OAM node is further configured to select a corresponding optimization strategy from the optimization policy library according to the wireless parameter, and select the optimized strategy and the optimized strategy. The wireless parameter configuration before and after the application and the cell wireless scene input are input to the optimization evaluation module located at the OAM node.

Correspondingly, the optimization evaluation module at the OAM node is further configured to: when the wireless parameter affects the first cell, and affect the second cell, and the first base station cannot obtain the basic information of the second cell, Then, the optimization decision module located at the first base station and the optimization decision module located at the second base station to which the second cell belongs are respectively optimized for the wireless parameters of the first cell and the second cell according to the optimization policy.

Based on the hybrid mode schematic diagram of the wireless parameter self-optimization shown in FIG. 3, the wireless parameter self-optimization process of the hybrid mode of the present invention is as shown in FIG. 4, and includes:

Step 401: Determine a cell that needs to perform radio parameter self-optimization.

The base station determines a cell that needs to perform radio parameter self-optimization according to the phenomenon of the cell failure and the information reported by the terminal, and is referred to as a first cell for convenience of subsequent description.

Step 402: The base station to which the first cell belongs (referred to as the first base station for convenience of subsequent description) determines the wireless parameter that the first cell needs to be optimized.

The first base station may analyze the fault of the first cell according to the policy in the optimization policy base, and determine the wireless parameter that the first cell needs to be optimized. According to different faults, the wireless parameter, such as the power configuration parameter of the uplink and downlink of the cell, the cell handover threshold, and the cell selection. Dedicated priority, etc. Step 403, the first base station determines whether the wireless parameter that needs to be optimized only affects the first cell, if yes, step 406; otherwise, step 404 is performed;

Step 404: If the change of the radio parameter to be optimized does not affect only the first cell, the first base station needs to determine other cells affected by the radio parameter (refer to the second cell for convenience of subsequent description, the second cell may There are multiple), then step 405 is performed;

Step 405, it is determined whether the first base station can obtain the basic information of the second cell, and if yes, go to step 406; if no, go to step 408;

Step 406: If the change of the radio parameter only affects the first cell, or the change of the radio parameter affects the second cell, and the first base station can acquire basic information of the second cell, the optimization decision module of the first base station is optimized. The corresponding optimization strategy of the wireless parameter is selected in the policy library, and then step 407 is performed.

Step 407: The first base station reports the selected optimization policy, the radio parameter configuration before and after the optimization policy application, and the cell radio scenario to the optimization evaluation module of the OAM node, and then performs step 410.

Step 408, if the first base station fails to obtain the basic information of the second cell, the first base station notifies the OAM node to optimize the wireless parameters of the first cell and the second cell, and then performs step 409;

Step 409: The OAM node selects an optimization strategy corresponding to the wireless parameter from the optimization policy database, and inputs the optimization parameter, the wireless parameter configuration before and after the optimization policy application, and the cell wireless scenario into its own optimization evaluation module, and then performs step 410.

Step 410: The optimization evaluation module of the OAM node evaluates the impact of the optimization strategy on network performance, and then performs step 411.

Step 411, it is determined whether the evaluation is passed, if yes, step 412 is performed; otherwise, step 413 is performed;

The optimization evaluation module evaluates the impact of the optimization strategy on network performance if there is a negative impact Specific network planning indicators, when the evaluation results do not meet the network planning indicators, such as the coverage of the cell is empty, the edge throughput does not meet the network planning requirements, etc., that is, it has a negative impact on the network performance) then the assessment fails; Otherwise, the assessment is passed.

Step 412: When the evaluation is passed, the change of the wireless parameter only affects the situation of the first cell, and the OAM node notifies the first base station to optimize the wireless parameter of the first cell according to the selected optimization policy;

For the case where the change of the wireless parameter also affects the second cell, and the first base station can acquire the basic information of the second cell, the OAM node notifies the first base station, and the base station to which the first base station and the second cell belong (referred to as the first The two base stations each optimize the wireless parameters of the first cell and the second cell;

For the case where the change of the wireless parameter affects the second cell and the first base station is unable to acquire the basic information of the second cell, the OAM node notifies the first base station and the second base station to each of the first cell and the first according to the selected optimization policy. The wireless parameters of the two cells are optimized;

Step 409: When the evaluation fails, the OAM node notifies the first base station that the optimization policy selection fails, and does not perform optimization of the wireless parameters.

In summary, the method for self-optimization of the wireless parameter of the present invention is: the first base station determines a radio parameter that needs to be optimized in the first cell that is subject to self-optimization of the radio parameter, and the first base station selects corresponding optimization according to the radio parameter. The policy is notified to the OAM node for evaluation; or the first base station notifies the OAM node to select a corresponding optimization policy according to the wireless parameter, and performs an evaluation; after the evaluation is passed, the wireless parameter is optimized according to the optimization policy. Embodiment 1

In the wireless networking scenario shown in FIG. 5, it is assumed that the wireless system is an LTE system, and there are three cells under each base station. In the figure, four base stations belong to the same OAM node control, and the connection relationship between the base stations is as shown in the figure. 5 is shown. The cell 2 controlled by the base station 1 discovers the LOAD sent by the cell 11. The interference indication is given in the INFORMATION message (indicating that the cell 2 has caused high interference to the cell 11;), at this time, the optimization process of the cell 2 radio parameters is as follows:

1. The base station 1 determines that the interference of the cell 2 to the cell 11 is too high according to the high interference indication in the LOAD INFORMATION message sent by the cell 11 to the cell 2;

2. The base station 1 knows that the transmission power of the current reference signal of the cell 2 is too high, causing excessive interference to the neighboring cell, and needs to reduce the transmit power of the cell 1 reference signal, thereby reducing interference to the neighboring cell;

3. The base station 1 determines, according to the optimization strategy for high interference in the optimization strategy library, that one radio parameter of the cell 2, that is, the reference signal downlink transmission power needs to be optimized, and the base station 1 evaluates the influence range of the radio parameter;

4. The base station 1 finds that the change of the radio parameter only affects the cell 2, and does not affect the downlink power parameters of other cells, so the base station 1 selects a corresponding optimization strategy for the high interference fault from the optimization strategy library (such as reducing the downlink transmit power of the reference signal). 2dB), and the optimization parameter, the wireless parameter configuration before and after the optimization strategy application, and the cell wireless scene are notified to the optimization evaluation module of the OAM node;

5. The optimization evaluation module evaluates whether the revision of the downlink transmit power of the reference signal of the cell 1 has a negative impact on the network planning indicator according to the selected optimization strategy according to the basic information of the network planning, such as cell coverage and edge throughput;

6. The optimization evaluation module considers that the downlink transmit power of the revised reference signal will not have a negative impact on the network planning, and then allows the downlink transmit power of the reference signal of the cell 1 to be revised according to the selected optimization strategy (the downlink transmit power of the reference signal is reduced) 2dB), and feed this result back to base station 1;

7. The base station 1 modifies the downlink transmission power of the reference signal of the cell 2.

Embodiment 2

In the wireless networking scenario shown in FIG. 5, it is assumed that the wireless system is an LTE system. The cell 1 controlled by station 1 is overloaded and needs to be load balanced with the surrounding cells. Its neighboring area includes cell 4, cell 5, cell 7 and cell 12. The optimization process of cell 1 radio parameters is as follows:

1. The base station 1 determines the neighbor relationship of the cell 1, and obtains the radio resource load information of the cell 4, the cell 5, the cell 7 and the cell 12 through the RESOURCE STATUS UPDATE message on the X2 port;

2. Based on the load information of the neighboring cells, the base station 1 can calculate that the load of the cell 7 is the lowest through the use rate of the cell radio resources, and therefore the cell 7 is the load-down cell of the cell 1;

3. The base station 1 finds a strategy for solving the load balancing problem from the optimization strategy database, and finds that the current network is switched to the A5 event. Therefore, the base station 1 considers that such a scenario is corrected between the cell 1 and the cell 7 according to the policy analysis for solving the load balancing problem. The cell-specific offset can solve the problem of excessive load on the cell 1;

4. The base station 1 determines that the radio parameter of the cell 1 to be optimized is a cell-specific offset, and evaluates the range of influence of the radio parameter;

5. The base station 1 finds that the change of the wireless parameter affects the cell 7. Although the cell 7 does not belong to the base station 1, the base station 1 can obtain the basic information of the cell 7 through the interface with the base station 3, and for the wireless parameter. The revision can be negotiated by the MOBILITY CHANGE REQUEST related procedure on the X2 port between the base station 1 and the base station 3, and then the base station 1 decides to optimize the cell-specific offset of the cell 1 by itself;

6. The base station 1 selects a corresponding optimization strategy of the cell-specific offset in the optimization strategy database, and notifies the optimization parameter, the wireless parameter configuration before and after the optimization strategy application, and the cell wireless scenario to the OAM optimization evaluation module;

7. The optimization evaluation module evaluates whether the revision of the cell-specific offset causes the handover hole and whether the handover failure rate exceeds the network planning index, etc. according to the basic information of the network planning; 8. The optimization evaluation module considers that the revised cell-specific offset does not affect the handover failure rate and the coverage of the network, thus allowing cell-specific offset optimization for cell 1 and cell 7, respectively, and feeding this result back to the base station 1 ;

9. The base station 1 modifies the cell-specific offsets of the cell 1 and the cell 7 according to the optimization strategy by negotiating with the base station 3.

Embodiment 3

In the wireless networking scenario shown in FIG. 5, it is assumed that the wireless system is an LTE system, and the cell 11 controlled by the base station 4 has a late handover failure, and its neighboring cell includes the cell 3, the cell 6 and the cell 9. At this time, the radio parameter optimization process of the cell 11 is as follows:

1. The base station 4 determines that the cell 11 has a late handover failure through the RLF INDICATION, HANDOVER REPORT message and the RRC CONNECTION RE-ESTABLISHMENT message reported by the terminal on the X2 interface, and the base station 4 learns that the need is correct based on the policy analysis in the optimization policy library. The high-speed scaling factor of the cell 11 is optimized, and it is determined that the adjustment of the radio parameter affects the neighbor cell 3 and the cell 6 of the cell 11; however, the base station 4 only has an open standard interface connection with the base station 1 (ie, the base station 4 only The basic information of the cell 3 can be obtained, and the basic information of the cell 6 cannot be obtained);

2. Since the base station 4 cannot acquire only the cell 3 but cannot acquire the basic information of the cell 6, the base station 4 determines that it cannot complete the optimization of the radio parameter (high-speed scaling factor) to solve the late handover failure of the cell 11, and then the cell is The fault problem of 11 , the fault cell ID obtained by the RRC CONNECTION RE-ESTABLISHMENT message, and the measurement report information of the UE, etc., are transmitted to the OAM node together with the information related to the cell 11 that can be obtained by the base station 4, and the OAM node is notified to the cell 11 Wireless parameters are optimized;

3. After receiving the information sent by the base station 4, the OAM node finds that the fault needs to be solved by the OAM node. Therefore, the OAM node aggregates the information of each neighboring cell of the cell 11 and selects the cell from the optimization policy library. The optimization strategy that matches the late fault type (assumed) The high-speed scaling factor in the cell 11 is adjusted to 0.25), and the optimization parameter, the wireless parameter configuration before and after the optimization strategy application, and the cell wireless scenario are input to the optimization evaluation module;

4. The optimization evaluation module evaluates whether the adjustment of the high-speed scaling factor causes the handover success rate of other UEs in the network to decrease according to the basic information of the network planning;

5. The evaluation module considers that the revised parameters do not affect the handover success rate of the normal UE in the cell, and therefore allows the cell 11 and its neighboring cell 3, cell 6 to optimize their respective high-speed scaling factors, and feed this result back to each control base station. , that is, the base station 1, the base station 2, and the base station 4;

6. The base station 1, the base station 2, and the base station 4 each revise the high speed scaling factor according to the optimization strategy. The above is only the preferred embodiment of the present invention and is not intended to limit the scope of the present invention. Industrial applicability

The wireless parameter self-optimization method and system proposed by the invention, in the framework of the existing protocol standard, decides whether to optimize the wireless parameters by itself according to the amount of information available to the base station, and determines the optimization strategy when determining to optimize by itself. The OAM node is evaluated and verified. After the evaluation and verification is passed, the base station can modify the radio parameters of one or more cells according to the optimization strategy. If the base station cannot make the decision, the basic information is reported to the OAM node, and the OAM node performs the optimization decision. Subsequent steps such as evaluation and verification overcome the unreliability of purely centralized or distributed parameter optimization, improve the efficiency and reliability of system wireless parameter optimization, and flexibly respond to optimization of different wireless parameters; The OAM node's sharing of parameter optimization can effectively reduce the computational complexity of the node, and can also significantly improve the reliability of parameter optimization.

Claims

Claim

A method for wireless parameter self-optimization, characterized in that the method comprises:

The first base station selects a corresponding optimization policy according to the wireless parameter, and notifies the operation management and maintenance (OAM) node for evaluation; or the first base station notifies the OAM node to select a corresponding optimization policy according to the wireless parameter, and performs an evaluation;

The wireless parameter self-optimization method according to claim 1, wherein the first base station selects a corresponding optimization policy according to the wireless parameter, and notifies the OAM node for evaluation, including:

The wireless parameter self-optimization method according to claim 2, wherein the evaluating, by optimizing the wireless parameter according to the optimization strategy, comprises:

When the wireless parameter only affects the first cell, after the evaluation is passed, the OAM node notifies the first base station to optimize the wireless parameter of the first cell according to an optimization policy selected by the first base station;

The radio parameter not only affects the first cell but also affects the second cell, and when the first base station can acquire basic information of the second cell, after the evaluation is passed, the OAM node notifies the first base station And selecting, by the first base station and the second base station to which the second cell belongs, according to the first base station And the optimized strategy, each optimizing the wireless parameters of the first cell and the second cell.

The wireless parameter self-optimization method according to claim 2, wherein the first base station notifies the OAM node to select a corresponding optimization strategy according to the wireless parameter, and performs an evaluation, including:

The wireless parameter self-optimization method according to claim 4, wherein the evaluating is performed by optimizing the wireless parameter according to the optimization policy, including:

The radio parameter not only affects the first cell but also affects the second cell, and when the first base station cannot acquire the basic information of the second cell, after the evaluation is passed, the OAM node notifies the first base station And the second base station to which the second cell belongs is optimized for the wireless parameters of the first cell and the second cell according to an optimization policy selected by an OAM node.

The wireless parameter self-optimization method according to any one of claims 1 to 5, wherein the evaluating the optimization strategy comprises: evaluating an impact of the optimization strategy on network performance, when the evaluation result is consistent with the formulation When the network is planning indicators, the assessment is passed; otherwise, the assessment is not passed.

7. A wireless parameter self-optimizing system, the system comprising: an optimization decision module, an optimization evaluation module, and an optimization strategy library, wherein:

The optimization strategy library is used to store an optimization strategy;

The optimization decision module of the first base station is configured to determine a radio parameter that needs to be optimized in a first cell that is required by the first base station to perform radio parameter self-optimization, and is further configured to use the radio parameter from the optimization policy. Select the corresponding optimization strategy in the library and report it to the OAM node. Or informing the OAM node to select a corresponding optimization policy according to the wireless parameter; the optimization decision module located at the OAM node, after receiving the notification of the optimization decision module of the first base station, according to the wireless parameter from the Select the appropriate optimization strategy in the optimization strategy library;

The wireless parameter self-optimization system according to claim 7, wherein the optimization decision module located in the first base station is further configured to determine that the first cell under the jurisdiction of the first base station needs to be optimized. After the wireless parameter is determined, the wireless parameter is determined to have an impact on the first cell, or the wireless parameter is determined to have an impact on the second cell, and the second base station is determined, and the first base station is determined. When the basic information of the second cell is obtained, the corresponding optimization policy is selected from the optimization policy library according to the wireless parameter; and the wireless parameter configuration before and after the optimization policy, the optimization of the policy application, and the reporting of the wireless area of the cell are also used. Give the optimized evaluation module at the OAM node.

The wireless parameter self-optimization system according to claim 8, wherein the optimization evaluation module located at the OAM node is further configured to: when the wireless parameter only affects the first cell, and evaluate After being passed, the optimization decision module located at the first base station is notified to optimize the wireless parameter of the first cell according to an optimization policy;

The optimization evaluation module of the OAM node is further configured to: in addition to affecting the first cell, the radio parameter has an impact on the second cell, and the first base station can acquire basic information of the second cell. And, after the evaluation is passed, notifying the first base station, the optimization decision module located at the first base station and the optimization decision mode located at the second base station to which the second cell belongs The blocks are optimized for the wireless parameters of the first cell and the second cell according to an optimization strategy.

The wireless parameter self-optimization system according to claim 8, wherein the optimization decision module located in the first base station is further configured to determine that the wireless parameter has an influence on the first cell, and is still When the second cell generates an impact, and determines that the first base station cannot obtain the basic information of the second cell, the OAM node is notified to optimize the wireless parameters of the first cell and the second cell;

The wireless parameter self-optimization system according to claim 10, wherein the optimization evaluation module located at the OAM node is further configured to: in addition to affecting the first cell, the wireless parameter When the second cell has an impact, and the first base station is unable to acquire the basic information of the second cell, and after the evaluation is passed, notifying the optimization decision module located at the first base station and the second base station belonging to the second cell The optimization decision module optimizes the wireless parameters of the first cell and the second cell according to an optimization policy.

The wireless parameter self-optimization system according to any one of claims 7 to 11, wherein the optimization evaluation module at the OAM node is further configured to evaluate the optimization when evaluating the optimization strategy. The impact of the strategy on network performance. When the assessment results are consistent with the established network planning indicators, the assessment is passed; otherwise, the assessment fails.