WO2015096059A1 - 网络优化方法及装置 - Google Patents

网络优化方法及装置 Download PDF

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Publication number
WO2015096059A1
WO2015096059A1 PCT/CN2013/090414 CN2013090414W WO2015096059A1 WO 2015096059 A1 WO2015096059 A1 WO 2015096059A1 CN 2013090414 W CN2013090414 W CN 2013090414W WO 2015096059 A1 WO2015096059 A1 WO 2015096059A1
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Prior art keywords
root cause
kpi
network
data
preset
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PCT/CN2013/090414
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English (en)
French (fr)
Inventor
汤斌淞
宋平
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华为技术有限公司
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Priority to CN201380022905.2A priority Critical patent/CN104995938A/zh
Priority to PCT/CN2013/090414 priority patent/WO2015096059A1/zh
Publication of WO2015096059A1 publication Critical patent/WO2015096059A1/zh

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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W24/00Supervisory, monitoring or testing arrangements
    • H04W24/02Arrangements for optimising operational condition

Definitions

  • Embodiments of the present invention relate to a wireless communication technology, and in particular, to a network optimization method and apparatus.
  • network optimization is a vital task, and is one of the main ways for operators to fully utilize network resources and provide better services to users.
  • the success rate and the radio resource control are established mainly through the current network handover success rate (HOF) and Enhanced Radio Access Bearer (E-RAB).
  • the five key performance indicators (KPIs) of success rate, RRC reestablishment success rate and Call Drop rate are used to optimize the current network.
  • the HOF success rate As an example, when the current KPI of the HOF success rate of the network (for example, 98%) is lower than the threshold of the preset HOF success rate (for example, 99.5%), the root cause of the HOF success rate reduction is found. , to solve the root cause and achieve the purpose of network optimization.
  • the threshold of the preset HOF success rate for example, 99.5%
  • the network of the area is manually checked to find the root cause of the drop.
  • improper mobility parameter setting may result in a decrease in the HOF, such as Cell Individual Offset (CIO). If the CIO is too large, it will lead to early switching. If the CIO is too small, it will lead to too late switching, which will lead to a decrease in the current KPI of the HOF success rate. Or, at some point, the operator's S1 link will be broken due to congestion or failure, and the S1 chain will be broken.
  • CIO Cell Individual Offset
  • the road refers to the link using the S1 interface, and the S1 interface is used for the communication interface between the base station and the packet core network.
  • the stream control transmission protocol (SCTP) of the S1 is stopped by the heart beat (Heart Beat).
  • Interface-South (Operation and Maintenance (OAM) system) the OAM system generates an alarm that the HOF KPI drops, causing the operator to arrange personnel to overhaul the fault; or, the user equipment itself, etc. For example. Therefore, when the current KPI of the H0F success rate is reduced, it is necessary to manually observe and eliminate the link failure or other faults, and then investigate whether the mobility parameter is set properly. If it is unreasonable, the size of the mobility parameter needs to be manually adjusted; If the mobility parameter is set properly, manual work is required. Analyze other possible causes.
  • Embodiments of the present invention provide a network optimization method and apparatus to improve network optimization efficiency.
  • a first aspect of the embodiments of the present invention provides a network optimization apparatus, including:
  • a determining module configured to determine that a current key performance indicator of the network in the area covered by the base station is lower than a preset KPI threshold
  • a processing module configured to determine, by analyzing network environment configuration data and user reporting data, a root cause that the current KPI is lower than a preset KPI threshold;
  • an optimization module configured to optimize a network in an area covered by the base station according to a root cause that the current KPI is lower than a preset KPI threshold.
  • the processing module is specifically configured to: when a degree of network fluctuation in an area covered by the base station is less than a first preset value, or a network form complexity of the network is less than The second preset value, or the number of users reporting the data in the network is greater than the third preset value, and the processing module analyzes the network environment configuration data and the user reported data by using a closed loop analysis manner, and determines that the current KPI is lower than the preset.
  • the root cause of the KPI threshold or, when the degree of network fluctuation in the area covered by the base station is greater than the first preset value, or the network configuration complexity of the network is greater than the second preset value, or the data is reported in the network
  • the number of users is less than the third preset value
  • the processing module analyzes the network environment configuration data and the user report data by using an open loop analysis manner, and determines that the current KPI is lower than the root cause of the preset KPI threshold.
  • the processing module is specifically configured to use the obtained network environment configuration data stored by the base station and the current user report data as a first data source;
  • a data source is matched with each of the root causes of the first KPI root cause set, and the root with the highest matching degree is determined because the current KPI is lower than the root cause of the preset KPI threshold;
  • the first KPI root cause set includes at least one of the following root causes:
  • Network switching capability root cause Neighborhood root cause abnormality management class root cause
  • the terminal runs an abnormal root cause
  • the processing module is specifically configured to use the acquired network environment configuration data stored by the base station and the current user report data as the first data source; according to the first KPI
  • the first data source is matched with the various root causes of the first KPI root cause set according to the order of priority of each root cause in the set, and the first data is determined first and the first data.
  • the first mobile KPI root cause set includes at least one of the following root causes:
  • the terminal runs an abnormal root cause
  • the processing module is specifically configured to use the network environment configuration data stored by the base station, current The user reports the data, the user reports the data in the first preset time in the future, minimizes the drone test MDT report data, and the user reports the data in the second preset time stored in the operation support subsystem OSS or the enhanced coordinator eCor.
  • a second data source matching the root causes of the second data source and the second KPI root cause set one by one to determine a root with the highest matching degree because the current KPI is lower than a root cause of the preset KPI threshold;
  • the second KPI root cause set includes at least one of the following root causes:
  • GCI does not have a configuration error sub-root cause
  • a second aspect of the embodiments of the present invention provides a network optimization method, including:
  • the network optimization device determines that the current key performance indicator KPI of the network in the area covered by the base station is lower than the preset KPI threshold
  • the network optimization device determines the root cause of the current KPI being lower than a preset KPI threshold by analyzing network environment configuration data and user reporting data;
  • the network optimization apparatus optimizes a network in an area covered by the base station according to a root cause that the current KPI is lower than a preset KPI threshold.
  • the network optimization device determines, by analyzing the network environment configuration data and the user reporting data, the root cause of the current KPI being lower than a preset KPI threshold, including:
  • the network fluctuation degree in the area covered by the base station is smaller than the first preset value, or the network configuration complexity of the network is less than the second preset value, or the number of users reporting the data in the network is greater than the third preset value.
  • the network optimization device analyzes the network environment configuration data and the user report data by using a closed loop analysis manner, and determines that the current KPI is lower than a root cause of the preset KPI threshold; or
  • the network fluctuation degree in the area covered by the base station is greater than the first preset value, or the network configuration complexity of the network is greater than the second preset value, or the number of users reporting the data in the network is less than the third preset value.
  • the network optimization device analyzes the network environment configuration data and the user report data by using an open loop analysis manner, and determines that the current KPI is lower than a root cause of the preset KPI threshold.
  • the network optimization apparatus uses a closed loop analysis manner to analyze network environment configuration data and user report data, and determines the current
  • the KPI is below the root cause of the default KPI threshold, including:
  • the network optimization device uses the acquired network environment configuration data stored by the base station and the current user report data as the first data source;
  • the network optimization device matches the first data source with each type of root cause in the first KPI root cause set to determine a root type with the highest matching degree because the current KPI is lower than the preset KPI threshold. Root cause
  • the first KPI root cause set includes at least one of the following root causes:
  • the terminal runs an abnormal root cause
  • the network optimization apparatus uses a closed loop analysis manner to analyze the network environment configuration data and the user report data, and determines that the current KPI is lower than a root cause of the preset KPI threshold, including :
  • the network optimization device uses the acquired network environment configuration data stored by the base station and the current user report data as the first data source;
  • the network optimization device matches the first data source with each root cause of the first KPI root cause set according to a priority of each root cause in the first KPI root cause set. Determining a type of root that first matches the first data source because the current KPI is lower than a root cause of a preset KPI threshold;
  • the first mobile KPI root cause set includes at least one of the following root causes:
  • the terminal runs an abnormal root cause
  • the network optimization apparatus uses an open loop analysis manner to analyze network environment configuration data and user report data. And determining that the current KPI is lower than a root cause of the preset KPI threshold, including:
  • the network optimization device stores the network environment configuration data stored by the base station, the current user report data, the user reports data in the first preset time, minimizes the road test MDT report data, and the operation support subsystem OSS or enhanced coordination.
  • the user reports data in the second preset time stored in the eCor as a second data source;
  • the network optimization device matches the root causes of the second data source and the second KPI root cause set one by one to determine the root with the highest matching degree because the current KPI is lower than the preset KPI. Root cause of the threshold;
  • the second KPI root cause set includes at least one of the following root causes:
  • GCI does not have a configuration error sub-root cause
  • the network optimization method and device provided by the embodiment of the present invention, after determining that the current KPI of the network in the area covered by the base station is lower than the preset KPI threshold, the network optimization device determines the current situation by analyzing the network environment configuration data and the data reported by the user.
  • the KPI is lower than the root cause of the preset KPI threshold, and the corresponding network is optimized for the determined root cause, so that the network optimization device can automatically and quickly analyze the root cause of the network KPI reduction and improve the network optimization efficiency.
  • Embodiment 1 is a flowchart of Embodiment 1 of a network optimization method according to the present invention
  • FIG. 2 is a network architecture diagram applicable to the network optimization method of the present invention.
  • Embodiment 3 is a schematic structural diagram of Embodiment 1 of a network optimization apparatus according to the present invention.
  • FIG. 4 is a schematic structural diagram of Embodiment 2 of a network optimization apparatus according to the present invention.
  • the technical solutions in the embodiments of the present invention are clearly and completely described in the following with reference to the accompanying drawings in the embodiments of the present invention.
  • the embodiments are a part of the embodiments of the invention, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present invention without creative efforts are within the scope of the present invention.
  • FIG. 1 is a flowchart of Embodiment 1 of a network optimization method according to the present invention.
  • the executor of the embodiment is a network optimization device. Specifically, the embodiment includes the following steps: S101: The network optimization device determines that the current KPI of the network in the coverage area is lower than a preset KPI threshold.
  • the following five KPIs of the current network are mainly concerned: handover success rate KPI, E-RAB establishment success rate KPI, RRC establishment success rate KPI, RRC reconstruction success rate KPK call drop rate KPI. Therefore, when the current ⁇ of the network is specifically the handover success rate, the preset threshold is the preset threshold for the handover success rate; or, the current ⁇ of the network is specifically established for the enhanced radio access bearer E-RAB. Rate, correspondingly, the preset threshold is the default threshold of the E-RAB success rate; or, the current state of the network is specifically the RRC establishment success rate of the RRC, and correspondingly, the preset threshold is RRC established successfully.
  • the default threshold of the rate is; or, the current frame of the network is specifically the RRC reestablishment success rate, and correspondingly, the preset threshold is the default threshold of the RRC reestablishment success rate; or, the current frame of the network is specifically the call drop rate.
  • the preset threshold is the default threshold of the dropped call rate.
  • other ⁇ can also be included, and the present invention does not limit this.
  • the network optimization apparatus determines that the current ⁇ of the network in the coverage area is lower than the preset threshold, including but not limited to the following manners:
  • the network optimization device can determine whether the current state of the network in the area covered by the base station is lower than a preset threshold in real time, periodically, or event-triggered. For example, a switch can be set on the network optimization device, when the operator presses the switch. The triggering network optimization device determines whether the current state of the network in the area covered by the base station is lower than a preset threshold, and determines that the current network of the coverage area is lower than the preset threshold.
  • the network optimization device determines that the current network in the covered area is not lower than the preset threshold, the default current network status is better, and no optimization is needed.
  • the network optimization device determines that the current network of the coverage area is lower than the preset threshold, the network needs to be optimized, and S102 is performed.
  • the network optimization device determines the root cause of the current KPI lower than the preset KPI threshold by analyzing the network environment configuration data and the user reporting data.
  • the root cause refers to the earliest reason that the current KPI is lower than the preset KPI threshold.
  • the network optimization device determines the root cause of the current KPI lower than the preset KPI threshold by analyzing the network environment configuration data and the user reporting data, and includes two analysis modes, namely, a closed loop analysis mode and an open loop analysis mode.
  • a closed loop analysis mode when the degree of network fluctuation in the area covered by the base station is less than the first preset value (that is, the network is relatively stable), or the network form complexity of the network is less than the second preset value (that is, the network form is relatively simple), or, in the network
  • the number of users of the reported user data is greater than the third preset value (that is, all or most of the user equipments in the coverage area of the base station simultaneously report data), and the network optimization apparatus analyzes the network environment configuration data and the user report data by using a closed loop analysis manner. Determines the root cause of the current KPI below the preset KPI threshold.
  • the two implementation methods are as follows: First, the obtained network environment configuration data stored by the base station and the current user report data are used as the first a data source, where the network environment configuration data stored by the base station includes: configuration parameters of the base station, etc.; the current user report data includes: a measurement report (MR) reported by the user at the current time point, where the received signal power and Receive signal quality. Then, the first data source is matched with each root cause in the first KPI root set one by one, and the root with the highest matching degree is determined because the current KPI is lower than the root cause of the preset KPI threshold.
  • MR measurement report
  • the first KPI root cause set includes at least one of the following root causes: a network switching capability class root cause; a neighboring zone abnormal management class root cause; a radio frequency (RF) coverage class root cause; a network abnormal operation class root cause; Terminal operation exception class root cause; different system switch type root cause.
  • RF radio frequency
  • the first KPI root cause set includes an optimized switch switch sub-root in the root cause of the network handover capability class, and configures Long Term Evolution (LTE), inter-frequency handover capability sub-root cause, and handover parameter configuration.
  • LTE Long Term Evolution
  • subclass root causes or a combination thereof. It also includes the optimal handover measurement report in the root cause of the abnormality management class of the neighboring area.
  • Sub-root cause, optimize Global Cell Identity (GCI), configure the root cause of the entire network uniquely, and optimize one type or combination of the root cause of the neighboring over-provision problem.
  • GCI Global Cell Identity
  • the terminal switching request in the root class of the exception class delays the long root cause, the request rejection causes the delay to be too long, the root cause is delayed, the terminal different system capability does not support the root cause, and the terminal moves the speed root.
  • One or a combination of the sub-root causes of the abnormality of the terminal. It also contains the A2 threshold problem class root cause, the B1 threshold problem class root cause, the A1 threshold problem class root cause, the A3 threshold problem class root cause, or a combination thereof.
  • the matching degree between the first data source and each type of root cause is obtained, and the one with the highest matching degree is determined.
  • the priority order of the KPI and each root cause may be established according to the matching degree between the first data source and each type of root cause, for example, when The network optimization apparatus determines that the RRC establishment success rate KPI of the current network is lower than the preset KPI threshold, and determines that the RRC establishment success rate KPI is lower than the preset KPI threshold because the neighboring area abnormal management type root cause determines that the RRC establishment is successful.
  • the rate KPI has the highest priority corresponding to the root cause of the abnormality management class of the neighboring area. If the closed-loop analysis method is used to analyze the root cause of the RRC establishment success rate KPI lower than the preset KPI threshold, the first data source and the neighboring area are firstly used. The root of the exception management class is matched, that is, the following second implementation is adopted.
  • the second implementation manner is specifically: the network optimization device uses the acquired network environment configuration data stored by the base station and the current user report data as the first data source; according to the priority of each root cause in the first KPI root cause set The high-to-low order is to match the first data source to the root causes of the first KPI root cause set, and determine the first type of root that matches the first data source first because the current KPI is lower than the preset KPI The root cause of the threshold.
  • the network environment configuration data, the current user report data, and the first KPI root cause set are the same as the first KPI root cause set of the first implementation manner.
  • the closed-loop analysis method is used for root cause analysis.
  • the data is the data reported by the current user and the network environment configuration data stored in the base station, so that the analysis efficiency can be improved; if the first data source is matched with the first data source according to the priority of each root cause in the first KPI root cause set, The first type of root that matches the first data source is able to further improve the analysis efficiency because the current KPI is lower than the root cause of the preset KPI threshold.
  • the degree of network fluctuation in the area covered by the base station is greater than the first preset value (that is, the network is unstable) Or, the network configuration complexity of the network is greater than a second preset value (that is, the network configuration is complex), or the number of users reporting data in the network is less than a third preset value (ie, a small area within the coverage area of the base station) Some user equipments report data at the same time.
  • the network optimization device analyzes the network environment configuration data and the user reports data by using an open loop analysis method to determine the root cause of the current KPI being lower than the preset KPI threshold.
  • the difference between the open loop analysis mode and the closed loop analysis mode is that the data to be analyzed in the open loop analysis mode includes the second preset stored in the OSS or the eCor in addition to the network environment configuration data and the current time user reporting data.
  • MDT Minimizing Drive Test
  • the network optimization device uses the open loop analysis method to analyze the network environment configuration data and the user reports the data, and determines the root cause of the current KPI lower than the preset KPI threshold.
  • the network optimization device stores the network environment configuration data of the base station and the current user. Reporting data, user reported data in the first preset time, MDT reporting data, and user reported data in the second preset time stored in the OSS or eCor as the second data source; the second data source and the second KPI root Because the root causes of the set are matched one by one, the root with the highest matching degree is determined because the current KPI is lower than the root cause of the preset KPI threshold.
  • the network environment configuration data includes: configuration parameters of the base station, etc.; the user reporting data includes: including received signal power and received signal quality.
  • the MDT report data includes location information and Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and the like.
  • the second KPI root cause set includes at least one of the following root causes: configuring a generic mobile communication system different system switching capability root cause; configuring a global mobile communication system GSM different system switching capability class root cause; GCI does not have a configuration error subroot cause ; RF RF coverage root cause.
  • the network optimization device can wait for more MRs, MDT reports, etc. reported by more user equipments by means of algorithm stop, etc., and then analyze the more user reports and network configuration environment data sources to determine the root cause.
  • the root cause analysis is performed by using an open loop analysis method, and the data analyzed by the open loop analysis mode includes the network optimization device storing the base station.
  • the network optimization device optimizes the network in the area covered by the base station according to the root cause that the current KPI is lower than the preset KPI threshold.
  • the network optimization device performs the corresponding network optimization for the root cause (ie, the earliest cause) of the KPI decline.
  • the network optimization apparatus determines that the current KPI is lower than the preset KPI threshold by analyzing the network environment configuration data and the data reported by the user.
  • the root cause is to optimize the network for the determined root cause, so that the network optimization device can automatically and quickly analyze the root cause of the network KPI reduction and improve the network optimization efficiency.
  • FIG. 2 is a network architecture diagram applicable to the network optimization method of the present invention.
  • there are two base stations in the network and there are a cell 1, a cell 2, and a cell 3 under the base station 1, and a cell 4, a cell 5, and a cell 6 in the base station 2 are taken as an example.
  • an ellipse filled with oblique lines indicates an area covered by the base station 1
  • an unfilled ellipse indicates an area covered by the base station 2.
  • Each base station is connected to a cell under its jurisdiction through an internal interface, as shown in the figure.
  • the interface between the base stations and the eCor is an X2 interface, such as a virtual X2 interface or a pseudo X2 interface, which is used to manage or coordinate radio resources between the base stations, and may be referred to as a management interface, as shown in the figure.
  • the black solid line is shown; the interface between each base station and the OSS is the northbound interface itf-N, as shown by the thin black dotted line in the figure.
  • each base station and the Mobility Management Entity (MME) are also connected through an internal interface (not shown), such as an S1 interface; each base station is connected through an X2 interface (not shown) .
  • a network optimization device (not shown) may be provided at the base station 1, base station 2, eCor or OSS, and the eCor or OSS may be located in an area covered by any of the base stations or outside the area covered by any of the base stations.
  • the network optimization device analyzes the MR, MDT, and the configuration parameters of the base station, which are reported by the user equipment in the slant-filled ellipse at the current time point or the current time period, Determine the root cause of the current KPI below the preset KPI threshold.
  • the KPI of the current network is decreased, and the network optimization apparatus uses the closed-loop analysis method to analyze the network environment configuration data and the user reported data as an example for description.
  • the network optimization apparatus analyzes the MR, the MDT, and the configuration parameters of the base station reported by the user at the current time, and each of the first KPI root cause sets.
  • the roots are matched one by one to determine the specific root cause. For example, when the RSRP reported by all or most of the user equipments in the MR and MDT reports is less than 120dBm, the root is determined because of the root cause of the RF coverage, and the root cause of the switch area coverage vulnerability is abnormal.
  • the network optimization device does not need to match the root causes of the first KPI root cause set one by one, but preferentially matches the RF coverage class root cause, and determines that the call drop rate KPI is lower than the preset. The reason for the KPI.
  • the network optimization device stops the algorithm, waits for more user equipments in the slanted line to fill the measurement report MR reported by the internal interface, minimizes the road test MDT report, and obtains a large amount of data. And then analyze the data to determine the root cause.
  • the network optimization device may also obtain historical data stored in the OSS or the eCor through a management interface between the base station and the eCor, a northbound interface between the base station and the operation support subsystem OSS, and the like, such as the user equipment in the coverage area of the base station.
  • the MR, MDT report, etc. reported to the OSS or eCor before the time point, and then analyze the large amount of data to determine the root cause.
  • the KPI of the handover success rate of the current network is decreased, and the network optimization apparatus uses the open loop analysis method to analyze the network environment configuration data and the user report data as an example.
  • the handover fails due to the absence of the new PCI on the neighbor base station.
  • the network optimization apparatus determines that the handover success rate KPI is lower than the preset KPI threshold, the network optimization apparatus stops the algorithm, waits for more user equipments to report the MR, MDT report data, etc., thereby obtaining a large amount of data.
  • the MRS and the MDT reported by the user before the current time point are obtained from the OSS or the eCor, so that a large amount of data is obtained, and then the data is analyzed to indicate that the base station is far away from the neighboring base station, and cannot form a neighboring cell, thereby determining a KPI that causes the handover to fail.
  • the root of the decline is due to the coverage of the root cause of the RF coverage class root cause.
  • the network optimization can be performed as follows: For an antenna with a directional angle (Azimuth), the downtilt of the cross-sectional direction is depressed. , thereby reducing the coverage; for omnidirectional antennas, reducing the transmission power to reduce the coverage.
  • FIG. 3 is a schematic structural diagram of Embodiment 1 of a network optimization apparatus according to the present invention.
  • the apparatus in this embodiment includes a determining module 301, a processing module 302, and an optimization module 303, where the determining module 301 is configured to determine a coverage of the base station.
  • the current key performance indicator KPI of the intra-area network is lower than the preset KPI threshold;
  • the processing module 302 is configured to determine the root cause of the current KPI being lower than the preset KPI threshold by analyzing the network environment configuration data and the user reporting data;
  • the network in the area covered by the foregoing base station is optimized according to the root cause that the current KPI is lower than the preset KPI threshold.
  • the network fluctuation degree in the area covered by the base station is smaller than the first preset value, or the network configuration complexity of the network is less than the second preset value, or the number of users reporting the data in the network is greater than the first
  • the three processing values are used to analyze the network environment configuration data and the user reporting data by using a closed loop analysis manner to determine the root cause of the current KPI being lower than the preset KPI threshold; or
  • the processing module 302 is specifically configured to analyze the network environment configuration data and the user reported data by using an open loop analysis manner to determine the root cause of the current KPI being lower than the preset KPI threshold.
  • the processing module 302 is specifically configured to use the acquired network environment configuration data stored by the base station and the current user report data as the first data source; and the first data source and the first KPI root cause set.
  • the root causes are matched one by one, and the root with the highest matching degree is determined because the current KPI is lower than the root cause of the preset KPI threshold;
  • the first KPI root cause set includes at least one of the following root causes:
  • Root cause of network switching capability root cause of abnormality management in neighboring area; root cause of RF RF coverage; root cause of network abnormal operation; root cause of abnormal operation of terminal; root cause of different system switching.
  • the processing module 302 is specifically configured to use the acquired base station to store the network.
  • the environment configuration data and the current user report data are used as the first data source; the first data source and the first KPI root are arranged according to the priority of each root cause in the first KPI root cause set from high to low Determining the root cause of the first data source that matches the first data source because of the matching of the root causes of the set; because the current KPI is lower than the root cause of the preset KPI threshold;
  • the first KPI root cause set includes at least one of the following root causes: a network switching capability class root cause; a neighboring zone abnormal management class root cause; a radio frequency RF coverage class root cause; a network abnormal operation class root cause; and a terminal running abnormal class Root cause; different system switching root cause.
  • the processing module 302 is specifically configured to use the network environment configuration data stored by the base station, the current user report data, the user report data in the first preset time, the MDT report data, and the operation support subsystem OSS or enhanced.
  • the user reports data in the second preset time stored in the type coordinator eCor as the second data source; and matches the root causes of the second data source and the second KPI root cause set one by one to determine the matching degree. The highest root because the current KPI is lower than the root cause of the default KPI threshold;
  • the second KPI root cause set includes at least one of the following root causes: configuring a generic mobile communication system different system switching capability root cause; configuring a global mobile communication system GSM different system switching capability class root cause; GCI does not exist configuration False subroot cause; RF RF coverage root cause.
  • the device of the above embodiment is corresponding to the technical solution that can be used to implement the method embodiment shown in FIG. 1. The implementation principle and the technical effect are similar, and details are not described herein again.
  • FIG. 4 is a schematic structural diagram of Embodiment 2 of a network optimization apparatus according to the present invention.
  • the apparatus of the present implementation includes: a memory 411, a processor 412, and a network interface 413, where the memory 411 is configured to store a current KPI and a preset KPI threshold of an intra-area network covered by the base station, and the processor 412 The current KPI in the area for determining the coverage of the base station is lower than the preset KPI threshold.
  • the processor 412 determines that the current KPI is lower than the preset KPI threshold, if the network fluctuation degree in the area covered by the base station is less than the first preset value, or The network configuration complexity of the network is less than a second preset value, or the number of users reporting data in the network is greater than a third preset value, and the network interface 413 sends an analysis root cause indication to the base station, so that the base station analyzes the network.
  • the environment configuration data and the user report data determine the root cause of the current KPI lower than the preset KPI threshold. After the base station determines the root cause, the base station reports the determined root cause to the network interface 413 of the network optimization apparatus.
  • the processor 412 determines the root cause of the current KPI being lower than the preset KPI threshold by analyzing the network environment configuration data and the user reporting data; the processor 412 formulates an optimization policy according to the root cause determined by the network or the network interface 413 to receive the root cause reported by the base station, The network interface 413 sends an optimization policy to the base station, and the base station optimizes the network in the area covered by the base station according to the above optimization strategy.
  • the network interface 413 may be a northbound interface (itf-N) or a private interface.
  • the processor is specifically configured to analyze the network environment configuration data and the user reported data by using an open loop analysis manner, and determine that the current KPI is lower than a root cause of the preset KPI threshold.
  • the processor is specifically configured to store the network environment configuration data stored by the base station, the current user report data, the user report data in the first preset time, the MDT report data, and the second history stored in the OSS or eCor.
  • the user reports the data as the second data source in a preset time; the roots of the second data source and the second KPI root cause set are matched one by one, and the root with the highest matching degree is determined because the current KPI is low.
  • the device in the foregoing embodiment is used to perform the method embodiment shown in FIG. 1.
  • the implementation principle and technical effects are similar, and details are not described herein again.

Abstract

本发明实施例提供一种网络优化方法及装置,网络优化装置在确定基站覆盖的区域内网络的当前KPI低于预设KPI门限条件下,通过分析网络环境配置数据以及用户上报的数据,确定导致当前KPI低于预设KPI门限的根因,针对所确定的根因,进行相应的网络优化,从而实现,网络优化装置自动、快速分析出网络KPI降低的根因,提高网络优化效率。

Description

网络优化方法及装置 技术领域
本发明实施例涉及无线通信技术, 尤其涉及一种网络优化方法及装置。 背景技术 移动通信网络中, 网络优化是一项至关重要的工作, 是运营商充分利用 网络资源、 为用户提供更好服务的主要途径之一。 网络优化过程中, 主要通 过当前网络的切换成功率 (Handover ratio, HOF ) 、 增强型无线接入承载 (Enhanced-Radio Access Bearer , E-RAB)建立成功率、无线资源控制(Radio Resource Control, RRC) 建立成功率、 RRC重建成功率和掉话 (Call Drop) 率的 5项关键性能指标(Key Performance Indicator, KPI) , 来对当前网络进 行优化。以 HOF成功率为例, 当网络的 HOF成功率的当前 KPI (比如, 98%) 低于预设的 HOF 成功率的 ΚΡΙ (比如, 99.5%) 门限时, 查找导致 HOF成功 率降低的根因, 解决根因从而达到网络优化的目的。
现有技术中, 当某一区域的网络的某项 ΚΡΙ降低时, 对该区域的网络进 行人工排查以查找导致 ΚΡΙ下降的根因。 以 HOF成功率的当前 ΚΡΙ降低为 例, 导致 HOF成功率的当前 ΚΡΙ降低的原因可能有多种:移动性参数设置不 当会导致 HOF的 ΚΡΙ下降, 如小区测量差值(Cell Individual offset, CIO) , CIO过大会导致过早切换, CIO过小会导致过晚切换, 进而导致 HOF成功率 的当前 KPI降低;或者,某一时刻由于拥塞或故障等使得运营商的 S1链路断 链, S1链路是指采用 S1接口的链路, S1接口是用于基站与分组核心网之间 的通讯接口, S1的流控制传输协议 ( Stream Control Transmission Protocol, SCTP) 心跳 (Heart Beat) 停止, 通过南向接口 (Interface- South) 通知操作 与维护 (Operation and Maintenance, OAM) 系统, OAM系统产生 HOF KPI 下降的告警, 使得运营商安排人员检修故障; 或者, 用户设备本身的问题等, 此处不一一例举。 因此, 当 H0F成功率的当前 KPI降低时, 需要人工观察和 排除链路故障或是其他故障, 随后调研移动性参数是否设置合理, 若不合理, 则需要人工调整移动性参数的大小等; 若移动性参数设置合理, 则需要人工 分析其他可能的原因。
然而, 导致上述各项 KPI降低的原因错综复杂, 包罗万象, 现有技术通 过人工分析 KPI降低的原因进行网络优化, 由于人工分析效率较低, 从而导 致网络优化效率较低。 发明内容 本发明实施例提供一种网络优化方法及装置, 以提高网络优化效率。 本发明实施例第一方面提供一种网络优化装置, 包括:
确定模块, 用于确定基站覆盖的区域内网络的当前关键性能指标 KPI 低于预设 KPI门限;
处理模块, 用于通过分析网络环境配置数据以及用户上报数据, 确定 所述当前 KPI低于预设 KPI门限的根因;
优化模块, 用于根据所述当前 KPI低于预设 KPI门限的根因, 对所述 基站覆盖的区域内的网络进行优化。
结合第一方面, 在第一种可能的实现方式中, 所述处理模块具体用于 当基站覆盖的区域内的网络波动程度小于第一预设值, 或者所述网络的网 络形态复杂度小于第二预设值, 或者, 所述网络中上报数据的用户数量大 于第三预设值, 所述处理模块采用闭环分析方式分析网络环境配置数据以 及用户上报数据, 确定所述当前 KPI低于预设 KPI门限的根因; 或者, 当 基站覆盖的区域内的网络波动程度大于第一预设值, 或者所述网络的网络 形态复杂度大于第二预设值, 或者, 所述网络中上报数据的用户数量小于 第三预设值, 所述处理模块采用开环分析方式分析网络环境配置数据以及 用户上报数据, 确定所述当前 KPI低于预设 KPI门限的根因。
结合第一方面, 在第二种可能的实现方式中, 所述处理模块具体用于 把获取的所述基站存储的网络环境配置数据以及当前的用户上报数据作 为第一数据源;将所述第一数据源与第一 KPI根因集合中的各类根因逐个 进行匹配, 确定匹配度最高的一类根因为所述当前 KPI低于所述预设 KPI 门限的根因;
其中, 所述第一 KPI根因集合包括如下至少一种根因:
网络切换能力类根因; 邻区异常管理类根因;
射频 RF覆盖类根因;
网络异常运行类根因;
终端运行异常类根因;
异系统切换类根因。
结合第一方面, 在第三种可能的实现方式中, 所述处理模块具体用于 把获取的所述基站存储的网络环境配置数据以及当前的用户上报数据作 为第一数据源;按照第一 KPI根因集合中的各类根因的优先级从高到低的 顺序, 将第一数据源与所述第一 KPI根因集合的各类根因进行匹配, 确定 最先与所述第一数据源相匹配的一类根因为所述当前 KPI 低于预设 KPI 门限的根因;
其中, 所述第一移动 KPI根因集合包括如下至少一种根因:
网络切换能力类根因;
邻区异常管理类根因;
射频 RF覆盖类根因;
网络异常运行类根因;
终端运行异常类根因;
异系统切换类根因。
结合第一种至第三种可能的实现方式中任一种可能的实现方式, 在第 四种可能的实现方式中, 所述处理模块具体用于把所述基站存储的网络环 境配置数据、 当前的用户上报数据、 未来第一预设时间内用户上报数据、 最小化路测 MDT上报数据以及操作支撑子系统 OSS或增强型协调器 eCor 中存储的历史第二预设时间内用户上报数据, 作为第二数据源; 将所述第 二数据源与第二 KPI根因集合中的各类根因逐个进行匹配,确定匹配度最 高的根因为所述当前 KPI低于预设 KPI门限的根因;
其中, 所述第二 KPI根因集合包含如下至少一种根因:
配置通用移动通信系统异系统切换能力类根因;
配置全球移动通信系统 GSM异系统切换能力类子根因;
GCI不存在配置错误子根因;
射频 RF覆盖类根因。 本发明实施例第二方面提供一种网络优化方法, 包括:
网络优化装置确定基站覆盖的区域内网络的当前关键性能指标 KPI 低于预设 KPI门限;
所述网络优化装置通过分析网络环境配置数据以及用户上报数据, 确 定所述当前 KPI低于预设 KPI门限的根因;
所述网络优化装置根据所述当前 KPI低于预设 KPI门限的根因,对所 述基站覆盖的区域内的网络进行优化。
结合第二方面, 在第一种可能的实现方式中, 所述网络优化装置通过 分析网络环境配置数据以及用户上报数据, 确定所述当前 KPI 低于预设 KPI门限的根因, 包括:
当基站覆盖的区域内的网络波动程度小于第一预设值, 或者所述网络 的网络形态复杂度小于第二预设值, 或者, 所述网络中上报数据的用户数 量大于第三预设值, 所述网络优化装置采用闭环分析方式分析网络环境配 置数据以及用户上报数据, 确定所述当前 KPI低于预设 KPI门限的根因; 或者,
当基站覆盖的区域内的网络波动程度大于第一预设值, 或者所述网络 的网络形态复杂度大于第二预设值, 或者, 所述网络中上报数据的用户数 量小于第三预设值, 所述网络优化装置采用开环分析方式分析网络环境配 置数据以及用户上报数据, 确定所述当前 KPI低于预设 KPI门限的根因。
结合第二方面, 在第二种可能的实现方式中, 所述网络优化装置采用 闭环分析方式分析网络环境配置数据以及用户上报数据, 确定所述当前
KPI低于预设 KPI门限的根因, 包括:
所述网络优化装置把获取的所述基站存储的网络环境配置数据以及 当前的用户上报数据作为第一数据源;
所述网络优化装置将所述第一数据源与第一 KPI 根因集合中的各类 根因逐个进行匹配,确定匹配度最高的一类根因为所述当前 KPI低于所述 预设 KPI门限的根因;
其中, 所述第一 KPI根因集合包括如下至少一种根因:
网络切换能力类根因;
邻区异常管理类根因; 射频 RF覆盖类根因;
网络异常运行类根因;
终端运行异常类根因;
异系统切换类根因。
结合第二方面, 在第三种可能的实现方式中, 所述网络优化装置采用 闭环分析方式分析网络环境配置数据以及用户上报数据, 确定所述当前 KPI低于预设 KPI门限的根因, 包括:
所述网络优化装置把获取的所述基站存储的网络环境配置数据以及 当前的用户上报数据作为第一数据源;
所述网络优化装置按照第一 KPI 根因集合中的各类根因的优先级从 高到低的顺序,将第一数据源与所述第一 KPI根因集合的各类根因进行匹 配,确定最先与所述第一数据源相匹配的一类根因为所述当前 KPI低于预 设 KPI门限的根因;
其中, 所述第一移动 KPI根因集合包括如下至少一种根因:
网络切换能力类根因;
邻区异常管理类根因;
射频 RF覆盖类根因;
网络异常运行类根因;
终端运行异常类根因;
异系统切换类根因。
结合第一种至第三种可能的实现方式中任一种可能的实现方式, 在第 四种可能的实现方式中, 所述网络优化装置采用开环分析方式分析网络环 境配置数据以及用户上报数据,确定所述当前 KPI低于预设 KPI门限的根 因, 包括:
所述网络优化装置把所述基站存储的网络环境配置数据、 当前的用户 上报数据、 未来第一预设时间内用户上报数据、 最小化路测 MDT上报数 据以及操作支撑子系统 OSS或增强型协调器 eCor中存储的历史第二预设 时间内用户上报数据, 作为第二数据源;
所述网络优化装置将所述第二数据源与第二 KPI 根因集合中的各类 根因逐个进行匹配, 确定匹配度最高的根因为所述当前 KPI低于预设 KPI 门限的根因;
其中, 所述第二 KPI根因集合包含如下至少一种根因:
配置通用移动通信系统异系统切换能力类根因;
配置全球移动通信系统 GSM异系统切换能力类子根因;
GCI不存在配置错误子根因;
射频 RF覆盖类根因。
本发明实施例提供的网络优化方法及装置, 网络优化装置在确定基站 覆盖的区域内网络的当前 KPI低于预设 KPI门限条件下,通过分析网络环 境配置数据以及用户上报的数据,确定导致当前 KPI低于预设 KPI门限的 根因, 针对所确定的根因, 进行相应的网络优化, 从而实现网络优化装置 自动、 快速分析出网络 KPI降低的根因, 提高网络优化效率。 附图说明 为了更清楚地说明本发明实施例或现有技术中的技术方案, 下面将对实 施例或现有技术描述中所需要使用的附图作简单地介绍, 显而易见地, 下面 描述中的附图仅仅是本发明的一些实施例, 对于本领域普通技术人员来讲, 在不付出创造性劳动性的前提下, 还可以根据这些附图获得其他的附图。
图 1为本发明网络优化方法实施例一的流程图;
图 2为本发明网络优化方法所适用的网络架构图;
图 3为本发明网络优化装置实施例一的结构示意图;
图 4为本发明网络优化装置实施例二的结构示意图。 具体实施方式 为使本发明实施例的目的、 技术方案和优点更加清楚, 下面将结合本 发明实施例中的附图, 对本发明实施例中的技术方案进行清楚、 完整地描 述, 显然,所描述的实施例是本发明一部分实施例, 而不是全部的实施例。 基于本发明中的实施例, 本领域普通技术人员在没有做出创造性劳动前提 下所获得的所有其他实施例, 都属于本发明保护的范围。
图 1为本发明网络优化方法实施例一的流程图。本实施例的执行主体 为网络优化装置, 具体的, 本实施例包括如下歩骤: S101 : 网络优化装置确定覆盖的区域内网络的当前 KPI低于预设 KPI门 限。
其中, 网络优化过程中, 主要关注当前网络的以下 5项 KPI: 切换成功 率 KPI、 E-RAB建立成功率 KPI、 RRC建立成功率 KPI、 RRC重建成功率 KPK 掉话率 KPI。 因此, 当网络的当前 ΚΡΙ具体为切换成功率 ΚΡΙ, 相应 的, 预设 ΚΡΙ门限为切换成功率的预设 ΚΡΙ门限; 或者, 网络的当前 ΚΡΙ 具体为增强型无线接入承载 E-RAB建立成功率 ΚΡΙ, 相应的, 预设 ΚΡΙ门 限为 E-RAB成功率的预设 ΚΡΙ门限; 或者, 网络的当前 ΚΡΙ具体为无线 资源控制 RRC建立成功率 ΚΡΙ, 相应的, 预设 ΚΡΙ门限为 RRC建立成功率 的预设 ΚΡΙ门限; 或者, 网络的当前 ΚΡΙ具体为 RRC重建成功率 ΚΡΙ, 相 应的, 预设 ΚΡΙ门限为 RRC重建成功率的预设 ΚΡΙ门限; 或者, 网络的 当前 ΚΡΙ具体为掉话率 ΚΡΙ, 相应的, 预设 ΚΡΙ门限为掉话率的预设 ΚΡΙ 门限。 当然, 还可以包含其他 ΚΡΙ, 本发明对此不作限制。
具体地, 网络优化装置确定覆盖的区域内网络的当前 ΚΡΙ低于预设 ΚΡΙ 门限包括但不限于以下几种方式:
网络优化装置可以实时的、 周期性的或者事件触发性的判断基站覆盖的 区域内网络的当前 ΚΡΙ是否低于预设 ΚΡΙ门限, 例如, 网络优化装置上可 设置一开关, 当运营商按下开关时, 触发网络优化装置判断基站覆盖的区 域内网络的当前 ΚΡΙ是否低于预设 ΚΡΙ门限, 确定覆盖的区域内网络的当 前 ΚΡΙ低于预设 ΚΡΙ门限。
若网络优化装置确定覆盖的区域内网络的当前 ΚΡΙ不低于预设 ΚΡΙ门限 时, 默认当前网络状态比较好, 无需优化。
若网络优化装置确定覆盖的区域内网络的当前 ΚΡΙ低于预设 ΚΡΙ 门限 时, 说明网络需要进行优化, 执行 S102。
S102: 网络优化装置通过分析网络环境配置数据以及用户上报数据, 确 定当前 KPI低于预设 KPI门限的根因。
其中, 根因是指导致当前 KPI低于预设 KPI门限的最早的原因。
具体地, 网络优化装置通过分析网络环境配置数据以及用户上报数据, 确定当前 KPI低于预设 KPI门限的根因, 包括两种分析方式, 分别为闭环分 析方式和开环分析方式。 通常, 当基站覆盖的区域内的网络波动程度小于第一预设值 (即网络比 较稳定) , 或者网络的网络形态复杂度小于第二预设值 (即网络形态比较单 一) , 或者, 网络中上报的用户数据的用户数量大于第三预设值 (即基站覆 盖区域内的所有或者大部分用户设备同时上报数据) , 所述网络优化装置 采用闭环分析方式分析网络环境配置数据以及用户上报数据, 确定当前 KPI 低于预设 KPI门限的根因。
采用闭环分析方式分析网络环境配置数据以及用户上报数据时, 包括 两种具体的实现方式, 第一种实现方式为: 首先, 把获取的基站存储的网 络环境配置数据以及当前的用户上报数据作为第一数据源, 其中, 基站存 储的网络环境配置数据包括: 基站的配置参数等; 当前的用户上报数据包 括: 当前时间点用户上报的测量报告(Measurement Report, MR) , 其中, 包括接收信号功率以及接收信号质量。 然后, 将第一数据源与第一 KPI根 因集合中的各类根因逐个进行匹配, 确定匹配度最高的一类根因为当前 KPI低于预设 KPI门限的根因。 其中, 第一 KPI根因集合包含如下至少一 种根因: 网络切换能力类根因; 邻区异常管理类根因; 射频 (Radio Frequency, RF ) 覆盖类根因; 网络异常运行类根因; 终端运行异常类根 因; 异系统切换类根因。
具体地, 第一 KPI根因集合中包含网络切换能力类根因中的优化切换 开关类子根因、 配置长期演进 (Long Term Evolution, LTE) , 异频切换 能力类子根因、 切换参数配置范围类子根因中的一类或其组合。 还包含邻 区异常管理类根因中的优化切换测量报告最强小区未知类子根因、 优化物 理小区标识 (Physical-layer Cell Identity, PCI) 冲突小区类子根因、 优化 NOHO切换禁止小区类子根因、 优化全球小区标识 (Global Cell Identity, GCI) 全网唯一性配置类子根因、 优化邻区超配问题类子根因中的一类或 其组合。 还包含 RF覆盖类根因中的切换小区弱覆盖异常类子根因、 切换 区域覆盖漏洞异常类子根因、 切换区域导频污染异常类子根因、 切换目标 小区针尖覆盖类子根因、 切换目标小区上行受限类子根因中的一类或其组 合。 还包含网络异常运行类根因包中的切换请求超时异常类子根因、 切换 请求拒绝异常类子根因、 非覆盖类异常子根因、 切换小区异常类子根因、 切换小区数据通道改变异常类子根因中的一类或其组合。还包含终端运行 异常类根因中的终端切换请求时延过长类子根因、请求拒绝导致时延过长 类子根因、 终端异系统能力不支持类子根因、 较大变化终端移动速度类子 根因、 终端异常能力低下类子根因中的一类或其组合。 还包含异系统切换 类根因中的 A2门限问题类子根因、 B1 门限问题类子根因、 A1 门限问题 类子根因、 A3门限问题类子根因中的一类或其组合。
在第一种实现方式中,将第一数据源与第一 KPI根因集合中各类根因 逐个进行匹配时, 获取第一数据源与每类根因的匹配度, 确定匹配度最高 的一类根因为 KPI低于预设 KPI门限的根因之后, 可选地, 还可以根据第 一数据源与每类根因的匹配度建立 KPI与各类根因对应的优先级顺序,例 如,当网络优化装置确定出当前网络的 RRC建立成功率 KPI低于预设 KPI 门限, 确定出导致 RRC建立成功率 KPI低于预设 KPI门限的根因为邻区 异常管理类根因, 则确定 RRC建立成功率 KPI与邻区异常管理类根因对 应的优先级最高; 在之后若采用闭环分析方式分析 RRC建立成功率 KPI 低于预设 KPI门限的根因时,最先将第一数据源与邻区异常管理类根因进 行匹配, 即采用下述第二种实现方式。
第二种实现方式具体为: 网络优化装置把获取的基站存储的网络环境 配置数据以及当前的用户上报数据作为第一数据源;按照第一 KPI根因集 合中的各类根因的优先级从高到低的顺序, 将第一数据源于所述第一 KPI 根因集合的各类根因进行匹配, 确定最先与第一数据源相匹配的一类根因 为当前 KPI低于预设 KPI门限的根因。 其中, 网络环境配置数据、 当前的 用户上报数据以及第一 KPI根因集合与第一种实现方式的第一 KPI根因集 合相同。
由于当基站覆盖的区域内的网络网络比较稳定,或者网络形态比较单一, 或者, 基站覆盖区域内的所有或者大部分用户设备同时上报数据时, 采用 闭环的分析方式进行根因分析, 所需要的数据为当前用户上报的数据以及基 站中存储的网络环境配置数据, 因此, 能够提高分析效率; 若按照第一 KPI 根因集合中的各类根因的优先级与第一数据源进行匹配, 确定最先与第一数 据源相匹配的一类根因为当前 KPI低于预设 KPI门限的根因, 能够进一歩地 提高分析效率。
当基站覆盖的区域内的网络波动程度大于第一预设值 (即网络不稳 定),或者所述网络的网络形态复杂度大于第二预设值(即网络形态复杂), 或者, 所述网络中上报数据的用户数量小于第三预设值 (即基站覆盖区域 内的小部分用户设备同时上报数据) , 网络优化装置采用开环分析方式分 析网络环境配置数据以及用户上报数据,确定当前 KPI低于预设 KPI门限 的根因。
具体地, 开环分析方式与闭环分析方式的不同在于, 开环分析方式需 要分析的数据除了网络环境配置数据和当前时间的用户上报数据之外, 还 包括 OSS或 eCor中存储的第二预设时间内 (过去一段时间内) 用户上报 的数据、 未来第一预设时间内 (未来一段时间内) 用户上报数据以及最小 路测 (Minimizing Drive Test, 以下简称: MDT)上报数据等。
网络优化装置采用开环分析方式分析网络环境配置数据以及用户上 报数据, 确定当前 KPI低于预设 KPI门限的根因的具体实现方式如下: 网 络优化装置将基站存储的网络环境配置数据、 当前用户上报数据、 未来第 一预设时间内用户上报数据、 MDT上报数据以及 OSS或者 eCor中存储的 历史第二预设时间内用户上报数据作为第二数据源; 将第二数据源与第二 KPI 根因集合中各类根因逐个进行匹配, 确定匹配度最高的根因为当前 KPI低于预设 KPI门限的根因。其中, 网络环境配置数据包括: 基站的配置 参数等; 用户上报数据包括: 包括接收信号功率以及接收信号质量。 MDT 上报数据包括位置信息和该位置的参考信号接收功率 (Reference Signal Received Power, RSRP)、 参考信号接收质量 (; Reference Signal Received Quality, RSRQ)等。 第二 KPI根因集合包含如下至少一种根因: 配置通用 移动通信系统异系统切换能力类根因; 配置全球移动通信系统 GSM异系 统切换能力类子根因; GCI不存在配置错误子根因; 射频 RF覆盖类根因。 网络优化装置可以采用算法停等的方式等待更多用户设备上报的 MR、 MDT 上报等, 再分析该些更多用户上报与网络配置环境数据源以确定根 因。
由于当网络部稳定、或者网络形态复杂或者基站覆盖区域内的小部分用 户设备同时上报数据, 采用开环分析方式进行根因分析, 开环分析方式所 分析的数据包括网络优化装置将基站存储的网络环境配置数据、 当前用户 上报数据、 未来第一预设时间内用户上报数据、 MDT上报数据以及 OSS 或者 eCor 中存储的历史第二预设事件内用户上报数据, 因此, 能够提高 分析的准确性。
S103 : 网络优化装置根据当前 KPI低于预设 KPI门限的根因, 对基站 覆盖的区域内的网络进行优化。
网络优化装置针对导致 KPI下降的根因 (即最早原因) , 进行相应的网 络优化。
本实施例中, 网络优化装置在确定基站覆盖的区域内网络的当前 KPI低 于预设 KPI门限条件下, 通过分析网络环境配置数据以及用户上报的数据, 确定导致当前 KPI低于预设 KPI门限的根因, 针对所确定的根因, 进行相应 的网络优化, 从而实现网络优化装置自动、快速分析出网络 KPI降低的根因, 提高网络优化效率。
图 2为本发明网络优化方法所适用的网络架构图。 本实施例中, 以网 络内存在 2个基站、 基站 1下存在小区 1、 小区 2、 小区 3, 基站 2下存在 小区 4、 小区 5、 小区 6为例。 如图 2所示, 以斜线条填充的椭圆表示基 站 1所覆盖的区域, 无填充的椭圆表示基站 2所覆盖的区域; 各个基站与 其所管辖的小区通过内部接口连接, 如图中黑色细实线所示; 各个基站与 eCor之间的接口为 X2接口,如虚拟 X2接口或伪 X2接口, 该接口用于管 理或协调各个基站之间的无线资源等, 可称为管理接口, 如图中黑色粗实 线所示; 各个基站与操作支撑子系统 OSS之间的接口为北向接口 itf-N, 如图中黑色细虚线所示。 另外, 各个基站与移动管理实体 (Mobility Management Entity, MME) 之间也通过内部接口连接(图中未示出) , 如 S1接口连接; 各个基站之间通过 X2接口连接 (图中未示出) 。 网络优化 装置 (图中未示出) 可设置在基站 1、 基站 2、 eCor或 OSS上, eCor或 OSS可位于任一基站覆盖的区域内或任一基站覆盖的区域之外。
参照图 2所示的网络架构图, 当采用闭环分析方式分析网络环境配置 数据以及用户上报数据, 确定当前 KPI低于预设 KPI门限的根因时, 若基 站 1所覆盖的区域内网络的某些当前 KPI低于预设 KPI门限时,网络优化 装置分析处于斜线填充的椭圆内的用户设备在当前时间点或当前时间段 通过内部接口上报的 MR、 MDT , 以及基站的配置参数等, 以确定当前 KPI低于预设 KPI门限的根因。 下面, 以当前网络的掉话率 KPI下降, 网络优化装置采用闭环分析方 式分析网络环境配置数据和用户上报数据为例进行说明。
具体的, 当发生掉话率 KPI 下降。 当网络优化装置的确定掉话率的 KPI低于预设 KPI门限值时,网络优化装置分析当前时间用户上报的 MR、 MDT以及基站的配置参数等,与第一 KPI根因集合中的各类根因逐个进行匹 配, 从而确定具体根因。 例如, 当 MR、 MDT上报中, 所有或者大部分用户 设备上报的 RSRP都低于 120dBm时,确定出的根因为 RF覆盖类根因,且具 体为切换区域覆盖漏洞异常类子根因。
当再发生掉话率 KPI下降, 网络优化装置无需与第一 KPI根因集合中 的各类根因逐个进行匹配, 而是优先匹配 RF 覆盖类根因, 确定导致掉话 率 KPI低于预设 KPI的原因。
参照图 2所示的网络架构图, 当采用开环分析方式分析网络环境配置 数据以及用户上报数据, 确定当前 KPI低于预设 KPI门限的根因时, 若基 站 1所覆盖的区域内网络的当前某项 KPI低于预设 KPI门限时,网络优化 装置进行算法停等, 等待斜线填充椭圆内更多的用户设备通过内部接口上 报的测量报告 MR、 最小化路测 MDT上报, 获得大量数据, 进而对该些 数据进行分析从而确定根因。 另外, 网络优化装置也可通过基站与 eCor之 间的管理接口、基站与操作支撑子系统 OSS之间的北向接口等获取存储在 OSS或 eCor的历史数据, 如基站覆盖区域内的用户设备在当前时间点之前 向 OSS或 eCor上报的 MR、 MDT上报等, 然后分析该些大量的数据从而确 定根因。
下面, 以当前网络的切换成功率 KPI下降, 网络优化装置采用开环分 析方式分析网络环境配置数据以及用户上报数据为例进行说明。
具体的,当基站通过自动网络选路(Automatic Network Routing, ANR) 尝试与邻居基站建立邻区关系, 由于邻居基站上无该新的 PCI, 导致切换 失败。此时, 若网络优化装置判断出切换成功率 KPI低于预设 KPI门限值 时, 网络优化装置进行算法停等, 等待更多的用户设备上报 MR、 MDT上 报数据等从而获得大量的数据, 或者, 向 OSS或 eCor获取当前时间点之 前用户上报的 MR、 MDT, 从而获得大量的数据, 然后分析该些数据表明 基站与邻居基站相距很远, 不能构成邻区, 从而确定出导致切换失败 KPI 下降的根因为 RF覆盖类根因中的越区覆盖类子根因。在确定出根因为 RF 覆盖类根因中的越区覆盖类子根因后, 可采用如下方式进行网络优化: 对 于有方向角 (Azimuth) 的天线, 则压低越区方向的下倾角 (tilting) , 从 而降低覆盖范围; 对于全向天线, 则以降低发射功率的方式来降低覆盖范 围。
图 3为本发明网络优化装置实施例一的结构示意图, 如图 3所示, 本实 施例的装置包括确定模块 301、 处理模块 302和优化模块 303, 其中, 确定模 块 301用于确定基站覆盖的区域内网络的当前关键性能指标 KPI低于预设 KPI门限; 处理模块 302用于通过分析网络环境配置数据以及用户上报数 据, 确定上述当前 KPI低于预设 KPI门限的根因; 优化模块 303用于根据 上述当前 KPI低于预设 KPI门限的根因,对上述基站覆盖的区域内的网络 进行优化。
在上述实施例中, 当基站覆盖的区域内的网络波动程度小于第一预设 值, 或者上述网络的网络形态复杂度小于第二预设值, 或者, 上述网络中 上报数据的用户数量大于第三预设值, 上述处理模块 302具体用于采用闭 环分析方式分析网络环境配置数据以及用户上报数据, 确定上述当前 KPI 低于预设 KPI门限的根因; 或者,
当基站覆盖的区域内的网络波动程度大于第一预设值, 或者上述网络 的网络形态复杂度大于第二预设值, 或者, 上述网络中上报数据的用户数 量小于第三预设值, 上述处理模块 302具体用于采用开环分析方式分析网 络环境配置数据以及用户上报数据,确定上述当前 KPI低于预设 KPI门限 的根因。
在上述实施例中, 上述处理模块 302具体用于把获取的基站存储的网 络环境配置数据以及当前的用户上报数据作为第一数据源; 将上述第一数 据源与第一 KPI根因集合中的各类根因逐个进行匹配,确定匹配度最高的 一类根因为上述当前 KPI低于上述预设 KPI门限的根因;
其中, 上述第一 KPI根因集合包括如下至少一种根因:
网络切换能力类根因; 邻区异常管理类根因; 射频 RF覆盖类根因; 网络异常运行类根因; 终端运行异常类根因; 异系统切换类根因。
在上述实施例中, 上述处理模块 302具体用于把获取的基站存储的网 络环境配置数据以及当前的用户上报数据作为第一数据源; 按照第一 KPI 根因集合中的各类根因的优先级从高到低的顺序, 将第一数据源与上述第 一 KPI根因集合的各类根因进行匹配,确定最先与上述第一数据源相匹配 的一类根因为上述当前 KPI低于预设 KPI门限的根因;
其中, 上述第一 KPI根因集合包括如下至少一种根因: 网络切换能力 类根因; 邻区异常管理类根因; 射频 RF覆盖类根因; 网络异常运行类根 因; 终端运行异常类根因; 异系统切换类根因。
在上述实施例中, 上述处理模块 302具体用于把基站存储的网络环境 配置数据、 当前的用户上报数据、 未来第一预设时间内用户上报数据、 MDT上报数据以及操作支撑子系统 OSS或增强型协调器 eCor中存储的历 史第二预设时间内用户上报数据, 作为第二数据源; 将上述第二数据源与 第二 KPI根因集合中的各类根因逐个进行匹配,确定匹配度最高的根因为 上述当前 KPI低于预设 KPI门限的根因;
其中, 所述第二 KPI根因集合包含如下至少一种根因: 配置通用移动 通信系统异系统切换能力类根因; 配置全球移动通信系统 GSM异系统切 换能力类子根因; GCI不存在配置错误子根因; 射频 RF覆盖类根因。 上 述实施例的装置, 对应的可用于执行图 1所示方法实施例的技术方案, 其 实现原理和技术效果类似, 此处不再赘述。
图 4为本发明网络优化装置实施例二的结构示意图。 如图 4所示, 本 实施的装置, 包括: 存储器 411、 处理器 412、 网络接口 413, 其中, 存储器 411用于存储基站覆盖的区域内网络当前 KPI和预设 KPI门限值,处理器 412 用于确定基站覆盖的区域内当前 KPI低于预设 KPI门限, 当处理器 412确定 当前 KPI低于预设 KPI门限时, 若基站覆盖的区域内的网络波动程度小于 第一预设值, 或者所述网络的网络形态复杂度小于第二预设值, 或者, 所 述网络中上报数据的用户数量大于第三预设值, 则网络接口 413向基站发 送分析根因指示, 这样基站通过分析网络环境配置数据以及用户上报数 据, 确定当前 KPI低于预设 KPI门限的根因, 基站确定根因之后, 基站向 网络优化装置的网络接口 413上报上述确定的根因。 若基站覆盖的区域内 的网络波动程度大于第一预设值, 或者所述网络的网络形态复杂度大于第 二预设值, 或者, 所述网络中上报数据的用户数量小于第三预设值, 则处 理器 412通过分析网络环境配置数据以及用户上报数据,确定当前 KPI低 于预设 KPI门限的根因;处理器 412根据自身确定的根因或者网络接口 413 接收基站上报的根因制定优化策略, 网络接口 413向基站发送优化策略, 基站根据上述优化策略对基站覆盖的区域内的网络进行优化。 具体的, 上 述网络接口 413可以是北向接口 (north bound interface, itf-N) , 也可以 是私有接口。
在上述实施例中, 处理器具体用于采用开环分析方式分析网络环境配 置数据以及用户上报数据, 确定所述当前 KPI低于预设 KPI门限的根因。
在上述实施例中, 处理器具体用于把基站存储的网络环境配置数据、 当前的用户上报数据、 未来第一预设时间内用户上报数据、 MDT 上报数 据以及 OSS或 eCor中存储的历史第二预设时间内用户上报数据, 作为第 二数据源;将所述第二数据源与第二 KPI根因集合中的各类根因逐个进行 匹配, 确定匹配度最高的根因为所述当前 KPI低于预设 KPI门限的根因; 其中, 所述第二 KPI根因集合包含如下至少一种根因: 配置通用移动通信 系统异系统切换能力类根因; 配置全球移动通信系统 GSM异系统切换能 力类子根因; GCI不存在配置错误子根因; 射频 RF覆盖类根因。
上述实施例中的装置用于执行图 1所示方法实施例, 其实现原理和技术 效果类似, 此处不再赘述。
本领域普通技术人员可以理解: 实现上述方法实施例的全部或部分歩骤 可以通过程序指令相关的硬件来完成, 前述的程序可以存储于一计算机可读 取存储介质中, 该程序在执行时, 执行包括上述方法实施例的歩骤; 而前述 的存储介质包括: ROM、 RAM, 磁碟或者光盘等各种可以存储程序代码的介 质。
最后应说明的是: 以上各实施例仅用以说明本发明的技术方案, 而非对 其限制; 尽管参照前述各实施例对本发明进行了详细的说明, 本领域的普通 技术人员应当理解:其依然可以对前述各实施例所记载的技术方案进行修改, 或者对其中部分或者全部技术特征进行等同替换; 而这些修改或者替换, 并 不使相应技术方案的本质脱离本发明各实施例技术方案的范围。

Claims

权 利 要 求 书
1、 一种网络优化装置, 其特征在于, 包括:
确定模块, 用于确定基站覆盖的区域内网络的当前关键性能指标 KPI 低于预设 KPI门限;
处理模块, 用于通过分析网络环境配置数据以及用户上报数据, 确定 所述当前 KPI低于预设 KPI门限的根因;
优化模块, 用于根据所述当前 KPI低于预设 KPI门限的根因, 对所述 基站覆盖的区域内的网络进行优化。
2、 根据权利要求 1 所述的装置, 其特征在于, 所述处理模块具体用 于当基站覆盖的区域内的网络波动程度小于第一预设值, 或者所述网络的 网络形态复杂度小于第二预设值, 或者, 所述网络中上报数据的用户数量 大于第三预设值, 所述处理模块采用闭环分析方式分析网络环境配置数据 以及用户上报数据, 确定所述当前 KPI低于预设 KPI门限的根因; 或者, 当基站覆盖的区域内的网络波动程度大于第一预设值, 或者所述网络的网 络形态复杂度大于第二预设值, 或者, 所述网络中上报数据的用户数量小 于第三预设值, 所述处理模块采用开环分析方式分析网络环境配置数据以 及用户上报数据, 确定所述当前 KPI低于预设 KPI门限的根因。
3、 根据权利要求 2所述的装置, 其特征在于, 所述处理模块具体用 于把获取的所述基站存储的网络环境配置数据以及当前的用户上报数据 作为第一数据源;将所述第一数据源与第一 KPI根因集合中的各类根因逐 个进行匹配, 确定匹配度最高的一类根因为所述当前 KPI 低于所述预设 KPI门限的根因;
其中, 所述第一 KPI根因集合包括如下至少一种根因:
网络切换能力类根因;
邻区异常管理类根因;
射频 RF覆盖类根因;
网络异常运行类根因;
终端运行异常类根因;
异系统切换类根因。
4、 根据权利要求 2所述的装置, 其特征在于, 所述处理模块具体用 于把获取的所述基站存储的网络环境配置数据以及当前的用户上报数据 作为第一数据源; 按照第一 KPI根因集合中的各类根因的优先级从高到低 的顺序, 将第一数据源与所述第一 KPI根因集合的各类根因进行匹配, 确 定最先与所述第一数据源相匹配的一类根因为所述当前 KPI低于预设 KPI 门限的根因;
其中, 所述第一移动 KPI根因集合包括如下至少一种根因:
网络切换能力类根因;
邻区异常管理类根因;
射频 RF覆盖类根因;
网络异常运行类根因;
终端运行异常类根因;
异系统切换类根因。
5、 根据权利要求 2〜4任一项所述的装置, 其特征在于, 所述处理模 块具体用于把所述基站存储的网络环境配置数据、 当前的用户上报数据、 未来第一预设时间内用户上报数据、 最小化路测 MDT上报数据以及操作 支撑子系统 OSS或增强型协调器 eCor中存储的历史第二预设时间内用户 上报数据, 作为第二数据源; 将所述第二数据源与第二 KPI根因集合中的 各类根因逐个进行匹配,确定匹配度最高的根因为所述当前 KPI低于预设 KPI门限的根因;
其中, 所述第二 KPI根因集合包含如下至少一种根因:
配置通用移动通信系统异系统切换能力类根因;
配置全球移动通信系统 GSM异系统切换能力类子根因;
GCI不存在配置错误子根因;
射频 RF覆盖类根因。
6、 一种网络优化方法, 其特征在于, 包括:
网络优化装置确定基站覆盖的区域内网络的当前关键性能指标 KPI 低于预设 KPI门限;
所述网络优化装置通过分析网络环境配置数据以及用户上报数据, 确 定所述当前 KPI低于预设 KPI门限的根因;
所述网络优化装置根据所述当前 KPI低于预设 KPI门限的根因,对所 述基站覆盖的区域内的网络进行优化。
7、 根据权利要求 6所述的方法, 其特征在于, 所述网络优化装置通 过分析网络环境配置数据以及用户上报数据,确定所述当前 KPI低于预设 KPI门限的根因, 包括:
当基站覆盖的区域内的网络波动程度小于第一预设值, 或者所述网络 的网络形态复杂度小于第二预设值, 或者, 所述网络中上报数据的用户数 量大于第三预设值, 所述网络优化装置采用闭环分析方式分析网络环境配 置数据以及用户上报数据, 确定所述当前 KPI低于预设 KPI门限的根因; 或者,
当基站覆盖的区域内的网络波动程度大于第一预设值, 或者所述网络 的网络形态复杂度大于第二预设值, 或者, 所述网络中上报数据的用户数 量小于第三预设值, 所述网络优化装置采用开环分析方式分析网络环境配 置数据以及用户上报数据, 确定所述当前 KPI低于预设 KPI门限的根因。
8、 根据权利要求 7所述的方法, 其特征在于, 所述网络优化装置采 用闭环分析方式分析网络环境配置数据以及用户上报数据, 确定所述当前
KPI低于预设 KPI门限的根因, 包括:
所述网络优化装置把获取的所述基站存储的网络环境配置数据以及 当前的用户上报数据作为第一数据源;
所述网络优化装置将所述第一数据源与第一 KPI 根因集合中的各类 根因逐个进行匹配,确定匹配度最高的一类根因为所述当前 KPI低于所述 预设 KPI门限的根因;
其中, 所述第一 KPI根因集合包括如下至少一种根因:
网络切换能力类根因;
邻区异常管理类根因;
射频 RF覆盖类根因;
网络异常运行类根因;
终端运行异常类根因;
异系统切换类根因。
9、 根据权利要求 7所述的方法, 其特征在于, 所述网络优化装置采 用闭环分析方式分析网络环境配置数据以及用户上报数据, 确定所述当前 KPI低于预设 KPI门限的根因, 包括:
所述网络优化装置把获取的所述基站存储的网络环境配置数据以及 当前的用户上报数据作为第一数据源;
所述网络优化装置按照第一 KPI 根因集合中的各类根因的优先级从 高到低的顺序,将第一数据源与所述第一 KPI根因集合的各类根因进行匹 配,确定最先与所述第一数据源相匹配的一类根因为所述当前 KPI低于预 设 KPI门限的根因;
其中, 所述第一移动 KPI根因集合包括如下至少一种根因:
网络切换能力类根因;
邻区异常管理类根因;
射频 RF覆盖类根因;
网络异常运行类根因;
终端运行异常类根因;
异系统切换类根因。
10、 根据权利要求 7〜9任一项所述的方法, 其特征在于, 所述网络优 化装置采用开环分析方式分析网络环境配置数据以及用户上报数据, 确定 所述当前 KPI低于预设 KPI门限的根因, 包括:
所述网络优化装置把所述基站存储的网络环境配置数据、 当前的用户 上报数据、 未来第一预设时间内用户上报数据、 最小化路测 MDT上报数 据以及操作支撑子系统 OSS或增强型协调器 eCor中存储的历史第二预设 时间内用户上报数据, 作为第二数据源;
所述网络优化装置将所述第二数据源与第二 KPI 根因集合中的各类 根因逐个进行匹配, 确定匹配度最高的根因为所述当前 KPI低于预设 KPI 门限的根因;
其中, 所述第二 KPI根因集合包含如下至少一种根因:
配置通用移动通信系统异系统切换能力类根因;
配置全球移动通信系统 GSM异系统切换能力类子根因;
GCI不存在配置错误子根因;
射频 RF覆盖类根因。
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