TWI724498B - System of hierarchical optimization for mobile network and method thereof - Google Patents

Abstract

This application discloses a system of hierarchical optimization for mobile network and a method thereof, which activates a network parameter initial value optimization sub-module, based on mobile network system data from the mobile network system, to generate an initial value of the network parameter optimization for the mobile network system to operate, and then activates a long-term network parameter optimization sub-module and a short-term network parameter optimization sub-module to perform long-term optimization and short-term optimization, respectively. The three sub-modules work together to optimize the hierarchy, so that the mobile network can have the advantages of real-time and stability, etc., and can improve the performance of the network and enhance the experience of the end-users.

Description

System and method for optimizing mobile network hierarchy

This case is about a wireless mobile network parameter optimization technology, in detail, it is about a mobile network hierarchical optimization system and method.

With the development of instant messaging or mobile payment, people are increasingly inseparable from the mobile network. The development of each generation of mobile communication networks has brought a better experience, and the advent of smart phones has not only driven the rise of the mobile generation. , And accelerate the innovation of communication technology.

The development of mobile network architecture is becoming more and more complex. Compared with the past, the existing 4G mobile network architecture has higher data throughput, lower latency, lower construction and execution and maintenance costs, and the future 5G mobile network The architecture has higher data compression density, modulation/demodulation, higher transmission rate, enhanced spectrum efficiency, and so on.

However, with the development of mobile communication technology and the increase in demand for mobile communication, the strength and quality of wireless signals, as well as the performance and performance indicators of wireless transmission will inevitably be affected. For example, the interference between base stations and the inability to grasp the actual network user’s The status and network parameters conflict with each other and make it difficult to optimize.

Therefore, how to effectively optimize network parameters and improve network performance is one of the important issues that need to be resolved in this field.

In order to solve the above and other problems, this case proposes a system and method for optimizing the mobile network hierarchy.

The mobile network hierarchical optimization system in this case includes: data storage; mobile network data processing module, which receives and/or processes the mobile network system data from the mobile network system to combine the received data and/or The processed data is stored in the data storage; and the mobile network parameter optimization module, based on the received data in the data storage and at least a part of the processed data, performs hierarchical optimization of the network parameters, The optimization result is stored in the data storage, where the optimization result includes the initial value of the network parameter, the short-term optimization result of the network parameter, and/or the long-term optimization result of the network parameter.

In addition, the mobile network system data includes the operating status of the mobile network system including configuration management, performance management, obstacle management and/or wireless network key performance indicators, including location, service type, traffic volume and/or movement path User identification, including user terminal measurement report and/or user terminal minimization drive test user data report, RF signal obtained by user terminal measurement report, scanner measurement and/or simulation estimation software, and/or Base station device type including device model, firmware version, and/or parameter characteristics.

In addition, the mobile network parameter optimization module includes: a network parameter initial value optimization sub-module, which is used before the base station is set up, based on the radio frequency signal and the received data stored in the data storage / Or the radio frequency map in the processed data, the network parameter Preliminary optimization of frequency, bandwidth, physical layer cell ID, random access channel, mobility, and/or neighbor cell list to provide the initial value of the network parameter, causing the mobile network system to operate according to the initial value of the network parameter ; And the long-term network parameter optimization sub-module and the short-term network parameter optimization sub-module, which are used after the base station is launched, based on the received data and the processed data stored in the data storage Configuration management, performance management, obstacle management, wireless network key performance indicators, user terminal measurement reports, user terminal minimization drive test, user location, user service type, user signal requirements, core network and/or multiple connections Take edge calculations to further optimize the network parameters to provide the long-term optimization results of the network parameters and the short-term optimization results of the network parameters respectively.

In addition, the long-term network parameter optimization sub-module optimizes network parameters that cannot be adjusted frequently and network parameters that require a long time to calculate. The network parameters that cannot be adjusted frequently include frequency, bandwidth, and physical layer cells. Identification code, random access channel and/or mobility, and the network parameters that require a long time calculation include long-term user measurement reports and/or radio frequency mapping. The short-term network parameter optimization sub-module optimizes network parameters that can be adjusted in real time. The network parameters that can be adjusted in real time include cell individual offset, power, and/or neighbor cell list.

In addition, the short-term network parameter optimization sub-module detects whether the mobile network system is abnormal and whether the long-term network parameter optimization sub-module generates the long-term network parameter optimization result, and among them, the long-term network The path parameter optimization sub-module detects whether the mobile network system is abnormal and detects whether the short-term network parameter optimization sub-module generates a short-term optimization result of the network parameters.

In addition, the mobile network data processing module processes the radio frequency signals in the received mobile network system data to obtain radio frequency maps before the base station is set up. After the base station is launched, the mobile network system data received The user terminal measurement report in the data is processed to obtain the radio frequency map, or the user terminal measurement report and the radio frequency signal in the received mobile network system data are processed to obtain the radio frequency map.

Secondly, the method for optimizing the mobile network hierarchy in this case includes: receiving and/or processing mobile network system data from the mobile network system; initial optimization of network parameters based on the received data and/or processed data , In order to provide the initial value of the network parameter, causing the mobile network system to operate according to the initial value of the network parameter; continue to receive and/or continue to process the mobile network system data from the mobile network system; and according to the received At least a part of the data, the processed data, the continuously received data, and the continuously processed data, perform short-term network parameter optimization and long-term network parameter optimization on the network parameters.

In addition, the short-term network parameter optimization and the long-term network parameter optimization are performed by event triggering, periodic triggering, or normal operation.

In addition, the received data is the radio frequency signal measured by the scanner, the processed data is the radio frequency map, and the continuously received data is the mobile network system operation status, user identification and/or user measurement report , The data that has been processed continuously is the key performance indicator of the wireless network.

In addition, the short-term network parameter optimization is performed based on the long-term network parameter optimization result of the long-term network parameter optimization, or the long-term network parameter optimization is performed based on the short-term network parameter optimization of the short-term network parameter optimization. result.

Therefore, the mobile network hierarchical optimization system and method in this case adopts the concept of hierarchical optimization, and first provides a set of appropriate network parameter values through the network parameter initial value optimization sub-module to avoid network parameter conflicts. Enable the mobile network to maintain basic operations, and then through the long-term The long-term network parameter optimization sub-module and the short-term network parameter optimization sub-module do a deeper optimization of the mobile network. By combining the above three sub-modules, the mobile network optimization can be real-time, stable, and accurate. And other advantages.

1‧‧‧Mobile network system

2‧‧‧Mobile network level optimization system

21‧‧‧Data Storage

22‧‧‧Mobile network data processing module

221‧‧‧Mobile network system operation status

222‧‧‧User Identification

223‧‧‧User Information Report

224‧‧‧Radio Frequency (RF) Signal

225‧‧‧Base station equipment type

23‧‧‧Mobile network parameter optimization module

231‧‧‧Network parameter initial value optimization sub-module

232‧‧‧Short-term network parameter optimization sub-module

233‧‧‧Long-term network parameter optimization sub-module

31~36‧‧‧Cube

51~55‧‧‧eNB A~eNB E

S61~S64‧‧‧Step

Figure 1 is a schematic diagram of an embodiment of the mobile network hierarchy optimization system of the project; Figure 2 is a schematic diagram of an embodiment of the mobile network data processing module of the mobile network hierarchy optimization system of the project; Figure 3 is a schematic diagram of an embodiment of the mobile network hierarchy optimization system of the project A schematic diagram of an embodiment of the mobile network parameter optimization module of the mobile network layer optimization system; Figure 4 is a block diagram of an embodiment of the mobile network layer optimization of the project; Figure 5 is a block diagram of the mobile network layer optimization system of the project A schematic diagram of the mobile network of the method and method; and Figure 6 is a schematic flow diagram of an embodiment of the mobile network hierarchy optimization method of this project.

The following specific examples are used to illustrate the implementation of this case. Those who are familiar with this technique can easily understand the other advantages and effects of this case from the content disclosed in this article. The structure, ratio, size, etc. shown in the drawings in this manual are only used to match the content disclosed in the manual for the understanding and reading of those who are familiar with the art, and are not used to limit the implementation of this case. Conditions, so any modification, change or adjustment shall still fall within the scope of the technical content disclosed in this case without affecting the effects and objectives that can be achieved in this case.

Please refer to Figure 1. The mobile network layer optimization system 2 of this case is connected and applied to the mobile network system 1. The mobile network layer optimization system 2 at least includes a data storage 21, a mobile network data processing module 22, And mobile network parameter optimization module 23. The mobile network data processing module 22 receives and/or processes mobile network system data from the mobile network system 1, such as mobile network system operating status, user identification, user data report, radio frequency signal, and base station equipment type, etc. , And then stored in the data storage 21; the mobile network parameter optimization module 23 obtains the required data from the data storage 21 to optimize the network parameters hierarchically, and then stores the optimization results in the data storage 21. The data storage 21 can store the received data, processed data, and optimization results of the mobile network parameter optimization module 23 of the mobile network data processing module 22. The optimization results include initial network parameter values, network parameters The result of short-term optimization of parameters, and/or the result of long-term optimization of network parameters.

Please refer to Figure 2, the mobile network data processing module 22 can receive the mobile network system operating status 221, including configuration management (Configuration Management; CM), performance management (Performance Management; PM), and fault management (Fault Management; FM), Wireless Network Key Performance Indicators (KPI)... etc.; User identification 222, including location, service type, traffic, movement path... etc.; User data report 223, including user terminal measurement report ( Measurement Report; MR), User Terminal Minimization Drive Test (MDT)... etc.; Radio Frequency (RF) signal 224, obtained by MR, scanner (scanner) measurement, analog estimation software... etc. In addition, the mobile network data processing module 22 can also receive the base station device type 225, such as device model, firmware version This, parameter characteristics, etc., are used as the reference basis for the subsequent algorithm. In addition, the mobile network data processing module 22 has the ability to generate KPIs and RF Maps (RF Map) required by the mobile network parameter optimization module 23, wherein the RF Map is obtained by calculating the RF Signal.

When the base station has not been set up, the RF Map can be calculated by scanner measurement, simulation estimation software... etc.; when the base station is set up, because the data source of the RF signal 224 can increase the collection of user terminal measurement reports (MR), so RF Map can be obtained by MR. It can also be obtained by combining scanner measurement and simulation estimation software with MR. Since MR is the return data of the actual user terminal, the accuracy and precision of network optimization can be improved.

The mobile network parameter optimization module 23 can perform wireless operations based on CM, PM, FM, KPI, MR, MDT, user identification 222 location, service type, traffic volume, movement path, RF signal 224, RF Map... etc. The network base station parameters (ie, network parameters) are optimized.

Referring to FIG. 3, the mobile network parameter optimization module 23 includes a network parameter initial value optimization sub-module 231, a short-term network parameter optimization sub-module 232, and a long-term network parameter optimization sub-module 233. The initial network parameter optimization sub-module 231, the short-term network parameter optimization sub-module 232, and the long-term network parameter optimization sub-module 233 have the ability to set mobile network system parameters. In addition, the initial network parameter optimization sub-module 231, the short-term network parameter optimization sub-module 232, and the long-term network parameter optimization sub-module 233 have the ability to perform network optimization according to the type of base station equipment.

The mobile network parameter initial value optimization sub-module 231 can check the frequency, bandwidth, physical cell identity (PCI), and random memory through RF signal, RF Map... etc. before the base station is set up. Take the channel (random access channel; RACH), mobility (Mobility), neighbor list (Neighbor List)... and other parameters to optimize, provide a set of suitable network The initial values of the path parameters are used to avoid conflicts between network parameters and enable the mobile network to maintain basic operations.

After the base station is opened, it can increase the collection of user terminal (User Equipment; UE) report data, such as MR, MDT... etc.; collect the mobile network system operating status data, such as CM, PM, FM, KPI... etc. ; Collect user identification from core network, Multi-access Edge Computing (MEC) or other data sources, such as user location, user service type, user signal demand... etc., long-term network parameter optimization The module 233 and the short-term network parameter optimization sub-module 232 can further solve the problems of the mobile network by using these data. In addition, when the base station is launched, because the data source of the RF signal can increase the collection of user terminal measurement reports (MR), the RF Map can be obtained by MR, and it can also be combined with scanner measurement, analog estimation software... Obtained as an optimization basis for the long-term network parameter optimization sub-module 223 and the short-term network parameter optimization sub-module 232.

In other words, the network parameter optimization module 23 adopts the concept of hierarchical optimization, and first provides a set of appropriate network parameter values through the mobile network parameter initial value optimization sub-module 231 to avoid network parameter conflicts, and make the mobile network The basic operation can be maintained, and the mobile network can be further optimized through the short-term network parameter optimization sub-module 232 and the long-term network parameter optimization sub-module 233. therefore. When the mobile network parameter initial value optimization sub-module 231 provides a set of appropriate network parameter values and sets the base station, since the base station has been activated at this time, it can further collect CM, PM, FM, KPI, MR , MDT, user location, user service type, user traffic, RF Signal, RF Map... and other data, so the long-term network parameter optimization sub-module 233 and short-term network parameter optimization sub-module 232 can be based on Service-based and Location-based optimization of network parameters, optimized for specific application services and specific areas. Furthermore, due to the interlocking of mobile network parameters, Different network parameters may affect each other. In order to improve the efficiency and performance of mobile network optimization and avoid conflicts between optimization results, the long-term network parameter optimization sub-module 233 and the short-term network parameter optimization sub-module 232 can be based on each other Do calculations and decision-making for the optimized results.

In an embodiment, taking handover between LTE technology base stations as an example, when the base station finds too late handover (HO), the adjustable parameters include Time to Trigger (TTT), A3 Offset, Cell Individual Offset (CIO), each parameter has an adjustable range, such as TTT is 0~5120ms, A3Offset is -15dB~15dB, CIO is -24dB~24dB, and A3 Event starts The threshold is Mn>Mp+Offsetn, where Mn is the signal strength of neighboring cells, Mp is the signal strength of the main cell, and Offsetn is A3Offset+Hys-CIO. Therefore, when the CIO reaches the upper and lower limits, you can adjust A3Offset so that there is still room to do Optimization. For example, when the CIO reaches the upper limit of 24dB, if the A3 Offset is reduced by 10dB, then the CIO can be increased by 10 to 14dB.

The mobile network base station equipment is implemented by various manufacturers. The characteristics of the same network parameter may be different under the equipment of different manufacturers. For example, the transmission power (Tx Power) parameter of a manufacturer needs to be restarted. Another manufacturer does not need to start, so the algorithm of the long-term network parameter optimization sub-module 233 and the algorithm of the short-term network parameter optimization sub-module 232 will also be a reference basis for network optimization based on the type of base station equipment.

The long-term network parameter optimization sub-module 233 is mainly optimized for network parameters that cannot be adjusted frequently, such as frequency, bandwidth, PCI, RACH, Mobility (partial)... and other parameter changes need to restart the base station, and less It needs to be changed at any time. In order to avoid frequently restarting the base station and causing instability of the mobile network, it will be restarted during off-peak hours. In addition, the long-term network parameter optimization sub-module 233 is mainly for optimization algorithms that require long-term data or long-term calculations. Line optimization, such as collecting long-term user measurement reports (MR), calculating the RF Map of the mobile network, and using frequency optimization algorithms to find the frequency configuration that can provide the best SINR of the system for setting.

The short-term network parameter optimization sub-module 232 is mainly optimized for network parameters that can be adjusted in real time, such as CIO, Power, NeighborList... and other parameter changes without restarting the base station, and can solve network issues such as Mobility, Loading... In addition, since the network parameters can be adjusted in real time, the short-term network parameter optimization sub-module can visualize the current status of the mobile network and optimize the network from a more precise perspective.

Furthermore, the long-term network parameter optimization sub-module 233 and the short-term network parameter optimization sub-module 232 can operate through event triggering, periodic triggering or normal (background) operation. By collocation of the two modules, mobile network optimization can be achieved. It has the advantages of real-time, stable, precise...etc.

Next, referring to Figure 4, it schematically illustrates an embodiment of the mobile network hierarchy optimization in this case. In this embodiment, the mobile network data received by the mobile network data processing module 22 from the mobile network system 1 is the RF signal measured by the scanner, as shown in block 31. The mobile network data processing module 22 processes the RF signal to become an RF MAP, and then stores the received and/or processed data in the data storage 21, as shown in block 32. The mobile network parameter optimization module 23 activates the network parameter initial value optimization sub-module based on the received data and/or processed data from the mobile network data processing module 22 stored in the data storage 21 Preliminary optimization is performed to generate initial values of network parameters for the mobile network system 1 to operate accordingly, such as setting and opening a base station, as shown in block 33. Then, the mobile network data continuously received from the mobile network system 1 by the mobile network data processing module 22 is data such as the operating status of the mobile network system, user identification, and user data report, as shown in block 34. The mobile network data processing module 22 calculates the KPI, and then stores the continuously received and/or continuously processed data in the data storage 21, as shown in block 35 Show. Finally, the short-term network parameter optimization sub-module and the long-term network parameter optimization sub-module are activated, based on the received data, processed data, and data from the mobile network data processing module 22 stored in the data storage 21 The continuously received data and at least part of the continuously processed data generate short-term network parameter optimization results and long-term network parameter optimization results for the mobile network system 1 to operate accordingly, and then store them in the data storage 21, This is shown in block 36.

The following example illustrates the application of the system and method for the optimization of the mobile network hierarchy in this case, and takes the Too-Late HO issue on the mobile network as an example. The mobile network diagram is shown in Figure 5. As shown in Figure 5, the LTE system includes five evolved node B (evolved node B; eNB), namely eNB A 51, eNB B 52, eNB C 53, eNB D 54, and eNB E 55. When the user terminal moves from the range of eNB A 51 to the range of eNB B 52, too late HO often occurs during the handover process of the LTE system.

First, 1.scanner measures the RF signal. Then, 2. Generate RF MAP based on the RF signal measured by the scanner and store it in the data storage. Furthermore, 3. Start the network parameter initial value optimization sub-module, that is, calculate the network parameters required by the base station to set up according to RF MAP, including frequency, bandwidth, power, PCI, TAC, RACH, Mobility, Neighbor List Table And so on, to set up and launch the base station. Next, 4. The mobile network system continuously reports CM, PM, FM, MR, MDT, KPI, etc., which are processed by the mobile network data processing module and stored in the data storage. Afterwards, 5. Start the long-term network parameter optimization sub-module/short-term network parameter optimization sub-module. In addition, starting the long-term network parameter optimization sub-module/short-term network parameter optimization sub-module may include the following methods: 5-1. The short-term network parameter optimization sub-module continuously detects whether the mobile network system has problems, and the long-term Whether network parameter optimization has long-term optimization results of network parameters. Long-term Internet Participation The data optimization sub-module continuously detects whether there is a problem with the mobile network system, and whether the short-term network parameter optimization sub-module has short-term optimization results of network parameters. 5-2. The short-term network parameter optimization sub-module judges the PM and KPI reported by the base station, detects the Too-Late HO issue in eNB A 51 in the mobile network system, activates the optimization algorithm, and notifies the long-term network parameters The optimization sub-module has started the optimization algorithm. 5-3. The short-term network parameter optimization sub-module performs CIO adjustments through optimization algorithms, gradually adjusting the CIO of the neighboring cell eNB B 52 of eNB A 51 from 0 to 24 dB, while the long-term network parameter optimization sub-module continues Receive short-term network parameter optimization results of the short-term network parameter optimization sub-module. 5-4. The long-term network parameter optimization sub-module detects that the optimization of the short-term network parameter optimization sub-module has reached the upper limit (CIO range is -24dB~24dB), the event triggers the optimization algorithm to start, and the short-term network is notified The path parameter optimization sub-module stops its optimization algorithm. The optimization algorithm of the long-term network parameter optimization sub-module adjusts the A3 offset setting value of eNB A 51 from 3 to -7, and adjusts the CIO of the neighboring cell eNB B 52 of eNB A 51 to 14 dB, and the rest of eNB A 51 The CIO of neighboring cells eNB C 53, eNB D 54, eNB E 55) is adjusted from 0 to -10dB. The short-term network parameter optimization sub-module stops the optimization algorithm. 5-5. The long-term network parameter optimization sub-module completes the optimization of the long-term network parameter optimization sub-module, and informs the short-term network parameter optimization sub-module to start the algorithm again.

Also take the Too-Late HO issue on the mobile network as an example. The schematic diagram of the mobile network is shown in Figure 5.

First, 1.scanner measures the RF signal. Then, 2. Generate RF MAP based on the RF signal measured by the scanner and store it in the data storage. Furthermore, 3. Start the network parameter initial value optimization sub-module. The network parameter initial value optimization sub-module calculates the network parameters required for the base station to open a station based on the RF MAP, including frequency, bandwidth, power, PCI, TAC, RACH, Mobility, Neighbor List Table, etc., and then sets the base station And open the stage. Next, 4. Action Network The road system continuously reports CM, PM, FM, MR, MDT, and KPI, which are processed by the mobile network data processing module and stored in the data storage. Afterwards, 5. Start the long-term network parameter optimization sub-module/short-term network parameter optimization sub-module. In addition, starting the long-term network parameter optimization sub-module/short-term network parameter optimization sub-module may include the following methods: 5-1. The short-term network parameter optimization sub-module continuously detects whether the mobile network system has problems, and the long-term Whether the network parameter optimization sub-module has long-term optimization results of network parameters. The long-term network parameter optimization sub-module continuously detects whether the mobile network system has problems, and the short-term network parameter optimization sub-module has short-term optimization results of network parameters. 5-2. The short-term network parameter optimization sub-module judges the PM and KPI reported by the base station, detects the Too-Late HO issue in the mobile network system eNB A 51, starts the optimization algorithm, and notifies the long-term network parameter optimization The sub-module has started the optimization algorithm. 5-3. The short-term network parameter optimization sub-module adjusts the CIO through the optimization algorithm, and gradually adjusts the CIO of the neighboring cell eNB B 52 of eNB A 51 from 0 to 20 dB. The long-term network parameter optimization sub-module continuously receives the short-term network parameter optimization results of the short-term network parameter optimization sub-module. 5-4. The long-term network parameter optimization sub-module periodically starts the optimization algorithm and notifies the short-term network parameter optimization sub-module to stop the algorithm. It is detected that the short-term network parameter optimization sub-module optimization is close to the lower limit (CIO range is -24dB~24dB), and the long-term network parameter optimization sub-module adjusts the A3 offset setting value of eNB A 51 from 3 to- 2. Adjust the CIO of the neighboring cell eNB B 52 of eNB A 51 to 15 dB, and adjust the CIO of the remaining neighboring cells eNB C 53, eNB D 54, and eNB E 55 of eNB A 51 from 0 to -5 dB. The short-term network parameter optimization sub-module stops the optimization algorithm. 5-5. The long-term network parameter optimization sub-module completes the optimization of the long-term network parameter optimization sub-module, and informs the short-term network parameter optimization sub-module to start the algorithm again.

The characteristics of the parameters adjusted in the above two embodiments are that the CIO does not need to restart the base station, and the A3 Offset can only take effect after restarting the base station. Therefore, the long-term network parameter optimization sub-module is optimized. The parameter characteristics adjusted in the embodiment shown below are TX Power, Mobility parameter Qoffset and CIO, Neighbor List Table, and can be adjusted in the long-term network parameter optimization sub-module or the short-term network parameter optimization sub-module without restarting the base station. The frequency, bandwidth, A5, and A3 offset must be restarted to take effect. Therefore, the long-term network parameter optimization sub-module makes a decision and adjustment.

First, 1. Scanner measures the RF signal or/and the industrial model mobile phone measures the RF signal. Then, 2. Generate RF MAP based on the RF signal measured by the scanner or/and the mobile phone and store it in the data storage. 3. Start the network parameter initial value optimization sub-module. According to RF MAP, calculate the network parameters required for the base station to open, including frequency, bandwidth, power, PCI, TAC, RACH, Mobility, Neighbor List Table, etc., and set and open the base station. Next, 4. Continue to collect mobile network systems for continuous CM, PM, FM, MR, MDT, KPI, Call Trace, CTUM, service types, etc., and store them in the data storage after being processed by the mobile network data processing module in. Afterwards, 5. Start the long-term network parameter optimization sub-module/short-term network parameter optimization sub-module.

The long-term network parameter optimization sub-module continues to detect whether the mobile network quality occurs according to the RF Map. The observation interval exceeds the critical ratio (such as 50%) and does not meet the target, such as the system average SINR>5dB, or/and CDF 10% data point SINR>5dB, or/and designated data point SINR>5dB, etc. If yes, then determine the PM (such as whether the number of users is below the critical value) or/and the time (such as 2 am), and then make a system signal quality optimization decision on the network parameters under monitoring. Among them, the RF Map can be obtained based on the RF signal measured by the scanner, or/and the RF signal measured by the industrial model mobile phone, or/and based on the MR reported by the mobile user terminal; the system signal quality is optimized by estimating every point of the RF Map SINR to optimize frequency, bandwidth, power, PCI, TAC, RACH, Mobility, Neighbor List Table related parameters to meet the target, such as average SINR>5dB, or/and CDF 10% data point SINR>5dB, or/and The designated data point SINR>5dB, etc.

The short-term network parameter optimization sub-module continues to detect whether the mobile network quality occurs based on the RF Map. The observation interval exceeds the critical proportion value (such as 50%) and does not meet the target, such as the system average SINR>5dB, or/and CDF 10% Data point SINR>5dB, or/and designated data point SINR>5dB, etc. If so, then determine the PM data (such as whether the number of users exceeds the threshold) or/and the time (if not at 2 am), and then make a system signal quality optimization decision on the network parameters that do not need to stop the equipment to provide services during the monitoring. The RF Map can be obtained based on the RF signal measured by the scanner, or/and the RF signal measured by the industrial mobile phone, or/and based on the MR reported by the mobile user terminal; the system signal quality is optimized by estimating the SINR at each point of the RF Map. Optimize power, Mobility, Neighbor List Table and other parameters to meet the target, such as average SINR>5dB, or/and CDF 10% data point SINR>5dB, or/and designated data point SINR>5dB, etc.

Please refer to Figure 6 to schematically illustrate the mobile network layer optimization method in this case. As shown in step S61, receiving and/or processing the mobile network system data from the mobile network system, that is, the mobile network system data is received and then processed and then stored, or the mobile network system data is received and stored, where The received data can be RF signals, and the processed data can be RF MAP; as shown in step S62, network parameters are initially optimized based on the received data and/or processed data to provide initial network parameters Value causes the mobile network system to operate, the mobile network system can maintain basic operation according to the initial values of the network parameters; as shown in step S63, continue to receive and/or continue to process the mobile network system data from the mobile network system. That is, when the mobile network system operates according to the initial value of the network parameters, it will continue to report the mobile network system data for continuous reception Then continue processing for storage, or continue to receive for storage, where the continuously received data can be mobile network system operating status, user identification, user measurement reports, etc., and the continued processing data can be KPIs; and As shown in step S64, according to at least a part of the received data, processed data, continuously received data, and continuously processed data, short-term network parameter optimization and long-term network parameter optimization are performed on the network parameters, and then Generate short-term optimization results of network parameters and long-term optimization results of network parameters, so that the mobile network system can operate according to the optimization results. Among them, the short-term optimization results of network parameters and the long-term optimization results of network parameters can cooperate with each other to decide when to start/stop Long-term optimization, when to start/stop short-term optimization.

In summary, the mobile network data processing module in this case can automatically interface or manually obtain mobile network data of the mobile network system, such as the operating status of the mobile network system (such as CM, PM, FM, KPI...) , User identification (such as location, service type, traffic volume, movement path...), user terminal measurement report (such as MR, MDT...), RF signal, base station equipment type (such as device model, firmware version) , Network parameter characteristics...), and has the ability to calculate RF Map and calculate custom/standard KPI capabilities. Secondly, the mobile network parameter optimization module in this case has a hierarchical network optimization concept and includes a network parameter initial value optimization module, a short-term network parameter optimization module, and a long-term network parameter optimization module. The optimization used The algorithm has the ability to perform network optimization based on the type of base station equipment, and has the ability to perform serviced-based and location-based optimization based on user identification. Thirdly, the data storage in this case can store CM, PM, FM, KPI, MR, MDT, user location, user service type, user traffic, user mobile path, RF Signal, RF Map, base station of mobile network system The ability of equipment type... and other information, and the ability to store the optimization results of the mobile network parameter optimization module. In addition, the mobile network system in this case can include user terminals, base stations, core networks, MEC, and network management systems. System...and other mobile network equipment.

The above-mentioned embodiments are only illustrative of the effects of the present case, and are not used to limit the present case. Anyone familiar with this technique can modify and change the above-mentioned implementation aspects without departing from the spirit and scope of the present case. Therefore, the scope of protection of the rights in this case should be listed in the scope of patent application described later.

1‧‧‧Mobile network system

2‧‧‧Mobile network level optimization system

21‧‧‧Data Storage

22‧‧‧Mobile network data processing module

23‧‧‧Mobile network parameter optimization module

Claims (12)

A mobile network hierarchical optimization system, which includes: a data storage; a mobile network data processing module, which receives and/or processes mobile network system data from the mobile network system to combine the received data and/or The processed data is stored in the data storage; and the mobile network parameter optimization module, based on the received data in the data storage and at least a part of the processed data, performs hierarchical optimization of the network parameters, The optimization result is stored in the data storage. The optimization result includes the initial value of the network parameter, the short-term optimization result of the network parameter, and/or the long-term optimization result of the network parameter. The initial values of network parameters enable the mobile network system to operate, and then short-term network parameter optimization and long-term network parameter optimization are performed on the network parameters. Such as the system described in item 1 of the scope of patent application, wherein the mobile network system data includes the operating status of the mobile network system including configuration management, performance management, obstacle management and/or wireless network key performance indicators, including location , Service type, traffic volume and/or user identification of mobile path, including user terminal measurement report and/or user terminal minimization drive test user data report, which is measured by user terminal measurement report, scanner measurement and/or The radio frequency signal obtained by the simulation estimation software, and/or the base station equipment type including the equipment model, firmware version and/or parameter characteristics. For example, in the system described in item 1 of the scope of patent application, the mobile network parameter optimization module includes: The network parameter initial value optimization sub-module is used before the base station is set up, according to the radio frequency signal in the received data stored in the data storage and/or the radio frequency map in the processed data, Preliminarily optimize the frequency, bandwidth, physical layer cell ID, random access channel, mobility, and/or neighbor cell list in the network parameters to provide the initial values of the network parameters to be based on the network parameters The initial values enable the mobile network system to operate; and the long-term network parameter optimization sub-module and the short-term network parameter optimization sub-module are used for the base station to be set up according to the received data stored in the data storage The data and the configuration management, performance management, obstacle management, wireless network key performance indicators, user terminal measurement reports, user terminal minimization drive test, user location, user service type, user signal demand in the processed data , Core network and/or multi-access edge computing to further optimize the network parameters to provide the long-term optimization results of the network parameters and the short-term optimization results of the network parameters respectively. For example, the system described in item 3 of the scope of patent application, wherein the long-term network parameter optimization sub-module optimizes network parameters that cannot be adjusted frequently and network parameters that require a long time to calculate. Network parameters include frequency, bandwidth, physical layer cell identification code, random access channel and/or mobility, and the network parameters that require a long time calculation include long-term user measurement reports and/or radio frequency mapping. And wherein, the short-term network parameter optimization sub-module optimizes network parameters that can be adjusted in real time, and the network parameters that can be adjusted in real time include cell individual offset, power, and/or neighbor cell list. For example, the system described in item 3 of the scope of patent application, wherein the short-term network parameter optimization sub-module detects whether the mobile network system is abnormal and detects whether the long-term network parameter optimization sub-module generates the The long-term optimization results of network parameters, and among them, the long-term network parameters The optimization sub-module detects whether the mobile network system is abnormal and detects whether the short-term network parameter optimization sub-module generates a short-term optimization result of the network parameters. For example, the system described in item 1 of the scope of patent application, wherein the mobile network data processing module processes the radio frequency signal in the received mobile network system data to obtain the radio frequency map before the base station is set up. And wherein, the mobile network data processing module processes the user terminal measurement reports in the received mobile network system data after the base station is launched to obtain radio frequency mapping, or to the received mobile network The user terminal measurement report and the RF signal in the road system data are processed to obtain the RF map. A method for optimizing the mobile network hierarchy includes: receiving and/or processing mobile network system data from the mobile network system; initial optimization of network parameters based on the received data and/or processed data to Provide initial values of network parameters to enable the mobile network system to operate according to the initial values of the network parameters; continue to receive and/or continue to process the mobile network system data from the mobile network system; and in accordance with the network parameters The initial value enables the mobile network system to operate and continue to receive and/or continue to process the mobile network system data from the mobile network system, and then based on the received data, the processed data, and the continuously received data And at least part of the data that has been continuously processed, short-term network parameter optimization and long-term network parameter optimization are performed on the network parameters. The method described in item 7 of the scope of patent application, wherein the short-term network parameter optimization and the long-term network parameter optimization are performed by event triggering, periodic triggering or normal operation. Such as the method described in item 7 of the scope of patent application, in which, Preliminary optimization of the network parameters includes: before the base station starts, according to the radio frequency signal in the received data and/or the radio frequency map in the processed data, the frequency, Initial optimization of bandwidth, physical layer cell identification code, random access channel, mobility, and/or neighbor cell list to provide initial values of the network parameters; and short-term network parameter optimization and long-term network parameter optimization for the network parameters The optimization of path parameters includes: after the base station is set up, the configuration management, performance management, obstacle management, and wireless management in the received data, the processed data, the continuously received data, and the continuously processed data are included. Network key performance indicators, user terminal measurement reports, user terminal minimization drive test, user location, user service type, user signal requirements, core network and/or multi-access edge computing to further optimize the network parameters . Such as the method described in item 7 of the scope of patent application, wherein the long-term network parameter optimization is to optimize the network parameters that cannot be adjusted frequently and the network parameters that require a long time to calculate, and the network parameters that cannot be adjusted frequently Including frequency, bandwidth, physical layer cell ID, random access channel and/or mobility, and the network parameters that require a long time calculation include long-term user measurement reports and/or radio frequency mapping, and among them, The short-term network parameter optimization is to optimize network parameters that can be adjusted in real time, and the network parameters that can be adjusted in real time include cell individual offset, power, and/or neighbor cell list. Such as the method described in item 7 of the scope of patent application, wherein the received data is a radio frequency signal measured by a scanner, the processed data is a radio frequency map, and the continuously received data is a mobile network system Operating status, user identification, and/or user measurement report, and the data that has been processed continuously is the key performance indicator of the wireless network. Such as the method described in item 7 of the scope of patent application, wherein the short-term network parameter optimization is performed based on the long-term network parameter optimization result of the long-term network parameter optimization, or the long-term network parameter optimization is performed based on The short-term network parameter optimization result of the short-term network parameter optimization.

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