CN111970719B - Method and device for evaluating quality of anchor point station in 5G NSA network - Google Patents
Method and device for evaluating quality of anchor point station in 5G NSA network Download PDFInfo
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Abstract
The invention relates to the field of communication, in particular to a method and a device for evaluating the quality of an anchor point station in a 5G NSA network. Mainly comprises the following steps: acquiring anchor point station quality index data; according to the evaluation dimension, selecting an evaluation factor to be evaluated from the quality index data; different weights are configured for each evaluation factor according to the evaluation service requirement; and calculating the weighted total score of each evaluation factor of the preset evaluation area according to the value and the weight of the evaluation factor, and taking the weighted total score as the quality score of the preset evaluation area. The invention can conveniently and accurately acquire the quality condition of each anchor point station, provides support for 5G NSA network optimization, and improves the user perception of 5G service users.
Description
[ field of technology ]
The invention relates to the field of communication, in particular to a method and a device for evaluating the quality of an anchor point station in a 5G NSA network.
[ background Art ]
The 5G standard is divided into two networking modes, namely Non-stand alone (NSA) and Stand Alone (SA), in order to realize a fast networking thought, a telecom operator selects an NSA architecture in the early stage of 5G networking and evolves to the SA architecture in the later stage. In NSA architecture, an anchor station is a channel of a 5G base station accessing a network, and the continuous coverage performance of the anchor network affects the mobility feeling of a user on the 5G network. In particular for 5G voice, it is implemented by VoLTE, employing anchor point bearers. If the anchor point continuous coverage performance is poor, the voice experience of the 5G user is possibly inferior to that of the existing network VoLTE, and the user experience is affected.
Currently, the anchor station quality assessment methods commonly used are: drive test, single station verification, network management monitoring, perceived quality assessment system (Deep Packet Inspection, abbreviated as DPI) and the like. The road test and the fixed-point test can only cover part of main roads, the road test cannot be implemented in special scenes or areas such as residential areas, parks, buildings and the like where the test vehicles are difficult to enter, the cost of the road test, such as manpower and vehicles, is high, and the road test is generally only applied in the initial stage of networking. Network management monitoring is more focused on the operation quality of network equipment, provides the service quality of the network from equipment parameter configuration and equipment performance evaluation, and is focused on KPI indexes, and the perception of user service cannot be embodied due to lack of KQI index evaluation. Moreover, the network management is mainly oriented to the equipment side, and the user level cannot be comprehensively monitored; on the other hand, the current network management monitoring is mainly applied to indexes in the aspect of operation and maintenance. However, as the service of the operator is gradually changed from the operation and maintenance to the operation, the operator starts to pay more attention to the service perception, and the network management monitoring cannot acquire the index corresponding to the service perception. DPI only covers core network data, and service awareness evaluation is calculated through the core network data, so that the result cannot comprehensively reflect or represent the quality of a wireless network and a transmission network.
In view of this, how to overcome the defects existing in the prior art, solve the phenomenon that the quality index of the anchor station cannot be obtained comprehensively and accurately conveniently in the existing quality evaluation of the anchor station, and is a problem to be solved in the technical field.
[ invention ]
Aiming at the defects or improvement demands of the prior art, the invention solves the problems that the current anchor point station quality evaluation method has insufficient coverage range of a drive test mode and higher cost, and a network management monitoring mode cannot acquire service perception indexes.
The embodiment of the invention adopts the following technical scheme:
in a first aspect, the present invention provides a method for evaluating quality of an anchor point station in a 5G NSA network, specifically: acquiring anchor point station quality index data; according to the evaluation dimension, selecting an evaluation factor to be evaluated from the quality index data; different weights are configured for each evaluation factor according to the evaluation service requirement; and calculating the weighted total score of each evaluation factor of the preset evaluation area according to the value and the weight of the evaluation factor, and taking the weighted total score as the quality score of the preset evaluation area.
Preferably, acquiring anchor point quality index data includes: and acquiring the anchor point station quality index data by one or more modes in a path measurement system, a fixed point test system, an integrated network management system, an MR and/or a perception index evaluation system.
Preferably, the evaluation dimension comprises a network quality of service dimension and/or a network traffic awareness dimension.
Preferably, a different weight is configured for each evaluation factor, including: selecting evaluation factors to be evaluated according to service requirements, and setting weights for each evaluation factor according to service characteristics; and selecting an evaluation index to be evaluated for each evaluation factor, and setting a weight for each evaluation index according to the service characteristics.
Preferably, calculating a weighted sum score of each evaluation factor of the preset evaluation area includes: calculating the weighted total score of all the evaluation indexes in each evaluation factor according to the value and the weight of each evaluation index, and taking the weighted total score of all the evaluation indexes as the value of the evaluation factor; and calculating the weighted total score of all the evaluation factors according to the value and the weight of each evaluation factor.
Preferably, calculating a weighted sum of all the evaluation factors of the preset evaluation region includes: presetting a reference value and a challenge value for each evaluation index in each evaluation factor; when the value of the first type of evaluation index is smaller than the reference value, calculating the evaluation index according to the preset lower limit value of the evaluation index; when the value of the first type of evaluation index is larger than or equal to the challenge value, calculating the evaluation index according to the preset upper limit value of the evaluation index; when the value of the second type of evaluation index is larger than the reference value, calculating the evaluation index according to the preset lower limit value of the evaluation index; and when the value of the second type of evaluation index is smaller than or equal to the challenge value, calculating the evaluation index according to the preset upper limit value of the evaluation index.
Preferably, when the evaluation dimension is a network quality of service dimension, one or more of terminal capability, coverage level, anchor point capacity, interference avoidance and anchor point performance are used as evaluation factors.
Preferably, when the evaluation dimension is a network traffic awareness dimension, one or more of the terminal, network, pipe and traffic are used as evaluation factors.
Preferably, when the terminal is used as an evaluation factor, the terminal is a 5G NSA terminal that has the same frequency as that of the 5G NSA base station for all anchor stations and 5G base stations in the area where the anchor priority scheme is implemented, and supports dual connectivity.
On the other hand, the invention provides a device for evaluating the quality of an anchor point station in a 5G NSA network, which specifically comprises the following steps: the method comprises the steps of connecting at least one processor with a memory through a data bus, wherein the memory stores instructions executed by the at least one processor, and the instructions are used for completing the quality assessment of an anchor point station under the 5G NSA network in the first aspect after being executed by the processor.
Compared with the prior art, the embodiment of the invention has the beneficial effects that: and acquiring data of a plurality of dimensions as evaluation factors, setting corresponding weights for the evaluation factors according to different services, and taking the weighted total score of the evaluation factors of the plurality of dimensions as a standard for quality evaluation of the anchor point station. By the quality evaluation mode, the quality condition of each anchor point station can be conveniently and accurately acquired, support is provided for 5G NSA network optimization, and user perception of 5G service users is improved.
[ description of the drawings ]
In order to more clearly illustrate the technical solution of the embodiments of the present invention, the drawings that are required to be used in the embodiments of the present invention will be briefly described below. It is evident that the drawings described below are only some embodiments of the present invention and that other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art.
Fig. 1 is a flowchart of a method for evaluating quality of an anchor point station in a 5G NSA network according to an embodiment of the present invention;
fig. 2 is a flowchart of another method for evaluating quality of an anchor station in a 5G NSA network according to an embodiment of the present invention;
fig. 3 is a flowchart of another method for evaluating quality of an anchor station in a 5G NSA network according to an embodiment of the present invention;
fig. 4 is an evaluation factor model used in a method for evaluating quality of an anchor station in a 5G NSA network according to an embodiment of the present invention;
fig. 5 is a schematic diagram of another evaluation factor model used in a method for evaluating quality of an anchor station in a 5G NSA network according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an apparatus for quality evaluation of an anchor station in a 5G NSA network according to an embodiment of the present invention.
[ detailed description ] of the invention
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The present invention is an architecture of a specific functional system, so that in a specific embodiment, functional logic relationships of each structural module are mainly described, and specific software and hardware implementations are not limited.
In addition, the technical features of the embodiments of the present invention described below may be combined with each other as long as they do not collide with each other. The invention will be described in detail below with reference to the drawings and examples.
The Option3 family has great advantages in quick 5G deployment, meanwhile, the commercial driving force of LTE upgrading to eLTE connected NGC is still to be further clarified, and in the Option3 family, the influence of the NR introduced by Option3x on the existing LTE network is minimum, and the performance is optimal. The 5GNR is a global 5G standard based on a brand new air interface design of OFDM, is also a very important cellular mobile technology base of the next generation, and the 5G technology can realize ultra-low time delay and high reliability. Option3x as a popular choice for NSA and Option2 as a popular choice for SA have become the first choice for most operators.
On one hand, the 5G NSA meets the construction requirement of the first 5G network, and on the other hand, the time for deploying the NGC core network, virtualizing and clouding reconstruction is saved. The Option3 xLTE eNB and the NR gNB adopt a double-connection mode, and the downlink peak rate of the user is obviously improved. NSA Option3x can formulate flexible shunt strategy according to 4G network load, and avoid causing the congestion of the existing 4G network while fully utilizing network resources. Under the NSA network, the user is born in the LTE network, and the mobility management multiplexes the existing mobility management of LTE. When the UE moves out of the NR coverage area, the data plane is not interrupted, and the LTE connection is maintained. Option3X needs to rely on the interconnection and interworking of an X2/Xn interface and LTE, and network upgrading and transformation needs corresponding LTE capacity matching and version matching, including that product realization meets the latest standard technical specification.
The networking of NSA and SA is mainly distinguished in that: NSA is to anchor 5G control signaling on a 4G base station, and the anchored base station is called an anchor station; the SA scheme is that a 5G base station is directly accessed to a 5G core network, and control signaling is completely independent of a 4G network. And a new core network is not needed under NSA standard, and the new 5G base station is accessed to the 4G core network or the 5G core network through the 4G base station. The 5G and the 4G can initiate service in the 4G and the 5G networks at the same time without interoperation, and the 5G terminal needs to access the 4G network at the same time and support 4G/5G double link.
In the NSA scheme, a user accesses the 5G base station and the 4G base station simultaneously in a double-connection mode, NAS signaling is transmitted by an anchor point station, user data flows are distributed in the 5G base station and the 4G base station, and 5G service is enjoyed through cooperation between the 5G base station and the 4G base station. The terms used therein are explained as follows:
(1) Double connection: the mobile terminal can communicate with both 4G and 5G simultaneously and can download data simultaneously. Typically there will be one master connection and at least one slave connection.
(2) Control plane anchor point: the responsible control plane in the dual connection is called the control plane anchor point.
(3) Shunt control point: the data of the user needs to be independently transmitted on two paths of the double connection, and the position for splitting is called a splitting control point.
Example 1:
in the NSA networking scenario, the existing network stock LTE base station is limited by the frequency range that can be supported by the NSA terminal, or other special factors, so that it is difficult to fully use the existing network stock LTE base station as an NSA anchor station. Once the NSA user accesses the non-anchor LTE base station, it will result in no NR auxiliary carrier being added, and thus no 5G service can be enjoyed. The core network connected with the Option 3X base station is a 4G core network, the control plane anchor point is arranged on the 4G base station, and the data distribution control point is arranged on the 5G base station. Because the anchor point is used as a signaling channel for the NSA terminal to access the network, a 4G frequency point with good network continuous coverage performance is selected as the anchor point. In order to select a proper NSA anchor point, the anchor point industrial chain end-to-end supporting condition and the estimated 4G network coverage condition are combined, and a 4G frequency point with good continuous coverage performance and high edge rate is selected as the anchor point. According to the method for evaluating the quality of the anchor point under the 5G NSA network, which is provided by the embodiment of the invention, the quality conditions of the anchor point are obtained by evaluating the quality of different dimensionalities of the anchor point, and data support is provided for optimization of the anchor point.
As shown in fig. 1, the method for evaluating the quality of an anchor point station in a 5G NSA network provided by the embodiment of the present invention specifically includes the following steps:
step 101: and acquiring the quality index data of the anchor point station.
The conventional quality evaluation method is generally performed by using only a single quality evaluation mode, and mainly used quality evaluation modes include drive test, single-station verification, network management monitoring, DPI and the like. The road test can intuitively reflect the communication quality of different areas, but only can cover part of main roads, and the road test cannot be implemented on the common streets or the roads where the test vehicles are difficult to drive in, such as areas of residents, parks, buildings, special scenes and the like, and is generally only used for optimizing the position of the base station in the initial stage of network construction, and the cost of the road test, such as manpower, vehicles and the like, is high. The network management is more focused on the operation quality of the network equipment, and evaluates the service quality provided by the network from the equipment parameter configuration and the equipment performance, wherein the evaluation emphasis is KPI (key point indicator) and is mainly applied to the operation and maintenance of the equipment. However, as operators gradually change from operation to maintenance, operators begin to pay more attention to service perception, and network management evaluation modes lack KQI index evaluation, so that the perception of user service cannot be reflected. And the network management is mainly oriented to the equipment side, so that the perception condition of the user cannot be comprehensively monitored. Measurement reports (Measurement Report, abbreviated MR) refer to the transmission of information on traffic channels once every 480ms (470 ms on signaling channels) of data that can be used for network evaluation and optimization. The DPI evaluation mode is used for performing service perception evaluation by collecting data through the DPI, and is mainly used for comprehensively evaluating service perception by setting different weights and index weights according to service types for key indexes in services such as accessing and browsing web pages, watching videos, sending/receiving instant messages, games and the like by a user, wherein the DPI has advantages in terms of signaling surface and service surface data, and the data comprises contents such as user information, terminal types, areas, network elements, base stations, access service types and the like. Therefore, the service can be perceptively evaluated according to different dimensions, but DPI only covers core network data, and the service perception evaluation is calculated through the core network data, so that the result can not comprehensively reflect or represent the quality of a wireless network and a transmission network, and an end-to-end service perception evaluation system can not be realized.
In the anchor point quality assessment method provided by the embodiment, various anchor point quality index data are acquired for quality assessment according to assessment dimensions and service requirements. In a specific embodiment of the present invention, according to different quality index data to be used, a method for acquiring quality index data of an anchor station includes: drive test, single station verification, integrated network management system, MR and DPI.
The quality index data acquired by the drive test and single-station verification mode comprises the following steps: (1) base coverage index: SS-RSRP, SINR, CSI-RSRP, SINR, CQI, coverage, CQI distribution statistics, beam level statistics measurements, etc. (2) throughput index: uplink and downlink average rate, uplink and downlink peak rate, PHY/MAC/RLC/PDCP layer rate distribution, etc. (3) a scheduling capability index: MCS statistics, RANK statistics, alert statistics, MIMO statistics, PDCCH statistics, etc.
The comprehensive network management system comprises a wireless network management part, a transmission network part, a core network management part and the like, and the acquired quality index data comprises the following components: (1) basic network metrics: uplink interference (cell RB uplink average interference level, cell RB uplink maximum interference level), transmission quality (transmission delay, transmission packet loss rate), channel quality (number of RBs used by the uplink MCS of 0-28 th order, number of RBs used by the downlink MCS of 0-28 th order), CQI, and the like. (2) network performance index: access class (SN addition success rate, SN addition average/maximum duration), maintenance class (SN abnormal release rate), mobility (handover success rate with SN leg), integrity class (RLC layer packet loss rate, MAC layer block error rate), etc. (3) network traffic metrics: resource class (number of PRBs occupied by uplink traffic channel, number of PRBs occupied by downlink traffic channel), traffic class (number of bytes of PDCP PDU of cell user plane uplink, number of bytes of PDCP PDU of cell user plane downlink), number of users (average number of terminal RRC connection, maximum number of terminal RRC connection), etc.
The quality index data acquired by the MR mode comprises a terminal and an eNodeB, wherein the terminal executes and reports the downlink level intensity, quality and TA of the eNodeB cell, and the eNodeB executes and reports the measurement of the receiving level intensity and quality of the uplink terminal.
The quality index data acquired by the DPI mode comprises the following steps: (1) a terminal: the core network obtains terminal access location, terminal capability, the number of terminal users, terminal traffic, terminal signaling index, terminal service index, etc. (2) accessing: NSA terminal access anchor station attachment success rate, attachment delay, etc. (3) reside: 5G service use duration residence ratio, 5G service flow residence ratio, etc. (4) switching: directional handoff, anchor station handoff, etc. (5) load: anchor station loading, non-anchor station loading, etc. (5) secondary station: NR site double connection establishment success rate, etc. (6) flow rate: anchor station traffic, NR station traffic, etc. (7) perception: and the service yield.
Step 102: and selecting the evaluation factor data to be evaluated from the quality index data according to the evaluation dimension.
Because the existing quality assessment methods have advantages and disadvantages, in order to better and comprehensively assess the quality of the anchor point, quality index data obtained by various modes is needed to be used to jointly establish a set of end-to-end perception assessment system comprising a wireless network, a transmission network and a core network. In a specific implementation process, multiple groups of evaluation indexes can be selected to be combined into multiple evaluation factors, evaluation of different aspects is performed on business perception, and each evaluation factor comprises one or more evaluation indexes.
In a specific implementation scenario of the present embodiment, the evaluation dimension generally includes a network quality of service dimension and a network traffic awareness dimension. In practical use, one dimension can be selected for evaluation according to factors such as service characteristics and acquired data, and comprehensive perception evaluation can be performed by using two evaluation dimensions at the same time so as to acquire more comprehensive perception data.
When network service quality is used as an evaluation dimension, one or more of coverage level, anchor point capacity, interference avoidance and anchor point performance are used as evaluation factors. Since the network service quality is normally positively correlated with the anchor station service quality perceived by the end user, the quality perceived by the end user can be indirectly estimated by the quality of the network service quality. In practical use, the evaluation index data may specifically include: obtained by the comprehensive network management system: coverage rate, uplink PRB utilization rate, downlink PRB utilization rate, RRC reestablishment success rate, call drop rate and the like; acquired by DPI: the same frequency, anchor station attachment success rate, handover success rate, etc.
When network traffic awareness is used as the evaluation dimension, one or more of the terminal, network, pipe, and traffic are used as the evaluation factors. The network service perception dimension can directly acquire the perception of the service quality of the anchor point by the user from the three aspects of occupation, residence and experience. In practical use, the evaluation index data may specifically include: and (3) a terminal: the number of 5G NSA terminals under the anchor point station, the state of terminal function switch and other conditions of attaching the anchor point station; network: analyzing network quality based on attachment, dual connectivity, cell user volume, performance, etc.; and (3) a pipeline: a service pipeline TCP quality analysis and the like; service: large bandwidth video quality of service analysis, and the like.
In the implementation scenario of this embodiment, only the 5G NSA terminal with the same frequency as the 5G NSA base station and supporting dual connectivity can access to the 5G NSA network, and only the data generated by this type of terminal has an evaluation value. Therefore, when the terminal is evaluated as an evaluation factor, only the data of the type of terminal is used for evaluation.
Further, when the terminal is used as an evaluation factor, the terminal is a 5G NSA terminal having the same frequency as the anchor station and supporting dual connectivity. After the NSA terminal must preempt the anchor point cell, the 5G service can be used to promote user perception, so that the NSA terminal needs to be migrated to the anchor point cell and stable occupation is ensured, which is an important subject to be solved at present.
Anchor points occupy 4 problems;
1. if the terminal occupies the non-anchor point, how to migrate from the non-anchor point to the anchor point in the connection state;
2. if the terminal occupies the non-anchor point, how to migrate from the non-anchor point to the anchor point in an idle state;
3. if the terminal already occupies the anchor point, how the connection state stably occupies the anchor point, and the premature switching to the non-anchor point is prevented;
4. if the terminal already occupies the anchor point, how to stably occupy the anchor point in the idle state, and the premature reselection to the non-anchor point is prevented. In the implementation scenario of this embodiment, the following anchor station priority schemes are generally used, mainly including: directional handover + directional reselection + NSA independent mobility policy + inhibit NSA load balancing.
(1) Directional switching:
1. and when the NSA terminal is accessed in the non-anchor point cell, initiating directional switching to the anchor point cell.
2. And when the NSA terminal is switched in the non-anchor point cell, initiating directional switching to the anchor point cell.
3. And when the NSA terminal does VoLTE service at a non-anchor point, the initiation of directional switching is forbidden.
4. And after the NSA terminal finishes VoLTE service at the non-anchor point, initiating directional switching to the anchor point cell.
(2) Directional reselection:
when the NSA terminal is released in the non-anchor cell, the rrcConnectionRelease message carries the anchor frequency point and is set to the highest priority, so that the terminal can be guided to the anchor frequency point.
When the NSA terminal is released in the anchor cell, the rrcConnectionRelease message carries the anchor frequency point and is set to the highest priority, so that the terminal can be guided to the anchor frequency point.
(3) Mobility policy:
the NSA terminal connection strategy is that a non-anchor cell is easy to switch to an anchor cell, the anchor cell is difficult to switch to the non-anchor cell, and the anchor cell ensures smooth switching.
(4) Inhibit NSA terminal load balancing configuration:
when the NSA terminal occupies the anchor point cell, the NSA terminal is forbidden to be balanced to other frequency points.
Step 103: and configuring different weights for each evaluation factor data according to the evaluation service requirements.
In the anchor point quality evaluation method provided in this embodiment, multiple quality index data are used to evaluate quality. According to different equipment scenes, service scenes and evaluation dimensions, different quality index data have different influence degrees on the service quality perceived by the terminal, so that different weights are required to be configured for the evaluation factors in the quality index data when quality evaluation is carried out.
Further, since more than one evaluation index may be included in each evaluation factor, the degree of influence of each evaluation index on the evaluation factor is also different. Therefore, in a specific use scene, not only can weights be set for different assessment factors to improve accuracy of quality assessment, but also different weights can be set for assessment indexes in each assessment factor to further distinguish the influence degree of different assessment indexes on quality perception. Specifically, as shown in fig. 2, in actual use, different weights may be configured for each evaluation factor by:
step 201: and selecting the evaluation factors to be evaluated according to the evaluation dimension, and setting a weight for each evaluation factor according to the service characteristics.
Step 202: and selecting an evaluation index to be evaluated for each evaluation factor, and setting a weight for each evaluation index according to the service characteristics.
Through the two-pole weight distribution in the step 201 and the step 202, the influence degree of different evaluation indexes and evaluation factors on service perception can be distinguished more accurately, and the evaluation accuracy is improved. In the specific implementation scenario of this embodiment, the number of stages of weight distribution is not limited to two, and can be adjusted according to actual needs, only one stage can be used when the evaluation indexes are fewer, and the evaluation indexes can be further grouped into more stages such as evaluation sub-factors for weight setting when the evaluation indexes and the evaluation factors are more, so that the evaluation accuracy is further improved.
Step 104: and calculating the weighted total score of each evaluation factor data of the preset evaluation area according to the value and the weight of the evaluation factor data, and taking the weighted total score as the quality score of the preset evaluation area.
After the weight is set for each evaluation factor, a weighted sum can be calculated for the obtained values of the evaluation factors, and the weighted sum is used as a score of the quality of the preset evaluation area, and the quality of the anchor point is evaluated according to the quality score.
Further, in some specific usage scenarios of the present embodiment, weights are also set for the evaluation indexes in each evaluation factor, and when calculating the value of the evaluation factor, it is necessary to calculate the weighted total score of all the evaluation indexes in each evaluation factor as the value of the evaluation factor.
In some embodiments of the present invention, the values of some evaluation factors or evaluation indexes may be far below normal values or far above abnormal values due to factors such as measurement limits or errors. In order to avoid that the value of the abnormal value deviates too much from the normal value, and affects the calculation result of the quality score, the lower limit of the normal value may be set as the reference value, and the upper limit of the normal value may be set as the challenge value. According to different evaluation index properties, the evaluation indexes are divided into two types: (1) a first type of evaluation index: calculating values lower than the reference value according to a preset lower limit value, and calculating values higher than the challenge value according to a preset upper limit value, such as a success rate index, a downloading rate index and the like; (2) a second type of evaluation index: for example, the time delay, retransmission rate, fragmentation rate index, etc., all values higher than the reference value are calculated according to a preset lower limit value, and all values lower than the challenge value are calculated according to a preset upper limit value. By the above processing, the influence of the specific value of the outlier on the quality score is reduced. As shown in fig. 3, the calculation can be performed by the following steps.
Step 301: a reference value and a challenge value are preset for each evaluation index data in each evaluation factor.
Step 302: judging the type of the evaluation index as a first type evaluation index or a second type evaluation index.
Step 303: and when the value of the first type of evaluation index is smaller than the reference value, calculating the evaluation index according to the preset lower limit value of the evaluation index.
Step 304: and when the value of the first type of evaluation index is larger than or equal to the challenge value, calculating the evaluation index according to the preset upper limit value of the evaluation index.
Step 305: and when the value of the second type of evaluation index is larger than the reference value, calculating the evaluation index according to the preset lower limit value of the evaluation index.
Step 306: and when the value of the second type of evaluation index is smaller than or equal to the challenge value, calculating the evaluation index according to the preset upper limit value of the evaluation index.
Through steps 301-306, according to the characteristics of different evaluation indexes, the influence of abnormal values on the perception evaluation result is eliminated through the reference value and the challenge value, and the evaluation result deviation caused by the fact that the absolute value of the evaluation index is too large or too small is avoided.
After steps 101-104 provided in this embodiment, the quality index of the anchor station may be evaluated by the quality index data of multiple evaluation dimensions. The problems of difficulty in implementation, difficulty in data acquisition, one-sided evaluation result and the like of various quality evaluation modes at present are avoided, and the perceived quality of an anchor point station can be comprehensively and accurately evaluated, and can be used as the basis for selecting a 5G NSA anchor point station or the evaluation basis of other service qualities.
Example 2:
in some specific embodiments, the method for evaluating the quality of the anchor station under the 5G NSA network provided in embodiment 1 may be implemented through the evaluation system model provided in this embodiment.
The evaluation system model evaluation used in the embodiment mainly uses terminal, coverage, capacity, interference, performance and other evaluation factors to perform the perception evaluation of anchor station quality on the network service quality dimension.
According to step 102, the evaluation factors to be evaluated are selected, and the evaluation principle of each evaluation factor is as follows:
terminal capability: obtained by DPI. The NSA terminal does not necessarily support all LTE frequency points of the existing network. So the main stream NSA terminal capability information needs to be selected when NSA anchor planning.
Coverage level: obtained through wireless network management data and a network management system. 1) NSA anchor points must be made coverage continuous, otherwise NR cannot be added in areas without anchor point coverage. 2) NSA anchor points supported by commercial terminals are limited, and for anchor points supported by main stream terminals, even if current coverage is poor, the anchor points must be used as high-priority anchor points, and capacity expansion and blind supplement are needed if necessary.
Anchor capacity: obtained by DPI. Including upstream capacity and downstream capacity. 1) Uplink capacity: it is suggested to prioritize the upstream capacity of the anchor point because 5G upstream is easily limited and there is a greater demand for upstream offloading. 2) If the downlink split needs to be started, the frequency point with large downlink capacity needs to be selected as the anchor point with high priority. If the LTE current network turns on the DL CA, the combined capability of the terminal NSA DC and the LTE CA needs to be considered. But there is no specific terminal capability information at this stage, so this factor is temporarily not considered. If the LTE current network does not open the DL CA, the LTE frequency point with higher downlink capacity of the single frequency point needs to be preferentially selected as an NSA high-priority anchor point.
Interference avoidance: obtained through wireless network management data. It is desirable to avoid harmonic/intermodulation interference. Certain lte+nr frequency band combinations present a risk of harmonic/intermodulation interference, such as (LTE1.8G + NR3.5G) (LTE2.6G + NR4.9G). Priority of LTE frequency points with interference risk is suggested to be reduced when planning NSA anchor points. Specifically, whether the interference risk exists or not is based on the calculation result of the actual formula.
Coupling of mobility policies: and obtaining through network management data. 1) The SRAN 15.0 LTE unnecessary mobile strategy is not decoupled from NSA, the common mobile strategy is CA PCC anchor point strategy/MLB, and if the tendency frequency point of the unnecessary mobile strategy is not configured as NSA anchor point, the risk that NR cannot add exists. Therefore, the prone frequency points of the unnecessary mobility strategy of the LTE existing network are suggested to be used as NSA anchor points, such as target frequency points of MLB. 2) For the necessary handover strategy of LTE, NSA users are required to adhere to, otherwise there is a risk of dropped calls.
Anchor base performance: obtained through a network management system. If the basic performance (including access, switching success rate, call drop rate, RRC reestablishment ratio and ping-pong switching times) of each frequency point of the LTE current network has large difference, the frequency point with poor basic performance is difficult to optimize and promote. Then the frequency point with good basic performance needs to be preferentially selected as the NSA high priority anchor point.
The evaluation index used in each evaluation factor includes:
1. same frequency: and supporting the terminal duty ratio of the same frequency as the cell frequency of the base station by all the terminal types under the cell in a certain time period.
2. Coverage rate: coverage is defined as the percentage of test points with an F value of 1 among all test points in the test area. Wherein: RSRP represents the downlink pilot signal received power; SINR represents the signal quality of the received pilot signal; RSRP.gtoreq.R and RSRQ.gtoreq.gtoreq.S indicate whether the condition is satisfied, R and S being thresholds for RSRP and RSRQ in the calculation. If RSRP is greater than or equal to R and RSRQ is greater than or equal to S, F takes value 1, and if one is not satisfied or neither is satisfied, F takes value 0.
3. Uplink PRB utilization rate and downlink PRB utilization rate:
TTI PUSCH PRB utilization = number of PUSCH PRB usage per TTI/total number of PUSCH PRBs per TTI.
TTI PDSCH PRB utilization = number of PDSCH PRB usage per TTI/total number of PDSCH PRBs per TTI.
4. Interference ratio: MR RIP > = -105dBm of sampling duty cycle.
5. Anchor station attachment success rate: anchor station attachment success number/anchor station attachment request number x 100%.
6. Switching success rate (X2 in, X2 out, S1 in, S1 out):
x2 hand-in success rate = X2 hand-in success times/X2 hand-in attempt times X100%.
X2 success rate = X2 success rate per X2 attempt rate X100%.
S1 hand-in success rate = S1 hand-in success times/S1 hand-in attempt times x 100%.
S1 cut success rate = S1 cut success number/S1 cut attempt number x 100%.
7. The disconnection rate: E-RAB drop rate = (number of E-RABs requested to be released by the eNodeB for exception reasons + number of E-RABs requested to be released by the eNodeB for exception reasons contained in UE context)/number of E-RABs establishment success x 100%.
8. Success rate of RRC reestablishment: RRC reestablishment success rate = number of RRC reestablishment success/number of RRC reestablishment attempts (service related) ×100%.
According to step 103, as shown in fig. 4, weights are set for the evaluation factors and the evaluation indexes, the weights of the respective evaluation factors and the weights of the evaluation indexes therein are as shown in table 1, wherein the weights, the reference values and the challenge values can be adjusted according to actual experience.
TABLE 1
The weighted total score of the assessment factors is calculated as a quality score of the assessment area, per step 104.
In order to obtain the quality score more accurately, the value of the evaluation index may not be directly used, but the score of each evaluation index may be calculated using the following formula.
The same frequency, coverage, and success rate indicator scores were calculated using equation 1:
Calculating the utilization rate, the interference rate and the dropping rate index score by using a formula 2:
and calculating the value of the evaluation index through the formula, and calculating the weight of the evaluation index and the evaluation factor to acquire the quality score of the anchor point in the evaluation area.
Example 3:
in some specific implementations, the method for evaluating the quality of the anchor station under the 5G NSA network provided in embodiment 1 may be implemented through another evaluation system model provided in this embodiment.
The evaluation system model evaluation used in the embodiment mainly starts from three aspects of occupation, residence and experience, uses four evaluation factors of a terminal, a network, a pipeline and a service to perform perception evaluation, and performs comprehensive perception evaluation of anchor station quality on network service quality dimension and network service perception dimension.
According to step 102, the evaluation factors to be evaluated are selected, and the evaluation principle of each evaluation factor is as follows:
and (3) a terminal: the number of 5G NSA terminals under the anchor station, the switching state of the terminal function and other conditions of the attached anchor station.
Network: network quality is analyzed based on attachment, dual connectivity, cell user volume, performance, etc.
And (3) a pipeline: based on analysis of traffic pipe TCP quality, etc.
Service: based on large bandwidth video quality of service, etc.
The evaluation index and the calculation method of the index used in each evaluation factor are as follows:
number of 5G terminals: obtained by DPI. And counting all the number of users of 5G terminals in the network by 4G and 5G signaling.
Number of 5G networks attached to 5G terminal: obtained by DPI. The number of 5G terminal users attached to the 5G network.
5G terminal attached 5G network duty cycle: obtained by DPI. [ number of 5G terminals attached to 5G network ]/[ number of 5G terminals ].
Reporting the total amount of 5G terminals in the 5G switch state: obtained by DPI. The reported number of terminals with dual connectivity.
Number of 5G terminals with 5G switch on: obtained by DPI. The number of terminals that are switched on in the reported dual connectivity terminals.
5G terminal 5G switch on duty cycle: [ number of 5G terminals with 5G switch on ]/[ total number of 5G terminals reporting 5G switch status ].
Anchor station 5G terminal attachment success rate: obtained by DPI. [ number of atach successes ]/[ number of atach requests ], the statistical range is: 1. 5G terminal, identifying based on a 5G terminal library; 2. the 4G anchor station is based on an anchor station configuration table.
ERAB modification indicates success rate: obtained by DPI. [ number of E-RAB modification successes ]/[ number of E-RAB modification requests ], E-RAB modification indicates number of successes: counting the number of E-RAB MODIFICATION CONFIRM messages; E-RAB modification indicates the number of requests: the cumulative number of E-RAB MODIFICATION INDICATION messages was counted.
Success rate of SgNB addition: obtained through a comprehensive network management system. [ number of successful SgNB addition ]/[ number of SgNB addition request ].
Anchor RRC connection establishment success rate: obtained through a comprehensive network management system. [ number of RRC connection establishment successes ]/[ number of RRC connection establishment requests ].
Area 5G access number dwell ratio: obtained by DPI. Calculating in a 5G coverage area, wherein the 5G access frequency residence ratio is = [5G terminal access frequency in 5G network service/[ 5G terminal access frequency in 5G network service +5G terminal access frequency in 4G network service ]; the 5G coverage area statistical range is for all anchor stations and 5G stations within the area where the anchor priority scheme was implemented.
Zone 5G traffic residence ratio: obtained by DPI. Calculating in a 5G coverage area, wherein the 5G traffic residence ratio= [5G terminal at 5G network traffic ]/[5G terminal at 5G network traffic+5G terminal at 4G network traffic ]; the 5G coverage area statistical range is for all anchor stations and 5G stations within the area where the anchor priority scheme was implemented.
Area 5G duration dwell ratio: obtained by DPI. Calculating in a 5G coverage area, wherein the 5G flow residence ratio is = [5G terminal in 5G network service duration ]/[5G terminal in 5G network service duration+5G terminal in 4G network service duration ]; the 5G coverage area statistical range is for all anchor stations and 5G stations within the area where the anchor priority scheme was implemented.
SN abnormal release rate (drop rate): obtained through a comprehensive network management system. 1- [ number of SN normal release requests ]/[ number of SN release requests ].
SN handover success rate: obtained through a comprehensive network management system. [ number of SN handover successes ]/[ number of SN handover requests ].
Anchor point wireless disconnection rate: obtained through a comprehensive network management system. [ number of abnormal eNodeB requests for release ]/[ number of eNodeB requests for release ].
Video download rate: obtained by DPI. Streaming media packet download amount/streaming media download duration; streaming media packet download amount: the SP sends an HTTP Reply 200OK message to the terminal and the SP sends a data downloading amount between the HTTP Reply 200OK message and the finish TCP data ack message to the terminal; streaming media download duration: the SP sends an "HTTP Reply 200OK" message to the terminal to the time when the SP sends an "finish TCP data ack" message to the terminal.
Rate-to-code ratio: obtained by DPI. Video effective download rate/code rate; effective download rate = Streaming effective document Streaming application layer download amount/(Streaming download total duration-no data packet data transmission duration).
Initial buffer success rate: obtained by DPI. The initial buffer success number/initial buffer request number is 100.
Initial buffering delay: obtained by DPI. Initial buffering total delay/initial buffering success times.
Video clip rate: obtained by DPI. The number of jams/initial buffer successes is 100.
Video clip duration ratio: obtained by DPI. The sum of buffering time length/initial buffering success times in playing is 100.
And (5) transmitting the uplink effective rate: obtained by DPI. [ push stream load ]/[ streaming media download duration ].
Pull-down rate (kbps): obtained by DPI. [ downstream flow under pull ]/[ downstream transmission duration ].
TCP 12-way handshake success rate: obtained by DPI. TCP SYN ACK times/TCP SYN times 100%.
TCP23 handshake success rate: obtained by DPI. TCP ACK times/TCP SYN ACK times 100%.
TCP12 handshake delay: obtained by DPI. TCP SYN ACK times-the sum of TCP SYN times/TCP SYN ACK times,
TCP 23-way handshake delay: obtained by DPI. The sum of TCP ACK time-TCP SYN ACK time/TCP ACK times.
TCP uplink retransmission rate: obtained by DPI. The number of TCP uplink retransmission packets/the number of uplink packets is 100%.
TCP downlink retransmission rate: obtained by DPI. The number of TCP downlink retransmission packets/number of downlink packets is 100%.
TCP uplink disorder rate: obtained by DPI. The number of TCP uplink out-of-order packets/uplink packet number is 100%.
TCP downlink disorder rate: obtained by DPI. TC; p number of out-of-order packets per number of downlink packets is 100%.
Average utilization of uplink PRB: obtained through a comprehensive network management system. And counting the average utilization rate of the cell uplink PRB in the period.
Average utilization of downlink PRB: obtained through a comprehensive network management system. And counting the average utilization rate of the cell downlink PRB in the period.
Uplink interference noise (average): obtained through a comprehensive network management system. Uplink average interference level.
Average number of users (RRC connection): obtained through a comprehensive network management system. And counting the average number of RRC connection users in the period.
Anchor paging congestion rate: obtained through a comprehensive network management system. Number of page drops/number of page requests.
Anchor point coverage: obtained by an integrated MR system. Coverage is defined as the percentage of test points with an F value of 1 among all test points in the test area.
According to step 103, as shown in fig. 5, weights are set for the evaluation factors and the evaluation indexes, the weights of the respective evaluation factors and the weights of the evaluation indexes therein are as shown in table 2, wherein the weights, the reference values and the challenge values can be adjusted according to actual experience. Because the model provided in this embodiment has more evaluation index values, when the weights are set, not only the two levels of the evaluation factors and the evaluation indexes provided in embodiment 1 and embodiment 2 are set, but also the level of the evaluation sub-factor is added in part of the evaluation factors.
TABLE 2
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The weighted total score of the assessment factors is calculated as a quality score of the assessment area, per step 104.
In order to obtain the quality score more accurately, the value of the evaluation index may not be directly used, but the score of each evaluation index may be calculated using the following formula.
Calculating scores for the number, duty cycle, coverage, success rate, and rate indicators using equation 3:
calculating scores of the indexes of the utilization rate, the retransmission rate, the dropped wire rate, the congestion rate, the jamming duration ratio, the time delay and the interference noise by using a formula 4:
and calculating the value of the evaluation index through the formula, and calculating the weight of the evaluation index and the evaluation factor to acquire the quality score of the anchor point in the evaluation area.
The evaluation system model provided in this embodiment is comprehensively compared with the evaluation system model in embodiment 2, and the evaluation system model in this embodiment is superior to the evaluation system model in embodiment 2 in that the dimension of the evaluation system model in this embodiment is finer and the coverage is wider, and has the value of end-to-end quality evaluation.
Example 4:
on the basis of the method for evaluating the quality of the anchor point under the 5G NSA network provided in the foregoing embodiments 1 to 3, the present invention further provides a device for evaluating the quality of the anchor point under the 5G NSA network, as shown in fig. 6, which is a schematic device architecture diagram of an embodiment of the present invention. The apparatus for evaluating quality of an anchor station under a 5G NSA network of the present embodiment includes one or more processors 21 and a memory 22. In fig. 6, a processor 21 is taken as an example.
The processor 21 and the memory 22 may be connected by a bus or otherwise, for example in fig. 6.
The memory 22 is used as a non-volatile computer readable storage medium for storing a non-volatile software program, a non-volatile computer executable program, and a module for performing the method for evaluating the quality of an anchor station in a 5G NSA network according to embodiments 1 to 3. The processor 21 performs various functional applications and data processing of the apparatus for anchor station quality assessment under the 5G NSA network, that is, the method for anchor station quality assessment under the 5G NSA network of embodiments 1 to 3, by running the nonvolatile software programs, instructions and modules stored in the memory 22.
The memory 22 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, memory 22 may optionally include memory located remotely from processor 21, which may be connected to processor 21 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
Program instructions/modules are stored in the memory 22 that, when executed by the one or more processors 21, perform the method of anchor station quality assessment under a 5G network in embodiments 1-3 described above, e.g., perform the various steps shown in fig. 1, 2 and 3 described above.
Those of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the embodiments may be accomplished by a program that instructs associated hardware, the program may be stored in a computer readable storage medium, the storage medium may comprise: read Only Memory (ROM), random access Memory (RAM, random Access Memory), magnetic or optical disk, and the like.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (4)
1. A method for evaluating the quality of an anchor station in a 5G NSA network is characterized by comprising the following steps:
acquiring anchor point station quality index data by one or more modes of drive test, single station verification, comprehensive network management system, MR and DPI;
the network service quality dimension and/or the network service perception dimension are used as evaluation dimensions, and evaluation factors needing to be evaluated are selected from the quality index data; when the network service quality is taken as an evaluation dimension, one or more of coverage level, anchor point capacity, interference avoidance and anchor point performance are taken as evaluation factors; when network service perception is taken as an evaluation dimension, one or more of a terminal, a network, a pipeline and a service are taken as evaluation factors;
Selecting at least one level of evaluation factors to be evaluated according to service requirements, and setting weights for each evaluation factor according to service characteristics; selecting an evaluation index to be evaluated for each evaluation factor, and setting a weight for each evaluation index according to the service characteristics;
calculating a weighted total score of each evaluation factor of a preset evaluation area according to the values and weights of the evaluation factors and the evaluation indexes, and taking the weighted total score as a quality score of the preset evaluation area;
when a terminal is used as the evaluation factor, determining whether the terminal initiates directional switching to an anchor point cell according to the access state of the terminal in a non-anchor point cell or the VoLTE service state, setting an anchor frequency point carried in a rrcConnectionRelease message when the terminal is released in the non-anchor point cell as the highest priority for directional reselection, ensuring that the non-anchor point cell is easier to switch to the anchor point cell but the anchor point cell is harder to switch to the non-anchor point cell according to an NSA independent mobility policy, prohibiting NSA terminal load balancing to other frequency points by using a policy prohibiting NSA load balancing, selecting an anchor point station based on the policies of directional switching, directional reselection, NSA independent mobility policy and prohibiting NSA load balancing, and using a 5G NSA terminal which has the same frequency as the anchor point station and supports dual-connection capability as the evaluation factor;
Acquiring the evaluation factor of the current pipeline based on a service pipeline TCP quality analysis when the pipeline is used as the evaluation factor;
when using the network as the evaluation factor, the network quality is analyzed based on one or more of the attach, dual connectivity, cell user volume and performance, with the analysis result being the evaluation factor of the current network.
2. The method for quality assessment of anchor stations in a 5G NSA network according to claim 1, wherein the calculating a weighted sum of the assessment factors of the preset assessment area includes:
calculating the weighted total score of all the evaluation indexes in each evaluation factor according to the value and the weight of each evaluation index, and taking the weighted total score of all the evaluation indexes as the value of the evaluation factor;
and calculating the weighted total score of all the evaluation factors according to the value and the weight of each evaluation factor.
3. The method for quality assessment of anchor stations under a 5G NSA network according to claim 1, wherein the calculating a weighted sum of all assessment factors of a preset assessment area includes:
presetting a reference value and a challenge value for each evaluation index in each evaluation factor;
when the value of the first type of evaluation index is smaller than the reference value, calculating the evaluation index according to the preset lower limit value of the evaluation index;
When the value of the first type of evaluation index is larger than or equal to the challenge value, calculating the evaluation index according to the preset upper limit value of the evaluation index;
when the value of the second type of evaluation index is larger than the reference value, calculating the evaluation index according to the preset lower limit value of the evaluation index;
and when the value of the second type of evaluation index is smaller than or equal to the challenge value, calculating the evaluation index according to the preset upper limit value of the evaluation index.
4. An apparatus for evaluating quality of an anchor station in a 5G NSA network, wherein the apparatus is characterized by:
comprising at least one processor and a memory connected by a data bus, the memory storing instructions for execution by the at least one processor, the instructions, when executed by the processor, for performing the method of anchor station quality assessment under a 5G NSA network according to any one of claims 1-3.
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