CN113115325B - Wireless network quality optimization method and device - Google Patents

Wireless network quality optimization method and device Download PDF

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CN113115325B
CN113115325B CN202010028238.0A CN202010028238A CN113115325B CN 113115325 B CN113115325 B CN 113115325B CN 202010028238 A CN202010028238 A CN 202010028238A CN 113115325 B CN113115325 B CN 113115325B
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rsrp
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interference
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CN113115325A (en
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朱震海
李戈
李容荣
陈俣兵
李伟
蒋翊生
林竹轩
安久江
周红刚
齐高远
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China Mobile Communications Group Co Ltd
China Mobile Group Design Institute Co Ltd
China Mobile Group Zhejiang Co Ltd
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China Mobile Group Design Institute Co Ltd
China Mobile Group Zhejiang Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/318—Received signal strength
    • H04B17/327—Received signal code power [RSCP]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/336—Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/373—Predicting channel quality or other radio frequency [RF] parameters
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/08—Testing, supervising or monitoring using real traffic

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Abstract

The embodiment of the invention provides a wireless network quality optimization method and a wireless network quality optimization device, wherein the method comprises the following steps: if at least one of the working parameters and the mobility parameters of the cell is adjusted, determining the home of the main service cell of the changed drive test sampling point; calculating a predicted SINR according to the interference type, the noise acquired in advance, the type of the adjustment parameter and whether the home of the main service cell changes; and establishing a corresponding relation between the adjustment quantity of the adjustment parameter and the increment of the predicted SINR, determining a target adjustment quantity of the adjustment parameter according to the corresponding increment of the optimized target value and the corresponding relation, and optimizing the quality of the wireless network according to the target adjustment quantity. The device performs the above method. According to the method and the device for optimizing the quality of the wireless network, the predicted SINR is calculated according to the noise, the type of the adjustment parameter and whether the home of the main service cell changes, which are obtained in advance, so that the quality of the wireless network is optimized.

Description

Wireless network quality optimization method and device
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a method and an apparatus for optimizing quality of a wireless network.
Background
In the network optimization work of the LTE wireless network covering line scenes such as high-speed rails, high-speed bridges, and the like, for the optimization of the problem of Reference Signal Receiving Power (RSRP) difference or Signal to Interference plus Noise Ratio (SINR) difference possibly caused by the network coverage in the network, the current main optimization means is: the optimization engineer adjusts the parameters of the worker or the mobility parameters according to the current network data such as MR, DT test, sweep frequency test and the like and the experience of the optimization engineer; after adjustment, whether the problem of RSRP difference or SINR difference is solved is determined through MR, DT test, frequency sweep test and the like; if the problem is not solved or the expected effect is not achieved, the work parameter or the mobility parameter is probably needed to be adjusted again, whether the RSRP difference or the SINR difference problem is solved or not is determined through MR, DT test, frequency sweep test and the like, and through the repeated process, not only is the optimization work efficiency low, but also the optimization cost is greatly improved.
Disclosure of Invention
Aiming at the problems in the prior art, the embodiment of the invention provides a wireless network quality optimization method and a wireless network quality optimization device.
The embodiment of the invention provides a wireless network quality optimization method, which comprises the following steps:
if at least one of the working parameters and the mobility parameters of the cell is adjusted, determining the home of the main service cell of the changed drive test sampling point;
calculating a predicted SINR according to the interference type, the noise acquired in advance, the type of the adjustment parameter and whether the home of the main service cell changes;
and establishing a corresponding relation between the adjustment quantity of the adjustment parameter and the increment of the predicted SINR, determining a target adjustment quantity of the adjustment parameter according to the corresponding increment of the optimized target value and the corresponding relation, and optimizing the quality of the wireless network according to the target adjustment quantity.
The type of the adjustment parameter comprises adjusting the cell parameters and the home of the main service cell is not changed; correspondingly, the calculating and predicting SINR according to the interference type, the pre-obtained noise, the type of the adjustment parameter, and whether the home of the primary serving cell changes includes:
calculating the predicted SINR according to the following formula:
Figure BDA0002363250870000021
wherein, the SINR Improvement of For the predicted SINR, RSRP Cell _0_ change Predicted RSRP for primary serving cell, RSRP cell _1_ change Predicting RSRP and RSRP of non-modular three-interference neighbor cell after work parameter adjustment cell_i Testing RSRP and RSRP of non-modular three-interference neighbor cell without work parameter adjustment Cell _2_ modified Prediction RSRP and RSRP of modular three-interference neighbor cell after working parameter adjustment Cell_j In order to test the RSRP of the interference neighborhood without the working parameter adjustment mode three, S1 represents a first correlation coefficient, S2 represents a second correlation coefficient, and N represents noise.
The type of the adjustment parameter comprises adjusting cell parameters and changing the home of a main service cell; correspondingly, the calculating and predicting SINR according to the interference type, the pre-obtained noise, the type of the adjustment parameter, and whether the home of the primary serving cell changes includes:
calculating the predicted SINR according to the following formula:
Figure BDA0002363250870000022
wherein, the SINR Improvement of To predict SINR, RSRP cell _1_ change Predicted RSRP and RSRP for switching original neighbor cell into current main service cell after work parameter adjustment Cell _0_ change After the working parameters are adjusted, the original main service cell is switched into the predicted RSRP and the RSRP of the current non-mode three-interference neighbor cell cell_i Testing RSRP and RSRP of non-modular three-interference neighbor cell without work parameter adjustment Cell _2_ modified Prediction RSRP and RSRP of modular three-interference neighbor cell after working parameter adjustment Cell_j In order to test the RSRP of the interference neighborhood without the working parameter adjustment mode three, S1 represents a first correlation coefficient, S2 represents a second correlation coefficient, and N represents noise.
The types of the adjustment parameters comprise that the working parameters of the cell are not adjusted, the mobility parameters of the cell are adjusted, and the home of the main service cell is changed; correspondingly, the calculating and predicting SINR according to the interference type, the pre-obtained noise, the type of the adjustment parameter, and whether the home of the primary serving cell changes includes:
calculating the predicted SINR according to the following formula:
Figure BDA0002363250870000031
wherein, the SINR Improvement of Is the predicted SINR, RSRP' scell Test RSRP, RSRP of Primary serving cell' Ncell_i Test RSRP and RSRP of non-mode three-interference neighbor cell' Ncell_j The RSRP of the test of the interference neighborhood of the mode three is S1, the first correlation coefficient is S2, the second correlation coefficient is S2, and the noise is N.
The embodiment of the invention provides a wireless network quality optimization device, which comprises:
the determining unit is used for determining the home of the main service cell of the changed drive test sampling point if at least one of the work parameter and the mobility parameter of the cell is adjusted;
a calculating unit, configured to calculate a predicted SINR according to the interference type, the pre-obtained noise, the type of the adjustment parameter, and whether the home of the primary serving cell changes;
and the optimizing unit is used for establishing a corresponding relation between the adjustment quantity of the adjustment parameter and the increment of the predicted SINR, determining a target adjustment quantity of the adjustment parameter according to the corresponding increment of the optimized target value and the corresponding relation, and optimizing the quality of the wireless network through the target adjustment quantity.
An embodiment of the present invention provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein,
the processor, when executing the computer program, implements the method steps of:
if at least one of the working parameters and the mobility parameters of the cell is adjusted, determining the home of the main service cell of the changed drive test sampling point;
calculating a predicted SINR according to the interference type, the noise acquired in advance, the type of the adjustment parameter and whether the attribution of the main service cell changes;
and establishing a corresponding relation between the adjustment quantity of the adjustment parameter and the increment of the predicted SINR, determining a target adjustment quantity of the adjustment parameter according to the corresponding increment of the optimized target value and the corresponding relation, and optimizing the quality of the wireless network according to the target adjustment quantity.
An embodiment of the invention provides a non-transitory computer readable storage medium having a computer program stored thereon, which when executed by a processor implements the following method steps:
if at least one of the working parameters and the mobility parameters of the cell is adjusted, determining the home of the main service cell of the changed drive test sampling point;
calculating a predicted SINR according to the interference type, the noise acquired in advance, the type of the adjustment parameter and whether the home of the main service cell changes;
and establishing a corresponding relation between the adjustment quantity of the adjustment parameter and the increment of the predicted SINR, determining a target adjustment quantity of the adjustment parameter according to the corresponding increment of the optimized target value and the corresponding relation, and optimizing the quality of the wireless network according to the target adjustment quantity.
According to the method and the device for optimizing the quality of the wireless network, the predicted SINR is calculated according to the noise, the type of the adjustment parameter and whether the home of the main service cell changes, which are obtained in advance, so that the quality of the wireless network is optimized.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a flowchart of a method for optimizing the quality of a wireless network according to an embodiment of the present invention;
fig. 2 is a schematic flow chart illustrating a main serving cell attribution of a changed drive test sampling point according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating an embodiment of the present invention with reference to adjustment, but without change in home of a primary serving cell;
FIG. 4 is a diagram illustrating an embodiment of a change in home of a primary serving cell in response to a change in an operational parameter;
fig. 5 is a diagram illustrating a comparison effect of predicted SINR according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an embodiment of a wireless network quality optimization apparatus according to the present invention;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a flowchart of an embodiment of a method for optimizing wireless network quality, and as shown in fig. 1, the method for optimizing wireless network quality provided in the embodiment of the present invention includes the following steps:
s101: and if at least one of the working parameters and the mobility parameters of the cell is adjusted, determining the home of the main service cell of the changed drive test sampling point.
Specifically, if at least one of the parameters of the cell and the mobility parameter is adjusted, the home of the main serving cell of the changed drive test sampling point is determined. The method steps may be performed by a computer device. The adjustment of the operating parameters of the cell may specifically include adjusting an antenna azimuth angle, an antenna downtilt angle, a vertical height of the antenna relative to a signal receiving point, and an antenna type, and is not specifically limited. The mobility parameters of the cell may specifically include handover parameters and reselection parameters, and are not specifically limited.
Fig. 2 is a schematic flow chart of determining the home of the main serving cell of the changed drive test sampling point according to the embodiment of the present invention, and as shown in fig. 2, the calculation method for generating the change of the home of the cell of the drive test sampling point by adjusting the working parameters and/or the mobility parameters is as follows:
for the job parameter adjustment, according to patent application No. 201710890155.0, it can be calculated: the single-cell RSRP predicted value after the work parameter adjustment specifically comprises the following steps: and obtaining reference signal received power RSRP received by the signal receiving end according to the reference signal transmitting power, the antenna three-dimensional space gain, the path loss and the penetration loss. The method comprises the following steps of establishing a functional relation among an antenna model, an antenna direction angle, an antenna downward inclination angle, a vertical height between a signal receiving point and an antenna, a station track gauge, a station spacing and RSRP (reference signal received power) through antenna three-dimensional space gain calculation; and obtaining a wireless propagation model through fitting with the sweep frequency data or the drive test data, further obtaining path loss and penetration loss, and finally obtaining an accurate single-cell RSRP predicted value. Under the condition of determining the path loss and the penetration loss, an accurate single-cell RSRP predicted value can be derived by using the model of the antenna, the direction angle of the antenna, the downward inclination angle of the antenna, the vertical height between a signal receiving point and the antenna, the station track distance and the station spacing. For network optimization of the stock stations, the station addresses are determined, namely the station track moments and the station distances are determined, and then the working parameters are adjusted as required to derive the changed single-cell RSRP predicted value.
Since the RSRP predicted value is different from the RSRP test value obtained by the drive test, the home of the main serving cell (or the camping cell) that generates the drive test sampling point changes according to the mobility parameter.
For the mobility parameter adjustment, a change of reselection or handover threshold occurs, which also results in a change of the home of the main serving cell (or the camping cell) of the drive test sampling point.
Under the condition of triggering cell reselection, cell reselection generally follows an R criterion, after a reselection decision threshold + reselection delay (1s) is reached, a sampling point within reselection execution delay still belongs to an original cell, and a sampling point after the reselection execution delay belongs to a newly resided cell after reselection, wherein the method is mature technology in the field and is detailed as follows:
(1) and (3) reselection at the same priority:
the formula: rn Rs + Treselection (reselection delay) and UE original cell dwell time >1 s. Serving cell Rs ═ Qmeas, s + QHyst; neighbor cell Rn ═ Qmeas, n-Qoffset; qmeas: measuring the RSRP value of the cell; QHyst: a serving cell reselection hysteresis value; qoffset: an offset value of the target cell; q-Hyst + Offset, which is generally set to be 2-3 dB; reselection delay (t-reselection eutra): typically set for 1 s.
(2) Low- > high priority reselection
The formula: the high priority target cell S > threshXHigh + Treselection (reselection time delay) and the UE original cell dwell time > 1S. ThreshX-high: a pilot frequency point high priority reselection threshold; reselection delay (t-reselection eutra): typically set for 1 s.
(3) High- > low priority reselection
The formula:
starting reselection measurement according to an S value Srxlev & ltSnonintrasearch of a serving cell;
secondly, the residence time of the original cell of the UE is more than 1S, the service cell S < threshServingLow & the low priority cell S > threshXLow, + Treselection (reselection time delay); threshServingLow: a service frequency point low priority reselection threshold; threshXlow: a pilot frequency point low priority reselection threshold; reselection delay (t-reselection eutra): typically set for 1 s.
(4) Reselection execution delay
107 sets of reselection data were sampled, average reselection execution delay 59.48ms, and intra-system reselection execution delay <200ms for 98.11% sample points. The time interval of sampling data and drive test point printing is comprehensively considered, and the reselection execution time delay can be classified and determined. After considering the sampled 107 sets of reselection data together with the time interval of the drive test point, the reselection execution delay may be determined as shown in table 1:
TABLE 1
Type of reselection Reselection execution time (ms)
Same frequency and priority reselection 50
Inter-frequency co-priority reselection 150
High-to-low priority reselection 100
Low to high priority reselection 150
Under the condition of triggering the cell switching, after the cell switching reaches the time point of the report transmitted, the sampling point within the switching execution delay (control plane + user plane delay) still belongs to the original main service cell, and the sampling point after the switching execution delay belongs to the new main service cell after switching, which is detailed as follows:
(1) same-frequency switching:
formula of trigger condition: mn + Ofn + Ocn-Hys > Ms + Ofs + Ocs + Off. Mn: neighbor cell measurement results; ofn: the specific frequency offset of the adjacent area is set to be 0 in the current network; and Ocn: the bias of a specific cell of the adjacent cell, namely CIO, is generally set to 0 in the current network; ms: a measurement result of a serving cell; ofs: the specific frequency offset of the serving cell, the current network is generally set to 0; and Ocs: the specific cell bias of the serving cell, the current network is generally set to 0; hys: a hysteresis parameter; off: a3 event bias parameters, used to adjust the switch difficulty, when taking positive value, increasing the event trigger difficulty, delaying switch; when taking a negative value, the difficulty of event triggering is reduced, and switching is carried out in advance;
switching Time lag (a3 Time to trigger): the general setting is 320 ms; when the A3 event meets the triggering condition, the event is not reported immediately, but the parameter always meets the event triggering condition within the appointed time to report the event, so that the reporting of the event with excessive accidental triggering of the measurement result is reduced; on-frequency switching offset + hysteresis (a 3offset + Hyst): typically 2 dB.
(2) Pilot frequency handover
The pilot frequency switching based on RSRP can be triggered by events of A3, A4 and A5;
a2+ A3 inter-frequency switching: when the inter-frequency A3 handover is triggered, the A3Offset parameter is determined by InterFreqHoA3Offset, the frequency Offset is determined by Qoffset Freq, and other inter-frequency handover A3 parameters are the same as the same-frequency handover A3 parameters. If inter-frequency handover is triggered by A3, a2 that needs the serving cell to meet the inter-frequency A3 event starts a threshold (different from the intra-frequency A3). The pilot frequency A1 RSRP triggering threshold parameter based on A3 is A3InterFreqHoA1ThdRsrp, and the pilot frequency A2 RSRP triggering threshold parameter based on A3 is A3InterFreqHoA2 ThdRsrp;
a2+ a4 inter-frequency switching: triggering A4, namely the service cell meets the pilot frequency A2 start-up threshold and the quality of the adjacent cell is higher than a certain threshold; pilot frequency a4 handover trigger condition formula: mn + Ofn + Ocn-Hys > Thresh; thresh: the threshold parameter of A4, the parameter corresponding to the threshold of pilot frequency switching is different according to the difference of the triggering quantity or the reporting quantity;
a2+ a5 inter-frequency switching: 5, triggering, namely the quality of the service cell is lower than a certain threshold value, and the quality of the adjacent cell is higher than a certain threshold value; a5 event trigger formula: ms + Hys < Thresh1 and Mn + Ofn + Ocn-Hys > Thresh 2; thresh 1: a threshold 1 parameter of a5, below a threshold value for a serving cell; thresh 2: the threshold 2 parameter of a5, being above a threshold value for the target cell.
(3) Handover execution time
The control plane (for transmitting rrcconnectionreconfiguration complete to the target cell from the target cell measurementReport to the UE) delay is about 30 ms; the user plane delay is around 60 ms. The actual execution time of the intra-system handover is about 90ms plus the control plane delay plus the user plane delay.
S102: and calculating the predicted SINR according to the interference type, the noise acquired in advance, the type of the adjustment parameter and whether the attribution of the main service cell changes.
Specifically, the predicted SINR is calculated according to the interference type, the noise obtained in advance, the type of the adjustment parameter, and whether the home of the primary serving cell changes. The interference types may include non-modulo three interference and modulo three interference; correspondingly, the adjacent cells can be divided into non-modular tri-interference adjacent cells and modular tri-interference adjacent cells. The method can specifically comprise the following steps: determining the predicted RSRP of multiple cells may include: according to the single-cell RSRP prediction value of patent application No. 201710890155.0, and the "mobility parameter" adjustment, the home of the main serving cell (or camping cell) of the sampling point can be determined. All main service cells or resident cells RSRP of the whole line formed by the multiple cells are predicted RSRP of the multiple cells, the predicted RSRP of the neighbor cells after power-on parameter adjustment is obtained from the predicted RSRP of the multiple cells, the rest cells in the multiple cells can be used as the neighbor cells without power-on parameter adjustment, and test RSRP of the cells is determined, the determination of the test RSRP is mature technology in the field, and repeated description is omitted.
S103: and establishing a corresponding relation between the adjustment quantity of the adjustment parameter and the increment of the predicted SINR, determining a target adjustment quantity of the adjustment parameter according to the corresponding increment of the optimized target value and the corresponding relation, and optimizing the quality of the wireless network according to the target adjustment quantity.
Specifically, a corresponding relation between the adjustment quantity of the adjustment parameter and the increment of the predicted SINR is established, a target adjustment quantity of the adjustment parameter is determined according to the corresponding increment of the optimized target value and the corresponding relation, and the quality of the wireless network is optimized through the target adjustment quantity. The adjustment amount of the adjustment parameter can be understood as: according to step S101, an adjustment range for adjusting the work parameter and/or the mobility parameter of the cell is determined. The increment of the predicted SINR may be understood as: the magnitude between the calculated predicted SINR and the measured SINR before parameter adjustment. Namely, the corresponding relationship is the corresponding relationship between the parameter adjustment amplitude and the SINR amplitude.
Since the predicted SINR is related to parameter adjustment, the optimized target value may be a certain optimized target value of the parameter (i.e. meeting the expected quality of the wireless network), and the increment corresponding to the optimized target value may be understood as the increment between the optimized target value and the current SINR, so that a target adjustment amount for adjusting the parameter may be determined according to the increment and the corresponding relationship, so as to optimize the quality of the wireless network by the target adjustment amount. It will be appreciated that adjusting the current parameters by the target adjustment amount may achieve a desired wireless network quality.
According to the wireless network quality optimization method provided by the embodiment of the invention, the predicted SINR is calculated according to the interference type, the noise acquired in advance, the type of the adjustment parameter and whether the home of the main service cell changes, so that the wireless network quality is optimized.
On the basis of the embodiment, the type of the adjustment parameter comprises the adjustment of the cell parameter and the home of the main service cell is unchanged; correspondingly, the calculating the predicted SINR according to the interference type, the pre-obtained noise, the type of the adjustment parameter, and whether the home country of the primary serving cell changes includes:
calculating the predicted SINR according to the following formula:
Figure BDA0002363250870000091
wherein, the SINR Improvement of For the predicted SINR, RSRP Cell _0_ change Predicted RSRP for primary serving cell, RSRP cell _1_ change Predicting RSRP and RSRP of non-modular three-interference neighbor cell after work parameter adjustment cell_i Testing RSRP and RSRP of non-modular three-interference neighbor cell without work parameter adjustment Cell _2_ modified Prediction RSRP and RSRP of modular three-interference neighbor cell after working parameter adjustment Cell_j In order to test the RSRP of the interference neighborhood without the working parameter adjustment mode three, S1 represents a first correlation coefficient, S2 represents a second correlation coefficient, and N represents noise.
Before the adjustment of the work parameters and/or mobility parameters of the cell, the noise is calculated according to the following formula:
Figure BDA0002363250870000101
wherein N represents noise, RSRP Scell Testing RSRP, SINR for primary serving cell before parameter adjustment Scell Testing SINR, RSRP for primary serving cell before parameter adjustment Ncell_i Testing RSRP and RSRP of non-modular three-interference neighbor cells before parameter adjustment Ncell_j For the test RSRP of the modulo three interference neighbor before parameter adjustment, the interference types include non-modulo three interference and modulo three interference, S1 represents a first correlation coefficient corresponding to the non-modulo three interference, and S2 represents a second correlation coefficient corresponding to the modulo three interference.
The downlink RS-SINR is the average of the SINRs over all REs carrying Reference signals (Reference Signal) within a certain Symbol (Symbol) within the considered measurement frequency bandwidth. And the SINR on the RE carrying the Reference Signal (RS) is equal to the ratio of the useful signal power on that RE and all interfering signal powers and noise powers on that RE. The useful signal power on the REs carrying the RS, i.e. RSRP.
The RSRP and SINR of the existing network can be at the UEIs found in the test data of (1), the sum of the interference signal power and the noise power on the RE carrying the RS ∑ I Ncell + N, where N represents noise, N ═ N T +N O 、N T Is thermal noise, N O The SINR is expressed by the following equation for other noise (receiver noise, interference outside the network, etc.) other than the thermal noise:
Figure BDA0002363250870000102
wherein, the SINR Scell Testing SINR, RSRP for primary serving cell before parameter adjustment Scell Testing RSRP, SIGMA I for primary serving cell before parameter adjustment Ncell Refers to the interference of the neighboring cells with the same frequency to the main service cell.
The modulo three interference is from the reference signal of the adjacent region, and the non-modulo three interference is from the traffic channel signal of the adjacent region. Since the RSRP is an average value obtained from all RSs in the RB, the average value of interference caused by the neighboring cell traffic signal may also be represented by a ratio of the scheduled number of the downlink shared channel. The ratio of the subcarrier power of the OFDM symbol without the pilot frequency to the pilot frequency subcarrier power is rho A (in the existing network ρ) A The value can be 1/2), there are 100 RBs in each time slot under 20M bandwidth, assuming that the interference cancellation factor is γ (γ can be 1), the number of PRBs occupied by PDSCH per time slot is PRBNum, where PRBNum can take the average value of the preset time period (can be queried through the background), then the non-modulo three-neighbor interference is:
Figure BDA0002363250870000103
the modulo three neighbor interference is:
∑I Ncell_j ＝γ×∑RSRP Ncell_j 。
wherein,
Figure BDA0002363250870000111
corresponding to the first correlation coefficient, and gamma corresponds to the second correlation coefficient.
The wireless network quality optimization method provided by the embodiment of the invention can further accurately calculate and predict SINR, thereby optimizing the wireless network quality.
On the basis of the embodiment, the type of the adjustment parameter comprises the adjustment of the cell parameter and the change of the home of the main service cell; correspondingly, the calculating and predicting SINR according to the interference type, the pre-obtained noise, the type of the adjustment parameter, and whether the home of the primary serving cell changes includes:
specifically, the predicted SINR is calculated according to the following formula:
Figure BDA0002363250870000112
wherein, the SINR Improvement of To predict SINR, RSRP cell _1_ change Predicted RSRP and RSRP for switching original neighbor cell into current main service cell after work parameter adjustment Cell _0_ change After the working parameters are adjusted, the original main service cell is switched into the predicted RSRP and the RSRP of the current non-mode three-interference neighbor cell cell_i Testing RSRP and RSRP of non-modular three-interference neighbor cell without work parameter adjustment Cell _2_ modified Prediction RSRP and RSRP of modular three-interference neighbor cell after working parameter adjustment Cell_j In order to test the RSRP of the interference neighborhood without the working parameter adjustment mode three, S1 represents a first correlation coefficient, S2 represents a second correlation coefficient, and N represents noise. For the specific description of N, reference may be made to the above discussion, and details are not repeated.
The wireless network quality optimization method provided by the embodiment of the invention can further accurately calculate and predict SINR, thereby optimizing the wireless network quality.
On the basis of the embodiment, the types of the adjustment parameters comprise that the working parameters of the cell are not adjusted, the mobility parameters of the cell are adjusted, and the home of the main service cell is changed; correspondingly, the calculating and predicting SINR according to the interference type, the pre-obtained noise, the type of the adjustment parameter, and whether the home of the primary serving cell changes includes:
calculating the predicted SINR according to the following formula:
Figure BDA0002363250870000113
wherein, the SINR Improvement of Is the predicted SINR, RSRP' scell Test RSRP, RSRP of Primary serving cell' Ncell_i Test RSRP and RSRP of non-mode three-interference neighbor cell' Ncell_j The RSRP of the test of the interference neighborhood of the mode three is S1, the first correlation coefficient is S2, the second correlation coefficient is S2, and the noise is N. For the specific description of N, refer to the above discussion, and are not described again.
Case of reselection: when the reselection parameters in the SIB3, SIB4, SIB5, and SIBR7 are adjusted as needed, based on the RSRP test, the time interval of the test dotting, and the user plane and control plane delays, the test sampling point at which the camping cell changes may be calculated.
Case of handover occurrence: the thresholds of switching parameters such as events a1, a2, A3, a4, a5 and the like are adjusted as required, and based on the time intervals of testing RSRP and testing dotting, and the time delays of the user plane and the control plane, the test sampling point where the main serving cell changes can be calculated.
The wireless network quality optimization method provided by the embodiment of the invention can further accurately calculate and predict SINR, thereby optimizing the wireless network quality.
Fig. 3 is a schematic diagram of the embodiment of the present invention, in which the parameters are adjusted, but the home of the primary serving Cell is unchanged, as shown in fig. 3, in the high-speed test, signals received by the terminal include signals of the primary serving Cell, signals of the same-frequency neighboring cells, and other external interference and thermal noise, where Cell _0 is the primary serving Cell, and the others are the same-frequency neighboring cells. If the "work parameters" of the main serving Cell _0, the non-modular three-interference neighbor Cell _1 and the modular three-interference neighbor Cell _2 are adjusted in the optimization, the RSRP needs to be calculated by the method of the patent application No. 201710890155.0 when the adjusted main serving Cell is calculated Cell _0_ change 、RSRP cell _1_ change 、RSRP Cell _2_ modified And N needs to be calculated by the above formula for calculating N. The values of S1 and S2 can refer to the above description, and are not described in detail.
Fig. 4 is a schematic diagram of the adjustment of the parameters and the change of the home location of the main serving Cell according to the embodiment of the present invention, and as shown in fig. 4, signals received by the terminal in the high-speed test include signals of the main serving Cell, signals of the same-frequency neighboring cells, and other external interference and thermal noise, where Cell _0 is the main serving Cell, and the others are the same-frequency neighboring cells. If the 'working parameters' of the main service Cell Cell _0, the non-module three-interference neighbor Cell Cell _1 and the module three-interference neighbor Cell Cell _2 are adjusted in the optimization. After the "work parameter" is adjusted, it is assumed that the primary serving Cell is handed over from Cell _0 to Cell _ 1. When calculating the new main service cell after the "work parameter" adjustment, the RSRP needs to be calculated by the method of patent application No. 201710890155.0 Cell _0_ change 、RSRP cell _1_ change 、RSRP Cell _2_ modified 。
Fig. 5 is a schematic diagram illustrating a comparison effect of predicted SINRs according to an embodiment of the present invention, where as shown in fig. 5, 7 cells to be optimized are selected to perform fixed point tests before and after the implementation of the optimization scheme, and it can be found through test results that a result obtained by using the algorithm is substantially the same as an actual measurement value, and a downlink SINR mean error is only 1.01 dB.
Fig. 6 is a schematic structural diagram of an embodiment of a wireless network quality optimization apparatus according to the present invention, and as shown in fig. 6, an embodiment of the present invention provides a wireless network quality optimization apparatus, which includes a determining unit 601, a calculating unit 602, and an optimizing unit 603, where:
the determining unit 601 is configured to determine a main serving cell affiliation of the changed drive test sampling point if at least one of the work parameter and the mobility parameter of the cell is adjusted; the calculating unit 602 is configured to calculate a predicted SINR according to the interference type, the pre-obtained noise, the type of the adjustment parameter, and whether the home of the primary serving cell changes; the optimizing unit 603 is configured to establish a corresponding relationship between an adjustment amount of an adjustment parameter and the increment of the predicted SINR, determine a target adjustment amount of the adjustment parameter according to the corresponding increment of the optimized target value and the corresponding relationship, and optimize the quality of the wireless network according to the target adjustment amount.
Specifically, the determining unit 601 is configured to determine that the main serving cell of the changed drive test sampling point belongs to if at least one of the parameters of the cell and the mobility parameter is adjusted; the calculating unit 602 is configured to calculate a predicted SINR according to the interference type, the pre-obtained noise, the type of the adjustment parameter, and whether the home of the primary serving cell changes; the optimizing unit 603 is configured to establish a corresponding relationship between an adjustment amount of an adjustment parameter and the increment of the predicted SINR, determine a target adjustment amount of the adjustment parameter according to the corresponding increment of the optimized target value and the corresponding relationship, and optimize the quality of the wireless network according to the target adjustment amount.
The wireless network quality optimization device provided by the embodiment of the invention calculates and predicts SINR according to the interference type, the noise acquired in advance, the type of the adjustment parameter and whether the home of the main service cell changes, thereby optimizing the wireless network quality.
On the basis of the embodiment, the type of the adjustment parameter comprises the adjustment of the cell parameter and the home of the main service cell is unchanged; correspondingly, the calculating unit 602 is specifically configured to:
calculating the predicted SINR according to the following formula:
Figure BDA0002363250870000131
wherein, the SINR In a modified way For the predicted SINR, RSRP Cell _0_ change Predicted RSRP for primary serving cell, RSRP cell _1_ change Predicting RSRP and RSRP of non-modular three-interference neighbor cell after work parameter adjustment cell_i Testing RSRP and RSRP of non-modular three-interference neighbor cell without work parameter adjustment Cell _2_ modified Prediction RSRP and RSRP of modular three-interference neighbor cell after working parameter adjustment Cell_j In order to test the RSRP of the interference neighborhood without the working parameter adjustment mode three, S1 represents a first correlation coefficient, S2 represents a second correlation coefficient, and N represents noise.
The wireless network quality optimization device provided by the embodiment of the invention can further accurately calculate and predict SINR, thereby optimizing the quality of the wireless network.
On the basis of the embodiment, the type of the adjustment parameter comprises the adjustment of the cell parameter and the change of the home of the main service cell; correspondingly, the calculating unit 602 is specifically configured to:
calculating the predicted SINR according to the following formula:
Figure BDA0002363250870000141
wherein, the SINR Improvement of To predict SINR, RSRP cell _1_ change Predicted RSRP and RSRP for switching original neighbor cell into current main service cell after work parameter adjustment Cell _0_ change After the working parameters are adjusted, the original main service cell is switched into the predicted RSRP and the RSRP of the current non-mode three-interference neighbor cell cell_i Testing RSRP and RSRP of non-modular three-interference neighbor cell without work parameter adjustment Cell _2_ modified Prediction RSRP and RSRP of modular three-interference neighbor cell after working parameter adjustment Cell_j In order to test the RSRP of the interference neighborhood without the working parameter adjustment mode three, S1 represents a first correlation coefficient, S2 represents a second correlation coefficient, and N represents noise.
The wireless network quality optimization device provided by the embodiment of the invention can further accurately calculate and predict SINR, thereby optimizing the quality of the wireless network.
On the basis of the embodiment, the types of the adjustment parameters comprise that the working parameters of the cell are not adjusted, the mobility parameters of the cell are adjusted, and the home of the main service cell is changed; correspondingly, the calculating unit 602 is specifically configured to:
calculating the predicted SINR according to the following formula:
Figure BDA0002363250870000142
wherein, the SINR Improvement of Is the predicted SINR, RSRP' scell Test RSRP, RSRP of Primary serving cell' Ncell_i Test RSRP and RSRP of non-mode three-interference neighbor cell' Ncell_j The RSRP of the test of the interference neighborhood of the mode three is S1, the first correlation coefficient is S2, the second correlation coefficient is S2, and the noise is N.
The wireless network quality optimization device provided by the embodiment of the invention can further accurately calculate and predict SINR, thereby optimizing the quality of the wireless network.
The wireless network quality optimization device provided in the embodiments of the present invention may be specifically configured to execute the processing flows of the above method embodiments, and its functions are not described herein again, and refer to the detailed description of the above method embodiments.
Fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, and as shown in fig. 7, the electronic device includes: a processor (processor)701, a memory (memory)702, and a bus 703;
the processor 701 and the memory 702 complete mutual communication through a bus 703;
the processor 701 is configured to call the program instructions in the memory 702 to execute the methods provided by the above-mentioned method embodiments, for example, including: if at least one of the working parameters and the mobility parameters of the cell is adjusted, determining the home of the main service cell of the changed drive test sampling point; calculating a predicted SINR according to the interference type, the noise acquired in advance, the type of the adjustment parameter and whether the home of the main service cell changes; and establishing a corresponding relation between the adjustment quantity of the adjustment parameter and the increment of the predicted SINR, determining a target adjustment quantity of the adjustment parameter according to the corresponding increment of the optimized target value and the corresponding relation, and optimizing the quality of the wireless network according to the target adjustment quantity.
The present embodiment discloses a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, enable the computer to perform the method provided by the above-mentioned method embodiments, for example, comprising: if at least one of the working parameters and the mobility parameters of the cell is adjusted, determining the home of the main service cell of the changed drive test sampling point; calculating a predicted SINR according to the interference type, the noise acquired in advance, the type of the adjustment parameter and whether the home of the main service cell changes; and establishing a corresponding relation between the adjustment quantity of the adjustment parameter and the increment of the predicted SINR, determining a target adjustment quantity of the adjustment parameter according to the corresponding increment of the optimized target value and the corresponding relation, and optimizing the quality of the wireless network according to the target adjustment quantity.
The present embodiments provide a non-transitory computer-readable storage medium storing computer instructions that cause the computer to perform the methods provided by the above method embodiments, for example, including: if at least one of the work parameter and the mobility parameter of the cell is adjusted, determining the home of the main service cell of the changed drive test sampling point; calculating a predicted SINR according to the interference type, the noise acquired in advance, the type of the adjustment parameter and whether the home of the main service cell changes; and establishing a corresponding relation between the adjustment quantity of the adjustment parameter and the increment of the predicted SINR, determining a target adjustment quantity of the adjustment parameter according to the corresponding increment of the optimized target value and the corresponding relation, and optimizing the quality of the wireless network according to the target adjustment quantity.
Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (10)

1. A method for optimizing wireless network quality, comprising:
if at least one of the working parameters and the mobility parameters of the cell is adjusted, determining the home of the main service cell of the changed drive test sampling point;
calculating a predicted SINR according to the interference type, the noise acquired in advance, the type of the adjustment parameter and whether the home of the main service cell changes;
establishing a corresponding relation between the adjustment quantity of the adjustment parameter and the increment of the predicted SINR, determining a target adjustment quantity of the adjustment parameter according to the corresponding increment of the optimized target value and the corresponding relation, and optimizing the quality of the wireless network according to the target adjustment quantity;
wherein, the calculating the predicted SINR according to the interference type, the pre-obtained noise, the type of the adjustment parameter, and whether the home of the primary serving cell changes includes:
if the type of the adjustment parameter is to adjust the cell working parameters and the affiliation of the main service cell is not changed, calculating a predicted SINR according to the predicted RSRP of the main service cell, the predicted RSRP of the non-modular three-interference neighbor cell after the working parameters are adjusted, the test RSRP of the non-modular three-interference neighbor cell without the working parameters being adjusted, the predicted RSRP of the modular three-interference neighbor cell after the working parameters are adjusted, the test RSRP of the modular three-interference neighbor cell without the working parameters being adjusted, a first correlation coefficient, a second correlation coefficient and noise;
if the type of the adjustment parameter is to adjust the cell working parameters and the affiliation of the main service cell changes, calculating a predicted SINR according to the predicted RSRP which is switched from the original adjacent cell to the current main service cell after the working parameters are adjusted, the predicted RSRP which is switched from the original main service cell to the current non-modular three-interference adjacent cell after the working parameters are adjusted, the test RSRP which is not subjected to the working parameters adjustment of the non-modular three-interference adjacent cell, the predicted RSRP which is subjected to the working parameters adjustment of the modular three-interference adjacent cell, the test RSRP which is not subjected to the working parameters adjustment of the modular three-interference adjacent cell, the first correlation coefficient, the second correlation coefficient and the noise;
and if the type of the adjustment parameter is that the working parameters of the cell are not adjusted, the mobility parameter of the cell is adjusted, and the affiliation of the main service cell is changed, calculating the predicted SINR according to the test RSRP of the main service cell, the test RSRP of the non-mode three-interference neighbor cell, the test RSRP of the mode three-interference neighbor cell, the first correlation coefficient, the second correlation coefficient and the noise.
2. The method of claim 1, wherein the adjusting the type of the parameter comprises adjusting a cell parameter and the home of the primary serving cell is unchanged; correspondingly, the calculating and predicting SINR according to the interference type, the pre-obtained noise, the type of the adjustment parameter, and whether the home of the primary serving cell changes includes:
calculating the predicted SINR according to the following formula:
Figure FDA0003591490590000021
wherein, the SINR Improvement of For the predicted SINR, RSRP Cell _0_ change Predicted RSRP for primary serving cell, RSRP cell _1_ change Predicting RSRP and RSRP of non-modular three-interference neighbor cell after work parameter adjustment cell_i Testing RSRP and RSRP of non-modular three-interference neighbor cell without work parameter adjustment Cell _2_ modified Prediction RSRP and RSRP of modular three-interference neighbor cell after working parameter adjustment Cell_j In order to test the RSRP of the interference neighborhood without the working parameter adjustment mode three, S1 represents a first correlation coefficient, S2 represents a second correlation coefficient, and N represents noise.
3. The method of claim 1, wherein the adjusting the type of the parameter comprises adjusting a cell parameter and a home of the primary serving cell changes; correspondingly, the calculating and predicting SINR according to the interference type, the pre-obtained noise, the type of the adjustment parameter, and whether the home of the primary serving cell changes includes:
calculating the predicted SINR according to the following formula:
Figure FDA0003591490590000022
wherein, the SINR Improvement of To predict SINR, RSRP cell _1_ change Predicted RSRP and RSRP for switching original neighbor cell into current main service cell after work parameter adjustment Cell _0_ change After the working parameters are adjusted, the original main service cell is switched into the predicted RSRP and the RSRP of the current non-mode three-interference neighbor cell cell_i Testing RSRP and RSRP of non-modular three-interference neighbor cell without work parameter adjustment Cell _2_ change Prediction RSRP and RSRP of modular three-interference neighbor cell after working parameter adjustment Cell_j In order to test the RSRP of the interference neighborhood without the working parameter adjustment mode three, S1 represents a first correlation coefficient, S2 represents a second correlation coefficient, and N represents noise.
4. The method of claim 1, wherein the type of the adjustment parameter includes that no adjustment is made to the working parameters of the cell, the mobility parameter of the cell is adjusted, and the home of the primary serving cell is changed; correspondingly, the calculating and predicting SINR according to the interference type, the pre-obtained noise, the type of the adjustment parameter, and whether the home of the primary serving cell changes includes:
calculating the predicted SINR according to the following formula:
Figure FDA0003591490590000031
wherein, the SINR Improvement of Is the predicted SINR, RSRP' scell Test RSRP, RSRP of Primary serving cell' Ncell_i Test RSRP and RSRP of non-mode three-interference neighbor cell' Ncell_j The RSRP of the test of the interference neighborhood of the mode three is S1, the first correlation coefficient is S2, the second correlation coefficient is S2, and the noise is N.
5. An apparatus for optimizing quality of a wireless network, comprising:
the determining unit is used for determining the home of the main service cell of the changed drive test sampling point if at least one of the work parameter and the mobility parameter of the cell is adjusted;
a calculating unit, configured to calculate a predicted SINR according to the interference type, the pre-obtained noise, the type of the adjustment parameter, and whether the home of the primary serving cell changes;
the optimization unit is used for establishing a corresponding relation between the adjustment quantity of the adjustment parameter and the increment of the predicted SINR, determining a target adjustment quantity of the adjustment parameter according to the corresponding increment of the optimized target value and the corresponding relation, and optimizing the quality of the wireless network through the target adjustment quantity;
the computing unit is further to:
if the type of the adjustment parameter is to adjust the cell working parameters and the affiliation of the main service cell is not changed, calculating a predicted SINR according to the predicted RSRP of the main service cell, the predicted RSRP of the non-modular three-interference neighbor cell after the working parameters are adjusted, the test RSRP of the non-modular three-interference neighbor cell without the working parameters being adjusted, the predicted RSRP of the modular three-interference neighbor cell after the working parameters are adjusted, the test RSRP of the modular three-interference neighbor cell without the working parameters being adjusted, a first correlation coefficient, a second correlation coefficient and noise;
if the type of the adjustment parameter is to adjust the cell working parameters and the affiliation of the main service cell changes, calculating a predicted SINR according to the predicted RSRP which is switched from the original adjacent cell to the current main service cell after the working parameters are adjusted, the predicted RSRP which is switched from the original main service cell to the current non-mode three-interference adjacent cell after the working parameters are adjusted, the test RSRP which is not subjected to working parameter adjustment and is not subjected to the non-mode three-interference adjacent cell, the predicted RSRP which is subjected to working parameter adjustment and is subjected to the mode three-interference adjacent cell, the test RSRP which is not subjected to working parameter adjustment and is subjected to the mode three-interference adjacent cell, the first correlation coefficient, the second correlation coefficient and the noise;
and if the type of the adjustment parameter is that the working parameters of the cell are not adjusted, the mobility parameter of the cell is adjusted, and the affiliation of the main service cell is changed, calculating the predicted SINR according to the test RSRP of the main service cell, the test RSRP of the non-mode three-interference neighbor cell, the test RSRP of the mode three-interference neighbor cell, the first correlation coefficient, the second correlation coefficient and the noise.
6. The wireless network quality optimizing apparatus of claim 5, wherein the type of the adjustment parameter comprises adjusting a cell parameter and the home of the primary serving cell is unchanged; correspondingly, the computing unit is specifically configured to:
calculating the predicted SINR according to the following formula:
Figure FDA0003591490590000041
wherein, the SINR Improvement of For the predicted SINR, RSRP Cell _0_ change Predicted RSRP for primary serving cell, RSRP cell _1_ change Predicting RSRP and RSRP of non-modular three-interference neighbor cell after work parameter adjustment cell_i Testing RSRP and RSRP of non-modular three-interference neighbor cell without work parameter adjustment Cell _2_ modified Prediction RSRP and RS of modular three-interference neighbor cell after adjustment of working parametersRP Cell_j In order to test the RSRP of the interference neighborhood without the working parameter adjustment mode three, S1 represents a first correlation coefficient, S2 represents a second correlation coefficient, and N represents noise.
7. The wireless network quality optimizing apparatus of claim 5, wherein the type of the adjustment parameter includes adjusting a cell parameter and a home of the primary serving cell is changed; correspondingly, the computing unit is specifically configured to:
calculating the predicted SINR according to the following formula:
Figure FDA0003591490590000042
wherein, the SINR Improvement of To predict SINR, RSRP cell _1_ change Predicted RSRP and RSRP for switching original neighbor cell into current main service cell after work parameter adjustment Cell _0_ change After the working parameters are adjusted, the original main service cell is switched into the predicted RSRP and the RSRP of the current non-mode three-interference neighbor cell cell_i Testing RSRP and RSRP of non-modular three-interference neighbor cell without work parameter adjustment Cell _2_ modified Prediction RSRP and RSRP of modular three-interference neighbor cell after working parameter adjustment Cell_j In order to test the RSRP of the interference neighborhood without the working parameter adjustment mode three, S1 represents a first correlation coefficient, S2 represents a second correlation coefficient, and N represents noise.
8. The apparatus of claim 5, wherein the type of the adjustment parameter includes that the working parameters of the cell are not adjusted, the mobility parameters of the cell are adjusted, and the home of the primary serving cell is changed; correspondingly, the computing unit is specifically configured to:
calculating the predicted SINR according to the following formula:
Figure FDA0003591490590000051
wherein, the SINR Improvement of Is the predicted SINR, RSRP' scell Test RSRP, RSRP of Primary serving cell' Ncell_i Test RSRP and RSRP of non-mode three-interference neighbor cell' Ncell_j The RSRP of the test of the interference neighborhood of the mode three is S1, the first correlation coefficient is S2, the second correlation coefficient is S2, and the noise is N.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method according to any of claims 1 to 4 are implemented when the computer program is executed by the processor.
10. A non-transitory computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 4.
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