CN102098710B - Road network quality simulation system and method - Google Patents
Road network quality simulation system and method Download PDFInfo
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Abstract
The invention discloses a road network quality simulation system, which at least comprises: a public data module for pre-treating road network sweep frequency data measured by a frequency sweeping meter, and a quality simulation module for analyzing and calculating to obtain a quality simulation result of the radio network according to the pre-treated sweep frequency data. Preferably, the quality simulation module further comprises a handover risk simulation module, a dropped call risk simulation module, a poor quality risk simulation module and an access risk simulation module which are used for calculation to obtain a handover risk simulation result, a dropped call risk simulation result, a poor quality risk simulation result and an access risk simulation result respectively. The invention further provides a road network quality simulation method correspondingly. By the method and the system, quality hidden danger in the road network can be found by a simulation algorism and the work effect and efficiency in the network optimization phase can be greatly improved.
Description
Technical field
The present invention relates to the quality testing of wireless network, relate in particular to a kind of road network quality simulation System and method for.
Background technology
In recent years, along with the develop rapidly of cellular telecommunication art, cellular network is widely used.In cellular network, impact due to factors such as Bus stop planning, network parameter unreasonable allocation or geographical environments, to make cellular network have the diverse network quality problems such as call drop, handoff failure, access failure, voice quality be poor, in order just addressing these problems, need to carry out network optimization work to cellular network.The network optimization is exactly that network to putting into operation carries out that problem is searched, problem reason location, finally by technological means, adjust accordingly the process that makes network reach optimal operational condition.Wherein, it is the basic link of network optimization work that problem is searched, and how to find out accurately and efficiently the network quality problem that the meeting existing in network affects user's subjective feeling, is the key point of the input and output of the whole network optimization stage work of directly impact.
A kind of method of conventional Network Search problem is that the drive test data based on the call of conventional terminal analog subscriber is analyzed.Through practical application experience for many years, showing, there is following problem in said method: the test data that needs special testing equipment and personnel to gather magnanimity, to waste time and energy, and cost is high, and effect of optimization is not good.Cause the main cause of this situation to be, the uncontrollable factors such as behavioral test (such as the speed of a motor vehicle) and test terminal performance (such as BSIC decode time) have determined that each test result can only reflect the few part in network all problems, in order to obtain than more comprehensive data, need a large amount of tests repeatedly, and test a large amount of time of professional and technical personnel that need to take because network coverage is larger at every turn, therefore greatly reduce operating efficiency, improved cost, also give follow-up problem reason location simultaneously and optimize and revise solution formulation work and bring larger difficulty, and then affect final network optimization effect.
In summary,, obviously there is in actual use inconvenience and defect in existing wireless network test technology, so be necessary to be improved.
Summary of the invention
For above-mentioned defect, the object of the present invention is to provide a kind of road network quality simulation System and method for, can search the various hidden danger of quality that road network exists by simulation algorithm, can greatly improve network optimization stage working effect and efficiency.
To achieve these goals, the invention provides a kind of road network quality simulation system, at least comprise:
Common data module, carries out preliminary treatment for the road network frequency sweep data that sweep generator is recorded;
Quality simulation module, for according to described pretreated frequency sweep data, analytical calculation obtains the quality simulation result of road network.
According to road network quality simulation system of the present invention, described common data module comprises:
Data rasterizing module, for processing the data sequence obtaining under the different speed of a motor vehicle to frequency sweep data;
Main overlay model module, obtains main coverage cell for described data sequence is carried out to computational analysis, sets up the overlapping overlay model in main plot;
Risk community computing module, for calculating risk community according to described frequency sweep data and main overlay model.
According to road network quality simulation system of the present invention, described quality simulation module comprises:
Risk of handover emulation module, obtains risk of handover simulation result for the treatment of analyzing the first input data;
Risk of dropped calls emulation module, obtains risk of dropped calls simulation result for the treatment of analyzing the first input data;
The poor risk emulation module of matter, obtains the poor risk simulation result of matter for the treatment of analyzing the first input data;
Access risk emulation module, obtains accessing risk simulation result for the treatment of analyzing the second input data.
According to road network quality simulation system of the present invention, the poor risk emulation module of described risk of handover emulation module, risk of dropped calls emulation module and matter all adopts Active sort algorithm, and described the first input data comprise frequency sweep data, TCH traffic data, Ericsson's handoff parameter, community acquistion probability, the test speed of a motor vehicle and terminal capabilities parameter.
According to road network quality simulation system of the present invention, described access risk emulation module adopts Idle sort algorithm, and described the second input data comprise frequency sweep data, the congested traffic data of SD, Ericsson's reselecting parameters, community acquistion probability, the test speed of a motor vehicle and terminal capabilities parameter.
The present invention provides a kind of road network quality simulation method accordingly, by foregoing analogue system, realizes, and described method at least comprises the following steps:
Data pre-treatment step: the road network frequency sweep data that preliminary treatment records;
Road network quality simulation step: described in analytical calculation, frequency sweep data obtain the quality simulation result of road network.
According to road network quality simulation method of the present invention, described data pre-treatment step further comprises:
Process frequency sweep data, obtain the data sequence under the different speed of a motor vehicle;
Described in computational analysis, data sequence obtains main coverage cell, sets up the overlapping overlay model in main plot;
According to described frequency sweep data and community overlay model, calculate risk community.
According to road network quality simulation method of the present invention, described quality simulation step further comprises:
Treatment Analysis the first input data, obtain respectively the poor risk simulation result of risk of handover simulation result, risk of dropped calls simulation result and matter;
Treatment Analysis the second input data, obtain accessing risk simulation result.
According to road network quality simulation method of the present invention, adopt Active sort algorithm Treatment Analysis the first input data, described the first input data comprise frequency sweep data, TCH traffic data, Ericsson's handoff parameter, community acquistion probability, the test speed of a motor vehicle and terminal capabilities parameter.
According to road network quality simulation method of the present invention, adopt Idle sort algorithm Treatment Analysis the second input data, described the second input data comprise frequency sweep data, the congested traffic data of SD, Ericsson's reselecting parameters, community acquistion probability, the test speed of a motor vehicle and terminal capabilities parameter.
The present invention carries out preliminary treatment by common data module to the frequency sweep data of sweep generator drive test, concrete, it processes the data sequence obtaining under the different speed of a motor vehicle to frequency sweep data by data rasterizing module, by main overlay model module and risk community computing module, obtain the overlapping overlay model in main plot and risk community respectively again, further, system calculates the quality simulation result of road network by quality simulation module analysis according to the various data messages of common data module.Whereby, the present invention can search the various hidden danger of quality that road network exists by simulation algorithm, can greatly improve network optimization stage working effect and efficiency.
Accompanying drawing explanation
Fig. 1 is the structural representation of road network quality simulation system of the present invention;
Fig. 2 is the structural representation of road network quality simulation system one embodiment of the present invention;
Fig. 3 is the main overlay model schematic diagram of one embodiment of the invention road network quality simulation system;
Fig. 4 is the risk community schematic diagram of one embodiment of the invention road network quality simulation system;
Fig. 5 is that the risk of handover simulation result of one embodiment of the invention road network quality simulation system presents figure;
Fig. 6 is that the risk of dropped calls simulation result of one embodiment of the invention road network quality simulation system presents figure;
Fig. 7 is that the poor risk simulation result of the matter of one embodiment of the invention road network quality simulation system presents figure;
Fig. 8 is that the access risk simulation result of one embodiment of the invention road network quality simulation system presents figure;
Fig. 9 is road network quality simulation method flow diagram of the present invention;
Figure 10 is the theory structure schematic diagram of road network quality simulation method of the present invention.
Embodiment
In order to make object of the present invention, technical scheme and advantage clearer, below in conjunction with drawings and Examples, the present invention is further elaborated.Should be appreciated that specific embodiment described herein, only in order to explain the present invention, is not intended to limit the present invention.
Fig. 1 is the basic structure schematic diagram of road network quality simulation system of the present invention, and road network quality simulation system 100 at least comprises public module 10 and quality simulation module 20,
Fig. 2 is the structural representation of road network quality simulation system one specific embodiment of the present invention, and in the present embodiment, common data module 10 comprises data rasterizing module 11, main overlay model module 12 and risk community computing module 13.Wherein:
Concrete, the algorithm that data rasterizing module 11 adopts is as described below:
Sweep generator carries out data acquisition in the speed of a motor vehicle during lower than 20Km/h, obtains sampled point as much as possible.Data rasterizing module 11 is processed by original frequency sweep data are done to rasterizing, by different distance interval samplings, obtains the data under the different speed of a motor vehicle and in software database, preserves into different files.In software, the speed of a motor vehicle is as variable parameter, input different values (20,40 ..., 20*N) transfer respectively corresponding data and do quality simulation calculating.For example, apart from interval, get 5.5m/s and sample, can obtain the data sequence that the speed of a motor vehicle is 5.5m/s*3600s ≈ 20km/h.Apart from interval, get 5.5m/s*2=11m/s and sample, can obtain the data sequence that the speed of a motor vehicle is 11m/s*3600s ≈ 40km/h.The like, can obtain the speed of a motor vehicle and be the data sequence of 20 different multiples.
Main overlay model module 12, carries out computational analysis for the data sequence that 11 processing obtain to data rasterizing module and obtains main coverage cell, and then set up the overlapping overlay model in main plot.In practical application, main overlay model module 12 is utilized Active/Idle sort algorithm, according to the RSSI of frequency sweep data Zhong Ge community and network-related parameters (Layer, Layerthr, Accmin, CR and PT), carry out community sequence, filter out the first six the community of ranking value of each sampled point, obtain whereby all main coverage cell in test zone, set up the overlapping overlay model in main plot.
Concrete, Active/Idle sort algorithm is described below:
Under Active (call mode) algorithm, following situation is main coverage cell: 1) during the strongest 1 layer of community RSSI (signal strength signal intensity indication) >=layerthr (switch level), this community is the 1st main coverage cell; 2), during all 1 layer of community RSSI < layerthr, Qiang community is the 1st main coverage cell.2nd～10 main coverage cell, community algorithms are as consistent in the 1st main coverage cell algorithm, do not repeat them here.
With the signal of certain certain sampled point You Shige community, before Active sequence, information is as following table.
| Ranking value | Cell name | RSSI | Layer | Layerthr |
| The last 1 | F | -50 | 2 | -80 |
| The last 2 | G | -55 | 2 | -80 |
| The last 3 | H | -60 | 2 | -80 |
| Semi-finals | I | -65 | 2 | -80 |
| The last 5 | A | -70 | 1 | -80 |
| The last 6 | B | -72 | 1 | -80 |
| The last 7 | C | -74 | 1 | -80 |
| The Final 8 | D | -78 | 1 | -80 |
| The last 9 | E | -79 | 1 | -80 |
| The last 10 | J | -82 | 1 | -80 |
First the community to layer=1, RSSI and Layerthr compare, if RSSI > is Layerthr, by RSSI, sort from big to small; Put together and sort by RSSI size in the community of RSSI < Layerthr and the community of layer=2.The result of sequence after handling is as following table:
Under Idle (idle pulley) algorithm, Wei Zhu coverage cell, following community: 1) RSSI > accmin (the minimum access in this community level); 2) C2 largest cell Wei Zhu coverage cell, 2nd～10 main coverage cell the like; 3) C2 calculates, and works as pt=0, C2=RSSI+accmin+2*cro, and when pt ≠ 0, C2=RSSI+accmin-2*cro; 4) the main covering of IDLE can not be done in 3 layers of community.According to above rule, can extrapolate each main coverage cell.It should be noted that, in embodiments of the invention, when emulation call drop, switching and the poor risk of matter, adopt Active sort algorithm, when emulation access risk, adopt Idle sort algorithm.
With the signal of certain sampled point You Shige community, before Active sequence, information is as following table:
| Ranking value | Cell name | RSSI | Accmin | C2 |
| The last 6 | F | -50 | -100 | 13 |
| The last 7 | G | -55 | -100 | 11 |
| The Final 8 | H | -60 | -100 | 9 |
| The last 9 | I | -65 | -100 | 7 |
| The last 1 | A | -70 | -100 | 23 |
| The last 2 | B | -72 | -100 | 21 |
| The last 3 | C | -74 | -100 | 19 |
| Semi-finals | D | -78 | -100 | 17 |
| The last 5 | E | -79 | -100 | 15 |
| The last 10 | J | -82 | -100 | 5 |
First RSSI and Accmin compare, and for the community of RSSI > Accmin, according to C2 value, sort from big to small; For the community of RSSI < Accmin, according to RSSI value, sort from big to small.
It is as follows that result is afterwards handled in Idle sequence:
As shown in Figure 3, in diagram, test trails represents direction of traffic from left to right to the main overlay model obtaining according to Active/Idle sort algorithm, and A～F represents different communities.
Risk community computing module 13, for calculating risk community according to frequency sweep data and main overlay model.It should be noted that, according to Principle of Communication, the have its source in radio link quality of community of the dissimilar network quality problems such as call drop, handoff failure, access failure that occur in road network occur to worsen and then causes and decodes unsuccessfully, and the C/I (carrier/interface ratio) of frequency sweep data small area can characterize radio link quality.Therefore, need to filter out the main coverage cell that exists continuous C/I low, these communities are referred to as risk community.
In one embodiment of the invention, the decision algorithm of risk community is as follows: on main overlay model basis, all front the last 6 community is judged, if there is the individual above sampled point C/I < Q (Q is defaulted as 9) of N continuous 1 (being defaulted as 6) will be defined as quality risk community; If there is the individual above sampled point RSSI < R (be defaulted as-90dbm of R) of N continuous 2 (being defaulted as 2) will be defined as weak signal risk community.
Wherein, for the algorithm of quality risk community, in one embodiment of the invention, certain continuous the first six strong cell information of six sampled points is as follows:
Continuous 6 the sampled point C/I < 9 in D community, judge accordingly as seen from the above table, and this D community is quality risk community.
For weak signal risk community decision algorithm processing procedure, in one embodiment of this invention, suppose that certain continuous the first six strong cell information of four sampled points in weak overlay area is as follows:
Continuous 3 the sampled point RSSI <-90dbm in F community, judge that this F community is as weak signal risk community accordingly as seen from the above table.
Better, quality simulation module 20 comprises risk of handover emulation module 21, risk of dropped calls emulation module 22, the poor risk emulation module 23 of matter and access risk emulation module 24.Each module is when concrete emulation, the poor risk emulation module 23 of risk of handover emulation module 21, risk of dropped calls emulation module 22 and matter all adopts Active sort algorithm, and the input data that these modules need comprise frequency sweep data, TCH traffic data, Ericsson's handoff parameter, community acquistion probability, the test speed of a motor vehicle and terminal capabilities parameter; Access risk emulation module 24 adopts Idle sort algorithm, and its input data comprise frequency sweep data, the congested traffic data of SD, Ericsson's reselecting parameters, community acquistion probability, the test speed of a motor vehicle and terminal capabilities parameter.
Risk of handover emulation module 21 obtains risk of handover simulation result for the treatment of analyzing relevant input data, for convenience of subsequent descriptions, at this, first three kinds of scenes of risk of handover and related notion is illustrated.
The first scene: using all main coverage cell that have an overlapping covering to as investigating object, according to the neighbor cell configuration table judgement of input, when certain exists adjacent area leakage to join risk of handover, i.e. 0 grade of risk of handover to having the minizone of overlapping covering not define adjacent area, will being determined.
The second scene: using quality risk community as investigating object, there is the community of overlapping covering as handover source community with the poor region of continuous matter, when the poor time of the continuous matter in quality risk community, be greater than the handoff failure time (T1+T2+T3), judge that this community is to existing general risk of handover; General risk of handover rank is consistent with risk community ranking value.If the sequence of risk community is the last 1 community, risk of handover rank corresponds to 1 grade of risk of handover; If the sequence of risk community is the last 2 community, risk of handover rank corresponds to 2 grades of risk of handover, and the rest may be inferred.
The third scene: using weak signal risk community as investigating object, there is the community of overlapping covering as handover source community with continuously weak overlay area, when weak signal risk community, the continuously weak cover time is greater than the switching deadline (T1+T2), judge that this community is to existing weak signal risk of handover, i.e. 7 grades of risk of handover.
Cell-of-origin: the Serving cell before switching; Target cell: the Serving cell after switching; Handover success required time: BSIC decode time T1+ switch decision time T 2; Handoff failure required time: handover success required time+handoff failure timer T3.
In a specific embodiment of the present invention, adjacent area leaks that to join risk of handover algorithm process procedure declaration as follows: as shown in Figure 3, main coverage cell has 6 to the main overlay model in certain region.For convenience of description, in this supposition A community and undefined adjacent area, C community, by main overlay model known A community and C community, there is overlapping covering relation.Further, by above condition, can judge that A and C community exist adjacent area to leak air distribution danger, i.e. 0 grade of risk of handover.
In conjunction with Fig. 4, certain regional quality risk community is D community, and S1～S2 scope is Zhi Cha region, D community.Suppose: S1～S2 sampling time is 10s simultaneously, handoff failure required time T1+T2+T3 is 6s, be the poor time of continuous matter to be greater than the handoff failure time, by the known A of main overlay model, B, C, E, five cell coverage areas of F, all have overlapping relation with the poor region of matter; When D community matter is poor, sequence is the last 6; By above condition, can judge that A, B, C, E and F community exist 6 grades of risk of handover while switching to D community.
Continuation is referring to Fig. 4, and in diagram, certain weak signal risk community, region is A community, and S3～S4 scope is weak overlay area, A community.Suppose that S3～S4 sampling time is 5s, having switched required time T1+T2 is 4s, and the continuously weak cover time is greater than and switches the deadline, by the known B of main overlay model, C, D, E, five cell coverage areas of F, all has overlapping relation with weak overlay area; Further, by above condition, can judge that community A, B, C, E and F are switched to community D and have weak signal risk of handover, i.e. 7 grades of risk of handover.
The simulation result of one embodiment of the invention risk of handover as shown in Figure 5, in this diagram, show that total sampling number is 706, wherein having the sampling number of wind force 0 danger (representing miss-configured neighboring cells) is 37, having the sampling number of moderate gale danger is 125, and having the sampling number of strong gale danger (multiple rank risk stack is defined as 8 grades) is 175.Message box content shows that cell-of-origin " old room 3 ", " gateway of the village, old room 1 ", " gateway of the village, old room 2 ", " gateway of the village, old room 3 " are switched to Target cell " Chen Wujinying road 3 " and have risk of handover.
Risk of dropped calls emulation module 22 obtains risk of dropped calls simulation result for the treatment of analyzing relevant input data, in practical application, risk of dropped calls can divide following two kinds of sights: 1) isolated island risk of dropped calls: usining risk community (comprising quality risk community and weak signal risk community) investigates as cell-of-origin, when the poor or weak cover time of the continuous matter in cell-of-origin, be greater than call drop timing T6, and in the poor or weak overlay area of matter, there is no switchable Target cell continuously, now will there is call drop, the ranking value that risk of dropped calls rank is cell-of-origin; 2) switch risk of dropped calls: usining risk community (comprising quality risk community and weak signal risk community) investigates as Target cell, and risk of dropped calls algorithm is consistent with risk of handover algorithm principle, risk of dropped calls level definition is consistent with risk of handover definition.
Referring to Fig. 4, in one embodiment of the invention, certain regional quality risk community is D community again, and S1～S2 scope is weak overlay area, D community, supposes: within the scope of S1～S2, the sampling time is 10 seconds, and call drop timer parameter T6 is 8s; D community and A, B, C, E and F Wu Ge community do not have individual event neighboring BS relationship, and D community cannot be switched to the arbitrary community in A, B, C, E and F; When D community matter is poor, sequence is the last 6; According to above condition, can judge that D community exists 6 grades of risk of dropped calls, switch risk of dropped calls simulation algorithm consistent with risk of handover algorithm, not repeat them here.
As shown in Figure 6, diagram shows that total sampling number is 706 to the simulation result of the risk of dropped calls of one embodiment of the invention, and wherein having the sampling number of moderate gale danger is 124, and having the sampling number of strong gale danger (multiple rank risk stack is defined as 8 grades) is 48.Message box content shows that cell-of-origin " old room 3 ", " gateway of the village, old room 1 " are switched to Target cell " gateway of the village, old room 3 " and have risk of dropped calls.
The poor risk emulation module 23 of matter obtains the poor risk simulation result of matter for the treatment of analyzing relevant input data.Concrete, the C/I of 23 pairs of all main coverage cell of the poor risk emulation module of matter judges, if have the individual sampled point C/I of continuous Z (being defaulted as 3) to be less than the poor thresholding Q of matter (being defaulted as 9), judge that corresponding region exists the poor risk of matter, the ranking value of degree of risk Wei Zhicha community.Its algorithm process process is as follows:
Referring to Fig. 4, it within the scope of certain region S1～S2, is Zhi Cha region, D community.Suppose: all sampled point C/I < 9 in S1～S2 region, the poor thresholding Q=9 of matter; S1～S2 sampling number is 5, parameter Z=3 of counting continuously; When D community matter is poor, sequence is the last 6; By above condition, can judge that D community exists 6 grades of poor risks of matter.
The simulation result of the poor risk of matter of one embodiment of the invention as shown in Figure 7, shows in diagram that total sampling number is 706, and the sampling number that has fresh gale danger is 228.Message box content shows that cell-of-origin " Chen Wujinying road 1 " exists the poor risk of matter.
Access risk emulation module 24, obtains accessing risk simulation result for the treatment of analyzing the second input data, for convenience of description, first three kinds of scenes of related notion and access risk is described: access risk: cell reselection access failure under idle condition at this; Cell-of-origin: the Serving cell before cell reselection; Target cell: the Serving cell after cell reselection; Cell reselection starting point: last sampled point of covering edge of cell-of-origin; Cell reselection success required time: BSIC decode time T1+ switch decision time T 4; Cell reselection failure required time: cell reselection success required time+cell reselection access failure timer T5.
The first access risk scene: using all main coverage cell that have an overlapping covering to as investigation object, according to the neighbor cell configuration table judgement of input, when certain exists adjacent area to leak to connect into risk to having the minizone of overlapping covering not define adjacent area, will being determined, i.e. 0 grade of risk of handover.
The second access risk scene: using quality risk community as investigating object, there is the community of overlapping covering as handover source community with the poor region of continuous matter, when the poor time of the continuous matter in quality risk community, be greater than cell reselection Time To Failure (T1+T4+T5), judge that this community is to existing general access risk; General access risk class is consistent with risk community ranking value.If the sequence of risk community is the last 1 community, accesses risk class and correspond to 1 grade of access risk; If the sequence of risk community is the last 2 community, access risk class and correspond to 2 grades of access risks, the rest may be inferred.
The third access risk scene: using weak signal risk community as investigating object, there is the community of overlapping covering as cell reselection cell-of-origin with continuously weak overlay area, when weak signal risk community, the continuously weak cover time is greater than cell reselection Time To Failure (T1+T4), judge that this community is to existing weak signal access risk, i.e. 7 grades of access risks.
Adjacent area leakage connects into risk algorithm process process prescription as follows: the main overlay model in certain region shown in Figure 3, main coverage cell has 6.Suppose the undefined adjacent area in A community and C community, by main overlay model known A community and C community, have overlapping covering relation, according to above condition, can judge that A and C community exist adjacent area to leak air distribution danger, i.e. 0 grade of access risk.
General risk of handover algorithm process procedure declaration is as follows: referring to Fig. 4, certain regional quality risk community is D community, and S1～S2 scope is Zhi Cha region, D community.Suppose that S1～S2 sampling time is 10s, handoff failure required time T1+T2+T3 is 7s, and the poor time of matter is greater than cell reselection Time To Failure continuously; By the known A of main overlay model, B, C, E, five cell coverage areas of F, all there is overlapping relation with the poor region of matter; When D community matter is poor, sequence is the last 6; According to above condition, can judge that A, B, C, E and F community exist 6 grades of access risks while being switched to D community.
Weak signal risk of handover algorithm process procedure declaration is as follows: please continue referring to Fig. 4, certain weak signal risk community, region is A community, and S3～S4 scope is weak overlay area, A community.Suppose that S3～S4 sampling time is 8s, it is 6s that cell reselection completes required time T1+T2, and the continuously weak cover time is greater than the cell reselection deadline; By the known B of main overlay model, C, D, E, five cell coverage areas of F, all there is overlapping relation with weak overlay area; According to above condition, can judge that A, B, C, E and F community exist weak signal access risk while being switched to D community, i.e. 7 grades of access risks.
The simulation result of the access risk of one embodiment of the invention as shown in Figure 8, in diagram, show that total sampling number is 706, wherein having the sampling number of moderate gale danger is 208, and having the sampling number of strong gale danger (multiple rank risk stack is defined as 8 grades) is 595.Message box content shows that cell-of-origin " gateway of the village, old room 1 ", " gateway of the village, old room 3 ", " Chen Wujinying road 3 " gravity treatment exist access risk to Target cell " Chen Wujinying road 1 ".
Fig. 9 is road network quality simulation method flow diagram of the present invention, and it can be realized by foregoing road network quality simulation system 100, at least comprises the following steps:
Step S901, the road network frequency sweep data that preliminary treatment records, this step is realized by common data module 10.Concrete, first it process frequency sweep data by data rasterizing module 11, obtains whereby the data sequence under the different speed of a motor vehicle; By data sequence described in main overlay model module 12 computational analysis, obtain main coverage cell again, set up the overlapping overlay model in main plot; Finally by risk community computing module 13, according to described frequency sweep data and community overlay model, calculate risk community.
Step S902, analytical calculation frequency sweep data obtain the quality simulation result of road network, and this step is realized by quality simulation module 20.Concrete, in conjunction with Figure 10, quality simulation module 20 is by adopting Active sort algorithm Treatment Analysis the first input data can obtain respectively the poor risk simulation result of risk of handover simulation result, risk of dropped calls simulation result and matter, wherein, the first input data comprise frequency sweep data, TCH traffic data, Ericsson's handoff parameter, community acquistion probability, the test speed of a motor vehicle and the terminal capabilities parameter of being obtained by common data module 10.Simultaneously, quality simulation module 20 also obtains accessing risk simulation result by Idle sort algorithm Treatment Analysis the second input data, wherein, the second input data comprise frequency sweep data, the congested traffic data of SD, Ericsson's reselecting parameters, community acquistion probability, the test speed of a motor vehicle and terminal capabilities parameter.
In sum, the present invention carries out preliminary treatment by common data module to the frequency sweep data of sweep generator drive test, concrete, it processes the data sequence obtaining under the different speed of a motor vehicle to frequency sweep data by data rasterizing module, by main overlay model module and risk community computing module, obtain the overlapping overlay model in main plot and risk community respectively again, further, system calculates the quality simulation result of road network by quality simulation module analysis according to the various data messages of common data module.Whereby, the present invention can search the various hidden danger of quality that road network exists by simulation algorithm, can greatly improve network optimization stage working effect and efficiency.
Certainly; the present invention also can have other various embodiments; in the situation that not deviating from spirit of the present invention and essence thereof; those of ordinary skill in the art are when making according to the present invention various corresponding changes and distortion, but these corresponding changes and distortion all should belong to the protection range of the appended claim of the present invention.
Claims (2)
1. a road network quality simulation system, is characterized in that, at least comprises:
Common data module, carries out preliminary treatment for the road network frequency sweep data that sweep generator is recorded;
Described common data module comprises:
Data rasterizing module, for frequency sweep data are processed, obtains the data sequence under the different speed of a motor vehicle;
Main overlay model module, obtains main coverage cell for described data sequence is carried out to computational analysis, sets up the overlapping overlay model in main plot;
Risk community computing module, for calculating risk community according to described frequency sweep data and main overlay model;
Quality simulation module, for according to described pretreated frequency sweep data, analytical calculation obtains the quality simulation result of road network;
Described quality simulation module comprises:
Risk of handover emulation module, obtains risk of handover simulation result for the treatment of analyzing the first input data;
Risk of dropped calls emulation module, obtains risk of dropped calls simulation result for the treatment of analyzing the first input data;
The poor risk emulation module of matter, obtains the poor risk simulation result of matter for the treatment of analyzing the first input data;
Access risk emulation module, obtains accessing risk simulation result for the treatment of analyzing the second input data;
The poor risk emulation module of described risk of handover emulation module, risk of dropped calls emulation module and matter all adopts Active sort algorithm, and described the first input data comprise frequency sweep data, TCH traffic data, Ericsson's handoff parameter, community acquistion probability, the test speed of a motor vehicle and terminal capabilities parameter;
Described access risk emulation module adopts Idle sort algorithm, and described the second input data comprise frequency sweep data, the congested traffic data of SD, Ericsson's reselecting parameters, community acquistion probability, the test speed of a motor vehicle and terminal capabilities parameter.
2. a road network quality simulation method, realizes by analogue system as claimed in claim 1, it is characterized in that, described method at least comprises the following steps:
Data pre-treatment step: the road network frequency sweep data that preliminary treatment records;
This data pre-treatment step further comprises:
Process frequency sweep data, obtain the data sequence under the different speed of a motor vehicle;
Described in computational analysis, data sequence obtains main coverage cell, sets up the overlapping overlay model in main plot;
According to described frequency sweep data and community overlay model, calculate risk community;
Road network quality simulation step: described in analytical calculation, frequency sweep data obtain the quality simulation result of road network;
This road network quality simulation step further comprises:
Treatment Analysis the first input data, obtain respectively the poor risk simulation result of risk of handover simulation result, risk of dropped calls simulation result and matter;
Treatment Analysis the second input data, obtain accessing risk simulation result;
The described first Active sort algorithm Treatment Analysis for input data acquisition, described the first input data comprise frequency sweep data, TCH traffic data, Ericsson's handoff parameter, community acquistion probability, the test speed of a motor vehicle and terminal capabilities parameter;
The described second Idle sort algorithm Treatment Analysis for input data acquisition, described the second input data comprise frequency sweep data, the congested traffic data of SD, Ericsson's reselecting parameters, community acquistion probability, the test speed of a motor vehicle and terminal capabilities parameter.
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