CN102457852B  Realization method of frequency optimization and apparatus thereof  Google Patents
Realization method of frequency optimization and apparatus thereof Download PDFInfo
 Publication number
 CN102457852B CN102457852B CN201010515971.1A CN201010515971A CN102457852B CN 102457852 B CN102457852 B CN 102457852B CN 201010515971 A CN201010515971 A CN 201010515971A CN 102457852 B CN102457852 B CN 102457852B
 Authority
 CN
 China
 Prior art keywords
 frequency
 community
 cell
 population
 interference
 Prior art date
 Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
 Active
Links
 238000005457 optimization Methods 0.000 title claims abstract description 22
 239000011159 matrix material Substances 0.000 claims abstract description 106
 230000000875 corresponding Effects 0.000 claims abstract description 37
 238000005259 measurement Methods 0.000 claims description 53
 238000000034 method Methods 0.000 claims description 22
 230000002068 genetic Effects 0.000 claims description 11
 238000006467 substitution reaction Methods 0.000 claims description 7
 238000010353 genetic engineering Methods 0.000 claims description 6
 238000004364 calculation method Methods 0.000 claims description 4
 239000000203 mixture Substances 0.000 claims description 4
 230000005540 biological transmission Effects 0.000 claims description 2
 230000004301 light adaptation Effects 0.000 abstract 4
 238000010586 diagram Methods 0.000 description 5
 238000001914 filtration Methods 0.000 description 4
 235000020127 ayran Nutrition 0.000 description 1
 230000005465 channeling Effects 0.000 description 1
 230000035772 mutation Effects 0.000 description 1
Abstract
The invention provides a realization method of frequency optimization and an apparatus thereof. The method comprises the following steps: (A) setting a whole network cell in a present network, and dividing a road guarantee cell in the whole network cell; (B) according to a set cell frequency point restriction condition, deploying a frequency point for each cell in the present network, and dividing frequency points of all cells into N groups, wherein N is a positive integer larger than 1; (C) establishing a whole network interference matrix for the whole network cell, and establishing a road interference matrix for a road guarantee cell; (D) by utilizing a multitarget heredity algorithm and every interference matrix established in the step (C), calculating an adaptation degree corresponding to each group, selecting an adaptation degree satisfying a set object from calculated adaptation degrees, and determining a frequency point of each cell in a group corresponding to the selected adaptation degree as an optimal frequency point of each cell. By employing the method and the apparatus in the invention, purposes of ensuring whole network performance and optimizing partial performance simultaneously can be realized.
Description
Technical field
The present invention relates to network field, particularly the implementation method of frequency optimization and device.
Background technology
In GSM network, the quality of frequency planning has directly affected the performance performance of network.At present, apply many frequency optimization algorithms and mainly comprise following three kinds of algorithms:
1, standard m × n channeling;
2, iteration optimization algorithms;
3, singlegoal function genetic algorithm;
Wherein, the first algorithm is the basic methods of frequency planning, is generally used for the networking initial stage, and along with the continuous variation of the complicated and network of network, this mode cannot practical requirement.Second algorithm is fairly simple, and cost is less, but is difficult to solve multipeak function problem, can not find the optimal solution of problem.The third algorithm is to use at present more a kind of algorithm, and it can find optimal solution to multipeak function, improves overall performance.
But, the third algorithm is mainly optimized from the enterprising line frequency of network entirety angle, although this can improve overall performance, but, be difficult to adapt to complicated at present network optimization demand, and, logical frequency optimization experience demonstration in a few years, the raising of overall performance realizes with the cost of sacrifice Local Property often.Therefore, one should ensure overall network performance, and the frequency optimization implementation method that ensures again Local Property is current technical problem urgently to be resolved hurrily.
Summary of the invention
The invention provides frequency optimization implementation method and device, ensure overall network performance to realize, and optimize Local Property simultaneously.
Technical scheme provided by the invention comprises:
An implementation method for frequency optimization, comprising: A, in current network, set the whole network community, and from the whole network community, mark off road support community;
B, is each cell configuration frequency in current network according to the subdistrict frequency point restrictive condition arranging, and the frequency of all communities is divided into N population, and N is positive integer, and is greater than 1;
C, for setting up the whole network interference matrix in the whole network community, for setting up road interference matrix in road support community;
D, each interference matrix that utilizes multiobjective genetic algorithm and step C to set up calculates the fitness that each population is corresponding, from the fitness calculating, select the fitness that meets target setting, the frequency of population Zhong Ge community corresponding this fitness of selecting is defined as to the optimum frequency of each community.
An implement device for frequency optimization, comprising:
Division unit for set the whole network community in current network, and marks off road support community from the whole network community;
Dispensing unit, for being each cell configuration frequency of current network according to the subdistrict frequency point restrictive condition arranging, is divided into N population by the frequency of all communities, and N is positive integer, and is greater than 1;
Set up unit, be used to the whole network community to set up the whole network interference matrix, for setting up road interference matrix in road support community;
Determining unit, for utilizing multiobjective genetic algorithm and described each interference matrix set up unit of setting up to calculate the fitness that each population is corresponding, from the fitness calculating, select the fitness that meets target setting, the frequency of population Zhong Ge community corresponding this fitness of selecting is defined as to the optimum frequency of each community.
As can be seen from the above technical solutions, in the present invention, by setting the whole network community, and from the whole network community, mark off road support community, be each cell configuration frequency in current network according to the subdistrict frequency point restrictive condition arranging, the frequency of all communities is divided into N population, for setting up the whole network interference matrix in the whole network community, for setting up road interference matrix in road support community, and utilize each interference matrix of multiobjective genetic algorithm and foundation to calculate the fitness that each population is corresponding, from the fitness calculating, select the fitness that meets target setting, the frequency of population Zhong Ge community corresponding this fitness of selecting is defined as to the optimum frequency of each community, can find out, the present invention is in the time carrying out frequency optimization, considered the integrated planning of network, also the regional areas such as road have been considered, can effectively solve the optimization problem of global index and local regional support, realize and both ensured overall network performance, optimize again the object of Local Property simultaneously.
Brief description of the drawings
The basic flow sheet that Fig. 1 provides for the embodiment of the present invention;
The Establishing process figure of the whole network interference matrix that Fig. 2 provides for the embodiment of the present invention;
Fig. 3 is the curve synoptic diagram of FER and CI;
The Establishing process figure of the road interference matrix that Fig. 4 provides for the embodiment of the present invention;
The difference set schematic diagram that Fig. 5 a provides for the embodiment of the present invention;
The difference set schematic diagram after treatment after filtering that Fig. 5 b provides for the embodiment of the present invention;
The schematic flow sheet of the step 104 that Fig. 6 provides for the embodiment of the present invention;
The structure chart of the device that Fig. 7 provides for the embodiment of the present invention.
Embodiment
In order to make the object, technical solutions and advantages of the present invention clearer, describe the present invention below in conjunction with the drawings and specific embodiments.
Referring to Fig. 1, the basic flow sheet that Fig. 1 provides for the embodiment of the present invention.As shown in Figure 1, this flow process can comprise the following steps:
Step 101 is set the whole network community in current network, marks off road support community from the whole network community.
This step 101 is to be the whole network community by all cell settings in real network, marks off road support community afterwards according to actual conditions or other modes in this whole network community.
Step 102, is each cell configuration frequency in current network according to the subdistrict frequency point restrictive condition arranging, and the frequency of all communities is divided into N population, and N is positive integer, and is greater than 1.
When this step 102 specific implementation, can comprise: step 1021 is each cell configuration at least two group frequency in current network according to the subdistrict frequency point restrictive condition having arranged, and wherein, in each frequency group, comprises at least one frequency; Step 1022 is selected a frequency group from the frequency group of each community, is combined to form 1 population; Step 1023, the principle according to different population with incomplete same frequency group is returned to execution step B12, until form N population.Such as, in network, there are 3 communities, if the 2 groups of frequencies that have been respectively these 3 cell configuration, the frequency group that is community 1 is frequency group 1 and 2, the frequency group of community 2 is frequency group 3 and 4, and the frequency group of community 3 is frequency group 5 and 6, so, can obtain at most following 8 populations: population 1, it comprises frequency group 1, frequency group 3 and frequency 5; Population 2, it comprises frequency group 1, frequency group 4 and frequency 5; Population 3, it comprises frequency group 1, frequency group 3 and frequency 6; Population 4, it comprises frequency group 1, frequency group 4 and frequency 6; Population 5, it comprises frequency group 2, frequency group 3 and frequency 5; Population 6, it comprises frequency group 2, frequency group 4 and frequency 5; Population 7, it comprises frequency group 2, frequency group 3 and frequency 6; Population 8, it comprises frequency group 2, frequency group 4 and frequency 6.
It should be noted that, consider and calculate simply, this step 102 not necessarily obtains the population being formed by the frequency group of all communities, and it can obtain two or more populations wherein at random, and the embodiment of the present invention does not specifically limit.
As for subdistrict frequency point restrictive condition, it can be according to practical situations setting, such as, it can comprise the restriction of Broadcast Control Channel (BCCH) frequency, the restriction of Traffic Channel (TCH) frequency, use restriction, uses restriction, adjacent cell frequency to use at least one in restriction with base station frequency point with subdistrict frequency point, limit, use restriction, use restriction, adjacent cell frequency use restriction how to arrange with base station frequency point with subdistrict frequency point as for the restriction of BCCH frequency, TCH frequency, the embodiment of the present invention does not specifically limit.
Step 103, for setting up the whole network interference matrix IM in the whole network community
_{all}, for setting up road interference matrix IM in road support community
_{road}.
In frequency optimization, the foundation of interference matrix is crucial, in the embodiment of the present invention, and the whole network interference matrix IM
_{all}the object of setting up is the quality in order to improve overall network, its dependence data from MR measurement report, and road interference matrix IM
_{road}object is the network performance quality for road improvement, its dependence data from frequency sweep data, this had obviously both been ensured overall network performance, optimized again the object of Local Property simultaneously.How to set up as for these two matrixes, be below specifically described.
Step 104, utilize each interference matrix that multiobjective genetic algorithm and step 103 are set up to calculate the fitness that each population is corresponding, from the fitness calculating, select the fitness that meets target setting, the frequency of population Zhong Ge the community corresponding fitness of this selection is defined as to the optimum frequency of each community.
In frequency optimization, determining of frequency allocation algorithm is also key factor, and the present invention had both ensured overall network performance for realizing, and optimized again the object of Local Property simultaneously, adopted multiobjective genetic algorithm conventional in current engineering to realize frequency optimization.Utilize multiobjective genetic algorithm to realize frequency optimization as for how to realize, hereinafter describe in detail.
So far, the flow process shown in Fig. 1 completes description.
The whole network interference matrix IM to step 103 in abovementioned flow process below
_{all}foundation be described.
The frame error rate (FER) is an index for reflecting voiceband user quality, it can objectively respond the impression of user speech quality, there is good linear approximate relationship with speech quality, and be a nonlinear value between 01, most suitable as the weighted value of disturbing.Therefore, for making the whole network interference matrix IM
_{all}more accurate, the invention process example is at definite the whole network interference matrix IM
_{all}time, except depending on mentioned above utilizing MR measurement report, also further depend on FER, concrete flow process as shown in Figure 2.
Referring to Fig. 2, the Establishing process figure of the whole network interference matrix that Fig. 2 provides for the embodiment of the present invention.As shown in Figure 2, this flow process can comprise the following steps:
Step 201 is collected the MR measurement report that each terminal sends in each Serving cell in the timing statistics of setting.
MR measurement report is the report that terminal is carried out the level of 6 the strongest adjacent areas under Serving cell, preferably, in the present embodiment, this MR measurement report also can further comprise the level of Serving cell and the BCCH of adjacent area, BCC, NCC, the information such as TA, wherein, Serving cell is the current residing community of terminal.
Step 202, belongs to according to the MR measurement report with same services community the MR measurement report that the principle of same group collects step 201 and is divided into X group.
That is to say, if the Serving cell that plural MR measurement report carries is identical, this MR measurement report belongs to same group.Certainly,, if the Serving cell that the MR measurement report that step 201 is collected carries is all different from the Serving cell that other MR measurement reports carry, this MR measurement report can be divided into separately to one group.
Step 203, for each group of dividing (being designated as group 1), execution step 204 is to step 209.
Step 204, is averaging the level of organizing the Serving cell that in 1, all MR measurement reports carry, obtains CI1, and judge in this group 1 whether have plural MR measurement report to carry identical adjacent cell, and if so, execution step 205, otherwise, finish current flow process.
Such as, in group 1, comprise 3 MR measurement reports, because the Serving cell that these 3 MR measurement reports carry is identical, therefore, the level of this Serving cell that these 3 MR measurement reports can be carried is averaging, and obtains CI1.
In addition, although the Serving cell that same group of MR measurement report comprising carries is identical, do not represent that the adjacent cell that the MR measurement report in this group carries is also necessarily identical, therefore, need to carry out the decision operation of this step 204.
Step 205, each adjacent cell of judging for step 204 using this adjacent cell interfered cell of Serving cell in group 1, is obtained the level of this interfered cell from organize 1 MR measurement report, and this level obtaining is averaging and obtains CI2.
If step 204 is judged plural MR measurement report in group 1 and has all been carried adjacent cell 1 and adjacent cell 2, therefore, while carrying out this step 205, by this each adjacent cell of judging, such as adjacent cell 1, (principle of adjacent cell 2 is similar, repeat no more) as the interfered cell of organizing Serving cell in 1, the level that obtains this adjacent cell 1 from organize 1 MR measurement report, is averaging and obtains level CI2 this level obtaining.
It should be noted that, step 204 to step 205 is to be greater than at 1 o'clock in the group 1 MR measurement report number comprising to carry out, if and step 202 by the Serving cell of carrying from other MR measurement reports all a different MR measurement report be divided into separately one group such as group 1, that is to say, group 1 only comprises 1 MR measurement report, for this situation, step 204 to step 205 can be carried out following step: using the level of the Serving cell that in group 1, MR measurement report carries as level CI1, for each adjacent cell that in group 1, MR measurement report carries, using the interfered cell of this adjacent cell Serving cell in group 1, the level that obtains this interfered cell from organize 1 MR measurement report is as level CI2.What this situation occurred in actual applications is possible smaller, therefore, does not do emphasis and describes.
Step 206, the difference of calculating CI1 and CI2 obtains difference CI3, utilizes this CI3 to calculate FER.
The present embodiment is according to the wireless link emulation of existing document, and the network model that wireless link emulation is used is TU3 model, can calculate FER according to following formula:
In addition, the embodiment of the present invention provides the curve synoptic diagram of FER and CI, and specifically as shown in Figure 3, in Fig. 3, abscissa is level value, and ordinate is FER value.As can be seen from Figure 3: in the time that level exceedes certain thresholding, the value of FER is substantially suitable, and at10db to 10db within the scope of this, the value of FER changes greatly, this has also just reflected in interferencelimited network, as long as the certain CI value of guarantee just can meet the demand of network quality, and too strong CI value does not need, in the time carrying out this step 206, also can directly obtain corresponding FER from Fig. 3 according to CI3.
Step 207, the level of the Serving cell that in calculating group 1, each MR measurement report carries and the difference of each level that step 205 is obtained, form CI set.
It should be noted that, this step 207 also can execute and obtain after level in step 205, and carries out before execution obtains CI2, and the embodiment of the present invention does not specifically limit.
Step 208, is greater than the number of times P1 that the difference of the first set point occurs in statistics CI set, the FER calculating according to this P1 and step 206 determines the cochannel interference value IM of group 1
_{with frequently}(i, j).
Wherein, the first set point can be according to actual conditions setting, such as can be6db.
In this step 208, the FER calculating according to P1 and step 206 determines the cochannel interference value IM of group 1
_{with frequently}(i, j) specifically comprises: step 2081, utilize the cochannel interference absolute probability of the quantity P calculating group 1 of all differences in P1 and CI set, and wherein, step 2081 is specially: calculate the business of P1 and P, the cochannel interference absolute probability using this business as this group; Step 2082, the FER that utilizes cochannel interference absolute probability to calculate step 206 is weighted processing, obtains, with frequency absolute interference value, this being normalized with frequency absolute interference value, obtains organizing 1 cochannel interference value IM
_{with frequently}(i, j), wherein, i represents Serving cell mark, j represents the interfered cell mark of Serving cell.
Step 209, is greater than the number of times P2 that the difference of the second set point occurs in statistics CI set, the FER calculating according to P2 and step 206 determines the adjacent frequency interference value IM of group 1
_{adjacent frequency}(i, j).
In the present embodiment, the second set point is much larger than the first set point, such as can be 12db.
In this step 209, the FER calculating according to P2 and step 206 determines the adjacent frequency interference value IM of group 1
_{adjacent frequency}(i, j) specifically comprises: step 2091, and utilize the adjacent frequency of the quantity P calculating group 1 of all differences in P2 and CI set to disturb absolute probability, wherein, this step 2091 is specially: calculate the business of P2 and P, the adjacent frequency using this business as group 1 is disturbed absolute probability; Step 2092, the FER that utilizes this adjacent frequency to disturb absolute probability to calculate step 206 is weighted processing, obtains adjacent frequency absolute interference value, and this adjacent frequency absolute interference value is normalized, and obtains organizing 1 adjacent frequency interference value IM
_{adjacent frequency}(i, j).
It should be noted that, step 208 does not have regular time sequencing to step 209, and it also can first perform step 209, performs step afterwards 208.
Step 210, arranges the cochannel interference value of X group and adjacent frequency interference value according to setting order, obtain the whole network interference matrix IM
_{all}.
Here, setting order can be laterally or is longitudinal, and the embodiment of the present invention does not specifically limit.
So far, obtain the whole network interference matrix IM by the flow process shown in Fig. 2
_{all}.
Road interference matrix IM to step 103 in abovementioned flow process below
_{road_k}foundation be described.
Because MR measurement report can not reflect the test case of road, therefore do not adopt MR data here but adopt and can accurately reflect that the frequency sweep data of road disturbed condition set up road interference matrix IM
_{road_k}, concrete flow process as shown in Figure 4.
Referring to Fig. 4, the Establishing process figure of the road interference matrix that Fig. 4 provides for the embodiment of the present invention.As shown in Figure 4, this flow process can comprise:
Step 401, determines the section under each road support community respectively.
This step 401 can be divided the section under each road support community difference according to actual conditions.
Step 402, performs step 403 to step 408 for each section (being designated as section 1).
Step 403, the road support community comprising from section 1, determine Serving cell and interfered cell.
In this step 403, the definite of Serving cell comprises: the level that obtains all road supports community on section 1 from scandata (comprising cell ID and community level), from the level obtaining, select the strongest level, it is the level of value maximum, for each road support community on section 1, set numeric ratio as 6db if the difference of the level of the level that this is selected and this road support community is less than, determine that this road support community is the Serving cell on section 1.It should be noted that, the quantity of the Serving cell that this step 403 is determined is more than or equal to 1.
And interfered cell is the community outside Zhong Chu Serving cell, all road supports community on section 1.
Step 404, each Serving cell of determining for step 403, forms respectively interfered cell pair by each interfered cell on this Serving cell and section 1.
Such as, the road support community in section 1 is community 1 to 4, and wherein, community 1 and community 2 are confirmed as the Serving cell on section 1 in step 403, and community 3 to community 4 is the interfered cell on section 1, so, while carrying out this step 404, for each Serving cell, such as community 1, (principle of community 2 is similar, repeat no more), community 1 and community 3 are formed to interfered cell pair, and community 1 and community 4 are formed to interfered cell pair.
Step 405 for each interfered cell pair, is obtained the level of this centering Serving cell, interfered cell and interfered cell from scandata, and the difference of the level of calculation services community and interfered cell obtains difference set.
Fig. 5 a shows the schematic diagram of difference set.In Fig. 5 a, abscissa is level difference value, and ordinate is the number of times that level difference value occurs.
Step 406, the difference set that step 405 is obtained is carried out filtering processing.
Because frequency sweep data are just for specific road section test gained, the result randomness obtaining is like this very high, and therefore, the difference set that the embodiment of the present invention need to obtain step 405 is carried out filtering processing, to eliminate accidentalia as far as possible.If the difference set that step 405 forms is as shown in Figure 5 a, while carrying out this step 406, the difference set shown in Fig. 5 a is carried out to filtering processing, obtain the difference set shown in Fig. 5 b.
Step 407, in statistical difference value set, be greater than the 3rd set point difference occur number of times P3, utilize the quantity of all differences in P3 and difference set to determine the cochannel interference value IM that this interfered cell is right
_{road_k}(i, j)
_{with frequently}.
In this step 407, the 3rd set point can be identical with the first set point above, such as being6db, and also can be different.Wherein, if difference set as shown in Figure 5 b, can directly obtain P3 from the difference set shown in Fig. 5 b.
In this step 407, utilize the quantity of all differences in P3 and difference set to determine the cochannel interference value IM that this interfered cell is right
_{road_k}(i, j)
_{with frequently}specifically comprise: step 4071, utilize the quantity of all differences in P3 and difference set to calculate the right cochannel interference absolute probability in this interfered cell, wherein, step 4071 is specially: calculate the business of the quantity of all differences in P3 and difference set, using this business cochannel interference absolute probability right as this interfered cell; Step 4072, utilizes cochannel interference absolute probability to determine the cochannel interference value IM that interfered cell is right
_{road_k}(i, j)
_{with frequently}, wherein, step 4072 can realize by following formula:
Wherein, k is the mark in section 1, and i is the mark of centering Serving cell, interfered cell, and j is the mark of centering interfered cell, interfered cell, CI
_{i, j}poor for the level of centering Serving cell, interfered cell and interfered cell, C (CI
_{i, j}) expression CI
_{i, j}the number of times occurring in difference set,
represent the right mean F ER in interfered cell, specifically can be referring to the calculating of abovementioned steps 206.
Step 408, in statistical difference value set, be greater than the 4th set point difference occur number of times P4, utilize the quantity of all differences in P4 and difference set to determine the adjacent frequency interference value IM that this interfered cell is right
_{road_k}(i, j)
_{adjacent frequency}.
In this step 408, the 4th set point can be identical with the second set point above, such as being 12db, and also can be different.Wherein, if difference set as shown in Figure 5 b, can directly obtain P4 from the difference set shown in Fig. 5 b.
In this step 408, utilize the quantity of all differences in P4 and difference set to determine the adjacent frequency interference value IM that this interfered cell is right
_{road_k}(i, j)
_{adjacent frequency}specifically comprise: step 4081, utilize the quantity of all differences in P4 and difference set to calculate adjacent frequency interference absolute probability, wherein, step 4081 is specially: calculate the business of the quantity of all differences in P4 and difference set, adjacent frequency right as this interfered cell this business is disturbed to absolute probability; Step 4082, utilizes this adjacent frequency to disturb absolute probability to determine the adjacent frequency interference value that interfered cell is right, and wherein, step 4082 can realize by following formula:
Step 409, arranges cochannel interference value right all interfered cells on all sections and adjacent frequency interference value according to setting order, obtain road interference matrix.
So far, obtain road interference matrix IM by the flow process shown in Fig. 4
_{road_k}.
It should be noted that, for improving local optimum function, in abovementioned steps 101, also can further comprise: from the whole network community, mark off community, key area; So, step 103 further comprises: key area interference matrix is set up in the community, region of attaching most importance to.Wherein, the foundation of this key area interference matrix depends on the whole network interference matrix shown in Fig. 2, specifically comprises: the X group of dividing from step 202, find the group of community, Wei Gai key area, Serving cell such as group 1; From the whole network interference matrix, select cochannel interference value and the alien frequencies interference value of this group; The cochannel interference value of selecting and alien frequencies interference value are arranged according to described setting order, obtain key area interference matrix.
Based on this, the step 104 in abovementioned flow process specifically can comprise the flow process shown in Fig. 6:
Step 601, determines respectively the whole network interference matrix, road interference matrix and target function corresponding to key area interference matrix.
In this step 601, the target function (being designated as the whole network target function) that the whole network interference matrix is corresponding can be determined by following formula:
Wherein, Q (x
_{i, j}) IM
_{all}(i, j)=Q
_{with frequently}(x
_{i, j}) IM
_{with frequently}(i, j)+Q
_{adjacent frequency}(x
_{i, j}) IM
_{adjacent frequency}(i, j);
The target function (being designated as road target function) that road interference matrix is corresponding is determined by following formula:
Wherein, Q (x
_{i, j}) IM
_{roadk}(i, j)=Q
_{with frequently}(x
_{i, j}) IM
_{roadk is with frequently}(i, j)+Q
_{adjacent frequency}(x
_{i, j}) IM
_{roadk adjacent frequency}(i, j), the numbering that k is section;
The target function (being designated as highest priority function) that key area interference matrix is corresponding is determined by following formula:
Wherein, Q (x
_{i, j}) IM (i, j)=Q
_{with frequently}(x
_{i, j}) IM
_{with frequently}(i, j)+Q
_{adjacent frequency}(x
_{i, j}) IM
_{adjacent frequency (}i, j) in abovementioned three formula, i represents Serving cell mark, j represents the interfered cell mark of this Serving cell, IM
_{with frequently}(i, j) is the definite cochannel interference value of Serving cell i and interfered cell j, IM
_{adjacent frequency}(i, j) is the definite adjacent frequency interference value of Serving cell i and interfered cell j, b
_{j}for the telephone traffic of interfered cell j, x
_{i, j}for the frequency combination of Serving cell i and interfered cell j, Q
_{with frequently}(x
_{i, j}) represent that interfered cell j judges the factor, Q to the same frequency of Serving cell i
_{adjacent frequency}(x
_{i, j}) represent that interfered cell j judges the factor to the adjacent frequency of Serving cell i.
Wherein, Q
_{with frequently}(x
_{i, j}) and Q
_{adjacent frequency}(x
_{i, j}) determine by following formula respectively:
Wherein, P
_{i}represent the frequency of Serving cell i, P
_{j}represent the frequency of interfered cell j.
Step 602, the N that poll step 102 an obtains population, in each target function that the frequency substitution step 601 that the population being polled to is comprised obtains, obtains the fitness that this population is corresponding.
Step 603, judges whether this fitness meets the termination condition of setting, if so, and execution step 604, otherwise, execution step 605.
Termination condition in this step 603 specifically can be according to actual conditions setting.
Step 604 is selected the fitness that meets target setting from the fitness having obtained, and the frequency of population Zhong Ge community corresponding this fitness of selecting is defined as to the optimum frequency of each community.Finish current flow process.
So far, can obtain the optimum frequency of each community in network by step 604, realize the frequency optimization of network.
Step 605, judges whether this population is last population of not calculated fitness, if so, and execution step 606; Otherwise, execution step 607.
Step 606 is selected the fitness that value is greater than predetermined threshold value from the fitness having obtained, and this population of selecting is carried out to genetic manipulation and obtain new population, and the new population that poll obtains, returns to the substitution operation in execution step 602.
Genetic manipulation in this step 606 mainly comprises the operation of selection, crossover and mutation, specifically how this population of selecting is carried out genetic manipulation obtain new population can be similar with existing mode, repeat no more here.
Step 607, continues poll by the population of calculating usage degree, returns to the substitution operation in step 602.
So far, the concrete operations of step 104 in the embodiment of the present invention have been realized.
The method above embodiment of the present invention being provided is described, and the device below embodiment of the present invention being provided is described.
Referring to Fig. 7, the structure drawing of device that Fig. 7 provides for the embodiment of the present invention.As shown in Figure 7, this device can comprise:
Division unit 701 for set the whole network community in current network, and marks off road support community from the whole network community;
Dispensing unit 702, for being each cell configuration frequency of current network according to the subdistrict frequency point restrictive condition arranging, is divided into N population by the frequency of all communities, and N is positive integer, and is greater than 1;
Set up unit 703, be used to the whole network community to set up the whole network interference matrix, for setting up road interference matrix in road support community;
Determining unit 704, for utilizing multiobjective genetic algorithm and described each interference matrix set up unit of setting up to calculate the fitness that each population is corresponding, from the fitness calculating, select the fitness that meets target setting, the frequency of population Zhong Ge community corresponding this fitness of selecting is defined as to the optimum frequency of each community.
Wherein, set up unit 703 and comprise that the whole network interference matrix is set up subelement 7031 and road interference matrix is set up subelement 7032.
Wherein, the whole network interference matrix is set up subelement 7031 for setting up the whole network interference matrix according to MR measurement report and FER;
Road interference matrix is set up subelement 7032 for setting up road interference matrix according to frequency sweep data.
Preferably, in the present embodiment, when setting up subelement 7031 specific implementation, the whole network interference matrix can comprise the structure shown in Fig. 7.As shown in Figure 7, this whole network interference matrix is set up subelement 7031 and can be comprised:
Divide module 7031a, for the principle that belongs to same group according to the MR measurement report with same services community, the MR measurement report of collecting in timing statistics is divided into X group;
Judge module 7032a, be used for for each group, the level of the Serving cell that in this group, all MR measurement reports carry is averaging and obtains CI1, and judge in this group whether have plural MR measurement report to carry identical adjacent cell, if, transmission processing is notified to the first processing module 7033a, otherwise, finish current flow process;
The first processing module 7033a, be used for receiving after described processing notice, each adjacent cell of judging for described judge module, determine that this adjacent cell is the interfered cell of Serving cell in this group, from the MR measurement report of this group, obtain the level of this interfered cell, calculate the difference of level and each level that this obtains of the Serving cell that in this group, each MR measurement report carries, form CI set; And, all level that obtain are averaging and obtain CI2, calculate FER according to the difference CI3 of described CI1 and CI2;
The second processing module 7034a, be greater than the number of times P1 of the difference appearance of the first set point for adding up CI set, determine the cochannel interference value of this group according to the FER of this P1 and described the first processing module calculating, and the number of times P2 that occurs of the difference that is greater than the second set point in statistics CI set, determine the adjacent frequency interference value of this group according to the FER of this P2 and the first processing module 7033a calculating, wherein, described the second set point is greater than the first set point;
First sets up module 7035a, for the cochannel interference value of X group and adjacent frequency interference value are arranged according to setting order, obtains the whole network interference matrix.
Wherein, the second processing module 7034a determines that according to the FER of P1 and the first processing module 7033a calculating the cochannel interference value of this group is: the cochannel interference absolute probability of calculating this group according to the quantity P of all differences in P1 and CI set, the FER that utilizes this cochannel interference absolute probability to calculate described the first processing module is weighted processing, obtain with frequency absolute interference value, this is normalized with frequency absolute interference value, obtains the cochannel interference value of this group;
The second processing module 7034a determines that according to the FER of P2 and the first processing module 7033a calculating the adjacent frequency interference value of this group is: the adjacent frequency of calculating this group according to the quantity P of all differences in P2 and CI set is disturbed absolute probability, utilize adjacent frequency to disturb absolute probability to be weighted processing to the FER that described the first processing module is calculated, obtain adjacent frequency absolute interference value, this adjacent frequency absolute interference value is normalized, obtains the adjacent frequency interference value of this group.
Preferably, in the present embodiment, when setting up subelement 7032 specific implementation, road interference matrix can comprise the structure shown in Fig. 7.As shown in Figure 7, this road interference matrix is set up subelement 7032 and can be comprised:
The first determination module 7031b, for determining the section under each road support community difference;
The second determination module 7032b, for for each section, determines Serving cell and interfered cell in the road support community comprising from this section; And, for each Serving cell, this Serving cell and each interfered cell are formed respectively to interfered cell pair;
Computing module 7033b, for each interfered cell pair for the second determination module 7032b composition, the level that obtains this centering Serving cell, interfered cell and interfered cell from scandata, the difference of the level of calculation services community and interfered cell obtains difference set;
Statistical module 7034b, for statistical difference value set be greater than the 3rd set point difference occur number of times P3, utilize the quantity of all differences in P3 and difference set to determine the cochannel interference value that this interfered cell is right; And, in statistical difference value set, be greater than the 4th set point difference occur number of times P4, utilize the quantity of all differences in P4 and difference set to determine the adjacent frequency interference value that this interfered cell is right, wherein, described the 4th set point is greater than the 3rd set point;
Second sets up module 7035b, for cochannel interference value right all interfered cells on all sections and adjacent frequency interference value are arranged according to setting order, obtains road interference matrix.
In the present embodiment, division unit 701 is further used for marking off community, key area from the whole network community;
Setting up unit 703 further comprises: key area matrix is set up subelement 7033;
Wherein, key area matrix is set up subelement 7033, is used to community, key area to set up key area interference matrix, specifically can comprise:
Search module 7031c, find the group of community, Wei Gai key area, Serving cell for the X group from described division Module Division;
Select module 7032c, for select cochannel interference value and the adjacent frequency interference value of searching the group that module 7031c finds from described the whole network interference matrix;
The 3rd sets up module 7033c, for the cochannel interference value of selecting and adjacent frequency interference value are arranged according to described setting order, obtains key area interference matrix.
In the present embodiment, determining unit 704 can comprise:
Determine subelement 7041, for determining respectively the whole network interference matrix, road interference matrix and target function corresponding to key area interference matrix;
Computation subunit 7042, for a poll N population, the frequency substitution that the population being polled to is comprised, to each target function of determining that subelement is determined, obtains the fitness that this population is corresponding;
Judgment subunit 7043, for judging whether this fitness meets the termination condition of setting, if, from the fitness having obtained, select the fitness that meets target setting, the frequency of population Zhong Ge community corresponding this fitness of selecting is defined as to the optimum frequency of each community, otherwise, trigger computation subunit 7042 and continue to carry out the operation of poll population.
Wherein, the operation that judgment subunit 7043 triggers computation subunit 7042 continuation execution poll populations comprises: judge whether this population is last population of not calculated fitness, if not, trigger computation subunit 7042 polls by the population of calculating usage degree; If so, from the fitness having obtained, select the fitness that value is greater than predetermined threshold value, this population of selecting is carried out to genetic manipulation and obtain new population, trigger the new population that computation subunit 7042 polls obtain.
The device above embodiment of the present invention being provided is described.
As can be seen from the above technical solutions, in the present invention, by setting the whole network community, and from the whole network community, mark off road support community, be each cell configuration frequency in current network according to the subdistrict frequency point restrictive condition arranging, the frequency of all communities is divided into N population, for setting up the whole network interference matrix in the whole network community, for setting up road interference matrix in road support community, and utilize each interference matrix of multiobjective genetic algorithm and foundation to calculate the fitness that each population is corresponding, from the fitness calculating, select the fitness that meets target setting, the frequency of population Zhong Ge community corresponding this fitness of selecting is defined as to the optimum frequency of each community, can find out, the present invention is in the time carrying out frequency optimization, considered the integrated planning of network, also the regional areas such as road have been considered, can effectively solve the optimization problem of global index and local regional support, realize and both ensured overall network performance, optimize again the object of Local Property simultaneously.
The foregoing is only preferred embodiment of the present invention, in order to limit the present invention, within the spirit and principles in the present invention not all, any amendment of making, be equal to replacement, improvement etc., within all should being included in the scope of protection of the invention.
Claims (18)
1. an implementation method for frequency optimization, is characterized in that, the method comprises:
A sets the whole network community in current network, marks off road support community from the whole network community;
B, is each cell configuration frequency in current network according to the subdistrict frequency point restrictive condition arranging, and the frequency of all communities is divided into N population, and N is positive integer, and is greater than 1;
C, for setting up the whole network interference matrix in the whole network community, for setting up road interference matrix in road support community; Wherein, described the whole network interference matrix is used for improving overall network quality, sets up according to mobile statistics MR measurement report and frame error rate FER; Described road interference matrix, for the network performance quality of road improvement, is set up according to frequency sweep data;
D, each interference matrix that utilizes multiobjective genetic algorithm and step C to set up calculates the fitness that each population is corresponding, from the fitness calculating, select the fitness that meets target setting, the frequency of population Zhong Ge the community corresponding fitness of this selection is defined as to the optimum frequency of each community.
2. method according to claim 1, is characterized in that, described step B comprises:
B11, is each cell configuration at least two group frequency in current network according to the subdistrict frequency point restrictive condition having arranged, and in each frequency group, comprises at least one frequency;
B12 selects a frequency group from the frequency group of each community, is combined to form 1 population;
B13, the principle according to different population with incomplete same frequency group is returned to execution step B12, until form N population.
3. method according to claim 1 and 2, it is characterized in that, described subdistrict frequency point restrictive condition comprises the restriction of BCCH channel of broadcast control frequency, the restriction of Traffic Channel TCH frequency, uses restriction, uses restriction, adjacent area frequency to use at least one in restriction with base station frequency point with subdistrict frequency point.
4. method according to claim 1, is characterized in that, sets up the whole network interference matrix comprise according to MR measurement report and FER:
C11, the MR measurement report of collecting in timing statistics is divided into X group by the principle that belongs to same group according to the MR measurement report with same services community; Perform step C12 to step C14 for each group;
C12, is averaging and obtains CI1 the level of the Serving cell that in this group, all MR measurement reports carry, and judges in this group whether have plural MR measurement report to carry identical adjacent cell, if so, and execution step C13; Otherwise, finish current flow process;
C13, each adjacent cell of judging for step C12, determine that this adjacent cell is the interfered cell of Serving cell in this group, from the MR measurement report of this group, obtain the level of this interfered cell, calculate the difference of level and each level that this obtains of the Serving cell that in this group, each MR measurement report carries, form CI set; And, all level that obtain are averaging and obtain CI2, calculate FER according to the difference CI3 of described CI1 and CI2;
C14, in statistics CI set, be greater than the number of times P1 of the difference appearance of the first set point, determine the cochannel interference value of this group according to the FER of this P1 and step C13 calculating, and the number of times P2 that occurs of the difference that is greater than the second set point in statistics CI set, determine the adjacent frequency interference value of this group according to the FER of this P2 and step C13 calculating, wherein, described the second set point is greater than the first set point;
C15, arranges the cochannel interference value of X group and adjacent frequency interference value according to setting order, obtain the whole network interference matrix.
5. method according to claim 4, it is characterized in that, in described step C14, determine that according to the FER of P1 and step C13 calculating the cochannel interference value of this group comprises: the cochannel interference absolute probability of calculating this group according to the quantity P of all differences in P1 and CI set; The FER that utilizes this cochannel interference absolute probability to calculate step C13 is weighted processing, obtains, with frequency absolute interference value, this being normalized with frequency absolute interference value, obtains the cochannel interference value of this group;
In described step C14, determine that according to the FER of P2 and step C13 calculating the adjacent frequency interference value of this group comprises: the adjacent frequency of calculating this group according to the quantity P of all differences in P2 and CI set is disturbed absolute probability; Utilize adjacent frequency to disturb absolute probability to be weighted processing to the FER that step C13 is calculated, obtain adjacent frequency absolute interference value, this adjacent frequency absolute interference value is normalized, obtain the adjacent frequency interference value of this group.
6. method according to claim 1, is characterized in that, sets up road interference matrix comprise according to frequency sweep data:
C21, determines the section under each road support community respectively, performs step C22 to step C24 for each section;
C22, determines Serving cell and interfered cell in the road support community comprising from this section, for each Serving cell, this Serving cell and each interfered cell is formed respectively to interfered cell pair;
C23 for each interfered cell pair, obtains the level of this centering Serving cell, interfered cell and interfered cell from scandata, and the difference of the level of calculation services community and interfered cell obtains difference set;
C24, in statistical difference value set, be greater than the 3rd set point difference occur number of times P3, utilize the quantity of all differences in P3 and difference set to determine the cochannel interference value that this interfered cell is right; And, in statistical difference value set, be greater than the 4th set point difference occur number of times P4, utilize the quantity of all differences in P4 and difference set to determine the adjacent frequency interference value that this interfered cell is right, wherein, described the 4th set point is greater than the 3rd set point;
C25, arranges cochannel interference value right all interfered cells on all sections and adjacent frequency interference value according to setting order, obtain road interference matrix.
7. method according to claim 4, is characterized in that, described steps A further comprises: from the whole network community, mark off community, key area;
Described step C further comprises: key area interference matrix is set up in the community, region of attaching most importance to, and is specially:
The X group of dividing from step C11, find the group of community, Wei Gai key area, Serving cell;
From the whole network interference matrix, select cochannel interference value and the adjacent frequency interference value of this group;
The cochannel interference value of selecting and adjacent frequency interference value are arranged according to described setting order, obtain key area interference matrix.
8. method according to claim 7, is characterized in that, described step D comprises:
D1, determines respectively the whole network interference matrix, road interference matrix and target function corresponding to key area interference matrix;
D2, a poll N population, the frequency substitution that the population being polled to is comprised, to each target function in step D1, obtains the fitness that this population is corresponding;
D3, judge whether this fitness meets the termination condition of setting, if, from the fitness having obtained, select the fitness that meets target setting, the frequency of population Zhong Ge community corresponding this fitness of selecting is defined as to the optimum frequency of each community, otherwise, continue to carry out the operation of poll population.
9. method according to claim 8, is characterized in that, the operation that continues poll population in described step D3 comprises:
Judge whether this population is last population of not calculated fitness, and if not, poll is not calculated the population of usage degree; If so, select the fitness that value is greater than predetermined threshold value from the fitness having obtained, this population of selecting is carried out to genetic manipulation and obtain new population, the new population that poll obtains, returns to the substitution operation in execution step D2.
10. method according to claim 8, is characterized in that, the target function that in described D1, the whole network interference matrix is corresponding represents by following formula:
Wherein, Q (x
_{i,j}) IM
_{all}(i, j)=Q
_{with frequently}(x
_{i,j}) IM
_{with frequently}(i, j)+Q
_{adjacent frequency}(x
_{i,j}) IM
_{adjacent frequency}(i, j);
The target function that in described D1, road interference matrix is corresponding represents by following formula:
Q (x
_{i,j}) IM
_{road_k}(i, j)=Q
_{with frequently}(x
_{i,j}) IM
_{with frequently}(i, j)+Q
_{adjacent frequency}(x
_{i,j}) IM
_{adjacent frequency}(i, j);
The target function that in described D1, key area matrix is corresponding represents by following formula:
Wherein, Q (x
_{i,j}) IM (i, j)=Q
_{with frequently}(x
_{i,j}) IM
_{with frequently}(i, j)+Q
_{adjacent frequency}(x
_{i,j}) IM
_{adjacent frequency}(i, j)
I represents Serving cell mark, and j represents the interfered cell mark of this Serving cell, IM
_{with frequently}(i, j) is the definite cochannel interference value of Serving cell i and interfered cell j, IM
_{adjacent frequency}(i, j) is the definite adjacent frequency interference value of Serving cell i and interfered cell j, b
_{j}for the telephone traffic of interfered cell j, x
_{i,j}for the frequency combination of Serving cell i and interfered cell j, Q
_{with frequently}(x
_{i,j}) represent that interfered cell j judges the factor, Q to the same frequency of Serving cell i
_{adjacent frequency}(x
_{i,j}) represent that interfered cell j judges the factor to the adjacent frequency of Serving cell i.
11. methods according to claim 10, is characterized in that, described Q
_{with frequently}(x
_{i,j}) and Q
_{adjacent frequency}(x
_{i,j}) determine by following formula:
Wherein, P
_{i}represent the frequency of Serving cell i, P
_{j}represent the frequency of interfered cell j.
The implement device of 12. 1 kinds of frequency optimizations, is characterized in that, this device comprises:
Division unit for set the whole network community in current network, and marks off road support community from the whole network community;
Dispensing unit, for being each cell configuration frequency of current network according to the subdistrict frequency point restrictive condition arranging, is divided into N population by the frequency of all communities, and N is positive integer, and is greater than 1;
Set up unit, be used to the whole network community to set up the whole network interference matrix, for setting up road interference matrix in road support community;
Determining unit, for utilizing multiobjective genetic algorithm and described each interference matrix set up unit of setting up to calculate the fitness that each population is corresponding, from the fitness calculating, select the fitness that meets target setting, the frequency of population Zhong Ge community corresponding this fitness of selecting is defined as to the optimum frequency of each community;
The described unit of setting up comprises that the whole network interference matrix is set up subelement and road interference matrix is set up subelement, wherein,
Described the whole network interference matrix is set up subelement for setting up the whole network interference matrix according to mobile statistics MR measurement report and frame error rate FER;
Described road interference matrix is set up subelement for setting up road interference matrix according to frequency sweep data.
13. devices according to claim 12, is characterized in that, described the whole network interference matrix is set up subelement and comprised:
Divide module, for the principle that belongs to same group according to the MR measurement report with same services community, the MR measurement report of collecting in timing statistics is divided into X group;
Judge module, be used for for each group, the level of the Serving cell that in this group, all MR measurement reports carry is averaging and obtains CI1, and judge in this group whether have plural MR measurement report to carry identical adjacent cell, if, transmission processing is notified to the first processing module, otherwise, finish current flow process;
Described the first processing module, be used for receiving after described processing notice, each adjacent cell of judging for described judge module, determine that this adjacent cell is the interfered cell of Serving cell in this group, from the MR measurement report of this group, obtain the level of this interfered cell, calculate the difference of level and each level that this obtains of the Serving cell that in this group, each MR measurement report carries, form CI set; And, all level that obtain are averaging and obtain CI2, calculate FER according to the difference CI3 of described CI1 and CI2;
The second processing module, be greater than the number of times P1 of the difference appearance of the first set point for adding up CI set, determine the cochannel interference value of this group according to the FER of this P1 and described the first processing module calculating, and the number of times P2 that occurs of the difference that is greater than the second set point in statistics CI set, determine the adjacent frequency interference value of this group according to the FER of this P2 and described the first processing module calculating, wherein, described the second set point is greater than the first set point;
First sets up module, for the cochannel interference value of X group and adjacent frequency interference value are arranged according to setting order, obtains the whole network interference matrix.
14. devices according to claim 13, it is characterized in that, described the second processing module determines that according to the FER of P1 and described the first processing module calculating the cochannel interference value of this group is: the cochannel interference absolute probability of calculating this group according to the quantity P of all differences in P1 and CI set, the FER that utilizes this cochannel interference absolute probability to calculate described the first processing module is weighted processing, obtain with frequency absolute interference value, this is normalized with frequency absolute interference value, obtains the cochannel interference value of this group;
Described the second processing module determines that according to the FER of P2 and described the first processing module calculating the adjacent frequency interference value of this group is: the adjacent frequency of calculating this group according to the quantity P of all differences in P2 and CI set is disturbed absolute probability, utilize adjacent frequency to disturb absolute probability to be weighted processing to the FER that described the first processing module is calculated, obtain adjacent frequency absolute interference value, this adjacent frequency absolute interference value is normalized, obtains the adjacent frequency interference value of this group.
15. devices according to claim 12, is characterized in that, described road interference matrix is set up subelement and comprised:
The first determination module, for determining the section under each road support community difference;
The second determination module, for for each section, determines Serving cell and interfered cell in the road support community comprising from this section; And, for each Serving cell, this Serving cell and each interfered cell are formed respectively to interfered cell pair;
Computing module for each interfered cell pair for described the second determination module composition, obtains the level of this centering Serving cell, interfered cell and interfered cell from scandata, and the difference of the level of calculation services community and interfered cell obtains difference set;
Statistical module, for statistical difference value set be greater than the 3rd set point difference occur number of times P3, utilize the quantity of all differences in P3 and difference set to determine the cochannel interference value that this interfered cell is right; And, in statistical difference value set, be greater than the 4th set point difference occur number of times P4, utilize the quantity of all differences in P4 and difference set to determine the adjacent frequency interference value that this interfered cell is right, wherein, described the 4th set point is greater than the 3rd set point;
Second sets up module, for cochannel interference value right all interfered cells on all sections and adjacent frequency interference value are arranged according to setting order, obtains road interference matrix.
16. devices according to claim 13, is characterized in that, described division unit is further used for marking off community, key area from the whole network community;
The described unit of setting up further comprises:
Key area matrix is set up subelement, is used to community, key area to set up key area interference matrix, specifically comprises:
Search module, find the group of community, Wei Gai key area, Serving cell for the X group from described division Module Division;
Select module, for search described in selecting from described the whole network interference matrix module searches to cochannel interference value and the adjacent frequency interference value of group;
The 3rd sets up module, for the cochannel interference value of selecting and adjacent frequency interference value are arranged according to described setting order, obtains key area interference matrix.
17. devices according to claim 16, is characterized in that, described determining unit comprises:
Determine subelement, for determining respectively the whole network interference matrix, road interference matrix and target function corresponding to key area interference matrix;
Computation subunit, for a poll N population, the frequency substitution that the population being polled to is comprised, to each target function of determining that subelement is determined, obtains the fitness that this population is corresponding;
Judgment subunit, for judging whether this fitness meets the termination condition of setting, if, from the fitness having obtained, select the fitness that meets target setting, the frequency of population Zhong Ge community corresponding this fitness of selecting is defined as to the optimum frequency of each community, otherwise, continue to carry out the operation of poll population.
18. devices according to claim 17, is characterized in that, the operation that described judgment subunit continues execution poll population comprises:
Judge that whether this population is last population of not calculated fitness, if not, triggers described computation subunit poll by the population of calculating usage degree; If so, from the fitness having obtained, select the fitness that value is greater than predetermined threshold value, this population of selecting is carried out to genetic manipulation and obtain new population, trigger the new population that described computation subunit poll obtains.
Priority Applications (1)
Application Number  Priority Date  Filing Date  Title 

CN201010515971.1A CN102457852B (en)  20101015  20101015  Realization method of frequency optimization and apparatus thereof 
Applications Claiming Priority (1)
Application Number  Priority Date  Filing Date  Title 

CN201010515971.1A CN102457852B (en)  20101015  20101015  Realization method of frequency optimization and apparatus thereof 
Publications (2)
Publication Number  Publication Date 

CN102457852A CN102457852A (en)  20120516 
CN102457852B true CN102457852B (en)  20140604 
Family
ID=46040403
Family Applications (1)
Application Number  Title  Priority Date  Filing Date 

CN201010515971.1A Active CN102457852B (en)  20101015  20101015  Realization method of frequency optimization and apparatus thereof 
Country Status (1)
Country  Link 

CN (1)  CN102457852B (en) 
Families Citing this family (5)
Publication number  Priority date  Publication date  Assignee  Title 

CN103813344B (en) *  20121112  20170620  中国移动通信集团浙江有限公司  A kind of interference matrix establishment method and system 
CN104754586A (en) *  20131230  20150701  中国移动通信集团福建有限公司  Method and device for automatic replanning frequency 
CN104955099B (en) *  20140326  20180817  中国移动通信集团浙江有限公司  A kind of method and apparatus of analysis area interference 
CN104168577B (en) *  20140806  20180202  武汉虹信技术服务有限责任公司  A kind of the whole network LTE cells PCI method and device for planning 
CN107148053B (en) *  20160301  20211029  中兴通讯股份有限公司  Data configuration method and device 
Citations (2)
Publication number  Priority date  Publication date  Assignee  Title 

GB0525433D0 (en) *  20051214  20060125  Motorola Inc  Apparatus and method for frequency planning for a celluar communication system 
CN101547449A (en) *  20090504  20090930  中国移动通信集团浙江有限公司  Frequency sweep and mobile phone measurement reportbased method for automatic frequency optimization 

2010
 20101015 CN CN201010515971.1A patent/CN102457852B/en active Active
Patent Citations (2)
Publication number  Priority date  Publication date  Assignee  Title 

GB0525433D0 (en) *  20051214  20060125  Motorola Inc  Apparatus and method for frequency planning for a celluar communication system 
CN101547449A (en) *  20090504  20090930  中国移动通信集团浙江有限公司  Frequency sweep and mobile phone measurement reportbased method for automatic frequency optimization 
NonPatent Citations (4)
Title 

基于遗传算法的GSM网络频率规划优化研究与应用;孙媛媛;《中国优秀硕士学位论文全文数据库》;20080917;全文 * 
基于遗传算法的自动频率规划;郝宁波;《安阳师范学院学报》;20050531(第5期);全文 * 
孙媛媛.基于遗传算法的GSM网络频率规划优化研究与应用.《中国优秀硕士学位论文全文数据库》.2008, 
郝宁波.基于遗传算法的自动频率规划.《安阳师范学院学报》.2005,(第5期), 
Also Published As
Publication number  Publication date 

CN102457852A (en)  20120516 
Similar Documents
Publication  Publication Date  Title 

CN106912015B (en)  Personnel trip chain identification method based on mobile network data  
CN101873623B (en)  Automatic frequency optimization method based on measurement report data  
CN107466103B (en)  Terminal positioning method and network equipment  
CN102457852B (en)  Realization method of frequency optimization and apparatus thereof  
CN102970696B (en)  A kind of frequency optimization method for communication system  
CN101409884A (en)  Method for optimizing network frequency based on measurement report  
JP2002057614A (en)  Method and device for evaluating rf propagation in radio communication system  
CN102256256A (en)  Method and device for planning frequency and scrambling codes  
CN107807346A (en)  Adaptive WKNN outdoor positionings method based on OTT Yu MR data  
CN103002459A (en)  Expansion planning method and device for WCDMA (wideband code division multiple access) network  
CN101296477B (en)  Method and device for planning network topological  
CN103765939A (en)  Method for controlling interference from white space units  
CN103037424B (en)  Evaluation method and device of the 3rd generation telecommunication (3G) network coverage  
CN104125580A (en)  Network planning method and apparatus  
CN105163344A (en)  Method for positioning TDLTE intrasystem interference  
CN101730114A (en)  Determining method and device of neighbor cells  
CN103002495A (en)  Assessment method and device of wireless network structure  
CN103974264A (en)  Frequency point optimal selection method  
CN102186203A (en)  Method, device and system for determining data service channel number  
CN102164379B (en)  Method and device for adjusting frequency  
CN104684091B (en)  Network architecture method of adjustment, device, network scheduling controller and base station  
CN101917724B (en)  Method and system for obtaining combined interference matrixes of broadcast control channels  
CN105898766A (en)  Base station planning method and apparatus  
CN108900325B (en)  Method for evaluating adaptability of power communication service and wireless private network technology  
CN101572722B (en)  Method for sensing interception node selected by radio system 
Legal Events
Date  Code  Title  Description 

C06  Publication  
PB01  Publication  
C10  Entry into substantive examination  
SE01  Entry into force of request for substantive examination  
C14  Grant of patent or utility model  
GR01  Patent grant 