CN104349376B - A kind of frequency scrambling code optimizing method and system - Google Patents
A kind of frequency scrambling code optimizing method and system Download PDFInfo
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Abstract
The invention discloses a kind of frequency scrambling code optimizing method and systems, and suitable for TD SCDMA systems, this method includes generation cell-level interference matrix；Corresponding inter-cell frequency scrambler rule is generated according to adjacent area situation；The interference matrix with inter-cell frequency scrambler rule is merged, generates the interference matrix with restrictive condition；Frequency scrambler is optimized using genetic algorithm.Technical scheme of the present invention can rapidly provide frequency scrambling code optimum scheme, increase substantially frequency scrambling code optimum planning efficiency, reduce cost.
Description
Technical field
The present invention relates to network optimisation techniques field more particularly to a kind of frequency scrambling code optimizing method and systems.
Background technology
TD-SCDMA network through development in a few years, have in the construction density and number of users of base station it is considerable into
Step, since TD-SCDMA system employs orthogonal frequency-time multiple access technology, the inter-user interference in cell is greatly inhibited.
And with data service large-scale promotion, intelligent terminal update is universal, and network size, number of users and network are born
Lotus is stepped up, and the interference of minizone becomes the main interference source of network.Since frequency point scrambling code planning in minizone is unreasonable
The problems led and caused also gradually highlight, and become and restrict the key factor that network quality is further promoted.
Current existing TD frequency points and scrambling code planning rely primarily on cell topology and emulation, planning software output result ginseng
The property examined is not strong, and artificial to plan that difficulty is big, producer's dependence is strong.
On the other hand, in the case where frequency resource is limited, identical networking is difficult to avoid that, co-channel interference is to cause network different
The main reason for ordinary affair part, while TD scrambler quantity is few, chip is short, is determined the features such as intersymbol dependence variation after displacement
Scrambling code planning has significant impact to network performance, and the interference problem of minizone is very difficult to avoid completely by manual type.
Invention content
In order to solve the technical issues of frequency scrambling code optimum is ineffective in the prior art, the present invention proposes that a kind of frequency is disturbed
Code optimization method and system can rapidly provide frequency scrambling code optimum scheme, increase substantially frequency scrambling code optimum planning effect
Rate reduces cost.
One aspect of the present invention provides frequency scrambling code optimizing method, suitable for TD-SCDMA system, includes the following steps：
Generate cell-level interference matrix；
Corresponding inter-cell frequency scrambler rule is generated according to adjacent area situation；
The interference matrix with inter-cell frequency scrambler rule is merged, generates the interference matrix with restrictive condition；
Frequency scrambler is optimized using genetic algorithm.
Another aspect of the present invention provides a kind of frequency scrambling code optimum system, suitable for TD-SCDMA system, including generation
Module and optimization module, wherein,
Generation module generates corresponding inter-cell frequency scrambler for generating cell-level interference matrix, according to adjacent area situation and advises
Then, the interference matrix with inter-cell frequency scrambler rule is merged, generates the interference matrix with restrictive condition；
Optimization module is used to optimize frequency scrambler using genetic algorithm.
Technical scheme of the present invention forms one by way of curing rule and establishing interference matrix and does not depend on manufacturer
Then generalized programming model requires to automatically generate corresponding programme according to user, it is achieved thereby that supporting all TD-
SCDMA producers MR parsings import, the function of generation interference matrix, can carry out already existing TD-SCDMA nets in all existing nets
The frequency dividing of network divides scrambling code planning to work；The interference very close to state of the current network is completed in a manner that data and adjacent area combine
Matrix lays a solid foundation for automation operation；It is excellent that frequency scrambler can rapidly be provided by the inventive technique scheme
Change scheme is greatly improved frequency scrambling code optimum planning efficiency, reduces cost.
Description of the drawings
Fig. 1 is the flow chart of the frequency scrambling code optimum in the embodiment of the present invention.
Fig. 2 is the flow chart that prioritization scheme is formulated using genetic algorithm in the embodiment of the present invention.
Fig. 3 is the structure diagram of the frequency scrambling code optimum system in the embodiment of the present invention.
Specific embodiment
The specific embodiment of the present invention is described in detail below in conjunction with the accompanying drawings.
In wireless communication network system, by open MR measure, carry out frequency sweep obtain it is single cell or drive test point small
Level difference situation between area and cell carries out Classifying Sum according to practical situation to data.
According to MR, frequency sweep data situation by decomposing, conclude, normalizing, by cell relations data digital metaplasia
Into the matrix of the reaction interference relationship between cells of pure mathematics.
Inter-cell frequency scrambler rule finds out that forbidden in TD-SCDMA system or there may be influences on existing net
Various restrictive conditions are made including channel code using relative influences business such as probability, minizone delay characteristics, composite code correlations
Restrictive condition.
It, according to demand will be final using the data in interference matrix according to the genetic algorithm for optimizing one of classical theory
Target is divided into several groups and is iterated operation, and inter-cell frequency scrambler rule then incorporates interference matrix as non-applicable population
Screening conditions during evolution are considered to evolve if triggering and unsuccessfully be abandoned.
Fig. 1 is the flow chart of the frequency scrambling code optimum in the embodiment of the present invention.As shown in Figure 1, the frequency scrambling code optimum
Flow suitable for TD-SCDMA system, includes the following steps：
Step 101, generation cell-level interference matrix.Cell-level interference matrix is specified serving cell by neighbouring each cell
The matrix of the probability numbers composition of interference.Usually in the wireless network for having N number of cell, if cell is represented with C, interference matrix
It is then：
Step 102 generates corresponding inter-cell frequency scrambler rule according to adjacent area situation.The rule includes：
1st, main adjacent cell cannot cannot be led with the same downlink frequency pilot code of frequency, any two adjacent area of a cell with frequency with downlink
Frequency code；
2nd, cannot be with scrambler group with station, main adjacent cell cannot be with frequency with scrambler group；
3rd, main adjacent cell cannot same scrambler, any two adjacent area of a cell cannot same scrambler；
4th, outdoor cell and outdoor cell cannot be the same as the same scramblers of frequency in 2 kilometers；
5th, outdoor cell and outdoor cell or outdoor cell and indoor cell cannot be the same as the same downlinks of frequency in 1.5 kilometers
Pilot code, room point cell divide cell cannot be with the same downlink frequency pilot code of frequency in 800 meters with room；
6th, when adjacent area number≤31, main adjacent cell cannot same downlink frequency pilot code.
Step 103 merges the interference matrix with inter-cell frequency scrambler rule, generates the interference square with restrictive condition
Battle array.
The each value of interference matrix in step 101 is multiplied by COEFFICIENT K, wherein not meeting step 102 medium and small interval frequency
The COEFFICIENT K of rate scrambler rule is 1, and the COEFFICIENT K for meeting inter-cell frequency scrambler rule is infinity（It is approximate during realizing
Giving an absolute value can make the coefficient in interference matrix exceed 1）.
Step 104 formulates a frequency scrambling code optimum scheme using genetic algorithm, and required data of developing programs include：It needs
The cell of optimization and protection band cell work parameter evidence are divided, distributes the rule setting of frequency point.
Fig. 2 is the flow chart that prioritization scheme is formulated using genetic algorithm in the embodiment of the present invention.As shown in Fig. 2, the stream
Journey includes the following steps：
Step 201 initializes genetic algorithm.
Individual binary coding is generated according to i*j, wherein i is cell number, and j is that total frequency point demand number or scrambler are always a
Number；
Frequency point allocation is carried out using random fashion, realizes algorithm initialization, wherein the frequency point distributed needs single subdistrict
Meet the frequency point demand of single subdistrict, and frequency point and scrambler distribution meet the inter-cell frequency scrambler rule of setting；
According to the population number defined in systematic parameter, a certain number of populations are generated；
Frequency point and scrambler individual in population are initialized.
Wherein, frequency point initialization further comprises the steps：
The frequency point that this cell has occupied is removed, removal does not meet the frequency point of inter-cell frequency scrambler rule；
By remaining available frequency point, the interference value of each frequency point is calculated according to this area interference matrix, by interference value minimum
Frequency point allocation to this cell, if the frequency point of interference value minimum has multiple, distribute access times minimum frequency point, otherwise with
Machine distributes the frequency point of an interference value minimum；
It repeats the above steps, until all optimization cell initials finish.
Scrambler initialization further comprises the steps：
Removal does not meet the scrambler of inter-cell frequency scrambler rule；
By remaining available scrambler, the interference value of each scrambler is calculated according to this area interference matrix, by interference value minimum
Scrambler distribute to this cell, if the scrambler of interference value minimum has multiple, distribute access times minimum scrambler, otherwise with
Machine distributes the scrambler of an interference value minimum；
It repeats the above steps, until all optimization cell initials finish.
Step 202, assessment population's fitness（Interference value）.
According to the definition of population's fitness=1/ (the total interference value+1 of population), the fitness of single individual in population is calculated, is converged
Always generate the population's fitness of each population；
The label wherein best individual of fitness, the individual for making the fitness best enters selection operation, it is ensured that optimal
Body can be able to heredity.If the fitness of optimum individual is better than the worst individual adaptation degree that this is generated in last iteration,
Using the optimum individual of last iteration, worst individual in this is replaced.
Step 203 carries out selection operation, determines to carry out the individual of mating operation in population.
Selection operation selects regeneration individual for determining which of population individual carries out mating operation, according to fitness,
Probability during the high individual of fitness is chosen is high, and the low individual of fitness may be eliminated, the matter of generation individual to ensure
Amount.
According to fitness, fitness ratio of each individual in population is calculated：
The Population adaptation angle value of adaptation rate DumpFitness=1/ of individual；
Population association adaptation rate RelaFitness=Population adaptation rate/population
It is sorted according to population, the association adaptation rate of the individual of each cumulative front of individual, as the cumulative suitable of current population
It should rate；
Two populations are taken at random, take roulette（Roulette）Mode, determine which population carries out heredity, until
Meet the population of population quantity set.
Step 204 carries out mating operation, generates new individual.
Two random numbers C1 and C2 are generated in (0, i*j), when C1 and C2 is in same a line, then exchange the row data, such as
Fruit C1 and C2 in same a line, are not then expert to C1 C1 and start to row end and C2 places every trade head to hand over to C2 positions
It changes, while the row among two rows is intersected.
Step 205 is adjusted operation, and the individual of post-coitum is adjusted, and will not meet setting in optimization cell
The frequency point and scrambler of allocation rule are rejected, and recalculate legal frequency point and scrambler.
Step 206 carries out mutation operation, presets the random number between one [0.0,1.0], as predetermined probabilities, when working as
Preceding individual mutation probability is more than predetermined probabilities, which is added in population, as the selectable individual of population.
Step 207, generation frequency scrambling code optimum scheme.
According to the fitness value of the population generated in stock assessment, when in the population of generation, exist meet end condition when
（For example fitness reaches 0 or meets the iterations specified）, system closure analysis process, and current optimal solution is exported, it is defeated
The optimal solution gone out is the prioritization scheme of frequency point and scrambler for optimizing cell.
In order to realize above-mentioned flow, the embodiment of the present invention additionally provides a kind of frequency scrambling code optimum system.Fig. 3 is the present invention
The structure diagram of frequency scrambling code optimum system in embodiment, as shown in figure 3, the frequency scrambling code optimum system, suitable for TD-
SCDMA systems, including generation module 31 and optimization module 32.Optimization module further comprises initialization unit, assessment unit, choosing
It selects unit, mating unit, become anticoincidence unit, adjustment unit, output unit and judging unit.
Wherein, generation module generation cell-level interference matrix generates corresponding inter-cell frequency scrambler according to adjacent area situation
The interference matrix with inter-cell frequency scrambler rule is merged, generates the interference matrix with restrictive condition by rule；
Optimization module optimizes frequency scrambler using genetic algorithm.
Initialization unit in optimization module initializes genetic algorithm；Assessment unit assesses population's fitness；Choosing
It selects unit and carries out selection operation, determine to carry out the individual of mating operation in population；Mating unit carries out mating operation, generates new
Individual；Become anticoincidence unit preset a probability, when mutation probability be more than predetermined probabilities, individual replicate portion is added in population,
As the selectable individual of population；The individual of post-coitum is adjusted by adjustment unit, will not meet setting in optimization cell
The frequency point and scrambler of allocation rule propose, and recalculate legal frequency point and scrambler；Output unit generates frequency scrambler
Prioritization scheme；Judging unit judges whether to meet end condition.
Technical scheme of the present invention forms one by way of curing rule and establishing interference matrix and does not depend on manufacturer
Then generalized programming model requires to automatically generate corresponding programme according to user, it is achieved thereby that supporting all TD-
SCDMA producers MR parsings import, the function of generation interference matrix, can carry out already existing TD-SCDMA nets in all existing nets
The frequency dividing of network divides scrambling code planning to work；The interference very close to state of the current network is completed in a manner that data and adjacent area combine
Matrix lays a solid foundation for automation operation；It is excellent that frequency scrambler can rapidly be provided by the inventive technique scheme
Change scheme is greatly improved frequency scrambling code optimum planning efficiency, reduces cost.
It should be noted that：Above example be only to illustrate the present invention and it is unrestricted, the present invention is also not limited to above-mentioned
Citing, all do not depart from the technical solution of the spirit and scope of the present invention and its improvement, should all cover the right in the present invention
In claimed range.
Claims (12)
1. a kind of frequency scrambling code optimizing method, suitable for TD-SCDMA system, which is characterized in that include the following steps：
Generate cell-level interference matrix；
Corresponding inter-cell frequency scrambler rule is generated according to adjacent area situation；
The interference matrix with inter-cell frequency scrambler rule is merged, generates the interference matrix with restrictive condition；
Frequency scrambler is optimized using genetic algorithm；
It is described that frequency scrambler is optimized using genetic algorithm, further comprise the steps：
Genetic algorithm is initialized；
Assess population's fitness；
Selection operation is carried out, determines to carry out the individual of mating operation in population；
Mating operation is carried out, generates new individual；
The individual of post-coitum is adjusted, the frequency point for optimizing the allocation rule that setting is not met in cell and scrambler are rejected,
And recalculate legal frequency point and scrambler；
Preset a probability, when mutation probability be more than predetermined probabilities, individual replicate portion is added in population, can as population
The individual of selection；
Generate frequency scrambling code optimum scheme；
It is described that genetic algorithm is initialized, further comprise the steps：
Individual binary coding is generated according to i*j, wherein i is cell number, and j is total frequency point demand number or scrambler total number；
Frequency point allocation is carried out using random fashion, algorithm initialization is realized, wherein the frequency point distributed meets the frequency point of single subdistrict
Demand, and frequency point and scrambler distribution meet the inter-cell frequency scrambler rule of setting；
According to the population number defined in systematic parameter, the population of preset quantity is generated；
Frequency point and scrambler individual in population are initialized.
2. a kind of frequency scrambling code optimizing method according to claim 1, which is characterized in that cell-level interference matrix is specified
The matrix that serving cell is formed by the probability numbers of the interference of neighbouring each cell, in the wireless network for having N number of cell, cell is used
C represents that interference matrix is：
A kind of 3. frequency scrambling code optimizing method according to claim 1, which is characterized in that the inter-cell frequency scrambler rule
Then include：
Main adjacent cell cannot be with the same downlink frequency pilot code of frequency, and any two adjacent area of a cell cannot be the same as the same downlink frequency pilot code of frequency；
Cannot be with scrambler group with station, main adjacent cell cannot be with frequency with scrambler group；
Main adjacent cell cannot same scrambler, any two adjacent area of a cell cannot same scrambler；
It outdoor cell cannot be with the same scrambler of frequency in 2 kilometers with outdoor cell；
Outdoor cell and outdoor cell or outdoor cell and indoor cell in 1.5 kilometers cannot with the same downlink frequency pilot code of frequency,
Room point cell divides cell cannot be with the same downlink frequency pilot code of frequency in 800 meters with room；
And/or when adjacent area number is not more than 31, main adjacent cell cannot same downlink frequency pilot code.
4. a kind of frequency scrambling code optimizing method according to claim 1, which is characterized in that the generation is with restrictive condition
Interference matrix further comprises the steps：
Interference matrix is each worth and is multiplied by COEFFICIENT K, wherein the COEFFICIENT K for not meeting inter-cell frequency scrambler rule is 1, and is met
The COEFFICIENT K of inter-cell frequency scrambler rule is infinity.
5. a kind of frequency scrambling code optimizing method according to claim 1, which is characterized in that the frequency point initialization is further
Include the following steps：
The frequency point that the cell has occupied is removed, removal does not meet the frequency point of setting inter-cell frequency scrambler rule；
By remaining available frequency point, the interference value of each frequency point is calculated according to the area interference matrix, interference value is minimum
Frequency point allocation gives the cell, if the frequency point of interference value minimum is no less than 2, distributes access times minimum frequency point, no
Then it is randomly assigned the frequency point of an interference value minimum；
It repeats the above steps, until all optimization cell initials finish.
6. a kind of frequency scrambling code optimizing method according to claim 1, which is characterized in that the scrambler initialization is further
Include the following steps：
Removal does not meet the scrambler of inter-cell frequency scrambler rule；
By remaining available scrambler, the interference value of each scrambler is calculated according to the area interference matrix, interference value is minimum
Scrambler distributes to the cell, if the scrambler of interference value minimum is no less than 2, distributes access times minimum scrambler, no
Then it is randomly assigned the scrambler of an interference value minimum；
It repeats the above steps, until all optimization cell initials finish.
7. a kind of frequency scrambling code optimizing method according to claim 1, which is characterized in that it is described assessment population's fitness into
One step includes the following steps：
According to the definition of population's fitness=1/ (the total interference value+1 of population), the fitness of single individual in population is calculated, is summarized
Generate the population's fitness of each population；
The label wherein best individual of fitness, the individual for making the fitness best enters selection operation, if last iteration
The fitness of middle optimum individual is better than the worst individual adaptation degree that this is generated, then using the optimum individual of last iteration, replaces
Worst individual in this.
8. a kind of frequency scrambling code optimizing method according to claim 1, which is characterized in that the selection operation that carries out is into one
Step includes the following steps：
According to fitness, fitness ratio of each individual in population is calculated：
The adaptation rate DumpFitness=1/ Population adaptation angle value of individual；
Population association adaptation rate RelaFitness=Population adaptations rate/population；
It is sorted according to population, the association adaptation rate of the individual of each cumulative front of individual, the cumulative adaptation rate as current population；
Two populations are taken at random, take the mode of roulette, determine that a population carries out heredity, until meeting the population set
The population of quantity.
9. a kind of frequency scrambling code optimizing method according to claim 1, which is characterized in that it is described carry out mating operate into one
Step includes the following steps：
Two random numbers C1 and C2 are generated in (0, i*j)；
When C1 and C2 is in same a line, then the row data are exchanged, if C1 and C2 are expert to C1 not in same a line C1 and open
Begin to row end and C2 places every trade head to swap to C2 positions, while intersect the row among two rows.
10. a kind of frequency scrambling code optimizing method according to claim 1, which is characterized in that the generation frequency scrambler is excellent
Change scheme further comprises the steps：
According to the fitness value of the population generated in stock assessment, when in the population of generation, exist meet end condition when, system
Termination analysis flow, and export current optimal solution, the optimal solution of the output be optimize cell frequency point and scrambler it is excellent
Change scheme.
11. a kind of frequency scrambling code optimizing method according to claim 10, which is characterized in that the end condition is to adapt to
Degree reaches 0 or meets the iterations specified.
12. a kind of frequency scrambling code optimum system, suitable for TD-SCDMA system, which is characterized in that including generation module and optimization
Module, wherein,
Generation module generates corresponding inter-cell frequency scrambler rule for generating cell-level interference matrix, according to adjacent area situation,
The interference matrix with inter-cell frequency scrambler rule is merged, generates the interference matrix with restrictive condition；
Optimization module is used to optimize frequency scrambler using genetic algorithm；
The optimization module further comprises initialization unit, assessment unit, selecting unit, mating unit, becomes anticoincidence unit, adjustment
Unit, output unit and judging unit, wherein,
Initialization unit is used to initialize genetic algorithm；
Assessment unit is used to assess population's fitness；
Selecting unit determines to carry out the individual of mating operation in population for carrying out selection operation；
Mating unit generates new individual for carrying out mating operation；
Become anticoincidence unit for presetting a probability, when mutation probability is more than predetermined probabilities, individual replicate portion is added to population
In, as the selectable individual of population；
Adjustment unit will optimize the frequency point for the allocation rule that setting is not met in cell for the individual of post-coitum to be adjusted
It is proposed with scrambler, and recalculates legal frequency point and scrambler；
Output unit is used to generate frequency scrambling code optimum scheme；
Judging unit is used to judge whether to meet end condition；
Wherein, it is described that genetic algorithm is initialized, further comprise the steps：
Individual binary coding is generated according to i*j, wherein i is cell number, and j is total frequency point demand number or scrambler total number；
Frequency point allocation is carried out using random fashion, algorithm initialization is realized, wherein the frequency point distributed meets the frequency point of single subdistrict
Demand, and frequency point and scrambler distribution meet the inter-cell frequency scrambler rule of setting；
According to the population number defined in systematic parameter, the population of preset quantity is generated；
Frequency point and scrambler individual in population are initialized.
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| CN102752812A (en) * | 2011-04-21 | 2012-10-24 | 中国移动通信集团广东有限公司 | Method and device for distributing frequency scrambles |
| CN102892133A (en) * | 2012-07-20 | 2013-01-23 | 华中科技大学 | Method for optimizing master frequencies and scrambling codes of time division-code division multiple access (TD-CDMA) network base station based on genetic algorithm |
| CN103179607A (en) * | 2011-12-26 | 2013-06-26 | 中国移动通信集团广东有限公司 | Method and device for optimizing configuration of network frequency scrambling codes |
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| CN101047937A (en) * | 2006-03-27 | 2007-10-03 | 浙江移动通信有限责任公司 | Mobile communication frequency planning method based on genetic algorithm |
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