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CN115589605A - Communication equipment debugging method based on tribal formation mechanism - Google Patents

Communication equipment debugging method based on tribal formation mechanismDownload PDF

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Publication number
CN115589605A
CN115589605ACN202211577031.4ACN202211577031ACN115589605ACN 115589605 ACN115589605 ACN 115589605ACN 202211577031 ACN202211577031 ACN 202211577031ACN 115589605 ACN115589605 ACN 115589605A
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individuals
clan
formula
tribal
individual
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CN115589605B (en
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戚建淮
刁润
周杰
宋晶
张莉
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Shenzhen Y&D Electronics Information Co Ltd
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Shenzhen Y&D Electronics Information Co Ltd
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Abstract

The invention relates to the technical field of communication equipment debugging, and particularly provides a communication equipment debugging method based on a tribal formation mechanism, which comprises the following steps: setting a target function based on the adjusting result and the adjusting parameter of the communication equipment; randomly putting N individuals in the feasible region of the decision variable, and allowing the individuals to randomly walk in the feasible region to generate population distribution meeting the conditions; clustering the individuals to form tribes, and eliminating tribes which do not meet requirements; selecting a clan center for the rest clans, traversing all independent individuals in the clans, and merging the individuals into the clan to which the clan center closest to the individual belongs; establishing a tribal center attraction mechanism, setting a tribal evolution condition, evolving tribals until the evolution times are reached, and taking the tribal centers of the evolved tribals as values of decision variables of local optimization; the method supplements multimodal optimization of a plurality of local optimal values, and can better meet the increasing optimization requirement of the Internet of things compared with the traditional optimization algorithm.

Description

Communication equipment debugging method based on tribal formation mechanism
Technical Field
The invention relates to the technical field of communication equipment debugging, in particular to a communication equipment debugging method based on a tribe formation mechanism.
Background
In the train-ground communication transmission process, because the data volume on a high-speed railway motor train unit is very large, the running speed of the motor train unit is very high, and the requirement on safety is also very high, 5G millimeter wave base stations erected on a train and on two sides of a track need to be debugged so as to achieve the average transmission rate of 8Gbps and the transmission delay within 1 millisecond, the transmission delay and the actual temperature, power and electricity consumption of millimeter wave equipment during operation are considered, more appropriate equipment configuration parameters need to be selected to debug millimeter wave equipment so as to meet the requirements of high-reliability train-ground data transmission and low-power operation of the millimeter wave equipment, and when the equipment is debugged, the antenna angle, the working mode, the output power, the working frequency band, the modulation mode, the working temperature, the frequency width, the path loss value and the antenna system need to be set.
At present, in a traditional equipment adjustment optimization algorithm, an optimization target is to find a global optimal point and avoid convergence of the algorithm on a suboptimal solution as much as possible, but in a vehicle-ground communication process, only the global optimal algorithm is found, and the requirement can not be met gradually, and in the vehicle-ground communication process, due to the continuous change of the position of a vehicle, the optimal solution obtained through the algorithm can not meet the communication requirement sometimes. Therefore, the present application provides a communication device debugging method based on a clan forming mechanism.
Disclosure of Invention
The invention aims to provide a communication equipment debugging method based on a tribe formation mechanism, which aims to solve the problem that the traditional optimization algorithm does not meet the vehicle-ground communication requirement.
In order to achieve the purpose, the invention provides the following technical scheme:
a communication equipment debugging method based on a clan forming mechanism comprises the following steps:
definition ofTransmission rate of communication equipment
Figure 937482DEST_PATH_IMAGE001
Adjusting parameters of the communication equipment to target variables
Figure 623678DEST_PATH_IMAGE002
，（
Figure 768351DEST_PATH_IMAGE003
) Setting an objective function for a decision variable
Figure 881801DEST_PATH_IMAGE004
Setting the value range of the decision variable based on the actual parameters of the communication equipment;
randomly putting N individuals in the feasible region of the decision variable, and allowing the individuals to randomly walk in the feasible region according to preset conditions to generate population distribution meeting the conditions;
clustering the individuals with the aggregation effect to form clans, eliminating clans which do not meet the requirements, and forming independent individuals in the eliminated clans; selecting a clan center for the rest clans, traversing all independent individuals in the clans, calculating the distance between each individual and each clan center, merging the individuals into the clan to which the clan center closest to the individual belongs to form a new clan, and reselecting the clan center for the new clan;
establishing a tribal center attraction mechanism, setting a tribal evolution condition, evolving tribals until the evolution times are reached, and taking the tribal centers of the evolved tribals as the values of decision variables of local optimization.
Further, the adjusting parameter is an antenna angle
Figure 807032DEST_PATH_IMAGE005
Working mode
Figure 969023DEST_PATH_IMAGE006
Output power of
Figure 296099DEST_PATH_IMAGE007
Work, workFrequency band
Figure 314870DEST_PATH_IMAGE008
Modulation system
Figure 665080DEST_PATH_IMAGE009
Operating temperature of
Figure 693079DEST_PATH_IMAGE010
Bandwidth of the frequency
Figure 874662DEST_PATH_IMAGE011
Path loss value
Figure 766132DEST_PATH_IMAGE012
Antenna system
Figure 400376DEST_PATH_IMAGE013
If the adjustment result and the adjustment parameter satisfy the function relationship:
Figure 966486DEST_PATH_IMAGE014
equation (1)
Wherein,
Figure 205838DEST_PATH_IMAGE015
in order to be able to communicate with the mobile station,
Figure 831991DEST_PATH_IMAGE016
is a communication delay;
Figure 891214DEST_PATH_IMAGE017
and
Figure 261016DEST_PATH_IMAGE018
in order to be able to set the parameters,
Figure 417190DEST_PATH_IMAGE019
formula (1) is taken as the objective function.
Preferably, the individual wanders based on equation (2):
Figure 151928DEST_PATH_IMAGE020
(ii) a Formula (2)
Wherein,
Figure 760764DEST_PATH_IMAGE021
the step length of the wandering is set in the feasible region according to the decision variable;
Figure 104896DEST_PATH_IMAGE022
is as follows
Figure 115577DEST_PATH_IMAGE023
In individual the first
Figure 83533DEST_PATH_IMAGE024
The step size of the walk of the decision variable,
Figure 117348DEST_PATH_IMAGE025
；
the individuals after the wandering are recorded as
Figure 828952DEST_PATH_IMAGE026
Then, then
Figure 694140DEST_PATH_IMAGE027
，
Figure 770680DEST_PATH_IMAGE028
Comparison of
Figure 354108DEST_PATH_IMAGE029
And
Figure 869403DEST_PATH_IMAGE030
size of (1), if
Figure 589098DEST_PATH_IMAGE031
In addition, another
Figure 836539DEST_PATH_IMAGE032
If, if
Figure 907264DEST_PATH_IMAGE033
Hold, hold
Figure 396888DEST_PATH_IMAGE034
The temperature of the molten steel is not changed,
Figure 236669DEST_PATH_IMAGE035
each decision variable in (c) is obtained based on equation (3):
Figure 717328DEST_PATH_IMAGE036
(ii) a Formula (3)
Wherein,
Figure 213032DEST_PATH_IMAGE037
is the first before wandering
Figure 804550DEST_PATH_IMAGE038
In individual the first
Figure 436520DEST_PATH_IMAGE039
The number of the decision-making variables is determined,
Figure 353660DEST_PATH_IMAGE040
for the first time after wandering
Figure 133397DEST_PATH_IMAGE038
In individual the first
Figure 466290DEST_PATH_IMAGE039
A decision variable;
Figure 280662DEST_PATH_IMAGE041
obtaining based on formula (4):
Figure 545202DEST_PATH_IMAGE042
；formula (4);
wherein,
Figure 812235DEST_PATH_IMAGE043
as decision variables
Figure 11136DEST_PATH_IMAGE044
The value range of (a).
Preferably, the method of generating a population distribution satisfying the condition comprises the steps of:
recording the population after the individuals are thrown as an initial population, and acquiring the initial population density based on a formula (5)
Figure 680014DEST_PATH_IMAGE045
：
Figure 611061DEST_PATH_IMAGE046
(ii) a Formula (5)
Wherein N is the number of delivered individuals;
after the individual has completed a walk, a new population is obtained, based on
Figure 365391DEST_PATH_IMAGE043
Setting individuals
Figure 102402DEST_PATH_IMAGE044
Neighborhood of (2)
Figure 563471DEST_PATH_IMAGE047
Counting the number of individuals in the neighborhood
Figure 993315DEST_PATH_IMAGE048
Defining individuals based on equation (6)
Figure 234941DEST_PATH_IMAGE049
Density of (2)
Figure 447747DEST_PATH_IMAGE050
：
Figure 91218DEST_PATH_IMAGE051
(ii) a Formula (6)
Figure 426385DEST_PATH_IMAGE052
Is an individual
Figure 591524DEST_PATH_IMAGE053
The number of individuals in the neighborhood of (c);
the individual repeatedly swims in the feasible region until reaching the set repetition times or the obtained population exists
Figure 670339DEST_PATH_IMAGE054
Wherein
Figure 168316DEST_PATH_IMAGE055
And obtaining the population distribution meeting the conditions, and recording as a first population.
Preferably, the specific method for clustering the communities comprises the following steps:
allowing individuals with aggregation effects to form tribes
Figure 877646DEST_PATH_IMAGE056
Wherein
Figure 828285DEST_PATH_IMAGE057
the number of the clans after density clustering;
counting the number of individuals in all tribes
Figure 710790DEST_PATH_IMAGE058
Calculating the tribal density based on equation (7):
Figure 957DEST_PATH_IMAGE059
equation (7)
Wherein,
Figure 943505DEST_PATH_IMAGE060
is as follows
Figure 381440DEST_PATH_IMAGE061
The density of the tribes of each tribe,
Figure 739740DEST_PATH_IMAGE053
is as follows
Figure 212310DEST_PATH_IMAGE038
(ii) individuals;
after calculating the tribal density, if
Figure 325759DEST_PATH_IMAGE062
Or
Figure 687208DEST_PATH_IMAGE063
Then eliminate tribe
Figure 911516DEST_PATH_IMAGE064
Taking the individuals in the eliminated tribe as independent individuals, and forming a set by all the independent individuals
Figure 973013DEST_PATH_IMAGE065
The number of the remaining radicals is recorded as
Figure 195047DEST_PATH_IMAGE066
Wherein
Figure 607574DEST_PATH_IMAGE067
is a pre-set parameter of the process,
Figure 635573DEST_PATH_IMAGE068
。
preferably, the first and second liquid crystal materials are,
Figure 754838DEST_PATH_IMAGE069
。
preferably, the tribal center is selected based on equation (8):
Figure 944511DEST_PATH_IMAGE070
(ii) a Formula (8)
Wherein,
Figure 844334DEST_PATH_IMAGE071
is as follows
Figure 348128DEST_PATH_IMAGE072
The tribe center of each tribe.
Preferably, for individuals
Figure 649796DEST_PATH_IMAGE073
，
Figure 446589DEST_PATH_IMAGE074
Establishing a tribal center attraction mechanism based on formula (9):
Figure 833708DEST_PATH_IMAGE075
(ii) a Formula (9)
Wherein,
Figure 203509DEST_PATH_IMAGE076
are all preset parameters;
all individuals
Figure 31788DEST_PATH_IMAGE077
The walk of (2) is realized based on the formula (10):
Figure 828843DEST_PATH_IMAGE078
(ii) a Formula (10)
Wherein,
Figure 437678DEST_PATH_IMAGE079
。
preferably, the clan evolution conditions are as follows:
setting individuals
Figure 611171DEST_PATH_IMAGE080
Probability of existence of outliers
Figure 559535DEST_PATH_IMAGE081
To, for
Figure 527491DEST_PATH_IMAGE082
，
Figure 623623DEST_PATH_IMAGE083
Randomly generating a random number of 0 to 1
Figure 272910DEST_PATH_IMAGE084
;
If it is
Figure 138098DEST_PATH_IMAGE085
Let us order
Figure 276955DEST_PATH_IMAGE086
Comparison of
Figure 314180DEST_PATH_IMAGE087
And
Figure 563896DEST_PATH_IMAGE088
size of (1), if
Figure 549169DEST_PATH_IMAGE089
Then another
Figure 796611DEST_PATH_IMAGE090
If, if
Figure 805018DEST_PATH_IMAGE091
Hold, hold
Figure 858425DEST_PATH_IMAGE092
The change is not changed;
if it is
Figure 698205DEST_PATH_IMAGE093
Let us order
Figure 116548DEST_PATH_IMAGE094
Comparison of
Figure 408989DEST_PATH_IMAGE087
And
Figure 266087DEST_PATH_IMAGE088
size of (1), if
Figure 396591DEST_PATH_IMAGE089
In addition, another
Figure 48153DEST_PATH_IMAGE090
If, if
Figure 93469DEST_PATH_IMAGE091
Hold, hold
Figure 426361DEST_PATH_IMAGE092
Unchanged, find updated leave
Figure 975154DEST_PATH_IMAGE092
The nearest clan center, and incorporate it into that clan, where,
Figure 879DEST_PATH_IMAGE095
is a preset parameter.
In conclusion, compared with the prior art, the invention has the following beneficial effects:
the communication equipment debugging method based on the tribe formation mechanism disclosed by the embodiment of the invention has the advantages that the tribe formation mechanism is introduced, the optimization algorithm is popularized to the multi-extreme value solution of the multi-peak optimization algorithm, and on the basis of meeting the global optimization solution, a plurality of local optimal values of the multi-peak optimization algorithm are supplemented, so that the method can better meet the increasing optimization requirements of the Internet of things than the traditional optimization algorithm, and is more suitable for the configuration requirements of equipment in the vehicle bottom communication process.
Drawings
Fig. 1 is a flowchart of a communication device debugging method based on a clan forming mechanism according to an embodiment of the present invention.
Fig. 2 is a flowchart of one subroutine in the communication device debugging method based on the clan forming mechanism disclosed in the embodiment of the present invention.
Fig. 3 is a flowchart of another subprogram in the communication device debugging method based on the clan forming mechanism disclosed in the embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments, and all other embodiments obtained by a person of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the protection scope of the present invention.
Example 1
As shown in fig. 1, an embodiment of the present invention provides a communication device debugging method based on a clan forming mechanism, where the algorithm includes the following steps:
step S100, defining the adjustment result of the communication equipment
Figure 205596DEST_PATH_IMAGE001
Adjusting parameters of the communication equipment to target variables
Figure 404496DEST_PATH_IMAGE002
，
Figure 807795DEST_PATH_IMAGE003
Setting an objective function for a decision variable
Figure 502957DEST_PATH_IMAGE096
Setting the value range of the decision variable based on the actual parameters of the communication equipment;
specifically, in this embodiment, the adjustment parameter of the communication device is the antenna angle
Figure 257286DEST_PATH_IMAGE005
Working mode
Figure 931981DEST_PATH_IMAGE006
Output power of
Figure 455366DEST_PATH_IMAGE007
WorkerFrequency band of operation
Figure 885210DEST_PATH_IMAGE008
And modulation method
Figure 798940DEST_PATH_IMAGE009
Operating temperature of
Figure 339643DEST_PATH_IMAGE010
Frequency bandwidth of
Figure 920797DEST_PATH_IMAGE011
Path loss value
Figure 255963DEST_PATH_IMAGE012
Antenna system
Figure 984885DEST_PATH_IMAGE013
Wherein, the relation between the adjusting result and the adjusting parameter is shown as formula (1):
Figure 63699DEST_PATH_IMAGE097
equation (1)
Wherein,
Figure 997895DEST_PATH_IMAGE015
in order to be able to communicate with the mobile station,
Figure 503962DEST_PATH_IMAGE016
is a communication delay;
Figure 657863DEST_PATH_IMAGE017
and
Figure 540369DEST_PATH_IMAGE018
in order to be able to set the parameters,
Figure 892852DEST_PATH_IMAGE019
；
wherein,
Figure 773084DEST_PATH_IMAGE098
；
Figure 457356DEST_PATH_IMAGE017
and
Figure 877973DEST_PATH_IMAGE099
the value-taking principle is as follows:
Figure 288226DEST_PATH_IMAGE100
when the transmission rate is targeted, the transmission rate,
Figure 136096DEST_PATH_IMAGE101
when only the transmission delay is targeted,
Figure 61327DEST_PATH_IMAGE102
when the transmission rate is to be ensured at the same time
Figure 285635DEST_PATH_IMAGE103
A transmission delay of
Figure 48929DEST_PATH_IMAGE104
And when the two have no obvious priority,
Figure 333280DEST_PATH_IMAGE105
when the transmission rate is V and the transmission delay is D and the priority exists between the transmission rate and the transmission delay, the parameter corresponding to the target with higher priority can be set to be a higher value;
in the present embodiment, formula (1) is taken as a target parameter.
S200, randomly throwing N individuals in the feasible region of the decision variable, and allowing the individuals to randomly walk in the feasible region according to preset conditions to generate population distribution meeting the conditions;
in particular, decision variables
Figure 745807DEST_PATH_IMAGE106
Value range ofDepending on the range of parameters of the communication device that need to be adjusted,
Figure 445910DEST_PATH_IMAGE044
is operable as
Figure 627492DEST_PATH_IMAGE107
(here, a cartesian product is represented), wherein,
Figure 82744DEST_PATH_IMAGE043
as decision variables
Figure 920250DEST_PATH_IMAGE044
The value range of (a) is, as in the present embodiment,
Figure 486361DEST_PATH_IMAGE044
is operable as
Figure 522450DEST_PATH_IMAGE108
；
In decision variables
Figure 86287DEST_PATH_IMAGE106
Randomly putting N individuals in the feasible domain, and marking as
Figure 473406DEST_PATH_IMAGE109
，
Figure 13846DEST_PATH_IMAGE110
；
Illustratively, in this embodiment, the individuals delivered are
Figure 170021DEST_PATH_IMAGE111
，
Figure 967076DEST_PATH_IMAGE110
；
As a preferred implementation in this embodiment, the individual wandering is based on equation (2):
Figure 513595DEST_PATH_IMAGE112
(ii) a Formula (2)
Wherein,
Figure 687087DEST_PATH_IMAGE113
the step length of the wandering is set in the feasible region according to the decision variable;
Figure 635451DEST_PATH_IMAGE114
is as follows
Figure 603408DEST_PATH_IMAGE115
In individual the first
Figure 699539DEST_PATH_IMAGE116
The step size of the walk of the decision variable,
Figure 83247DEST_PATH_IMAGE025
；
the individuals after the wandering are recorded as
Figure 214014DEST_PATH_IMAGE026
Then, then
Figure 789090DEST_PATH_IMAGE027
，
Figure 372518DEST_PATH_IMAGE028
Comparison of
Figure 622234DEST_PATH_IMAGE029
And
Figure 545191DEST_PATH_IMAGE030
size of (1), if
Figure 854949DEST_PATH_IMAGE031
In addition, another
Figure 925673DEST_PATH_IMAGE032
If, if
Figure 916763DEST_PATH_IMAGE033
Hold, hold
Figure 756543DEST_PATH_IMAGE034
The temperature of the molten steel is not changed,
Figure 174886DEST_PATH_IMAGE035
each decision variable in (c) is obtained based on equation (3):
Figure 467327DEST_PATH_IMAGE036
(ii) a Formula (3)
Wherein,
Figure 324425DEST_PATH_IMAGE037
is the first before wandering
Figure 460789DEST_PATH_IMAGE038
In individual the first
Figure 112350DEST_PATH_IMAGE039
The number of the decision-making variables is determined,
Figure 157667DEST_PATH_IMAGE040
for the first time after wandering
Figure 490559DEST_PATH_IMAGE038
In individual first
Figure 39352DEST_PATH_IMAGE039
A decision variable;
Figure 127394DEST_PATH_IMAGE041
obtaining based on formula (4):
Figure 332110DEST_PATH_IMAGE042
；formula (4)
Wherein the walk step length of decision variables in different individuals is oneSo that;
Figure 265431DEST_PATH_IMAGE043
as decision variables
Figure 934310DEST_PATH_IMAGE044
The value range of (a);
it should be noted that in this embodiment, the individual may also have other ways, such as a difference algorithm, a leian flight algorithm, etc.;
as an implementation manner in this embodiment, the method for generating a population distribution that satisfies the condition includes the following steps:
step S210, recording the population after the individuals are thrown as an initial population, and acquiring the density of the initial population based on a formula (5)
Figure 130936DEST_PATH_IMAGE045
：
Figure 619686DEST_PATH_IMAGE046
(ii) a Formula (5)
Wherein N is the number of released individuals;
step S220, after the individual finishes one-time wandering, a new population is obtained, according to the method
Figure 622277DEST_PATH_IMAGE043
Setting individuals
Figure 145662DEST_PATH_IMAGE044
Neighborhood of (2)
Figure 746146DEST_PATH_IMAGE047
Counting the number of individuals in the neighborhood
Figure 987771DEST_PATH_IMAGE048
Defining individuals based on equation (6)
Figure 528474DEST_PATH_IMAGE049
Density of (2)
Figure 844049DEST_PATH_IMAGE050
：
Figure 444794DEST_PATH_IMAGE051
(ii) a Formula (6)
Figure 908137DEST_PATH_IMAGE052
Is an individual
Figure 190213DEST_PATH_IMAGE053
The number of individuals in the neighborhood of (a),
Figure 688191DEST_PATH_IMAGE117
is an individual
Figure 194259DEST_PATH_IMAGE118
Neighborhood of (2)
Figure 348159DEST_PATH_IMAGE119
In the first place
Figure 230665DEST_PATH_IMAGE039
The value range of each decision variable;
step S230, the individual repeatedly swims in the feasible region until the set repeated times are reached or the obtained population exists
Figure 583149DEST_PATH_IMAGE054
Wherein
Figure 696336DEST_PATH_IMAGE055
Obtaining population distribution meeting the conditions, and marking as a first population;
specifically, the individual is allowed to repeatedly walk in the manner of step S220 until the number of walks is reached, for example, 50 times, or the population obtained after several walks exists
Figure 134270DEST_PATH_IMAGE120
Then stop the wandering and go for the last timeAnd marking the obtained population by wandering as a first population.
S300, clustering the individuals with the aggregation effect to form clans, eliminating clans which do not meet requirements, and forming independent individuals in the eliminated clans; selecting clan centers for the rest clans, traversing all independent individuals in the clans, calculating the distance between the individual and each clan center, merging the individual into the clan to which the clan center closest to the individual belongs to form a new clan, and reselecting the clan center for the new clan;
specifically, when an individual walks, the individual can walk to the position with the optimal target function, if the target function is not customized, the individual can have an aggregation phenomenon after walking in a certain step number, and a tribe is formed by a density clustering method;
in this embodiment, a specific method for clustering the communities includes the following steps:
step S310, let the individuals with aggregation effect form the tribe
Figure 820467DEST_PATH_IMAGE056
Wherein, in the process,
Figure 965140DEST_PATH_IMAGE057
the number of the clans after density clustering;
step S320, counting the number of individuals of all the tribes
Figure 78590DEST_PATH_IMAGE058
Calculating the tribal density based on equation (7):
Figure 3820DEST_PATH_IMAGE059
equation (7)
Wherein,
Figure 165812DEST_PATH_IMAGE060
is as follows
Figure 492888DEST_PATH_IMAGE061
The density of the tribes of each tribe,
Figure 777238DEST_PATH_IMAGE053
is as follows
Figure 924186DEST_PATH_IMAGE038
(ii) individuals;
after step S320, calculating the density of the tribe, if
Figure 889868DEST_PATH_IMAGE062
Or
Figure 71451DEST_PATH_IMAGE063
Then eliminate tribe
Figure 526703DEST_PATH_IMAGE064
Taking the individuals in the eliminated tribe as independent individuals, and forming a set by all the independent individuals
Figure 862744DEST_PATH_IMAGE065
The remaining number of radicals is recorded as
Figure 428854DEST_PATH_IMAGE066
Wherein
Figure 464944DEST_PATH_IMAGE067
is a pre-set parameter of the process,
Figure 28780DEST_PATH_IMAGE068
；
as a preferred embodiment in this embodiment,
Figure 150320DEST_PATH_IMAGE069
；
after the elimination department, selecting a clan center for the remaining clans based on formula (8):
Figure 520121DEST_PATH_IMAGE121
(ii) a Formula (8)
Wherein,
Figure 613979DEST_PATH_IMAGE071
is as follows
Figure 411034DEST_PATH_IMAGE072
A tribe center for each tribe;
after selecting the clan center, traversing all the independent individuals in the set S, and calculating the independent individuals and each clan center
Figure 19870DEST_PATH_IMAGE071
Into the tribe to which the tribe center closest thereto belongs, e.g. independent of the individual
Figure 865466DEST_PATH_IMAGE122
Distance and tribal center of
Figure 876147DEST_PATH_IMAGE123
More recently, the individuals are
Figure 844103DEST_PATH_IMAGE122
Merge into tribe center
Figure 394032DEST_PATH_IMAGE123
The tribe in which it is located;
and after all the independent individuals in the set S are merged into the clan, reselecting the center of the clan for the formed new clan according to a formula (8).
S400, establishing a tribal center attraction mechanism, setting a tribal evolution condition, evolving the tribal until the evolution times are reached, and taking the tribal center of the evolved tribal as a value of a decision variable for local optimization;
in particular, for individuals
Figure 105636DEST_PATH_IMAGE073
，
Figure 236403DEST_PATH_IMAGE074
Establishing a tribal center attraction mechanism based on formula (9):
Figure 312943DEST_PATH_IMAGE075
(ii) a Formula (9)
Wherein,
Figure 630792DEST_PATH_IMAGE076
are all preset parameters;
all individuals
Figure 146087DEST_PATH_IMAGE080
The walk of (2) is realized based on the formula (10):
Figure 131361DEST_PATH_IMAGE078
(ii) a Formula (10)
Wherein,
Figure 378802DEST_PATH_IMAGE124
；
in this embodiment, the individual's wandering between clans follows equation (10);
wherein,
Figure 183947DEST_PATH_IMAGE125
；
as a preferred real-time method in this embodiment, the clan evolution conditions are as follows:
setting individuals
Figure 237354DEST_PATH_IMAGE126
Probability of existence of outliers
Figure 14817DEST_PATH_IMAGE081
I.e. individuals
Figure 495477DEST_PATH_IMAGE126
In the evolution process, there is
Figure 53497DEST_PATH_IMAGE081
The probability is wandered, to
Figure 81234DEST_PATH_IMAGE082
，
Figure 41100DEST_PATH_IMAGE083
Randomly generating a random number of 0 to 1
Figure 692661DEST_PATH_IMAGE084
;
If it is
Figure 410081DEST_PATH_IMAGE085
Let us order
Figure 805290DEST_PATH_IMAGE086
Comparison of
Figure 619663DEST_PATH_IMAGE087
And
Figure 379808DEST_PATH_IMAGE088
in the size of (1)
Figure 646842DEST_PATH_IMAGE089
Then another
Figure 845742DEST_PATH_IMAGE090
If, if
Figure 452304DEST_PATH_IMAGE091
Hold, hold
Figure 445667DEST_PATH_IMAGE092
The change is not changed;
if it is
Figure 199997DEST_PATH_IMAGE093
Let us order
Figure 638806DEST_PATH_IMAGE094
Comparison of
Figure 162191DEST_PATH_IMAGE087
And
Figure 326456DEST_PATH_IMAGE088
size of (1), if
Figure 505765DEST_PATH_IMAGE089
In addition, another
Figure 46468DEST_PATH_IMAGE090
If, if
Figure 424360DEST_PATH_IMAGE091
Hold, hold
Figure 962788DEST_PATH_IMAGE092
Not changed, at this point, find updated back
Figure 426131DEST_PATH_IMAGE092
The nearest clan center is merged into the clan, at this time, a new clan is formed, and the clan center is selected for the formed new clan according to formula (8), which is denoted as an evolution,
Figure 770524DEST_PATH_IMAGE095
is a preset parameter;
in this embodiment, during tribe evolution, once evolution is performed based on tribe evolution conditions to form a new tribe, then the new tribe is evolved again until the number of evolution times Q preset in tribe evolution is reached to form a final tribe, and tribe centers are selected for the final M tribes according to formula (8)
Figure 940606DEST_PATH_IMAGE127
Then with the tribe center of the final tribe
Figure 712252DEST_PATH_IMAGE127
The value of which is used as M local optimization decision variables, i.e.
Figure 662891DEST_PATH_IMAGE127
The values in (c) are used as tuning parameters for the communication device,
Figure 981615DEST_PATH_IMAGE128
a local optimum value;
selecting a global optimal decision variable based on formula (11):
Figure 334099DEST_PATH_IMAGE129
(ii) a Formula (11)
Figure 276647DEST_PATH_IMAGE130
The global optimal value is the optimal adjustment effect which can be achieved by the communication equipment adjustment;
note that, in the present embodiment, the tribe center
Figure 652264DEST_PATH_IMAGE127
An individual
Figure 338461DEST_PATH_IMAGE092
In the same sense, a clan center is an individual that is the center in a clan, and an individual is an element in a clan.
Example 2
The present invention also discloses an electronic device, which includes a processor, and when executing a computer program stored in a memory, the processor implements the communication device debugging method based on the clan formation mechanism as described in embodiment 1 or the communication device debugging method as described in embodiment 2.
Example 3
The invention also discloses a readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the processor realizes the debugging method of the communication equipment according to the embodiment 1 when the processor runs the computer program.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
In a typical configuration of an embodiment of the present invention, an electronic device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memories.
The memory may include forms of volatile memory in a computer readable medium, random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash-RAM. Memory is an example of a computer-readable medium.
Readable storage media, including both permanent and non-permanent, removable and non-removable media, may implement the information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data.
Examples of storage media for electronic devices include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include non-transitory computer-readable media (transient-media), such as modulated data signals and carrier waves.
It is obvious to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to perform all or part of the above described functions. The specific working process of the device described above can refer to the corresponding process in the foregoing method embodiments, and will not be repeated here
The description is given in detail.

Claims (9)

1. A communication equipment debugging method based on a tribe formation mechanism is characterized by comprising the following steps:
defining adjustment results for communication devices
Figure 569518DEST_PATH_IMAGE001
Adjusting parameters of the communication equipment to target variables
Figure 743011DEST_PATH_IMAGE002
，
Figure 753692DEST_PATH_IMAGE003
Setting an objective function for a decision variable
Figure 659331DEST_PATH_IMAGE004
Setting the value range of the decision variable based on the actual parameters of the communication equipment;
randomly putting N individuals in the feasible region of the decision variable, and allowing the individuals to randomly walk in the feasible region according to preset conditions to generate population distribution meeting the conditions;
clustering the individuals with the aggregation effect to form clans, eliminating clans which do not meet the requirements, and forming independent individuals in the eliminated clans; selecting a clan center for the rest clans, traversing all independent individuals in the clans, calculating the distance between each individual and each clan center, merging the individuals into the clan to which the clan center closest to the individual belongs to form a new clan, and reselecting the clan center for the new clan;
establishing a tribal center attraction mechanism, setting a tribal evolution condition, evolving tribals until the evolution times are reached, and taking the tribal centers of the evolved tribals as the values of decision variables of local optimization.
2. The method as claimed in claim 1, wherein the adjustment parameter is an antenna angle
Figure 755463DEST_PATH_IMAGE005
Working mode
Figure 201488DEST_PATH_IMAGE006
Output power of
Figure 269938DEST_PATH_IMAGE007
Working frequency band
Figure 408795DEST_PATH_IMAGE008
And modulation method
Figure 992223DEST_PATH_IMAGE009
Operating temperature of
Figure 179622DEST_PATH_IMAGE010
Bandwidth of the frequency
Figure 164896DEST_PATH_IMAGE011
Path loss value
Figure 474654DEST_PATH_IMAGE012
Antenna system
Figure 981597DEST_PATH_IMAGE013
If the adjustment result and the adjustment parameter satisfy the function relationship:
Figure 35003DEST_PATH_IMAGE014
equation (1)
Wherein,
Figure 874783DEST_PATH_IMAGE015
in order to be able to communicate with the mobile station,
Figure 293126DEST_PATH_IMAGE016
is a communication delay;
Figure 585568DEST_PATH_IMAGE017
and
Figure 442665DEST_PATH_IMAGE018
in order to be able to set the parameters,
Figure 74635DEST_PATH_IMAGE019
formula (1) is taken as the objective function.
3. The clan-forming-mechanism-based communication device debugging method according to claim 1, wherein the individual wandering is based on formula (2);
Figure 726196DEST_PATH_IMAGE020
(ii) a Formula (2)
Wherein,
Figure 771512DEST_PATH_IMAGE021
the step length of the wandering is set in the feasible region according to the decision variable;
Figure 166722DEST_PATH_IMAGE022
is as follows
Figure 653198DEST_PATH_IMAGE023
In individual the first
Figure 741239DEST_PATH_IMAGE024
The step size of the walk of the decision variable,
Figure 8273DEST_PATH_IMAGE025
；
the individuals after the wandering are recorded as
Figure 377812DEST_PATH_IMAGE026
Then, then
Figure 46691DEST_PATH_IMAGE027
，
Figure 305634DEST_PATH_IMAGE028
Comparison of
Figure 732067DEST_PATH_IMAGE029
And
Figure 734658DEST_PATH_IMAGE030
size of (1), if
Figure 258043DEST_PATH_IMAGE031
In addition, another
Figure 359991DEST_PATH_IMAGE032
If, if
Figure 601617DEST_PATH_IMAGE033
Hold, hold
Figure 142320DEST_PATH_IMAGE034
The temperature of the molten steel is not changed,
Figure 457895DEST_PATH_IMAGE035
each decision variable in (c) is obtained based on equation (3):
Figure 58640DEST_PATH_IMAGE036
(ii) a Formula (3)
Wherein,
Figure 521982DEST_PATH_IMAGE037
is the first before wandering
Figure 302594DEST_PATH_IMAGE038
In individual the first
Figure 800572DEST_PATH_IMAGE039
The number of the decision-making variables is determined,
Figure 306640DEST_PATH_IMAGE040
for the first time after wandering
Figure 460540DEST_PATH_IMAGE038
In individual the first
Figure 343046DEST_PATH_IMAGE039
A decision variable;
Figure 695530DEST_PATH_IMAGE041
obtaining based on formula (4):
Figure 372499DEST_PATH_IMAGE042
；formula (4)
Wherein,
Figure 748116DEST_PATH_IMAGE043
as decision variables
Figure 434313DEST_PATH_IMAGE044
The value range of (a).
4. The clan-forming-mechanism-based communication device debugging method according to claim 3, wherein the method for generating the population distribution satisfying the condition comprises the steps of:
recording the population after the individuals are thrown as an initial population, and acquiring the initial population density based on a formula (5)
Figure 641303DEST_PATH_IMAGE045
：
Figure 692436DEST_PATH_IMAGE046
(ii) a Formula (5)
Wherein N is the number of delivered individuals;
after the individual has completed a walk, a new population is obtained, based on
Figure 617666DEST_PATH_IMAGE043
Setting individuals
Figure 841974DEST_PATH_IMAGE044
Neighborhood of (2)
Figure 611128DEST_PATH_IMAGE047
Counting the number of individuals in the neighborhood
Figure 895479DEST_PATH_IMAGE048
Defining individuals based on equation (6)
Figure 42426DEST_PATH_IMAGE049
Density of (2)
Figure 8108DEST_PATH_IMAGE050
：
Figure 189691DEST_PATH_IMAGE051
(ii) a Formula (6)
Figure 644943DEST_PATH_IMAGE052
Is an individual
Figure 482449DEST_PATH_IMAGE053
The number of individuals in the neighborhood of (c);
the individual repeatedly swims in the feasible region until reaching the set repetition times or the obtained population exists
Figure 48560DEST_PATH_IMAGE054
Wherein
Figure 84649DEST_PATH_IMAGE055
And obtaining the population distribution meeting the conditions, and recording as a first population.
5. The communication device debugging method based on clan forming mechanism as claimed in claim 4, wherein the specific method for clustering the clans comprises the following steps:
allowing individuals with aggregation effects to form tribes
Figure 648485DEST_PATH_IMAGE056
Wherein
Figure 770025DEST_PATH_IMAGE057
the number of the clans after density clustering;
counting the number of individuals in all tribes
Figure 139827DEST_PATH_IMAGE058
Calculating the tribal density based on equation (7):
Figure 732220DEST_PATH_IMAGE059
equation (7)
Wherein,
Figure 529274DEST_PATH_IMAGE060
is as follows
Figure 138110DEST_PATH_IMAGE061
The density of the number of the individual sections,
Figure 983706DEST_PATH_IMAGE053
is as follows
Figure 994388DEST_PATH_IMAGE038
(ii) individuals;
after calculating the tribal density, if
Figure 962344DEST_PATH_IMAGE062
Or
Figure 996159DEST_PATH_IMAGE063
Then eliminate tribe
Figure 707763DEST_PATH_IMAGE064
Taking the individuals in the eliminated tribe as independent individuals, and forming a set by all the independent individuals
Figure 838530DEST_PATH_IMAGE065
The number of the remaining radicals is recorded as
Figure 915070DEST_PATH_IMAGE066
Wherein
Figure 232919DEST_PATH_IMAGE067
is a pre-set parameter of the process,
Figure 748214DEST_PATH_IMAGE068
。
6. the communication device tuning method of claim 5, wherein the first and second communication devices are connected to the first communication device,
Figure 733488DEST_PATH_IMAGE069
。
7. the communication device tuning method of claim 5, wherein the clan center is selected based on formula (8):
Figure 479465DEST_PATH_IMAGE070
(ii) a Formula (8)
Wherein,
Figure 284610DEST_PATH_IMAGE071
is as follows
Figure 338016DEST_PATH_IMAGE072
The tribe center of each tribe.
8. The clan-forming-mechanism-based communication device debugging method according to claim 7, wherein the individual is debugged
Figure 115479DEST_PATH_IMAGE073
，
Figure 596139DEST_PATH_IMAGE074
Establishing a tribal center attraction mechanism based on formula (9):
Figure 154160DEST_PATH_IMAGE075
(ii) a Formula (9)
Wherein,
Figure 683361DEST_PATH_IMAGE076
are all preset parameters;
all individuals
Figure 643227DEST_PATH_IMAGE077
The walk of (2) is realized based on the formula (10):
Figure 294788DEST_PATH_IMAGE078
(ii) a Formula (10)
Wherein,
Figure 12208DEST_PATH_IMAGE079
。
9. the clan-formation-mechanism-based communication device debugging method of claim 8, wherein clan evolution conditions are as follows:
setting individuals
Figure 407418DEST_PATH_IMAGE080
Probability of existence of outliers
Figure 221790DEST_PATH_IMAGE081
To, for
Figure 480471DEST_PATH_IMAGE082
，
Figure 747504DEST_PATH_IMAGE083
Randomly generating a random number of 0 to 1
Figure 946404DEST_PATH_IMAGE084
;
If it is
Figure 552966DEST_PATH_IMAGE085
Let us order
Figure 546330DEST_PATH_IMAGE086
Comparison of
Figure 300659DEST_PATH_IMAGE087
And
Figure 240933DEST_PATH_IMAGE088
size of (1), if
Figure 764318DEST_PATH_IMAGE089
Then another
Figure 928584DEST_PATH_IMAGE090
If, if
Figure 107892DEST_PATH_IMAGE091
Hold, hold
Figure 648595DEST_PATH_IMAGE092
Keeping the original shape;
if it is
Figure 26487DEST_PATH_IMAGE093
Let us order
Figure 627232DEST_PATH_IMAGE094
Comparison of
Figure 591292DEST_PATH_IMAGE087
And
Figure 935685DEST_PATH_IMAGE088
size of (1), if
Figure 168084DEST_PATH_IMAGE089
In addition, another
Figure 877414DEST_PATH_IMAGE090
If, if
Figure 828052DEST_PATH_IMAGE091
Hold, hold
Figure 710557DEST_PATH_IMAGE092
Unchanged, find updated leave
Figure 724DEST_PATH_IMAGE092
The nearest clan center, and incorporate it into that clan, where,
Figure 943273DEST_PATH_IMAGE095
is a preset parameter.
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Citations (6)

* Cited by examiner, † Cited by third party
Publication numberPriority datePublication dateAssigneeTitle
US20170147941A1 (en)*2015-11-232017-05-25Alexander BauerSubspace projection of multi-dimensional unsupervised machine learning models
CN110972062A (en)*2019-12-242020-04-07邑客得（上海）信息技术有限公司Base station position parameter calibration method and system based on mobile phone signaling data
CN113891334A (en)*2021-09-262022-01-04电子科技大学Directional base station debugging method of high-speed magnetic levitation train ground communication system
CN114239439A (en)*2021-12-242022-03-25浙江金乙昌科技股份有限公司Automatic filter design method based on tribal algorithm
WO2022179384A1 (en)*2021-02-262022-09-01山东英信计算机技术有限公司Social group division method and division system, and related apparatuses
WO2022237568A1 (en)*2021-05-102022-11-17中兴通讯股份有限公司Base station performance optimization method and apparatus, base station, and storage medium

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication numberPriority datePublication dateAssigneeTitle
US20170147941A1 (en)*2015-11-232017-05-25Alexander BauerSubspace projection of multi-dimensional unsupervised machine learning models
CN110972062A (en)*2019-12-242020-04-07邑客得（上海）信息技术有限公司Base station position parameter calibration method and system based on mobile phone signaling data
WO2022179384A1 (en)*2021-02-262022-09-01山东英信计算机技术有限公司Social group division method and division system, and related apparatuses
WO2022237568A1 (en)*2021-05-102022-11-17中兴通讯股份有限公司Base station performance optimization method and apparatus, base station, and storage medium
CN113891334A (en)*2021-09-262022-01-04电子科技大学Directional base station debugging method of high-speed magnetic levitation train ground communication system
CN114239439A (en)*2021-12-242022-03-25浙江金乙昌科技股份有限公司Automatic filter design method based on tribal algorithm

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