Method for determining antenna parameter combination and related device

Abstract

A method for determining an antenna parameter combination and a related device, the method comprising: obtaining a value of each antenna parameter combination in N groups of antenna parameter combinations, the value of a first antenna parameter combination in the N groups of antenna parameter combinations representing an adaptation degree of the first antenna parameter combination to user demand; taking M groups of antenna parameter combinations with larger values in the N groups of antenna parameter combinations as candidate antenna parameters; and taking an antenna parameter combination in the candidate antenna parameter set as a parent to determine a target antenna parameter combination. The method can more quickly and efficiently obtain an antenna parameter combination matching actual user demand from each generation of offspring, and improve the determination speed of the antenna parameter combination.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wireless communication, and in particular to a method for determining an antenna parameter combination and related apparatuses. BACKGROUND

[0002] The azimuth angle, the tilt angle, the weight value and other antenna parameters of a cell antenna are closely related to the coverage rate, the signal interference degree and other communication indexes of the signal of the cell antenna. However, no matter how the parameters of the antenna are adjusted, a set of parameters that can make each communication index optimal at the same time cannot be found. For example, when the coverage rate is greater, the interference degree between the signals of the antenna can also be more serious. With the iterative update of wireless technology and the gradual encryption of station sites, the antenna parameters of different cells among multiple sites need to be cooperatively planned, and a suitable antenna parameter combination is determined to make the communication indexes of the signal of the cell antenna reach relatively optimal values.

[0003] Therefore, finding an efficient method for determining an antenna parameter combination is a problem to be solved by those skilled in the art. SUMMARY

[0004] Embodiments of the present application provide a method for determining an antenna parameter combination and related apparatuses. The method can more quickly and efficiently obtain an antenna parameter combination that matches the actual needs of a user from the offspring of each generation by selecting a particle that matches the needs of the user as the parent particle of the subsequent offspring from the particle population according to the needs of the user, and improve the determination speed of the antenna parameter combination.

[0005] In a first aspect, embodiments of the present application provide a method for determining an antenna parameter combination. The method comprises: obtaining the value of each antenna parameter combination in N sets of antenna parameter combinations, wherein the value of a first antenna parameter combination in the N sets of antenna parameter combinations represents the degree of adaptation of the first antenna parameter combination to the needs of a user; selecting M sets of antenna parameter combinations with greater values from the N sets of antenna parameter combinations as a candidate antenna parameter set, wherein M is less than N, M is an integer greater than 0, and N is an integer greater than 1; and determining a target antenna parameter combination by taking the antenna parameter combinations in the candidate antenna parameter set as parents, wherein the target antenna parameter combination is used for antenna signal transmission.

[0006] In the method, the needs of the user include the priority of the user on multiple communication indexes of the antenna signal and the requirement for the compliance rate of the multiple communication indexes. The multiple communication indexes can include the coverage rate, the rate, the interference degree between signals and the like of the antenna signal, and the degree of excellence of these communication indexes is determined by one or more of the antenna parameter combinations such as the direction angle, the tilt angle, the horizontal lobe width, the vertical lobe width, the number of beams and the weight value parameter.

[0007] It should be understood that different users can have different requirements for the communication indexes. For example, user A can hope that the coverage of the antenna signal is above 90% and the rate is above 65 Mbit / s; but user B can not pay attention to the coverage and the rate of the antenna signal, but hope that the interference between the multi-antenna signals can be controlled within a certain range. Therefore, in the method, after the genetic algorithm obtains the plurality of antenna parameter combinations, the value of each of the antenna parameter combinations (i.e. the degree of adaptation of the antenna parameter combination to the user intention) can be calculated. For example, when the user hopes that the coverage of the antenna signal is above 90% but does not pay attention to the rate of the antenna signal, if there are two antenna parameter combinations (hereinafter referred to as combination 1 and combination 2 respectively), the coverage of the signal transmitted by the antenna using combination 1 is 90% and the rate is 585 Mbit / s, and the coverage of the signal transmitted by the antenna using combination 2 is 88% and the rate is 65 Mbit / s, then the device will select combination 1 as the antenna parameter combination in the candidate antenna parameter set, and combination 1 will be crossed and mutated as other antenna parameter combinations in the parent candidate antenna parameter set to obtain the next offspring.

[0008] The method sets the value of each antenna parameter combination in combination with the user intention, and in the selection process of each generation of offspring, the antenna parameter combination matched with the actual needs of the user can be obtained from each generation of offspring more quickly and efficiently, and the determination speed of the antenna parameter combination is improved.

[0009] In an optional implementation of the first aspect, the obtaining of the value of each antenna parameter combination in the N groups of antenna parameter combinations comprises: obtaining P incentive values of the first antenna parameter combination on P communication indexes, the incentive value of the first antenna parameter combination on a first index in the P communication indexes being determined by a completion amount of the first antenna parameter combination on the first index, and Q intervals of the first index and Q incentive coefficients corresponding to the Q intervals, the completion amount representing the degree of quality of the communication quality of the signal transmitted by the antenna using the first parameter combination on the first index, and P and Q being integers greater than 1; and obtaining the value of the first antenna parameter combination according to the P incentive values of the first antenna parameter combination on the P communication indexes.

[0010] In the implementation, the P communication indexes can include indexes such as the coverage of the antenna signal, the rate, the degree of interference between signals, etc. The first index is an index in the P communication indexes, which can be any one of the indexes such as the coverage of the antenna signal, the rate, the signal, etc. The Q intervals of the first index can be set according to the user requirements.

[0011] For example, assume that the optimal value of the first index (i.e. the best degree that the first index can reach) is 100, and the user's requirement for the first index is that the value of the first index cannot be lower than 90. Then the above Q intervals can be [0, 80], [80, 90] and [90, 100], and the corresponding incentive coefficients can be 10, 1 and 0 respectively. Then the incentive value of the first antenna parameter combination on the first index can be calculated by the relationship between the completion amount and the Q intervals. For example, when the completion amount of the first antenna parameter combination on the first index is 88, the completion amount falls in the interval [80, 90], and then the incentive value of the first antenna parameter combination on the first index in the P communication indexes is: (80 x 10) + (88-80) x 1 = 808; when the completion amount of the first antenna parameter combination on the first index is 92, the completion amount falls in the interval [90, 100], and then the incentive value of the first antenna parameter combination on the first index in the P communication indexes is: (80-0) x 10 + (90-80) x 1 + (92-90) x 0 = 810; and so on.

[0012] In the embodiment, by obtaining the incentive values of the antenna parameter combination on the P indexes, the gap between the completion amount of the antenna parameter combination on each index in the P indexes and the user's expectation value is obtained, and the incentive values of the antenna parameter combination on each index are calculated, so that the value of the antenna parameter combination can fully reflect the adaptation degree of the antenna parameter combination to the user's intention.

[0013] In an optional embodiment of the first aspect, before obtaining the P incentive values of the first antenna parameter combination on the P communication indexes, the method further comprises: obtaining a first parameter and a second parameter; the first parameter comprises a target threshold of each communication index in the P communication indexes, and the second parameter comprises a weight of each communication index in the P communication indexes, and the P is an integer greater than 1; the first parameter and the second parameter are used to determine Q intervals of the first index, and the Q intervals correspond to Q incentive coefficients respectively.

[0014] The Q intervals of the first index and the incentive coefficients corresponding to the Q intervals can be set according to the user's requirement. The following examples give four specific user requirements:

[0015] User requirement ①: priority is given to guarantee the optimization degree of the first target, and the user's requirement for the first index is that the value of the first index cannot be lower than N1.

[0016] For user requirement ①, the Q intervals of the first index can be set as [0, N1] and [N1, 100], and the corresponding incentive coefficients can be 1 and 0 respectively. Alternatively, the Q intervals can be set as [0, N1-10], [N1-10, N1] and [N1-10, 100], and the corresponding incentive coefficients can be w1, w2 and w3 respectively, and w1>w2>w3.

[0017] User requirement ②: the Q indexes further include a second index, a third index and the like. At this time, the user requirement for the first index is that the expected value of the first index is N2, but the deterioration is allowed, but the deterioration degree cannot exceed a lower limit (i.e. the completion amount of the antenna parameter combination in the offspring on the first index is less than the completion amount of the antenna parameter combination in the offspring on the first index, but the completion amount of the antenna parameter combination in each subsequent offspring on the first index cannot be less than a preset threshold, which is assumed to be N3), and the optimization degree of the second index, the third index and the like in the subsequent offspring is focused on.

[0018] For user requirement ②, it is assumed that the maximum completion amount of all antenna parameter combinations of the parent (assuming this generation is G1) of the first antenna parameter combination on the first index is N4. When N4 is less than N3 (i.e. the completion amount of all antenna parameter combinations in G1 on the first index is less than N3), the Q intervals of the first index can be set as [0, N4], [N4, N3], [N3, 100], and the corresponding incentive coefficients can be w4, w5 and w6 respectively, and w4>w5>w6. When N4 is greater than N3 (i.e. there is an antenna parameter combination in G1 whose completion amount on the first index is greater than N3), if the completion amount of the first antenna parameter combination on the first index is less than N3, the Q intervals can be set at will, and the incentive coefficients corresponding to the Q intervals are all negative infinity; if the completion amount of the first antenna parameter combination on the first index is not less than N3, the Q intervals of the first index can be set as [0, N2], [N2, 100], and the corresponding incentive coefficients can be w7 and w8 respectively, and w7<w8.

[0019] User requirement ③: the Q indexes further include a second index, a third index and the like. At this time, the user requirement for the first index is that the expected value of the first index is N5, and the user hopes to focus on the optimization degree of the second index, the third index and the like in the subsequent offspring. At this time, the user hopes that the Q indexes are optimized simultaneously. If the antenna parameter combination in the parent has reached the expected value of the user for a certain index, the optimization degree for this index can be reduced in the subsequent process.

[0020] For the user requirement ③, assume that the maximum amount of completion on the first index among all antenna parameter combinations of the same generation as the first antenna parameter combination (assume that this generation is the G2 generation) is N6. The Q intervals of the first index can be set as [0, N6-N7], [N6-N7, N5], and [N5, 100], where N7 can be any positive integer less than N6; and the corresponding incentive coefficients can be w7, w8, and w9 respectively, and w8 > w7 > w9.

[0021] The user requirement ④: the Q indexes further include a second index, a third index, and the like, and the user hopes that the value of the parameter combination finally used by the antenna can be maximum.

[0022] For the user requirement ④, assume that the maximum amount of completion on the first index among all antenna parameter combinations of the same generation as the first antenna parameter combination (assume that this generation is the G3 generation) is N8. The Q intervals of the first index can be set as [0, N8-N9], [N8-N9, 100], where N9 can be any positive integer less than N8; and the corresponding incentive coefficients can be w10, w11 respectively, and w11 > w10.

[0023] The above only exemplarily gives several specific user requirements, and the setting rules of the Q intervals of the first index and the corresponding Q incentive coefficients under the user requirement. For different user requirements, the Q intervals of the first index and the corresponding Q incentive coefficients can be different, which will not be listed one by one here.

[0024] It should be understood that the setting of the Q intervals of the first index and the corresponding Q incentive coefficients needs to be completed before the optimization of the antenna parameter combination begins (i.e., the first generation of antenna parameter combinations is generated). That is, in the subsequent process of optimizing the antenna parameter combination, the device only needs to set the Q intervals of the first index and the corresponding Q incentive coefficients for the antenna parameter combinations in the sub-generation according to the user requirements.

[0025] In an optional implementation of the first aspect, the Q intervals of the first index include a first interval and a second interval, the right end point value of the first interval is less than or equal to the left end point value of the second interval, the corresponding incentive coefficient of the second interval is a second incentive coefficient, the corresponding incentive coefficient of the first interval is a first incentive coefficient, and the second incentive coefficient is less than the first incentive coefficient.

[0026] It can be understood that in the multi-objective optimization problem of the antenna parameter, the optimization degree of multiple objectives is contradictory. For example, when the coverage of the antenna signal is greater, the interference between the signals is also stronger. Therefore, in the embodiment, since the greater the completion amount of the certain antenna parameter combination on the first index is, the closer the antenna parameter combination is to the customer expectation on the first index. At this time, the Q incentive coefficients corresponding to the Q intervals are set to decrease with the increase of the interval value, so as to avoid the continuous optimization of the subsequent offspring (i.e. the antenna parameter combination generated subsequently) on the index, so as to obtain the antenna parameter combination which is more optimal in the communication quality on each index.

[0027] In an optional implementation of the first aspect, the left end point value of the second interval is the completion amount of the first antenna parameter combination on the first index, and the completion amount represents the degree of the communication quality of the signal transmitted by the antenna using the first parameter combination on the first index.

[0028] In the embodiment, the Q intervals of the first index can also include a third interval, a fourth interval, and the like. The left end point value of the second interval is greater than any value contained in the other (Q-1) intervals. By setting the left end point value of the second interval as the completion amount of the first antenna parameter combination on the first index, the difference between the completion amount of the antenna parameter combination in the subsequent offspring on the first index and the demand of the user on the first index can be more accurately controlled under the condition that the demand of the user on the first index is met, so as to obtain a greater optimization degree of the antenna parameter combination generated subsequently on other indexes.

[0029] In an optional implementation of the first aspect, the second incentive coefficient is less than or equal to 0.

[0030] Any value in the second interval corresponding to the second incentive coefficient is greater than the demand of the user on the first index. After the completion amount of the first antenna parameter combination on the first index exceeds the demand of the user on the first index, by adjusting the second incentive coefficient to 0 or a negative number, the parameter combination which is excessively optimized on the first index such as the first antenna parameter combination can be avoided to be determined as the parent of the next generation. In this way, the difference between the completion amount of the antenna parameter combination in the subsequent offspring on the first index and the demand of the user on the first index can be more accurately controlled under the condition that the demand of the user on the first index is met, so as to obtain a greater optimization degree of the antenna parameter combination generated subsequently on other indexes.

[0031] In an optional implementation of the first aspect, the M groups of antenna parameter combinations with higher values from the N groups of antenna parameter combinations are selected as the candidate antenna parameter set.

[0032] In the embodiments of the present application, the M groups of antenna parameter combinations with higher values from the N groups of antenna parameter combinations are selected as the candidate antenna parameter set, and in the process of crossover and mutation (i.e., generating offspring through a genetic algorithm) of subsequent antenna parameter combinations, the matching degree of the antenna parameter combinations in the offspring to the user demand can be maximally guaranteed.

[0033] In the second aspect, the embodiments of the present application provide a device for determining an antenna parameter combination. The device comprises: a calculation unit configured to obtain a value of each group of antenna parameter combinations from N groups of antenna parameter combinations, wherein the value of a first antenna parameter combination from the N groups of antenna parameter combinations represents an adaptation degree of the first antenna parameter combination to a user demand; a determination unit configured to select M groups of antenna parameter combinations with higher values from the N groups of antenna parameter combinations as a candidate antenna parameter set, wherein the M is less than the N, the M is an integer greater than 0, and the N is an integer greater than 1; and a genetic unit configured to determine a target antenna parameter combination by taking an antenna parameter combination in the candidate antenna parameter set as a parent, wherein the target antenna parameter combination is used for antenna signal transmission.

[0034] In an optional implementation of the second aspect, the calculation unit is specifically configured to: obtain P incentive values of the first antenna parameter combination on P communication indexes, wherein the incentive value of the first antenna parameter combination on a first index from the P communication indexes is determined by a completed amount of the first antenna parameter combination on the first index, Q intervals of the first index, and Q incentive coefficients corresponding to the Q intervals, the completed amount represents an advantage or disadvantage degree of a signal transmitted by the antenna using the first parameter combination on the first index in terms of communication quality, and the P and the Q are integers greater than 1; and obtain the value of the first antenna parameter combination according to the P incentive values of the first antenna parameter combination on the P communication indexes.

[0035] In an optional implementation of the second aspect, the device further comprises an acquisition unit configured to acquire a first parameter and a second parameter, wherein the first parameter comprises a target threshold of each communication index from the P communication indexes, the second parameter comprises a weight of each communication index from the P communication indexes, and the P is an integer greater than 1; and the first parameter and the second parameter are used to determine the Q intervals of the first index and the Q incentive coefficients corresponding to the Q intervals, respectively.

[0036] In an optional implementation of the second aspect, the Q intervals of the first index include a first interval and a second interval, a right end point value of the first interval is less than or equal to a left end point value of the second interval, the second interval corresponds to a second excitation coefficient, the first interval corresponds to a first excitation coefficient, and the second excitation coefficient is less than the first excitation coefficient.

[0037] In an optional implementation of the second aspect, the left end point value of the second interval is a completion amount of the first antenna parameter combination on the first index, and the completion amount represents a degree of quality of communication of a signal transmitted by the antenna using the first parameter combination on the first index.

[0038] In an optional implementation of the second aspect, the second excitation coefficient is less than or equal to 0.

[0039] In an optional implementation of the second aspect, the determining unit is specifically configured to: take the top M antenna parameter combinations in the N groups of antenna parameter combinations as the candidate antenna parameter set.

[0040] In a third aspect, an embodiment of the present application provides an electronic device, including: a memory configured to store a program; and a processor configured to execute the program stored in the memory, and when the program is executed, the processor is configured to execute the method in the first aspect and any optional implementation.

[0041] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, the computer readable storage medium stores a computer program, the computer program includes program instructions, and the program instructions, when executed by a processor, cause the processor to execute the method in the first aspect and any optional implementation.

[0042] The technical solutions provided in the second to fourth aspects of the present application have the beneficial effects of the technical solutions provided in the first aspect, which will not be repeated here. BRIEF DESCRIPTION OF DRAWINGS

[0043] The drawings needed in the following embodiment description will be briefly introduced.

[0044] Figure 1A A Pareto frontier diagram of an antenna parameter combination optimization solution provided by an embodiment of the present application;

[0045] Figure 1A A schematic diagram of a candidate antenna set provided by an embodiment of the present application;

[0046] Figure 2 A flowchart of a determination method of an antenna parameter combination provided by an embodiment of the present application;

[0047] Figure 3 A flowchart illustrating a method for determining a set of candidate parameters provided in an embodiment of this application;

[0048] Figure 4 A graph showing the relationship between an index range and an incentive coefficient is provided for an embodiment of this application.

[0049] Figure 5 A graph showing the relationship between the overall completion rate of an antenna parameter combination in terms of performance indicators and the optimization efficiency of those indicators, provided for an embodiment of this application.

[0050] Figure 6 A schematic diagram of particle population distribution in a two-dimensional search space provided in an embodiment of this application;

[0051] Figure 7 A graph showing the relationship between the number of particle iterations and the degree of index optimization is provided in an embodiment of this application;

[0052] Figure 8 A graph showing the relationship between particle iteration count and coverage optimization degree is provided in an embodiment of this application.

[0053] Figure 9 A schematic diagram of the structure of an antenna parameter combination determination device provided in an embodiment of this application;

[0054] Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0055] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0056] For ease of understanding, the following examples illustrate some concepts related to the embodiments of this application for reference. As follows:

[0057] 1 particle

[0058] A combination of multiple cell parameters, radio frequency (RF) parameters, and beamforming (BF) parameters is called a particle. Cell parameters include parameters characterizing the cell's location region and parameters characterizing the cell's communication quality, such as mobile network code, tracking area code, received signal strength, reference signal received power, and sector code. RF represents the electromagnetic frequency (300 kHz - 300 GHz) that can be radiated into space. RF parameters include azimuth, tilt, station height, gain coefficient, beamwidth, and directivity. Beamforming is a combination of antenna technology and digital signal processing technology, used for directional signal transmission or reception. BF parameters include the weighting parameters used in massive MIMO (Massively Multi-Size Antenna) technology.

[0059] 2 Multi-objective optimization

[0060] People will often encounter the optimization problem that makes multiple objectives in a given area at the same time as best as possible, that is, multi-objective optimization problem. In practice, most optimization problems are multi-objective optimization problems, and in general, the sub-goals of multi-objective optimization problems are contradictory. Improvement of one goal may cause performance degradation of another or several goals. It is impossible to simultaneously optimize multiple sub-goals to optimal values, and only coordination and compromise among them can be made to achieve optimization as much as possible. The essential difference between single-objective optimization problem and multi-objective optimization problem is that the solution of the former is unique, while the solution of the latter is a set of Pareto optimal solutions. Each element in the optimal solution set composed of a large number of Pareto optimal solutions is called a Pareto optimal solution or a non-inferior optimal solution. Multi-objective optimization problem is described in words as an optimization problem composed of D decision variable parameters, N objective functions, and (m+n) constraints. The decision variable and the objective function, the constraint condition are in functional relationship. In the non-inferior solution set, the decision maker can only select a non-inferior solution that satisfies the specific problem requirements as the final solution.

[0061] 3. Genetic Algorithm (GA)

[0062] Genetic algorithm is originated from computer simulation research on biological systems. It is a random global search and optimization method that simulates the biological evolution mechanism in nature, drawing on Darwin's theory of evolution and Mendel's genetic theory. Its essence is a high-efficiency, parallel, global search method that can automatically acquire and accumulate knowledge about the search space during the search process and adaptively control the search process to obtain the best solution.

[0063] 4. Pareto optimal solution set and Pareto front

[0064] If vector u = (u1,..., um) and vector v = (v1,..., vm) satisfy uk≤ vk, then the vector u dominates the vector v, denoted as u < v. If the vector u does not dominate the vector v and the vector v does not dominate the vector u, we call u and v mutually undominated, denoted as u≮v or v≮u. If a feasible solution x* in the solution space S satisfies: then we call x* a Pareto optimal solution in the solution space S. All Pareto optimal solutions constitute a Pareto optimal solution set, and these solutions form the Pareto optimal front or Pareto front surface of the problem through the mapping of the objective function, that is, the objective function value corresponding to the Pareto optimal solution is the Pareto optimal front. For multiple objectives, the Pareto front is usually a hyper-surface.

[0065] 5. Completion Quantity

[0066] The completion rate characterizes the communication quality of a signal transmitted by an antenna using a certain combination of antenna parameters on a specific metric. It can be quantified into a specific numerical value; the higher the completion rate, the better the communication quality. For example, in this embodiment, the best coverage effect that the antenna signal can achieve is 100% coverage. Therefore, when the coverage rate of the signal transmitted by the antenna using a certain combination of antenna parameters is 90%, the completion rate of the signal transmitted by the antenna using that combination of antenna parameters is 90%.

[0067] With the iterative updates of wireless technology and the gradual densification of site locations, the antenna parameters (RF / BF parameters, etc.) of different cells across multiple sites need to be planned collaboratively to achieve a balance between ensuring coverage and reducing interference. Antenna parameters such as azimuth, tilt, and weights are closely related to communication indicators such as signal coverage and signal interference levels. However, no matter how the antenna parameters are adjusted, it is often impossible to find a set of parameters that simultaneously optimizes every communication indicator. For example, the greater the coverage, the more severe the mutual interference between antenna signals may be. Therefore, with the iterative updates of wireless technology and the gradual densification of site locations, the antenna parameters of different cells across multiple sites need to be planned collaboratively to determine suitable combinations of antenna parameters, allowing the various communication indicators of the cell antenna signal to achieve relatively optimal values.

[0068] Currently, in multi-objective optimization problems involving various communication indicators of antennas, the determination of antenna parameter combinations is generally based on the method of fast sorting of dominant solutions, selecting the relatively optimal parameter combination from the numerous parameter combinations in the offspring. Figure 1A This is a Pareto front plot of an antenna parameter combination optimization solution provided in an embodiment of this application. Figure 1A As shown, the search space contains a large number of particles, all of which are offspring of the same generation of parent particles. In fact, the dimension of the search space is the same as the number of objective functions in a multi-objective optimization problem. That is, when there are P communication indicators for the antenna signal, the corresponding search space should be P-dimensional. However, for the convenience of the reader, Figure 1A The search shown is in a two-dimensional space. In this search space, particle AH is a particle selected from the particle population using a traditional dominant solution quicksort algorithm. These particles are all Pareto optimal solutions, and AH also forms the front of this search space. In the subsequent evolution of the genetic algorithm, particle AH will act as the parent for crossover and mutation, generating the next generation (i.e., offspring) of particles; while the remaining particles in the same generation as particle AH (such as particles K and I) will be eliminated and will no longer participate in subsequent crossover, mutation, and other reproductive processes.

[0069] but, Figure 1AEach of the parameters A to H shown in the middle is a relatively optimal solution in a certain aspect. If optimization is directly based on these relatively optimal solutions, a large amount of optimization computing power will be consumed. In addition, in actual use, the demand level of users for various communication indicators of the antenna is different. The particles determined by the universal sorting search method of the above-mentioned method based on the fast sorting of the dominated solution often do not match the actual needs of the user.

[0070] In view of the deficiencies in the above-mentioned antenna parameter combination determination method, the embodiment of the present application provides an antenna parameter combination determination method. The method can select particles that match the user's needs from the particle population as the parent particles of the subsequent offspring according to the user's needs, so as to more quickly and efficiently obtain an antenna parameter combination that matches the user's actual needs from each generation of offspring, thereby improving the determination speed of the antenna parameter combination. As shown in Figure 1B The method can select particles C and D that match the user's needs from the particle population (i.e., determine particles C and D as particles in the candidate parameter set), and continue to cross and mutate based on particles C and D until the final antenna parameter combination for use is generated, thereby improving the determination speed of the antenna parameter combination. As shown in Figure 2 The method can include the following steps:

[0071] 201 The electronic device obtains the value of each antenna parameter combination in the N groups of antenna parameter combinations.

[0072] The above-mentioned electronic device can be a computer (such as a notebook computer, a palm computer, etc.) with data transceiving function, a mobile phone, a tablet computer, a mobile internet device (MID), a terminal in industrial control, a terminal in smart city, a terminal device in 5G network, or a terminal device in future evolved public land mobile network (PLMN), etc. The specific form of the electronic device is not limited in the present application.

[0073] The above-mentioned N groups of antenna parameter combinations can be an initialized particle population. That is, the above-mentioned electronic device can first randomly initialize the particle population in a given solution space, and the number of variables of the problem to be optimized determines the dimension of the solution space. Each particle has an initial position and an initial speed, and then iteratively optimizes. In addition, the above-mentioned N groups of antenna parameter combinations can also be the particle population of a generation in the subsequent iterative optimization process. It should be noted that the N groups of antenna combinations should belong to the particles in the same generation of particle population.

[0074] In the application embodiment, the value of any one of the N groups of antenna parameter combinations represents the degree of adaptation of the group of antenna parameter combinations to the user demand. Taking the first antenna parameter combination and the second antenna parameter combination in the N groups of antenna parameter combinations as an example, when the value of the first antenna parameter combination is greater than the value of the second antenna parameter combination, it indicates that the first antenna parameter combination is more in line with the user demand than the second antenna parameter combination.

[0075] Specifically, in order to quantify the value of each antenna parameter combination in the N groups of antenna parameter combinations, taking the first antenna combination as an example, in an optional embodiment, the electronic device can obtain P excitation values of the first antenna parameter combination on P communication indicators, and obtain the value of the first antenna parameter combination according to the P excitation values of the first antenna parameter combination on the P communication indicators. The excitation value of the first indicator in the P communication indicators is determined by the completion amount of the first antenna parameter combination on the first indicator, and the Q intervals of the first indicator and the Q excitation coefficients corresponding to the Q intervals. P and Q are integers greater than 1.

[0076] The P communication indicators can include coverage, rate, interference degree between signals, and the like. The first indicator is any one of the indicators, such as coverage, rate, signal, and the like. The Q intervals of the first indicator can be set according to the user demand. The completion amount represents the degree of quality of the communication quality of the signal transmitted by the antenna using the first parameter combination on the first indicator. For example, when the first indicator is the coverage of the antenna signal, the best result it can achieve is 100% (assuming that the completion amount corresponding to this coverage is 100), and when the coverage of the signal transmitted by the antenna using the first parameter combination is 90%, the completion amount of the first antenna parameter combination on the first indicator is 90, and so on.

[0077] Specifically, the calculation method of the excitation value of the first indicator can be represented as:

[0078] P1=W p1 *L[T0,T1]*J1+W p1 *L[T1,T2]*J2+......+W p1 *L[T Q-1 ,T Q ]*J Q ;

[0079] Wherein, P1 is the excitation value of the first indicator, W p1represents the multi-objective weight corresponding to the first index among the P communication indexes, which can be defined by the user, and by default, the multi-objective weight corresponding to each index among the P communication indexes is the same, which is set to 1. "*" represents multiplication, [T N-l , T N ](N=1, 2, 3,..., Q) represents the Nth interval among the Q intervals of the first index. N (N=1, 2, 3,..., Q) is the incentive value corresponding to the Nth interval among the Q intervals of the first index. L[T N-1 , T N ] represents the length of the completion amount covering the Nth interval; for example, assuming that the completion amount is 60, when T N-1 =30, T N =80, then L[30, 80]=60-30=30; when T N-1 =0, T N =50, then L[0, 80]=60-0=60; when T N-1 =30, T N =40, then L[30, 40]=40-30=10; when T N-1 =80, T N =90, then L[30, 80]=0; and so on.

[0080] It should be understood that the Q intervals of the first index can be set according to user needs. For example, assuming that the optimal value of the first index (i.e., the best degree that the first index can reach) is 100, and the user's requirement for the first index is that the value of the first index cannot be lower than 90. Then the Q intervals can be [0, 80], [80, 90], and [90, 100], and the corresponding incentive coefficients can be 10, 1, and 0, respectively. Assuming that the completion amount of the first antenna parameter combination on the first index is 88, at this time the completion amount falls into the interval [80, 90], then according to the above expression and the setting condition of the Q intervals and the Q incentive coefficients, the incentive value of the first antenna parameter combination on the first index among the P communication indexes is calculated as: (80*10)+(88-80)*1=808; assuming that the completion amount of the first antenna parameter combination on the first index is 92, at this time the completion amount falls into the interval [90, 100], then the incentive value of the first antenna parameter combination on the first index among the P communication indexes is: (80-0)*10+(90-80)*1+(92-90)*0=810.

[0081] In addition, the Q intervals can be continuous Q intervals or discontinuous Q intervals, which are not limited by the embodiments of the present application.

[0082] Further, based on the above-mentioned calculation expression of the incentive value of the first index for the first antenna parameter combination, the calculation manner of the value of the first antenna parameter combination can be expressed as:

[0083]

[0084] wherein P w1 is the value of the first antenna parameter combination, W pi represents the multi-objective weight corresponding to the i-th (i = 1, 2, 3, …, P) index among the P communication indexes, which can be defined by the user, and by default, the multi-objective weight corresponding to each index among the P communication indexes is the same, which is set to 1. P i is the incentive value of the first antenna parameter combination on the i-th (i = 1, 2, 3, …, P) communication index among the P communication indexes, and the calculation manner of P i can refer to the above-mentioned calculation expression of the incentive value of the first index for the first antenna parameter combination.

[0085] Specifically, in order to flexibly set the Q intervals of the first index and the Q incentive coefficients corresponding thereto according to the user demand. In an optional embodiment, before obtaining the P incentive values of the first antenna parameter combination on the P communication indexes, the method further obtains a first parameter and a second parameter; the first parameter includes the target threshold of each communication index among the P communication indexes, and the second parameter includes the weight of each communication index among the P communication indexes, wherein P is an integer greater than 1; the first parameter and the second parameter are used to determine the Q intervals of the first index, and the Q intervals correspond to Q incentive coefficients respectively.

[0086] The Q intervals of the first index and the incentive coefficients corresponding to the Q intervals can be set according to the above-mentioned user demand. The following examples give four specific user demands:

[0087] User demand ①: priority is given to the optimization degree of the first target, and the user's requirement for the first index is that the value of the first index cannot be lower than N1.

[0088] For user demand ①, the Q intervals of the first index can be set as [0, N1] and [N1, 100], and the corresponding incentive coefficients can be 1 and 0 respectively. Or, the Q intervals can be set as [0, N1-10], [N1-10, N1] and [N1-10, 100], and the corresponding incentive coefficients can be w1, w2 and w3 respectively, and w1 > w2 > w3.

[0089] User requirement ②: the Q indexes further include a second index, a third index, and the like. At this time, the user requires the first index to have an expected value of N2, but allows the first index to deteriorate, but the deterioration degree cannot exceed a lower limit (i.e., the first index of the offspring is allowed to have a performance less than the performance of the first index of the offspring, but the performance of the first index of each subsequent offspring cannot be less than a preset threshold, which is assumed to be N3), and the optimization degree of the second index, the third index, and the like in the subsequent offspring is emphasized.

[0090] For user requirement ②, it is assumed that the performance of the first index of all the antenna parameter combinations of the parent of the first antenna parameter combination (assuming that this generation is the G1 generation) is N4. When N4 is less than N3 (i.e., the performance of the first index of all the antenna parameter combinations of the G1 generation is less than N3), the Q intervals of the first index can be set as [0, N4], [N4, N3], and [N3, 100], and the corresponding incentive coefficients can be w4, w5, and w6, respectively, and w4 > w5 > w6. When N4 is greater than N3 (i.e., there is an antenna parameter combination of the G1 generation whose performance of the first index is greater than N3), if the performance of the first index of the first antenna parameter combination is less than N3, the Q intervals can be set at will, and the incentive coefficients corresponding to the Q intervals are all negative infinity; if the performance of the first index of the first antenna parameter combination is not less than N3, the Q intervals of the first index can be set as [0, N2] and [N2, 100], and the corresponding incentive coefficients can be w7 and w8, respectively, and w7 < w8.

[0091] User requirement ③: the Q indexes further include a second index, a third index, and the like. At this time, the user requires the first index to have an expected value of N5, and the user hopes to emphasize the optimization degree of the second index, the third index, and the like in the subsequent offspring. At this time, the user hopes that the Q indexes are simultaneously optimized. If the antenna parameter combination of the parent has reached the expected value of a certain index, the optimization degree of the index in the subsequent process can be reduced.

[0092] For user requirement ③, it is assumed that the performance of the first index of all the antenna parameter combinations of the first antenna parameter combination parent (assuming that this generation is the G2 generation) is N6. The Q intervals of the first index can be set as [0, N6-N7], [N6-N7, N5], and [N5, 100], where N7 can be any positive integer less than N6; the corresponding incentive coefficients can be w7, w8, and w9, respectively, and w8 > w7 > w9.

[0093] User requirement ④: the above Q indexes also include second index, third index and so on, and the user hopes that the value of the parameter combination used by the antenna can be maximized.

[0094] For user requirement ④, assuming that the maximum amount of completion of the above first antenna parameter combination parent (assuming this generation is the G3 generation) in all antenna parameter combinations on the above first index is N8. The Q intervals of the above first index can be set to [0, N8-N9], [N8-N9, 100], where N9 can be any positive integer less than N8; the corresponding incentive coefficients can be w10, w11 respectively, and w11>w10.

[0095] The above only exemplarily gives several specific user requirements and the setting rules of the Q intervals of the above first index and the corresponding Q incentive coefficients under these user requirements. For different user requirements, the Q intervals of the above first index and the corresponding Q incentive coefficients can be different, which will not be listed one by one here.

[0096] It should be understood that the setting of the Q intervals of the above first index and the corresponding Q incentive coefficients needs to be completed before the antenna parameter combination starts to be optimized (i.e. the first generation of antenna parameter combination is generated). That is, in the subsequent process of antenna parameter combination optimization, the user cannot change the setting of the Q intervals of the above first index and the corresponding Q incentive coefficients, and the device will set the above Q intervals of the above first index and the corresponding Q incentive coefficients for the antenna parameter combinations in the offspring according to the user requirements.

[0097] In an optional embodiment, the Q intervals of the first index include a first interval and a second interval, the right end point value of the first interval is less than or equal to the left end point value of the second interval, the excitation coefficient corresponding to the second interval is a second excitation coefficient, the excitation coefficient corresponding to the first interval is a first excitation coefficient, and the second excitation coefficient is less than the first excitation coefficient. That is, the Q excitation coefficients corresponding to the Q intervals of the first index are set to decrease as the interval value increases. In addition, the Q intervals can further include a third interval, when the right end point value of the third interval is less than or equal to the left end point value of the first interval, the second excitation coefficient is less than a third excitation coefficient corresponding to the third interval. It can be understood that in the multi-objective optimization problem of the antenna parameters, the optimization degrees of multiple objectives are contradictory. For example, when the coverage of the antenna signal is greater, the interference between signals is also stronger. Therefore, in the present embodiment, when the completion amount of the certain antenna parameter combination on the first index is greater, the antenna parameter combination is closer to the customer expectation on the first index. At this time, the Q excitation coefficients corresponding to the Q intervals are set to decrease as the interval value increases, to avoid the continuous optimization of the subsequent offspring on the index, so as to obtain the antenna parameter combination with better comprehensive communication quality on each index.

[0098] In an optional embodiment, the left end point value of the second interval is the completion amount of the first antenna parameter combination on the first index, and the completion amount represents the optimization degree of the communication quality of the signal emitted by the antenna using the first antenna parameter combination on the first index. In the present embodiment, the Q intervals of the first index can further include a third interval, a fourth interval, and the like. Among them, the left end point value of the second interval is greater than any value contained in the other (Q-1) intervals. By setting the left end point value of the second interval as the completion amount of the first antenna parameter combination on the first index, the difference between the completion amount of the antenna parameter combination in the subsequent offspring on the first index and the user demand for the first index can be more accurately controlled under the condition that the user demand for the first index is met, so as to obtain greater optimization degree of the subsequent generated antenna parameter combination on other indexes.

[0099] In an optional embodiment, the second incentive coefficient is less than or equal to 0. In this embodiment, any value in the second interval corresponding to the second incentive coefficient is greater than the user's demand for the first index. That is, when the first antenna parameter combination exceeds the user's demand for the first index, by adjusting the second incentive coefficient to 0 or a negative number, the parameter combination that is over-optimized in the first index, such as the first antenna parameter combination, can be avoided to be determined as the parent of the next generation. In this way, the difference between the amount of the first index completed by the antenna parameter combination in the subsequent offspring and the user's demand for the first index can be more accurately controlled to exchange for greater optimization of the antenna parameter combination in other indexes generated subsequently, while meeting the user's demand for the first index.

[0100] 202. The electronic device compares the values of the N groups of antenna parameter combinations, and selects M groups of antenna parameter combinations with greater values as the candidate antenna parameter set.

[0101] After obtaining the value of each group of antenna parameter combinations in the N groups of antenna parameter combinations, the electronic device compares the values of each group of antenna parameter combinations in the N groups of antenna parameter combinations, and selects M groups of antenna parameter combinations with greater values as the candidate antenna parameter set.

[0102] In an optional embodiment, in order to maximize the matching degree of the antenna parameter combination in the offspring with the user's demand in the process of crossover and mutation (i.e., generating offspring by genetic algorithm) of subsequent antenna parameter combinations, the electronic device can select the M antenna parameter combinations with the greatest values in the N groups of antenna parameter combinations as the candidate antenna parameter set.

[0103] 203. The electronic device determines the target antenna parameter combination by taking the antenna parameter combination in the candidate antenna parameter set as the parent.

[0104] After determining the candidate antenna parameter combination, the electronic device performs crossover and mutation between the antenna parameter combinations in the candidate antenna parameter set based on the genetic algorithm, i.e., taking the antenna parameter combinations in the candidate antenna parameter set as parent particles, to generate a new generation of particles.

[0105] It can be understood that in the process of continuous iteration of the genetic algorithm, the population of particles generated in each generation can be calculated based on the method provided in the embodiments of the present application to calculate the value of each particle, and based on the value of each particle, the particles used for breeding as parents can be selected from the particle population of this generation.

[0106] Specifically, when G x generation and G x.1 generation (G xGeneration and G x.1 Generation is two generations in succession, namely G x Particles in the Generation G x.1 When the value of the particle in the Generation G x Particles in the Generation G x-1 Particles in the Generation G x For example, when the average value of the value of each particle in the Generation G x-1 When the average value of the value of each particle in the Generation G x When the value of the particle with the highest value in the Generation G x-1 When the value of the particle with the highest value in the Generation G x Particles in the Generation G x-1 Particles in the Generation G

[0107] The method can more quickly and efficiently obtain the antenna parameter combination matching the actual demand of the user from each generation of offspring, and improve the determination speed of the antenna parameter combination, by selecting the particle matching the demand of the user as the parent particle of the subsequent offspring from the particle population according to the demand of the user.

[0108] Based on the method for determining the antenna parameter combination, an embodiment of the present application provides a method for determining a candidate parameter set. The candidate parameter set in the method can be determined based on the method for determining the candidate parameter set provided by the embodiment of the present application. For details, refer to the method for determining the candidate parameter set. Figure 2 Figure 3 As shown in FIG. 13, the method can include the following steps: Figure 3

[0109] 301 The electronic device obtains a first parameter and a second parameter.

[0110] ​​The electronic device can be a computer (e.g., a notebook computer, a palm computer, etc.) with data transceiving function, a mobile phone, a pad, a mobile internet device (MID), a terminal in industrial control, a terminal in a smart city, a terminal device in a 5G network, or a terminal device in a future evolved public land mobile network (PLMN), etc. The specific form of the electronic device is not limited in the present application. Specifically, the electronic device can be the aforementioned electronic device in the description. Figure 2 The electronic device in the description.

[0111] The first parameter can include a target threshold of each of P communication indexes, and the second parameter includes a weight of each of the P communication indexes. P is an integer greater than 1. The first parameter and the second parameter are used to determine a plurality of intervals of each of the P indexes, and a plurality of incentive coefficients corresponding to the plurality of intervals of each index. For example, the first parameter and the second parameter can be used to determine Q intervals of a first index of the P indexes, and Q incentive coefficients corresponding to the Q intervals of the first index.

[0112] 302 The electronic device obtains P incentive values of the first antenna parameter combination on P communication indexes.

[0113] Specifically, in order to determine a candidate parameter set as a next-generation parent from N antenna parameter combinations, the value of each antenna parameter combination in the N antenna parameter combinations needs to be quantified, which represents the degree of adaptation of the antenna parameter combination to user demand. Taking the first antenna combination as an example, in an optional implementation, the electronic device can obtain P incentive values of the first antenna parameter combination on P communication indexes, and obtain the value of the first antenna parameter combination according to the P incentive values of the first antenna parameter combination on the P communication indexes.

[0114] The P communication indexes can include coverage, rate, interference degree between signals, and the like. The first index is an index in the P communication indexes, which can be any one of the indexes of coverage, rate, signal, and the like. The Q intervals of the first index can be set according to the user demand. The completion quantity represents the pros and cons of the communication quality of the signal transmitted by the antenna using the first parameter combination in the first index. For example, when the first index is the coverage of the antenna signal, the best result that can be achieved is 100% (assuming that the completion quantity corresponding to the coverage is 100), and when the coverage of the signal transmitted by the antenna using the first parameter combination is 90%, the completion quantity of the first antenna parameter combination in the first index is 90, and the like.

[0115] Specifically, the calculation method of the incentive value of the first index can be represented as:

[0116] P1=W p1 *L[T0, T1]*J1+W p1 *L[T1, T2]*J2+......+W p1 *L[T Q-1 , T Q ]*J Q ;

[0117] P1 is the incentive value of the first index, W p1 represents the multi-objective weight corresponding to the first index in the P communication indexes, which can be customized by the user. By default, the multi-objective weight corresponding to each index in the P communication indexes is the same, which is set to 1. "*" represents multiplication. [T N-1 , T N ](N=1, 2, 3,..., Q) represents the Nth interval in the Q intervals of the first index. J N (N=1, 2, 3,..., Q) is the incentive value corresponding to the Nth interval in the Q intervals of the first index. L[T N-1 , T N ] represents the length of the completion quantity covering the Nth interval; for example, assuming that the completion quantity is 60, when T N-1 =30, T N =80, then L[30, 80]=60-30=30; when T N-1 =0, T N =50, then L[0, 80]=60-0=60; when T N-1 =30, T N =40, then L[30, 40]=40-30=10; when T N-1 =80, TN = 90, then L[30, 80] = 0; and so on.

[0118] It should be understood that the Q intervals of the first index described above can be set according to user requirements. For example, assuming that the optimal value of the first index described above (i.e., the best degree that the first index can reach) is 100, and the user's requirement for the first index is that the value of the first index cannot be lower than 90. Then the Q intervals described above can be [0, 80], [80, 90] and [90, 100], and the corresponding incentive coefficients can be 10, 1 and 0 respectively. Assuming that the completion amount of the first antenna parameter combination on the first index is 88, at this time the completion amount falls into the interval [80, 90], then according to the above expression and the setting condition of the Q intervals and the Q incentive coefficients, the incentive value of the first antenna parameter combination on the first index in the P communication indexes can be calculated as: (80 x 10) + (88-80) x 1 = 808; assuming that the completion amount of the first antenna parameter combination on the first index is 92, at this time the completion amount falls into the interval [90, 100], then the incentive value of the first antenna parameter combination on the first index in the P communication indexes can be calculated as: (80-0) x 10 + (90-80) x 1 + (92-90) x 0 = 810.

[0119] 303. The electronic device described above obtains the value of the first antenna parameter combination according to the P incentive values of the first antenna parameter combination on the P communication indexes.

[0120] Further, based on the calculation expression of the incentive value of the first antenna parameter combination on the first index, the calculation method of the value of the first antenna parameter combination can be represented as:

[0121]

[0122] wherein, P w1 is the value of the first antenna parameter combination, W pi represents the multi-objective weight corresponding to the i-th (i = 1, 2, 3,..., P) index in the P communication indexes, which can be customized by the user, and by default, the multi-objective weight corresponding to each index in the P communication indexes is the same, which is set to 1. P i is the incentive value of the first antenna parameter combination on the i-th (i = 1, 2, 3,..., P) communication index in the P communication indexes, and the calculation method of P i can refer to the calculation expression of the incentive value of the first antenna parameter combination on the first index.

[0123] 304. The electronic device described above obtains the value of each antenna parameter combination in the N groups of antenna parameter combinations.

[0124] It can be understood that the first antenna parameter combination is one of the N antenna parameter combinations. The first parameter and the second parameter can also be used to determine the intervals of the P indicators other than the first indicator, and the intervals of the other indicators correspond to the excitation coefficients respectively. For example, the first parameter and the second parameter can also be used to determine the R intervals of the second indicator and the corresponding R excitation coefficients, and the S intervals of the third indicator and the corresponding S excitation coefficients, and so on. Correspondingly, the first antenna parameter combination in steps 303-304 corresponds to the excitation value P1 of the first indicator and the first antenna parameter combination P wl According to the calculation method of the first antenna parameter combination in steps 303-304 and the P indicators, the electronic device can also calculate the value of each antenna parameter combination in the N antenna parameter combinations, which will not be listed one by one.

[0125] 305. The electronic device takes the top M antenna parameter combinations in the N antenna parameter combinations as the candidate antenna parameter set.

[0126] After obtaining the value of each antenna parameter combination in the N antenna parameter combinations, in order to maximize the matching degree of the antenna parameter combination in the offspring and the user demand in the process of crossover and mutation (i.e., generating offspring through genetic algorithm) of subsequent antenna parameter combinations, the electronic device compares the values of the N antenna parameter combinations, and takes the top M antenna parameter combinations in the N antenna parameter combinations as the candidate antenna parameter set.

[0127] The embodiment of the present application quantifies the adaptation degree of the antenna parameter combination and the user demand by setting the excitation intervals of the communication indicators of the cell antenna and the excitation coefficients of each indicator in different excitation intervals according to the user demand, and can more quickly and efficiently obtain the antenna parameter combination matching the actual demand of the user from each generation of offspring.

[0128] As can be seen from the foregoing description, in the multi-objective optimization problem of the antenna parameters, the optimization degrees of the multiple objects are contradictory. For example, when the coverage of the antenna signal is greater, the interference between the signals is also stronger. Therefore, in the present application, when the completion amount of a certain antenna parameter combination on a certain index is greater, it indicates that the antenna parameter combination is closer to the expectation of the customer on the first index. At this time, the multiple intervals corresponding to the index and the corresponding multiple incentive coefficients can be set to decrease with the increase of the interval values, and even the incentive coefficients of some intervals are adjusted to 0 or negative numbers, so as to avoid the continuous optimization of the subsequent offspring on the index, so as to obtain the optimization of the subsequent generated antenna parameter combination on other indexes, and obtain the antenna parameter combination with better comprehensive communication quality on each index. Accordingly, the present application provides a relationship diagram between the index interval and the incentive coefficient, and a relationship diagram between the overall completion amount of the antenna parameter combination on the index and the optimization efficiency of the index. Please refer to Figure 4 and Figure 5 .

[0129] First, please refer to Figure 4 . Figure 4 The present application provides a relationship diagram between the index interval and the incentive coefficient. As shown in Figure 4 , in the coordinate system in Figure 4 , the horizontal coordinate represents the completion amount of the antenna parameter combination on a certain index, and the vertical coordinate represents the incentive coefficient corresponding to each interval of the index. It should be understood that for different indexes, the intervals corresponding to the index and the incentive coefficient can be different. In order to facilitate the reader to understand, the present embodiment takes the index as the first index, and the intervals and the incentive coefficients corresponding to the first index are all three.

[0130] In Figure 4 , the intervals corresponding to the first index are divided into [0, T1], [T1, T2] and [T2, 100], wherein T2 is the expectation of the user on the index, and "100" is the completion amount corresponding to the optimal value that the index can actually reach. Correspondingly, the incentive coefficient corresponding to the interval [0, T1] is the first incentive coefficient, and the value is 10; the incentive coefficient corresponding to the interval [T1, T2] is the second incentive coefficient, and the value is 1; the incentive coefficient corresponding to the interval [T2, 100] is the third incentive coefficient, and the value is 0; in an optional mode, the incentive coefficient corresponding to the interval [T2, 100] can also be the fourth incentive coefficient, and the value is -1. When calculating the incentive value of each antenna parameter combination on the first index, only the completion amount of each antenna parameter combination on the index and the three intervals [0, T1], [T1, T2] and [T2, 100] and the three incentive coefficients corresponding to the intervals need to be calculated. For details, please refer to the foregoing description, which will not be repeated here.

[0131] Thus, when selecting the parent particle of the next iteration from each generation of particles, when the completion amount of the particles in the particle population of this generation on the first index is far from T2 (for example, the completion amount is less than T1), then when selecting the particle with the greater value from the particle population, since the incentive coefficient corresponding to the interval [0, T1] is greater, the completion amount of the selected particle on the first index is also greater, so as to complete the accelerated optimization of the first index. Similarly, when the completion amount of most of the particles in the particle population of this generation on the first index has reached T2, then when selecting the particle with the greater value from the particle population, since the incentive coefficient corresponding to the interval [T2, 100] is 0 or negative, the selected particle will not be a particle that has completed too much on the first index, and will not be selected as the parent particle of the next generation, so as to inhibit the continuous optimization of the subsequent generations on the first index, and in exchange for the optimization of the subsequent generated antenna parameter combinations on other indexes.

[0132] Figure 5 A diagram of the relationship between the overall completion amount of an antenna parameter combination on an index and the optimization efficiency of the index. As shown in Figure 5 , in the coordinate system of Figure 5 , the horizontal coordinate represents the iteration number of the particle population, and the vertical coordinate represents the overall completion amount of the particle population on a certain index. The overall completion amount can be the average of the completion amounts of all particles in the particle population of each generation on the index. Specifically, Figure 5 , the first index and the second index in may be the first index and the second index described in the foregoing description.

[0133] Figure 5 In Figure 5It can be seen that before the total completion amount is less than 95, with the increase of the iteration number of the total particle population (i.e., the evolution of the genetic algorithm), the total completion amount of the particle population of each generation on the first index and the second index is gradually improved, but after the total completion amount reaches 95, with the increase of the iteration number of the total particle population, the total completion amount of the particle population of each generation on the index tends to be stable or slightly decreased. Moreover, in the offspring corresponding to the t1-t2 segment in the figure, the total completion amount of the particles in the particle population on the first index is far from the user expectation, the incentive coefficient of the index in this interval is large, and the optimization rate (i.e., the growth rate of the total completion amount) of the particle population of each generation on the first index is extremely fast; however, in the offspring corresponding to the t2-t3 segment, the total completion amount of the particles in the particle population on the first index is close to the user expectation, although the total completion amount of the particle population of each generation on the first index is also continuously increasing, the optimization rate is obviously reduced compared with the optimization rate in the offspring corresponding to the t1-t2 segment; until the total completion amount of the total particle population in the offspring corresponding to the t3-t4 segment has reached the user demand, the total completion amount of the particle population of each generation on the first index reaches the user expectation, the incentive coefficient in this interval segment is 0, and the total completion amount of the particle population of each generation on the index tends to be stable, and the optimization on the first index stops.

[0134] Similarly, referring to the curve corresponding to the second index in Figure 5 , the user expectation value of the second index is also 95. In the offspring corresponding to the t5-t6 segment, the total completion amount of the particles in the particle population on the first index has exceeded the user expectation, the total completion amount of the particle population of each generation on the first index is negatively increased, and the optimization rate is negative.

[0135] Next, the determination process of the above candidate antenna set is described in combination with the user intention. Please refer to Figure 6 .

[0136] Figure 6 The schematic diagram of the distribution of the particle population in the two-dimensional search space provided by the embodiments of the present application is shown. The two dimensions represented by the two-dimensional search space can be the coverage rate and the rate in the aforementioned Q communication indexes. Now it is assumed that the user has only these two index aspects of the antenna signal, the optimal values of the two indexes are both 100, and Figure 6 The completion amounts of the particles 61, 62, 63 and 64 on the two indexes of coverage rate and rate are shown in Table 1:

[0137] Table 1

[0138] Particle 61 Particle 62 Particle 63 Particle 64 Coverage 86 87 92 91 Rate 70 90 50 51

[0139] And the user intentions of the user 1, the user 2, the user 3 and the user 4 on the above two indexes are as follows:

[0140] User intention ①: the optimization degree of coverage rate is prioritized, and the user's requirement for coverage rate is not less than 90.

[0141] Therefore, for user requirement ①, the multiple intervals corresponding to coverage rate can be set as [0, 90] and [90, 100], and the corresponding incentive coefficients can be 100 and 0, respectively; the multiple intervals corresponding to rate can be set as [0, 90] and [90, 100], and the corresponding incentive coefficients can be 1 and 0, respectively. Based on the foregoing description, the value Pl of particle 61 w61 = 86 x 100 + 70 x 1 = 8670 (here, it is assumed that the multi-objective weights corresponding to the two indexes are both 1, and the same below); the value Pl of particle 62 w62 = 87 x 100 + 90 x 1 = 8790; the value Pl of particle 63 w63 = 90 x 100 + 2 x 0 + 70 x 1 = 9050; the value Pl of particle 64 w64 = 90 x 100 + 1 x 0 + 51 x 1 = 9051; therefore, particle 64 is determined as a particle in the candidate antenna set.

[0142] User intention ②: the expected value of coverage rate is 90, but the deterioration is allowed, but the deterioration degree cannot exceed a lower limit (i.e., the completion amount of the antenna parameter combination in the offspring on coverage rate is less than the completion amount of the antenna parameter combination in the offspring on the above-mentioned first index, but the completion amount of the antenna parameter combination on the above-mentioned first index in each subsequent offspring cannot be less than a preset threshold, which is assumed to be 87), and the optimization degree of rate in the subsequent offspring is prioritized, and the user's requirement for rate is not less than 90.

[0143] Therefore, for user requirement ②, it is assumed that the completion amount of the particle with the maximum completion amount in the parent particles of particle 61-particle 64 on coverage rate is 88, then for the particle with the completion amount less than 87 on coverage rate, the value is negative infinity; for the particle with the completion amount not less than 87 on coverage rate, the multiple intervals corresponding to coverage rate can be set as [0, 90] and [90, 100], and the corresponding incentive coefficients can be 1 and 0, respectively. The multiple intervals corresponding to rate can be set as [0, 90] and [90, 100], and the corresponding incentive coefficients can be 10 and 0, respectively. Based on the foregoing description, the value P2 of particle 61 w61 = -∞; the value P2 of particle 62 w62 = 87 x 1 + 90 x 10 = 987; the value P2 of particle 63 w63 = 90 x 1 + 50 x 10 = 590; the value P2 of particle 64 w64= 90 x 1 + 51 x 10 = 600; then the particle 62 is determined as a particle in the candidate antenna set.

[0144] User intention ③: the expected value of coverage and rate is 90, and the optimization degree of rate in the subsequent offspring is focused on. And the user hopes to optimize both the rate and the coverage. When the completion amount of a certain index in the parent has reached the user's expectation of the index, the optimization degree of the index in the subsequent process can be reduced.

[0145] Then for user requirement ③, assuming that in the parent particles of particles 61-64, the completion amount of the particle with the largest completion amount in coverage is 88, and the completion amount of the particle with the largest completion amount in rate is 85. The multiple intervals of coverage can be set as [0, 88-2], [88-2, 90] and [90, 100], and the corresponding incentive coefficients can be 1, 10 and 0 respectively. The multiple intervals of rate can be set as [0, 85-2], [85-2, 90] and [90, 100], and the corresponding incentive coefficients can be 1, 10 and 0 respectively. Based on the foregoing description, it can be known that the value P3 of particle 61 w61 = 86 x 1 + 70 x 1 = 156; the value P3 of particle 62 w62 = 86 x 1 + 1 x 10 + 83 x 1 + 7 x 10 = 249; the value P3 of particle 63 w63 = 86 x 1 + 4 x 10 + 2 x 0 + 50 x 1 = 176; the value P3 of particle 64 w64 = 86 x 1 + 4 x 10 + 1 x 0 + 51 x 1 = 177; then the particle 64 is determined as a particle in the candidate antenna set.

[0146] User intention ④: the value of the antenna parameter combination used by the antenna can be maximum.

[0147] Then for user requirement ④, assuming that in the parent particles of particles 51-54, the completion amount of the particle with the largest completion amount in coverage is 88, and the completion amount of the particle with the largest completion amount in rate is 85. The multiple intervals of coverage can be set as [0, 88-2], [88-2, 100], and the corresponding incentive coefficients can be 1, 10 respectively. The multiple intervals of rate can be set as [0, 85-2], [85-2, 100], and the corresponding incentive coefficients can be 1, 10 respectively. Based on the foregoing description, it can be known that the value P4 of particle 61 w61 = 86 x 1 + 70 x 1 = 156; the value P4 of particle 62 w62 = 86 x 1 + 1 x 10 + 83 x 1 + 7 x 10 = 249; the value P4 of particle 63 w63 = 86 x 1 + 6 x 10 + 50 x 1 = 196; the value P4 of particle 64w64 =86×1+5×10+51×1=187; therefore, particle 63 is determined to be a particle in the candidate antenna set.

[0148] This method, by setting the excitation ranges for various communication indicators of the cell antenna and the excitation coefficients for each indicator under different excitation ranges according to user needs, can more quickly and efficiently obtain antenna parameter combinations that match the user's actual needs from each generation of offspring, thus improving the speed of determining antenna parameter combinations. For details, please refer to [link / reference]. Figure 7 and Figure 8 .

[0149] Figure 7 This is a graph illustrating the relationship between the number of particle iterations and the degree of index optimization, provided as an embodiment of this application. Figure 6 As shown, Figure 7 In the coordinate system, the horizontal axis represents the completion amount of the antenna parameter combination in terms of coverage, and the vertical axis represents the completion amount of the antenna parameter combination in terms of data rate. Curve 701 represents the completion amount of each antenna parameter combination in terms of coverage and data rate obtained after 500 iterations using the traditional Pareto dominance sorting method. Curves 702, 703, and 704 represent the completion amounts of each antenna parameter combination in terms of coverage and data rate obtained after 50, 150, and 500 iterations respectively using the antenna parameter combination determination method provided in this application. Overall, it can be seen that, with the same number of iterations, the antenna parameter combination determination method provided in this application can obtain better antenna parameter combinations. Accordingly, Figure 8 A graph showing the relationship between the number of particle iterations and the degree of coverage optimization is provided. Figure 7 In the coordinate system, the horizontal axis represents the number of iterations for the particles, and the vertical axis represents the completion amount of the antenna parameter combination in terms of coverage. Curve 801 shows the relationship between the coverage completion amount of each antenna parameter combination obtained by iteration using the traditional Pareto dominance sorting method and the number of iterations; curve 802 shows the relationship between the coverage completion amount of each antenna parameter combination obtained by iteration using the antenna parameter combination determination method provided in this application and the number of iterations. Similarly, it can be seen from the overall perspective that, with the same number of iterations, the antenna parameter combination determination method provided in this application can obtain a better antenna parameter combination.

[0150] The following is a schematic diagram of the structure of an antenna parameter combination determination device provided in an embodiment of this application. Please refer to [link / reference]. Figure 9 . Figure 9 The device for determining the combination of antenna parameters in the middle can perform Figure 2 The flowchart for determining the combination of antenna parameters can also be executed. Figure 3 The process of determining the candidate parameter set, such as...Figure 9 The apparatus can include, as shown:

[0151] The computing unit 901 is configured to obtain a value of each of N sets of antenna parameter combinations, wherein the value of a first set of antenna parameter combinations in the N sets of antenna parameter combinations represents a degree of adaptation of the first set of antenna parameter combinations to user demand; the determining unit 902 is configured to determine M sets of antenna parameter combinations with greater values in the N sets of antenna parameter combinations as a candidate set of antenna parameters, wherein M is less than N, M is an integer greater than 0, and N is an integer greater than 1; the genetic unit 903 is configured to determine a target set of antenna parameters by taking a set of antenna parameters in the candidate set of antenna parameters as a parent, wherein the target set of antenna parameters is used for antenna signal transmission.

[0152] In an optional implementation, the computing unit 901 is specifically configured to: obtain P incentive values of the first set of antenna parameter combinations on P communication indexes, wherein an incentive value of the first set of antenna parameter combinations on a first index in the P communication indexes is determined by a completed amount of the first set of antenna parameter combinations on the first index, and Q intervals of the first index and Q incentive coefficients corresponding to the Q intervals, the completed amount representing a degree of quality of communication quality of a signal transmitted by the antenna using the first set of parameters on the first index, and P and Q are integers greater than 1; and obtain the value of the first set of antenna parameter combinations according to the P incentive values of the first set of antenna parameter combinations on the P communication indexes.

[0153] In an optional implementation, the apparatus further includes: an obtaining unit 904 configured to obtain a first parameter and a second parameter, wherein the first parameter includes a target threshold of each of the P communication indexes, and the second parameter includes a weight of each of the P communication indexes, and P is an integer greater than 1; and the first parameter and the second parameter are used to determine the Q intervals of the first index and the Q incentive coefficients corresponding to the Q intervals, respectively.

[0154] In an optional implementation, the Q intervals of the first index include a first interval and a second interval, a right end point value of the first interval is less than or equal to a left end point value of the second interval, an incentive coefficient corresponding to the second interval is a second incentive coefficient, an incentive coefficient corresponding to the first interval is a first incentive coefficient, and the second incentive coefficient is less than the first incentive coefficient.

[0155] In an optional implementation, the left end point value of the second interval is the completed amount of the first set of antenna parameter combinations on the first index, and the completed amount represents a degree of quality of communication quality of a signal transmitted by the antenna using the first set of parameters on the first index.

[0156] In an optional implementation, the second incentive coefficient is less than or equal to 0.

[0157] In an optional implementation, the determining unit 902 is specifically configured to: take the top M antenna parameter combinations in the N groups of antenna parameter combinations as the candidate antenna parameter set.

[0158] It should be understood that the division of each unit of the above antenna parameter combination determining apparatus is merely a logical division of functions, and in actual implementation, all or part of the units can be integrated into one physical entity, or can be physically separated. For example, each unit can be a separately established processing element, or can be integrated into one chip, and in addition, each unit can be stored in the form of program code in a storage element of a controller and called and executed by a processing element of a processor. In addition, each unit can be integrated together or implemented independently. The processing element herein can be an integrated circuit chip having a signal processing capability. In the implementation process, each step of the method or each unit can be completed by an integrated logic circuit of hardware or an instruction in the form of software in the processor element. The processing element can be a general-purpose processor, such as a CPU, and can also be one or more integrated circuits configured to implement the above method, such as one or more application-specific integrated circuits (ASICs), or one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs), etc.

[0159] Figure 10 A structural schematic diagram of an electronic device provided by an embodiment of the present application is shown in FIG. 1. As shown in the figure, the electronic device 100 includes a processor 1001, a memory 1002, and a communication interface 1003; the processor 1001, the memory 1002, and the communication interface 1003 are connected to each other through a bus. The electronic device can be the antenna parameter combination determining apparatus described in the foregoing description. Figure 10

[0160] ​The memory 1002 includes, but is not limited to, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), or a compact disc read-only memory (CDROM), which is used to store relevant instructions and data. The communication interface 1003 is used to receive and send data, which can be implemented by a transceiver, a network interface card, a modem, or the like. Figure 9 The processor 1001 can be one or more central processing units (CPUs), which can be a single-core CPU or a multi-core CPU in the case of the processor 1001 being a CPU. The steps performed by the determination apparatus of the antenna parameter combination in the above embodiments can be based on the processor 1001.

[0161] The processor 1001 can be one or more central processing units (CPUs), which can be a single-core CPU or a multi-core CPU in the case of the processor 1001 being a CPU. The steps performed by the determination apparatus of the antenna parameter combination in the above embodiments can be based on the processor 1001. Figure 10 The processor 1001 can be one or more central processing units (CPUs), which can be a single-core CPU or a multi-core CPU in the case of the processor 1001 being a CPU. The steps performed by the determination apparatus of the antenna parameter combination in the above embodiments can be based on the processor 1001. Figure 9 The processor 1001 can be one or more central processing units (CPUs), which can be a single-core CPU or a multi-core CPU in the case of the processor 1001 being a CPU. The steps performed by the determination apparatus of the antenna parameter combination in the above embodiments can be based on the processor 1001.

[0162] The processor 1001 in the electronic device 100 is configured to read program codes stored in the memory 1002, and execute the antenna parameter combination determination method in the above embodiments.

[0163] In the embodiments of the present application, another computer readable storage medium is provided, which stores a computer program. When the computer program is executed by a processor, the following steps are implemented: obtaining a value of each antenna parameter combination in N groups of antenna parameter combinations, the value of a first antenna parameter combination in the N groups of antenna parameter combinations representing an adaptation degree of the first antenna parameter combination to user demand; taking M groups of antenna parameter combinations with larger values in the N groups of antenna parameter combinations as a candidate antenna parameter set, the M being smaller than the N, the M being an integer greater than 0, and the N being an integer greater than 1; and determining a target antenna parameter combination by taking an antenna parameter combination in the candidate antenna parameter set as a parent, the target antenna parameter combination being used for antenna signal emission.

[0164] The embodiments of the present application further provide a computer program product containing instructions, which, when running on a computer, causes the computer to execute the antenna parameter combination determination method provided in the above embodiments.

[0165] In the present application, the word "exemplary" or "for example" is used to mean "an example of" or "an example, only. Any embodiment or design solution described as "exemplary" or "for example" in the present application should not be construed as preferred or advantageous over other embodiments or design solutions. In fact, the use of the word "exemplary" or "for example" is intended to present concepts in a concrete manner.

[0166] In the present application, "at least one" refers to one or more, and "multiple" refers to two or more. "At least one of the following (one)" or the like refers to any combination of the items, including any combination of single or multiple items. For example, at least one of a, b, or c can mean a, b, c, (a and b), (a and c), (b and c), or (a and b and c), where a, b, and c can be single or multiple. "And / or" describes the relationship between the associated objects, which means that there can be three relationships, for example, A and / or B, which can mean that A exists alone, A and B exist together, and B exists alone, where A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects.

[0167] In addition, unless otherwise stated, the ordinal numbers "first", "second", etc. used in the embodiments of the present application are used to distinguish multiple objects, and are not used to limit the order, time sequence, priority or importance of the multiple objects. For example, the first device and the second device are only for ease of description, and do not mean that the structures, importance, etc. of the first device and the second device are different. In some embodiments, the first device and the second device can also be the same device.

[0168] In the above embodiments, according to the context, the term "when" can be interpreted as meaning "if", "after", "in response to determining", or "in response to detecting". The above is only an optional embodiment of the present application, and is not used to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the concept and principle of the present application shall be included in the protection scope of the present application. Those skilled in the art can understand that all or part of the steps of the above embodiments can be completed by hardware, or by a program instructing relevant hardware, and the program can be stored in a computer readable storage medium, which can be a read-only memory, a magnetic disk or an optical disk, etc.

Claims

1. A method for determining antenna parameter combinations, characterized in that, include: Obtain the value of each antenna parameter combination in N groups of antenna parameter combinations. The value of the first antenna parameter combination in the N groups of antenna parameter combinations represents the degree of adaptation of the first antenna parameter combination to user needs. The M antenna parameter combinations with higher value among the N antenna parameter combinations are selected as the candidate antenna parameter set, where M is less than N, M is an integer greater than 0, and N is an integer greater than 1. The antenna parameter combinations in the candidate antenna parameter set are used as the parent to determine the target antenna parameter combination, which is used for antenna transmission signals.

2. The method according to claim 1, characterized in that, The process of obtaining the value of each antenna parameter combination in the N sets of antenna parameter combinations includes: The first antenna parameter combination is obtained as P excitation values ​​on P communication indicators. The excitation value of the first antenna parameter combination on the first indicator among the P communication indicators is determined by the completion amount of the first antenna parameter combination on the first indicator, Q intervals of the first indicator and Q excitation coefficients corresponding to the Q intervals. The completion amount characterizes the quality of communication of the signal transmitted by the antenna using the first antenna parameter combination on the first indicator. P and Q are integers greater than 1. The value of the first antenna parameter combination is obtained based on the P excitation values ​​of the P communication indicators.

3. The method according to claim 2, before obtaining the P excitation values ​​of the first antenna parameter combination on the P communication indicators, the method further includes: Get the first parameter and the second parameter; The first parameter includes the target threshold of each of the P communication indicators, and the second parameter includes the weight of each of the P communication indicators, where P is an integer greater than 1; the first parameter and the second parameter are used to determine Q intervals of the first indicator, and Q incentive coefficients corresponding to the Q intervals respectively.

4. The method according to claim 2 or 3, characterized in that, The first indicator has Q intervals, including a first interval and a second interval. The right endpoint of the first interval is less than or equal to the left endpoint of the second interval. The incentive coefficient corresponding to the second interval is the second incentive coefficient, and the incentive coefficient corresponding to the first interval is the first incentive coefficient. The second incentive coefficient is less than the first incentive coefficient.

5. The method according to claim 4, characterized in that, The left endpoint value of the second interval is the completion amount of the first antenna parameter combination on the first index. The completion amount characterizes the communication quality of the signal transmitted by the antenna using the first antenna parameter combination on the first index.

6. The method according to claim 4, characterized in that, The second excitation coefficient is less than or equal to 0.

7. The method according to any one of claims 1-3, characterized in that, The step of selecting the M antenna parameter combinations with higher value from the N antenna parameter combinations as the candidate antenna parameter set includes: The top M antenna parameter combinations with the highest value among the N sets of antenna parameter combinations are selected as the candidate antenna parameter set.

8. A device for determining antenna parameter combinations, characterized in that, include: The calculation unit is used to obtain the value of each antenna parameter combination in N groups of antenna parameter combinations, wherein the value of the first antenna parameter combination in the N groups of antenna parameter combinations represents the degree of adaptation of the first antenna parameter combination to user needs. The determining unit is used to select the M antenna parameter combinations with higher value from the N antenna parameter combinations as the candidate antenna parameter set, where M is less than N, M is an integer greater than 0, and N is an integer greater than 1. A genetic unit is used to determine a target antenna parameter combination by using the antenna parameter combinations in the candidate antenna parameter set as the parent, and the target antenna parameter combination is used for antenna transmission signals.

9. The apparatus according to claim 8, characterized in that, The computing unit is specifically used for: The first antenna parameter combination is obtained as P excitation values ​​on P communication indicators. The excitation value of the first antenna parameter combination on the first indicator among the P communication indicators is determined by the completion amount of the first antenna parameter combination on the first indicator, Q intervals of the first indicator and Q excitation coefficients corresponding to the Q intervals. The completion amount characterizes the quality of communication of the signal transmitted by the antenna using the first antenna parameter combination on the first indicator. P and Q are integers greater than 1. The value of the first antenna parameter combination is obtained based on the P excitation values ​​of the P communication indicators.

10. The apparatus according to claim 9, characterized in that, The device further includes: The acquisition unit is used to acquire a first parameter and a second parameter; the first parameter includes the target threshold of each of the P communication indicators, and the second parameter includes the weight of each of the P communication indicators, where P is an integer greater than 1; the first parameter and the second parameter are used to determine Q intervals of the first indicator, and Q incentive coefficients corresponding to the Q intervals respectively.

11. The apparatus according to claim 9 or 10, characterized in that, The first indicator has Q intervals, including a first interval and a second interval. The right endpoint of the first interval is less than or equal to the left endpoint of the second interval. The incentive coefficient corresponding to the second interval is the second incentive coefficient. The incentive value of the first interval is the first incentive coefficient. The second incentive coefficient is less than the first incentive coefficient.

12. The apparatus according to claim 11, characterized in that, The left endpoint value of the second interval is the completion amount of the first antenna parameter combination on the first index. The completion amount characterizes the communication quality of the signal transmitted by the antenna using the first antenna parameter combination on the first index.

13. The apparatus according to claim 11, characterized in that, The second excitation coefficient is less than or equal to 0.

14. The apparatus according to any one of claims 8-10, characterized in that, The determining unit is specifically used for: The top M antenna parameter combinations with the highest value among the N sets of antenna parameter combinations are selected as the candidate antenna parameter set.

15. An electronic device, characterized in that, include: Memory, used to store programs; A processor for executing the program stored in the memory, wherein when the program is executed, the processor is configured to perform the method as described in any one of claims 1 to 7.

16. A computer-readable storage medium, characterized in that, The computer storage medium stores a computer program, the computer program including program instructions, which, when executed by a processor, cause the processor to perform the method as described in any one of claims 1 to 7.

17. A computer program product, characterized in that, Includes program instructions that, when executed by a processor, cause the processor to perform the method as described in any one of claims 1 to 7.

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