Communication comb interference resource allocation method and system based on intelligent optimization algorithm

Abstract

The present invention discloses a method and system for allocating communication comb interference resources based on an intelligent optimization algorithm. The method comprises: constructing a population based on a preset population size parameter, randomly initializing the frequency intervals of the population to obtain a population frequency interval allocation matrix; calculating the maximum interference bandwidth of each jammer based on the frequency interval allocation matrix and a preset maximum number of jammer frequencies to generate an interference bandwidth allocation matrix for the population; utilizing a first iterative algorithm to obtain the optimal starting frequency allocation strategy for each individual in the population, utilizing a second iterative algorithm to mutate the frequency interval allocation strategy for each individual in the population; and obtaining the population and the optimal individual in the population at the time of iteration termination after a preset maximum number of iterations. The present invention implements interference resource allocation based on a hierarchical structure combining the first iterative algorithm and the second iterative algorithm, effectively improving the interference resource allocation effect and the interference rate of the interference resource allocation result on communication comb interference.

Description

Technical Field

[0001] The present invention relates to the field of communication interference technology, and in particular to a communication comb interference resource allocation method and system based on an intelligent optimization algorithm. Background Art

[0002] In communication, frequency hopping is one of the most important anti-interference methods. The interference against frequency hopping communication mainly adopts blocking interference, tracking interference and multi-frequency continuous wave interference [1]. Blocking interference refers to the interference method that can cover all or part of the frequency hopping communication frequency. Blocking interference can be divided into broadband blocking interference, partial frequency band blocking interference and comb blocking interference. Broadband blocking interference refers to the seamless suppression interference of the detected frequency hopping full band or larger frequency band. Broadband blocking interference is simple to implement, but the disadvantage is that it requires a large amount of interference resources and is easy to interfere with one's own communication. Partial blocking interference and broadband interference have the same principle, the difference is that it only concentrates interference on part of the frequency band, which is easier to implement than broadband blocking interference. Comb blocking interference needs to select a suitable frequency hopping interval and starting frequency based on the obtained frequency hopping communication band. Different selection strategies will lead to different interference efficiency. At present, most researchers [2][3] mainly start from the perspective of interference style, interference target and interference power, and optimize the interference parameters in the established specific communication countermeasure model to obtain the optimal interference efficiency.

[0003] The interference spectrum is a mixture of multiple frequency hopping and fixed frequencies. Comb-blocking jamming is a common jamming method. For wider spectrums, multiple jammers are required to perform simultaneous jamming. When multiple jammers use comb jamming, the combination of different starting frequencies, frequency intervals, and interference bandwidths affects the final interference rate on the mixed spectrum. Using an exhaustive approach is very time-consuming. Summary of the Invention

[0004] In response to the problems existing in the above-mentioned prior art, the present invention provides a communication comb interference resource allocation method and system based on an intelligent optimization algorithm. The first iterative algorithm is used to iteratively optimize the starting frequency allocation method, and the second iterative algorithm is used to iteratively optimize the frequency point interval allocation method, thereby effectively improving the interference resource allocation effect and the interference rate of the interference resource allocation result on the communication comb interference.

[0005] On the one hand, the present invention provides a method for allocating communication comb interference resources based on an intelligent optimization algorithm, comprising:

[0006] (1) constructing a population based on preset population size parameters, wherein each individual in the population represents an interference resource allocation strategy for all jammers to be assigned, and the interference resource allocation strategy includes a starting frequency, a frequency interval, and an interference bandwidth;

[0007] (2) Randomly initialize the frequency intervals of the population to obtain the population frequency interval allocation matrix;

[0008] (3) Based on the frequency interval allocation matrix and the preset maximum frequency number of the jammer, the maximum interference bandwidth of each jammer is calculated to generate the interference bandwidth allocation matrix of the population, and the allocated frequency number of each jammer in the population is obtained;

[0009] (4) using the first iterative algorithm to obtain the optimal allocation strategy of the starting frequency of each individual in the population, and using the second iterative algorithm to mutate the frequency interval allocation strategy of each individual in the population;

[0010] (5) Based on the mutated population frequency interval allocation matrix, repeat steps (3) and (4) until the number of repetitions reaches the preset maximum number of iterations, and obtain the population at the time of iteration stop and the optimal individual in the population.

[0011] In some embodiments, the optimal individual in the population is the individual with the largest interference rate of the target interference frequency, and the interference rate of the target interference frequency of the individual is: the ratio of the number of target interference frequencies among the frequencies formed by all jammers of the individual to the total number of target interference frequencies.

[0012] In some embodiments, the first iterative algorithm in (4) adopts a greedy algorithm, and (4) specifically includes the following steps:

[0013] (41) The number of jammers to be assigned is T. For the i-th jammer among the T jammers of the current individual in the population, the target jamming frequency rate of the i-th jammer is obtained when the starting frequency is assigned to each candidate frequency point among all candidate frequency points, and the starting frequency when the target jamming frequency rate is the largest is obtained, i = 1, 2, ..., T;

[0014] (42) Taking the starting frequency when the current individual i-th jammer obtains the maximum target jamming frequency interference rate as the optimal starting frequency of the current individual i-th jammer, obtain the target jamming frequency interference rate of the current individual;

[0015] (43) The interference rate of the target interference frequency point of the current individual is greater than the historical optimal value α of the interference rate of the target interference frequency point of the current individual best When the current individual target interference frequency interference rate historical optimal value α is updated and saved best , and update and save the current individual historical optimal value α best Interference resource allocation strategy under ;

[0016] (44) Using the second iterative algorithm, the frequency interval allocation strategy of the T jammers in the current individual is mutated;

[0017] (45) Execute the above steps (41)-(44) for the next individual in the population until the last individual in the population completes the execution of steps (41)-(44), and obtain the frequency point interval allocation matrix and the starting frequency allocation matrix after the mutation of all individuals in the population at the current iteration number.

[0018] In some embodiments, the (41) comprises:

[0019] (411) Obtain all target interference frequencies to be interfered with;

[0020] (412) All target interference frequency points occupy the frequency band R with the minimum frequency interval f Δ Divide and obtain the N of the frequency band occupied by all target interference frequencies R quantized sub-frequency points;

[0021] (413) Get the target interference frequency at N R The position of the quantized sub-frequency points, for N R quantized sub-frequency points, if there is a target interference frequency point on the quantized sub-frequency point, then the quantized sub-frequency point is marked as a first mark, otherwise, the quantized sub-frequency point is marked as a second mark, and the index set F of the target interference frequency point is obtained. index , the index set F index Including N R A set of elements, each element has the value of the first tag or the second tag;

[0022] (414) Based on N R quantized sub-frequency points to obtain all candidate frequency points of the starting frequency, and obtain the target interference frequency interference rate of the i-th jammer obtained by combining the frequency point interval and interference bandwidth allocation result of the i-th jammer at the current number of iterations when the starting frequency of the i-th jammer is set as each candidate frequency point;

[0023] (415) Obtain a candidate frequency point used as the starting frequency when the i-th jammer obtains the maximum target jamming frequency interference rate.

[0024] In some embodiments, the N-based R All candidate frequency points of the starting frequency are obtained by quantizing sub-frequency points, including: R A preset number m of quantized sub-frequency points among the quantized sub-frequency points are used as candidate frequency points of the starting frequency.

[0025] In some embodiments, the method for obtaining the interference rate of the target interference frequency of the jammer includes:

[0026] Based on the starting frequency point of the i-th jammer and all subsequent interval frequency points in the index set F index Find the corresponding position point in the index set F indexWhen the corresponding position point is the first mark (1), the corresponding position point value is modified to the third mark (2), and in the index set F index When the corresponding position point is the second mark (0), the corresponding position point value is marked as the fourth mark (-1), and the number of times the corresponding position point value is modified to the third mark is obtained. According to the number of times the value is modified to the third mark and the original index set F index The ratio of the number of first marks in determines the frequency interference rate of the i-th jammer.

[0027] In some embodiments, the second iterative algorithm adopts an evolutionary algorithm, and the (44) includes:

[0028] Randomly select the mth jammer from all the jammers of the current individual and s Randomly select a frequency interval from the frequency interval types and assign it to the jammer m;

[0029] At the same time, the frequency interval of the mod(n+m, T)th jammer among the current individual T jammers is used as the frequency interval of the nth jammer among the current individual T jammers, where n=1, 2, ..., T.

[0030] On the other hand, the present invention provides a communication comb interference resource allocation system based on an intelligent optimization algorithm, comprising:

[0031] A population establishment unit is used to establish a population based on preset population size parameters, wherein each individual in the population represents an interference resource allocation strategy for all jammers to be allocated, and the interference resource allocation strategy includes a starting frequency, a frequency interval, and an interference bandwidth;

[0032] A frequency interval allocation strategy initialization unit is used to randomly initialize the frequency intervals of the population to obtain a population frequency interval allocation matrix;

[0033] An interference bandwidth strategy generating unit is used to calculate the maximum interference bandwidth of each jammer based on the frequency interval allocation matrix and the preset maximum frequency number of the jammer, generate the interference bandwidth allocation matrix of the population, and obtain the allocated frequency number of each jammer in the population;

[0034] A first iterative calculation unit is used to obtain the optimal starting frequency allocation strategy of each individual in the population using a first iterative algorithm, and to mutate the frequency point interval allocation strategy of each individual in the population using a second iterative algorithm;

[0035] The second iterative calculation unit is used to repeatedly execute the interference bandwidth strategy generation unit and the first iterative calculation unit based on the mutated population frequency interval allocation matrix until the number of repetitions reaches a preset maximum number of iterations, and obtain the population when the iteration stops and the optimal individual in the population.

[0036] In some embodiments, the first iterative algorithm in the first iterative calculation unit adopts a greedy algorithm.

[0037] In some embodiments, the optimal individual in the population is the individual with the largest interference rate of the target interference frequency, and the interference rate of the target interference frequency of the individual is: the ratio of the number of target interference frequencies among the frequencies formed by all jammers of the individual to the total number of target interference frequencies.

[0038] The present invention provides a method and system for allocating comb-type interference resources for communication based on an intelligent optimization algorithm, achieving the following beneficial effects: utilizing a first iterative algorithm to search for the optimal starting frequency allocation strategy for each individual, and utilizing a second iterative algorithm to mutate the frequency spacing allocation strategy for each individual in the population. This achieves interference resource allocation based on a hierarchical structure combining the first and second iterative algorithms. The first iterative algorithm iteratively optimizes the starting frequency allocation strategy, and the second iterative algorithm iteratively optimizes the frequency spacing allocation strategy, effectively improving the effectiveness of interference resource allocation and the interference rate of the interference resource allocation results on comb-type interference. The second iterative algorithm optimizes the frequency spacing. When the frequency spacing is fixed, the maximum bandwidth is selected based on the constraint relationship between the frequency spacing and the interference bandwidth. The first iterative algorithm is then used to search for the starting frequencies of multiple jammers. This method significantly improves the interference rate compared to manual methods and significantly reduces the computational effort compared to exhaustive methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a flow chart of a method for allocating communication comb interference resources according to an embodiment of the present application;

[0040] Figure 2 Flowcharts of the first and second iterative algorithms of the communication comb interference resource allocation method according to an embodiment of the present application;

[0041] Figure 3 This is a flow chart of a method for obtaining the optimal starting frequency of the i-th jammer in an embodiment of the present application;

[0042] Figure 4 is a flow chart of the second iterative algorithm of the embodiment of the present application;

[0043] Figure 5 This is a structural diagram of a communication comb interference resource allocation system according to an embodiment of the present application;

[0044] Figure 6 2. It is a schematic diagram showing the comparison results between the method of the embodiment of the present application and the manual method;

[0045] Figure 7 2 is a schematic diagram showing the comparison results between the method of the embodiment of the present application and the method based on the greedy strategy. DETAILED DESCRIPTION

[0046] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limiting the present invention. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0047] The embodiment of the present application provides a method for allocating communication comb interference resources based on an intelligent optimization algorithm, including:

[0048] (1) constructing a population based on preset population size parameters, wherein each individual in the population represents an interference resource allocation strategy for all jammers to be assigned, and the interference resource allocation strategy includes a starting frequency, a frequency interval, and an interference bandwidth;

[0049] (2) Randomly initialize the frequency intervals of the population to obtain the population frequency interval allocation matrix;

[0050] (3) Based on the frequency interval allocation matrix and the preset maximum frequency number of the jammer, the maximum interference bandwidth of each jammer is calculated to generate the interference bandwidth allocation matrix of the population, and the allocated frequency number of each jammer in the population is obtained;

[0051] (4) using the first iterative algorithm to obtain the optimal allocation strategy of the starting frequency of each individual in the population, and using the second iterative algorithm to mutate the frequency interval allocation strategy of each individual in the population;

[0052] (5) Based on the mutated population frequency interval allocation matrix, repeat steps (3) and (4) until the number of repetitions reaches the preset maximum number of iterations, and obtain the population at the time of iteration stop and the optimal individual in the population.

[0053] In the embodiment of the present application, it is assumed that the population size parameter is N gene , the number of jammers to be assigned is T, then the frequency interval assignment matrix is N gene A matrix of rows and columns,

[0054]

[0055] where r i,j ∈[1,N s ],i=1,2,...,N gene , j=1,2,...,T,N s The number of allocable frequency interval types;

[0056] The above calculation is based on the frequency interval allocation matrix and the preset maximum frequency number of the jammer to calculate the maximum interference bandwidth of each jammer, that is, the preset maximum frequency number of the jammer is recorded as K max, then the frequency interval allocation parameter r of the jammer can be obtained in the frequency interval allocation matrix i,j , then the maximum interference bandwidth of the jammer is b max (i,j)=r i,j *K max , the maximum interference bandwidth of the jammer is used as the interference bandwidth allocation parameter of the jammer to form the interference bandwidth allocation matrix of the population, based on N i,j =floor(B i,j / r i,j ) to obtain the number of allocated frequencies for each jammer, and floor(x) means rounding x.

[0057] In the above (4), the first iterative algorithm is used to search for the optimal allocation strategy of the starting frequency for each individual, and the second iterative algorithm is used to mutate the frequency interval allocation strategy of each individual in the population. Specifically, the first iterative algorithm is used to obtain the optimal allocation strategy of the starting frequency for the first individual in the population, and the second iterative algorithm is used to mutate the frequency interval allocation strategy. Then, the first iterative algorithm is used to obtain the optimal allocation strategy of the starting frequency for the second individual in the population, and the second iterative algorithm is used to mutate the frequency interval allocation strategy. ..., for the Nth individual in the population, the optimal allocation strategy of the starting frequency is obtained. gene After each individual uses the first iterative algorithm to obtain the optimal allocation strategy for the starting frequency, the second iterative algorithm is used to mutate the frequency interval allocation strategy, and then the above step (5) is entered, realizing the interference resource allocation based on the hierarchical structure of the combination of the first iterative algorithm and the second iterative algorithm. The first iterative algorithm is used to iteratively optimize the starting frequency allocation method, and the second iterative algorithm is used to iteratively optimize the frequency interval allocation method, effectively improving the interference resource allocation effect and the interference rate of the interference resource allocation result on the communication comb interference.

[0058] In the above step (5), the optimal individual in the population is the individual with the largest interference rate of the target interference frequency point, and the interference rate of the target interference frequency point of the individual is: the ratio of the number of target interference frequency points among the frequency points formed by all the jammers of the individual to the total number of target interference frequency points.

[0059] Specifically, based on the starting frequency, frequency interval, and interference bandwidth allocation results of each jammer in the individual under the interference resource allocation strategy, the frequency formed by each jammer of the individual and the frequency formed by all jammers of the individual can be obtained. It can be understood that the ratio of the intersection of the frequency formed by all jammers of the individual and the target interference frequency set to the total number of target interference frequencies in the target interference frequency set is the target interference frequency interference rate of the individual. Correspondingly, the target interference frequency interference rate of a single jammer is: the ratio of the number of target interference frequencies among the frequency points formed by a single jammer under its starting frequency, frequency interval, and interference bandwidth parameters to the total number of target interference frequencies.

[0060] In one embodiment, the above step (4) uses a first iterative algorithm to obtain the optimal starting frequency allocation strategy for each individual in the population, and uses a second iterative algorithm to mutate the frequency point interval allocation strategy for each individual in the population, wherein the first iterative algorithm adopts a greedy algorithm. The step (4) specifically includes the following steps:

[0061] (41) Let the number of jammers to be assigned be T. For the i-th jammer among the T jammers of the current individual in the population, obtain the target jamming frequency interference rate of the i-th jammer when the starting frequency is assigned to each candidate frequency point among all candidate frequency points, and obtain the starting frequency when the target jamming frequency interference rate is the largest, i = 1, 2, ..., T; wherein the target jamming frequency interference rate is determined based on the jammer's starting frequency, frequency interval, interference bandwidth, and target jamming frequency set;

[0062] (42) Taking the starting frequency when the current individual i-th jammer obtains the maximum target jamming frequency interference rate as the optimal starting frequency of the current individual i-th jammer, obtain the target jamming frequency interference rate of the current individual;

[0063] (43) The interference rate of the target interference frequency point of the current individual is greater than the historical optimal value α of the interference rate of the target interference frequency point of the current individual best When the current individual target interference frequency interference rate historical optimal value α is updated and saved best , and update and save the current individual historical optimal value α best The interference resource allocation strategy under , including the starting frequency, frequency interval, and interference bandwidth allocation strategy of each jammer in the current individual;

[0064] (44) Using the second iterative algorithm, the frequency interval allocation strategy of the T jammers in the current individual is mutated;

[0065] (45) Execute the above steps (41)-(44) for the next individual in the population until the last individual in the population completes the execution of steps (41)-(44), and obtain the frequency point interval allocation matrix and the starting frequency allocation matrix after the mutation of all individuals in the population at the current iteration number.

[0066] In the embodiment of the present application, the starting frequency allocation strategy for the individual is obtained by iteratively adopting a greedy algorithm. The starting frequency of a single jammer in the individual is successively allocated to multiple candidate frequency points and the target interference frequency interference rate of the jammer is calculated. The optimal starting frequency configuration of a single jammer is determined, and then the optimal starting frequency configuration is analyzed and determined for the next jammer, thereby achieving the optimal starting frequency configuration of all jammers in the current individual, and then obtaining the target interference frequency interference rate of the current individual. When the target interference frequency interference rate of the current individual is greater than the historical optimal value, the target interference frequency interference rate historical optimal value of the current individual and the corresponding interference resource allocation strategy under the historical optimal value are updated. When searching for the optimal starting frequency, the optimal solution should exhaustively enumerate T! (factorial) combinations. Only one combination is required using the greedy strategy, which reduces the amount of calculation. In addition, in the embodiment of the present application, after executing the first iterative algorithm to obtain the optimal starting frequency configuration of the individual, the second iterative algorithm is then executed on the individual to mutate the frequency interval allocation strategy of the individual, and then the first iterative algorithm and the second iterative algorithm execution process of the next individual are performed.

[0067] In one embodiment, the above (41) obtains the target interference frequency interference rate of the i-th interferer when the starting frequency is respectively assigned to each candidate frequency point among all candidate frequency points for the i-th interferer among the T interferers of the current individual in the population, and obtains the starting frequency when the interference rate of the target interference frequency point is maximum, including:

[0068] (411) Obtain all target interference frequencies to be interfered with;

[0069] (412) All target interference frequency points occupy the frequency band R with the minimum frequency interval f Δ Divide and obtain the N of the frequency band occupied by all target interference frequencies R quantized sub-frequency points;

[0070] (413) Get the target interference frequency at N R The position of the quantized sub-frequency points, for N R quantized sub-frequency points, if there is a target interference frequency point on the quantized sub-frequency point, then the quantized sub-frequency point is marked as a first mark, otherwise, the quantized sub-frequency point is marked as a second mark, and the index set F of the target interference frequency point is obtained. index , the index set F index Including N R A set of elements, each element has a value of a first tag or a second tag. In one embodiment, the first tag has a value of 1 and the second tag has a value of 0;

[0071] (414) Based on N Rquantized sub-frequency points to obtain all candidate frequency points of the starting frequency, and obtain the target interference frequency interference rate of the i-th jammer obtained by combining the frequency point interval and interference bandwidth allocation result of the i-th jammer at the current number of iterations when the starting frequency of the i-th jammer is set as each candidate frequency point;

[0072] (415) Obtain a candidate frequency point used as the starting frequency when the i-th jammer obtains the maximum target jamming frequency interference rate.

[0073] In the embodiment of the present application, the frequency band R occupied by all target interference frequencies is quantized and all target interference frequencies are calculated as index positions in the quantized sub-frequency set, so as to simplify the calculation of the starting frequency, frequency interval, interference bandwidth and interference rate of the subsequent jammer and improve the efficiency of communication comb interference resource allocation. Specifically, the frequency band R occupied by all target interference frequencies is quantized to obtain N R quantized sub-frequency points, then the target interference frequency point is in this N R The corresponding position can be found in each of the N quantized sub-frequency points, and the starting frequency and subsequent interval frequency allocated by the jammer can also be found in the N R The corresponding position can be found in each quantized sub-frequency point. For example:

[0074] Assume that the target interference frequency set to be interfered is: N invest is the number of target interference frequencies; the frequency band can be expressed as:

[0075] Use the minimum frequency interval f for the frequency band R Δ Quantify it into R c , assuming R c The number of intermediate frequency points is N R , whose frequency set is:

[0076]

[0077] Assumption F invest The target interference frequency is at R c The middle position is:

[0078]

[0079] Using R c The index value in represents the frequency set F invest for: in,

[0080]

[0081] In one embodiment, the above-mentioned N-based RAll candidate frequency points of the starting frequency are obtained by quantizing sub-frequency points, including: R The preset number m of quantized sub-frequency points among the quantized sub-frequency points is used as the candidate frequency points of the starting frequency. R The first N quantized sub-frequency points R -1 quantized sub-frequency point is used as a candidate frequency point for the starting frequency.

[0082] Furthermore, the above step (414) includes:

[0083] Assign the starting frequency of the i-th jammer to N R The first quantized sub-frequency point in the quantized sub-frequency points is used to obtain the frequency interference rate of the i-th jammer based on the frequency interval and the number of frequencies of the i-th jammer;

[0084] Assign the starting frequency of the i-th jammer to N R The first quantized sub-frequency point in the quantized sub-frequency points is used to obtain the frequency interference rate of the i-th jammer based on the frequency interval and the number of frequencies of the i-th jammer;

[0085] And so on, until the starting frequency of the i-th jammer is assigned to the quantized sub-frequency position corresponding to the preset maximum starting frequency, and the frequency interference rate of the i-th jammer is obtained;

[0086] Get the starting frequency setting parameters when the interference rate of the target frequency point of the i-th jammer is maximum.

[0087] In one embodiment, the method for obtaining the interference rate of the target interference frequency of the jammer includes:

[0088] Based on the starting frequency point of the i-th jammer and all subsequent interval frequency points in the index set F index Find the corresponding position point in the index set F index When the corresponding position point is the first mark (1), the corresponding position point value is modified to the third mark (2), and in the index set F index When the corresponding position point is the second mark (0), the corresponding position point value is marked as the fourth mark (-1), and the number of times the corresponding position point value is modified to the third mark is obtained. According to the number of times the value is modified to the third mark and the original index set F index The ratio of the number of first marks in determines the frequency interference rate of the i-th jammer.

[0089] Then, when calculating the interference rate of the individual target interference frequency point, it is only necessary to calculate the starting frequency points of all jammers and all subsequent interval frequency points in the index set F index The corresponding position point is found in the data and the mark of the corresponding position point is modified to the third mark or the fourth mark. Then, the interference rate of the individual target interference frequency point is calculated based on the total number of the third marks.

[0090] In one embodiment, the second iterative algorithm adopts an evolutionary algorithm, and the (44) uses the second iterative algorithm to mutate the frequency interval allocation strategy of the T jammers in the current individual, including:

[0091] (441) Randomly select the mth jammer from all jammers of the current individual and s Randomly select a frequency interval from the frequency interval types and assign it to the jammer m;

[0092] (442) At the same time, the frequency interval of the mod(n+m, T)th jammer among the current individual T jammers is used as the frequency interval of the nth jammer among the current individual T jammers, n=1, 2, ..., T.

[0093] Specifically, this step includes:

[0094] A number m is randomly generated between 1 and T, and the mth jammer is randomly selected from all the jammers of the current individual;

[0095] In 1 to N s A number is randomly generated between as the frequency interval of the mth jammer;

[0096] The frequency interval of the mod(n+m, T)th jammer among all jammers is used as the frequency interval of the nth jammer among the current individual T jammers, where n=1, 2, ..., T;

[0097] This step realizes the variation and replacement of the frequency intervals of all jammers in the current individual.

[0098] See also Figure 5 , an embodiment of the present application further provides a communication comb interference resource allocation system based on an intelligent optimization algorithm, the system comprising:

[0099] A population establishment unit 501 is configured to establish a population based on preset population size parameters, wherein each individual in the population represents an interference resource allocation strategy for all jammers to be allocated, and the interference resource allocation strategy includes a starting frequency, a frequency interval, and an interference bandwidth;

[0100] The frequency interval allocation strategy initialization unit 502 is used to randomly initialize the frequency intervals of the population to obtain a population frequency interval allocation matrix;

[0101] The interference bandwidth strategy generating unit 503 is configured to calculate the maximum interference bandwidth of each jammer based on the frequency interval allocation matrix and the preset maximum frequency number of the jammer, generate the interference bandwidth allocation matrix of the population, and obtain the allocated frequency number of each jammer in the population;

[0102] The first iterative calculation unit 504 is configured to obtain the optimal starting frequency allocation strategy for each individual in the population using the first iterative algorithm, and to mutate the frequency interval allocation strategy for each individual in the population using the second iterative algorithm;

[0103] The second iterative calculation unit 505 is used to repeatedly execute the interference bandwidth strategy generation unit and the first iterative calculation unit based on the mutated population frequency interval allocation matrix until the number of repetitions reaches a preset maximum number of iterations, and obtain the population and the optimal individual in the population when the iteration stops.

[0104] In one embodiment, the first iterative algorithm in the first iterative calculation unit adopts a greedy algorithm.

[0105] In one embodiment, in the above-mentioned second iterative calculation unit, the optimal individual in the population is the individual with the largest interference rate of the target interference frequency point, and the interference rate of the target interference frequency point of the individual is: the ratio of the number of target interference frequency points among the frequency points formed by all the jammers of the individual to the total number of target interference frequency points.

[0106] It should be noted that the communication comb interference resource allocation system based on the intelligent optimization algorithm provided in this embodiment only uses the division of the above-mentioned functional units as an example to illustrate the allocation of communication comb interference resources. In actual applications, the above-mentioned functional allocation can be completed by different functional units as needed, that is, the internal structure of the system can be divided into different functional units to complete all or part of the functions described above. In addition, the communication comb interference resource allocation system based on the intelligent optimization algorithm provided in this embodiment and the communication comb interference resource allocation method embodiment based on the intelligent optimization algorithm provided in the above embodiment belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0107] The following describes the implementation effect of the above-mentioned communication comb interference resource allocation method based on a simulation experiment. The comb interference resource allocation algorithm based on the first iterative algorithm and the second iterative algorithm is denoted as the algorithm of this paper.

[0108] The simulation experiments compare the proposed algorithm with the manual method and the greedy strategy method. The greedy strategy method is part of the proposed algorithm, and this part of the experiment mainly verifies the contribution of the greedy strategy to the interference rate of the proposed algorithm.

[0109] The manual method simulates the way humans directly allocate resources. In this article, the manual method is described as multiple jammers simultaneously using a single frequency interval, allocating resources sequentially from the beginning of the frequency band to ensure that each jammer's starting frequency is an effective interference point, and to achieve the optimal interference rate among different frequency intervals.

[0110] Compared with the algorithm in this paper, the greedy strategy-based method removes the evolutionary algorithm part and only retains the greedy strategy part. The frequency intervals of different jammers use fixed values.

[0111] Experimental data parameters: There are 1000 experimental samples in total, and each sample frequency set F invest Randomly generated, divided into 10 to 15 frequency bands, each band has 30 to 70 frequency points, and the interval between frequency points is randomly 1 to 7 times of f Δ , the sample data is concentrated in a bandwidth of 200MHz.

[0112] (1) Comparison between this algorithm and manual methods

[0113] In this algorithm, N gene =100, preset maximum number of iterations N loop =100, the number of frequency interval types N s =7, the interference bandwidth set is B s ={1MHZ, 2MHZ, ..., 10MHZ}, the maximum frequency of each jammer is K max = 60, and the number of jammers T = {4, 5, 6}. The manual method uses the same frequency spacing for all jammers, taking the optimal values for different frequency spacings. The remaining parameters are consistent with the proposed algorithm. Simulation results show that the proposed algorithm improves the jamming rate compared to the manual method. Table 1 compares the maximum and minimum jamming rates of the proposed algorithm and the manual method. This table shows that the proposed algorithm significantly improves the jamming rate compared to the manual method. Figure 6 This graph shows the relationship between the difference in interference rate between our algorithm and the manual method and the corresponding number of samples. The horizontal axis represents the difference in interference rate between our algorithm and the manual method, while the vertical axis represents the number of samples within the ±0.05% range of the horizontal axis, reflecting the probability density. It can be seen that the curves for different T values approximate a normal distribution, with most sample interference rate differences concentrated in the middle. As the number of jammers T increases, the curve shifts further to the right, indicating that as the number of jammers increases, the algorithm achieves a more significant improvement in interference rate compared to the manual method.

[0114] Table 1 Comparison of interference rates between the proposed algorithm and the manual method

[0115]

[0116] (2) Comparison between the proposed algorithm and the greedy strategy-based method

[0117] The algorithm in this paper includes the greedy strategy and the evolutionary algorithm. This experiment is designed to analyze the impact of the two methods on the algorithm in this paper. In the algorithm in this paper, the main function of the evolutionary algorithm is to optimize the frequency interval. Therefore, in the experiment, the frequency interval in the greedy strategy method is randomly generated, and the rest is consistent with the algorithm in this paper.gene =100, preset maximum number of iterations N loop =100, the number of frequency interval types N s =7, the interference bandwidth set is B s ={1MHZ, 2MHZ, ..., 10MHZ}, the maximum frequency of each jammer is K max =60, the number of jammers T = {4, 5, 6}.

[0118] Definition: The relative interference rate of interference rate α1 and interference rate α2 is:

[0119] The simulation results are as follows Figure 7 The horizontal axis represents the relative interference rate between the greedy strategy and our algorithm. The vertical axis represents the number of samples within the ±0.5% range of the horizontal axis, reflecting its probability density. The figure shows that the relative interference rates between the greedy strategy and our algorithm are mostly concentrated around 90%, indicating that the greedy strategy contributes significantly to our algorithm.

[0120] This paper addresses the inefficiency of manual comb-based blocking interference resource allocation in communication jamming. We propose a comb-based interference resource allocation algorithm based on both a first- and second-iterative algorithm. The first-iterative algorithm utilizes a greedy algorithm, while the second-iterative algorithm employs an evolutionary algorithm. The second-iterative algorithm optimizes the frequency spacing. Given a fixed frequency spacing, the maximum bandwidth is selected based on the relationship between the frequency spacing and the interference bandwidth. The first-iterative algorithm is then used to search for the starting frequencies of multiple jammers. This method significantly improves the jamming rate compared to manual methods and significantly reduces the computational effort compared to exhaustive methods.

[0121] The present invention is not limited to the above-mentioned specific implementation methods. Various changes made by ordinary technicians in this field based on the above-mentioned concept without creative work are all within the scope of protection of the present invention.

Claims

1. A communication comb interference resource allocation method based on an intelligent optimization algorithm, characterized in that: include: (1) constructing a population based on preset population size parameters, wherein each individual in the population represents an interference resource allocation strategy for all jammers to be assigned, and the interference resource allocation strategy includes a starting frequency, a frequency interval, and an interference bandwidth; (2) Randomly initialize the frequency intervals of the population to obtain the population frequency interval allocation matrix; (3) Based on the frequency interval allocation matrix and the preset maximum frequency number of the jammer, the maximum interference bandwidth of each jammer is calculated to generate the interference bandwidth allocation matrix of the population, and the allocated frequency number of each jammer in the population is obtained; (4) using the first iterative algorithm to obtain the optimal allocation strategy for the starting frequency of each individual in the population, and using the second iterative algorithm to mutate the frequency interval allocation strategy of each individual in the population; (5) Based on the mutated population frequency interval allocation matrix, repeat steps (3) and (4) until the number of repetitions reaches the preset maximum number of iterations, and obtain the population at the time of iteration stop and the optimal individual in the population; The first iterative algorithm in step (4) adopts a greedy algorithm, which specifically includes the following steps: (41) The number of jammers to be assigned is T. For the i-th jammer among the T jammers of the current individual in the population, the target jamming frequency rate of the i-th jammer is obtained when the starting frequency is assigned to each candidate frequency point among all candidate frequency points, and the starting frequency when the target jamming frequency rate is the largest is obtained, i = 1, 2, ..., T; (42) Taking the starting frequency when the current individual i-th jammer obtains the maximum target jamming frequency interference rate as the optimal starting frequency of the current individual i-th jammer, obtain the target jamming frequency interference rate of the current individual; (43) The interference rate of the target interference frequency point of the current individual is greater than the historical optimal value α of the interference rate of the target interference frequency point of the current individual best When the current individual target interference frequency interference rate historical optimal value α is updated and saved best , and update and save the current individual historical optimal value α best Interference resource allocation strategy under ; (44) Using the second iterative algorithm, the frequency interval allocation strategy of the T jammers in the current individual is mutated; (45) Execute the above steps (41) to (44) for the next individual in the population until the last individual in the population completes the execution of steps (41) to (44), and obtain the frequency interval allocation matrix and the starting frequency allocation matrix of all individuals in the population after mutation at the current iteration number; The step (41) comprises: (411) Obtain all target interference frequencies to be interfered with; (412) All target interference frequency points occupy the frequency band R with the minimum frequency interval f Δ Divide and obtain the frequency band occupied by all target interference frequency points N R quantized sub-frequency points; (413) Get the target interference frequency at N R The position of the quantized sub-frequency points, for N R quantized sub-frequency points, if there is a target interference frequency point on the quantized sub-frequency point, then the quantized sub-frequency point is marked as a first mark, otherwise, the quantized sub-frequency point is marked as a second mark, and the index set F of the target interference frequency point is obtained. index , the index set F index Including N R A set of elements, each element has the value of the first tag or the second tag; (414) Based on N R quantized sub-frequency points to obtain all candidate frequency points of the starting frequency, and obtain the target interference frequency interference rate of the i-th jammer obtained by combining the frequency point interval and interference bandwidth allocation result of the i-th jammer at the current number of iterations when the starting frequency of the i-th jammer is set as each candidate frequency point; (415) Obtain a candidate frequency point used as the starting frequency when the i-th jammer obtains the maximum target jamming frequency interference rate.

2. The communication comb interference resource allocation method based on the intelligent optimization algorithm according to claim 1 is characterized in that: The optimal individual in the population is the individual with the largest interference rate of the target interference frequency point, and the interference rate of the target interference frequency point of the individual is: the ratio of the number of target interference frequency points among the frequency points formed by all the jammers of the individual to the total number of target interference frequency points.

3. The communication comb interference resource allocation method based on intelligent optimization algorithm according to claim 2 is characterized in that: The N-based R All candidate frequency points of the starting frequency are obtained by quantizing sub-frequency points, including: R A preset number m of quantized sub-frequency points among the quantized sub-frequency points are used as candidate frequency points of the starting frequency.

4. The communication comb interference resource allocation method based on intelligent optimization algorithm according to claim 1 is characterized in that: The method for obtaining the target interference frequency interference rate of the jammer includes: Based on the starting frequency point of the i-th jammer and all subsequent interval frequency points in the index set F index Find the corresponding position point in the index set F index When the corresponding position point is the first mark (1), the corresponding position point value is modified to the third mark (2), and in the index set F index When the corresponding position point is the second mark (0), the corresponding position point value is marked as the fourth mark (-1), and the number of times the corresponding position point value is modified to the third mark is obtained. According to the number of times the value is modified to the third mark and the original index set F index The ratio of the number of first marks in determines the frequency interference rate of the i-th jammer.

5. The communication comb interference resource allocation method based on intelligent optimization algorithm according to claim 2 is characterized in that: The second iterative algorithm adopts an evolutionary algorithm, and the (44) includes: Randomly select the mth jammer from all the jammers of the current individual and s Randomly select a frequency interval from the frequency interval types and assign it to the jammer m; At the same time, the frequency interval of the mod(n+m, T)th jammer among the current individual T jammers is used as the frequency interval of the nth jammer among the current individual T jammers, where n=1, 2, ..., T.

6. A communication comb interference resource allocation system based on an intelligent optimization algorithm, characterized by: include: A population establishment unit is used to establish a population based on preset population size parameters, wherein each individual in the population represents an interference resource allocation strategy for all jammers to be allocated, and the interference resource allocation strategy includes a starting frequency, a frequency interval, and an interference bandwidth; A frequency interval allocation strategy initialization unit is used to randomly initialize the frequency intervals of the population to obtain a population frequency interval allocation matrix; An interference bandwidth strategy generating unit is used to calculate the maximum interference bandwidth of each jammer based on the frequency interval allocation matrix and the preset maximum frequency number of the jammer, generate the interference bandwidth allocation matrix of the population, and obtain the allocated frequency number of each jammer in the population; A first iterative calculation unit is used to obtain the optimal starting frequency allocation strategy of each individual in the population using a first iterative algorithm, and to mutate the frequency point interval allocation strategy of each individual in the population using a second iterative algorithm; A second iterative calculation unit is configured to repeatedly execute the interference bandwidth strategy generation unit and the first iterative calculation unit based on the mutated population frequency interval allocation matrix until the number of repetitions reaches a preset maximum number of iterations, and obtain the population and the optimal individual in the population when the iteration stops; The first iterative algorithm in the first iterative calculation unit adopts a greedy algorithm, which specifically includes the following steps: (41) The number of jammers to be assigned is T. For the i-th jammer among the T jammers of the current individual in the population, the target jamming frequency rate of the i-th jammer is obtained when the starting frequency is assigned to each candidate frequency point among all candidate frequency points, and the starting frequency when the target jamming frequency rate is the largest is obtained, i = 1, 2, ..., T; (42) Taking the starting frequency when the current individual i-th jammer obtains the maximum target jamming frequency interference rate as the optimal starting frequency of the current individual i-th jammer, obtain the target jamming frequency interference rate of the current individual; (43) The interference rate of the target interference frequency point of the current individual is greater than the historical optimal value α of the interference rate of the target interference frequency point of the current individual best When the current individual target interference frequency interference rate historical optimal value α is updated and saved best , and update and save the current individual historical optimal value α best Interference resource allocation strategy under ; (44) Using the second iterative algorithm, the frequency interval allocation strategy of the T jammers in the current individual is mutated; (45) Execute the above steps (41) to (44) for the next individual in the population until the last individual in the population completes the execution of steps (41) to (44), and obtain the frequency interval allocation matrix and the starting frequency allocation matrix of all individuals in the population after mutation at the current iteration number; The step (41) comprises: (411) Obtain all target interference frequencies to be interfered with; (412) All target interference frequency points occupy the frequency band R with the minimum frequency interval f Δ Divide and obtain the frequency band occupied by all target interference frequency points N R quantized sub-frequency points; (413) Get the target interference frequency at N R The position of the quantized sub-frequency points, for N R quantized sub-frequency points, if there is a target interference frequency point on the quantized sub-frequency point, then the quantized sub-frequency point is marked as a first mark, otherwise, the quantized sub-frequency point is marked as a second mark, and the index set F of the target interference frequency point is obtained. index , the index set F index Including N R A set of elements, each element has the value of the first tag or the second tag; (414) Based on N R quantized sub-frequency points to obtain all candidate frequency points of the starting frequency, and obtain the target interference frequency interference rate of the i-th jammer obtained by combining the frequency point interval and interference bandwidth allocation result of the i-th jammer at the current number of iterations when the starting frequency of the i-th jammer is set as each candidate frequency point; (415) Obtain a candidate frequency point used as the starting frequency when the i-th jammer obtains the maximum target jamming frequency interference rate.

7. The communication comb interference resource allocation system based on intelligent optimization algorithm according to claim 6, characterized in that: The optimal individual in the population is the individual with the largest interference rate of the target interference frequency point, and the interference rate of the target interference frequency point of the individual is: the ratio of the number of target interference frequency points among the frequency points formed by all the jammers of the individual to the total number of target interference frequency points.

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