Anti-interference decision-making method and system based on quantum circadian monkey mechanism

Abstract

The invention discloses an anti-interference decision-making method based on a quantum cirrus mechanism, and relates to the technical field of anti-interference decision-making. The method is technically characterized by comprising the following steps: constructing an anti-interference decision model, wherein the anti-interference decision model is a combination of a channel, a coding mode, a modulation mode and transmitting power of a communication party; setting a target function and a constraint condition based on the anti-interference decision model; and carrying out optimization solution on the target function by utilizing a quantum curtail mechanism to obtain an optimal combination of a channel, a coding mode, a modulation mode and transmitting power. The quantum curtail monkey mechanism effectively improves the problems that an original curtail monkey search mechanism is too slow in convergence speed and prone to falling into a local optimal solution due to too large search space when solving the high-dimensional discrete optimization problem, and breaks through the problem that the original curtail monkey search mechanism is difficult to process the coexistence of discrete optimization and continuous optimization. The quantum cirrus monkey mechanism provided by the invention has obvious superiority in the aspects of convergence speed, convergence precision and global optimal solution searching.

Description

Technical Field

[0001] The present invention relates to the field of anti-interference decision-making technology, and in particular to an anti-interference decision-making method and system based on a quantum capuchin mechanism. Background Art

[0002] Anti-interference decision-making methods play an important role in all areas of society, especially in national security. Anti-interference decision-making refers to the communication receiving end obtaining the electromagnetic interference environment and giving feedback to the sending end, making decisions based on the different electromagnetic environments, and selecting the optimal anti-interference strategy to achieve efficient and economical communication while ensuring the safe and reliable transmission of information. For both the communication party and the interference party, anti-interference decision-making is a game process between the two parties. Especially on the battlefield, the interference party does not know what frequency we will use to transmit signals, and most interference signals need to be generated for frequency. Different frequencies will also be interfered to varying degrees due to the occurrence of various situations such as adjacent channel interference, spectrum leakage and multipath effects. Moreover, the higher the transmission power, the better the coding method and modulation method, the more costly support is required. Therefore, the communication party can prepare several frequencies in advance at both ends of the transmitter and receiver for communication, and switch between the frequencies when interfered. If one frequency is affected by interference, it is converted to another frequency that is not interfered with for transmission, but the interference situation in the actual environment is more complicated. In the worst case, all prepared frequencies are affected, and only the frequency with the least impact can be selected for transmission. At the same time, the anti-interference performance can also be improved by adjusting the coding method, modulation method and transmission power. If we consider the possible information protracted war or limited resources in the future, and a series of situations that require economic costs, we can control the economic costs from three aspects: coding method, modulation method and transmission power. Therefore, it is of great significance to design an anti-interference decision-making method that controls economic costs through reasonable resource allocation decisions while meeting the requirements of information transmission rate, and maintains economical and highly reliable signal transmission under the harsh conditions of frequency selectability and multiple interferences at the receiving end.

[0003] After searching the existing literature, it was found that Ran Yu et al. proposed a cognitive anti-interference intelligent decision-making technology based on an improved artificial bee colony mechanism in the Journal of Signal Processing (2019, 35(2), 240-249). This method not only improves the artificial bee colony mechanism, but also uses the improved mechanism to improve the traditional anti-interference method, which improves its global optimization search capability and convergence speed to a certain extent, and makes the average convergence times less and the probability of the optimal solution higher. The intelligent decision-making method of this mechanism includes four aspects: channel, modulation mode, transmission power and interference suppression mode. It uses multi-channel to simulate multi-frequency situations, but there is only one type of interference in each channel, and the complexity is relatively high, so there is room for further discussion and improvement. J. Li et al. published "Satellite communication anti-jamming based on artificial bee colony blind source separation" at the 6th International Conference on Communication (2021, pp. 240-244). They proposed a method of using artificial bee colony optimization mechanism to study the blind source separation problem to conduct satellite communication anti-jamming research, which further solved the defects in spectrum efficiency and anti-jamming performance of the current satellite communication anti-jamming based on spread spectrum and filtering technology. The results showed that it can achieve data transmission under strong interference conditions, but it also only analyzed the situation of single interference and has a high complexity, and there is room for further discussion and improvement.

[0004] The results of existing literature retrieval show that most of the existing anti-interference decision-making methods deal with single-frequency single interference and do not consider economic costs, but the actual interference and game situations are more complicated. If a series of situations that require consideration of economic costs such as information protracted warfare or limited resources occur, economic costs are also one of the issues that must be considered. Summary of the invention

[0005] In view of the above problems, the present invention proposes an anti-interference decision-making method and system based on the quantum capuchin mechanism.

[0006] According to one aspect of the present invention, an anti-interference decision-making method based on a quantum capuchin mechanism is proposed, the method comprising:

[0007] Step 1: construct an anti-interference decision model, where the anti-interference decision model is a combination of the communication party's channel, coding mode, modulation mode and transmission power;

[0008] Step 2: setting the objective function and constraint conditions based on the anti-interference decision model;

[0009] Step 3: Use the quantum capuchin mechanism to optimize and solve the objective function to obtain the optimal combination of channel, coding method, modulation method and transmission power.

[0010] Furthermore, the objective function in step 2 is:

[0011] F(C n ,M f ,I q ,K l )=w1f ber +w2f s

[0012] Among them, C n Indicates the optional channel for the nth communication party; M f Indicates the optional modulation mode of the fth communication party; I q represents the optional transmission power of the qth communication party; K l Indicates the optional encoding method for the first communication party; represents the minimum normalized average bit error rate, E max is the maximum average bit error rate, E min is the minimum average bit error rate, E represents the average bit error rate; represents the minimum normalized transmit power, I max is the maximum transmit power, I min is the minimum transmission power; w1 and w2 are the user's expected parameters, w1+w2=1;

[0013] The constraints are:

[0014] Among them, f R =R b ×K l ×log2(M f ) represents the information transmission rate, R b It is the original uncoded information transmission rate set according to the actual environment during communication. Indicates the minimum information transmission rate required for communication based on the actual environment.

[0015] Furthermore, the specific steps of step three include:

[0016] Step 31: Initialize the quantum position in the quantum capuchin mechanism;

[0017] Step 32: Measure the initial quantum position of each quantum capuchin, set a fitness function with a penalty function and calculate the fitness values ​​of all initial quantum positions, and determine the local optimal measurement position and the global optimal measurement position;

[0018] Step 3. Different types of quantum capuchins update the corresponding measured positions of quantum rotation angles and quantum positions according to their respective update strategies.

[0019] Step 34: Convert the updated measurement position into a communication strategy, calculate the fitness value of each quantum capuchin's updated measurement position, and update the local optimal measurement position and the global optimal measurement position;

[0020] Step 35: determine whether the search mechanism has reached the maximum number of iterations, if so, output the global optimal measurement position; otherwise, return to step 33 to continue iterating;

[0021] Step 36: Convert the obtained global optimal measurement position into the corresponding channel, coding mode, modulation mode and transmission power according to the mapping rule of step 32 to obtain the optimal anti-interference decision combination.

[0022] Furthermore, the specific steps of step 31 include: assuming that there are H quantum capuchins, which are recorded as a quantum capuchin group, and H is an even number; the quantum position of each quantum capuchin has S dimensions, where S is the maximum dimension of the solution space, represents rounding up, N is the total number of channels available to the communication party, F is the total number of modulation methods available to the communication party, L is the total number of coding methods available to the communication party, and Q is the total number of transmission powers available to the communication party; the quantum position of the h-th quantum capuchin monkey of the t-th generation is in t is the number of iterations, h = 1, 2, ..., H, s = 1, 2, ..., S; in the first generation, let t = 1, and the dimensions of the quantum positions of the H quantum capuchins are set to Then the quantum position set of the entire quantum capuchin group of generation t is

[0023] Furthermore, the specific steps of step 32 include:

[0024] The measured position of the h-th quantum capuchin monkey of the t-th generation is obtained by measurement: The measurement equation for the s-dimensional quantum position of the h-th quantum capuchin monkey of the t-th generation is: in is a random number that follows a uniform distribution between [0,1]. Will According to the mapping rules, it is mapped to And substitute it into the anti-interference decision model, where the mapping rule is

[0025] and are the first The communication party can select the channel, The communication parties can select the modulation mode, Each communicating party can select the transmission power and Optional encoding methods for communication parties;

[0026] According to the constraints, the penalty function is set as Where ρ is the penalty coefficient; the fitness value of the h-th quantum capuchin monkey with penalty function in the t-th generation is calculated as:

[0027]

[0028] The measurement position with the best fitness value of the h-th quantum capuchin monkey up to the t-th generation is recorded as the local optimal measurement position The measurement position with the best fitness value of all quantum capuchins up to the tth generation is recorded as the global optimal measurement position

[0029] Furthermore, the specific steps of step three include:

[0030] According to the functions of the capuchins, the front of the quantum capuchin group The quantum capuchins always serve as quantum leader monkeys and quantum companion capuchins that go out to find food, recorded as the quantum leader monkey group, then the quantum position set of the t-th generation quantum leader monkey group is back The quantum capuchin monkeys always serve as quantum follower monkeys, recorded as quantum follower monkey group, then the quantum position set of the t-th generation quantum follower monkey group is

[0031] For the quantum leader monkey group, two selection probabilities ε1 and ε2 are set, and then a random number between [0,1] is generated that follows a uniform distribution in ε1∈[0,1],ε2∈[0,1],ε1+ε2∈[0,1];if Then define the t+1th generation The s-th dimension quantum rotation angle of the quantum leader monkey is in is the life exponential function, β0, β1 and β2 are fixed parameters of the life exponential function, is the sth dimension of the local optimal measurement position, is the sth dimension of the global optimal measurement position, s=1,2,…,S; if Then define the t+1th generation The s-th dimension quantum rotation angle of the quantum leader monkey is in is the sth dimension of the local optimal measurement position of the quantum leader monkey labeled u randomly selected from other quantum leader monkeys, s=1,2,…,S; if Then define the tth generation The measured position of the random orientation foraging that the quantum leader monkey will perform is Define the t+1th generation The s-th dimension quantum rotation angle of the quantum leader monkey is in For the tth generation The measurement equation for the sth dimension of the random orientation foraging measurement position that the quantum leader monkey is about to perform is: is a random number uniformly distributed between [0,1], δ is the random orientation foraging parameter, s=1,2,…,S;define the t+1th generation The evolution method of the s-dimensional quantum position of the quantum leader monkey is in is a random number that follows a uniform distribution between [0,1], and c1 represents the probability of a quantum bit mutating when the quantum rotation angle is 0, and its value is The constant between s=1,2,…,S; get the t+1th generation The quantum position of the quantum leader monkey is in Then the quantum position set of the updated t+1th generation quantum leader monkey group is

[0032] For the quantum monkey group, define the t+1th generation The rotation angle of the s-th dimension quantum of the monkey following the quantum is in For the tth generation The s-dimensional quantum rotation angle of the quantum leader monkey, For the tth generation The quantum follows the monkey's s-dimensional quantum rotation angle, is a random number that follows a uniform distribution between [0,1]. s=1,2,…,S. Define the t+1th generation The evolution method of the s-dimensional quantum position of the quantum following monkey is in is a random number that follows a uniform distribution between [0,1], and c2 represents the probability of a quantum bit mutating when the quantum rotation angle is 0, and its value is The constant between s=1,2,…,S; get the t+1th generation The quantum position of the monkey following is in Then the quantum position set of the t+1th generation quantum following monkey group after update is

[0033] Then the quantum position set of the entire quantum capuchin monkey group of the t+1th generation after the update is obtained as The measured position is obtained by measuring the s-dimensional quantum position of the h-th quantum capuchin monkey of the t+1th generation The measurement equation is Then the measured position of the hth quantum capuchin monkey in the t+1th generation after measurement is in is a random number that follows a uniform distribution between [0,1]. After measurement, the measurement positions of the t+1th generation of H quantum capuchins are obtained.

[0034] Furthermore, the specific steps of step three and step four include: after the quantum position of the h-th quantum capuchin monkey of the t+1th generation is measured, According to the mapping rules, it is mapped to And substitute it into the anti-interference decision model to calculate the fitness value with penalty function The measurement position with the best fitness value of the hth quantum capuchin monkey up to the t+1th generation is recorded as the local optimal measurement position The measurement position with the best fitness value of all quantum capuchins up to the t+1th generation is recorded as the global optimal measurement position

[0035] According to another aspect of the present invention, an anti-interference decision-making system based on a quantum capuchin mechanism is proposed, the system comprising:

[0036] A model building module, configured to build an anti-interference decision model, wherein the anti-interference decision model is a combination of a channel, a coding method, a modulation method, and a transmission power of a communication party;

[0037] An objective function design module, configured to set an objective function and constraints based on the anti-interference decision model;

[0038] The optimal decision-making solution module is configured to optimize and solve the objective function using the quantum capuchin mechanism to obtain the optimal combination of channel, coding method, modulation method and transmission power.

[0039] Furthermore, the objective function in the objective function design module is:

[0040] F(C n ,M f ,I q ,K l )=w1f ber+w2f s

[0041] Among them, C n Indicates the optional channel for the nth communication party; M f Indicates the optional modulation mode of the fth communication party; I q represents the optional transmission power of the qth communication party; K l Indicates the optional encoding method for the first communication party; represents the minimum normalized average bit error rate, E max is the maximum average bit error rate, E min is the minimum average bit error rate, E represents the average bit error rate; represents the minimum normalized transmit power, I max is the maximum transmit power, I min is the minimum transmission power; w1 and w2 are the user's expected parameters, w1+w2=1;

[0043] The constraints are: R ≥

[0044] Among them, f R =R b ×K l ×log2(M f ) represents the information transmission rate, R b It is the original uncoded information transmission rate set according to the actual environment during communication. Indicates the minimum information transmission rate required for communication based on the actual environment.

[0047] Furthermore, the step of optimizing and solving the objective function by using the quantum capuchin mechanism in the optimal decision-solving module to obtain the optimal combination of channel, coding mode, modulation mode and transmission power includes:

[0048] Step 31: Initialize the quantum position in the quantum capuchin mechanism;

[0049] Step 32: Measure the initial quantum position of each quantum capuchin, set a fitness function with a penalty function and calculate the fitness values ​​of all initial quantum positions, and determine the local optimal measurement position and the global optimal measurement position;

[0050] Step 3. Different types of quantum capuchins update the corresponding measured positions of quantum rotation angles and quantum positions according to their respective update strategies.

[0051] Step 34: Convert the updated measurement position into a communication strategy, calculate the fitness value of each quantum capuchin's updated measurement position, and update the local optimal measurement position and the global optimal measurement position;

[0052] Step 35: determine whether the search mechanism has reached the maximum number of iterations, if so, output the global optimal measurement position; otherwise, return to step 33 to continue iterating;

[0053] Step 36: Convert the obtained global optimal measurement position into the corresponding channel, coding mode, modulation mode and transmission power according to the mapping rule of step 32 to obtain the optimal anti-interference decision combination.

[0054] The beneficial technical effects of the present invention are:

[0055] In the face of meeting the information transmission rate requirements, the present invention controls economic costs through reasonable resource allocation decisions, and finds an optimal anti-interference decision, namely, the transmission frequency and transmission power, in the harsh conditions where the frequency is optional and the receiving end may be subject to multiple interferences, to ensure signal transmission in an economical and highly reliable manner. At the same time, in order to solve the problems of high complexity and large amount of calculation, the anti-interference decision is combined with an intelligent optimization mechanism to reduce complexity. Compared with the prior art, the advantages of the present invention are:

[0056] 1) The electromagnetic environment faced in the real environment is diverse. Different frequencies may be superimposed with multiple interferences due to adjacent channel interference, spectrum leakage, multipath effect and other different situations, and the interference power of each interference in each channel is also different. For both ends of the communication party, multiple frequencies can be set as options for signal transmission and reception. When interfered, the strategy can be quickly adjusted to convert to a frequency without interference or a frequency with less interference to ensure signal transmission. The present invention simulates a variety of electromagnetic environments, that is, there may be multiple interferences in one frequency and the power of each interference is different. In the face of meeting the information transmission rate requirements, the economic cost is controlled by making reasonable resource allocation decisions, and an optimal anti-interference strategy is found through the quantum capuchin mechanism to transmit signals in an economical and highly reliable manner.

[0057] 2) Compared with the original capuchin search mechanism, the quantum capuchin mechanism involved in the present invention effectively improves the problem that the original capuchin search mechanism is too slow to converge and easy to fall into the local optimal solution due to the large search space when solving high-dimensional discrete optimization problems, and breaks through the problem that the original capuchin search mechanism is difficult to handle the coexistence of discrete optimization and continuous optimization. It can be seen from the simulation results that the quantum capuchin mechanism has obvious advantages over the original capuchin search mechanism in terms of convergence speed, convergence accuracy and finding the global optimal solution. Compared with some classic group intelligence optimization mechanisms such as the improved particle swarm mechanism, the quantum capuchin mechanism improves the search efficiency and can find the global optimal solution with fewer iterations. It can be seen from the simulation results that the quantum capuchin mechanism is significantly better than the improved particle swarm mechanism in terms of convergence speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] The present invention can be better understood by referring to the description given below in conjunction with the accompanying drawings, which together with the following detailed description are included in this specification and form a part of this specification, and are used to further illustrate the preferred embodiments of the present invention and explain the principles and advantages of the present invention.

[0059] Figure 1 The present invention is a flowchart of an anti-interference decision-making method based on the quantum capuchin mechanism according to an embodiment of the present invention.

[0060] Figure 2 This is another flow chart of an anti-interference decision-making method based on the quantum capuchin mechanism described in an embodiment of the present invention.

[0061] Figure 3 This is an example diagram of convergence curves of various optimization methods when the user expectation is 0.6 and 0.4 in an embodiment of the present invention.

[0062] Figure 4 1 is an example diagram of convergence curves of various optimization methods when the user expectation is 0.5 and 0.5 in an embodiment of the present invention.

[0063] Figure 5 1 is an example diagram of convergence curves of various optimization methods when user expectations are 0.4 and 0.6 in an embodiment of the present invention. DETAILED DESCRIPTION

[0064] In order to enable those skilled in the art to better understand the scheme of the present invention, exemplary implementations or embodiments of the present invention will be described below in conjunction with the accompanying drawings. Obviously, the described implementations or embodiments are only implementations or embodiments of a part of the present invention, not all of them. Based on the implementations or embodiments of the present invention, all other implementations or embodiments obtained by ordinary technicians in the field without creative work should fall within the scope of protection of the present invention.

[0065] The present invention considers controlling economic costs through reasonable resource allocation decisions in the face of meeting the requirements of information transmission rate, focusing on the frequency selectability and the harsh situation where the receiving end may be subject to multiple interferences, finding an optimal anti-interference decision, and ensuring signal transmission in an economical and highly reliable manner, thereby designing an anti-interference decision method based on the quantum capuchin mechanism. The quantum optimization theory is used, and the new quantum rotation angle is used to combine the degree of change of the quantum rotation angle with the life exponential function of the capuchin search mechanism to achieve a balance between global and local searches, effectively improving the shortcomings of the existing capuchin search mechanism in dealing with high-dimensional discrete optimization problems, such as not only slow convergence speed and too large search space, but also easy to fall into the local optimal solution, breaking through the problem that the existing capuchin search mechanism cannot solve the simultaneous existence of discrete optimization and continuous optimization.

[0066] The embodiment of the present invention proposes an anti-interference decision-making method based on the quantum capuchin mechanism, such as Figures 1-2 As shown, the method includes:

[0067] Step 1: construct an anti-interference decision model, where the anti-interference decision model is a combination of the communication party's channel, coding mode, modulation mode and transmission power;

[0068] Step 2: setting the objective function and constraint conditions based on the anti-interference decision model;

[0069] Step 3: Use the quantum capuchin mechanism to optimize and solve the objective function to obtain the optimal combination of channel, coding method, modulation method and transmission power; specifically, including:

[0070] Step 31: Initialize the quantum position in the quantum capuchin mechanism;

[0071] Step 32: Measure the initial quantum position of each quantum capuchin, set a fitness function with a penalty function and calculate the fitness values ​​of all initial quantum positions, and determine the local optimal measurement position and the global optimal measurement position;

[0072] Step 3. Different types of quantum capuchins update the corresponding measured positions of quantum rotation angles and quantum positions according to their respective update strategies.

[0073] Step 34: Convert the updated measurement position into a communication strategy, calculate the fitness value of each quantum capuchin's updated measurement position, and update the local optimal measurement position and the global optimal measurement position;

[0074] Step 35: Determine whether the search mechanism has reached the maximum number of iterations. If so, output the global optimal measurement position; otherwise, return to step 33 to continue iterating.

[0075] Step 36: Convert the obtained global optimal measurement position into the corresponding channel, coding mode, modulation mode and transmission power according to the mapping rule of step 32 to obtain the optimal anti-interference decision combination.

[0076] The method starts from step 1. In step 1, an anti-interference decision model is constructed, and the anti-interference decision model is a combination of a channel, a coding method, a modulation method and a transmission power of a communication party.

[0077] According to an embodiment of the present invention, Figure 2 As shown in the figure, an intelligent anti-interference decision model is established to determine the key parameters of the quantum capuchin mechanism corresponding to the communication. Set the optional channel vector of the communication party to C = [C1, C2, ..., C N ], where N is the total number of optional channels for the communication parties, C nThe nth communication party selected for decision making can choose the channel, n = 1, 2, ..., N; the communication party can choose the modulation mode vector M = [M1, M2, ..., M F ], where F is the total number of modulation methods available to the communication parties, M f The fth communication party can choose the modulation mode for the decision, f = 1, 2, ..., F; the communication party can choose the coding mode vector K = [K1, K2, ..., K L ], where L is the total number of optional coding methods for the communication parties, K l The optional encoding mode of the lth communication party selected for the decision is l = 1, 2, ..., L; the optional transmission power vector of the communication party is I = [I1, I2, ..., I Q ], where Q is the total number of optional transmit powers of the communication parties, I q The qth communication party selected for the decision can choose the transmission power, q = 1, 2, ..., Q; the interference party can choose the interference signal vector Y = [Y1, Y2, ..., Y A ], where A is the total number of interference signals that can be selected by the interference party, Y a is the interference signal that the a-th interferer can select, a=1,2,…,A; the interference power vector that the interferer can select is J=[J1,J2,…,J B ], where B is the total interference power available to the interferer, J b The interference power of the bth interferer can be selected, b = 1, 2, …, B.

[0078] The probability of various interference signals appearing in the nth channel is in is the probability of occurrence of the ath interference signal of the interference party in the nth communication party's optional channel, n = 1, 2, ..., N. Then, a random number between [0, 1] that follows a uniform distribution is generated for each interference signal in the nth channel. in To generate a random number uniformly distributed between [0,1] for the a-th interference party's optional interference signal in the n-th communication party's optional channel, n = 1, 2, ..., N. Less than This means that there is Y in the nth channel a Interference, otherwise it does not exist, and each interference will randomly select the interference power J b Launch.

[0079] The intelligent anti-interference decision selection is divided into four aspects: channel vector C, coding mode vector K, modulation mode vector M and transmit power vector I. Different combinations of channels, coding modes, modulation modes and transmit powers can obtain different anti-interference strategies D. o =[C n ,M f,I q ,K l ], where o = 1, 2, ..., p, p = N × F × Q × ..., and the anti-interference decision set is D = {D1, D2, ..., D p}. The randomly generated information is encoded at a code rate K l Encode the information and modulate it in a modulation mode M f Modulate the signal and then transmit it with a power of I q Transmit to channel C n There are multiple interference signals in the channel and each interference signal has different interference power. After receiving the signal, the receiving end demodulates and decodes it and compares it with the original information to get the bit error rate E1. The bit error rates obtained by calculating multiple times under the same simulation conditions are recorded as E2, E3, ..., E m-1 and E m , the average bit error rate obtained by using the anti-interference method selected by the decision is recorded as This can reduce the chance of interference signals being too large or too small, and m is the number of calculations performed under the same simulation conditions.

[0080] Then, step 2 is performed, in which an objective function and constraint conditions are set based on the anti-interference decision model.

[0081] According to the embodiment of the present invention, starting from the communication system indicators, in order to achieve an economical and highly reliable transmission mode, the minimum normalized average bit error rate and the minimum normalized transmission power are used to set the objective function. The objective function is set as:

[0082] F(C n ,M f ,I q ,K l )=w1f ber +w2f s

[0083] in, is the minimum normalized average bit error rate obtained by using the anti-interference method selected by the decision, E max is the maximum average bit error rate, E min is the minimum average bit error rate, is the minimum normalized transmit power obtained by using the anti-interference method selected by the decision, I max is the maximum transmit power, I minis the minimum transmission power, w1 and w2 are the user expected parameters, w1+w2=1. Because the average bit error rate and transmission power have different sizes and units, they are normalized to unify the dimensions, so as to obtain a reasonable value to evaluate the quality of the strategy. The user expected parameter refers to the importance of the average bit error rate and transmission power that users can assign according to their own needs.

[0084] In the face of meeting the information transmission rate requirements, the economic cost is controlled through reasonable resource allocation decisions, so that it can be used in a series of situations where economic costs need to be considered, such as limited resources or information protracted warfare. Therefore, the constraints are set as follows:

[0085]

[0086] Among them, f R =R b ×K l ×log2(M f ) is the information transmission rate obtained after using the anti-interference method selected by the decision, R b It is the original uncoded information transmission rate set according to the actual environment during communication. It is the minimum information transmission rate required for communication based on the actual environment.

[0087] Then, step three is executed. In step three, the objective function is optimized and solved using the quantum capuchin mechanism to obtain the optimal combination of channel, coding method, modulation method and transmission power.

[0088] First, in step three one, the quantum positions in the quantum capuchin mechanism are initialized.

[0089] According to an embodiment of the present invention, it is assumed that there are H quantum capuchins, which are recorded as a quantum capuchin group, and H is an even number. The quantum position of each quantum capuchin has S dimensions, where S is the maximum dimension of the solution space. represents rounding up. Each quantum capuchin has its own quantum position, so the quantum position of the h-th quantum capuchin in the t-th generation is in t is the number of iterations, T is the maximum number of iterations, h = 1, 2, ..., H, s = 1, 2, ..., S. In the first generation, let t = 1, and the dimensions of the quantum positions of the H quantum capuchins are set to Then the quantum position set of the entire quantum capuchin group of generation t is

[0090] Then, in step three-two, the initial quantum position of each quantum capuchin is measured, a fitness function with penalty is set and the fitness values ​​of all initial positions are calculated to determine the local optimal measurement position and the global optimal measurement position.

[0091] According to an embodiment of the present invention, the measured position of the h-th quantum capuchin monkey of the t-th generation is obtained by measurement: The measurement equation for the s-dimensional quantum position of the h-th quantum capuchin monkey of the t-th generation is: in is a random number that follows a uniform distribution between [0,1]. h=1,2,…,H,s=1,2,…,S。 Mapping to anti-interference method according to mapping rules And substitute it into the anti-interference decision model, where the mapping rule is and are the first The communication party can select the channel, The communication parties can select the modulation mode, Each communicating party can select the transmission power and The communication parties can select the encoding method.

[0092] According to the constraints, the penalty function is set as Where ρ is the penalty coefficient.

[0093] Calculate the fitness value with penalty of the h-th quantum capuchin monkey in the t-th generation as:

[0094]

[0095] The measurement position with the best fitness value of the h-th quantum capuchin monkey up to the t-th generation is recorded as the local optimal measurement position The measurement position with the best fitness value of all quantum capuchins up to the tth generation is recorded as the global optimal measurement position

[0096] Then, in step three, different types of quantum capuchins update the corresponding measured positions of quantum rotation angles and quantum positions according to their respective update strategies.

[0097] According to an embodiment of the present invention, the front of the quantum capuchin group is divided according to the functions of the capuchin. The quantum capuchins always serve as quantum leader monkeys and quantum companion capuchins that go out to find food, recorded as the quantum leader monkey group, then the quantum position set of the t-th generation quantum leader monkey group is back The quantum capuchin monkeys always serve as quantum follower monkeys, recorded as quantum follower monkey group, then the quantum position set of the t-th generation quantum follower monkey group is

[0098] For the quantum leader monkey group, two selection probabilities ε1 and ε2 are set, and then a random number between [0,1] is generated that follows a uniform distribution in ε1∈[0,1],ε2∈[0,1],ε1+ε2∈[0,1]. If Then define the t+1th generation The s-th dimension quantum rotation angle of the quantum leader monkey is in is the life exponential function, β0, β1 and β2 are fixed parameters of the life exponential function, is the sth dimension of the local optimal measurement position, is the sth dimension of the global optimal measurement position, s=1,2,…,S; if Then define the t+1th generation The s-th dimension quantum rotation angle of the quantum leader monkey is in is the sth dimension of the local optimal measurement position of the quantum leader monkey labeled u randomly selected from other quantum leader monkeys, s=1,2,…,S; if Then define the tth generation The measured position of the random orientation foraging that the quantum leader monkey will perform is Define the t+1th generation The s-th dimension quantum rotation angle of the quantum leader monkey is in For the tth generation The measurement equation for the sth dimension of the random orientation foraging measurement position that the quantum leader monkey is about to perform is: is a random number uniformly distributed between [0,1], δ is the random orientation foraging parameter, s=1,2,…,S. Define the t+1th generation The evolution method of the s-dimensional quantum position of the quantum leader monkey is in is a random number that follows a uniform distribution between [0,1], and c1 represents the probability of a quantum bit mutating when the quantum rotation angle is 0, and its value is The constant between s=1,2,…,S. Get the t+1th generation The quantum position of the quantum leader monkey is in Then the quantum position set of the updated t+1th generation quantum leader monkey group is

[0099] For the quantum monkey group, define the t+1th generation The rotation angle of the s-th dimension quantum of the monkey following the quantum is in For the tth generation The s-dimensional quantum rotation angle of the quantum leader monkey, For the tth generation The quantum follows the monkey's s-dimensional quantum rotation angle, is a random number that follows a uniform distribution between [0,1]. s=1,2,…,S. Define the t+1th generation The evolution method of the s-dimensional quantum position of the quantum following monkey is in is a random number that follows a uniform distribution between [0,1], and c2 represents the probability of a quantum bit mutating when the quantum rotation angle is 0, and its value is The constant between s=1,2,…,S. Get the t+1th generation The quantum position of the monkey following is in Then the quantum position set of the t+1th generation quantum following monkey group after update is

[0100] Then the quantum position set of the entire quantum capuchin monkey group of the t+1th generation after the update is obtained as The measured position is obtained by measuring the s-dimensional quantum position of the h-th quantum capuchin monkey of the t+1th generation The measurement equation is Then the measured position of the hth quantum capuchin monkey in the t+1th generation after measurement is in is a random number that follows a uniform distribution between [0,1], h=1,2,…,H, s=1,2,…,S. After measurement, the measurement positions of the t+1th generation of H quantum capuchins are obtained.

[0101] Then, in steps three and four, the updated measurement positions are converted into communication strategies, the fitness value of the updated measurement positions of each quantum capuchin is calculated, and the local optimal measurement positions and the global optimal measurement positions are updated.

[0102] According to an embodiment of the present invention, after the quantum position of the hth quantum capuchin monkey of the t+1th generation is measured, Mapping to anti-interference method according to mapping rules And substitute it into the anti-interference decision model to calculate the fitness value with penalty Where h = 1, 2, ..., H. The measurement position with the best fitness value of the hth quantum capuchin monkey up to the t+1th generation is recorded as the local optimal measurement position The measurement position with the best fitness value of all quantum capuchins up to the t+1th generation is recorded as the global optimal measurement position

[0103] Then, in step 35, determine whether the search mechanism has reached the maximum number of iterations. If so, output the global optimal measurement position; otherwise, set t=t+1, return to step 33, and continue iterating.

[0104] Then, in step 36, the obtained global optimal measurement position is converted into the corresponding channel, coding mode, modulation mode and transmission power according to the mapping rule of step 32 to obtain the optimal anti-interference decision combination.

[0105] The technical effect of the present invention is further verified through experiments.

[0106] The anti-interference decision-making method of the quantum capuchin mechanism proposed in the present invention is abbreviated as QCapSA, and the search mechanisms used for comparison are the anti-interference decision-making method of the capuchin search mechanism and the anti-interference decision-making method of the improved particle swarm mechanism, which are abbreviated as CapSA and IPO-PSO respectively.

[0107] In order to comprehensively compare the performance of the three methods, QCapSA, CapSA and IPO-PSO are initialized in the same way and the same communication system parameters are set: R b =10 7 bit / s; N = 4; F = 4, respectively BPSK, QPSK, 16QAM and 64QAM; L = 4, respectively 1 encoding, i.e. no encoding, coding, Coding and Coding; Q = 64, transmit power range is -11dB to 20.5dB, resolution is 0.5dB; E max =0.5, E min =10 -6 ;I max =20.5,I min = -11; B = 10, the interference power range of the interferer is 21dB to 30dB, and the resolution is 1dB; A = 3, which are 50% partial band interference, 10% comb interference and 10% single-tone frequency sweep interference, and the probability of each interference appearing in each channel is

[0108] In QCapSA, we set S = 12 and penalty function ρ = 10. -7 , ε1=0.8,ε2=0.1,β0=2,β1=21,β2=2,δ=0.5. After observing the quantum capuchin, the first two dimensions correspond to the channel, "00" represents the first channel, "01" represents the second channel, "10" represents the third channel and "11" represents the fourth channel; the third and fourth dimensions represent the modulation mode, "00" represents BPSK, "01" represents QPSK, "10" represents 16QAM and "11" represents 64QAM; the fifth to tenth dimensions correspond to the transmission power, "000000" represents -11dB, "000001" represents -10.5dB, and so on until "111111" represents 20.5dB, corresponding to a resolution of 0.5dB; the last two dimensions represent the coding mode, "00" represents 1 coding, "01" represents Coding, "10" represents Coding and "11" represents Coding. The population size and maximum number of iterations of the three mechanisms are the same, H = 20 and T = 1000 respectively. The average fitness of 500 runs is taken to draw the fitness curve. For other relevant parameter settings of CapSA, see "A novel meta-heuristic search algorithm for solving optimization problems: capuchin search algorithm" published by Malik Braik et al. in "Neural Computing and Applications" (2021, Volume 33, pages 2515-2547). For other relevant parameter settings of IPO-PSO, see "Communication anti-interference decision engine based on initial population optimization particle swarm mechanism" published by Hui Xianyang et al. in "Communication Technology" (2015, Volume 48, No.7).

[0109] Figure 3-Figure 5 Examples of convergence curves of various optimization methods for different user expected parameters are given. It can be seen that QCapSA has obvious advantages over CapSA in terms of convergence speed, convergence accuracy and finding the global optimal solution. Although IPO-PSO can also find the global optimal solution in a larger number of simulation runs, it is obvious that its convergence speed is much weaker than that of QCapSA.

[0110] Another embodiment of the present invention provides an anti-interference decision-making system based on the quantum capuchin mechanism, the system comprising:

[0111] A model building module, configured to build an anti-interference decision model, wherein the anti-interference decision model is a combination of a channel, a coding method, a modulation method, and a transmission power of a communication party;

[0112] An objective function design module, configured to set an objective function and constraints based on the anti-interference decision model;

[0113] The optimal decision-making solution module is configured to optimize and solve the objective function using the quantum capuchin mechanism to obtain the optimal combination of channel, coding method, modulation method and transmission power.

[0114] In this embodiment, preferably, the objective function in the objective function design module is:

[0115] F(C n ,M f ,I q ,K l )=w1f ber +w2f s

[0116] Among them, C n Indicates the optional channel for the nth communication party; M f Indicates the optional modulation mode of the fth communication party; I q represents the optional transmission power of the qth communication party; K l Indicates the optional encoding method for the first communication party; represents the minimum normalized average bit error rate, E max is the maximum average bit error rate, E min is the minimum average bit error rate, E represents the average bit error rate; represents the minimum normalized transmit power, I max is the maximum transmit power, I min is the minimum transmission power; w1 and w2 are the user's expected parameters, w1+w2=1;

[0117] The constraints are:

[0118] Among them, f R =R b ×K l ×log2(M f ) represents the information transmission rate, R b It is the original uncoded information transmission rate set according to the actual environment during communication. Indicates the minimum information transmission rate required for communication based on the actual environment.

[0119] In this embodiment, preferably, the step of optimizing and solving the objective function by using the quantum capuchin mechanism in the optimal decision solving module to obtain the optimal combination of channel, coding mode, modulation mode and transmit power includes:

[0120] Step 31: Initialize the quantum position in the quantum capuchin mechanism;

[0121] Step 32: Measure the initial quantum position of each quantum capuchin, set a fitness function with a penalty function and calculate the fitness values ​​of all initial quantum positions, and determine the local optimal measurement position and the global optimal measurement position;

[0122] Step 3. Different types of quantum capuchins update the corresponding measured positions of quantum rotation angles and quantum positions according to their respective update strategies.

[0123] Step 34: Convert the updated measurement position into a communication strategy, calculate the fitness value of each quantum capuchin's updated measurement position, and update the local optimal measurement position and the global optimal measurement position;

[0124] Step 35: determine whether the search mechanism has reached the maximum number of iterations, if so, output the global optimal measurement position; otherwise, return to step 33 to continue iterating;

[0125] Step 36: Convert the obtained global optimal measurement position into the corresponding channel, coding mode, modulation mode and transmission power according to the mapping rule of step 32 to obtain the optimal anti-interference decision combination.

[0126] The function of the anti-interference decision-making system based on the quantum capuchin mechanism described in an embodiment of the present invention can be explained by the aforementioned anti-interference decision-making method based on the quantum capuchin mechanism. Therefore, for the part not described in detail in the system embodiment, please refer to the above method embodiment and will not be repeated here.

[0127] Although the present invention has been described according to a limited number of embodiments, it will be apparent to those skilled in the art, with the benefit of the above description, that other embodiments are contemplated within the scope of the invention thus described. The disclosure of the present invention is intended to be illustrative rather than restrictive of the scope of the invention, which is defined by the appended claims.

Claims

1. An anti-interference decision-making method based on quantum capuchin mechanism, characterized in that: include: Step 1: construct an anti-interference decision model, where the anti-interference decision model is a combination of the communication party's channel, coding mode, modulation mode and transmission power; Step 2: setting the objective function and constraint conditions based on the anti-interference decision model; Step 3: Use the quantum capuchin mechanism to optimize and solve the objective function to obtain the optimal combination of channel, coding method, modulation method and transmission power.

2. According to claim 1, the anti-interference decision-making method based on the quantum capuchin mechanism is characterized in that: The objective function in step 2 is: F(C n ,M f ,I q ,K l )=w1f ber +w2f s Among them, C n Indicates the optional channel for the nth communication party; M f Indicates the optional modulation mode of the fth communication party; I q K represents the optional transmission power of the qth communication party; l Indicates the optional encoding method for the first communication party; represents the minimum normalized average bit error rate, E max is the maximum average bit error rate, E min is the minimum average bit error rate, E represents the average bit error rate; represents the minimum normalized transmit power, I max is the maximum transmit power, I min is the minimum transmission power; w1 and w2 are the user's expected parameters, w1+w2=1; The constraints are: Among them, f R =R b ×K l ×log2(M f ) represents the information transmission rate, R b It is the original uncoded information transmission rate set according to the actual environment during communication. Indicates the minimum information transmission rate required for communication based on the actual environment.

3. The anti-interference decision-making method based on the quantum capuchin mechanism according to claim 2 is characterized in that: The specific steps of step three include: Step 31: Initialize the quantum position in the quantum capuchin mechanism; Step 32: Measure the initial quantum position of each quantum capuchin, set a fitness function with a penalty function and calculate the fitness values ​​of all initial quantum positions, and determine the local optimal measurement position and the global optimal measurement position; Step 3. Different types of quantum capuchins update the corresponding measured positions of quantum rotation angles and quantum positions according to their respective update strategies. Step 34: Convert the updated measurement position into a communication strategy, calculate the fitness value of each quantum capuchin's updated measurement position, and update the local optimal measurement position and the global optimal measurement position; Step 35: determine whether the search mechanism has reached the maximum number of iterations, if so, output the global optimal measurement position; otherwise, return to step 33 to continue iterating; Step 36: Convert the obtained global optimal measurement position into the corresponding channel, coding mode, modulation mode and transmission power according to the mapping rule of step 32 to obtain the optimal anti-interference decision combination.

4. The anti-interference decision-making method based on the quantum capuchin mechanism according to claim 3 is characterized in that: The specific steps of step 31 include: assuming that there are H quantum capuchins, recorded as a quantum capuchin group, H is an even number; the quantum position of each quantum capuchin has S dimensions, where S is the maximum dimension of the solution space, represents rounding up, N is the total number of channels available to the communication party, F is the total number of modulation methods available to the communication party, L is the total number of coding methods available to the communication party, and Q is the total number of transmission powers available to the communication party; the quantum position of the h-th quantum capuchin monkey of the t-th generation is in t is the number of iterations, h = 1, 2, L, H, s = 1, 2, L, S; in the first generation, t = 1, and the dimensions of the quantum positions of the H quantum capuchins are set to Then the quantum position set of the entire quantum capuchin group of generation t is 5. The anti-interference decision-making method based on the quantum capuchin mechanism according to claim 4 is characterized in that: The specific steps of step 32 include: The measured position of the h-th quantum capuchin monkey of the t-th generation is obtained by measurement: The measurement equation for the s-dimensional quantum position of the h-th quantum capuchin monkey of the t-th generation is: in is a random number that follows a uniform distribution between [0,1]. Will According to the mapping rules, it is mapped to And substitute it into the anti-interference decision model, where the mapping rule is and are the first The communication party can select the channel, The communication parties can select the modulation mode, Each communicating party can select the transmission power and Optional encoding methods for communication parties; According to the constraints, the penalty function is set as Where ρ is the penalty coefficient; the fitness value of the h-th quantum capuchin monkey with penalty function in the t-th generation is calculated as: The measurement position with the best fitness value of the h-th quantum capuchin monkey up to the t-th generation is recorded as the local optimal measurement position The measurement position with the best fitness value of all quantum capuchins up to the tth generation is recorded as the global optimal measurement position 6. The anti-interference decision-making method based on the quantum capuchin mechanism according to claim 5 is characterized in that: The specific steps of step three include: According to the functions of the capuchins, the front of the quantum capuchin group The quantum capuchins always serve as quantum leader monkeys and quantum companion capuchins that go out to find food, recorded as the quantum leader monkey group, then the quantum position set of the t-th generation quantum leader monkey group is back The quantum capuchin monkeys always serve as quantum follower monkeys, recorded as quantum follower monkey group, then the quantum position set of the t-th generation quantum follower monkey group is For the quantum leader monkey group, two selection probabilities ε1 and ε2 are set, and then a random number between [0,1] is generated that follows a uniform distribution in ε1∈[0,1],ε2∈[0,1],ε1+ε2∈[0,1];if Then define the t+1th generation The s-th dimension quantum rotation angle of the quantum leader monkey is in is the life exponential function, β0, β1 and β2 are fixed parameters of the life exponential function, is the sth dimension of the local optimal measurement position, is the sth dimension of the global optimal measurement position, s=1,2,L,S; if Then define the t+1th generation The s-th dimension quantum rotation angle of the quantum leader monkey is in is the sth dimension of the local optimal measurement position of the quantum leader monkey labeled u randomly selected from other quantum leader monkeys, s=1,2,L,S; if Then define the tth generation The measured position of the random orientation foraging that the quantum leader monkey will perform is Define the t+1th generation The s-th dimension quantum rotation angle of the quantum leader monkey is in For the tth generation The measurement equation for the sth dimension of the random orientation foraging measurement position that the quantum leader monkey is about to perform is: is a random number uniformly distributed between [0,1], δ is the random orientation foraging parameter, s=1,2,L,S;define the t+1th generation The evolution method of the s-dimensional quantum position of the quantum leader monkey is in is a random number that follows a uniform distribution between [0,1], and c1 represents the probability of a quantum bit mutating when the quantum rotation angle is 0, and its value is The constant between s=1,2,L,S; get the t+1th generation The quantum position of the quantum leader monkey is in Then the quantum position set of the updated t+1th generation quantum leader monkey group is For the quantum monkey group, define the t+1th generation The rotation angle of the s-th dimension quantum of the monkey following the quantum is in For the tth generation The s-dimensional quantum rotation angle of the quantum leader monkey, For the tth generation The quantum follows the monkey's s-dimensional quantum rotation angle, is a random number that follows a uniform distribution between [0,1]. s=1,2,L,S;define the t+1th generation The evolution method of the s-dimensional quantum position of the quantum following monkey is in is a random number that follows a uniform distribution between [0,1], and c2 represents the probability of a quantum bit mutating when the quantum rotation angle is 0, and its value is The constant between s=1,2,L,S; get the t+1th generation The quantum position of the monkey following is in Then the quantum position set of the t+1th generation quantum following monkey group after update is Then the quantum position set of the entire quantum capuchin monkey group of the t+1th generation after the update is obtained as The measured position is obtained by measuring the s-dimensional quantum position of the h-th quantum capuchin monkey of the t+1th generation The measurement equation is Then the measured position of the hth quantum capuchin monkey in the t+1th generation after measurement is in is a random number that follows a uniform distribution between [0,1]. After measurement, the measurement positions of the t+1th generation of H quantum capuchins are obtained.

7. The anti-interference decision-making method based on the quantum capuchin mechanism according to claim 6 is characterized in that: The specific steps of step three and four include: after the quantum position of the hth quantum capuchin monkey in the t+1th generation is measured, According to the mapping rules, it is mapped to And substitute it into the anti-interference decision model to calculate the fitness value with penalty function The measurement position with the best fitness value of the hth quantum capuchin monkey up to the t+1th generation is recorded as the local optimal measurement position The measurement position with the best fitness value of all quantum capuchins up to the t+1th generation is recorded as the global optimal measurement position 8. An anti-interference decision-making system based on quantum capuchin mechanism, characterized in that: include: A model building module, configured to build an anti-interference decision model, wherein the anti-interference decision model is a combination of a channel, a coding method, a modulation method, and a transmission power of a communication party; An objective function design module, configured to set an objective function and constraints based on the anti-interference decision model; The optimal decision-making solution module is configured to optimize and solve the objective function using the quantum capuchin mechanism to obtain the optimal combination of channel, coding method, modulation method and transmission power.

9. The anti-interference decision-making system based on the quantum capuchin mechanism according to claim 8 is characterized in that: The objective function in the objective function design module is: F(C n ,M f ,I q ,K l )=w1f ber +w2f s Among them, C n Indicates the optional channel for the nth communication party; M f Indicates the optional modulation mode of the fth communication party; I q K represents the optional transmission power of the qth communication party; l Indicates the optional encoding method for the first communication party; represents the minimum normalized average bit error rate, E max is the maximum average bit error rate, E min is the minimum average bit error rate, E represents the average bit error rate; represents the minimum normalized transmit power, I max is the maximum transmit power, I min is the minimum transmission power; w1 and w2 are the user's expected parameters, w1+w2=1; The constraints are: R ≥ Among them, f R =R b ×K l ×log2(M f ) represents the information transmission rate, R b It is the original uncoded information transmission rate set according to the actual environment during communication. Indicates the minimum information transmission rate required for communication based on the actual environment.

10. The anti-interference decision-making system based on the quantum capuchin mechanism according to claim 9 is characterized in that: The step of optimizing and solving the objective function by using the quantum capuchin mechanism in the optimal decision-solving module to obtain the optimal combination of channel, coding mode, modulation mode and transmission power includes: Step 31: Initialize the quantum position in the quantum capuchin mechanism; Step 32: Measure the initial quantum position of each quantum capuchin, set a fitness function with a penalty function and calculate the fitness values ​​of all initial quantum positions, and determine the local optimal measurement position and the global optimal measurement position; Step 3. Different types of quantum capuchins update the corresponding measured positions of quantum rotation angles and quantum positions according to their respective update strategies. Step 34: Convert the updated measurement position into a communication strategy, calculate the fitness value of each quantum capuchin's updated measurement position, and update the local optimal measurement position and the global optimal measurement position; Step 35: determine whether the search mechanism has reached the maximum number of iterations, if so, output the global optimal measurement position; otherwise, return to step 33 to continue iterating; Step 36: Convert the obtained global optimal measurement position into the corresponding channel, coding mode, modulation mode and transmission power according to the mapping rule of step 32 to obtain the optimal anti-interference decision combination.

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