A joint interference decision-making method for control and traffic channels for multi-formation communication targets

Abstract

The present application provides a method for joint interference decision-making of control and service channels for multi-formation communication targets, the method comprising: step 1, giving an interference period and setting parameters for the total length of each periodic time slot; in each interference period, performing the following steps until the maximum number of iterations is reached: step 2, calculating the power of the interfering service channel and the reward value after interference; step 3, updating the Q table corresponding to the service channel and the service channel to be interfered in the next period; step 4, the communication formation calculates the communication success rate of the service channel; step 5, calculating the power of the interfering control channel and the reward value of the jammer in the control channel; step 6, updating the Q table corresponding to the control channel and the control channel to be interfered in the next period; step 7, calculating the control channel interaction success rate. The present application provides a good cognitive interference decision-making for multi-formation communication targets.

Description

Technical Field

[0001] The present application relates to the field of wireless communication interference technology, and in particular to a control and service channel joint interference decision-making method for multi-formation communication targets. Background Art

[0002] In the intelligent information age, communication jamming technology, as a core technology, can affect data transmission and collaborative operation capabilities by suppressing the signal-to-interference-noise ratio of communication links.

[0003] Current multi-node communication systems often use distributed collaborative architectures and dynamic frequency hopping mechanisms to build highly robust communication networks, which poses many challenges to traditional interference strategies. On the one hand, traditional strategies are difficult to adapt to the dynamic competition for channel resources between formations. On the other hand, they lack the ability to optimize the cross-band coordination mechanism of control channels and service channels. Existing technologies have limited interference effectiveness due to the inadequate modeling of formation coupling relationships and communication dynamics. At the same time, existing communication interference research focuses on single-user scenarios and has difficulty coping with the internal coordination of frequency strategies among multiple targets. In addition, research on interference technology for control channels is still in the initial exploratory stage and cannot effectively address interference requirements in complex communication scenarios.

[0004] In this context, studying cognitive jamming decision-making methods for multi-formation communication targets has important practical significance. Summary of the Invention

[0005] The present application provides a control and service channel joint interference decision method for multiple formation communication targets, which can be used to solve the technical problem of imperfect frequency utilization strategy among multiple targets.

[0006] The present application provides a method for joint interference decision-making of control and traffic channels for multi-formation communication targets, the method comprising:

[0007] Step 1: Given an interference period, set the parameters of the total length of each periodic time slot.

[0008] Maximum number of iterations for a given interference period , the length of the traffic channel time slot and the control channel time slot in each cycle , initialize the control channel Value Table , business channel Value Table ,in represents the environmental state selected at time slot t, Indicates the action of time slot selection t.

[0009] In each interference cycle, the following steps are performed until the maximum number of iterations is reached:

[0010] Step 2: Calculate the power of the interfering traffic channel and the reward value after interference.

[0011] Let the total power of the jammer be , To interfere with the power required for a single service channel, within a time slot, it is assumed that when multiple service channels are interfered with at the same time, the total power will be evenly distributed to each service channel, that is, , is the number of interfering traffic channels in a time slot; the reward value function of the interfering traffic channel is: ,in ; Used to identify the time slot number in which the calculation is currently being performed. is the minimum signal-to-interference-and-noise ratio demodulation threshold of the traffic channel, Indicates that the team user is in the The channel set used by the communication time slots, Indicates that the jammer is The set of channels interfered by the communication time slots, It represents the traffic channel of the formation user and the jammer in the first For channels used simultaneously in a communication time slot, the signal-to-noise ratio is determined by the following method:

[0012] , where the power used by the communication formation is , represents the channel gain between the user's transmitting and receiving ends, represents the channel gain between the jammer and the user receiving end, is the noise power, represents the indicator function, and defines .

[0013] Step 3: Update the traffic channel corresponding table and the service channels interfered with in the next cycle.

[0014] Jammer senses and obtains current spectrum information to update current status , and according to the following method: renew Value table, where represents the learning rate of the jammer, express The discount factor corresponding to the value update; Indicates that the jammer executes Immediate benefits after the action; Indicates status The following action makes the intelligent jammer obtain the maximum benefit value;

[0015] Then the interfering traffic channel is selected according to the following rules: ,in is the Boltzmann coefficient, Indicates that the jammer is in time slot Select The probability of a jamming strategy, Indicates the selected interference strategy.

[0016] Step 4: The communication formation calculates the communication success rate of the service channel.

[0017] When the communication formation completes a communication cycle, the successful communication ratio of the service channel in a cycle is counted and the decision-making mode is selected. It is defined as the successful communication ratio of the traffic channel of the communication formation within one cycle.

[0018] Step 5: Calculate the power of the interference control channel and the reward value of the jammer in the control channel.

[0019] set up The power required to interfere with a single control channel is , so in one time slot, assuming that when multiple control channels are interfered with at the same time, the total power will be evenly distributed to each control channel, that is, , is the number of jammer control channels in a time slot; the reward function of the jammer in the control channel is ,in ; Used to identify the time slot number in which the calculation is currently being performed. It is the minimum signal to interference and noise ratio demodulation threshold of the control channel.

[0020] Step 6: Update the control channel corresponding table and the control channel of the next period interference.

[0021] Jammer senses and obtains current spectrum information to update current status , and according to the following method:

[0022] renew Table; The jammer obtains the control channel for the current user to make decisions through spectrum sensing and updates the current state to , and select the interference channel according to the following rules: .

[0023] Step 7: Calculate the control channel interaction success rate.

[0024] When the communication formation completes a communication cycle, the successful interaction ratio of the control channel within a cycle is counted and the decision-making mode is selected; and ,in It is the successful communication ratio of the control channel within one cycle of the communication formation; and It is a fixed value set according to actual conditions; Defined as the successful communication ratio of the service channel of the communication formation within one cycle, the communication formation randomly selects the next mode and executes step 2, otherwise it maintains the original communication mode.

[0025] This application addresses challenges in multi-formation communication systems, such as the difficulty of traditional jamming strategies in adapting to dynamic competition for channel resources and lacking cross-band optimization capabilities. By constructing an interference model that integrates formation collaboration and channel competition, this application defines a dual-mode jamming benefit function, designs a dynamic decision-making architecture based on reinforcement learning, and implements online adaptive adjustment of the jamming strategy through a Markov model. Simulations demonstrate that this approach significantly improves the success rate of jamming control and traffic channels, effectively addresses the dynamic mode switching of communication formations, and provides a new approach to multi-formation communication jamming technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A flowchart for implementing the maximum jamming effectiveness of a jammer provided in an embodiment of the present application;

[0027] Figure 2 A wireless communication interference scenario diagram provided in an embodiment of the present application;

[0028] Figure 3 A dynamic change diagram of the success rate of the interference control channel and the traffic channel in multiple modes provided in an embodiment of the present application;

[0029] Figure 4 A comparison chart of the signal-to-interference-and-noise ratio of the jammer provided in an embodiment of the present application. DETAILED DESCRIPTION

[0030] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0031] The following first introduces the embodiments of the present application with reference to the accompanying drawings.

[0032] Figure 1 The jammer of the present invention achieves the maximum jamming utility diagram, and the implementation steps are as follows: first, the maximum number of iterations within the jamming cycle is set; then, the jammer obtains the user's service channel through the channel sensing module; based on the obtained channel information, the Boltzmann strategy is used to select the service channel to be jammed; after the jamming is completed, the reward value corresponding to the jamming behavior is calculated, and the reward value is updated according to the reward value. Then, the jammer determines whether to switch the working mode by comparing the business success rate with a fixed value. After the mode decision is completed, the jammer performs channel sensing again to obtain the control channel between formations and uses the Boltzmann strategy to select the jamming control channel again. The reward value of the jamming control channel is also calculated and updated. Value table; finally, the system monitors the current number of iterations in real time. If the preset maximum number of iterations is reached, the interference process is terminated, otherwise the interference operation and parameter update will continue.

[0033] Figure 2 This is the wireless communication interference scene diagram proposed by the present invention. Figure 2 In the multi-formation communication architecture presented, each formation has a central management node responsible for coordinating and controlling cross-formation communication activities. To ensure efficient information exchange with other formations and minimize mutual interference, each formation is assigned non-overlapping operating frequency bands. Specifically, the central management node within each formation uses a specific operating frequency band to optimize communication management and reduce mutual interference. To enhance anti-interference capabilities, nodes within each formation perform frequency hopping according to a pre-set frequency hopping sequence. During each cycle, the communication formation first uses the traffic channel to transmit data according to the pre-set frequency hopping sequence, and then makes mode decisions and adjustments through the control channel at the end of the cycle. If the control channel is not effectively interfered with by the jammer, but the communication success rate of the traffic channel is lower than the performance threshold set by the formation, the communication mode is considered to be ineffective. The communication formation will exchange information through the control channel and dynamically decide to adjust to a new communication mode to ensure continuous and reliable communication.

[0034] Figure 3 The dynamic changes of the success rate of interference control channel and traffic channel in multiple modes are shown. Since the required interference effect evaluation criteria are different in different application scenarios, different setting mechanisms are used for the probability factor of successful interference by the jammer, which is set to Specifically, in the initial first communication mode, the intelligent jammer based on the reinforcement learning algorithm continuously optimizes the jamming strategy, so that the jamming success rate of the control channel and the service channel shows a steadily increasing trend. As the jamming process progresses, when the communication success rate drops to the threshold, the degree of interference on the control channel is not less than 0.6, and the system will automatically switch to the second communication mode. This mode continues with a similar jamming strategy and evaluation mechanism to achieve continuous adaptation to changes in the communication environment. The system advances into the third mode in this way. In the third mode, although the overall communication success rate of the communication formation is still lower than 0.8, the control channel jamming success rate has reached 0.6, and the system cannot switch modes at this time. However, due to the introduction of the Boltzmann exploration mechanism, the control channel communication success rate may still be temporarily higher than the threshold, so the system still has a certain probability of triggering mode switching. The switch from the third mode to the fourth mode also follows the same mechanism.

[0035] This study compared three baseline strategies: a greedy algorithm, a switching strategy that relies solely on the success rate of the traffic channel, ignoring the state of the control channel and triggering mode switching only when the traffic channel success rate falls below a threshold, and an ideal scenario where the jammer can successfully interfere. Simulation results show that due to the high dimensionality of the action space, the greedy algorithm converges to a local optimal solution after a short exploration, resulting in an overall jamming success rate significantly lower than that of other strategies. In the early stages of interference, the switching strategy that relies solely on the traffic channel has a mode switching rhythm similar to that of the strategy that considers the control channel because the control channel has not yet reached the interference threshold. However, as the interference progresses, this strategy does not need to wait for the control channel communication success rate to rise above the threshold, and in the middle and late stages, it exhibits faster mode switching speeds and more significant strategy differences. In stark contrast, when the probability factor for successful control channel jamming is set to 1, the system rarely switches modes. This is because, as the jamming progresses, the control channel remains effectively jammed. Even with some random perturbations due to the Boltzmann exploration mechanism, the control channel's information exchange success rate remains low, as the jamming success rate is guaranteed to be 100% once it takes effect. There are no significant fluctuations sufficient to trigger a mode switch. As a result, the system exhibits a highly stable jamming effect and a very low switching frequency.

[0036] Figure 4The signal-to-interference-and-noise ratio (SINR) of the jammers under different algorithms was compared. The SINR metric visually demonstrates the differences in jamming effectiveness between the different algorithms during training. Experimental results show that the jamming effect is most significant when the jammer's probability factor for successful jamming is 1. This is primarily due to the fact that the communication formation pattern remains virtually unchanged, allowing the jamming strategy to quickly adapt and stably learn, resulting in effective jamming suppression. A second-best performance outcome is the control channel's jamming decision strategy based on a threshold of 0.8. While the system still maintains a mode switching mechanism, it is triggered only when the control channel interference intensity falls below the threshold. Therefore, the jamming effectiveness is second only to that of the ideal control scenario.

[0037] In contrast, while strategies that rely solely on the success rate of traffic channels for mode switching exhibit a faster response to channel changes, their overall jamming effectiveness declines due to a lack of effective perception and coordinated consideration of control channel status. The greedy algorithm, however, has limited exploration capabilities in the action space and prematurely converges to a local optimum, limiting the learning process of the jamming strategy. This results in the worst SINR performance and significantly weaker jamming effectiveness than other strategies. In summary, these experimental results fully demonstrate the critical role of control channel status in constructing efficient dynamic jamming strategies. Incorporating this into the jamming decision-making mechanism can help improve the stability and learning efficiency of the jamming system.

[0038] The above-described embodiments of the present application do not constitute a limitation on the scope of protection of the present application.

Claims

1. A joint interference decision method for control and traffic channels for multi-formation communication targets, characterized in that: The method comprises: Step 1: Given an interference period, set the parameters of the total length of each periodic time slot; In each interference cycle, the following steps are performed until the maximum number of iterations is reached: Step 2: Calculate the power of the interfering traffic channel and the reward value after interference; Step 3: Update the traffic channel corresponding Table and the service channels interfered with in the next cycle; Step 4: The communication formation calculates the communication success rate of the service channel; Step 5, calculate the power of the interference control channel and the reward value of the jammer in the control channel; Step 6: Update the control channel corresponding table and the control channel of interference in the next cycle; Step 7: Calculate the control channel interaction success rate; Step 2: Calculate the power of the interfering traffic channel and the reward value after interference, including: Let the total power of the jammer be , To interfere with the power required for a single service channel, within a time slot, it is assumed that when multiple service channels are interfered with at the same time, the total power will be evenly distributed to each service channel, that is, , is the number of interfering traffic channels in a time slot; the reward value function of the interfering traffic channel is: ,in ; Used to identify the time slot number in which the calculation is currently being performed. is the minimum signal-to-interference-and-noise ratio demodulation threshold of the traffic channel, Indicates that the team user is in the The channel set used by the communication time slots, Indicates that the jammer is The set of channels interfered by the communication time slots, It represents the traffic channel of the formation user and the jammer in the first For channels used simultaneously in a communication time slot, the signal-to-interference-and-noise ratio is determined by the following method: , where the power used by the communication formation is , represents the channel gain between the user's transmitting and receiving ends, represents the channel gain between the jammer and the user receiving end, is the noise power, represents the indicator function, and defines ; Step 5, calculating the power of the interference control channel and the reward value of the jammer in the control channel, including: set up The power required to interfere with a single control channel is , so in one time slot, assuming that when multiple control channels are interfered with at the same time, the total power will be evenly distributed to each control channel, that is, , is the number of jammer control channels in a time slot; the reward function of the jammer in the control channel is ,in ; Used to identify the time slot number in which the calculation is currently being performed. It is the minimum signal to interference and noise ratio demodulation threshold of the control channel.

2. The method according to claim 1, characterized in that Step 1: Given an interference period, set the parameters for the total length of each periodic time slot, including: Maximum number of iterations for a given interference period , the length of the traffic channel time slot and the control channel time slot in each cycle , initialize the control channel Value Table , business channel Value Table ,in represents the environmental state selected at time slot t, Indicates the action of time slot selection t.

3. The method according to claim 2, characterized in that Step 3: Update the traffic channel corresponding Table and the service channels interfered with in the next period, including: Jammer senses and obtains current spectrum information to update current status , and according to the following method: renew Value table, where represents the learning rate of the jammer, express The discount factor corresponding to the value update; Indicates that the jammer executes Immediate benefits after the action; Indicates status The following action makes the intelligent jammer obtain the maximum benefit value; Then the interfering traffic channel is selected according to the following rules: ,in is the Boltzmann coefficient, Indicates that the jammer is in time slot Select The probability of a jamming strategy, Indicates the selected interference strategy.

4. The method according to claim 3, characterized in that Step 4: The communication team calculates the communication success rate of the service channel, including: When the communication formation completes a communication cycle, the successful communication ratio of the service channel in a cycle is counted and the decision-making mode is selected. It is defined as the successful communication ratio of the traffic channel of the communication formation within one cycle.

5. The method according to claim 4, characterized in that Step 6: Update the control channel corresponding Table and the control channel of the next period interference, including: Jammer senses and obtains current spectrum information to update current status , and according to the following method: renew Table; The jammer obtains the control channel for the current user to make decisions through spectrum sensing and updates the current state to , and select the interference channel according to the following rules: .

6. The method according to claim 5, characterized in that Step 7, calculating the control channel interaction success rate, including: When the communication formation completes a communication cycle, the successful interaction ratio of the control channel within a cycle is counted and the decision-making mode is selected; and ,in It is the successful communication ratio of the control channel within one cycle of the communication formation; and It is a fixed value set according to actual conditions. Defined as the successful communication ratio of the service channel of the communication formation within one cycle, the communication formation randomly selects the next mode and executes step 2, otherwise it maintains the original communication mode.

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