Control and service channel joint interference decision-making method for multi-formation communication targets

Abstract

The invention provides a multi-formation communication target-oriented control and service channel joint interference decision-making method, which comprises the following steps of: 1, giving an interference period, and setting a parameter of the total length of a time slot in each period; in each interference period, the following steps are executed until the maximum number of iterations is reached: step 2, calculating the power of an interference service channel and a reward value after interference; step 3, updating the Q table corresponding to the service channel and the service channel interfered in the next period; step 4, calculating a service channel communication success rate by the communication formation; step 5, calculating the power of the interference 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 interfered in the next period; and step 7, calculating a control channel interaction success rate. The invention provides a good cognitive interference decision of multiple formation communication targets.

Description

Technical Field

[0001] This application relates to the field of wireless communication interference technology, and particularly to a joint interference decision-making method for control and service channels for multi-formation communication targets. Background Art

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

[0003] Current multi-node communication systems often adopt a distributed cooperative architecture and a dynamic frequency hopping mechanism to build a highly robust communication network, which poses many challenges to traditional interference strategies. On the one hand, traditional strategies are difficult to adapt to the dynamic competition of 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 insufficient modeling of formation coupling relationships and communication dynamics. At the same time, existing communication interference research mostly focuses on single-user scenarios, making it difficult to address the internal coordination problem of frequency usage strategies among multiple targets, and the research on interference technology for control channels is still in the initial exploration stage, unable to effectively meet the interference requirements in complex communication scenarios.

[0004] Under this background, researching a cognitive interference decision-making method for multi-formation communication targets has important practical significance. Summary of the Invention

[0005] This application provides a joint interference decision-making method for control and service channels for multi-formation communication targets, which can be used to solve the technical problem of imperfect frequency usage strategies among multiple targets.

[0006] This application provides a joint interference decision-making method for control and service channels for multi-formation communication targets. The method includes:

[0007] Step 1, given an interference period and set parameters for the total length of each period's time slots.

[0008] Given the maximum number of iterations of the interference period , the time slot lengths of the service channel and the control channel within each period , initialize the control channel value table , the service channel value table , where represents the environmental state selected at time slot t, represents the action selected at time slot t.

[0009] Within each interference period, perform the following steps until the maximum number of iterations is reached:

[0010] Step 2, calculate the power of the interfering service channel and the reward value after interference.

[0011] Let the total power of the jammer be , be the power required to interfere with a single service channel. In one time slot, assume that when interfering with multiple service channels simultaneously, the total power is evenly distributed to each service channel, i.e., , is the number of service channels interfered with in one time slot; the reward value function of the interfered service channel is: , where ; is used to identify the time slot number currently performing the calculation, is the minimum signal-to-interference-plus-noise ratio demodulation threshold of the service channel, represents the channel set used by the formation user in the th communication time slot, represents the channel set interfered with by the jammer in the th communication time slot, represents the channel used simultaneously by the service channel of the formation user and the jammer in the th 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 transmitter and receiver, represents the channel gain between the jammer and the user receiver, is the noise power, represents the indicator function, defined as .

[0013] Step 3, update the table corresponding to the service channel and the service channels to be interfered in the next cycle.

[0014] The jammer senses and obtains the current spectrum information to update the current state , and according to the following method: Update the value table, where represents the learning rate of the jammer, represents the discount factor corresponding to the value update; represents the immediate reward after the jammer executes the action; represents the action that enables the intelligent jammer to obtain the maximum reward value in state

[0015] Then, the interfering traffic channels are selected according to the following rules: , where is the Boltzmann coefficient, indicates the probability that the jammer selects the th interference strategy in time slot , represents the selected interference strategy.

[0016] Step 4: The communication formation calculates the communication success rate of the traffic channels.

[0017] When the communication formation completes a communication cycle, the successful communication ratio of the traffic channels within one cycle is statistically counted, the decision selection mode is determined, and is defined as the successful communication ratio of the traffic channels 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 on the control channel.

[0019] Let be the power required to interfere with a single control channel. Therefore, within one time slot, assuming that when multiple control channels are interfered simultaneously, the total power is evenly distributed to each control channel, that is , is the number of control channels interfered within one time slot; the reward value function of the jammer on the control channel is , where ; is used to identify the time slot number currently performing the calculation, is the minimum signal-to-interference-plus-noise ratio demodulation threshold of the control channel.

[0020] Step 6: Update the table corresponding to the control channel and the control channels to be interfered in the next cycle.

[0021] The jammer senses and obtains the current spectrum information to update the current state , and according to the following method:

[0022] Update the table; the jammer obtains the control channels for which the current users make decisions through spectrum sensing, updates the current state to , and selects the interference channels 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 channels within one cycle is statistically counted, and the decision selection mode is determined; when and , where is the successful communication ratio of the control channel within one cycle of the communication formation; and is a fixed value set according to the actual situation; is defined as the successful communication ratio of the service channel of the communication formation within one cycle. Then the communication formation randomly selects the next mode and executes step 2; otherwise, it maintains the original communication mode.

[0025] In view of the challenges that traditional interference strategies in multi-formation communication systems are difficult to adapt to the dynamic competition of channel resources and lack the ability of cross-band optimization, etc., this application constructs an interference model that integrates formation cooperation and channel competition characteristics, defines a dual-mode interference benefit function, designs a dynamic decision-making architecture based on reinforcement learning, and realizes the online adaptive adjustment of interference strategies through a Markov model. Simulations show that this method significantly improves the interference success rate for the control channel and the service channel, can effectively cope with the dynamic mode switching of the communication formation, and provides a new method for multi-formation communication interference technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is the implementation flowchart of the maximum interference utility of the jammer provided by the embodiment of this application;

[0027] Figure 2 is the wireless communication interference scenario diagram provided by the embodiment of this application;

[0028] Figure 3 is the dynamic change diagram of the success rates of interfering with the control channel and the service channel in multiple modes provided by the embodiment of this application;

[0029] Figure 4 is the comparison diagram of the signal-to-interference-plus-noise ratio of the jammer provided by the embodiment of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0030] To make the objectives, technical solutions, and advantages of this application clearer, the following will further describe the embodiments of this application in detail with reference to the drawings.

[0031] The embodiments of this application will be introduced below with reference to the drawings first.

[0032] Figure 1 is the diagram of the jammer realizing the maximum interference utility according to the present invention, and the implementation steps are as follows: First, set the maximum number of iterations within the interference period; subsequently, the jammer obtains the service channels of users through the channel sensing module; based on the obtained channel information, the Boltzmann strategy is used to select the service channels to be interfered; after the interference is completed, calculate the reward value corresponding to this interference behavior, and update according to the reward value Value table; then, the jammer determines whether to switch the working mode by comparing the service 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 again uses the Boltzmann strategy to select the interference control channel; similarly, calculate the reward value of this interference control channel and update the value table; finally, the system monitors the current iteration step in real time. If the preset maximum number of iterations is reached, the interference process is terminated; otherwise, the interference operation and parameter update are continued.

[0033] Figure 2 is the wireless communication interference scenario diagram proposed by the present invention. In Figure 2 the multi-formation communication architecture shown, each formation is equipped with a central management node responsible for coordinating and controlling cross-formation communication activities. To ensure efficient information interaction with other formations and minimize mutual interference, each formation is assigned non-overlapping working frequency bands. Specifically, the central management node within each formation uses a specific working frequency band to optimize communication management and reduce mutual interference. To enhance the anti-jamming ability, the nodes within each formation perform frequency hopping according to a preset frequency hopping sequence. In each cycle, the communication formation first uses the service channel to transmit data according to the preset 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 jammed by the jammer, but the communication success rate of the service channel is lower than the effectiveness threshold set by the formation itself, it is considered that the communication effect of this mode is not good. The communication formation will perform information interaction through the control channel and dynamically decide to adjust to a new communication mode to ensure the continuity and reliability of communication.

[0034] Figure 3 shows the dynamic changes in the success rates of the interference control channel and the service channel in multiple modes. Since in different application scenarios, the required interference effect evaluation criteria are different. Therefore, different setting mechanisms are adopted for the probability factor that the jammer can successfully jam, and it is set to Specifically, in the initial first communication mode, the intelligent jammer based on the reinforcement learning algorithm continuously optimizes the jamming strategy, making the jamming success rate of the control channel and the service channel show a steady upward trend. As the jamming process progresses, when the communication success rate drops to the threshold, and at this time the degree of interference on the control channel is not lower than 0.6, the system will automatically switch to the second communication mode. This mode continues a similar jamming strategy and evaluation mechanism to continuously adapt to changes in the communication environment. The system will enter the third mode in this way. In the third mode, although the overall communication success rate of the communication formation is lower than 0.8, and there is a situation where it is lower than 0.8, the jamming success rate of the control channel has reached 0.6. At this time, the system cannot perform mode switching. However, due to the introduction of the Boltzmann exploration mechanism, there is still a possibility that the communication success rate of the control channel will be briefly higher than the threshold. Therefore, there is still a certain probability for the system to trigger mode switching. The switch from the third mode to the fourth mode also follows the same mechanism.

[0035] This study compared three baseline strategies: the greedy algorithm, the switching strategy that only depends on the success rate of the service channel, that is, without considering the state of the control channel, and only triggers mode switching when the success rate of the service channel is lower than the threshold, and the ideal scenario where the jammer can successfully jam. The simulation results show that due to the high dimension of the action space, the greedy algorithm converges to a local optimal solution after a short exploration, resulting in a significantly lower overall jamming success rate than other strategies. In the initial stage of jamming, for the switching strategy that only depends on the service channel, since the control channel has not reached the interference threshold, its mode switching rhythm is similar to that considering the control channel; but as the jamming process progresses, this strategy shows a faster mode switching speed and more significant strategy differences in the middle and late stages because it does not need to wait for the communication success rate of the control channel to rise above the threshold. In sharp contrast, when the probability factor of successful jamming of the control channel is set to 1, the system hardly undergoes mode switching. The reason is that as the jamming process progresses, the control channel is always in an effectively jammed state; even with certain random perturbations under the action of the Boltzmann exploration mechanism, since the jamming can ensure a 100% jamming success rate once it takes effect, the information interaction success rate of the control channel always remains at a low level, and there is no effective fluctuation sufficient to trigger mode switching. Therefore, the system shows a highly stable jamming effect and an extremely low switching frequency.

[0036] Figure 4The signal-to-interference-plus-noise ratio (SINR) of the jammer under different algorithms was compared. The SINR metric intuitively shows the differences in interference effectiveness of different comparison algorithms during the training process. The experimental results show that when the probability factor of successful jamming by the jammer is 1, the jamming effect is the most significant. The main reason is that the pattern of the communication formation remains almost unchanged, and the jamming strategy can quickly adapt and stably learn, thus achieving efficient jamming suppression. Secondly, it is the interference determination strategy of the control channel based on a threshold of 0.8. Although there is still a mode switching mechanism in the system, it needs to wait until the interference intensity of the control channel is lower than the threshold to be triggered. Therefore, the jamming effect is second only to the ideal control scenario.

[0037] In contrast, the strategy that only relies on the success rate of the service channel for mode switching, although it has a faster response ability in responding to channel changes, due to the lack of effective perception and coordinated consideration of the control channel state, its overall interference effectiveness has decreased. And the greedy algorithm has limited exploration ability in the action space and converges to the local optimal solution prematurely, restricting the learning process of the jamming strategy. Its SINR performance is the worst, and the jamming effect is significantly weaker than other strategies. In summary, the experimental results fully verify the key role of the control channel state in constructing an efficient dynamic jamming strategy. Incorporating it into the jamming decision-making mechanism helps 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 protection scope of the present application.

Claims

1. A joint interference decision method for control and service channels for multi-formation communication targets, characterized in that The method includes: Step 1: Given an interference period, set parameters for the total length of each cycle time slot; Within each interference period, perform the following steps until the maximum number of iterations is reached: Step 2: Calculate the power of the interference service channel and the reward value after interference; Step 3, update the table corresponding to the traffic channel and the traffic channels interfered in the next period; 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 on the control channel; Step 6, update the table corresponding to the control channel and the control channel for interference in the next period; Step 7: Calculate the interaction success rate of the control channel.

2. The method according to claim 1, wherein Step 1: Given an interference period, set parameters for the total length of each cycle time slot, including: Maximum number of iterations for a given interference period and the slot lengths of the traffic channel and the control channel within each period Initialize the control channel Value table Traffic channel Value table where represents the environmental state selected at time slot t, represents the action selected at time slot t.

3. The method according to claim 2, characterized in that, Step 2: Calculate the power of the interference service channel and the reward value after interference, including: Let the total power of the jammer be , be the power required to jam a single service channel. In a time slot, assuming that when jamming multiple service channels simultaneously, the total power is evenly distributed to each service channel, that is , is the number of service channels jammed in a time slot; the reward value function of the jammed service channels is: , where ; is used to identify the sequence number of the time slot currently performing the calculation, is the minimum signal-to-interference-plus-noise ratio demodulation threshold of the service channel, represents the channel set used by the formation users in the th communication time slot, represents the channel set jammed by the jammer in the th communication time slot, represents the channels simultaneously used by the service channels of the formation users and the jammer in the th communication time slot. The signal-to-noise ratio is determined by the following method: , where the power used by the communication formation is , represents the channel gain between the user transmitter and the receiver, represents the channel gain between the jammer and the user receiver, is the noise power, represents the indicator function, defined as .

4. The method according to claim 3, wherein Step 3, update the table corresponding to the traffic channel and the traffic channels interfered in the next period, including: The jammer senses and obtains the current spectrum information to update its current state , and according to the following method: Update the value table, where represents the learning rate of the jammer, represents the discount factor corresponding to the value update; represents the immediate reward after the jammer executes the action; represents the state under which the intelligent jammer obtains the maximum reward value for the action; Then, the interfering traffic channels are selected according to the following rules: , where is the Boltzmann coefficient, indicates the probability that the jammer selects the th interference strategy in time slot , and represents the selected interference strategy.

5. The method according to claim 4, characterized in that, Step 4: The communication formation calculates the communication success rate of the service channel, including: When the communication formation completes a communication cycle, count the successful communication ratio of the traffic channel within one cycle, make a decision on the selection mode, and is defined as the successful communication ratio of the traffic channel of the communication formation within one cycle.

6. The method according to claim 5, wherein Step 5: Calculate the power of the interference control channel and the reward value of the jammer on the control channel, including: Let be the power required to interfere with a single control channel. Therefore, within a time slot, assuming that when interfering with multiple control channels simultaneously, the total power is evenly distributed to each control channel, that is , is the number of control channels interfered with within a time slot; the reward value function of the jammer for the control channel is , where ; is used to identify the serial number of the time slot currently performing the calculation, is the minimum signal-to-interference-plus-noise ratio demodulation threshold of the control channel.

7. The method according to claim 6, wherein Step 6, update the table corresponding to the control channel and the control channel of the interference in the next period, including: The jammer senses and obtains the current spectrum information to update its current state , and according to the following method: Update the table; The jammer obtains the control channel for the current user to make decisions through spectrum sensing, and updates the current state to , and selects the interference channel according to the following rules: .

8. The method according to claim 7, wherein Step 7: Calculate the interaction success rate of the control channel, including: When a communication formation completes a communication cycle, count the successful interaction ratio of the control channel within one cycle and decide on the selection mode; when and , where is the successful communication ratio of the control channel within one cycle of the communication formation; and are fixed values set according to the actual situation, is defined as the successful communication ratio of the traffic channel within one cycle of the communication formation. Then the communication formation randomly selects the next mode and executes step 2, otherwise it maintains the original communication mode.

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