A communication anti-interference autonomous decision-making method based on joint evaluation of interference parameters and channel conditions

Abstract

The application discloses a communication anti-interference autonomous decision-making method, system and device based on joint evaluation of interference parameters and channel conditions, and belongs to the technical field of wireless communication. The method comprises the following steps: processing a received composite signal, extracting parameters such as a signal-to-noise ratio, an interference signal-to-interference ratio, an interference lock time difference and an interference bandwidth proportion; constructing a state vector and selecting a target mode from candidate anti-interference modes based on a decision function; and performing waveform or parameter reconfiguration to maintain service communication. The application realizes quantitative differentiation of interference types and autonomous optimal selection of anti-interference modes, and solves the problem that existing systems cannot accurately cope with complex interference due to reliance on artificial experience.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and more specifically, to a communication anti-interference autonomous decision-making method, system, and device. Background Technology

[0002] Shortwave communication, with its unique advantages such as long skywave propagation distance, strong resilience, and independence from ground infrastructure, has always held an irreplaceable position in fields such as long-distance emergency communication, military command, aviation and maritime mobile services, and electronic warfare. After decades of development, shortwave communication systems have formed a relatively complete international standard system at the physical layer, link establishment layer, data link layer, and network layer. Typical examples include: the MIL-STD-188-110 series (physical layer waveform and modulation standards), the MIL-STD-188-141 series (Automatic Link Establishment (ALE) standards), STANAG 5066 (data link protocol), and STANAG 5070 (network layer protocol). These standards provide technical support for the interconnection and reliability of shortwave communication at different levels.

[0003] However, shortwave communication in complex electromagnetic environments currently faces increasingly severe threats from human interference, and existing shortwave communication systems have the following shortcomings in practical applications:

[0004] First, existing shortwave communication systems, including the MIL-STD-188-110 series, MIL-STD-188-141 series, STANAG 5066, and STANAG 5070, have waveforms that are independent of each other and lack effective correlation. The waveform used in the communication process depends entirely on manual pre-configuration and cannot be autonomously scheduled according to the real-time interference environment.

[0005] Second, shortwave channels themselves have time-varying, frequency-varying, and space-varying characteristics, and signal-to-noise ratio fluctuations are the norm. Existing technologies cannot accurately determine whether the root cause is the deterioration of ionospheric propagation conditions or intentional interference from external sources.

[0006] Third, waveform switching relies on human experience, making it difficult to make optimal decisions in real time. Operators often have to rely on experience to try switching waveforms or changing operating frequencies. This approach is significantly lagging behind in dealing with dynamic and intelligent interference sources and cannot meet the requirements for ensuring business continuity.

[0007] Fourth, existing systems lack comprehensive decision-making capabilities based on interference quantification assessment and channel conditions.

[0008] Existing shortwave communication systems lack a quantifiable, computable, and executable method for autonomous anti-interference decision-making. Therefore, there is an urgent need to propose a communication method that can quantitatively assess human interference and autonomously select anti-interference waveforms or modes based on channel conditions and interference parameters. Summary of the Invention

[0009] The present invention aims to overcome at least one of the defects of the prior art and provide a communication anti-interference autonomous decision-making method, system, device and medium based on joint evaluation of interference parameters and channel conditions, so as to solve the problem that the existing system relies on human experience and cannot accurately judge the type and severity of interference.

[0010] The technical solution adopted in this invention includes: A communication anti-interference autonomous decision-making method based on joint evaluation of interference parameters and channel conditions, the method comprising: S1, performing component estimation processing on the composite signal acquired at the receiving end; S2, extracting the signal-to-noise ratio of the composite signal. The power ratio of interference signal to useful signal Disturbance lock time difference and interference bandwidth ratio Parameters; S3, After extracting the parameters, construct the interference-channel state vector. The interference-channel state vector is input into the anti-interference decision module; S4, the physical layer / link layer of the receiving end is controlled to perform waveform or parameter reconfiguration according to the mode generated by the anti-interference decision module.

[0011] Step S1, component estimation, is the foundation of anti-interference decision-making, and its core lies in establishing a signal model in the communication link. This model accurately decomposes various signal components in the communication process, providing data support for subsequent parameter extraction and interference identification, and avoiding anti-interference decision bias caused by signal component confusion. The specific formula is as follows:

[0012] in, Useful signal This is a man-made interference signal. For noise, For time.

[0013] Step S2, based on the component estimation in Step S1, extracts key parameters that characterize the interference intensity, channel state, and interference type. These parameters complement each other and together constitute a complete description of the interference-channel state, providing a quantitative basis for anti-interference decisions. The specific calculation formula is as follows: The signal-to-noise ratio The calculation formula is ; The power ratio of the interference signal to the useful signal The calculation formula is ; It reflects whether malicious interference has been applied with sufficient power to affect normal communication; The locking time difference The calculation formula is ; in, The arrival time of the useful signal. When the interference signal arrives, The determination was made as tracking and locking interference. The preset threshold; It reflects the extent to which malicious human interference can track and lock onto communication signals; The percentage of interference bandwidth The calculation formula is ; in, For the equivalent bandwidth of the interference signal, This represents the bandwidth of the current service waveform.

[0014] After extracting the above key parameters, step S3 is to construct the complete interference-channel state vector. This vector comprehensively integrates channel noise status, man-made interference intensity, interference tracking capability, and interference bandwidth characteristics. Inputting it into the anti-interference decision module enables accurate identification of the current interference-channel state, thereby generating the optimal anti-interference mode selection result. ; Furthermore, this invention employs two decision-making methods—threshold rules and weighted scoring functions—to generate pattern selection results. ; The weighted scoring function generation modes include: Define candidate pattern set ; Define comprehensive score ; Select the optimal mode ; in, It should include at least one or more of the following: latency, throughput, bit error rate, and service priority. Weights and satisfying ; Furthermore, the threshold rules include: (1) and If noise is determined to be dominant, then the low-speed strong error correction / spread spectrum mode is selected; (2) , , Then, narrowband fixed-frequency interference is identified, and frequency agility is selected; (3) If tracking interference is detected, variable speed frequency hopping and time diversity should be selected. (4) If broadband suppression is detected, a narrowband robust waveform or relay path should be selected. in, , , , The threshold set based on the waveform.

[0015] The waveform or parameter switching in step S4 includes a combination of one or more of the following: Encoded spread spectrum, frequency agility, constant-speed frequency hopping, variable-speed frequency hopping, frequency diversity, time diversity, narrowband robust transmission, and relay-assisted communication; Select the different anti-interference modes mentioned above based on channel conditions, interference lockout, interference intensity, and interference bandwidth status. Furthermore, the switching logic is based on the data extracted in step S2. The channel conditions represented by, by The interference-locked state is characterized by... The intensity of the interference and its characteristics The different anti-interference modes mentioned above are selected based on the characteristics of the interference broadband state. Specifically, noise-dominated scenarios focus on noise anti-noise design, narrowband interference scenarios focus on frequency avoidance, tracking interference scenarios focus on breaking tracking lock, and broadband suppression scenarios focus on signal suppression or path avoidance. Furthermore, during the service transmission process, steps S1 to S4 are executed cyclically to achieve closed-loop adaptive control of component estimation, parameter extraction, anti-interference decision-making, and waveform switching, ensuring that the communication link can respond to interference and channel changes in real time.

[0016] An autonomous decision-making system for communication anti-interference based on joint evaluation of interference parameters and channel conditions, characterized by comprising: a signal model building module for acquiring composite signals and performing component estimation; and a parameter extraction module for extracting channel and interference parameters, including signal-to-noise ratio. The power ratio of interference signal to useful signal Disturbance lock time difference and interference bandwidth ratio Parameters; State vector construction module, used to construct interference-channel state vectors. The anti-interference decision module is used to generate mode selection results based on the interference-channel state vector using threshold rules or a weighted scoring function. The waveform or parameter switching module is used to control the physical layer / link layer to perform waveform or parameter reconfiguration.

[0017] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the above-mentioned communication anti-interference autonomous decision-making method based on joint evaluation of interference parameters and channel conditions.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: The communication anti-interference autonomous decision-making method, system, device, and medium provided by this invention can effectively distinguish whether communication anomalies are caused by malicious human interference or excessive environmental noise, overcoming the limitations of existing technologies where operators rely solely on experience to determine the source of anomalies. Furthermore, it supports automatic evaluation and optimal selection from a set of candidate modes composed of various waveforms and parameters, enabling switching between multiple anti-interference methods such as coded spread spectrum, frequency agility, variable-speed frequency hopping, and narrowband robust transmission, adapting to complex and ever-changing electromagnetic environments. This invention also integrates signal modeling, parameter extraction, state evaluation, decision functions, and waveform switching through a closed-loop architecture, enhancing the system's survivability and robustness in complex electromagnetic environments. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the execution flow of method steps S1 to S4 in Embodiment 1 of the present invention.

[0020] Figure 2 This is a schematic diagram of the signal composition of the receiving channel in Embodiment 1 of the present invention.

[0021] Figure 3 This is a schematic diagram illustrating the calculation of the interference lock-in communication formula in step S2 of the method according to Embodiment 1 of the present invention.

[0022] Figure 4 This is a schematic diagram of the method flow of Embodiment 2 of the present invention. Detailed Implementation

[0023] The accompanying drawings are for illustrative purposes only and should not be construed as limiting the invention. To better illustrate the following embodiments, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions; it is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0024] Example 1 like Figure 1 As shown, this embodiment provides a communication anti-interference autonomous decision-making method based on joint evaluation of interference parameters and channel conditions, applied to [the following], with steps including S1~S4: S1. Perform component estimation processing on the composite signal acquired by the receiving end; Specifically, the receiver acquires the composite signal and performs component estimation to establish a signal model:

[0025] in, Useful signal This is a man-made interference signal. For noise; Specifically, the composite signal received from the receiving channel consists of three types of signals, such as... Figure 2 As shown, it includes useful signals, interference, and noise. Interference refers to man-made interference signals, and everything else is classified as noise. Therefore, interference represents the signal that is degraded by malicious noise and is used as the basis for anti-interference decision-making to determine whether service transmission can proceed. Noise represents the channel noise baseline signal and is used to judge the channel transmission conditions to determine whether it is suitable for a certain rate of service. Interference can be classified into narrowband interference and wideband interference according to bandwidth, and into fixed-frequency interference and tracking interference according to duration. The parameters reflecting interference are interference amplitude, interference duration, and interference bandwidth. The interference parameters reflected in the useful signal are interference amplitude, which reflects the interference intensity; interference duration, which reflects whether the interference locks onto the signal; interference bandwidth, which reflects the coverage of the interference capability; and signal parameters such as the received signal-to-noise ratio, which reflects the channel conditions. Furthermore, the core parameters used to reflect the characteristics of man-made interference signals include interference amplitude, interference time, and interference bandwidth. Among them, interference amplitude is used to characterize the strength of the interference signal; the larger the amplitude, the stronger the interference effect on the useful signal. Interference time is used to characterize the duration of the interference signal and whether the interference signal can lock onto the useful signal and continuously interfere. Interference bandwidth is used to characterize the coverage range of the interference signal in the frequency domain; the larger the bandwidth, the wider the frequency domain interference coverage of the useful signal.

[0026] When conducting anti-interference analysis and service adaptation for useful signals, the aforementioned interference parameters can be further transformed into interference effect parameters directly related to service transmission. These parameters include: interference effect amplitude reflecting the strength of the interference on the useful signal; interference effect duration reflecting whether the interference locks onto the useful signal; and interference effect bandwidth reflecting the frequency domain coverage capability of the useful signal. Simultaneously, combined with signal parameters such as the received signal-to-noise ratio reflecting the basic transmission conditions of the channel, these parameters together constitute the signal and interference evaluation system at the receiver. This provides comprehensive parameter support for the receiver to adaptively adjust transmission strategies, initiate corresponding anti-interference measures, and determine appropriate service transmission rates, ensuring the stable operation of the anti-interference communication system.

[0027] S2. Extract the signal-to-noise ratio from the composite signal. The power ratio of interference signal to useful signal Disturbance lock time difference and interference bandwidth ratio parameter; Specifically, the formulas for calculating the extracted parameters include: The signal-to-noise ratio The calculation formula is ; The power ratio of the interference signal to the useful signal The calculation formula is ; like Figure 3 As shown, by calculating the amplitude difference between the useful signal and the interference signal, i.e. It can estimate whether malicious interference has been applied with sufficient power to affect normal communication. For example, in shortwave fixed-frequency or frequency-hopping communication scenarios, when the power amplitude difference between the useful signal and the interference signal is about 3dB (i.e. the power of the interference signal is close to or exceeds the power of the useful signal), it is determined that the interfering party has effectively interfered with the communication receiver. At this time, it is necessary to start anti-suppression measures such as frequency agility or spread spectrum. The locking time difference The calculation formula is ; in, The arrival time of the useful signal. When the interference signal arrives, The determination was made as tracking and locking interference. The preset threshold; By calculating the arrival time difference between the useful signal and the interference signal, i.e. It can estimate the tracking and locking capability of malicious interference on communication signals. For example, in shortwave fixed frequency or frequency hopping communication scenarios, when the arrival time difference between the useful signal and the interference signal is within 100ms, it is determined that the signals of both communicating parties have been effectively locked by the interfering party. At this time, anti-tracking interference strategies such as variable speed frequency hopping and time diversity need to be adopted. The percentage of interference bandwidth The calculation formula is ; in, For the equivalent bandwidth of the interference signal, This represents the bandwidth of the current service waveform. Specifically, the interference bandwidth ratio The estimation uses the energy accumulation method, which normalizes the power spectral density of the interference signal and then calculates the bandwidth spanned by the accumulated energy from 10% to 90% as the equivalent interference bandwidth. Then, compared with the current waveform bandwidth Find the ratio; In estimation, the energy accumulation method is usually used for analysis: first, the frequency domain distribution characteristics of the interference signal are normalized, and then the effective frequency band range of the interference is determined according to the energy distribution range. The frequency range covered by the energy accumulation from the lower threshold to the higher threshold is selected as the equivalent bandwidth of the interference signal. The interference bandwidth is calculated by comparing this equivalent bandwidth with the signal bandwidth occupied by the current service waveform. The resulting relative ratio is the interference bandwidth percentage. This metric effectively characterizes the degree of frequency overlap between the interference and the service signal. It can be used to assess the potential impact of interference on service signal reception, demodulation, and other processes, providing a quantitative basis for interference identification and suppression strategy development. Based on the amplitude and duration of the interference signal, the equivalent bandwidth of the malicious interference is estimated, and the transmission bandwidth of the useful signal is determined accordingly. Specifically, For the equivalent bandwidth of the interference signal, This refers to the bandwidth of the current service waveform; for example, in the shortwave band, when the bandwidth of the malicious interference signal is much larger than the bandwidth of the useful communication signal (i.e., ... When the bandwidth of the malicious interference signal is less than the bandwidth of the useful communication signal (i.e., ≥1), a narrowband robust waveform should be selected first to avoid broadband suppression interference; when the bandwidth of the malicious interference signal is less than the bandwidth of the useful communication signal (i.e., ≥1), a narrowband robust waveform should be selected first to avoid broadband suppression interference. When <1), broadband signals are preferred to utilize spread spectrum gain to combat narrowband interference.

[0028] S3. After extracting the parameters, construct the interference-channel state vector. The interference-channel state vector is input into the anti-interference decision module; Specifically, construct the interference-channel state vector. The interference-channel state vector is then input into the anti-interference decision module. After input, the mode selection result is generated using threshold rules or a weighted scoring function. ; Specifically, the weighted scoring function generation modes include: Define candidate pattern set ; Define comprehensive score ; Select the optimal mode ; in, It should include at least one or more of the following: latency, throughput, bit error rate, and service priority. Weights and satisfying ; Specifically, the threshold rules include: and If noise is determined to be dominant, then the low-speed strong error correction / spread spectrum mode is selected; , , Then, narrowband fixed-frequency interference is identified, and frequency agility is selected; If tracking interference is detected, variable speed frequency hopping and time diversity should be selected. If broadband suppression is detected, a narrowband robust waveform or relay path should be selected. in, , , , The threshold is set based on the waveform; S4. Based on the pattern generated by the anti-interference decision module, control the physical layer / link layer of the receiving end to perform waveform or parameter reconfiguration; Specifically, the present invention selects different anti-interference modes based on channel conditions, interference lock-in, interference intensity, interference bandwidth, and other conditions.

[0029] During the service transmission process, steps S1 to S4 are executed cyclically.

[0030] Example 2 like Figure 4 As shown, this embodiment provides an adaptive anti-interference communication method. Through a layered and progressive anti-interference strategy, communication parameters are dynamically adjusted according to channel interference conditions and signal-to-noise ratio (SNR) conditions to achieve reliable communication in complex electromagnetic environments. The specific implementation process is as follows: The communication system first initiates full-band spectrum sensing to monitor key parameters such as interference intensity, signal-to-noise ratio, latency, and Doppler spread in real time. When weak interference is detected, interference is not locked to a specific frequency, and channel conditions are good with a high signal-to-noise ratio, the system directly adjusts the data rate, modulation and demodulation methods, and encoding and decoding strategies based on the sensed channel quality parameters to maximize transmission efficiency while ensuring communication reliability. If interference is detected locking to a specific frequency, the system enters a fixed-rate frequency hopping process. The system locks a preset frequency hopping frequency to perform frequency hopping communication at a fixed hopping rate. If the interference is still weak, the interference is not locked to the frequency, and the channel conditions are good, the system can further select different hopping rates and simultaneously adjust the data rate, modulation / demodulation and encoding / decoding parameters to optimize communication performance. When strong interference is detected and the interference is not locked to the current frequency hopping frequency, the frequency agility process is triggered. For scenarios with strong interference, interference frequencies not locked to, and generally poor channel conditions and signal-to-noise ratios, the system avoids interference by selecting different operating frequencies and dynamically adjusting data rates, modulation / demodulation, and encoding / decoding. If the interference continues to lock onto the current frequency, a frequency hopping process is initiated, quickly switching to an unaffected idle frequency to achieve frequency avoidance. The system adopts a variable hopping rate and variable bandwidth frequency hopping mechanism. For scenarios with strong interference, interference locked to the frequency and general channel conditions, it improves anti-interference capability by selecting different bandwidths and operating frequencies, and by adaptively adjusting the data rate, modulation and demodulation and encoding and decoding. When the interference continues to lock to the frequency and the channel conditions further deteriorate, the coding spread spectrum process is started. The system employs coded spread spectrum technology to address scenarios with strong broadband interference, persistent frequency locking, poor channel conditions, and poor signal-to-noise ratio. By selecting different spreading factors and adjusting the spreading duration, the system uses spreading gain to counteract broadband interference. If the interference is strong narrowband interference and persistent frequency locking, the system switches to the direct spread spectrum process. When using direct sequence spread spectrum technology, for scenarios with strong narrowband interference, interference that is continuously locked to the frequency, poor channel conditions, and poor signal-to-noise ratio, different spreading factors are selected and the spreading bandwidth is adjusted to suppress narrowband interference with the spreading processing gain, thereby ensuring the basic communication link. When the above anti-interference strategies fail to achieve link establishment and synchronization, the system activates backup solutions such as collaborative relay, and completes link establishment, synchronization and communication through relay nodes to ensure uninterrupted communication under extreme interference environments.

[0031] In summary, the embodiments of the present invention have the following advantages over the prior art: 1. Clearly distinguish the source of interference: It can effectively distinguish whether the communication anomaly is caused by malicious human interference or by excessive environmental noise, avoiding the limitations of existing technologies that rely on the experience of operators, and providing a clear basis for anti-interference decision-making.

[0032] 2. Automatic decision-making and switching across waveform systems: It supports automatic evaluation and selection of the optimal solution among various candidate modes such as coded spread spectrum, frequency agility, constant speed frequency hopping, variable speed frequency hopping, frequency diversity, time diversity, narrowband robust transmission, and relay-assisted communication, so as to realize intelligent adaptive switching in complex electromagnetic environments.

[0033] 3. Reduce manual intervention and improve recovery speed: Significantly reduce reliance on the experience level of operators, avoid time delays caused by manual troubleshooting and trial and error, and quickly complete "detection-evaluation-decision-reconfiguration" through a closed-loop adaptive architecture, greatly improving communication recovery efficiency.

[0034] 4. Forming system-level anti-interference capability: By organically integrating signal modeling, parameter extraction, state assessment, decision function and waveform switching, the anti-interference capability is elevated from the isolated characteristics of a single waveform to the overall system-level capability of the communication system, enhancing the survivability and robustness of the system in complex electromagnetic environments.

[0035] The above embodiments are merely preferred embodiments of the present invention and do not constitute a limitation on the scope of protection of the present invention. Those skilled in the art should understand that various modifications, combinations, or substitutions can be made to the above embodiments without departing from the concept of the present invention, and all resulting technical solutions fall within the scope of protection claimed by the present invention.

Claims

1. A communication anti-interference autonomous decision-making method based on joint evaluation of interference parameters and channel conditions, the method comprising: S1. Perform component estimation processing on the composite signal acquired by the receiving end; S2. Extract the signal-to-noise ratio from the composite signal. The power ratio of interference signal to useful signal Disturbance lock time difference and interference bandwidth ratio parameter; S3. After extracting the parameters, construct the interference-channel state vector. The interference-channel state vector is input into the anti-interference decision module; S4. Based on the pattern generated by the anti-interference decision module, control the physical layer / link layer of the receiving end to perform waveform or parameter reconfiguration.

2. The communication anti-interference autonomous decision-making method based on joint evaluation of interference parameters and channel conditions according to claim 1, characterized in that, S1 component estimation processing includes: Establish signal model The specific formula is as follows: in, Useful signal This is a man-made interference signal. For noise, For time.

3. The communication anti-interference autonomous decision-making method based on joint evaluation of interference parameters and channel conditions according to claim 1, characterized in that, The formulas for calculating parameters extracted from S2 include: The signal-to-noise ratio The calculation formula is ; in, For useful signal power, Noise power; The power ratio of the interference signal to the useful signal The calculation formula is ,in, This refers to the power of artificially generated interference signals. The locking time difference The calculation formula is ; in, The arrival time of the useful signal. When the interference signal arrives, The determination was made as tracking and locking interference. The preset threshold; The percentage of interference bandwidth The calculation formula is ; in, For the equivalent bandwidth of the interference signal, This represents the bandwidth of the current service waveform.

4. The communication anti-interference autonomous decision-making method based on joint evaluation of interference parameters and channel conditions according to claim 1, characterized in that, S3 also includes: After inputting the interference-channel state vector into the anti-interference decision module, the mode selection result is generated using threshold rules or a weighted scoring function. .

5. The communication anti-interference autonomous decision-making method based on joint evaluation of interference parameters and channel conditions according to claim 4, characterized in that, The weighted scoring function generation modes include: Define candidate pattern set ; Define comprehensive score ; Select the optimal mode ; in, It should include at least one or more of the following: latency, throughput, bit error rate, and service priority. Weights and satisfying The mapping function normalizes and maps various metrics such as SNR and JSR.

6. The communication anti-interference autonomous decision-making method based on joint evaluation of interference parameters and channel conditions according to claim 5, characterized in that, Threshold rules include: and If noise is determined to be dominant, then the low-speed strong error correction / spread spectrum mode is selected; , , Then, narrowband fixed-frequency interference is identified, and frequency agility is selected; If tracking interference is detected, variable speed frequency hopping and time diversity should be selected. If broadband suppression is detected, a narrowband robust waveform or relay path should be selected. in, , , , The threshold set based on the waveform.

7. The communication anti-interference autonomous decision-making method based on joint evaluation of interference parameters and channel conditions according to claim 1, characterized in that, Waveform or parameter switching in S4 includes one or more of the following combinations: Encoded spread spectrum, frequency agility, fixed-speed frequency hopping, variable-speed frequency hopping, frequency diversity, time diversity, narrowband robust transmission, and relay-assisted communication.

8. The communication anti-interference autonomous decision-making method based on joint evaluation of interference parameters and channel conditions according to claim 1, characterized in that: During the service transmission process, steps S1 to S4 are executed cyclically.

9. The communication anti-interference autonomous decision-making system based on joint evaluation of interference parameters and channel conditions according to the method described in claims 1 to 7, characterized in that, include: The signal model building module is used to acquire composite signals and perform component estimation. The parameter extraction module is used to extract channel and interference parameters, including signal-to-noise ratio. The power ratio of interference signal to useful signal Disturbance lock time difference and interference bandwidth ratio parameter; The state vector construction module is used to construct the interference-channel state vector. ; The anti-interference decision module is used to generate mode selection results based on the interference-channel state vector using threshold rules or a weighted scoring function. ; The waveform or parameter switching module is used to control the physical layer / link layer to perform waveform or parameter reconfiguration.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method according to any one of claims 1 to 7.

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