High-definition video transmission optimization and encryption method based on wifi7 chip module

Abstract

The invention discloses a high-definition video transmission optimization and encryption method based on a wifi7 chip module, and relates to the technical field of data transmission resource allocation, and the method comprises the steps: collecting load data, interference data and signal intensity data of each frequency band in real time; dynamically selecting an optimal frequency band combination for parallel transmission; adjusting a modulation mode according to the signal quality, and distributing network resources; the load change is predicted by monitoring the network load in real time; dynamically adjusting a preamble puncturing mode based on the interference condition; generating a dynamic key through a hardware security module, distributing the dynamic key to terminal equipment through a security channel, and establishing a key life cycle management system; and carrying out continuous identity verification and authorization on the equipment and the user by adopting a zero-trust architecture. By adjusting a resource allocation strategy in advance, the video transmission problem caused by load mutation is effectively avoided, a key life cycle management system is established, generation, distribution, use and destruction of keys are managed, and the key management safety is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data transmission resource allocation, and specifically to an optimization and encryption method for high-definition video transmission based on a Wi-Fi 7 chip module. Background Art

[0002] With the accelerating advancement of the digital age, the application demand for high-definition video transmission has shown an explosive growth in many fields. In the home entertainment scenario, 8K ultra-high-definition videos and VR / AR content are gradually popularized, and users have extremely high requirements for video smoothness and picture quality clarity, requiring a stable and high-speed network to ensure an ultimate audio-visual experience. In the corporate office field, remote video conferencing and online collaborative work have become the norm, and the real-time transmission of high-definition videos is crucial for communication efficiency and decision-making quality. In the security monitoring industry, high-definition video monitoring systems need to transmit a large amount of high-definition video data in real time to detect security risks in a timely manner and take measures.

[0003] However, the existing network technologies face many challenges in high-definition video transmission. Traditional Wi-Fi technology is difficult to provide stable and high-speed transmission in the face of multi-device connections and complex interference environments, resulting in problems such as video stuttering and picture quality degradation. At the same time, high-definition video data contains a large amount of sensitive information, such as home privacy, corporate secrets, medical data, etc., and the data security issue has become increasingly prominent. Summary of the Invention

[0004] To solve the above technical problems, an optimization and encryption method for high-definition video transmission based on a Wi-Fi 7 chip module is provided, and this technical solution solves the problems raised in the above background art.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows: An optimization and encryption method for high-definition video transmission based on a Wi-Fi 7 chip module, including: Deploying network monitoring sensors to collect load data, interference data, and signal strength data of each frequency band in real time; Based on the real-time network load, interference situation, and signal strength, dynamically select the optimal frequency band combination for parallel transmission, and dynamically adjust the bandwidth allocation of each frequency band according to the bandwidth utilization rate of the frequency band; Dynamically bind at least one channel according to the network environment, adjust the modulation method according to the signal quality, and allocate network resources; Establishing a load prediction model to predict load changes by real-time monitoring of network load, and adjusting the resource allocation strategy in advance; Dynamically adjusting the preamble puncturing pattern based on the interference situation, shielding the interfered frequency bands, and retaining the available frequency bands; Generate dynamic keys through a hardware security module and distribute them to terminal devices through a secure channel, establish a key lifecycle management system to manage the generation, distribution, use, and destruction of keys; Adopt a zero-trust architecture to continuously authenticate and authorize devices and users, and combine identity authentication methods to optimize end-to-end encryption performance through hardware acceleration.

[0006] Preferably, the generating dynamic keys through a hardware security module and distributing them to terminal devices through a secure channel, establishing a key lifecycle management system to manage the generation, distribution, use, and destruction of keys specifically includes: Deploy a hardware security module to prevent unauthorized access, and perform initialization configuration on the hardware security module, set the administrator password and security policies; Based on security standards and business requirements, select the generated key length, define the conditions and frequencies of key generation; The hardware security module uses an internal true random number generator to generate key materials and uses a key derivation function to derive the final key from the key materials; Select the Secure Sockets Layer cryptographic communication framework encryption channel as the secure channel for key distribution, and configure digital certificates for both ends of the channel; Configure the security parameters of the encryption channel, and the security parameters include encryption algorithms, key lengths, and session timeout times; Encapsulate the key in a key container and add metadata to the key container, and the metadata includes key ID, generation time, and validity period; Select a symmetric encryption algorithm to encrypt the key container and use the hardware security module to manage the encryption key; The terminal device initiates a key distribution request through the client of the key management system, and the key management system verifies the distribution request; The key management system transmits the encrypted key container to the terminal device through the secure channel, and monitors the key transmission process in real time and records the transmission log; After receiving the key container, the terminal device performs integrity verification and decrypts the key container using the pre-configured decryption key to obtain the key; When the terminal device needs to perform encryption and decryption operations, it obtains the key from the storage environment and performs operations using the corresponding encryption algorithm; When the key reaches the preset validity period, the destruction process is automatically triggered, the authorized administrator initiates a key destruction request, verifies the destruction request, and locates the key to be destroyed.

[0007] Preferably, the adopting a zero-trust architecture to continuously authenticate and authorize devices and users, and combining identity authentication methods to optimize end-to-end encryption performance through hardware acceleration specifically includes: Based on the principle of least privilege, ensure that each user and device only has the minimum privileges required to complete their tasks. Based on the principle of continuous verification, conduct continuous authentication and authorization checks on each access request; Based on business logic and security requirements, divide the network into three micro-segments: the application layer, the data layer, and the management layer. Keep secure isolation between each micro-segment and prohibit lateral movement within the network; The first factor of user authentication is recorded as the username and user password, and the password is stored using an encrypted hash algorithm; The second factor of user authentication is recorded as a dynamic token and biometrics. Use a hardware token to generate a dynamic token, and the user inputs the token value for verification. Support biometric technologies such as fingerprint and facial recognition; The third factor of user authentication is recorded as the user behavior model, and the normal behavior pattern of the user is recorded; Collect user information context, device information context, and environmental information context. The user information context includes user identity, role, and permission information. The device information context includes device type, status, and location information. The environmental information context includes information on the collection access time, location, and network status; The policy decision point makes authorization decisions based on the collected context information, conducts risk assessments on access requests, and dynamically adjusts authorization decisions; The policy enforcement point executes the access control policy according to the authorization decision of the policy decision point, allowing or denying access requests; Utilize the parallel computing power of the hardware accelerator to simultaneously process at least one encryption and decryption task, improving the task processing speed.

[0008] Compared with the prior art, the beneficial effects of the present invention are as follows: Dynamically adjust the bandwidth allocation of each frequency band according to the bandwidth utilization rate of the frequency band, improve the utilization efficiency of spectrum resources, and ensure the smooth transmission of high-definition videos. Adjust the modulation method according to the signal quality and allocate network resources, which can make full use of network resources and improve the quality and efficiency of video transmission. Predict load changes by real-time monitoring of network load and adjust the resource allocation strategy in advance, effectively avoiding video transmission problems caused by sudden load changes. By establishing a key lifecycle management system to manage the generation, distribution, use, and destruction of keys, improve the security of key management, prevent key leakage, adopt a zero-trust architecture to continuously authenticate and authorize devices and users, combine identity authentication methods, and optimize the end-to-end encryption performance through hardware acceleration, enhancing the security of the network and ensuring that only legitimate devices and users can access video data. Description of the Drawings

[0009] Figure 1Flowchart of the high-definition video transmission optimization and encryption method based on the wifi7 chip module of the present invention; Figure 2 Flowchart of the method for dynamically selecting the optimal frequency band combination for parallel transmission of the present invention; Figure 3 Flowchart of the method for adjusting the modulation mode according to the signal quality of the present invention; Figure 4 Flowchart of the method for predicting load changes by real-time monitoring of network load of the present invention; Figure 5 Flowchart of the method for dynamically adjusting the preamble puncturing pattern based on the interference situation of the present invention; Figure 6 Flowchart of the method for establishing a key lifecycle management system of the present invention; Figure 7 Flowchart of the method for continuously authenticating and authorizing devices and users by adopting a zero-trust architecture of the present invention. Detailed implementation manners

[0010] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments in the following description are only examples, and those skilled in the art can think of other obvious variations.

[0011] Refer to Figure 1 As shown, the high-definition video transmission optimization and encryption method based on the wifi7 chip module includes: Deploy network monitoring sensors to collect load data, interference data, and signal strength data of each frequency band in real time; Based on the real-time network load, interference situation, and signal strength, dynamically select the optimal frequency band combination for parallel transmission, and dynamically adjust the bandwidth allocation of each frequency band according to the bandwidth utilization rate of the frequency band; Dynamically bind at least one channel according to the network environment, adjust the modulation mode according to the signal quality, and allocate network resources; Establish a load prediction model, predict load changes by real-time monitoring of network load, and adjust the resource allocation strategy in advance; Dynamically adjust the preamble puncturing pattern based on the interference situation, shield the interfered frequency bands, and retain the available frequency bands; Generate dynamic keys through a hardware security module, and distribute them to terminal devices through a secure channel, establish a key lifecycle management system, and manage the generation, distribution, use, and destruction of keys; Adopt a zero-trust architecture to continuously authenticate and authorize devices and users, and combine identity authentication methods to optimize the end-to-end encryption performance through hardware acceleration.

[0012] Refer to Figure 2As shown, based on real-time network load, interference situation, and signal strength, the optimal frequency band combination is dynamically selected for parallel transmission, and the bandwidth allocation for each frequency band is dynamically adjusted according to the bandwidth utilization rate of the frequency band, specifically including: Analyze the time series data of the bandwidth utilization rate of each frequency band, and identify and mark the peak and trough periods therein; Draw a curve of the interference intensity varying with the frequency band, and analyze the time pattern of the interference occurrence; Statistically analyze the distribution of the signal strength and signal-to-noise ratio of each frequency band, and evaluate the stability of the signal quality; Based on the device location and the collected signal strength data, establish a signal attenuation model to predict the signal coverage; Establish a frequency band scoring model, with the load indicators determined as the bandwidth utilization rate, the number of device connections, and the degree of traffic congestion, the interference indicators determined as the interference intensity, the proportion of interfering frequency bands, and the interference duration, and the signal quality indicators determined as the signal strength, the signal-to-noise ratio, and the signal strength fluctuation range; Based on historical data, analyze the correlation between each scoring indicator and the transmission performance, and preset the corresponding weights for each scoring indicator; List at least one frequency band combination, exclude the combinations containing interfering frequency bands, and score and rank each frequency band combination according to the frequency band scoring model; Evaluate the synergy caused by the interference situation between frequency bands and the performance improvement during parallel transmission, and select the combination with the optimal comprehensive performance.

[0013] Steps for establishing the signal attenuation model: Collect the location information of the device such as GPS coordinates or relative position and the signal strength data of the corresponding frequency band. Based on the collected data, establish a signal attenuation model such as the free space path loss model or the log-distance path loss model to predict the signal coverage; According to the frequency band scoring and the bandwidth utilization rate, dynamically adjust the bandwidth allocation strategy for each frequency band, allocate more bandwidth to the frequency bands with high scores and low utilization rates, and reduce the bandwidth of the frequency bands with low scores and high utilization rates.

[0014] Refer to Figure 3 As shown, dynamically bind at least one channel according to the network environment, adjust the modulation method according to the signal quality, and allocate network resources, specifically including: Measure the received signal strength indication of each channel, and evaluate the signal coverage and quality; Based on the change of the network environment, dynamically bind the terminal device to the optimal channel or the standby channel through software configuration; Statistically analyze the bit error rate and packet loss rate during the transmission process, and set the threshold ranges for the bit error rate and packet loss rate indicators respectively based on historical data; According to the set threshold ranges, conduct the division of the signal quality, where the signal quality includes excellent, good, average, and poor; Select a modulation method that matches the signal quality level; When the signal quality is excellent, select 64-QAM to improve the transmission rate; When the signal quality is good, select 16-QAM to improve the noise resistance performance; When the signal quality is average, select QPSK to reduce the difficulty of data transmission; When the signal quality is poor, select BPSK to improve the transmission reliability; Collect the bandwidth requirements and latency requirements of each user or device, and count the total load, the load of each channel, and the number of device connections on the current network; Based on the importance and bandwidth requirements of the user or device, set at least one priority level to preferentially meet the resource requirements of high-priority users or devices; Dynamically adjust the resource allocation strategy based on changes in network load and user requirements.

[0015] When the signal quality is excellent, selecting 64-QAM can transmit 6 bits of information in one symbol. Compared with lower-order modulation methods, it can significantly improve the transmission rate. When the signal quality is good, selecting 16-QAM can transmit 4 bits of information in one symbol. Compared with 64-QAM, it has better noise resistance performance and can maintain a high transmission efficiency when the signal quality drops slightly. When the signal quality is average, selecting QPSK can transmit 2 bits of information in one symbol. Its modulation and demodulation are relatively simple, which can reduce the difficulty of data transmission and adapt to the environment with average signal quality. When the signal quality is poor, selecting BPSK can transmit 1 bit of information in one symbol. Although the transmission rate is low, its anti-interference ability is the strongest, which can ensure the reliable transmission of data when the signal quality is very poor.

[0016] Refer to Figure 4 As shown, establish a load prediction model, and predict the load change by real-time monitoring of the network load. Adjusting the resource allocation strategy in advance specifically includes: Collect historical network load data and record timestamps for each data record; Remove outliers, missing values, and duplicate data from the load data, and perform normalization processing on the remaining data to obtain a load data set; Construct an autoregressive integrated moving average (ARIMA) model for load prediction. The ARIMA model includes an autoregressive model part, a differencing process part, and a moving average model part; The autoregressive model part eliminates the influence of the observed values in at least one past period on the current value by processing the autoregressive part of the time series; The difference process part makes the non-stationary time series stationary through second-order difference processing, eliminating the trends and seasonal factors in the time series; The moving average model part eliminates the influence of past prediction errors on the current value by processing the moving average part of the time series; The load dataset is divided into a training set, a validation set, and a test set. The training set is used to train the model, adjust the model parameters to optimize the prediction performance, and the validation set is used to validate the model to evaluate its generalization ability; The trained load prediction model is used to predict the real-time data to obtain the load change trend in at least a period of time in the future; Based on the network load prediction results, set the threshold range for resource allocation; Formulate at least one resource allocation strategy under the load condition, increase the bandwidth, adjust the number of device connections, and optimize the traffic routing.

[0017] The autoregressive model part determines the autoregressive order p, that is, the influence of the observations in the past p periods on the current value, by analyzing the autocorrelation of the historical load data; the difference process part makes the non-stationary time series reach a stationary state through first-order or second-order difference processing, eliminating the trends and seasonal factors in the time series, and determines the difference order d; the moving average model part determines the moving average order q, that is, the influence of the prediction errors in the past q periods on the current value, by analyzing the autocorrelation of the prediction errors.

[0018] Refer to Figure 5 As shown, dynamically adjust the preamble puncturing pattern based on the interference situation, shield the interfered frequency bands, and retain the available frequency bands, which specifically includes: Real-time collect the interference intensity, interference frequency range, and interference duration data of each frequency band; Identify the interference source type through signal feature analysis, and the interference source type includes co-channel interference, adjacent-channel interference, and external device interference; Evaluate the interference degree of each frequency band based on the interference intensity, duration, and influence range; Set the puncturing positions corresponding to the interfered frequency bands in the preamble, shield all signals on the interfered frequency bands, and identify the available frequency bands based on the interference analysis results; Adjust the puncturing pattern, retain the preamble information and communication resources on the available frequency bands, and allocate them to at least one user or device according to actual needs.

[0019] According to the interference degree evaluation result, determine the interfered frequency band, and set the puncture position corresponding to the interfered frequency band in the preamble. The preamble is a part of the Wi-Fi signal and is used for signal synchronization and channel estimation at the receiving end. If it is determined that the frequency band of 5.2 GHz - 5.3 GHz is interfered, perform puncture processing on the signal position corresponding to this frequency range in the preamble, that is, shield all signals on this frequency band. Specifically, when implementing, the preamble generation algorithm can be modified. When generating the preamble, set the signal part corresponding to the interfered frequency band to zero or use a specific marking method so that the receiving end can identify and ignore these signals.

[0020] Refer to Figure 6 As shown, generate a dynamic key through the hardware security module and distribute it to the terminal device through a secure channel. Establish a key lifecycle management system to manage the generation, distribution, use, and destruction of keys, specifically including: Deploy a hardware security module to prevent unauthorized access and perform initialization configuration on the hardware security module, setting an administrator password and security policies; Based on security standards and business requirements, select the generated key length and define the conditions and frequencies for key generation; The hardware security module uses an internal true random number generator to generate key materials and uses a key derivation function to derive the final key from the key materials; Select the Secure Sockets Layer cryptographic communication framework encryption channel as the secure channel for key distribution and configure digital certificates for both ends of the channel; Configure the security parameters of the encryption channel. The security parameters include encryption algorithms, key lengths, and session timeout times; Encapsulate the key in a key container and add metadata to the key container. The metadata includes key ID, generation time, and validity period; Select a symmetric encryption algorithm to encrypt the key container and use the hardware security module to manage the encryption key; The terminal device initiates a key distribution request through the client of the key management system, and the key management system verifies the distribution request; The key management system transmits the encrypted key container to the terminal device through the secure channel and monitors the key transmission process in real time, recording the transmission log; After receiving the key container, the terminal device performs integrity verification and decrypts the key container using the pre-configured decryption key to obtain the key; When the terminal device needs to perform encryption and decryption operations, it obtains the key from the storage environment and performs operations using the corresponding encryption algorithm; When the key reaches the preset validity period, the destruction process is automatically triggered, authorizing the administrator to initiate a key destruction request, verifying the destruction request, and locating the key to be destroyed.

[0021] The parameters contained in the key derivation function are as follows: DK is the finally generated derived key, PRF is the pseudorandom function, Password is the original password used to generate the key, Salt is the salt value, a random number or random bit sequence used to increase the security of the password, c is the number of iterations, indicating the number of repeated calculations of the password hash, and dkLen is the expected key length in bits. The key derivation function concatenates the password and the salt value as the initial input of the pseudorandom function, and derives the key through multiple rounds of iterative calculations. In each round of iteration, the result of the previous round is used as the input and passed to the pseudorandom function together with the password, the salt value, and the current iteration number. For each round of iteration i, the exclusive-or chain traversed c times is calculated, and the results of each round of iteration are concatenated to form the final derived key DK.

[0022] Refer to Figure 7 As shown, the zero-trust architecture is adopted to continuously authenticate and authorize devices and users. Combining identity authentication methods, the end-to-end encryption performance is optimized through hardware acceleration, which specifically includes: Based on the principle of least privilege, ensure that each user and device only has the minimum privileges required to complete their tasks. Based on the principle of continuous verification, conduct continuous identity authentication and authorization checks on each access request; Based on business logic and security requirements, the network is divided into three micro-segments: the application layer, the data layer, and the management layer. There is secure isolation between each micro-segment, and lateral movement within the network is prohibited; The first factor of user authentication is recorded as the username and user password, and the password is stored using an encrypted hash algorithm; The second factor of user authentication is recorded as the dynamic token and biometrics. The dynamic token is generated using a hardware token, and the user inputs the token value for verification, and biometric technologies such as fingerprint and face recognition are supported; The third factor of user authentication is recorded as the user behavior model, recording the normal behavior patterns of users; Collect user information context, device information context, and environmental information context. The user information context includes user identity, role, and permission information. The device information context includes device type, status, and location information. The environmental information context includes the collected access time, location, and network status information; The policy decision point makes authorization decisions based on the collected context information, conducts risk assessments on access requests, and dynamically adjusts authorization decisions; The policy enforcement point executes the access control policy according to the authorization decision of the policy decision point, allowing or denying access requests; Utilize the parallel computing power of the hardware accelerator to simultaneously process at least one encryption and decryption task, improving the task processing speed.

[0023] The principle of least privilege evaluates the permissions of all users and devices, clarifies the tasks they need to complete and the corresponding set of minimum permissions, and uses an access control list or a role-based access control system to ensure that users and devices only have the minimum permissions required to complete the tasks. Regularly review the permission allocation to ensure that the permissions are consistent with the actual requirements; the principle of continuous verification embeds a continuous verification mechanism in all access requests. Through continuous authentication and authorization checks, use real-time monitoring tools to detect abnormal access behaviors, such as access during non-working hours, unconventional operation sequences, etc., and trigger the re-verification process.

[0024] Furthermore, this solution also proposes a computer-readable storage medium, on which a computer-readable program is stored. When the computer-readable program is called, it executes the above-mentioned high-definition video transmission optimization and encryption method based on the wifi7 chip module.

[0025] It can be understood that the storage medium can be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; an optical medium such as a DVD; or a semiconductor medium such as a solid-state drive SolidStateDisk, SSD, etc.

[0026] In summary, the advantages of the present invention are as follows: Dynamically adjust the bandwidth allocation of each frequency band according to the bandwidth utilization rate of the frequency band, improve the utilization efficiency of spectrum resources, and ensure the smooth transmission of high-definition video. Adjust the modulation method according to the signal quality and allocate network resources, which can make full use of network resources and improve the quality and efficiency of video transmission. Predict the load change by real-time monitoring of the network load, and adjust the resource allocation strategy in advance to effectively avoid video transmission problems caused by sudden load changes. By establishing a key lifecycle management system to manage the generation, distribution, use, and destruction of keys, the security of key management is improved, and key leakage is prevented. Adopt a zero-trust architecture to continuously authenticate and authorize devices and users, combined with identity authentication methods, and optimize the end-to-end encryption performance through hardware acceleration, enhancing the security of the network and ensuring that only legitimate devices and users can access video data.

[0027] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art of this industry should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification is only the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection required by the present invention is defined by the appended claims and their equivalents.

Claims

1. An optimization and encryption method for high-definition video transmission based on a Wi-Fi 7 chip module, characterized in that, Including: Deploy network monitoring sensors to collect load data, interference data, and signal strength data of each frequency band in real time; Based on real-time network load, interference situation, and signal strength, dynamically select the optimal frequency band combination for parallel transmission, and dynamically adjust the bandwidth allocation of each frequency band according to the bandwidth utilization rate of the frequency band; Dynamically bind at least one channel according to the network environment, adjust the modulation method according to the signal quality, and allocate network resources; Establish a load prediction model, predict load changes by real-time monitoring of network load, and adjust the resource allocation strategy in advance; Dynamically adjust the preamble puncturing pattern based on the interference situation, shield the interfered frequency bands, and retain the available frequency bands; Generate dynamic keys through a hardware security module and distribute them to terminal devices through a secure channel, and establish a key lifecycle management system to manage the generation, distribution, use, and destruction of keys; Adopt a zero-trust architecture to continuously authenticate and authorize devices and users, and combine identity authentication methods to optimize end-to-end encryption performance through hardware acceleration.

2. The high-definition video transmission optimization and encryption method based on the wifi7 chip module according to claim 1, wherein The dynamically selecting the optimal frequency band combination for parallel transmission based on real-time network load, interference situation, and signal strength, and dynamically adjusting the bandwidth allocation of each frequency band according to the bandwidth utilization rate of the frequency band specifically includes: Analyze the time series data of the bandwidth utilization rate of each frequency band, identify and mark the peak periods and trough periods therein; Draw a curve of interference intensity varying with the frequency band, and analyze the time pattern of interference occurrence; Statistically analyze the distribution of signal strength and signal-to-noise ratio of each frequency band, and evaluate the stability of signal quality; Based on the device location and the collected signal strength data, establish a signal attenuation model to predict the signal coverage; Establish a frequency band scoring model, with the load indicators determined as bandwidth utilization rate, number of device connections, and traffic congestion degree, the interference indicators determined as interference intensity, proportion of interfered frequency bands, and interference duration, and the signal quality indicators determined as signal strength, signal-to-noise ratio, and signal strength fluctuation range; Based on historical data, analyze the correlation between each scoring indicator and transmission performance, and preset the corresponding weights for each scoring indicator; List at least one frequency band combination, exclude the combinations containing interfered frequency bands, and score and rank each frequency band combination according to the frequency band scoring model; Evaluate the synergy caused by the interference situation between frequency bands and the performance improvement during parallel transmission, and select the combination with the optimal comprehensive performance.

3. The high-definition video transmission optimization and encryption method based on the wifi7 chip module according to claim 2, wherein, The dynamically binding at least one channel according to the network environment, adjusting the modulation method according to the signal quality, and allocating network resources specifically includes: Measure the received signal strength indication of each channel and evaluate the signal coverage and quality; Based on the change of the network environment, dynamically bind the terminal device to the optimal channel or standby channel through software configuration; Statistically analyze the bit error rate and packet loss rate during the transmission process, and set threshold ranges for the bit error rate and packet loss rate indicators respectively based on historical data; According to the set threshold ranges, conduct signal quality division, and the signal quality includes excellent, good, average, and poor; Based on the signal quality level, select the modulation method that matches it; Select 64-QAM when the signal quality is excellent to improve the transmission rate; Select 16-QAM when the signal quality is good to improve the anti-noise performance; Select quadrature phase shift keying when the signal quality is average to reduce the difficulty of data transmission; Select binary phase shift keying when the signal quality is poor to improve transmission reliability; Collect the bandwidth requirements and latency requirements of each user or device, and count the total load, the load of each channel, and the number of device connections on the current network; Based on the importance and bandwidth requirements of the user or device, set at least one priority to preferentially meet the resource requirements of high-priority users or devices; Dynamically adjust the resource allocation strategy based on changes in network load and user requirements.

4. The high-definition video transmission optimization and encryption method based on the wifi7 chip module according to claim 3, characterized in that, The establishment of the load prediction model to predict load changes by real-time monitoring of network load and adjust the resource allocation strategy in advance specifically includes: Collect historical network load data and timestamp each data record; Remove outliers, missing values, and duplicate data from the load data, and normalize the remaining data to obtain a load data set; Construct an autoregressive integrated moving average model for load prediction, and the autoregressive integrated moving average model includes an autoregressive model part, a differencing process part, and a moving average model part; The autoregressive model part eliminates the influence of observations in the past at least one period on the current value by processing the autoregressive part of the time series; The differencing process part makes the non-stationary time series stationary through second-order differencing to eliminate trends and seasonal factors in the time series; The moving average model part eliminates the influence of past prediction errors on the current value by processing the moving average part of the time series; Divide the load data set into a training set, a validation set, and a test set, use the training set to train the model, adjust the model parameters to optimize the prediction performance, use the validation set to validate the model, and evaluate the generalization ability of the model; Use the trained load prediction model to predict real-time data to obtain the load change trend in at least a future period of time; Based on the network load prediction result, set the threshold range for resource allocation; Formulate at least one resource allocation strategy under different load conditions, increase bandwidth, adjust the number of device connections, and optimize traffic routing.

5. The high-definition video transmission optimization and encryption method based on the wifi7 chip module according to claim 4, characterized in that, The dynamic adjustment of the preamble puncturing pattern based on the interference situation to block the interfered frequency band and retain the available frequency band specifically includes: Real-time collect the interference intensity, interference frequency range, and interference duration data of each frequency band; Identify the type of interference source through signal feature analysis, and the type of interference source includes co-channel interference, adjacent-channel interference, and external device interference; Based on the interference intensity, duration, and influence range, evaluate the interference degree of each frequency band; Set the puncturing positions corresponding to the interfered frequency bands in the preamble to block all signals on the interfered frequency bands, and based on the interference analysis result, identify the available frequency bands; Adjust the puncturing pattern to retain the preamble information and communication resources on the available frequency bands and allocate them to at least one user or device according to actual needs.

6. The high-definition video transmission optimization and encryption method based on the wifi7 chip module according to claim 5, characterized in that, The generation of dynamic keys through the hardware security module and the distribution to the terminal device through the secure channel, and the establishment of a key lifecycle management system to manage the generation, distribution, use, and destruction of keys specifically includes: Deploy a hardware security module to prevent unauthorized access, and perform initialization configuration on the hardware security module, set the administrator password and security policy; Based on security standards and business requirements, select the generated key length, and define the conditions and frequencies for key generation; The hardware security module uses an internal true random number generator to generate key material and derives the final key from the key material using a key derivation function; Select the Secure Sockets Layer (SSL) cryptographic communication framework encryption channel as the secure channel for key distribution, and configure digital certificates for both ends of the channel; Configure the security parameters of the encryption channel, where the security parameters include the encryption algorithm, key length, and session timeout; Encapsulate the key in a key container and add metadata to the key container, where the metadata includes the key ID, generation time, and validity period; Select a symmetric encryption algorithm to encrypt the key container and use the hardware security module to manage the encryption key; The terminal device initiates a key distribution request through the client of the key management system, and the key management system verifies the distribution request; The key management system transmits the encrypted key container to the terminal device through the secure channel, and monitors the key transmission process in real time and records the transmission log; After receiving the key container, the terminal device performs integrity verification and decrypts the key container using the pre-configured decryption key to obtain the key; When the terminal device needs to perform encryption and decryption operations, it obtains the key from the storage environment and performs operations using the corresponding encryption algorithm; When the key reaches the preset validity period, the destruction process is automatically triggered, and the authorized administrator initiates a key destruction request, verifies the destruction request, and locates the key to be destroyed; 7. The high-definition video transmission optimization and encryption method based on the wifi7 chip module according to claim 6, characterized in that, The continuous authentication and authorization of devices and users using the zero-trust architecture, combined with the identity authentication method, and the end-to-end encryption performance optimization through hardware acceleration specifically include: Based on the principle of least privilege, ensure that each user and device only has the minimum privilege required to complete their tasks. Based on the principle of continuous verification, perform continuous identity authentication and authorization checks on each access request; Based on business logic and security requirements, divide the network into three micro-segments: the application layer, the data layer, and the management layer. Keep secure isolation between each micro-segment and prohibit lateral movement within the network; The first factor of user authentication is recorded as the username and user password, and the password is stored using an encrypted hash algorithm; The second factor of user authentication is recorded as a dynamic token and biometrics. Use a hardware token to generate the dynamic token, and the user enters the token value for verification, and support biometric technologies such as fingerprint and facial recognition; The third factor of user authentication is recorded as the user behavior model, which records the normal behavior patterns of users; Collect user information context, device information context, and environmental information context. The user information context includes user identity, role, and permission information. The device information context includes device type, status, and location information. The environmental information context includes the collected access time, location, and network status information; Based on the collected context information, the policy decision point makes authorization decisions, conducts risk assessments on access requests, and dynamically adjusts authorization decisions; The policy enforcement point executes the access control policy according to the authorization decision of the policy decision point, allowing or denying access requests; Utilize the parallel computing power of the hardware accelerator to process at least one encryption and decryption task simultaneously, thereby improving the task processing speed.

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