WIFI6 wireless channel binding optimization method and system and storage medium

Abstract

The invention relates to the technical field of communication, in particular to a WIFI6 wireless channel binding optimization method and system and a storage medium. The optimization method comprises the following steps: starting an ultrahigh frequency width mode between the wireless router and at least one terminal, and negotiating available main channels and auxiliary channels at the same time; the wireless router dynamically monitors load conditions of the main channel and the auxiliary channel so as to identify a potential channel congestion problem; when the congestion of the auxiliary channel is detected, the wireless router activates a preamble tunneling mechanism, and directly places one or more busy auxiliary channel subcarriers in an null state in an orthogonal frequency division multiple access (OFDMA) transmission process so as to be compatible with an original transmission node existing on the auxiliary channel. According to the invention, by introducing the WIFI6 wireless channel binding optimization method, the data transmission efficiency and the network stability under the condition of network congestion are improved.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and specifically to a WIFI6 wireless channel binding optimization method, system and storage medium. Background Art

[0002] Wi-Fi uses high-frequency signals to transmit information. High-frequency signals are defined by the ISM (Industrial Scientific Medical) frequency band of the International Telecommunication Union Radiocommunication Bureau. The protocol stipulates that the width of each channel is 20MHz. The transmission capacity of a 20MHz channel is limited. If you want to improve the transmission capacity, the direct approach is to widen the channel.

[0003] The 802.11n protocol introduces the concept of channel bonding, which binds two adjacent 20MHz channels into a 40MHz channel for use, so that the data transmission rate can be doubled. The bonded channel is not simply the superposition of two channels. It removes some of the intermediate protection intervals and merges them into a wide channel for use. One of these two channels is called the main channel and the other is the auxiliary channel. The difference between the main channel and the auxiliary channel is that management messages such as Beacon frames are sent on the main channel while the auxiliary channel is not sent. The main channel is more important than the auxiliary channel. The WIFI6 protocol introduces 80MHz, 160MHz and 80+80MHz. For the 80M channel, the 40M channel where the main channel is located is the main 40M channel. The same is true for 160M. The 80M channel where the main channel is located is the main 80M channel.

[0004] After completing channel bonding, it is necessary to detect on both the main channel and the auxiliary channel at the same time to determine whether the channel is busy. This will lead to the situation of how to deal with the remaining channels after a certain 20M channel is congested. After detecting congestion, 11n and 11ac handle it differently. 11n uses a static channel management mechanism. If any 20M channel is congested, it will not be used as a whole. That is, if the auxiliary channel is congested, the main channel will not be used for transmission. 11ac uses a dynamic channel management mechanism. If the auxiliary channel is congested, it will be transmitted on the main channel. As the rate increases, the disadvantages of channel bonding are also emerging. Both static channel management and dynamic channel management waste spectrum resources, especially when the channels next to the main 20M channel are busy, all auxiliary channels will be directly abandoned as a whole. Summary of the invention

[0005] The present invention provides a WIFI6 wireless channel binding optimization method, system and storage medium to solve the technical problem of low data transmission efficiency in a congested network.

[0006] The technical solution of the present invention to solve the above technical problems is as follows:

[0007] A WIFI6 wireless channel binding optimization method is provided, and the optimization method comprises the following steps:

[0008] Enable the ultra-high bandwidth mode between the wireless router and at least one terminal, and negotiate the available primary channel and auxiliary channel;

[0009] The wireless router dynamically monitors the load status of the primary and secondary channels to identify potential channel congestion issues;

[0010] When the auxiliary channel is detected to be congested, the wireless router activates the Preamble Puncturing mechanism, which directly puts the busy single or multiple auxiliary channel subcarriers into the Null state during the Orthogonal Frequency Division Multiple Access (OFDMA) transmission process to be compatible with the existing transmission nodes on the auxiliary channel.

[0011] The wireless router intelligently selects and binds the remaining discontinuous idle channel subcarriers for efficient data transmission while ensuring that there is no negative impact on the main channel;

[0012] Adopting adaptive channel allocation algorithm, the channel bonding mode is adjusted in real time according to network conditions to maximize network throughput and minimize latency.

[0013] Furthermore, the steps of using the adaptive channel allocation algorithm include:

[0014] Based on the real-time load rate and historical data of the main channel and auxiliary channel, a channel quality assessment model is constructed to predict the possibility of channel congestion;

[0015] Through the channel quality assessment model, the expected performance indicators of each potential channel bonding mode are calculated, including throughput, delay, and packet loss rate;

[0016] The optimal channel bonding mode is determined by using a weighted multi-objective optimization algorithm. The weighted value is dynamically adjusted based on user demand. When the user is sensitive to delay, the weighted value of delay will be increased.

[0017] The wireless router implements the optimal channel bonding mode and continuously monitors the performance of the optimal channel bonding mode to make timely adjustments;

[0018] The expression of weighted multi-objective optimization algorithm is:

[0019] Where X represents different channel bonding modes, α, β, and γ are weighted values ​​of throughput, delay, and packet loss rate, respectively. and are the actual throughput and the maximum throughput respectively, and are the target delay and actual delay respectively, E is the packet loss rate, and α+β+γ=1.

[0020] Furthermore, the Preamble Puncturing mechanism optimizes the puncturing position and number through an adaptive puncturing algorithm. The adaptive puncturing algorithm selects the subcarriers to be punctured based on the channel congestion level and network load conditions to ensure that as many idle subcarriers as possible are used for data transmission in the case of channel congestion. The steps of the adaptive puncturing algorithm include:

[0021] Calculate the congestion level of the channel. The calculation formula for the congestion level is:

[0022] Among them, C represents the channel congestion level, N busy Indicates the number of busy subcarriers detected, N total Indicates the total number of subcarriers in the channel;

[0023] Determine the puncturing position and quantity according to the channel congestion level. When the channel congestion level exceeds a preset threshold, select the busiest continuous subcarriers for puncturing, and ensure that the puncturing position and quantity do not affect the subcarriers of the main channel.

[0024] Evaluate the performance of the punctured channel and calculate the available bandwidth of the channel:

[0025] B available =B total -N punctured ·B subcarrier , where B available represents the available bandwidth, B total Represents the total bandwidth of the channel, N punctured Indicates the number of punctured subcarriers, B subcarrier Indicates the bandwidth of each subcarrier.

[0026] Furthermore, the wireless router determines the optimal subcarrier bundling scheme through an intelligent selection algorithm. The intelligent selection algorithm calculates the performance indicators of different bundling schemes based on the location and quality of the remaining idle subcarriers and selects the best scheme. The steps of the intelligent selection algorithm include:

[0027] Collect information about all remaining idle subcarriers, including location, bandwidth, signal-to-noise ratio, and interference level;

[0028] Based on the subcarrier information, the expected bandwidth and expected throughput of each bonding solution are calculated using the following formula:

[0029] Among them, T expected represents the expected throughput, I represents the set of all considered subcarriers, and B irepresents the bandwidth of the i-th subcarrier, SNR i represents the signal-to-noise ratio of the i-th subcarrier, I i represents the interference level of the i-th subcarrier;

[0030] The bonding scheme with the highest expected throughput is selected for data transmission.

[0031] Furthermore, the wireless router uses an adaptive channel monitoring algorithm to dynamically evaluate the channel load. The adaptive channel monitoring algorithm predicts the future channel load conditions based on real-time data transmission volume and historical load data to identify potential congestion problems in advance. The steps of the adaptive channel monitoring algorithm include:

[0032] Collect historical load data for each channel, including transmission volume, occupancy time, and congestion times;

[0033] Build a channel load prediction model based on historical load data;

[0034] Monitor the transmission volume and occupancy time of the current channel in real time, and use the channel load prediction model to estimate the future channel load status;

[0035] When it is detected that the channel load will exceed the preset threshold in the future, the Preamble Puncturing mechanism is activated in advance to avoid congestion.

[0036] Furthermore, the Preamble Puncturing mechanism also includes a channel interference detection algorithm for accurately identifying interference sources in the channel. The channel interference detection algorithm determines the type and intensity of interference by analyzing the signal strength and noise level of the channel, thereby more accurately selecting the puncturing location. The steps of the channel interference detection algorithm include:

[0037] Detect the signal strength and noise level of each subcarrier and calculate the channel interference index:

[0038] Among them, I channel Indicates the channel interference index max(SNR i ) and min(SNR i ) represent the maximum and minimum signal-to-noise ratio in the channel, σ noise represents the standard deviation of noise in the channel;

[0039] According to the channel interference index, determine the location and strength of the interference source;

[0040] The subcarrier with the highest interference intensity is selected for puncturing to reduce the impact on network performance.

[0041] Furthermore, the adaptive channel allocation algorithm also includes a channel allocation priority mechanism. The channel allocation priority mechanism dynamically adjusts the priority of channel binding according to the transmission requirements of the terminal device and the network status to ensure that high-priority devices can maintain transmission performance even in congestion. The steps of the priority mechanism include:

[0042] Assign a priority value to each terminal device based on the device's transmission requirements and device type;

[0043] When channel congestion is detected, the channel subcarriers with less congestion are preferentially selected to meet the transmission needs of high-priority devices;

[0044] The priority value is calculated as follows:

[0045] P i =w1·R i +w2·Q i +w3·D i , where P i represents the priority value of the i-th terminal device, w1, w2 and w3 are the weighted values ​​of bandwidth requirement, delay requirement and device type respectively, R i represents the bandwidth requirement of the i-th terminal device, Q i represents the delay requirement of the i-th terminal device, D i represents the type weight of the i-th terminal device, and w1+w2+w3=1.

[0046] Furthermore, the optimization method also includes using multi-user MIMO (MU-MIMO) technology to improve channel utilization through spatial multiplexing of multi-antenna channels. When some channels are congested, the wireless router uses uncongested antennas for data transmission.

[0047] On the other hand, a WIFI6 wireless channel binding optimization system is provided, and the optimization system includes:

[0048] Channel negotiation module, supporting 160MHz ultra-high bandwidth mode, used for negotiation between wireless routers and terminals on available primary and secondary channels;

[0049] Channel monitoring module, dynamically monitors the load status of the main channel and auxiliary channel to identify potential channel congestion problems;

[0050] Preamble Puncturing module: When the auxiliary channel is congested, the Preamble Puncturing mechanism is activated to put the busy single or multiple auxiliary channel subcarriers into the null state to be compatible with the existing transmission nodes on the channel.

[0051] The channel selection module intelligently selects and binds the remaining discontinuous idle channel subcarriers for efficient data transmission while ensuring that there is no negative impact on the main channel;

[0052] Adaptive channel allocation module, which adjusts the channel bonding mode in real time based on network conditions to maximize network throughput and minimize latency;

[0053] The channel negotiation optimization module ensures that there is no need to re-negotiate the channel between the wireless router and the terminal when the channel binding state changes, which is used to improve network performance.

[0054] On the other hand, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a computer processor, the above-mentioned WIFI6 wireless channel binding optimization method can be implemented.

[0055] The beneficial effects of the present invention are:

[0056] The present invention improves the data transmission efficiency and network stability under network congestion by introducing a WIFI6 wireless channel binding optimization method. In the prior art, both the static channel management mechanism of 11n and the dynamic channel management mechanism of 11ac have the problem of wasting spectrum resources, especially when the auxiliary channels next to the main 20MHz channel are busy, all auxiliary channels will be directly abandoned as a whole, resulting in a sharp reduction in the actual available bandwidth. The present invention activates the Preamble Puncturing mechanism to directly put a busy single or multiple auxiliary channel subcarriers into a null state during the OFDMA transmission process, while the remaining discontinuous idle channel subcarriers continue to perform normal data transmission, thereby avoiding the waste of idle channels caused by inefficient protocol operation mechanisms.

[0057] In addition, the present invention adopts an adaptive channel allocation algorithm, which can adjust the channel binding mode in real time according to the actual situation of the network to maximize network throughput and minimize latency, thereby improving the overall performance of the network. In the high-frequency ISM band, the present invention can manage channel resources more effectively, avoiding the problem of a significant decrease in overall transmission efficiency due to congestion of individual channels. Through these technical means, the present invention not only improves the data transmission performance of the network under congested conditions, but also enhances the stability of the network, providing users with a better wireless network experience. At the same time, the dynamic change of the channel binding state can be achieved without re-negotiation of the channel, which further simplifies network management and improves the response speed of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 This is a flowchart of a WIFI6 wireless channel binding optimization method in one embodiment of the present invention.

[0059] Figure 2 This is a logic diagram of a WIFI6 wireless channel binding optimization method in one embodiment of the present invention.

[0060] Figure 3 FIG. 4 is a load rate diagram of a channel quality assessment model in an embodiment of the present invention.

[0061] Figure 4 It is a performance diagram of different binding modes of the adaptive channel allocation algorithm in one embodiment of the present invention.

[0062] Figure 5 Schematic diagram of puncturing position selection of the Preamble Puncturing mechanism in one embodiment of the present invention.

[0063] Figure 6 The figure is a schematic diagram of a channel allocation priority mechanism in one embodiment of the present invention. DETAILED DESCRIPTION

[0064] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0065] The term "comprise" and any variation thereof in the specification and claims of the present application are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units need not be limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. In addition, the use of "and / or" in the specification and claims to indicate at least one of the connected objects, such as A and / or B, means including A alone, B alone, and A and B.

[0066] In the embodiments of the present invention, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0067] The present invention provides the following preferred embodiments:

[0068] Embodiment 1

[0069] In order to solve the problem in the prior art that frequent renegotiation of channels in the case of channel congestion leads to decreased network performance, this embodiment proposes a WIFI6 wireless channel binding optimization method to improve channel utilization and network stability.

[0070] like Figure 1 and Figure 2 As shown, this embodiment provides a WIFI6 wireless channel binding optimization method, which specifically includes the following steps:

[0071] S100: Enable ultra-high bandwidth mode between the wireless router and at least one terminal, and negotiate available primary channels and auxiliary channels.

[0072] S200, the wireless router dynamically monitors the load status of the primary channel and the secondary channel to identify potential channel congestion problems.

[0073] S300. When congestion of the auxiliary channel is detected, the wireless router activates the Preamble Puncturing mechanism, and directly places the busy single or multiple auxiliary channel subcarriers in the null state during the orthogonal frequency division multiple access (OFDMA) transmission process to be compatible with the existing transmission nodes on the auxiliary channel.

[0074] S400, wireless router intelligently selects and binds the remaining discontinuous idle channel subcarriers for efficient data transmission while ensuring that there is no negative impact on the main channel.

[0075] S500 uses an adaptive channel allocation algorithm to adjust the channel bonding mode in real time according to network conditions to maximize network throughput and minimize latency.

[0076] Specifically, an ultra-high bandwidth mode, such as a 160MHz bandwidth mode, is enabled between the wireless router and at least one terminal, and the available main channels and auxiliary channels are negotiated. In actual applications, the wireless router and the terminal decide whether to support the 160MHz bandwidth mode and which main channels and auxiliary channels can be used for binding by exchanging channel capability information. It should be understood that the negotiation process of the main channel and the auxiliary channel is completed through the channel negotiation protocol, which ensures the effective use of the main channel and the auxiliary channel and avoids unnecessary channel occupation. By enabling the 160MHz bandwidth mode, this method can significantly improve the bandwidth of data transmission, thereby providing a better user experience in high-flow scenarios.

[0077] Furthermore, the wireless router dynamically monitors the load status of the main channel and the auxiliary channel to identify potential channel congestion problems. Dynamic monitoring is achieved through indicators such as channel utilization, channel interference level, and the activity level of terminal devices. The wireless router regularly collects these indicators and analyzes them through the data processing module to evaluate the channel load status in real time. It can be understood that this dynamic monitoring mechanism can detect channel congestion in a timely manner and provide accurate data support for subsequent channel optimization. When it is detected that the load rate of a sub-channel exceeds the preset threshold, the wireless router will trigger further optimization measures to ensure that the network performance will not be degraded due to channel congestion.

[0078] Furthermore, when congestion in the auxiliary channel is detected, the wireless router activates the Preamble Puncturing mechanism. Specifically, during the orthogonal frequency division multiple access (OFDMA) transmission process, the wireless router places the detected busy auxiliary channel subcarriers in a null state to be compatible with the existing transmission nodes on the auxiliary channel. Through the Preamble Puncturing mechanism, the wireless router can avoid the impact of auxiliary channel congestion on the overall network performance while maintaining compatibility with existing transmission nodes. It should be understood that this mechanism can not only reduce interference, but also ensure the continuity of data transmission.

[0079] Furthermore, the wireless router intelligently selects and binds the remaining discontinuous idle channel subcarriers for efficient data transmission while ensuring that there is no negative impact on the main channel. The intelligent selection algorithm calculates the expected performance indicators of each binding scheme based on parameters such as the position of the remaining idle subcarriers, signal-to-noise ratio (SNR), and interference level, and selects the optimal scheme for implementation. It can be understood that this intelligent selection mechanism can make full use of idle resources in the network, improve data transmission efficiency, avoid negative impact on the main channel, and ensure the overall performance of the network.

[0080] Furthermore, an adaptive channel allocation algorithm is used to adjust the channel bonding mode in real time according to the network conditions to maximize network throughput and minimize latency. The adaptive channel allocation algorithm collects channel load data and historical data in real time, builds a channel quality assessment model, predicts the possibility of channel congestion, and calculates the expected performance indicators of different channel bonding modes, such as Figure 3 and Figure 4 As shown. Through the weighted multi-objective optimization algorithm, the optimal channel bonding mode is determined, and the channel bonding strategy is adjusted in real time. It should be understood that the adaptive channel allocation algorithm can dynamically optimize the channel bonding according to the network conditions, thereby maintaining the efficient and stable operation of the network under different network environments and terminal device requirements.

[0081] Furthermore, the wireless router and the terminal do not need to renegotiate the channel to achieve dynamic changes in the channel binding state, thereby improving the overall performance and stability of the network. Through this mechanism, the wireless router can automatically adjust the channel binding state after detecting channel congestion and optimizing it, without having to renegotiate the channel with the terminal. It can be understood that this not only simplifies the channel management process, but also reduces network interruptions and performance degradation caused by renegotiating the channel. Furthermore, the wireless router further improves the efficiency of dynamic adjustment by caching the channel negotiation results and referring to these results in the subsequent optimization process.

[0082] The benefit of this embodiment is that, through the optimization of this embodiment, it is possible to effectively deal with channel congestion problems, improve the channel utilization and data transmission performance of the network, reduce network interruptions and performance degradation, and provide users with a more stable and efficient wireless network experience. Through the combination of the Preamble Puncturing mechanism and the adaptive channel allocation algorithm, this embodiment can dynamically adjust the channel binding strategy in a complex and changing network environment to ensure the optimal use of network resources. In addition, the dynamic change mechanism without the need for re-negotiation of channels simplifies network management, improves the response speed of the system, and provides a technical foundation for future high-density, high-traffic wireless network applications.

[0083] Embodiment 2

[0084] In order to solve the problem in the prior art that the channel binding mode selection in a multi-user scenario is not flexible enough, resulting in limited network performance, this embodiment further optimizes the adaptive channel allocation algorithm. This embodiment provides a WIFI6 wireless channel binding optimization method, which specifically includes the following steps:

[0085] First, in this embodiment, an adaptive channel allocation algorithm is used to optimize the channel bonding mode. The algorithm builds a channel quality assessment model based on the real-time load rate and historical data of the primary channel and the auxiliary channel to predict the possibility of channel congestion. It should be understood that the real-time load rate data reflects the current network usage, while the historical data provides the long-term trend of the network. The combination of these data can more accurately predict the future channel status.

[0086] Furthermore, the channel quality assessment model is constructed by the following steps:

[0087] Real-time load rate data collection: The wireless router regularly collects the utilization rate of the main channel and auxiliary channel, including the channel transmission volume, occupancy time and channel interference level. These data can be obtained through channel state information (CSI) and channel quality indication (CQI).

[0088] Historical data collection: The wireless router saves channel load data for a period of time, including transmission volume, occupancy time, and congestion times. These historical data can be stored in local storage or on a remote server for subsequent analysis.

[0089] Channel quality assessment model construction: Use machine learning algorithms, such as support vector machines (SVM) or neural networks, to build a channel quality assessment model based on real-time load rates and historical data. This model can predict the possibility of congestion for each channel in the future, thus providing a basis for selecting the channel bonding mode.

[0090] Next, the channel quality assessment model is used to calculate the expected performance indicators for each potential channel bonding mode. These performance indicators include throughput, latency, and packet loss rate. Specifically:

[0091] Throughput calculation: The evaluation model predicts the actual throughput in each bonding mode based on the channel load rate and historical data. The maximum throughput is calculated based on the theoretical bandwidth and channel conditions.

[0092] Latency calculation: The evaluation model predicts the actual latency and target latency for each bonding mode. The target latency can be set based on user requirements and other network parameters.

[0093] Packet loss rate calculation: The evaluation model predicts the packet loss rate in each bonding mode. The packet loss rate prediction is based on the packet loss records in the historical data and the current channel interference level.

[0094] Furthermore, this embodiment uses a weighted multi-objective optimization algorithm to determine the optimal channel binding mode. The weighted values ​​(α, β, γ) are dynamically adjusted based on user needs. When the user is sensitive to delay, the weighted value of delay (β) will be increased. It should be understood that the weighted multi-objective optimization algorithm can balance different performance indicators to ensure that the most appropriate channel binding mode is selected under different user needs. The specific optimization objective function is:

[0095] Among them, X represents different

[0096] ˉˉ is the channel bonding mode, α, β, γ are the weighted values ​​of throughput, delay and packet loss rate respectively, T actual and T max are the actual throughput and the maximum throughput respectively, and are the target delay and actual delay respectively, E is the packet loss rate, and α+β+γ=1.

[0097] Furthermore, the wireless router implements the optimal channel bonding mode and continuously monitors the performance of the mode to make timely adjustments. The monitoring includes real-time collection of channel load data, terminal device activity, and network transmission performance. Through these data, the performance of the current bonding mode can be evaluated and the optimal bonding mode can be recalculated when necessary.

[0098] The benefit of this embodiment is that by constructing a channel quality assessment model and utilizing a weighted multi-objective optimization algorithm, it can flexibly respond to changes in network load in multi-user scenarios, ensure that the optimal channel binding mode is selected according to different user needs, and improve network throughput and reduce latency and packet loss rate.

[0099] Embodiment 3

[0100] In order to solve the problem that the Preamble Puncturing mechanism in the prior art selects the punching position and quantity inaccurately, this embodiment further optimizes the Preamble Puncturing mechanism. This embodiment provides a WIFI6 wireless channel binding optimization method, which specifically includes the following steps:

[0101] First, when the auxiliary channel is detected to be congested, the wireless router activates the Preamble Puncturing mechanism and optimizes the puncturing position and number through an adaptive puncturing algorithm. This mechanism can select the most appropriate subcarrier for puncturing in the case of channel congestion, thereby improving network utilization and performance.

[0102] Further, the steps of the adaptive puncturing algorithm include:

[0103] Calculate the congestion level of the channel. Use the following formula:

[0104] Among them, C represents the channel congestion level, N busy Indicates the number of busy subcarriers detected, N total Indicates the total number of subcarriers in the channel. It should be understood that the calculation of the congestion level can directly reflect the load of the channel and provide a basis for the selection of puncturing locations.

[0105] The puncturing position and number are determined according to the channel congestion level. When the channel congestion level exceeds the preset threshold, the busiest continuous subcarriers are selected for puncturing, and the puncturing position and number are ensured not to affect the subcarriers of the main channel. It can be understood that selecting the busiest continuous subcarriers for puncturing can maximize the utilization of idle subcarriers while maintaining network stability.

[0106] Evaluate the performance of the perforated channel and calculate the available bandwidth of the channel. Use the following formula:

[0107] B available =B total -N punctured ·B subcarrier , where B available represents the available bandwidth, B total Represents the total bandwidth of the channel, N punctured Indicates the number of punctured subcarriers, B subcarrier It indicates the bandwidth of each subcarrier. It should be understood that, through performance evaluation, it is possible to ensure that the punctured channel can still efficiently transmit data while reducing the impact on network performance.

[0108] In addition, wireless routers can use different sensors and monitoring modules to collect channel usage and interference data, such as channel state information (CSI) module and channel quality indication (CQI) module. These modules can provide detailed channel usage and help wireless routers more accurately determine channel congestion and select hole punching locations.

[0109] The benefit of this embodiment is that, through the adaptive punching algorithm, it is possible to more accurately select the punching location and number in the case of channel congestion, thereby improving the channel utilization and data transmission efficiency of the network, reducing the performance degradation caused by channel congestion, and thus improving the user's wireless network experience.

[0110] Embodiment 4

[0111] In order to solve the problem in the prior art that the selection of subcarriers during the channel binding process is not intelligent enough, resulting in low network resource utilization, this embodiment further optimizes the subcarrier selection algorithm of the wireless router. This embodiment provides a WIFI6 wireless channel binding optimization method, which specifically includes the following steps:

[0112] First, the wireless router collects information about all remaining idle subcarriers, including location, bandwidth, signal-to-noise ratio (SNR), and interference level (I). This step is implemented by the channel scanning module, which can regularly detect channel usage and interference levels, thereby providing accurate data support for subsequent subcarrier selection.

[0113] Furthermore, the expected bandwidth and expected throughput of each bundling solution are calculated based on the subcarrier information. Specifically, the following calculation formula is used:

[0114] Among them, T expected represents the expected throughput, I represents the set of all considered subcarriers, and B i represents the bandwidth of the i-th subcarrier, SNR i represents the signal-to-noise ratio of the i-th subcarrier, I iIt is necessary to understand that the data of the signal-to-noise ratio and the interference level reflect the transmission quality of the subcarrier, and the performance of each bundling scheme can be predicted more accurately through these data.

[0115] Furthermore, the binding scheme with the highest expected throughput is selected for data transmission. The wireless router selects the scheme with the highest expected throughput from all possible subcarrier binding schemes through an intelligent selection algorithm. The intelligent selection algorithm not only considers bandwidth and signal-to-noise ratio, but also combines the interference level of subcarriers to ensure that the selected binding scheme can achieve the best transmission performance in the actual network environment.

[0116] In addition, wireless routers can use different optimization strategies to further improve the accuracy of subcarrier selection. For example, genetic algorithms (GA) or particle swarm optimization (PSO) can be used to search for the best bundling solution. These optimization algorithms can find the global optimal solution in a large solution space, thereby improving the efficiency and accuracy of subcarrier selection.

[0117] The benefit of this embodiment is that through the intelligent selection algorithm and optimization strategy, the optimal subcarrier binding solution can be selected more accurately, the resource utilization and data transmission efficiency of the network can be improved, and the network performance degradation caused by unreasonable subcarrier selection can be reduced.

[0118] Embodiment 5

[0119] In order to solve the problem that channel monitoring in the prior art is not timely and accurate enough, resulting in unsatisfactory channel binding optimization, this embodiment further optimizes the adaptive channel monitoring algorithm. This embodiment provides a WIFI6 wireless channel binding optimization method, which specifically includes the following steps:

[0120] First, the wireless router collects historical load data for each channel, including transmission volume, occupancy time, and congestion times. These historical data can reflect the long-term use of the channel and provide a basis for future channel load prediction. It should be understood that detailed recording and analysis of historical data is the key to predicting future channel load.

[0121] Furthermore, based on the historical load data, a channel load prediction model is constructed. This embodiment uses time series analysis technology, such as a long short-term memory (LSTM) network, to construct a channel load prediction model. The LSTM network is a recurrent neural network (RNN) that can process long-term dependencies in time series data, thereby more accurately predicting future channel load conditions.

[0122] Furthermore, the transmission volume and occupancy time of the current channel are monitored in real time, and the channel load prediction model is used to estimate the load status of the future channel. The wireless router regularly collects the transmission volume and occupancy time data of the channel through the real-time monitoring module, and inputs it into the channel load prediction model. The model outputs the load prediction results of the future channel, including the transmission volume, occupancy time and congestion possibility in the future period of time.

[0123] Furthermore, when it is detected that the channel load will exceed the preset threshold in the future, the Preamble Puncturing mechanism is activated in advance to avoid congestion. The preset threshold can be set according to the actual situation of the network and user needs. When it is predicted that the channel load will exceed this threshold in the future, the wireless router will take optimization measures in advance to avoid the degradation of network performance caused by channel congestion.

[0124] Furthermore, wireless routers can combine other monitoring technologies, such as channel state information (CSI) and channel quality indication (CQI), to further improve the accuracy of channel load prediction. These technologies can provide more detailed channel usage and interference data, helping wireless routers to more comprehensively evaluate channel conditions.

[0125] The benefit of this embodiment is that, through the adaptive channel monitoring algorithm, optimization can be performed in time before channel congestion occurs, thereby avoiding network performance degradation caused by channel congestion. The combination of real-time monitoring and future load prediction ensures that the network is always in the best state.

[0126] Embodiment 6

[0127] In order to solve the problem that the Preamble Puncturing mechanism in the prior art is difficult to accurately identify the interference source in the channel, resulting in unsatisfactory optimization effect, this embodiment further optimizes the Preamble Puncturing mechanism and introduces a channel interference detection algorithm. This embodiment provides a WIFI6 wireless channel binding optimization method, which specifically includes the following steps:

[0128] First, the wireless router detects the signal strength and noise level of each subcarrier. Specifically, through the channel interference detection module, the wireless router can detect the signal strength (Signal Strength) and noise level (Noise Level) of each subcarrier in real time. The collection of these data can be achieved through the channel state information (CSI) module, which can provide high-precision channel usage.

[0129] Furthermore, the channel interference index is calculated based on the detected data. The following calculation formula is used:

[0130] Among them, Ichannel Indicates the channel interference index max(SNR i ) and min(SNR i ) represent the maximum and minimum signal-to-noise ratio in the channel, σ noise Indicates the standard deviation of noise in the channel. It should be understood that the channel interference index can comprehensively reflect the interference situation in the channel and provide a scientific basis for the subsequent selection of puncturing locations.

[0131] Furthermore, the location and strength of the interference source are determined based on the channel interference index. The channel interference detection algorithm identifies the specific location and strength of the interference source by analyzing the channel interference index. Specifically, when the channel interference index of a subcarrier is high, it can be considered that the subcarrier is subject to strong interference. The wireless router will record the location and strength of these interfering subcarriers to provide guidance for subsequent punching operations.

[0132] Furthermore, the subcarrier with the highest interference intensity is selected for puncturing to reduce the impact on network performance. Through the adaptive puncturing algorithm, the wireless router places the subcarrier with the highest interference intensity in a null state, thereby reducing the impact of interference on data transmission. It should be understood that selecting the subcarrier with the strongest interference for puncturing can minimize the impact of interference while maintaining the overall performance of the network.

[0133] Furthermore, the wireless router can combine the channel usage rate and the activity level data of the terminal device to further optimize the selection of the puncturing position. For example, if the usage rate of a certain subcarrier is low and the interference intensity is high, the subcarrier is preferentially selected for puncturing to reduce the impact on the active terminal.

[0134] The benefit of this embodiment is that, through the channel interference detection algorithm, the interference source in the channel can be more accurately identified, thereby optimizing the selection of the puncturing position, such as Figure 5 This precise interference identification and processing mechanism avoids network performance degradation caused by mis-punching and improves network stability and data transmission efficiency.

[0135] Embodiment 7

[0136] In order to solve the problem in the prior art that the channel binding optimization algorithm is difficult to meet the transmission requirements of different devices in a multi-user scenario, this embodiment further optimizes the adaptive channel allocation algorithm and introduces a channel allocation priority mechanism, such as Figure 6 Specifically, this embodiment provides a WIFI6 wireless channel binding optimization method, including the following steps:

[0137] First, in this embodiment, the wireless router assigns a priority value to each terminal device, and the priority value is calculated based on the transmission requirements and device type of the device. Specifically, the wireless router obtains the bandwidth requirements, delay requirements and device type of each device through communication with the terminal device. These demand information can be determined by the service type, application requirements and historical communication data of the terminal device. For example, for video streaming devices, the bandwidth requirement is higher and the delay requirement is lower, while for real-time communication devices, the delay requirement is higher and the bandwidth requirement is lower.

[0138] Furthermore, based on these demand information, the priority value of each terminal device is calculated. The calculation formula of the priority value is:

[0139] P i =w1·R i +w2·Q i +w3·D i , where P i represents the priority value of the i-th terminal device, w1, w2 and w3 are the weighted values ​​of bandwidth requirement, delay requirement and device type respectively, R i represents the bandwidth requirement of the i-th terminal device, Q i represents the delay requirement of the i-th terminal device, D i represents the type weight of the ith terminal device, and w1+w2+w3=1. It should be understood that the setting of the weighted value can be dynamically adjusted according to the actual needs of the user to adapt to different network environments and application requirements.

[0140] Furthermore, when channel congestion is detected, the wireless router preferentially selects a channel subcarrier with less congestion to meet the transmission requirements of high-priority devices. The specific steps include:

[0141] Real-time monitoring of channel load: The wireless router monitors the utilization rate and interference level of each subcarrier in real time through the channel state information (CSI) and channel quality indication (CQI) modules.

[0142] Congestion detection: When the load rate of a channel exceeds a preset threshold, the wireless router determines that the channel is in a congested state.

[0143] Priority sorting: Terminal devices are sorted according to the calculated priority values, and devices with higher priorities are given priority to obtain channel resources.

[0144] Channel subcarrier selection: In congested situations, the wireless router selects subcarriers with lower loads and allocates them to high-priority devices first, ensuring that the transmission performance of these devices is not affected.

[0145] Furthermore, the channel allocation priority mechanism can be implemented in a variety of ways. For example, a priority queue can be used to manage the channel requests of terminal devices to ensure that the requests of high-priority devices are processed first. In addition, the wireless router can dynamically adjust the priority value based on the network status and user behavior patterns to adapt to changes in the network environment.

[0146] The benefit of this embodiment is that by introducing a channel allocation priority mechanism, channel resources can be reasonably allocated in the case of channel congestion to ensure the transmission performance of high-priority devices. This mechanism not only improves the overall performance of the network, but also enhances the adaptability and flexibility of the network in multi-user scenarios.

[0147] Embodiment 8

[0148] In order to solve the problem of low network resource utilization in the case of partial channel congestion in the prior art, this embodiment further optimizes the WIFI6 wireless channel binding method and introduces multi-user MIMO (MU-MIMO) technology. Specifically, this embodiment provides a WIFI6 wireless channel binding optimization method, including the following steps:

[0149] The wireless router supports multi-user MIMO (MU-MIMO) technology, which improves channel utilization through spatial multiplexing of multi-antenna channels. MU-MIMO technology can simultaneously transmit data to multiple terminal devices in the same frequency band, making full use of the characteristics of multiple antennas to improve the overall performance of the network. It should be understood that MU-MIMO technology not only improves channel utilization, but also can transmit data through uncongested antennas when some channels are congested, ensuring network stability.

[0150] Furthermore, when the wireless router detects that part of the channel is congested, it uses the uncongested antenna to transmit data. The specific steps include:

[0151] The wireless router monitors the channel load status in real time and detects whether channel congestion occurs through the channel state information (CSI) and channel quality indication (CQI) modules.

[0152] Furthermore, when channel congestion is detected, the wireless router selects an uncongested antenna for data transmission based on a channel quality assessment model. The channel quality assessment model is based on the real-time load rate and historical data of the channel and can accurately predict the possibility of channel congestion.

[0153] Furthermore, through multi-user MIMO technology, wireless routers can use multiple uncongested antennas to simultaneously transmit data to multiple terminal devices in the same channel, which not only improves channel utilization but also reduces performance degradation caused by channel congestion.

[0154] Furthermore, wireless routers can combine other optimization technologies, such as adaptive puncturing algorithms and intelligent channel selection algorithms, to further improve network performance. For example, when a subcarrier is detected to be severely congested, non-congested subcarriers can be prioritized for puncturing, and combined with MU-MIMO technology to ensure efficient and stable data transmission.

[0155] Furthermore, wireless routers can use different types of antennas and signal processing modules to implement MU-MIMO technology. For example, using an 8x8 or 16x16 antenna array, combined with a high-precision digital signal processing (DSP) module, can provide more powerful spatial multiplexing capabilities, further improving network throughput and stability. It is understandable that different antenna configurations and signal processing technologies can be selected and optimized according to the actual needs of the network to ensure the best network performance.

[0156] Through this embodiment, the wireless router can fully utilize uncongested antennas for data transmission when some channels are congested, thereby improving channel utilization and overall network performance and reducing performance degradation caused by channel congestion.

[0157] Embodiment 9

[0158] In order to solve the problem in the prior art that in a multi-user scenario, it is difficult for a wireless router to efficiently manage channel resources, resulting in limited network performance, this embodiment proposes a WIFI6 wireless channel binding optimization system, including the following components:

[0159] The channel negotiation module supports 160MHz ultra-high bandwidth mode and is used to negotiate the available primary and secondary channels between the wireless router and the terminal. This step ensures the effective binding and use of the primary and secondary channels by exchanging channel capability information. The channel negotiation module can support multiple frequency bands and channel configurations to adapt to different network environments and user needs.

[0160] The channel monitoring module dynamically monitors the load status of the main channel and auxiliary channel to identify potential channel congestion problems. The channel monitoring module can timely detect channel congestion and provide early warning information by collecting data such as channel transmission volume, occupancy time and interference level in real time. It should be understood that the channel monitoring module not only monitors the current channel status, but also can make predictions based on historical data to provide a basis for subsequent channel optimization.

[0161] When the Preamble Puncturing module detects congestion in the auxiliary channel, it activates the Preamble Puncturing mechanism and puts the busy single or multiple auxiliary channel subcarriers into a null state to be compatible with the existing transmission nodes on the channel. The Preamble Puncturing module can flexibly select the puncturing position and number through an adaptive puncturing algorithm to ensure that the network can still efficiently transmit data in the case of channel congestion.

[0162] The channel selection module intelligently selects and binds the remaining discontinuous idle channel subcarriers for efficient data transmission while ensuring that there is no negative impact on the main channel. The channel selection module collects information about all remaining idle subcarriers, including location, bandwidth, signal-to-noise ratio, and interference level, calculates the expected performance indicators of each binding scheme, and selects the optimal binding scheme for data transmission. It should be understood that the channel selection module can dynamically adjust the channel binding mode according to the actual situation of the network to ensure the efficiency and stability of the network.

[0163] The adaptive channel allocation module adjusts the channel bonding mode in real time based on the network status to maximize network throughput and minimize latency. The adaptive channel allocation module can flexibly respond to changes in network load through the channel quality assessment model and weighted multi-objective optimization algorithm to ensure that the optimal channel bonding mode is selected under different user needs. Specifically, the module can adjust the channel allocation strategy in real time according to the transmission requirements and priorities of the terminal device to improve the overall performance of the network.

[0164] The channel negotiation optimization module ensures that there is no need to renegotiate channels between the wireless router and the terminal when the channel binding state changes, which is used to improve network performance. The channel negotiation optimization module caches the channel negotiation results and dynamically updates the channel configuration. It can quickly adjust the connection parameters of the terminal device when the channel binding mode changes, avoiding network interruption and performance degradation caused by renegotiation.

[0165] Furthermore, the coordination and cooperation between the various modules ensures the efficient operation of the system. For example, the load data provided by the channel monitoring module in real time provides an accurate basis for the selection and adjustment of the channel selection module and the adaptive channel allocation module. The selection of the puncturing position of the Preamble Puncturing module also needs to be combined with the detection results of the channel monitoring module to ensure that the puncturing operation will not have a negative impact on the main channel. The channel negotiation optimization module ensures a smooth transition when the channel binding state changes through a cache and update mechanism.

[0166] Furthermore, the optimization system in this embodiment can be combined with other network management technologies, such as QoS (Quality of Service) management and flow control, to further improve the performance and stability of the network. For example, QoS management can provide different service quality guarantees for different devices according to the priority and service type of the terminal device, and flow control can balance the network load and reduce congestion by adjusting the data transmission rate.

[0167] The benefit of this embodiment is that through this embodiment, the wireless router can efficiently manage channel resources in a multi-user scenario, ensure the stability and high performance of the network through the collaborative work of various modules, and improve the user's wireless network experience.

[0168] Embodiment 10

[0169] In order to solve the problem that the WIFI6 wireless channel binding optimization method in the prior art is difficult to implement in practical applications, this embodiment proposes a design of a computer-readable storage medium and provides a computer program for storing the optimization method. Specifically, this embodiment provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a computer processor, the WIFI6 wireless channel binding optimization method can be implemented.

[0170] It is understood that the computer-readable storage medium can be a storage device in various forms, such as a hard disk, a flash memory, an SSD (solid state drive), or a storage space on a remote server. These storage devices can support large-capacity data storage and high-speed data access, ensuring the efficient operation of the optimization algorithm. It should be understood that selecting a suitable storage medium is a prerequisite for implementing the optimization method.

[0171] Furthermore, the program code of each module can be independently developed and tested through modular design, and finally integrated into a unified system. Modular design not only improves development efficiency, but also facilitates subsequent maintenance and upgrades. It should be understood that the functions and algorithms of each module can be optimized and adjusted according to actual needs to ensure the flexibility and adaptability of the system.

[0172] Furthermore, the program on the computer-readable storage medium can support multiple processor architectures, such as ARM, x86, and MIPS, to meet the needs of different hardware platforms. The program can also be combined with virtualization technology to run in a cloud computing environment to achieve a wider range of applications and deployments. It is understandable that these technologies can not only improve the operating efficiency of the program, but also enhance the scalability of the system.

[0173] The benefit of this embodiment is that by storing the various modules of the WIFI6 wireless channel binding optimization method in the form of program code on a computer-readable storage medium, the optimization method is efficiently implemented and applied. This design not only simplifies the deployment and management of the optimization method, but also improves the adaptability of the system, providing users with a convenient and efficient wireless network optimization solution.

Claims

1. A WIFI6 wireless channel binding optimization method, characterized in that: The optimization method comprises the following steps: Enable the ultra-high bandwidth mode between the wireless router and at least one terminal, and negotiate the available primary channel and auxiliary channel; The wireless router dynamically monitors the load conditions of the primary channel and the secondary channel to identify potential channel congestion problems; When the auxiliary channel is detected to be congested, the wireless router activates the Preamble Puncturing mechanism to directly place the busy single or multiple auxiliary channel subcarriers in a null state during the orthogonal frequency division multiple access (OFDMA) transmission process to be compatible with the existing transmission nodes on the auxiliary channel; The wireless router intelligently selects and binds the remaining discontinuous idle channel subcarriers to perform efficient data transmission while ensuring that no negative impact is caused on the main channel; Adopting adaptive channel allocation algorithm, the channel bonding mode is adjusted in real time according to network conditions to maximize network throughput and minimize latency.

2. The WIFI6 wireless channel binding optimization method according to claim 1, characterized in that: The step of adopting an adaptive channel allocation algorithm comprises: Based on the real-time load rates and historical data of the primary channel and the secondary channel, a channel quality assessment model is constructed to predict the possibility of channel congestion; Calculating the expected performance indicators of each potential channel bonding mode, including throughput, delay, and packet loss rate, through the channel quality assessment model; The optimal channel bonding mode is determined by using a weighted multi-objective optimization algorithm. The weighted value is dynamically adjusted based on user demand. When the user is sensitive to delay, the weighted value of delay will be increased. The wireless router implements the optimal channel binding mode and continuously monitors the performance of the optimal channel binding mode to make timely adjustments; The expression of the weighted multi-objective optimization algorithm is: Where X represents different channel bonding modes, α, β, and γ are weighted values ​​of throughput, delay, and packet loss rate, respectively. and are the actual throughput and the maximum throughput respectively, and are the target delay and actual delay respectively, E is the packet loss rate, and α+β+γ=1.

3. The WIFI6 wireless channel binding optimization method according to claim 1, characterized in that: The Preamble Puncturing mechanism optimizes the puncturing position and number through an adaptive puncturing algorithm. The adaptive puncturing algorithm selects the subcarriers to be punctured based on the channel congestion level and the network load condition to ensure that in the case of channel congestion, as many idle subcarriers as possible are used for data transmission. The steps of the adaptive puncturing algorithm include: The congestion degree of the channel is calculated, and the calculation formula of the congestion degree is: Among them, C represents the channel congestion level, N busy Indicates the number of busy subcarriers detected, N total Indicates the total number of subcarriers in the channel; Determine the puncturing position and quantity according to the channel congestion degree, and when the channel congestion degree exceeds a preset threshold, select the busiest continuous subcarriers for puncturing, and ensure that the puncturing position and quantity do not affect the subcarriers of the main channel; Evaluate the performance of the channel after puncturing and calculate the available bandwidth of the channel: B available =B total -N punctured ·B subcarrier , where B available represents the available bandwidth, B total Represents the total bandwidth of the channel, N punctured Indicates the number of punctured subcarriers, B subcarrier Indicates the bandwidth of each subcarrier.

4. The WIFI6 wireless channel binding optimization method according to claim 1, characterized in that: The wireless router determines the optimal subcarrier bundling scheme through an intelligent selection algorithm, wherein the intelligent selection algorithm calculates performance indicators of different bundling schemes based on the positions and qualities of the remaining idle subcarriers, and selects the best scheme, wherein the steps of the intelligent selection algorithm include: Collect information about all remaining idle subcarriers, including location, bandwidth, signal-to-noise ratio, and interference level; According to the information of the subcarriers, the expected bandwidth and expected throughput of each bundling scheme are calculated using the following formula: Among them, T expected represents the expected throughput, I represents the set of all considered subcarriers, and B i represents the bandwidth of the i-th subcarrier, SNR i represents the signal-to-noise ratio of the i-th subcarrier, I i represents the interference level of the i-th subcarrier; The bonding scheme with the highest expected throughput is selected for data transmission.

5. The WIFI6 wireless channel binding optimization method as described in claim 4 is characterized in that: The wireless router uses an adaptive channel monitoring algorithm to dynamically evaluate the channel load. The adaptive channel monitoring algorithm predicts the future channel load status based on the real-time data transmission volume and historical load data to identify potential congestion problems in advance. The steps of the adaptive channel monitoring algorithm include: Collect historical load data for each channel, including transmission volume, occupancy time, and congestion times; Based on the historical load data, construct a channel load prediction model; Monitor the transmission volume and occupancy time of the current channel in real time, and use the channel load prediction model to estimate the load status of the future channel; When it is detected that the channel load will exceed the preset threshold in the future, the Preamble Puncturing mechanism is activated in advance to avoid congestion.

6. The WIFI6 wireless channel binding optimization method according to claim 1, characterized in that: The PreamblePuncturing mechanism also includes a channel interference detection algorithm for accurately identifying interference sources in the channel. The channel interference detection algorithm determines the type and intensity of interference by analyzing the signal strength and noise level of the channel, thereby more accurately selecting the puncturing position. The steps of the channel interference detection algorithm include: Detect the signal strength and noise level of each subcarrier and calculate the channel interference index: Among them, I channel Indicates the channel interference index max(SNR i ) and min(SNR i ) represent the maximum and minimum signal-to-noise ratio in the channel, σ noise represents the standard deviation of noise in the channel; Determining the location and strength of the interference source according to the channel interference index; The subcarrier with the highest interference intensity is selected for puncturing to reduce the impact on network performance.

7. The WIFI6 wireless channel binding optimization method according to claim 1, characterized in that: The adaptive channel allocation algorithm also includes a channel allocation priority mechanism, which dynamically adjusts the priority of channel binding according to the transmission requirements of the terminal device and the network status to ensure that high-priority devices can maintain transmission performance even in congestion. The steps of the priority mechanism include: Assign a priority value to each terminal device based on the device's transmission requirements and device type; When channel congestion is detected, the channel subcarriers with less congestion are preferentially selected to meet the transmission needs of high-priority devices; The priority value is calculated as follows: P i =w1·R i +w2·Q i +w3·D i , where P i represents the priority value of the i-th terminal device, w1, w2 and w3 are the weighted values ​​of bandwidth requirement, delay requirement and device type respectively, R i represents the bandwidth requirement of the i-th terminal device, Q i represents the delay requirement of the i-th terminal device, D i represents the type weight of the i-th terminal device, and w1+w2+w3=1.

8. The WIFI6 wireless channel binding optimization method according to any one of claims 1 to 7, characterized in that: The optimization method also includes using multi-user MIMO (MU-MIMO) technology to improve channel utilization through spatial multiplexing of multi-antenna channels. When some channels are congested, the wireless router uses uncongested antennas to transmit data.

9. A WIFI6 wireless channel binding optimization system, characterized in that: The optimization system comprises: Channel negotiation module, supporting 160MHz ultra-high bandwidth mode, used for negotiation between wireless routers and terminals on available primary and secondary channels; A channel monitoring module dynamically monitors the load conditions of the primary channel and the secondary channel to identify potential channel congestion problems; Preamble Puncturing module: When the auxiliary channel is congested, the Preamble Puncturing mechanism is activated to put the busy single or multiple auxiliary channel subcarriers into the null state to be compatible with the existing transmission nodes on the channel. A channel selection module intelligently selects and binds the remaining discontinuous idle channel subcarriers for efficient data transmission while ensuring that no negative impact is caused on the main channel; Adaptive channel allocation module, which adjusts the channel bonding mode in real time based on network conditions to maximize network throughput and minimize latency; The channel negotiation optimization module ensures that the wireless router and the terminal do not need to re-negotiate the channel when the channel binding state changes, so as to improve the network performance.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor of a computer, it can implement the WIFI6 wireless channel binding optimization method as described in any one of claims 1 to 8.

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