Wireless network signal conversion method and system

Abstract

The invention discloses a wireless network signal conversion method and system, and relates to the technical field of wireless networks, and the method comprises the steps: S1, full-band scanning, S2, interference feature recognition and classification, S3, channel quality evaluation and sorting, and S4, distributed collaboration, the method comprises the following steps: S1, carrying out information exchange on a local router, carrying out merging and cooperative calculation on a local priority list and a neighbor list obtained by carrying out information exchange from adjacent routers to obtain a coordinated regional channel allocation scheme, S5, carrying out non-inductive channel switching execution, and S6, carrying out closed-loop verification. Through a distributed collaborative and non-inductive switching mechanism, independent decision behaviors of a plurality of routers in a region are converted into collective optimization actions based on shared information and collaborative computing, and it is ensured that the switching process is transparent to users without interruption, so that the technical requirements on the users are greatly reduced, and the switching efficiency is improved. And the overall stability, throughput and user experience of the wireless network in a complex and dense network environment are fundamentally improved.

Description

Technical Field

[0001] This invention relates to the field of wireless network technology, and in particular to a wireless network signal conversion method and system. Background Technology

[0002] Wireless network signals are data carriers transmitted via radio waves; their essence is electromagnetic waves. Generated by devices such as wireless routers, they propagate through space, enabling mobile phones, computers, and other terminals to access the internet without a network cable, thus achieving functions such as web browsing, video playback, and file transfer.

[0003] In current wireless networks, optimizing signal quality often involves channel selection. Whether relying on users to manually identify and switch channels in the router's backend or on the device's own automatic selection algorithm, the core goal is to find and occupy the channel with the least interference. However, manual operation has a high technical threshold for ordinary users, while automatic selection may lead to unstable or suboptimal results due to algorithm limitations. This situation is still not convenient and intelligent enough in actual use. Summary of the Invention

[0004] The purpose of this invention is to provide a wireless network signal conversion method and system to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a wireless network signal conversion method, comprising the following steps:

[0006] S1: Full-band scanning, through the integrated broadband RF sampling front end, performs periodic scanning of the operating frequency band to obtain raw spectrum data including signal strength and noise floor;

[0007] S2: Interference feature identification and classification. By performing signal demodulation and feature matching on the raw spectrum data, a classified spectrum map is obtained that accurately identifies Wi-Fi networks, Bluetooth devices and other pulse interference sources.

[0008] S3: Channel quality assessment and ranking. By comparing the classified spectrum with the real-time performance data of this network and performing weighted calculations, a list of channel priorities ranked by comprehensive scores is obtained.

[0009] S4: Distributed coordination, through the coordination channel, merges and coordinates the local priority list with the neighbor list obtained from information exchange with neighboring routers to obtain a coordinated area channel allocation scheme;

[0010] S5: Seamless channel handover execution. By following the regional channel allocation scheme, the standard channel handover announcement protocol is executed, and the radio frequency front end is controlled to reconfigure in precise timing to obtain a new channel link that is seamlessly switched to the connected client and completes the hardware handover.

[0011] S6: Closed-loop verification. By performing continuous performance monitoring on the new channel, the collected throughput, latency, and retransmission rate data are compared and analyzed with the predicted performance before the handover to verify the effectiveness of this collaboration.

[0012] Preferably, step S4 includes the following steps:

[0013] S41: Encapsulates the local channel priority list and device metadata;

[0014] S42: Broadcast and receive coordination messages between adjacent nodes via a dedicated coordination channel;

[0015] S43: Aggregate the received neighbor messages to build a unified regional network status view;

[0016] S44: Executes a collaborative computation algorithm based on the local view and the aggregated neighbor view;

[0017] S45: Coordinate actions based on shared neighbor information, generate and distribute the final area channel allocation scheme;

[0018] S46: Confirm the plan is synchronized and complete the execution preparation.

[0019] Preferably, step S45 includes the following steps:

[0020] S451: Input the local collaborative calculation results and aggregated neighbor status data;

[0021] S452: Perform collision detection to identify channel allocation conflicts;

[0022] S453: Coordination and Synchronization: Based on shared neighbor state data, coordinate the subsequent actions of the local machine and its neighbors, resolve conflicts, and generate a final allocation scheme;

[0023] S454: Encapsulate the final solution into coordination instructions;

[0024] S455: Distribute the coordination instruction via a dedicated coordination channel.

[0025] Preferably, in step S453, the expected performance gain of the local device and each neighboring device under each conflict resolution proposal is calculated based on the shared neighbor status data, and the expected performance gains of all devices are weighted and summed according to a set weight to evaluate the total regional gain corresponding to the proposal. Based on this, the subsequent actions of the local device and its neighbors are coordinated to generate the final allocation scheme.

[0026] Preferably, in the step of coordinating subsequent actions between the local machine and its neighbors based on shared neighbor state data and resolving conflicts, collaborative computation is performed by processing shared data. Specifically, the collaborative computation includes the following judgments:

[0027] Interference analysis and judgment are used to identify and quantify the impact weights of different interference sources on channel quality;

[0028] Real-time performance assessment is used to incorporate current and historical network status data to correct channel scores.

[0029] Perform comprehensive scoring and ranking to generate a comparable list of channel priorities to drive decision-making.

[0030] Preferably, the interference analysis and judgment includes identifying signal characteristics in the radio frequency spectrum:

[0031] If the signal characteristics match the known Wi-Fi beacon frame format, it is determined to be co-channel Wi-Fi interference;

[0032] If the signal characteristics are high-frequency narrowband pulses and conform to the Bluetooth frequency hopping pattern, it is determined to be Bluetooth interference;

[0033] If the signal characteristics are broadband continuous noise, it is determined to be non-Wi-Fi electrical appliance interference;

[0034] For each signal source identified as interference, the interference penalty value on channel quality is calculated based on its signal strength and duty cycle.

[0035] Preferably, the real-time performance judgment includes monitoring the real-time performance indicators of the device on the current channel and querying the historical performance database:

[0036] If the real-time packet retransmission rate exceeds the first preset threshold, it is determined that the current channel quality has deteriorated instantaneously, and a real-time quality penalty value is generated.

[0037] If the historical average throughput of the channel is lower than the second preset threshold during the current period, it is determined that the channel has periodic performance degradation, and a historical trend penalty value is generated.

[0038] Preferably, the comprehensive scoring and ranking judgment includes assigning a basic score to each channel, sequentially calculating various penalty values ​​generated by interference analysis and real-time performance judgment, obtaining a final comprehensive score, and comparing the final comprehensive scores of all channels:

[0039] If the score of the first channel is higher than that of the second channel, then the first channel will be ranked before the second channel in the priority list.

[0040] If the scores are the same, the channel numbers are compared, and the channel with the smaller number is ranked first. Finally, the sorted channel priority list is output.

[0041] Preferably, after the final allocation scheme is generated, a coordination transaction identifier containing the hash value of the final allocation scheme and a preset execution time sequence is broadcast on the coordination channel, and the acknowledgment responses returned by neighboring devices to this identifier are listened for and collected.

[0042] If valid confirmations are received from all relevant neighbors in the coordination group within the preset timeout window, the final allocation scheme will be marked as an executable scheme that has reached a coordination consensus, and the process will proceed to S454. Otherwise, the coordination transaction will be rolled back, and the conflict resolution process will be re-executed.

[0043] The present invention also provides a wireless network signal conversion system, comprising:

[0044] The full-band scanning module, through the integration of a broadband radio frequency sampling front end, performs periodic scanning of the operating frequency band to obtain raw spectrum data including signal strength and noise floor.

[0045] The interference feature identification and classification module performs signal demodulation and feature matching on the raw spectrum data to obtain a classified spectrum map that accurately identifies Wi-Fi networks, Bluetooth devices and other pulse interference sources;

[0046] The channel quality assessment and ranking module compares and correlates the classified spectrum with the real-time performance data of the network and performs weighted calculations to obtain a list of channel priorities ranked by comprehensive scores.

[0047] The distributed coordination module, through the coordination channel, merges and coordinates the local priority list with the neighbor list obtained from information exchange with neighboring routers to obtain a coordinated regional channel allocation scheme.

[0048] The seamless channel switching execution module executes the standard channel switching announcement protocol according to the regional channel allocation scheme and controls the radio frequency front end to reconfigure in precise timing to obtain a new channel link that is seamlessly switched to the connected client and completes the hardware switching.

[0049] The closed-loop verification module performs continuous performance monitoring on the new channel, compares and analyzes the collected throughput, latency, and retransmission rate data with the predicted performance before the handover, and completes the verification of the effectiveness of this collaboration.

[0050] The technical effects and advantages of this invention are as follows:

[0051] (1) This invention transforms the independent decision-making behavior of multiple routers in the area into a collective optimization action based on shared information and collaborative computing through a distributed collaboration and seamless handover mechanism, and ensures that the handover process is transparent to the user without interruption. This brings about a significant improvement from single-point optimization to global optimization and from manual intervention to fully automatic intelligent scheduling. It not only greatly reduces the technical requirements for users, but also fundamentally improves the overall stability, throughput and user experience of wireless networks in complex and dense network environments.

[0052] (2) By introducing full-band scanning and intelligent identification technology for interference features, this invention upgrades the traditional simple channel perception to accurate “fingerprint” identification and quantitative evaluation of various interference sources such as Wi-Fi and Bluetooth, bringing about a fundamental change from blind avoidance to accurate cognition, enabling channel assessment to have a high-dimensional environmental understanding capability, and providing an accurate data foundation for solving interference problems. Attached Figure Description

[0053] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention, but do not constitute a limitation thereof. In the drawings:

[0054] Figure 1 This is a flowchart of the wireless network signal conversion method of the present invention. Detailed Implementation

[0055] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0056] This invention provides, for example Figure 1 The wireless network signal conversion method shown includes the following steps:

[0057] S1: Full-band scanning, through the integrated broadband RF sampling front end, performs periodic scanning of the operating frequency band to obtain raw spectrum data including signal strength and noise floor;

[0058] S2: Interference feature identification and classification. By performing signal demodulation and feature matching on the raw spectrum data, a classified spectrum map is obtained that accurately identifies Wi-Fi networks, Bluetooth devices and other pulse interference sources.

[0059] S3: Channel quality assessment and ranking. By comparing the classified spectrum with the real-time performance data of this network and performing weighted calculations, a list of channel priorities ranked by comprehensive scores is obtained.

[0060] S4: Distributed coordination, through the coordination channel, merges and coordinates the local priority list with the neighbor list obtained from information exchange with neighboring routers to obtain a coordinated area channel allocation scheme;

[0061] S5: Seamless channel handover execution. By following the regional channel allocation scheme, the standard channel handover announcement protocol is executed, and the radio frequency front end is controlled to reconfigure in precise timing to obtain a new channel link that is seamlessly switched to the connected client and completes the hardware handover.

[0062] S6: Closed-loop verification. By performing continuous performance monitoring on the new channel, the collected throughput, latency, and retransmission rate data are compared and analyzed with the predicted performance before the handover to verify the effectiveness of this collaboration.

[0063] By performing full-band scanning and interference feature identification, different interference sources such as Wi-Fi and Bluetooth are accurately distinguished. Secondly, channel quality is comprehensively evaluated and ranked by combining real-time network performance data. Through distributed collaborative steps, multiple routers in the area can exchange evaluation information and perform collaborative calculations to generate a channel allocation scheme that optimizes the overall regional network efficiency. Subsequently, a seamless channel handover that is transparent to users is performed. Finally, the handover effect is monitored and evaluated through a closed-loop verification step, realizing complete automation of channel management, completely eliminating the need for users to perform complex manual configuration, fundamentally reducing co-channel interference, and improving the overall spectrum utilization and network capacity in dense network environments.

[0064] Step S1: Full-band scanning specifically includes the following steps:

[0065] S11: Frequency band division, dividing the operating frequency band (such as the 2.4GHz and / or 5GHz ISM band) into multiple consecutive scanning sub-channels;

[0066] S12: Radio frequency sampling, energy detection sampling of each scanning sub-channel is performed through a broadband radio frequency sampling front end in a preset order or frequency hopping mode;

[0067] S13: Data generation, recording the signal strength value of each sampling point, calculating the average noise floor of the sub-channel, and integrating to generate raw spectrum data covering the entire frequency band;

[0068] Step S1 provides complete raw spectrum data, laying the foundation for accurate analysis and avoiding the problem of missing interference sources due to incomplete scanning range in traditional methods.

[0069] Step S2: Interference Feature Identification and Classification specifically includes the following steps:

[0070] S21: Signal demodulation, attempting to demodulate signal segments with abrupt energy changes in the original spectrum data using standard protocols (such as Wi-Fi beacon frame demodulation).

[0071] S22: Feature extraction: For signals that cannot be demodulated, extract their time-domain features (such as pulse width and repetition period) and frequency-domain features (such as center frequency and bandwidth).

[0072] S23: Classification matching, matching the extracted features with a pre-set interference source feature library (including typical patterns such as Wi-Fi, Bluetooth, microwave oven, cordless phone, etc.), and outputting a classification spectrum with category labels.

[0073] Step S2 enables accurate identification of interference sources, clearly distinguishing between Wi-Fi, Bluetooth, or other electrical interference, thus upgrading subsequent assessments from vague judgments of "signal strength" to precise management of "targeted solutions".

[0074] Step S3: Channel quality assessment and ranking specifically includes the following steps:

[0075] S31: Interference weight calculation, based on the classification map, statistically analyzes the intensity and density of different types of interference on each candidate channel, and calculates the comprehensive interference weight;

[0076] S32: Real-time performance correlation, obtain the real-time throughput, latency and packet loss rate data of this network in the current channel, compare it with the historical baseline, and generate a performance correction factor;

[0077] S33: Comprehensive scoring and ranking. The interference weight and performance correction factor are substituted into the scoring model to calculate the comprehensive quality score for each candidate channel and generate a priority list in descending order.

[0078] Step S3 generates a dynamic, personalized channel priority list. It considers not only external interference but also the real-time performance of the network, making channel selection more aligned with current service needs. The decision quality is significantly higher than traditional algorithms based solely on static signal strength.

[0079] Step S4 includes the following steps:

[0080] S41: Encapsulates the local channel priority list and device metadata;

[0081] S42: Broadcast and receive coordination messages between adjacent nodes via a dedicated coordination channel;

[0082] S43: Aggregate the received neighbor messages to build a unified regional network status view;

[0083] S44: Executes a collaborative computation algorithm based on the local view and the aggregated neighbor view;

[0084] S45: Coordinate actions based on shared neighbor information, generate and distribute the final area channel allocation scheme;

[0085] S46: Confirm the plan is synchronized and complete the execution preparation.

[0086] Through the information exchange and aggregation in steps S42-S43, each participating device obtains a unified panoramic view of the regional network status, far exceeding its own perception range. This lays a reliable data foundation for making globally optimal decisions, overcoming the limitations of traditional devices making decisions based solely on their own scans. Steps S44 and S45 clarify that collaboration is not simply information reporting, but a complete process involving executing specific algorithms based on shared data to calculate solutions and actively coordinating the actions of all parties to reach consensus. This ensures the feasibility of collaboration and the effectiveness of the results. Through the final solution synchronization confirmation mechanism S46, it ensures that all relevant devices are in the same state before action, effectively avoiding execution chaos or conflicts caused by information asynchrony, enabling the entire distributed system to operate reliably and stably.

[0087] Step S45 includes the following steps:

[0088] S451: Input the local collaborative calculation results and aggregated neighbor status data;

[0089] S452: Perform collision detection to identify channel allocation conflicts;

[0090] S453: Coordination and Synchronization: Based on shared neighbor state data, coordinate the subsequent actions of the local machine and its neighbors, resolve conflicts, and generate a final allocation scheme;

[0091] S454: Encapsulate the final solution into coordination instructions;

[0092] S455: Distribute the coordination instruction via a dedicated coordination channel.

[0093] Through a dedicated conflict detection step S452, the system can pre-identify resource contention issues such as multiple devices selecting the same channel, thereby transforming potential, post-event network performance conflicts into pre-event, manageable logical problems, ensuring stable network deployment. Step S453 explicitly states that the essence of coordination is to unify the planning of subsequent actions based on shared data from multiple parties. This is not a simple matter of majority rule, but rather calculation and arbitration with the overall regional performance as the objective, ensuring the fairness and global optimization of the final allocation scheme. From generating the scheme S453 to encapsulating the instructions S454 and distributing them S455, this process forms a clear and reliable technical path, enabling the intelligent decisions derived from collaborative calculations to be accurately and efficiently converted into explicit commands that all relevant devices can receive and execute, guaranteeing the accurate implementation of collaborative intentions.

[0094] In step S453, based on shared neighbor state data, the expected performance gain of the local device and each neighbor device under each conflict resolution proposal is calculated, and the expected performance gains of all devices are weighted and summed according to a set weight to evaluate the total regional gain corresponding to the proposal. Based on this, the subsequent actions of the local device and its neighbors are coordinated to generate the final allocation scheme.

[0095] In the step of coordinating subsequent actions between the local machine and its neighbors based on shared neighbor state data and resolving conflicts, collaborative computation is performed by processing shared data. Specifically, collaborative computation includes the following judgments:

[0096] Interference analysis and judgment are used to identify and quantify the impact weights of different interference sources on channel quality;

[0097] Real-time performance assessment is used to incorporate current and historical network status data to correct channel scores.

[0098] Perform comprehensive scoring and ranking to generate a comparable list of channel priorities to drive decision-making.

[0099] Interference analysis and judgment include identifying signal characteristics in the radio frequency spectrum:

[0100] If the signal characteristics match the known Wi-Fi beacon frame format, it is determined to be co-channel Wi-Fi interference;

[0101] If the signal characteristics are high-frequency narrowband pulses and conform to the Bluetooth frequency hopping pattern, it is determined to be Bluetooth interference;

[0102] If the signal characteristics are broadband continuous noise, it is determined to be non-Wi-Fi electrical appliance interference;

[0103] For each signal source identified as interference, the interference penalty value on channel quality is calculated based on its signal strength and duty cycle.

[0104] Specifically, an interference penalty value P is calculated for channel c. i (c) The formula is:

[0105]

[0106] Where Ix is the intensity of the x-th type of interference source (based on signal strength and duty cycle), and kx is the weight of the corresponding interference type (Wi-Fi > Bluetooth > electrical appliances).

[0107] Real-time performance assessment includes monitoring the device's real-time performance metrics on the current channel and querying the historical performance database:

[0108] If the real-time packet retransmission rate exceeds the first preset threshold, it is determined that the current channel quality has deteriorated instantaneously, and a real-time quality penalty value is generated.

[0109] If the historical average throughput of the channel is lower than the second preset threshold during the current period, it is determined that the channel has periodic performance degradation, and a historical trend penalty value is generated.

[0110] Specifically, the formula for calculating a performance penalty value Pp(c) for channel c is:

[0111]

[0112] Where R(c) is the real-time penalty value when the retransmission rate exceeds the limit, H(c) is the historical penalty value when the throughput is insufficient, and a and b are weighting coefficients (e.g., a+b=1).

[0113] The comprehensive scoring and ranking process involves assigning a base score to each channel, calculating various penalty values ​​generated by interference analysis and real-time performance assessments, obtaining the final comprehensive score, and comparing the final comprehensive scores of all channels.

[0114] If the score of the first channel is higher than that of the second channel, then the first channel will be ranked before the second channel in the priority list.

[0115] If the scores are the same, the channel numbers are compared, and the channel with the smaller number is ranked first. Finally, the sorted channel priority list is output.

[0116] The specific formula for calculating the final score S(c) and sorting the channels is as follows:

[0117]

[0118] Where B is the channel baseline score, and m and n are the global weight coefficients of the total penalty term. Finally, the S(c) of all channels are sorted from high to low to obtain the priority list.

[0119] After the final allocation scheme is generated, a coordination transaction identifier containing the hash value of the final allocation scheme and the preset execution sequence is broadcast on the coordination channel. The channel listens for and collects the acknowledgment responses returned by neighboring devices to this identifier.

[0120] If valid confirmations are received from all relevant neighbors in the coordination group within the preset timeout window, the final allocation scheme will be marked as an executable scheme that has reached a coordination consensus, and the process will proceed to S454. Otherwise, the coordination transaction will be rolled back, and the conflict resolution process will be re-executed.

[0121] By introducing a distributed consensus confirmation step based on transaction identifiers, a crucial reliability guarantee is provided for the entire collaborative handover process. What might otherwise be asynchronous and loosely coordinated actions are transformed into a reliable transaction with atomicity (either all succeed or all rollback) and eventual consistency. By broadcasting a transaction identifier containing the scheme hash and execution sequence and collecting confirmations, the system can explicitly verify whether all relevant neighboring devices are synchronized and ready to execute the same scheme before the actual handover action occurs. This completely avoids the risk of network fragmentation, channel conflicts, or handover failures caused by some devices not being synchronized. If a consensus cannot be reached, a rollback and renegotiation are automatically triggered. This gives the system the robustness to recover from temporary communication failures, ensuring that the aforementioned intelligent collaboration can be executed securely, reliably, and consistently in a real, imperfect wireless distributed environment—a core technological guarantee.

[0122] Step S5: Seamless channel handover execution specifically includes the following steps:

[0123] S51 handover announcement: Before the handover, a standardized channel handover announcement and countdown synchronization process is executed, and the handover notification is broadcast to the associated clients;

[0124] S52 RF Reconfiguration: At the precise moment announced, controls the phase-locked loop and filters of the RF front end to reconfigure their operating frequency and bandwidth to the target channel;

[0125] S53 Link Reconstruction: Quickly retransmits beacon frames on the new channel to guide the client to seamlessly re-associate and complete the link switch.

[0126] Step S5 improves performance while ensuring a continuous user experience. By employing standard protocol announcements and precise timing control, the handover process is smooth and uninterrupted, so users will not experience any lag or disconnection, achieving zero-perceptible network optimization.

[0127] Step S6: Closed-loop verification specifically includes the following steps:

[0128] S61 performance monitoring: During the stabilization period after the handover, continuously monitor the key performance indicators of the new channel;

[0129] S62 Data Comparison: Compare the monitored actual performance data with the predicted performance data used for decision-making in step S3;

[0130] S63 Validity Determination: Calculate the performance difference between the actual and the predicted performance. If the difference is within the fault tolerance threshold, the collaboration is deemed valid; otherwise, it is marked as an inefficient decision and can trigger the optimization learning process.

[0131] Step S6 forms a closed loop of self-verification and optimization. It not only verifies the effectiveness of a single decision, but the verification results can also serve as feedback data to optimize future evaluation and collaborative algorithms, enabling the system to continuously learn and improve itself.

[0132] The above six steps are interconnected and together constitute a complete intelligent system from perception, analysis, collaboration to execution and verification. This upgrades Wi-Fi channel management from a manual / simple automatic mode that relies on user experience and passive response to a globally autonomous mode driven by the system proactively, intelligently, and collaboratively, fundamentally improving network performance and user experience in dense wireless environments.

[0133] The present invention also provides a wireless network signal conversion system, comprising:

[0134] The full-band scanning module, through the integration of a broadband radio frequency sampling front end, performs periodic scanning of the operating frequency band to obtain raw spectrum data including signal strength and noise floor.

[0135] The interference feature identification and classification module performs signal demodulation and feature matching on the raw spectrum data to obtain a classified spectrum map that accurately identifies Wi-Fi networks, Bluetooth devices and other pulse interference sources;

[0136] The channel quality assessment and ranking module compares and correlates the classified spectrum with the real-time performance data of the network and performs weighted calculations to obtain a list of channel priorities ranked by comprehensive scores.

[0137] The distributed coordination module, through the coordination channel, merges and coordinates the local priority list with the neighbor list obtained from information exchange with neighboring routers to obtain a coordinated regional channel allocation scheme.

[0138] The seamless channel switching execution module executes the standard channel switching announcement protocol according to the regional channel allocation scheme and controls the radio frequency front end to reconfigure in precise timing to obtain a new channel link that is seamlessly switched to the connected client and completes the hardware switching.

[0139] The closed-loop verification module performs continuous performance monitoring on the new channel, compares and analyzes the collected throughput, latency, and retransmission rate data with the predicted performance before the handover, and completes the verification of the effectiveness of this collaboration.

[0140] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A wireless network signal conversion method, characterized in that, Includes the following steps: S1: Full-band scanning, through the integrated broadband RF sampling front end, performs periodic scanning of the operating frequency band to obtain raw spectrum data including signal strength and noise floor; S2: Interference feature identification and classification. By performing signal demodulation and feature matching on the raw spectrum data, a classified spectrum map is obtained that accurately identifies Wi-Fi networks, Bluetooth devices and other pulse interference sources. S3: Channel quality assessment and ranking. By comparing the classified spectrum with the real-time performance data of this network and performing weighted calculations, a list of channel priorities ranked by comprehensive scores is obtained. S4: Distributed coordination, through the coordination channel, merges and coordinates the local priority list with the neighbor list obtained from information exchange with neighboring routers to obtain a coordinated area channel allocation scheme; S5: Seamless channel handover execution. By following the regional channel allocation scheme, the standard channel handover announcement protocol is executed, and the radio frequency front end is controlled to reconfigure in precise timing to obtain a new channel link that is seamlessly switched to the connected client and completes the hardware handover. S6: Closed-loop verification. By performing continuous performance monitoring on the new channel, the collected throughput, latency, and retransmission rate data are compared and analyzed with the predicted performance before the handover to verify the effectiveness of this collaboration.

2. The wireless network signal conversion method according to claim 1, characterized in that, Step S4 includes the following steps: S41: Encapsulates the local channel priority list and device metadata; S42: Broadcast and receive coordination messages between adjacent nodes via a dedicated coordination channel; S43: Aggregate the received neighbor messages to build a unified regional network status view; S44: Executes a collaborative computation algorithm based on the local view and the aggregated neighbor view; S45: Coordinate actions based on shared neighbor information, generate and distribute the final area channel allocation scheme; S46: Confirm the plan is synchronized and complete the execution preparation.

3. The wireless network signal conversion method according to claim 2, characterized in that, Step S45 includes the following steps: S451: Input the local collaborative calculation results and aggregated neighbor status data; S452: Perform collision detection to identify channel allocation conflicts; S453: Coordination and Synchronization: Based on shared neighbor state data, coordinate the subsequent actions of the local machine and its neighbors, resolve conflicts, and generate a final allocation scheme; S454: Encapsulate the final solution into coordination instructions; S455: Distribute the coordination instruction via a dedicated coordination channel.

4. The wireless network signal conversion method according to claim 3, characterized in that, In step S453, based on shared neighbor state data, the expected performance gain of the local device and each neighbor device under each conflict resolution proposal is calculated, and the expected performance gains of all devices are weighted and summed according to a set weight to evaluate the total regional gain corresponding to the proposal. Based on this, the subsequent actions of the local device and its neighbors are coordinated to generate the final allocation scheme.

5. The wireless network signal conversion method according to claim 4, characterized in that, In the step of coordinating subsequent actions between the local machine and its neighbors and resolving conflicts based on shared neighbor state data, collaborative computation is performed by processing shared data. Specifically, the collaborative computation includes the following judgments: Interference analysis and judgment are used to identify and quantify the impact weights of different interference sources on channel quality; Real-time performance assessment is used to incorporate current and historical network status data to correct channel scores. Perform comprehensive scoring and ranking to generate a comparable list of channel priorities to drive decision-making.

6. The wireless network signal conversion method according to claim 5, characterized in that, The interference analysis and judgment includes identifying signal characteristics in the radio frequency spectrum: If the signal characteristics match the known Wi-Fi beacon frame format, it is determined to be co-channel Wi-Fi interference; If the signal characteristics are high-frequency narrowband pulses and conform to the Bluetooth frequency hopping pattern, it is determined to be Bluetooth interference; If the signal characteristics are broadband continuous noise, it is determined to be non-Wi-Fi electrical appliance interference; For each signal source identified as interference, the interference penalty value on channel quality is calculated based on its signal strength and duty cycle.

7. The wireless network signal conversion method according to claim 5, characterized in that, The real-time performance assessment includes monitoring the device's real-time performance metrics on the current channel and querying the historical performance database: If the real-time packet retransmission rate exceeds the first preset threshold, it is determined that the current channel quality has deteriorated instantaneously, and a real-time quality penalty value is generated. If the historical average throughput of the channel is lower than the second preset threshold during the current period, it is determined that the channel has periodic performance degradation, and a historical trend penalty value is generated.

8. The wireless network signal conversion method according to claim 5, characterized in that, The process of performing comprehensive scoring and ranking includes assigning a basic score to each channel, sequentially calculating various penalty values ​​generated by interference analysis and real-time performance assessments, obtaining a final comprehensive score, and comparing the final comprehensive scores of all channels: If the score of the first channel is higher than that of the second channel, then the first channel will be ranked before the second channel in the priority list. If the scores are the same, the channel numbers are compared, and the channel with the smaller number is ranked first. Finally, the sorted channel priority list is output.

9. The wireless network signal conversion method according to claim 4, characterized in that, After the final allocation scheme is generated, a coordination transaction identifier containing the hash value of the final allocation scheme and a preset execution time sequence is broadcast on the coordination channel, and the acknowledgment responses returned by neighboring devices to this identifier are listened for and collected. If valid confirmations are received from all relevant neighbors in the coordination group within the preset timeout window, the final allocation scheme will be marked as an executable scheme that has reached a coordination consensus, and the process will proceed to S454. Otherwise, the coordination transaction will be rolled back, and the conflict resolution process will be re-executed.

10. A wireless network signal conversion system, applied to a wireless network signal conversion method as described in any one of claims 1-9, characterized in that, include: The full-band scanning module, through the integration of a broadband radio frequency sampling front end, performs periodic scanning of the operating frequency band to obtain raw spectrum data including signal strength and noise floor. The interference feature identification and classification module performs signal demodulation and feature matching on the raw spectrum data to obtain a classified spectrum map that accurately identifies Wi-Fi networks, Bluetooth devices and other pulse interference sources; The channel quality assessment and ranking module compares and correlates the classified spectrum with the real-time performance data of the network and performs weighted calculations to obtain a list of channel priorities ranked by comprehensive scores. The distributed coordination module, through the coordination channel, merges and coordinates the local priority list with the neighbor list obtained from information exchange with neighboring routers to obtain a coordinated regional channel allocation scheme. The seamless channel switching execution module executes the standard channel switching announcement protocol according to the regional channel allocation scheme and controls the radio frequency front end to reconfigure in precise timing to obtain a new channel link that is seamlessly switched to the connected client and completes the hardware switching. The closed-loop verification module performs continuous performance monitoring on the new channel, compares and analyzes the collected throughput, latency, and retransmission rate data with the predicted performance before the handover, and completes the verification of the effectiveness of this collaboration.

Images