Anti-interference method and system for wireless audio equipment

Abstract

The invention discloses an anti-interference method and system for wireless audio equipment, relates to the technical field of anti-interference, and aims to determine a corresponding data delay level according to a scene influence factor, a plurality of data delay factors and a working state of the wireless audio equipment, so that the accuracy of the data delay level is improved. Therefore, a dynamic data transmission system of the wireless audio equipment is constructed according to the wireless transmission environment, the data delay level and the corresponding to-be-transmitted data, and a plurality of interference nodes are marked based on identification of the dynamic data transmission system; in the plurality of interference nodes, the anti-interference event of the wireless audio equipment is triggered based on the node position of each interference node, the corresponding interference form and the dynamic data transmission system, and the corresponding anti-interference mode is determined based on the identification of the anti-interference event, so that the adaptability of the anti-interference mode of the wireless audio equipment is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of anti-interference, and in particular to an anti-interference method and system of a wireless audio device. BACKGROUND

[0002] With the development of science and technology, wireless audio devices perform data transmission based on wireless networks and wirelessly transmit corresponding audio data. The wireless audio devices have corresponding interference factors in different scenarios, which affect the data transmission of the wireless audio devices. In the prior art, the scenario in which the wireless audio device is located is collected, and corresponding scenario factors are marked. Based on the scenario factors and the data transmission state of the wireless audio device, a corresponding delay level is determined. However, multiple data delay factors are ignored, which affects the accuracy of the data delay level and results in low adaptability of the anti-interference mode of the wireless audio device. SUMMARY

[0003] The present application aims to overcome the shortcomings of the prior art, and provides an anti-interference method and system of a wireless audio device.

[0004] The anti-interference method of the wireless audio device provided by the embodiments of the present application comprises the following steps. Wireless transmission data of the wireless audio device is collected, corresponding data transmission events are determined according to each wireless transmission data and a response behavior of the wireless audio device, and multiple data delay factors are determined based on the identification of the data transmission events. Corresponding scenario influence factors are determined based on the scenario in which the wireless audio device is located, and a corresponding data delay level is determined according to the scenario influence factors, the multiple data delay factors and a working state of the wireless audio device. The wireless transmission environment of the wireless audio device and a corresponding interactive device is marked, a dynamic data transmission system of the wireless audio device is constructed according to the wireless transmission environment, the data delay level and corresponding to-be-transmitted data, and multiple interference nodes are marked based on the identification of the dynamic data transmission system. Among the multiple interference nodes, an anti-interference event of the wireless audio device is triggered based on the node position of each interference node, the corresponding interference mode and the dynamic data transmission system, and a corresponding anti-interference mode is determined based on the identification of the anti-interference event.

[0005] The anti-interference system of the wireless audio device provided by the embodiments of the present application is applied to the anti-interference method of the wireless audio device described above.

[0006] Compared with the prior art, the present application has the following advantages: The system collects wireless transmission data from wireless audio devices, determines corresponding data transmission events based on each wireless transmission data and the response behavior of the wireless audio devices, and identifies multiple data delay factors based on the identification of these data transmission events. It also determines corresponding scene influencing factors based on the scene in which the wireless audio devices are located, and determines the corresponding data delay level based on these scene influencing factors, multiple data delay factors, and the working status of the wireless audio devices. This approach incorporates scene influencing factors, taking into account the scene influencing factors, multiple data delay factors, and the working status of the wireless audio devices, thus improving the accuracy of the data delay level.

[0007] Therefore, the wireless transmission environment of the wireless audio device and its corresponding interactive device is marked. Based on this wireless transmission environment, data delay level, and corresponding data to be transmitted, a dynamic data transmission system for the wireless audio device is constructed. Multiple interference nodes are marked based on the identification of this dynamic data transmission system. Among the multiple interference nodes, anti-interference events of the wireless audio device are triggered based on the node location, corresponding interference pattern, and the dynamic data transmission system. Based on the identification of the anti-interference event, the corresponding anti-interference mode is determined, and multiple interference nodes are controlled. This realizes the triggering of anti-interference events of the wireless audio device and improves the adaptability of the anti-interference mode of the wireless audio device. Attached Figure Description

[0008] Figure 1 This is a flowchart illustrating the anti-interference method for a wireless audio device in an embodiment of the present invention. Figure 2 This is a flowchart illustrating step S11 of the anti-interference method for a wireless audio device in an embodiment of the present invention. Figure 3 This is a flowchart illustrating step S12 of the anti-interference method for a wireless audio device in an embodiment of the present invention. Figure 4 This is a flowchart illustrating step S13 of the anti-interference method for a wireless audio device in an embodiment of the present invention. Figure 5 This is a flowchart illustrating step S14 of the anti-interference method for a wireless audio device in an embodiment of the present invention. Figure 6 This is a schematic diagram of the structure of the anti-interference system of the wireless audio device in an embodiment of the present invention. Detailed Implementation

[0009] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0010] Please see Figures 1 to 6 An anti-interference method for a wireless audio device, applied in anti-interference scenarios; the anti-interference method for the wireless audio device includes: Step S11: Collect wireless transmission data from wireless audio devices, determine the corresponding data transmission events based on each wireless transmission data and the response behavior of wireless audio devices, and determine multiple data delay factors based on the identification of the data transmission events; Step S12: Determine the corresponding scene influencing factors based on the scene where the wireless audio device is located, and determine the corresponding data delay level based on the scene influencing factors, multiple data delay factors and the working status of the wireless audio device; Step S13: Mark the wireless transmission environment of the wireless audio device and the corresponding interactive device, construct a dynamic data transmission system for the wireless audio device based on the wireless transmission environment, data delay level and corresponding data to be transmitted, and mark multiple interference nodes based on the identification of the dynamic data transmission system; Step S14: Among multiple interference nodes, based on the node location of each interference node, the corresponding interference pattern and the dynamic data transmission system, trigger the anti-interference event of the wireless audio device, and determine the corresponding anti-interference mode based on the identification of the anti-interference event; Step S15: Determine dynamic lighting events based on the key audio data of each sub-audio control node, the corresponding lighting control content, and the working status of each light pole, and construct a collaborative control system for multiple light poles and audio equipment.

[0011] refer to Figure 2 In step S11, the specific steps are as follows: S111: When the wireless audio device is in wireless transmission mode, mark the wireless transmission channel of the wireless audio device, determine the wireless transmission data of the wireless audio device based on the detection of the wireless transmission channel, and determine multiple sub-wireless data combinations based on the identification of the wireless transmission data. S112: Collect the response signal of the wireless audio device, determine the response behavior of the wireless audio device based on the parsing of the response signal, determine multiple data transmission items based on the response behavior of the wireless audio device and multiple sub-wireless data combinations, determine the corresponding data transmission event based on the multiple data transmission items and the working state of the wireless audio device, determine multiple data delay events based on the identification of the data transmission event, and mark the corresponding data delay factors to determine multiple data delay factors.

[0012] In the embodiments of this application, when the wireless audio device is in a wireless transmission state, the wireless transmission channel of the wireless audio device is marked, and the wireless transmission data of the wireless audio device is determined based on the detection of the wireless transmission channel. Multiple sub-wireless data combinations are determined based on the identification of the wireless transmission data, which is compatible with the overall consideration of the identification of wireless transmission data and ensures the accuracy of multiple sub-wireless data combinations.

[0013] At this time, when the system starts up, it will establish an independent logical channel for the dual transmitter-single receiver architecture based on the ATS2831 chip. This is not only a physical connection, but also creates a channel context for TX1, TX2 and RX respectively, which includes channel ID, operating frequency, modulation method, encryption key and initial link quality benchmark. This marking mechanism ensures the traceability and distinguishability of subsequent data streams.

[0014] The system continuously collects multi-dimensional metadata for each channel at a high sampling rate through the RF front-end and baseband processor, including channel quality indicators (such as real-time RSSI, SNR, PER), data packet layer information (sequence number, retransmission count), and RF layer status (working channel, transmit power). The system aggregates the raw time series data in real time according to preset templates to form structured data blocks such as signal quality combination, data packet integrity combination, and RF resource combination, transforming discrete data points into information units with clear physical meaning.

[0015] Specifically, in a home karaoke scenario, when the wireless audio device is activated, the system immediately creates a CTX1 channel (2412MHz, -45dBm) for the microphone on the living room sofa and a CTX2 channel (2417MHz, -60dBm) for the microphone at the bedroom door, while simultaneously establishing a CRX receiver channel. When the user sings in the bedroom, the system continuously monitors the CTX2 channel. At T=10.6s, it suddenly records that the RSSI drops sharply from -62dBm to -75dBm, the SNR drops from 18dB to 12dB, and the PER rises to 0.1%. The system then generates two key data combinations: one reflecting instantaneous channel degradation (average RSSI -77.5dBm, average SNR 10dB, 3 CRC errors), and the other showing stable RF status (constant transmit power 10dBm, normal temperature 45°C). This structured data clearly indicates that the interference originates from external factors rather than device malfunctions, providing accurate input for subsequent intelligent anti-interference decisions.

[0016] Furthermore, the response signals of the wireless audio device are collected, and the response behavior of the wireless audio device is determined based on the analysis of the response signals. Multiple data transmission items are determined based on the response behavior of the wireless audio device and multiple sub-wireless data combinations. The corresponding data transmission events are determined based on the multiple data transmission items and the working status of the wireless audio device. Multiple data delay events are determined based on the identification of the data transmission events, and the corresponding data delay factors are marked. This process of identifying multiple data delay factors is compatible with the overall consideration of data transmission event identification and ensures the accuracy of multiple data delay events.

[0017] At this time, the system deeply monitors the key nodes of the ATS2831 chip and its peripheral circuits, and collects response signals in real time from the RF layer (such as the dynamic adjustment of AGC gain and the lockout state of PLL), the baseband layer (such as the synchronization loss or checksum error interruption thrown by the audio decoder), and even the power management layer (such as the output voltage ripple and real-time current consumption of the ME6322 voltage regulator chip). Based on the built-in expert rule base, the system interprets these raw physiological signals into response behaviors with clear physical meaning, such as gain surge and decoder entering high-frequency error correction mode.

[0018] Through a high-efficiency correlation engine, the structured sub-data produced in step S111 is combined with these response behaviors and aligned with millisecond-level time windows and logical causal matching. This allows the external channel degradation phenomenon to be correlated with the internal gain adjustment behavior, generating data transmission projects with clear causal chains, such as signal quality sabotage projects or data integrity impairment projects.

[0019] The system further intelligently aggregates multiple closely related data transmission items into a complete data transmission event and immediately assesses its actual impact on user experience. For example, by monitoring whether the audio buffer level at the receiving end falls below the safety lower limit or whether the synchronization error between the two transmitters exceeds the acceptable threshold, once the performance indicators deteriorate, the event is officially marked as a data delay event.

[0020] Based on this confirmation, the system initiates a deep diagnostic process. It eliminates the possibility of equipment malfunction and performs high-precision matching of the key characteristics of the event (such as the frequency band, intensity, and duration of the interference) with the preset 2.4GHz band interference feature library. Through intelligent reasoning and causal tracing, it ultimately accurately identifies the root cause of the delay, such as the non-periodic strong electromagnetic interference of the microwave oven.

[0021] Specifically, the system collected signals such as a 15dB surge in the ATS2831's AGC gain within 100ms and five consecutive CRC check failure interrupts from the decoder, and analyzed these as specific response behaviors. The system then correlated the instantaneous channel degradation data detected in step S111 to generate signal quality countermeasures and data integrity impairment items. These two items were further aggregated into a sudden radio frequency interference event caused by a microwave oven. At the same time, the system detected a 30% drop in the receiver's audio buffer level, triggering an underload warning. Therefore, this event was officially marked as a data delay event. Through feature matching, the system confirmed that the sudden drop in RSSI at 2.45GHz highly matched the microwave oven characteristics in the interference database. Combined with user behavior, the system successfully marked the delay factor as non-periodic strong electromagnetic interference from a microwave oven, providing a clear diagnostic basis for subsequent precise anti-interference strategies.

[0022] refer toFigure 3 In step S12, the specific steps are as follows: S121: Based on the surrounding detection of the wireless audio device, determine multiple scene features, determine multiple scene influence combinations based on the feature positions, corresponding feature shapes and the current position of the wireless audio device, and determine the corresponding scene influence factors based on the recognition of multiple scene influence combinations. S122: Collect multiple working data from the wireless audio device, determine the working status of the wireless audio device based on the identification of the multiple working data, and determine the first data delay coefficient based on the working status of the wireless audio device and the influencing factors of the scenario. S123: Determine the second data delay coefficient based on the working status of the wireless audio device and multiple data delay factors, and determine the corresponding data delay level based on the mapping relationship between the first data delay coefficient, the second data delay coefficient and the data delay level.

[0023] In the embodiments of this application, multiple scene features are determined based on the surrounding detection of the wireless audio device. Multiple scene influence combinations are determined based on the feature positions, corresponding feature shapes, and the current position of the wireless audio device. The corresponding scene influencing factors are determined based on the identification of multiple scene influence combinations. This approach takes into account the overall consideration of identifying multiple scene influence combinations and ensures the accuracy of the corresponding scene influencing factors.

[0024] At this time, the system drives the RF front-end of the ATS2831 chip to perform a high-resolution FFT scan of the entire 2.4GHz ISM band. By finely analyzing the spectral energy distribution, it distinguishes the OFDM characteristic peaks of Wi-Fi signals, the frequency hopping energy traces of Bluetooth signals, and the broadband impulse noise pattern generated by the microwave oven magnetron. At the same time, the system analyzes the time-domain waveform of the channel impulse response, quantifies the delay, intensity, and number of each reflection peak in multipath propagation, and activates the dual-MIC array to synchronously collect the ambient background noise, calculate its spectral structure and coherence, and thus derive the acoustic reverberation characteristics of the space. These RF, spatial, and acoustic data together constitute the basic scene characteristics describing the complexity of the environment.

[0025] The system deeply correlates and fuses these isolated features. It uses the time difference of arrival (TDoA) between two microphones to triangulate and estimate strong interference sources. It also performs morphological fusion of Wi-Fi signals from specific directions with multipath reflection features from the same direction to construct scene impact combinations with clear physical orientations, such as the superposition of fixed Wi-Fi co-frequency interference and wall multipath effects. The system performs high-speed pattern matching of these real-time generated combinations with the built-in scene knowledge base. Through induction and identification, it abstracts specific physical phenomena and names them as macroscopic scene impact factors. For example, it accurately identifies non-periodic broadband pulse combinations as sudden electromagnetic pulse interference caused by microwave ovens, thus completing the final, highly structured qualitative characterization of environmental challenges.

[0026] Specifically, the wireless audio device performed a spectrum scan and detected persistent Wi-Fi energy peaks in the 2.412 GHz and 2.437 GHz channels, while also detecting periodic microwave oven pulse noise near 2.45 GHz. CIR analysis revealed two reflection paths with delays of 150 ns and 300 ns, in addition to the direct path, indicating that the signal was reflected by walls. The system combined these features to infer the presence of a Wi-Fi router in a certain direction, with the signal path attenuated by walls, forming a radio frequency-spatial combination. Simultaneously, the pulse characteristics of the microwave oven were combined with its non-periodic timing pattern, forming a radio frequency-time combination. By matching a knowledge base, the system identified the former as a persistent influencing factor resulting from the superposition of fixed Wi-Fi co-channel interference and the multipath effect of walls, and the latter as a transient influencing factor resulting from the sudden electromagnetic pulse interference caused by the microwave oven. Thus, the device not only knew that the signal was interfered with, but also more accurately understood the source, nature, and composition of the interference, laying a solid foundation for taking targeted anti-interference measures.

[0027] Furthermore, multiple working data points of the wireless audio device are collected, and the working status of the wireless audio device is determined based on the identification of these multiple working data points. The first data delay coefficient is determined based on the working status of the wireless audio device and the influencing factors of the scenario. This approach takes into account both the working status of the wireless audio device and the influencing factors of the scenario, ensuring the accuracy of the first data delay coefficient.

[0028] At this time, the system reads the registers of the ATS2831 chip and peripheral circuits to comprehensively collect radio frequency parameters (such as transmit power and working channel), baseband and audio parameters (such as coding rate and frame length settings), and power consumption and performance parameters (such as system current and CPU utilization). These data are not viewed in isolation, but are integrated into a meaningful working state vector. For example, high transmit power, high code rate and long frame length are combined to comprehensively determine a high throughput and long-distance transmission state, thereby accurately reflecting the current task priority and resource allocation strategy of the device.

[0029] The system takes the macro-level scene influencing factors output by S121 and the current working state as input and feeds them into a built-in multi-dimensional evaluation model. The model performs fusion calculations based on the persistence weight of different scene influencing factors (e.g., fixed Wi-Fi interference is higher than sudden microwave oven interference) and the vulnerability score of different working states to interference (e.g., high-fidelity state is more sensitive to stuttering), and finally outputs a first data delay coefficient between 0 and 1. This forward-looking indicator accurately quantifies the potential delay risk that environmental factors may cause to transmission under the current working state.

[0030] Specifically, the system detected that the device was operating at a high power of 12dBm, a high bit rate of 48kbps, and a long frame length of 5ms. This indicates that the device was operating at high power and high fidelity, meaning it was doing its utmost to ensure sound quality. Simultaneously, the S121 identified the complex electromagnetic and acoustic environment of the stage as a contributing factor. The evaluation model determined this complex environment to be a high-weight, persistent threat. While the high power and high fidelity were being maintained, the system's redundancy was low, making it relatively vulnerable overall. The model calculated a first data delay coefficient as high as 0.85, clearly indicating that the device was operating at full capacity.

[0031] Therefore, a second data delay coefficient is determined based on the working status of the wireless audio device and multiple data delay factors. The corresponding data delay level is determined based on the mapping relationship between the first data delay coefficient, the second data delay coefficient, and the data delay level. This approach takes into account the overall consideration of the mapping relationship between the first data delay coefficient, the second data delay coefficient, and the data delay level, ensuring the accuracy of the corresponding data delay level.

[0032] At this point, the system focuses on quantifying data delay events that have occurred and caused actual impact. Based on the specific data delay factors identified by S11, it determines the second data delay coefficient through a calculation model that includes factor weights, impact quantification, and working status correction. This model will preset weights for different delay factors (such as microwave oven interference) and quantify them according to the performance degradation indicators they cause (such as packet loss rate and synchronization error). At the same time, it will make corrections based on the current working status of the equipment (such as low latency mode being more sensitive to synchronization error), and finally output a coefficient value.

[0033] The system weights and fuses the first data delay coefficient, representing the potential threat, with the second data delay coefficient, representing the actual impact. For example, it calculates the data delay using a comprehensive scoring formula (comprehensive score = α × first coefficient + β × second coefficient). This comprehensive score is mapped to a preset discrete level set, such as {low, medium, high, urgent}. Each level corresponds to a clear performance range and a preset response strategy, thus forming a final data delay level that directly guides subsequent actions.

[0034] Specifically, the system evaluates the delay factors identified by S11: sudden microwave interference and multipath attenuation caused by signal obstruction. Microwave interference causes a sudden spike in packet loss rate, while signal obstruction increases synchronization error. Since the equipment is in a low-latency operating state, the increase in synchronization error is given a higher negative weight. After comprehensive calculation, the system outputs a second data delay coefficient of 0.6, indicating that the interference has caused a moderate to high actual impact. In the final evaluation stage, the system merges this coefficient (0.6) with the first coefficient (assumed to be 0.4) from S122, which represents the potential threat. The system calculates a comprehensive score of 0.48 using the formula (e.g., comprehensive score = 0.6 x 0.4 + 0.4 x 0.6 = 0.48). This score is mapped to a preset level range, and the final data delay level is rated as medium. This medium level serves as a clear instruction, informing the equipment that the current situation is noteworthy. Although it has not reached a crisis level, the corresponding anti-interference plan must be activated to prevent the situation from deteriorating further.

[0035] refer to Figure 4 In step S13, the specific steps are as follows: S131: Based on the tracing of wireless audio devices, determine the corresponding interactive devices, monitor the dynamic interaction between wireless audio devices and interactive devices in real time, collect multiple dynamic interactive signals, and determine the corresponding wireless transmission environment based on multiple dynamic interactive signals, wireless audio devices and interactive devices. S132: Determine the corresponding data to be transmitted based on the detection of the wireless audio device, determine the first layer of data transmission content based on the wireless transmission environment and the data to be transmitted, construct and determine the second layer of data transmission content based on the data delay level and the data to be transmitted, and construct the dynamic data transmission system of the wireless audio device based on the first layer of data transmission content and the second layer of data transmission content. S133: Based on the identification of the dynamic data transmission system, multiple transmission anomalies are identified. Based on the detection of each transmission anomaly, the corresponding interference content and time point are determined. Based on the interference content, time point and the working status of the wireless audio device, multiple interference nodes are determined and marked.

[0036] In the embodiments of this application, the corresponding interactive device is determined based on the tracing of the wireless audio device, the dynamic interaction between the wireless audio device and the interactive device is monitored in real time, and multiple dynamic interactive signals are collected. The corresponding wireless transmission environment is determined based on the multiple dynamic interactive signals, the wireless audio device and the interactive device. This approach takes into account the overall consideration of multiple dynamic interactive signals, the wireless audio device and the interactive device, and ensures the accuracy of the corresponding wireless transmission environment.

[0037] At this point, the system obtains the unique identifier (such as MAC address) of the interacting device through the identification mechanism of the protocol layer, such as the Bluetooth pairing process or Wi-FiDirect negotiation, and binds it with a logical device name (such as Soundbar-LivingRoom-01) to establish the communication relationship and ensure the accuracy of subsequent monitoring.

[0038] The system continuously and with high precision monitors the bidirectional information flow between established device pairs. It extracts key signals from the uplink (such as packet transmission timestamps and transmit power) and downlink (such as RSSI, SNR, and ACK / NACK feedback) in real time using the ATS2831 chip, and adds microsecond-level timestamps to form a dynamic interactive signal flow. The system aggregates and calculates these raw signals to generate key performance indicators such as round-trip time (RTT), average signal quality, jitter, and packet loss rate (PER). Combined with device pair information, it ultimately constructs a structured, multi-dimensional wireless transmission environment model.

[0039] Specifically, the wireless audio device establishes a connection with the living room soundbar via BLE broadcast. During the handshake process, it obtains the device name JBL-Soundbar-5.1 and MAC address, thus establishing the interaction partner. During karaoke, the system continuously monitors the data packet transmission of the TX1 transmitter in the uplink and simultaneously captures the ACK confirmation and RSSI and SNR reports returned by the soundbar in the downlink, forming paired, timestamped dynamic interactive signal streams. Based on these signals, the system ultimately constructs a wireless transmission environment model for this pair of devices, clearly presenting key indicators such as {average round-trip time: 8ms, latency jitter: 2ms, average signal-to-noise ratio: 28dB, packet loss rate: 0.01%}. This healthy model not only reflects the excellent state of the current link in real time but also serves as a dynamic baseline. If a significant deviation occurs subsequently, the system can immediately identify the anomaly.

[0040] Furthermore, the corresponding data to be transmitted is determined based on the detection of the wireless audio device. The first layer of data transmission content is determined based on the wireless transmission environment and the data to be transmitted. The second layer of data transmission content is determined based on the data delay level and the data to be transmitted. A dynamic data transmission system for the wireless audio device is constructed based on the first layer of data transmission content and the second layer of data transmission content. This system takes into account the overall considerations of data delay level and the construction of the data to be transmitted, ensuring the accuracy of the second layer of data transmission content.

[0041] At this point, the system performs real-time feature analysis on the original audio payload through the DSP unit of the ATS2831 chip, distinguishes between speech and music signals based on the spectral centroid and zero-crossing rate, and evaluates its complexity by calculating short-time energy entropy, thereby classifying and labeling the data to be transmitted.

[0042] The system combines these data features with the wireless transmission environment model constructed by S131, and determines the basic transmission parameters through a decision matrix. For example, it forces the use of short frame mode for voice data in a jitter environment, or uses long frames for music data to improve throughput in a high-quality link. At the same time, it adaptively adjusts the forward error correction redundancy according to the packet loss rate to form the first layer of data transmission content.

[0043] The system combines the data delay level assessed by S12 with the data type to make higher-level strategic decisions. It selects and activates corresponding strategies from the anti-interference tool library. For example, it activates the LSTM interference prediction model and authorizes frequency hopping at a high level, and fully activates the spatiotemporal joint defense system at an emergency level, forming a second layer of data transmission content. The system integrates these two layers into a unified configuration instruction set, which is distributed to various execution units of the ATS2831 chip through the internal bus, thereby building a complete dynamic data transmission system that can be adjusted in real time.

[0044] Specifically, the system analyzes the lead singer's microphone signal and determines that its short-time energy entropy is 0.25, belonging to high-priority vocal data. Combined with the slight jitter shown by the S131 environmental model, the system compresses the frame length to 1ms to enhance anti-jitter capability, forming the first layer of transmission content. At this time, if S12 detects that the microwave oven in the kitchen is turned on and rates the delay level as high, the system activates the LSTM interference prediction model and authorizes it to immediately hop frequencies when high-probability interference is predicted, while forcibly enabling link pre-decision, forming the second layer of strategy content. The system integrates these two parts to construct a complete dynamic data transmission system instruction: transmit vocal data in 1ms short frames, activate LSTM prediction frequency hopping, and forcibly enable link pre-decision. This instruction is immediately issued and executed, putting the wireless audio device into a highly vigilant active defense mode to prioritize the continuity of key vocals and avoid stuttering during the performance.

[0045] Therefore, based on the identification of the dynamic data transmission system, multiple transmission anomalies are identified. The corresponding interference content and time points are determined based on the detection of each anomaly. Multiple interference nodes are then identified based on the interference content, time points, and the operating status of the wireless audio equipment. This approach marks multiple interference nodes, taking into account the overall consideration of interference content, time points, and the operating status of the wireless audio equipment, ensuring the accuracy of multiple interference nodes. Simultaneously, scene-related factors are introduced, taking into account these factors, multiple data delay factors, and the operating status of the wireless audio equipment, thus improving the accuracy of data delay levels.

[0046] At this time, when the system is running in a dynamic data transmission system, it monitors multiple key performance indicators such as latency, quality, synchronization and link in parallel. Once any indicator, such as end-to-end round-trip time (RTT) or its jitter exceeds the preset safety threshold, or packet loss rate (PER) shows a sudden jump, or the synchronization error between the two transmitters, the received signal strength indication (RSSI) of the main link and the signal-to-noise ratio (SNR) fall below the minimum threshold for maintaining the link, the system will immediately identify this deviation behavior and mark it as an independent transmission anomaly. The system performs in-depth root cause analysis on each abnormal item by rapidly correlating it with real-time wireless transmission environment data collected by S131 and using feature matching algorithms to identify the specific physical form of interference. For example, it identifies broadband pulses in the spectrum as microwave oven interference or continuous energy peaks on a specific channel as Wi-Fi co-channel interference. At the same time, it uses high-precision timestamps to accurately locate the moment when the anomaly first occurs and combines trend analysis to predict its duration.

[0047] The system will integrate the abnormal transmission items, interference content, time nodes, and the current working status of the equipment (such as transmission power and encoding mode) to build a structured interference node containing the whole picture of the problem. This interference node is then pushed into a high-priority pending event queue and triggers a system-level interrupt or event flag, thereby providing a clear, explicit, and directly callable action instruction for step S14.

[0048] Specifically, the system continuously monitors the synchronization status of the lead singer's microphone and the accompaniment signal. When the lead singer moves the microphone behind the sofa, the system detects that the phase difference between the two signals momentarily exceeds the synchronization threshold, immediately marking a synchronization loss anomaly. The system reviews the data and finds that the RSSI of the lead singer's microphone drops sharply at the same time. Combining the microphone's movement information, the system identifies the interference as an aggravation of multipath interference caused by human occlusion, and accurately records the start time and expected duration of the anomaly. The system integrates this information to construct and mark a complete interference node. This node clearly indicates that at a specific time, the lead singer's microphone link suffered multipath interference due to occlusion. This marked node immediately becomes the action command for step S14, triggering the system to activate the corresponding anti-interference mode, such as activating deep Kalman filtering or increasing the microphone's transmission power, to combat the interference in real time.

[0049] refer to Figure 5 In step S14, the specific steps are as follows: S141: Dynamically monitor each interference node and mark the node position of each interference node. At the same time, determine the corresponding interference pattern based on the tracing of each interference node, and determine the corresponding anti-interference elements according to the node position of each interference node, the corresponding interference pattern and the dynamic data transmission system. S142: Determine the anti-interference event of the wireless audio device based on multiple anti-interference factors and the working status of the wireless audio device, so as to trigger the anti-interference event of the wireless audio device; determine multiple sub-anti-interference items based on the identification of the anti-interference event; S143: Determine the corresponding anti-interference mode based on the content of each sub-anti-interference project, the corresponding project priority, and the data load of the wireless audio device, and mark the anti-interference status of the wireless audio device so that the wireless audio device can dynamically adjust the data parameters in the anti-interference state.

[0050] In the embodiments of this application, each interference node is dynamically monitored and its location is marked. At the same time, the corresponding interference pattern is determined based on the tracing of each interference node. The corresponding anti-interference elements are determined according to the node location of each interference node, the corresponding interference pattern, and the dynamic data transmission system. This approach takes into account the overall consideration of the node location of each interference node, the corresponding interference pattern, and the dynamic data transmission system, ensuring the accuracy of the corresponding anti-interference elements.

[0051] At this point, the system performs real-time and continuous dynamic monitoring of each interference node, tracking not only its complete lifecycle in the time dimension and real-time impact changes in the intensity dimension, but also constructing a four-dimensional coordinate system for it that includes the frequency domain, time domain, spatial domain, and link location. By recording the center frequency and bandwidth occupied by the interference, marking its start and end timestamps using a high-precision timer, estimating its azimuth angle relative to the device with the help of TDoA or beamforming, and clearly indicating the specific communication link it affects, the system can accurately lock onto the interference target.

[0052] The system performs precise pathological analysis on nodes by matching the real-time spectrum and waveform characteristics of nodes with the built-in interference database at high speed. It combines this with the analysis of the behavioral patterns of interference time series (such as persistence, periodicity, or burstiness) and uses the channel impulse response (CIR) to determine the propagation path. Finally, it traces the interference morphology to specific categories such as constant interference at the same frequency, adjacent channel interference at different frequencies, non-periodic pulse interference, or broadband blocking interference.

[0053] Based on the precise location of the node and the specific form traced back, the system queries the internal countermeasure knowledge base and transforms the abstract analysis results into a series of specific anti-interference elements that can be directly called by the system. Each element encapsulates clear action instructions and expected effects. For example, it generates a frequency domain evasion element {Action: Evasion, Target: [2.412-2.427GHz], Expected Gain: 15dB}, or a spatial domain suppression element {Action: Suppression, Direction: 180°, Method: Antenna Beamforming, Expected Gain: 20dB}.

[0054] Specifically, for the interference node Node-Karaoke-001 caused by the lead singer's movement, the system dynamically monitors and marks its location, continuously tracks its intensity fluctuations, and determines that it causes broadband attenuation in the frequency domain, records the precise start and end times in the time domain, locates the interference source in the spatial domain via TDoA (directly behind the equipment, on the sofa), and clearly marks it as affecting the lead singer's MIC-RX link. The system performs morphological tracing, matching the database and analyzing behavioral patterns, combined with CIR analysis showing attenuation in the direct path and enhancement in the reflected path, ultimately determining the morphology as broadband signal attenuation caused by human occlusion and the superposition of multipath effects. Based on this, the system generates specific anti-interference elements: one at the link layer, triggering intelligent link switching to a backup link (such as a stable link for the accompaniment signal) when the lead singer's MIC SNR is too low; the other at the baseband layer, activating deep Kalman filtering to remove multipath reflection components. These elements are packaged and passed to the next step, constituting the direct basis for accurately combating this interference.

[0055] Furthermore, anti-interference events of the wireless audio device are determined based on multiple anti-interference factors and the working status of the wireless audio device to trigger anti-interference events of the wireless audio device; multiple sub-anti-interference items are determined based on the identification of anti-interference events, which takes into account multiple anti-interference factors and the overall working status of the wireless audio device to ensure the accuracy of anti-interference events of the wireless audio device.

[0056] At this point, the system will comprehensively analyze the multiple anti-interference elements generated by S141 with the current real-time operating status of the device. This process involves element aggregation, which correlates multiple tactical elements (such as frequency hopping and filtering) targeting the same interference node. Combined with device status assessment, key indicators such as current transmit power, CPU / DSP load, and remaining power are considered. Finally, through a conflict resolution mechanism, elements that may have command conflicts are arbitrated according to preset priority rules (such as stability taking precedence over power consumption). When the analysis results indicate that coordinated action is necessary to effectively combat interference, the system will trigger a high-priority system-level anti-interference event. This signifies that the device status has officially switched from the conventional dynamic transmission mode to the comprehensive anti-interference mode.

[0057] The system meticulously decomposes this macroscopic anti-interference event into a set of specific sub-anti-interference projects, which can be assigned to different hardware or software modules for parallel execution, according to the principles of functional domain, execution timing, and project independence. Each sub-project encapsulates clear execution instructions, target parameters, and expected results. For example, an RF sub-project might contain {execution module: RF front-end, instruction: execute LSTM prediction frequency hopping, target channel: avoid 2.45GHz, expected result: packet loss rate <0.05%}, a baseband sub-project might contain {execution module: DSP, instruction: load notch filter coefficients, center frequency: 2.45GHz, expected result: interference suppression >20dB}, and an application layer sub-project might contain {execution module: audio encoder, instruction: switch frame length, from: 5ms to: 1ms, expected result: end-to-end latency <30ms}. This decomposition mechanism ensures that complex anti-interference strategies can be implemented in an orderly and efficient parallel manner, thereby greatly shortening the overall system response time.

[0058] Specifically, in response to microwave oven interference, the system integrates three anti-interference elements: intelligent frequency hopping, narrowband notch filtering, and switching to short frames. After assessing that the device has sufficient power and the DSP load rate is low, the system determines that there is no conflict and a coordinated response is required, thus formally triggering the anti-interference event -EVT-HOME-001, and the device status indicator light turns yellow as a warning. This event is quickly decomposed into three sub-projects: Sub-project A commands the RF front-end to switch to a clean channel based on LSTM prediction; Sub-project B commands the DSP to load a narrowband notch filter for 2.45GHz to provide immediate protection; Sub-project C commands the audio encoder to switch the frame length from 5ms to 1ms to reduce the duration of audio interruptions caused by interference. These three sub-projects are simultaneously dispatched to the corresponding modules for parallel execution, marking the entry of the device into a comprehensive and efficient anti-interference implementation phase.

[0059] Therefore, based on the project content, corresponding priority, and data load of each sub-anti-interference project, the corresponding anti-interference mode is determined, and the anti-interference status of the wireless audio device is marked. This allows the wireless audio device to dynamically adjust data parameters in the anti-interference state, taking into account the overall consideration of the project content, priority, and data load of each sub-anti-interference project, ensuring the accuracy of the corresponding anti-interference mode. At the same time, multiple interference nodes are managed, enabling the triggering of anti-interference events for the wireless audio device and improving the adaptability of the anti-interference mode of the wireless audio device.

[0060] At this point, the system performs a global resource trade-off and strategy selection. It dynamically prioritizes each sub-anti-interference item, for example, giving the highest priority to radio frequency items that prevent link interruption (such as frequency hopping), while giving the next priority to baseband items that improve sound quality (such as filtering). Combining the load analysis of the data type and bit rate to be transmitted, it finally matches the system with multiple built-in anti-interference modes (such as the power saving mode representing minimum power consumption, the balanced mode that balances performance and power consumption, the performance mode that pursues effect at all costs, or the emergency mode that deals with the imminent link interruption). After comprehensive consideration through a weighted decision function, it decides on the anti-interference mode that is most suitable for the current situation.

[0061] The system makes a system-level announcement by updating the core status register or flags to formally switch the device state from normal operation or alert to the selected anti-interference mode. This global flag allows the system interrupt service routine, task scheduler and all other functional modules to read the state and adjust their behavior accordingly.

[0062] Based on the selected mode and state, the system sends specific parameter adjustment commands in parallel to various hardware and software modules such as RF, baseband, application layer, and power management via internal buses (such as SPI, I2C, or on-chip bus). For example, it sends commands to the RF front end to configure the frequency synthesizer (PLL) to switch to a new channel and adjust the power amplifier (PA) gain; sends commands to the DSP unit to load a new set of filter coefficients and update the Kalman filter parameters; sends commands to the audio encoder to modify the frame length setting; and sends commands to the power management module to adjust the output voltage. This ensures that all sub-interference immunity projects are truly implemented and completes a closed loop from high-level decision-making to low-level physical implementation.

[0063] Specifically, in response to microwave oven interference, the system evaluated the priorities of three sub-items: RF frequency hopping, baseband filtering, and application layer frame length switching. Considering the current high-bitrate music data load, it ultimately selected performance mode to maximize anti-interference effectiveness. The system marked the device's global state as anti-interference mode: performance mode. In this mode, the task scheduler prioritized relevant tasks, and the power management module removed power consumption limits. The system executed a series of dynamic parameter adjustments in parallel: commanding the RF front-end to switch to a clean channel within 10ms; loading notch filter coefficients for 2.45GHz onto the DSP; and forcibly changing the audio encoder's frame length from 5ms to 1ms. Through this series of coordinated actions, the device truly entered a high-efficiency anti-interference state, ensuring smooth music playback with the optimal strategy.

[0064] Please see Figure 6 , Figure 6 This is a schematic diagram of the structural composition of the anti-interference system of the wireless audio device in an embodiment of the present invention; the anti-interference system of the wireless audio device includes: The data delay factor module 21 is used to collect wireless transmission data from wireless audio devices, determine the corresponding data transmission events based on each wireless transmission data and the response behavior of the wireless audio devices, and determine multiple data delay factors based on the identification of the data transmission events. The data delay level module 22 is used to determine the corresponding scene influencing factors based on the scene where the wireless audio device is located, and to determine the corresponding data delay level based on the scene influencing factors, multiple data delay factors and the working status of the wireless audio device. Interference node module 23 is used to mark the wireless transmission environment of the wireless audio device and the corresponding interactive device, construct a dynamic data transmission system of the wireless audio device based on the wireless transmission environment, data delay level and corresponding data to be transmitted, and mark multiple interference nodes based on the identification of the dynamic data transmission system. The anti-interference mode module 24 is used to trigger anti-interference events of the wireless audio device based on the node position of each interference node, the corresponding interference pattern and the dynamic data transmission system among multiple interference nodes, and to determine the corresponding anti-interference mode based on the identification of the anti-interference event.

[0065] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

Claims

1. An anti-interference method for a wireless audio device, characterized in that, include: Collect wireless transmission data from wireless audio devices, determine the corresponding data transmission events based on each wireless transmission data and the response behavior of the wireless audio devices, and identify multiple data delay factors based on the identification of the data transmission events. Based on the scene where the wireless audio device is located, determine the corresponding scene influencing factors, and based on the scene influencing factors, multiple data delay factors and the working status of the wireless audio device, determine the corresponding data delay level. The wireless transmission environment of the wireless audio device and the corresponding interactive device is marked. Based on the wireless transmission environment, data delay level and corresponding data to be transmitted, a dynamic data transmission system of the wireless audio device is constructed, and multiple interference nodes are marked based on the identification of the dynamic data transmission system. Among multiple interference nodes, the anti-interference event of the wireless audio device is triggered based on the node location of each interference node, the corresponding interference pattern, and the dynamic data transmission system, and the corresponding anti-interference mode is determined based on the identification of the anti-interference event.

2. The anti-interference method for wireless audio devices according to claim 1, characterized in that, The process involves collecting wireless transmission data from wireless audio devices, determining corresponding data transmission events based on each wireless transmission data and the response behavior of the wireless audio devices, and identifying multiple data delay factors based on the recognition of these data transmission events, including: When the wireless audio device is in wireless transmission mode, the wireless transmission channel of the wireless audio device is marked, and the wireless transmission data of the wireless audio device is determined based on the detection of the wireless transmission channel. Multiple sub-wireless data combinations are determined based on the identification of the wireless transmission data. The system collects response signals from wireless audio devices, determines the response behavior of wireless audio devices based on the parsing of the response signals, determines multiple data transmission items based on the response behavior of wireless audio devices and multiple sub-wireless data combinations, determines the corresponding data transmission events based on the multiple data transmission items and the working status of wireless audio devices, identifies multiple data delay events based on the identification of the data transmission events, and marks the corresponding data delay factors to determine multiple data delay factors.

3. The anti-interference method for wireless audio devices according to claim 1, characterized in that, The process involves determining the corresponding scene-related influencing factors based on the environment in which the wireless audio device is located, and then determining the corresponding data delay level based on these scene-related influencing factors, multiple data delay factors, and the operating status of the wireless audio device. This includes: Multiple scene features are determined based on the surrounding detection of wireless audio devices. Multiple scene influence combinations are determined based on the feature locations, corresponding feature shapes, and the current location of the wireless audio devices. The corresponding scene influencing factors are determined based on the identification of multiple scene influence combinations.

4. The anti-interference method for a wireless audio device according to claim 3, characterized in that, The process of determining the corresponding scene-related influencing factors based on the scene where the wireless audio device is located, and determining the corresponding data delay level based on the scene-related influencing factors, multiple data delay factors, and the working status of the wireless audio device, further includes: Collect multiple working data from the wireless audio device, determine the working status of the wireless audio device based on the identification of the multiple working data, and determine the first data delay coefficient based on the working status of the wireless audio device and the influencing factors of the scenario. The second data delay coefficient is determined based on the working status of the wireless audio device and multiple data delay factors. The corresponding data delay level is determined based on the mapping relationship between the first data delay coefficient, the second data delay coefficient, and the data delay level.

5. The anti-interference method for a wireless audio device according to claim 1, characterized in that, The wireless transmission environment of the marked wireless audio device and the corresponding interactive device is used to construct a dynamic data transmission system for the wireless audio device based on the wireless transmission environment, data delay level, and corresponding data to be transmitted. Multiple interfering nodes are then marked based on the identification of this dynamic data transmission system, including: Based on the tracing of wireless audio devices, the corresponding interactive devices are identified, the dynamic interaction between wireless audio devices and interactive devices is monitored in real time, and multiple dynamic interactive signals are collected. Based on the multiple dynamic interactive signals, wireless audio devices and interactive devices, the corresponding wireless transmission environment is determined. The corresponding data to be transmitted is determined based on the detection of the wireless audio device. The first layer of data transmission content is determined based on the wireless transmission environment and the data to be transmitted. The second layer of data transmission content is determined based on the data delay level and the data to be transmitted. The dynamic data transmission system of the wireless audio device is constructed based on the first layer of data transmission content and the second layer of data transmission content.

6. The anti-interference method for a wireless audio device according to claim 5, characterized in that, The method further includes marking the wireless transmission environment of the wireless audio device and its corresponding interactive device, constructing a dynamic data transmission system for the wireless audio device based on the wireless transmission environment, data delay level, and corresponding data to be transmitted, and marking multiple interfering nodes based on the identification of this dynamic data transmission system. Based on the identification of the dynamic data transmission system, multiple transmission anomalies are identified. The corresponding interference content and time point are determined according to the detection of each transmission anomaly. Based on the interference content, time point and the working status of the wireless audio device, multiple interference nodes are identified and marked.

7. The anti-interference method for a wireless audio device according to claim 1, characterized in that, The process involves triggering anti-interference events for wireless audio devices based on the node location, corresponding interference pattern, and dynamic data transmission system of each interference node among multiple interference nodes, and determining the corresponding anti-interference mode based on the identification of the anti-interference event, including: Each interference node is dynamically monitored and its location is marked. At the same time, the corresponding interference pattern is determined based on the tracing of each interference node. Based on the node location, the corresponding interference pattern, and the dynamic data transmission system, the corresponding anti-interference elements are determined.

8. The anti-interference method for a wireless audio device according to claim 7, characterized in that, The method of triggering anti-interference events for wireless audio devices based on the node location, corresponding interference pattern, and dynamic data transmission system of each interference node among multiple interference nodes, and determining the corresponding anti-interference mode based on the identification of the anti-interference event, further includes: Based on multiple anti-interference factors and the operating status of the wireless audio device, anti-interference events of the wireless audio device are determined to trigger anti-interference events of the wireless audio device; multiple sub-anti-interference items are determined based on the identification of anti-interference events.

9. The anti-interference method for a wireless audio device according to claim 8, characterized in that, The method of triggering anti-interference events for wireless audio devices based on the node location, corresponding interference pattern, and dynamic data transmission system of each interference node among multiple interference nodes, and determining the corresponding anti-interference mode based on the identification of the anti-interference event, further includes: The corresponding anti-interference mode is determined based on the project content, corresponding project priority, and data load of each sub-anti-interference project, and the anti-interference status of the wireless audio device is marked, so that the wireless audio device can dynamically adjust the data parameters in the anti-interference state.

10. An anti-interference system for a wireless audio device, characterized in that, The anti-interference system of the wireless audio device is applied to the anti-interference method of the wireless audio device as described in any one of claims 1-9.

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