CN117715156A - Bluetooth headset connection method and system - Google Patents
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Abstract
The present invention relates to the field of bluetooth technologies, and in particular, to a method and a system for connecting a bluetooth headset. The method comprises the following steps: performing data matching with the Bluetooth headset by using the mobile equipment, and acquiring a Bluetooth headset connection signal; performing environmental signal spectrum analysis on the Bluetooth headset to generate environmental signal spectrum data; performing signal disturbance analysis on the environmental signal spectrum data to generate signal disturbance data; performing adaptive frequency adjustment on the Bluetooth headset connection signal by utilizing the signal interference data to generate adaptive connection frequency data; detecting the distance between the mobile equipment and the Bluetooth headset to generate connection distance data; detecting the signal intensity of the Bluetooth headset connection signal based on the connection distance data to generate signal intensity data; the invention realizes stable and efficient Bluetooth connection by carrying out transmission signal characteristic analysis on signal intensity data through environmental signal spectrum data to generate transmission signal characteristic data.
Description
Technical Field
The present invention relates to the field of bluetooth technologies, and in particular, to a method and a system for connecting a bluetooth headset.
Background
With the rapid development of mobile communication and audio technologies, bluetooth headsets have been widely used as convenient audio output devices. However, the conventional bluetooth headset connection method has some problems, such as unstable connection and low connection efficiency, and therefore, an intelligent bluetooth headset connection method is proposed to provide a more stable, convenient and high-quality audio transmission experience.
Disclosure of Invention
The invention provides a connection method and a system of a Bluetooth headset for solving at least one of the technical problems.
In order to achieve the above object, the present invention provides a connection method of a bluetooth headset, comprising the following steps:
step S1: performing data matching with the Bluetooth headset by using the mobile equipment, and acquiring a Bluetooth headset connection signal; performing environmental signal spectrum analysis on the Bluetooth headset to generate environmental signal spectrum data;
step S2: performing signal disturbance analysis on the environmental signal spectrum data to generate signal disturbance data; performing adaptive frequency adjustment on the Bluetooth headset connection signal by utilizing the signal interference data to generate adaptive connection frequency data;
Step S3: detecting the distance between the mobile equipment and the Bluetooth headset to generate connection distance data; detecting the signal intensity of the Bluetooth headset connection signal based on the connection distance data to generate signal intensity data; performing transmission signal characteristic analysis on the signal intensity data through the environmental signal spectrum data to generate transmission signal characteristic data;
step S4: performing signal adaptability analysis on the transmission signal characteristic data according to the signal intensity data to generate signal adaptability data; carrying out dynamic signal adjustment processing on the Bluetooth headset connection signal through the signal adaptability data so as to generate a dynamic connection signal;
step S5: detecting a current connection channel of the Bluetooth headset connection signal to generate connection channel data; performing channel stability evaluation processing on the connection channel data through the transmission signal characteristic data to generate a channel stability evaluation index; comparing the channel stability evaluation index based on a preset channel stability evaluation threshold index, and performing intelligent channel skipping processing to generate intelligent skipping channel data when the preset channel stability evaluation threshold index is greater than or equal to the channel stability evaluation index; when the preset channel stability evaluation threshold value index is smaller than the channel stability evaluation index, carrying out channel stability optimization processing to generate intelligent jump channel data;
Step S6: carrying out Bluetooth connection decision analysis on the self-adaptive connection frequency data, the dynamic connection signals and the intelligent skip channel data to generate an intelligent Bluetooth connection decision; and carrying out data mining modeling on the intelligent Bluetooth connection decision to construct an intelligent Bluetooth connection model.
The invention ensures stable data transmission between the Bluetooth earphone and the mobile device by carrying out data matching with the Bluetooth earphone and acquiring the connection signal, provides a reliable audio transmission channel, ensures that audio content can be smoothly transmitted to the earphone, analyzes the environmental signal spectrum data, reduces the influence of wireless signal interference in the environment on Bluetooth connection, automatically adjusts the frequency of the Bluetooth connection to avoid collision with other wireless devices, improves the stability and reliability of the connection, determines the distance between the mobile device and the Bluetooth earphone, is used for optimizing connection parameters and adjusting signal transmission power, evaluates the signal strength to determine the stability and reliability of the connection, analyzes the environmental signal spectrum, provides a basis for subsequent signal adaptability analysis, adjusts the transmitting power, the working frequency and the transmission rate of the Bluetooth earphone according to the information such as real-time signal strength, the environmental signal spectrum and the like, so as to optimize the quality and the performance of the connection signal, adaptively adapts to different channel conditions, provides more stable and reliable connection, evaluates the stability of the connection channel, judges whether the current channel is suitable for stable data transmission or not, and carries out intelligent channel switching to a more stable channel when the channel stability is lower, so as to reduce interference and improve the quality of the connection. When the channel stability is higher, channel stability optimization is performed, the stability and reliability of the channel are improved by adjusting transmission parameters and taking error correction measures, connection decisions are performed based on real-time data and historical data, an optimal connection mode and parameter configuration are selected, an intelligent Bluetooth connection model is constructed, connection efficiency and stability are improved, a Bluetooth connection algorithm is optimized, and better user experience and wireless audio transmission quality are provided.
Preferably, step S1 comprises the steps of:
step S11: performing data matching with the Bluetooth headset by using the mobile equipment, and acquiring a Bluetooth headset connection signal;
step S12: performing environmental signal intensity analysis on the Bluetooth headset connection signal to generate environmental signal intensity data;
step S13: calculating the signal frequency utilization rate of the Bluetooth headset connection signal according to the environmental signal intensity data, and generating the signal frequency utilization rate;
step S14: detecting signal fluctuation of the Bluetooth headset according to the signal frequency utilization rate to generate signal fluctuation data;
step S15: and carrying out spectrum analysis on the Bluetooth headset by using the signal fluctuation data to generate environmental signal spectrum data.
The invention establishes stable data connection between the mobile equipment and the Bluetooth headset so as to realize interaction of audio transmission and control instructions, provides reliable connection signals, ensures that audio content can be transmitted to the Bluetooth headset without errors, provides good audio experience, knows the wireless signal strength condition in the environment, comprises the signal strength of other Bluetooth equipment, wi-Fi network or other interference sources, provides environment signal strength data for subsequent signal optimization and interference suppression so as to improve connection quality and stability, analyzes the signal frequency utilization condition in the environment, evaluates occupied frequency resources and available frequency resource proportion, generates signal frequency utilization rate data, is used for subsequent channel selection and signal adjustment so as to optimize the stability and performance of Bluetooth headset connection signals, detects the fluctuation condition of the signal strength change and frequency fluctuation of the Bluetooth headset connection signals, generates signal fluctuation data for subsequent signal analysis and optimization so as to cope with the influence of the signal fluctuation on the connection quality, analyzes the distribution condition of the signal fluctuation data on a frequency spectrum, knows the signal strength and interference condition in the frequency range, provides basis for subsequent signal optimization and interference suppression so as to improve the connection quality and the Bluetooth headset, and the reliability of the connection signal connection is improved, the connection quality and the signal quality is optimized based on the frequency stability and the frequency of the Bluetooth headset.
Preferably, step S2 comprises the steps of:
step S21: performing signal frequency utilization analysis on the environmental signal spectrum data to generate signal frequency utilization data;
step S22: performing signal response detection on the signal frequency utilization rate data to generate signal packet loss rate data;
step S23: performing signal disturbance analysis on the environmental signal spectrum data by utilizing the signal packet loss rate data to generate signal interference data;
step S24: frequency conflict recognition is carried out on the Bluetooth headset connection signals based on the signal interference data so as to generate conflict frequencies;
step S25: and performing idle frequency self-adaptive adjustment processing on the Bluetooth headset connection signal through the conflict frequency to generate self-adaptive connection frequency data.
The invention analyzes the signal frequency utilization rate of the environmental signal spectrum data, analyzes the environmental signal spectrum data, determines the occupation condition and the utilization rate of signals in different frequency ranges, provides information about the utilization condition of frequency resources, is used for subsequent channel selection and optimization, detects the response condition of Bluetooth headset connection signals, comprises the transmission rate, response time, packet loss rate and the like of the signals, generates signal packet loss rate data, is used for evaluating the stability and reliability of signal transmission, analyzes the association relation between the signal packet loss rate data and the environmental signal spectrum data, determines the correlation between the signal packet loss rate and signal interference, generates signal interference data, provides information about the possible signal interference condition in the environment, is used for subsequent interference suppression and optimization, identifies the possible frequency conflict condition of Bluetooth headset connection signals, namely the conflict on the occurrence frequency of other signal sources, generates conflict frequency data, provides information about the conflict frequency which possibly causes connection problems, automatically adjusts the frequency of the Bluetooth headset connection signals according to the conflict frequency data, avoids the interference with the conflict frequency, generates self-adaptive connection frequency data, provides connection frequency data after adjustment, improves the connection frequency and the reliability, and the reliability of the connection frequency stability and the connection frequency can be improved, the connection frequency can be better, the reliability of the Bluetooth headset connection signals can be realized, the connection frequency can be better realized, the connection quality can be realized, and the connection quality has better quality, and the stability can be better realized, and the quality realized.
Preferably, step S3 comprises the steps of:
step S31: detecting the distance between the mobile equipment and the Bluetooth headset to generate connection distance data;
step S32: detecting the signal intensity of the Bluetooth headset connection signal based on the connection distance data to generate signal intensity data;
step S33: performing distance attenuation calculation on the signal intensity data to generate signal intensity attenuation data;
step S34: carrying out transmission rate analysis on the signal intensity data through the environmental signal spectrum data to generate signal transmission rate data;
step S35: carrying out noise power spectrum density calculation on the signal transmission rate data according to the signal intensity attenuation data so as to generate noise power spectrum density data;
step S36: and carrying out signal quality characteristic analysis on the signal transmission rate data and the noise power spectrum density data to generate transmission signal characteristic data.
According to the invention, the connection distance information between the mobile equipment and the Bluetooth headset is obtained by measuring the physical distance between the mobile equipment and the Bluetooth headset, the connection distance data can be used for evaluating the stability and reliability of the connection, because the signal strength and the transmission rate are often attenuated or changed along with the change of the distance, the signal strength data related to the connection distance is obtained by measuring the receiving strength of the connection signal of the Bluetooth headset, the signal strength data can be used for evaluating the stability and the reliability of the connection, the stronger signal strength generally represents better connection quality, the attenuation condition of the signal in the transmission process is calculated based on the known signal strength data and the connection distance, the signal strength attenuation data can provide information about the propagation attenuation of the signal in the space, the stability and the accessibility of the signal are helped to be known, the current transmission rate condition is evaluated based on the environmental signal spectrum data and the signal strength data, the signal transmission rate data can be used for judging the current data transmission capacity, the stability and the efficiency of data transmission are helped to be optimized, the noise power spectrum density existing in the signal transmission process is calculated according to the signal strength attenuation data, the noise power spectrum density data in the signal transmission process provides information about noise interference in the signal transmission process, the signal quality and the reliability of the signal transmission is helped to be used for evaluating the signal quality and the reliability of the signal spectrum and the signal quality is helped to be used for optimizing the quality and the quality of the signal, and the quality of the signal is favorable to be used for evaluating the quality and the quality of the quality, and the quality of the quality is favorable for the quality is analyzed and has good quality.
Preferably, step S4 comprises the steps of:
step S41: performing stability detection on the transmission signal characteristic data according to the signal intensity data to obtain signal stability data;
step S42: performing error rate recognition on the signal stability data to generate error rate data;
step S43: carrying out signal adaptability analysis on the transmission signal characteristic data according to the bit error rate data to generate signal adaptability data;
step S44: multipath attenuation compensation processing is carried out on the signal adaptability data, and multipath attenuation compensation data are generated;
step S45: and carrying out dynamic signal adjustment processing on the Bluetooth headset connection signal by utilizing the multipath attenuation compensation data so as to generate a dynamic connection signal.
The invention evaluates the stability of the transmitted signal characteristic data through the signal intensity data, the signal stability data provides the information about the stability degree of the signal transmission, is used for judging the reliability and stability of the connection, the signal stability data is analyzed to identify the possible error rate condition, the error rate data provides the information about the degree of error code in the signal transmission, the reliability and accuracy of the signal are evaluated, the adaptability of the transmitted signal characteristic data under different conditions is analyzed based on the error rate data, the signal adaptability data provides the information about the performance adaptation condition of the signal under different environments or conditions, the reliability and stability of the signal transmission are optimized, the multipath fading is compensated according to the signal adaptability data, so as to reduce the influence of multipath fading on the signal transmission, the multipath fading compensation data provides the information about the multipath effect compensation condition in the signal transmission, the reliability and stability of the signal transmission are helped to be improved, the parameters and characteristics of the Bluetooth headset connection signal are dynamically adjusted based on the multipath fading compensation data, so that more stable and reliable connection is provided, the dynamic connection signal is provided, and the Bluetooth headset performance is improved, and the user experience is improved.
Preferably, step S5 comprises the steps of:
step S51: performing test packet sending processing on the Bluetooth headset according to the Bluetooth headset connection signal, and collecting response detection of the Bluetooth headset on the test packet to generate test packet response data;
step S52: detecting the current connection channel of the test packet response data to generate connection channel data;
step S53: performing signal delay analysis on the connection channel data by transmitting signal characteristic data to generate signal delay data;
step S54: performing channel stability evaluation calculation on the connection channel data by using a Bluetooth headset channel stability evaluation calculation formula based on the signal delay data so as to generate a channel stability evaluation index;
step S55: comparing the channel stability evaluation index based on a preset channel stability evaluation threshold index, and performing intelligent channel skipping processing to generate intelligent skipping channel data when the preset channel stability evaluation threshold index is greater than or equal to the channel stability evaluation index;
step S56: and when the preset channel stability evaluation threshold index is smaller than the channel stability evaluation index, performing channel stability optimization processing to generate intelligent skip channel data.
The invention detects the response condition of the test packet to the Bluetooth headset by sending the test packet to the Bluetooth headset, the test packet response data provides information about the response capability and stability of the Bluetooth headset connection, the test packet response data is analyzed to determine the channel used by the current Bluetooth headset connection, the connection channel data provides information about the current connection channel, the subsequent signal analysis and optimization are facilitated, the signal delay condition in the connection channel data is analyzed based on the transmission signal characteristic data, the signal delay data provides information about the delay degree in signal transmission, the connection instantaneity and the response are facilitated to be evaluated, the Bluetooth headset channel stability evaluation calculation formula is used for calculating the stability evaluation index of the connection channel based on the signal delay data, the channel stability evaluation index provides quantitative indexes about the stability of the connection channel, the quantitative indexes are used for evaluating the reliability and the stability of the connection, the channel stability evaluation index is compared with the preset channel stability evaluation threshold index, the intelligent channel jump processing is executed when the preset channel stability evaluation threshold index is larger than or equal to the channel stability evaluation index, the intelligent channel jump processing is generated, the intelligent channel data is improved, the quality of the connection is improved, the connection stability is optimized, the channel stability is improved, and the connection stability is improved, and the performance is improved.
Preferably, the calculation formula for the stability evaluation of the bluetooth headset channel in step S54 is specifically:
wherein, C is the stable evaluation index of the Bluetooth earphone channel, S is the packet loss rate, N is the jitter rate, d is the signal transmission distance between the Bluetooth earphone and the connecting device, lambda is the signal-to-noise ratio, R is the signal periodic oscillation frequency, N is the channel bandwidth, T is the data transmission rate, L is the signal interference intensity, f is the received power attenuation index, and x is the noise power.
The invention is realized byThe adjustment factors representing the packet loss rate and the jitter rate are important indexes for measuring the channel quality, and the lower the adjustment factors represent the better channel quality, the stability and the reliability of the channel can be reflected in the evaluation index C by adjusting the packet loss rate and the jitter rate, and the lower the adjustment factors are>The signal-to-noise ratio is the square root of the ratio of signal transmission distance to signal-to-noise ratio, which is used to measure the sharpness and reliability of the signal, the stability and reliability of the channel can be more fully evaluated by considering the influence of the signal-to-noise ratio in the evaluation index C, the evaluation index C can be adjusted and normalized by taking the logarithm of the whole adjustment factor, the use of a logarithmic function can map a larger range of input values to a smaller range of output values, so that the value of the evaluation index C is easier to compare and interpret >The channel bandwidth refers to a frequency range available for signal transmission in a specific frequency band, the utilization efficiency and adaptability of signals can be evaluated by comparing the signal periodic oscillation frequency with the channel bandwidth, and when the signal periodic oscillation frequency is matched with the channel bandwidth, the signal transmission effect is better, the stability and transmission quality of the channel are improved, and the channel bandwidth is good for the user to use>The square of the ratio of the data transmission rate, which is the amount of data transmitted per unit time, to the signal-to-interference strength, which is the degree of interference present in the channel, is expressed, and the reliability and stability of the channel transmission can be evaluated by comparing the data transmission rate with the signal-to-interference strength, with higher data transmission rates and lower signal-to-interference strengths being beneficial for improving the stability and transmission quality of the channel, and with higher data transmission rates and lower signal-to-interference strengths being beneficial for improving the reliability and stability of the channel>The sine function representing the signal frequency attenuation refers to attenuation of a signal caused by various factors (such as transmission distance, material attenuation and the like) in the transmission process, the attenuation degree of signal transmission can be estimated more accurately by carrying out sine function calculation and limit operation on the signal frequency attenuation so as to reflect the stability and transmission quality of a channel, the average value of estimation indexes can be obtained by carrying out limit operation and square root operation on the sine function of the signal frequency attenuation, the influence of instantaneous fluctuation and noise can be eliminated, more stable and representative estimation on the signal attenuation can be provided, the attenuation condition of the signal in the transmission process can be estimated more comprehensively by considering the signal frequency attenuation, and higher frequency attenuation possibly causes insufficient signal strength and influences on the transmission quality and stability.
Preferably, the intelligent channel hopping process in step S55 and the channel stability optimization process in step S56 are specifically:
step S5501: surrounding channel scanning is carried out on the Bluetooth headset based on the environmental signal spectrum data so as to acquire an environmental available channel;
step S5502: performing channel stability evaluation calculation on the environment available channels to generate available channel stability evaluation indexes;
step S5503: when the available channel stability evaluation index is greater than or equal to a preset channel stability evaluation threshold index, performing channel skipping processing and generating intelligent skipping channel data;
step S5504: when the available channel stability evaluation index is smaller than a preset channel stability evaluation threshold index, performing channel stability optimization processing to generate intelligent skip channel data;
step S5601: performing high-code rate optimization on the connection channel data to generate high-code rate channel data;
step S5602: performing channel frequency hopping anti-interference optimization on the high-code-rate channel data to generate anti-interference channel data;
step S5603: and carrying out multipath equalization optimization on the connection channel data based on the anti-interference channel data to generate intelligent skip channel data.
The invention scans the signal spectrum of the surrounding environment to obtain available channel information, the signal spectrum data of the surrounding environment provides reference of available channels for subsequent channel selection and configuration, based on the environment available channel data, uses a channel stability evaluation calculation formula to evaluate the stability of each available channel, the available channel stability evaluation index provides quantitative indexes related to the stability of each available channel for evaluating the quality and reliability of the available channel, compares the available channel stability evaluation index with a preset channel stability evaluation threshold index, performs channel jump processing when the available channel stability evaluation index is greater than or equal to the preset channel stability evaluation threshold index, selects more stable channels for connection, and generates intelligent jump channel data to improve the quality and reliability of connection, when the available channel stability evaluation index is smaller than a preset channel stability evaluation threshold index, performing channel stability optimization processing, optimizing a current channel to improve the stability and reliability of connection, wherein the channel stability optimization processing can comprise methods of adjusting connection parameters, optimizing a channel selection algorithm and the like to improve the performance and reliability of connection, generating intelligent skip channel data, optimizing the current connection channel data to improve the code rate of data transmission, providing higher data transmission rate by the high-code rate channel data, improving the quality and transmission efficiency of audio transmission, providing the capability of resisting surrounding interference signals by the anti-interference channel data, improving the stability and reliability of connection, reducing the interference influence in audio transmission, and multipath balance optimization can be realized by adjusting signal transmission paths, compensating transmission delay and the like, the balance and stability of signal transmission are improved, and intelligent skip channel data are generated, so that the quality and reliability of connection are further optimized.
Preferably, step S6 comprises the steps of:
step S61: carrying out Bluetooth connection decision analysis on the self-adaptive connection frequency data, the dynamic connection signals and the intelligent skip channel data to generate an intelligent Bluetooth connection decision;
step S62: performing data interaction visualization processing on the intelligent Bluetooth connection decision to generate an interaction visualization Bluetooth connection decision diagram;
step S63: performing expansion convolution on the interactive visual Bluetooth connection decision graph to generate a Bluetooth connection decision convolution graph;
step S64: and carrying out data mining modeling on the Bluetooth connection decision convolution graph to construct an intelligent Bluetooth connection model.
According to the invention, by comprehensively considering the self-adaptive connection frequency data, the dynamic connection signals and the intelligent skip channel data, bluetooth connection decision analysis is carried out, the self-adaptive connection frequency data provides information of different connection frequencies, the dynamic connection signals provide signal intensity and quality of current connection, the intelligent skip channel data provide stability information of available channels, the intelligent Bluetooth connection decision can be formulated by analyzing the data, the optimal connection frequency, channel and parameter configuration are selected so as to realize optimal connection quality and performance, the intelligent Bluetooth connection decision is converted into a visual form so as to facilitate interaction and understanding of users, key parameters, indexes and results of the connection decision are displayed in the form of a graph, a graph and the like through a data visualization technology, expansion convolution operation is carried out on the interactive visual Bluetooth connection decision graph so as to highlight key characteristics and structures in the image, the expansion convolution is an image processing technology, the characteristics such as edges and textures in the image can be enhanced by carrying out convolution operation on the image, therefore, the connection decision graph with a better area is provided, the connection decision graph is based on the Bluetooth connection decision graph, the data and the convolution operation graph is carried out, the data and the working mode is extracted, the connection decision graph and the connection quality is predicted, the connection quality is optimized, the connection quality is predicted according to the optimal connection performance and the connection model is predicted, and the connection quality is optimized, and the connection is connected with the connection quality is predicted according to the optimal connection performance and the connection model.
In this specification, a method and a system for connecting a bluetooth headset are provided, including:
the environment signal module is used for carrying out data matching with the Bluetooth headset by using the mobile equipment and acquiring a Bluetooth headset connection signal; performing environmental signal spectrum analysis on the Bluetooth headset to generate environmental signal spectrum data;
the frequency adjustment module is used for carrying out signal disturbance analysis on the environmental signal spectrum data so as to generate signal interference data; performing adaptive frequency adjustment on the Bluetooth headset connection signal by utilizing the signal interference data to generate adaptive connection frequency data;
the signal characteristic module is used for detecting the distance between the mobile equipment and the Bluetooth headset so as to generate connection distance data; detecting the signal intensity of the Bluetooth headset connection signal based on the connection distance data to generate signal intensity data; performing transmission signal characteristic analysis on the signal intensity data through the environmental signal spectrum data to generate transmission signal characteristic data;
the dynamic signal adjustment module is used for carrying out signal adaptability analysis on the transmission signal characteristic data according to the signal intensity data so as to generate signal adaptability data; carrying out dynamic signal adjustment processing on the Bluetooth headset connection signal through the signal adaptability data so as to generate a dynamic connection signal;
The channel jump module is used for detecting the current connection channel of the Bluetooth headset connection signal so as to generate connection channel data; performing channel stability evaluation processing on the connection channel data through the transmission signal characteristic data to generate a channel stability evaluation index; comparing the channel stability evaluation index based on a preset channel stability evaluation threshold index, and performing intelligent channel skipping processing to generate intelligent skipping channel data when the preset channel stability evaluation threshold index is greater than or equal to the channel stability evaluation index; when the preset channel stability evaluation threshold value index is smaller than the channel stability evaluation index, carrying out channel stability optimization processing to generate intelligent jump channel data;
the Bluetooth connection model module is used for carrying out Bluetooth connection decision analysis on the self-adaptive connection frequency data, the dynamic connection signals and the intelligent skip channel data so as to generate an intelligent Bluetooth connection decision; and carrying out data mining modeling on the intelligent Bluetooth connection decision to construct an intelligent Bluetooth connection model.
The invention is through constructing the connection system of the bluetooth earphone, through carrying on the data match with the mobile device, obtain the environmental signal of the bluetooth earphone connection signal, carry on the environmental signal spectrum analysis to the bluetooth earphone, produce the environmental signal spectrum data, through the operation of the environmental signal module, can obtain the signal information of the environment where the bluetooth earphone connects, provide the data basis for the subsequent step, utilize the signal interference data to carry on the adaptive frequency adjustment to the bluetooth earphone connection signal, produce the adaptive connection frequency data, the frequency adjustment module can be according to the interference situation of the environmental signal, the connection frequency of the automatic adjustment bluetooth earphone, in order to reduce the signal interference, improve connection quality and stability, the signal characteristic module can provide key parameters such as the connection distance and signal intensity, signal analysis and optimization decision for the subsequent step, the dynamic signal adjustment module can be according to the signal adaptability data, adjust the connection signal of the bluetooth earphone in real time, in order to adapt to different signal environments and conditions, improve connection performance and stability, the channel hopping module can be according to the stability assessment of the connection channel, the connection of the more stable channel is selected intelligently, improve reliability and performance of the bluetooth earphone connection, the bluetooth connection can be considered comprehensively, the various parameters and the connection quality of the bluetooth earphone can be improved, the connection module can be provided with the signal quality and the signal of the connection can be optimized, the connection quality is improved through the signal of the connection module is optimized, the connection module is connected with the signal quality of the connection module is connected according to the signal of the signal with the signal of the connection, the invention, the operation of the signal characteristic module and the dynamic signal adjustment module can adjust the connection signal in real time according to the signal intensity and the adaptability data so as to adapt to different signal environments and conditions, improve connection performance and stability, and the channel hopping module can select a more stable channel for connection through channel stability evaluation and intelligent channel hopping processing, so that the reliability and performance of Bluetooth headset connection are improved, and the Bluetooth connection model module performs connection decision analysis and modeling by comprehensively considering various parameter data, and provides intelligent Bluetooth connection decision support so as to optimize the performance and user experience of Bluetooth headset connection.
Drawings
Fig. 1 is a schematic flow chart of steps of a connection method and system of a bluetooth headset according to the present invention;
FIG. 2 is a detailed implementation step flow diagram of step S1;
FIG. 3 is a detailed implementation step flow diagram of step S2;
fig. 4 is a detailed implementation step flow diagram of step S3.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The application example provides a Bluetooth headset connection method and system. The implementation main body of the Bluetooth headset connection method and system includes but is not limited to the implementation of the system: mechanical devices, data processing platforms, cloud server nodes, network uploading devices, etc. may be considered general purpose computing nodes of the present application, including but not limited to: at least one of an audio image management system, an information management system and a cloud data management system.
Referring to fig. 1 to 4, the present invention provides a connection method of a bluetooth headset, the connection method of the bluetooth headset includes the following steps:
step S1: performing data matching with the Bluetooth headset by using the mobile equipment, and acquiring a Bluetooth headset connection signal; performing environmental signal spectrum analysis on the Bluetooth headset to generate environmental signal spectrum data;
Step S2: performing signal disturbance analysis on the environmental signal spectrum data to generate signal disturbance data; performing adaptive frequency adjustment on the Bluetooth headset connection signal by utilizing the signal interference data to generate adaptive connection frequency data;
step S3: detecting the distance between the mobile equipment and the Bluetooth headset to generate connection distance data; detecting the signal intensity of the Bluetooth headset connection signal based on the connection distance data to generate signal intensity data; performing transmission signal characteristic analysis on the signal intensity data through the environmental signal spectrum data to generate transmission signal characteristic data;
step S4: performing signal adaptability analysis on the transmission signal characteristic data according to the signal intensity data to generate signal adaptability data; carrying out dynamic signal adjustment processing on the Bluetooth headset connection signal through the signal adaptability data so as to generate a dynamic connection signal;
step S5: detecting a current connection channel of the Bluetooth headset connection signal to generate connection channel data; performing channel stability evaluation processing on the connection channel data through the transmission signal characteristic data to generate a channel stability evaluation index; comparing the channel stability evaluation index based on a preset channel stability evaluation threshold index, and performing intelligent channel skipping processing to generate intelligent skipping channel data when the preset channel stability evaluation threshold index is greater than or equal to the channel stability evaluation index; when the preset channel stability evaluation threshold value index is smaller than the channel stability evaluation index, carrying out channel stability optimization processing to generate intelligent jump channel data;
Step S6: carrying out Bluetooth connection decision analysis on the self-adaptive connection frequency data, the dynamic connection signals and the intelligent skip channel data to generate an intelligent Bluetooth connection decision; and carrying out data mining modeling on the intelligent Bluetooth connection decision to construct an intelligent Bluetooth connection model.
The invention ensures stable data transmission between the Bluetooth earphone and the mobile device by carrying out data matching with the Bluetooth earphone and acquiring the connection signal, provides a reliable audio transmission channel, ensures that audio content can be smoothly transmitted to the earphone, analyzes the environmental signal spectrum data, reduces the influence of wireless signal interference in the environment on Bluetooth connection, automatically adjusts the frequency of the Bluetooth connection to avoid collision with other wireless devices, improves the stability and reliability of the connection, determines the distance between the mobile device and the Bluetooth earphone, is used for optimizing connection parameters and adjusting signal transmission power, evaluates the signal strength to determine the stability and reliability of the connection, analyzes the environmental signal spectrum, provides a basis for subsequent signal adaptability analysis, adjusts the transmitting power, the working frequency and the transmission rate of the Bluetooth earphone according to the information such as real-time signal strength, the environmental signal spectrum and the like, so as to optimize the quality and the performance of the connection signal, adaptively adapts to different channel conditions, provides more stable and reliable connection, evaluates the stability of the connection channel, judges whether the current channel is suitable for stable data transmission or not, and carries out intelligent channel switching to a more stable channel when the channel stability is lower, so as to reduce interference and improve the quality of the connection. When the channel stability is higher, channel stability optimization is performed, the stability and reliability of the channel are improved by adjusting transmission parameters and taking error correction measures, connection decisions are performed based on real-time data and historical data, an optimal connection mode and parameter configuration are selected, an intelligent Bluetooth connection model is constructed, connection efficiency and stability are improved, a Bluetooth connection algorithm is optimized, and better user experience and wireless audio transmission quality are provided.
In the embodiment of the present invention, as described with reference to fig. 1, the steps of the connection method of the bluetooth headset of the present invention are shown in the schematic diagram, and in this example, the steps of the connection method of the bluetooth headset include:
step S1: performing data matching with the Bluetooth headset by using the mobile equipment, and acquiring a Bluetooth headset connection signal; performing environmental signal spectrum analysis on the Bluetooth headset to generate environmental signal spectrum data;
in this embodiment, an available bluetooth device is searched in a bluetooth setting interface of the mobile device, and a target bluetooth headset is found and paired with the bluetooth device. According to the pairing instruction provided by the device, a pairing password is generally required to be established between the mobile device and the Bluetooth headset or a pairing request is confirmed, a professional spectrum analysis instrument or spectrum analysis software on the mobile device is used for ensuring that the mobile device supports analysis of Bluetooth frequency bands, the Bluetooth headset is placed in an environment to be tested, the connection state of the Bluetooth headset is ensured to be kept stable, the spectrum analysis instrument or software is started, the Bluetooth frequency bands are selected as analysis targets, the acquisition of environmental signal spectrum data is started, a period of time is continued to be used for acquiring sufficient samples, and the analysis instrument or software analyzes and records the spectrum of the Bluetooth headset connection signals to generate the environmental signal spectrum data.
Step S2: performing signal disturbance analysis on the environmental signal spectrum data to generate signal disturbance data; performing adaptive frequency adjustment on the Bluetooth headset connection signal by utilizing the signal interference data to generate adaptive connection frequency data;
in this embodiment, the environmental signal spectrum data is analyzed by using a suitable signal processing method to identify and extract signal disturbance characteristics therein, the signal disturbance may include noise, an interference source, frequency offset, and the like, the identified signal disturbance characteristics are converted into signal disturbance data according to the result of the signal disturbance analysis, which may be a set of values, which represent the strength, frequency offset, and the like of the signal disturbance, and the connection frequency of the bluetooth headset is adjusted according to the signal disturbance data by using an adaptive algorithm or mechanism, which may include increasing or decreasing the connection frequency, adjusting channel selection, and the like, so as to reduce the influence of the signal disturbance on the bluetooth connection, and in the adaptive frequency adjustment process, the connection quality and performance of the bluetooth headset are continuously monitored and evaluated, and relevant indexes and measurement methods, such as signal strength indication, bit error rate, transmission rate, and the like, may be used, and adaptive connection frequency data may be generated according to the result of the adaptive frequency adjustment, and these data may be recorded or used for subsequent optimization and adjustment.
Step S3: detecting the distance between the mobile equipment and the Bluetooth headset to generate connection distance data; detecting the signal intensity of the Bluetooth headset connection signal based on the connection distance data to generate signal intensity data; performing transmission signal characteristic analysis on the signal intensity data through the environmental signal spectrum data to generate transmission signal characteristic data;
in this embodiment, the distance between the mobile device and the bluetooth headset is detected by using a suitable method or tool, which may be based on an approximate estimate of the bluetooth signal strength indication (RSSI), or an accurate measurement using other distance measurement techniques (such as bluetooth positioning or ultrasonic ranging), connection distance data is generated according to the result of the distance detection, which may be a set of values, which represent the distance between the mobile device and the bluetooth headset, the strength of the bluetooth headset connection signal is detected using the bluetooth function or related tool of the mobile device, which may be implemented by reading the bluetooth signal strength indication (RSSI) value or other related indicator, signal strength data is generated according to the result of the signal strength detection, which may be a set of values, which represent the strength of the bluetooth headset connection signal, the environmental signal spectrum data is analyzed with the signal strength data to identify characteristics of the transmission signal, which may include analyzing the transmission signal spectrum distribution in the spectrum, the signal power distribution, the spectrum shape, etc., and the transmission signal characteristic data is generated according to the result of the transmission signal characteristic analysis, which may include the spectrum characteristic description, the signal power distribution curve, etc., for further analysis and evaluation.
Step S4: performing signal adaptability analysis on the transmission signal characteristic data according to the signal intensity data to generate signal adaptability data; carrying out dynamic signal adjustment processing on the Bluetooth headset connection signal through the signal adaptability data so as to generate a dynamic connection signal;
in this embodiment, an algorithm or method for signal adaptability analysis is prepared. This may be based on techniques such as machine learning, statistical analysis, or rule engines for analyzing the relationship between the signal strength data and the transmitted signal characteristic data, which are analyzed to determine an adaptive relationship therebetween. This may include modeling, training algorithms, performing statistical analysis, etc., generating signal adaptation data based on the results of the signal adaptation analysis. This may be a set of values or rules that indicate the adaptability of the transmitted signal characteristic data under different signal strength conditions, and based on the signal adaptability data, the connection signal of the bluetooth headset is adjusted using an algorithm or mechanism for dynamic signal adjustment. This may include adjusting signal power, changing channel selection, optimizing transmission parameters, etc. to accommodate current signal strength conditions, and continuously monitoring and evaluating connection quality and performance of the bluetooth headset during dynamic signal adjustment. The dynamic connection signal data may be generated based on the results of the dynamic signal adjustment using related metrics and measurement methods, such as signal strength indication, bit error rate, transmission rate, etc. These data may be recorded or used for subsequent optimization and adjustment.
Step S5: detecting a current connection channel of the Bluetooth headset connection signal to generate connection channel data; performing channel stability evaluation processing on the connection channel data through the transmission signal characteristic data to generate a channel stability evaluation index; comparing the channel stability evaluation index based on a preset channel stability evaluation threshold index, and performing intelligent channel skipping processing to generate intelligent skipping channel data when the preset channel stability evaluation threshold index is greater than or equal to the channel stability evaluation index; when the preset channel stability evaluation threshold value index is smaller than the channel stability evaluation index, carrying out channel stability optimization processing to generate intelligent jump channel data;
in this embodiment, the bluetooth headset or a related tool is used to detect the currently connected channel. This may be achieved by reading the configuration of the bluetooth headset or using an associated bluetooth analysis tool, generating connection channel data based on the results of the current connection channel detection. This may be a number or identifier indicating the currently connected channel, and the connection channel data is subjected to a channel stability evaluation process. This may include analyzing the transmission signal characteristic data, detecting channel interference or fading, etc., and generating a channel stability assessment index based on the results of the channel stability assessment process. This may be a value representing the stability level of the connection channel, comparing a preset channel stability assessment threshold index with the channel stability assessment index. If the preset index is greater than or equal to the channel stability evaluation index, executing intelligent channel jump processing; if the preset index is smaller than the channel stability evaluation index, performing channel stability optimization processing, and if necessary, performing intelligent channel jump processing when the channel stability evaluation threshold index is greater than or equal to the channel stability evaluation index. This may include selecting a new channel and performing a connection switch to provide a more stable connection, and performing a channel stability optimization process when the channel stability assessment threshold index is less than the channel stability assessment index. This may include improving the condition of the current connection channel, for example by interference cancellation, signal enhancement, or transmission parameter optimization, and generating intelligent hop channel data based on the results of the intelligent channel hop processing or channel stability optimization processing. This may be a number or identifier indicating the new connection channel after performing the intelligent hopping or after channel stability optimization.
Step S6: carrying out Bluetooth connection decision analysis on the self-adaptive connection frequency data, the dynamic connection signals and the intelligent skip channel data to generate an intelligent Bluetooth connection decision; and carrying out data mining modeling on the intelligent Bluetooth connection decision to construct an intelligent Bluetooth connection model.
In this embodiment, dynamic connection signal data is analyzed to understand information on connection quality, stability, performance, and the like. This may include analysis of signal strength, signal noise, bit error rate, and transmission rate, etc., analysis of intelligent hop channel data, and knowledge of the effect of the connection channel after optimization by channel hopping. This may include evaluation of connection stability, interference conditions, and transmission performance, combining adaptive connection frequency data, dynamic connection signals, and intelligent skip channel data, and performing analysis of bluetooth connection decisions. This may include making connection decisions based on historical data and current data using techniques such as statistical analysis, machine learning, or decision rules, and generating intelligent bluetooth connection decisions based on the results of bluetooth connection decision analysis. The intelligent bluetooth connection decision is modeled using data mining techniques such as machine learning algorithms, statistical analysis, or deep learning models, etc. The method can comprise the steps of feature selection, model training, parameter tuning, verification and the like, so as to construct a model for accurately predicting connection decisions, and an intelligent Bluetooth connection model is constructed according to the result of data mining modeling. The model can predict the optimal Bluetooth connection decision according to the input self-adaptive connection frequency data, dynamic connection signals and intelligent skip channel data.
In this embodiment, as described with reference to fig. 2, a detailed implementation step flow diagram of the step S1 is described, and in this embodiment, the detailed implementation step of the step S1 includes:
step S11: performing data matching with the Bluetooth headset by using the mobile equipment, and acquiring a Bluetooth headset connection signal;
step S12: performing environmental signal intensity analysis on the Bluetooth headset connection signal to generate environmental signal intensity data;
step S13: calculating the signal frequency utilization rate of the Bluetooth headset connection signal according to the environmental signal intensity data, and generating the signal frequency utilization rate;
step S14: detecting signal fluctuation of the Bluetooth headset according to the signal frequency utilization rate to generate signal fluctuation data;
step S15: and carrying out spectrum analysis on the Bluetooth headset by using the signal fluctuation data to generate environmental signal spectrum data.
The invention establishes stable data connection between the mobile equipment and the Bluetooth headset so as to realize interaction of audio transmission and control instructions, provides reliable connection signals, ensures that audio content can be transmitted to the Bluetooth headset without errors, provides good audio experience, knows the wireless signal strength condition in the environment, comprises the signal strength of other Bluetooth equipment, wi-Fi network or other interference sources, provides environment signal strength data for subsequent signal optimization and interference suppression so as to improve connection quality and stability, analyzes the signal frequency utilization condition in the environment, evaluates occupied frequency resources and available frequency resource proportion, generates signal frequency utilization rate data, is used for subsequent channel selection and signal adjustment so as to optimize the stability and performance of Bluetooth headset connection signals, detects the fluctuation condition of the signal strength change and frequency fluctuation of the Bluetooth headset connection signals, generates signal fluctuation data for subsequent signal analysis and optimization so as to cope with the influence of the signal fluctuation on the connection quality, analyzes the distribution condition of the signal fluctuation data on a frequency spectrum, knows the signal strength and interference condition in the frequency range, provides basis for subsequent signal optimization and interference suppression so as to improve the connection quality and the Bluetooth headset, and the reliability of the connection signal connection is improved, the connection quality and the signal quality is optimized based on the frequency stability and the frequency of the Bluetooth headset.
In this embodiment, the mobile device is paired with the bluetooth headset and ensures that they establish a reliable bluetooth connection. This may involve turning on the bluetooth function on the mobile device, searching for and selecting the correct bluetooth headset device, and completing the pairing process, once the mobile device successfully establishes a connection with the bluetooth headset, the connection signal of the bluetooth headset may be obtained. This connection signal may include information such as signal strength, transmission rate, channel utilization, etc., and in the environment of a connected bluetooth headset, ambient signal strength data is collected periodically using a mobile device or other suitable device. This can be achieved by scanning surrounding signal sources (e.g., wi-Fi, bluetooth, or mobile networks) to compare the bluetooth headset connection signal with the ambient signal strength data. The difference or correlation between the connection signal and the ambient signal may be calculated to evaluate the strength level of the connection signal in the current environment, and the frequency utilization of the bluetooth headset connection signal may be calculated. The method can be realized by statistically analyzing the frequency utilization rate of different signal sources in the environment and comparing the Bluetooth headset connection signals with the frequency utilization rate, and the fluctuation condition of the Bluetooth headset connection signals is detected. The fluctuation mode of the signal can be identified by analyzing the change of the frequency utilization rate of the connecting signal, and the acquired signal fluctuation data is utilized to perform spectrum analysis so as to convert the signal fluctuation data in the time domain into the frequency domain.
In this embodiment, as described with reference to fig. 3, a detailed implementation step flow diagram of the step S2 is shown, and in this embodiment, the detailed implementation step of the step S2 includes:
step S21: performing signal frequency utilization analysis on the environmental signal spectrum data to generate signal frequency utilization data;
step S22: performing signal response detection on the signal frequency utilization rate data to generate signal packet loss rate data;
step S23: performing signal disturbance analysis on the environmental signal spectrum data by utilizing the signal packet loss rate data to generate signal interference data;
step S24: frequency conflict recognition is carried out on the Bluetooth headset connection signals based on the signal interference data so as to generate conflict frequencies;
step S25: and performing idle frequency self-adaptive adjustment processing on the Bluetooth headset connection signal through the conflict frequency to generate self-adaptive connection frequency data.
The invention analyzes the signal frequency utilization rate of the environmental signal spectrum data, analyzes the environmental signal spectrum data, determines the occupation condition and the utilization rate of signals in different frequency ranges, provides information about the utilization condition of frequency resources, is used for subsequent channel selection and optimization, detects the response condition of Bluetooth headset connection signals, comprises the transmission rate, response time, packet loss rate and the like of the signals, generates signal packet loss rate data, is used for evaluating the stability and reliability of signal transmission, analyzes the association relation between the signal packet loss rate data and the environmental signal spectrum data, determines the correlation between the signal packet loss rate and signal interference, generates signal interference data, provides information about the possible signal interference condition in the environment, is used for subsequent interference suppression and optimization, identifies the possible frequency conflict condition of Bluetooth headset connection signals, namely the conflict on the occurrence frequency of other signal sources, generates conflict frequency data, provides information about the conflict frequency which possibly causes connection problems, automatically adjusts the frequency of the Bluetooth headset connection signals according to the conflict frequency data, avoids the interference with the conflict frequency, generates self-adaptive connection frequency data, provides connection frequency data after adjustment, improves the connection frequency and the reliability, and the reliability of the connection frequency stability and the connection frequency can be improved, the connection frequency can be better, the reliability of the Bluetooth headset connection signals can be realized, the connection frequency can be better realized, the connection quality can be realized, and the connection quality has better quality, and the stability can be better realized, and the quality realized.
In this embodiment, the environmental signal spectrum data is analyzed, and the signal energy duty ratios in different frequency ranges are counted to calculate the signal frequency utilization rate. The frequency spectrum data can be divided into a plurality of frequency segments, the ratio of the sum of the signal energy in each frequency segment to the total energy is calculated, the signal frequency utilization rate data is analyzed, and the response condition of the signal is detected. The method can judge whether the signal normally responds by setting a threshold value or using a statistical method, count the number of times that the signal does not respond or is lost according to the signal response detection result, divide the number of times by the total signal number to calculate the signal packet loss rate, and analyze the environmental signal spectrum data to detect the disturbance condition of the signal. The method can identify possible interference sources in a frequency range with higher signal packet loss rate, generate signal interference data according to the result of signal disturbance analysis, identify the frequency range or specific signal source which is interfered in the frequency spectrum data, identify the frequency range or signal source which is possibly in conflict with Bluetooth earphone connection signals, generate conflict frequency data according to the result of frequency conflict identification, identify the frequency range or signal source which is possibly causing Bluetooth earphone connection problems, and carry out self-adaptive adjustment on the frequency of the Bluetooth earphone connection signals. This can be achieved by selecting an idle frequency channel or avoiding a conflicting frequency range, generating adaptive connection frequency data according to the result of idle frequency adaptive adjustment, and identifying frequency information of the bluetooth headset connection signal after adjustment, so as to ensure more stable connection quality.
In this embodiment, as described with reference to fig. 4, a detailed implementation step flow diagram of the step S3 is shown, and in this embodiment, the detailed implementation step of the step S3 includes:
step S31: detecting the distance between the mobile equipment and the Bluetooth headset to generate connection distance data;
step S32: detecting the signal intensity of the Bluetooth headset connection signal based on the connection distance data to generate signal intensity data;
step S33: performing distance attenuation calculation on the signal intensity data to generate signal intensity attenuation data;
step S34: carrying out transmission rate analysis on the signal intensity data through the environmental signal spectrum data to generate signal transmission rate data;
step S35: carrying out noise power spectrum density calculation on the signal transmission rate data according to the signal intensity attenuation data so as to generate noise power spectrum density data;
step S36: and carrying out signal quality characteristic analysis on the signal transmission rate data and the noise power spectrum density data to generate transmission signal characteristic data.
According to the invention, the connection distance information between the mobile equipment and the Bluetooth headset is obtained by measuring the physical distance between the mobile equipment and the Bluetooth headset, the connection distance data can be used for evaluating the stability and reliability of the connection, because the signal strength and the transmission rate are often attenuated or changed along with the change of the distance, the signal strength data related to the connection distance is obtained by measuring the receiving strength of the connection signal of the Bluetooth headset, the signal strength data can be used for evaluating the stability and the reliability of the connection, the stronger signal strength generally represents better connection quality, the attenuation condition of the signal in the transmission process is calculated based on the known signal strength data and the connection distance, the signal strength attenuation data can provide information about the propagation attenuation of the signal in the space, the stability and the accessibility of the signal are helped to be known, the current transmission rate condition is evaluated based on the environmental signal spectrum data and the signal strength data, the signal transmission rate data can be used for judging the current data transmission capacity, the stability and the efficiency of data transmission are helped to be optimized, the noise power spectrum density existing in the signal transmission process is calculated according to the signal strength attenuation data, the noise power spectrum density data in the signal transmission process provides information about noise interference in the signal transmission process, the signal quality and the reliability of the signal transmission is helped to be used for evaluating the signal quality and the reliability of the signal spectrum and the signal quality is helped to be used for optimizing the quality and the quality of the signal, and the quality of the signal is favorable to be used for evaluating the quality and the quality of the quality, and the quality of the quality is favorable for the quality is analyzed and has good quality.
In this embodiment, the distance between the mobile device and the bluetooth headset is measured using the selected distance detection method. This may be achieved by measuring signal propagation time, signal strength decay or other relevant indicators, generating connection distance data based on the result of the distance detection, for representing the distance between the mobile device and the bluetooth headset, and using the connection distance data to detect the strength of the bluetooth headset connection signal. This may be accomplished by measuring a Received Signal Strength Indicator (RSSI) or other relevant indicator, generating signal strength data from the result of the signal strength detection, representing the strength level of the bluetooth headset connection signal, and performing a distance decay calculation using the connection distance data and the signal strength data. The signal propagation model, such as a free space propagation model or other empirical model, can be used to estimate the attenuation of the signal strength with distance, signal strength attenuation data is generated according to the result of the distance attenuation calculation, the attenuation of the signal strength with distance is represented, and the transmission rate analysis is performed by using the environmental signal spectrum data and the signal strength data. This may be achieved by matching the signal strength and spectral data with a predefined transmission rate model or algorithm, generating signal transmission rate data based on the result of the transmission rate analysis, representing the signal transmission rate at the current signal strength and ambient conditions, using the signal strength attenuation data and the signal transmission rate data for noise power spectral density calculation. The noise power spectral density during signal transmission may be estimated using a related signal processing technique or algorithm, noise power spectral density data is generated from the result of the noise power spectral density calculation, representing the noise level during signal transmission, signal quality profile analysis is performed on the signal transmission rate data and the noise power spectral density data to generate transmission signal profile data, and the selected signal quality profile is analyzed using the signal transmission rate data and the noise power spectral density data. This may be achieved by comparing with predefined signal quality criteria or applying a related signal processing algorithm, generating transmission signal characteristic data representing the quality condition of the transmission signal based on the result of the signal quality characteristic analysis. These characteristic data may include specific values of signal quality indicators or classification results.
In this embodiment, step S4 includes the following steps:
step S41: performing stability detection on the transmission signal characteristic data according to the signal intensity data to obtain signal stability data;
step S42: performing error rate recognition on the signal stability data to generate error rate data;
step S43: carrying out signal adaptability analysis on the transmission signal characteristic data according to the bit error rate data to generate signal adaptability data;
step S44: multipath attenuation compensation processing is carried out on the signal adaptability data, and multipath attenuation compensation data are generated;
step S45: and carrying out dynamic signal adjustment processing on the Bluetooth headset connection signal by utilizing the multipath attenuation compensation data so as to generate a dynamic connection signal.
The invention evaluates the stability of the transmitted signal characteristic data through the signal intensity data, the signal stability data provides the information about the stability degree of the signal transmission, is used for judging the reliability and stability of the connection, the signal stability data is analyzed to identify the possible error rate condition, the error rate data provides the information about the degree of error code in the signal transmission, the reliability and accuracy of the signal are evaluated, the adaptability of the transmitted signal characteristic data under different conditions is analyzed based on the error rate data, the signal adaptability data provides the information about the performance adaptation condition of the signal under different environments or conditions, the reliability and stability of the signal transmission are optimized, the multipath fading is compensated according to the signal adaptability data, so as to reduce the influence of multipath fading on the signal transmission, the multipath fading compensation data provides the information about the multipath effect compensation condition in the signal transmission, the reliability and stability of the signal transmission are helped to be improved, the parameters and characteristics of the Bluetooth headset connection signal are dynamically adjusted based on the multipath fading compensation data, so that more stable and reliable connection is provided, the dynamic connection signal is provided, and the Bluetooth headset performance is improved, and the user experience is improved.
In this embodiment, stability detection is performed on the transmission signal characteristic data using the signal intensity data. This may be accomplished by analyzing the trend of the signal strength, the degree of fluctuation, or other relevant indicators. And generating signal stability data for representing the stability condition of the transmission signal according to the signal stability detection result. The data may include specific values of stability indicators or classification results, with the signal stability data identifying the bit error rate of the transmitted signal. This may be achieved by comparing with a predefined bit error rate threshold or applying a related bit error rate recognition algorithm, generating bit error rate data representing the bit error rate level of the transmission signal based on the bit error rate recognition result, and performing a signal adaptation analysis using the bit error rate data and the transmission signal characteristic data. This may be by comparing with predefined signal suitability criteria or applying a related signal processing algorithm to evaluate the signal suitability. And generating signal adaptability data according to the result of the signal adaptability analysis, wherein the signal adaptability data represents the adaptability state of the transmission signal. The data may include specific values of the adaptation index or classification results, and the signal adaptation data is used to perform multipath fading compensation processing on the transmission signal. Multipath fading is a fading condition caused by a signal undergoing a plurality of paths in the propagation process, and multipath fading compensation data is generated according to the result of the multipath fading compensation process, which represents a compensation operation performed on the transmission signal. The data can be used for adjusting the attenuation condition in the signal transmission process, and the multipath attenuation compensation data is utilized to dynamically adjust the Bluetooth headset connection signal. This may include increasing signal power, adjusting transmission parameters, or other related operations to optimize signal quality and connection stability, generating dynamic connection signals based on the results of the dynamic signal adjustment process, representing the processed bluetooth headset connection signals. These signals have better quality and stability, providing a better audio transmission experience.
In this embodiment, step S5 includes the following steps:
step S51: performing test packet sending processing on the Bluetooth headset according to the Bluetooth headset connection signal, and collecting response detection of the Bluetooth headset on the test packet to generate test packet response data;
step S52: detecting the current connection channel of the test packet response data to generate connection channel data;
step S53: performing signal delay analysis on the connection channel data by transmitting signal characteristic data to generate signal delay data;
step S54: performing channel stability evaluation calculation on the connection channel data by using a Bluetooth headset channel stability evaluation calculation formula based on the signal delay data so as to generate a channel stability evaluation index;
step S55: comparing the channel stability evaluation index based on a preset channel stability evaluation threshold index, and performing intelligent channel skipping processing to generate intelligent skipping channel data when the preset channel stability evaluation threshold index is greater than or equal to the channel stability evaluation index;
step S56: and when the preset channel stability evaluation threshold index is smaller than the channel stability evaluation index, performing channel stability optimization processing to generate intelligent skip channel data.
The invention detects the response condition of the test packet to the Bluetooth headset by sending the test packet to the Bluetooth headset, the test packet response data provides information about the response capability and stability of the Bluetooth headset connection, the test packet response data is analyzed to determine the channel used by the current Bluetooth headset connection, the connection channel data provides information about the current connection channel, the subsequent signal analysis and optimization are facilitated, the signal delay condition in the connection channel data is analyzed based on the transmission signal characteristic data, the signal delay data provides information about the delay degree in signal transmission, the connection instantaneity and the response are facilitated to be evaluated, the Bluetooth headset channel stability evaluation calculation formula is used for calculating the stability evaluation index of the connection channel based on the signal delay data, the channel stability evaluation index provides quantitative indexes about the stability of the connection channel, the quantitative indexes are used for evaluating the reliability and the stability of the connection, the channel stability evaluation index is compared with the preset channel stability evaluation threshold index, the intelligent channel jump processing is executed when the preset channel stability evaluation threshold index is larger than or equal to the channel stability evaluation index, the intelligent channel jump processing is generated, the intelligent channel data is improved, the quality of the connection is improved, the connection stability is optimized, the channel stability is improved, and the connection stability is improved, and the performance is improved.
In this embodiment, according to the connection signal of the bluetooth headset, a test packet is generated and sent to the bluetooth headset, the test packet may be a specific data packet or command for evaluating the response performance and connection quality of the bluetooth headset, according to the result of response detection, test packet response data is generated, the data may include a flag of whether the response is successful or not, a specific value of response time delay or other relevant information, the test packet response data is utilized to detect the channel of the current bluetooth headset connection, the characteristic of the response of the test packet or other relevant index is analyzed to determine the channel of the current connection, according to the result of detection of the current connection channel, connection channel data is generated for representing the channel information of the current connection, the data may include a channel number, a channel quality index or other relevant information, and by utilizing the transmission signal characteristic data, performing signal delay analysis on the connection channel data, which may evaluate the delay condition of the signal by comparing the transmission delay of the signal on different channels or applying a related signal processing algorithm, generating signal delay data according to the result of the signal delay analysis, representing the delay condition of the connection channel, which may include a specific value or classification result of a delay index, calculating a stability evaluation index of the connection channel using the signal delay data and a preset channel stability evaluation calculation formula, which may include converting the delay data into a specific value or score of a stability index, generating a channel stability evaluation index representing the stability level of the connection channel according to the result of the channel stability evaluation calculation, comparing a preset channel stability evaluation threshold index with the channel stability evaluation index, if the preset threshold value is greater than or equal to the evaluation index, and when the channel stability evaluation index is higher than the preset threshold, the channel stability optimization processing is performed, which may include adjusting channel parameters, optimizing signal transmission settings or other related optimization measures, and generating intelligent skip channel data according to the result of the channel stability optimization processing, wherein the intelligent skip channel data is used for indicating the optimization result or suggestion of the current connection channel.
In this embodiment, the calculation formula for the stability evaluation of the bluetooth headset channel in step S54 is specifically:
wherein, C is the stable evaluation index of the Bluetooth earphone channel, S is the packet loss rate, N is the jitter rate, d is the signal transmission distance between the Bluetooth earphone and the connecting device, lambda is the signal-to-noise ratio, R is the signal periodic oscillation frequency, N is the channel bandwidth, T is the data transmission rate, L is the signal interference intensity, f is the received power attenuation index, and x is the noise power.
The invention is realized byThe adjustment factors representing the packet loss rate and jitter rate, which are important indicators for measuring the channel quality, represent the lowerThe better the channel quality, the stability and reliability of the channel can be reflected in the evaluation index C by adjusting the packet loss rate and jitter rate, +.>The signal-to-noise ratio is the square root of the ratio of signal transmission distance to signal-to-noise ratio, which is used to measure the sharpness and reliability of the signal, the stability and reliability of the channel can be more fully evaluated by considering the influence of the signal-to-noise ratio in the evaluation index C, the evaluation index C can be adjusted and normalized by taking the logarithm of the whole adjustment factor, the use of a logarithmic function can map a larger range of input values to a smaller range of output values, so that the value of the evaluation index C is easier to compare and interpret >The channel bandwidth refers to a frequency range available for signal transmission in a specific frequency band, the utilization efficiency and adaptability of signals can be evaluated by comparing the signal periodic oscillation frequency with the channel bandwidth, and when the signal periodic oscillation frequency is matched with the channel bandwidth, the signal transmission effect is better, the stability and transmission quality of the channel are improved, and the channel bandwidth is good for the user to use>The square of the ratio of the data transmission rate, which is the amount of data transmitted per unit time, to the signal-to-interference strength, which is the degree of interference present in the channel, is expressed, and the reliability and stability of the channel transmission can be evaluated by comparing the data transmission rate with the signal-to-interference strength, with higher data transmission rates and lower signal-to-interference strengths being beneficial for improving the stability and transmission quality of the channel, and with higher data transmission rates and lower signal-to-interference strengths being beneficial for improving the reliability and stability of the channel>A sinusoidal function representing the attenuation of the signal frequency, which is due to the signal during transmissionThe attenuation caused by various factors (such as transmission distance, material attenuation and the like), the attenuation degree of signal transmission can be estimated more accurately by carrying out sine function calculation and limit operation on the signal frequency attenuation so as to reflect the stability and transmission quality of a channel, the average value of estimation indexes can be obtained by carrying out limit operation and square root operation on the sine function of the signal frequency attenuation, the influence of instantaneous fluctuation and noise can be eliminated, more stable and representative estimation on the signal attenuation is provided, the attenuation condition of the signal in the transmission process can be estimated more comprehensively by considering the signal frequency attenuation, and the higher frequency attenuation can lead to insufficient signal strength and influence on the transmission quality and stability.
In this embodiment, the intelligent channel hopping process in step S55 and the channel stability optimization process in step S56 are specifically:
step S5501: surrounding channel scanning is carried out on the Bluetooth headset based on the environmental signal spectrum data so as to acquire an environmental available channel;
step S5502: performing channel stability evaluation calculation on the environment available channels to generate available channel stability evaluation indexes;
step S5503: when the available channel stability evaluation index is greater than or equal to a preset channel stability evaluation threshold index, performing channel skipping processing and generating intelligent skipping channel data;
step S5504: when the available channel stability evaluation index is smaller than a preset channel stability evaluation threshold index, performing channel stability optimization processing to generate intelligent skip channel data;
step S5601: performing high-code rate optimization on the connection channel data to generate high-code rate channel data;
step S5602: performing channel frequency hopping anti-interference optimization on the high-code-rate channel data to generate anti-interference channel data;
step S5603: and carrying out multipath equalization optimization on the connection channel data based on the anti-interference channel data to generate intelligent skip channel data.
The invention scans the signal spectrum of the surrounding environment to obtain available channel information, the signal spectrum data of the surrounding environment provides reference of available channels for subsequent channel selection and configuration, based on the environment available channel data, uses a channel stability evaluation calculation formula to evaluate the stability of each available channel, the available channel stability evaluation index provides quantitative indexes related to the stability of each available channel for evaluating the quality and reliability of the available channel, compares the available channel stability evaluation index with a preset channel stability evaluation threshold index, performs channel jump processing when the available channel stability evaluation index is greater than or equal to the preset channel stability evaluation threshold index, selects more stable channels for connection, and generates intelligent jump channel data to improve the quality and reliability of connection, when the available channel stability evaluation index is smaller than a preset channel stability evaluation threshold index, performing channel stability optimization processing, optimizing a current channel to improve the stability and reliability of connection, wherein the channel stability optimization processing can comprise methods of adjusting connection parameters, optimizing a channel selection algorithm and the like to improve the performance and reliability of connection, generating intelligent skip channel data, optimizing the current connection channel data to improve the code rate of data transmission, providing higher data transmission rate by the high-code rate channel data, improving the quality and transmission efficiency of audio transmission, providing the capability of resisting surrounding interference signals by the anti-interference channel data, improving the stability and reliability of connection, reducing the interference influence in audio transmission, and multipath balance optimization can be realized by adjusting signal transmission paths, compensating transmission delay and the like, the balance and stability of signal transmission are improved, and intelligent skip channel data are generated, so that the quality and reliability of connection are further optimized.
In this embodiment, the environmental signal spectrum data is scanned to identify available channels. The scanning process may include detecting signal strength, occupancy, interference conditions, etc. in the spectrum, and determining available channels in the environment based on the surrounding channel scan results. These channels may be used for connection selection with the bluetooth headset, each of which is evaluated using a preset channel stability evaluation calculation formula using the environment available channel data. This may include generating a stability assessment index for the available channel based on the results of the channel stability assessment calculations taking into account factors such as signal strength, interference conditions, signal to noise ratio, etc. The numerical value of the index represents the stability of the channel, and is used for evaluating the applicability of the channel, and the available channel stability evaluation index is compared with a preset channel stability evaluation threshold index. And if the index is greater than or equal to the threshold value, the stability of the available channel is enough to meet the requirement, and when the available channel stability evaluation index is greater than or equal to the preset threshold value, the channel skipping processing is carried out. And selecting a more stable channel for connection, generating intelligent skip channel data for indicating the information of the channel after skip, and when the stability evaluation index of the available channel is lower than a preset threshold value, indicating that the stability of the available channel is insufficient to meet the requirement. And performing channel stability optimization processing, which may include adjusting channel parameters, optimizing signal transmission settings or other related optimization measures, generating intelligent skip channel data according to the result of the channel stability optimization processing, wherein the intelligent skip channel data is used for indicating the optimization result or suggestion of the current connection channel, and performing high-code rate optimization processing on the current connection channel so as to improve the data transmission rate. The method can include the steps of generating high-code-rate channel data according to the result of high-code-rate optimization processing by using a higher modulation mode, an optimized coding algorithm or other related optimization strategies, representing optimized connection channel information, and performing frequency hopping anti-interference optimization processing on the high-code-rate channel data. And by performing frequency hopping switching between different channels, the influence of interference on signal transmission is reduced, and anti-interference channel data is generated according to the result of channel frequency hopping anti-interference optimization processing. The data represent the channel information after anti-interference optimization, can be used for improving the reliability and stability of signal transmission, and perform multipath equalization optimization processing on the connection channel data by utilizing the anti-interference channel data. The multipath equalization is to solve the influence of multipath effect (multipath fading, phase distortion, etc.) on the signal in the transmission process, improve the quality and stability of the signal, and generate intelligent skip channel data according to the result of multipath equalization optimization processing. These data represent channel information optimized for multipath equalization to indicate the final connection channel setting.
In this embodiment, step S6 includes the following steps:
step S61: carrying out Bluetooth connection decision analysis on the self-adaptive connection frequency data, the dynamic connection signals and the intelligent skip channel data to generate an intelligent Bluetooth connection decision;
step S62: performing data interaction visualization processing on the intelligent Bluetooth connection decision to generate an interaction visualization Bluetooth connection decision diagram;
step S63: performing expansion convolution on the interactive visual Bluetooth connection decision graph to generate a Bluetooth connection decision convolution graph;
step S64: and carrying out data mining modeling on the Bluetooth connection decision convolution graph to construct an intelligent Bluetooth connection model.
According to the invention, by comprehensively considering the self-adaptive connection frequency data, the dynamic connection signals and the intelligent skip channel data, bluetooth connection decision analysis is carried out, the self-adaptive connection frequency data provides information of different connection frequencies, the dynamic connection signals provide signal intensity and quality of current connection, the intelligent skip channel data provide stability information of available channels, the intelligent Bluetooth connection decision can be formulated by analyzing the data, the optimal connection frequency, channel and parameter configuration are selected so as to realize optimal connection quality and performance, the intelligent Bluetooth connection decision is converted into a visual form so as to facilitate interaction and understanding of users, key parameters, indexes and results of the connection decision are displayed in the form of a graph, a graph and the like through a data visualization technology, expansion convolution operation is carried out on the interactive visual Bluetooth connection decision graph so as to highlight key characteristics and structures in the image, the expansion convolution is an image processing technology, the characteristics such as edges and textures in the image can be enhanced by carrying out convolution operation on the image, therefore, the connection decision graph with a better area is provided, the connection decision graph is based on the Bluetooth connection decision graph, the data and the convolution operation graph is carried out, the data and the working mode is extracted, the connection decision graph and the connection quality is predicted, the connection quality is optimized, the connection quality is predicted according to the optimal connection performance and the connection model is predicted, and the connection quality is optimized, and the connection is connected with the connection quality is predicted according to the optimal connection performance and the connection model.
In this embodiment, the adaptive connection frequency data, the dynamic connection signal and the intelligent skip channel data are analyzed, which may include using a machine learning algorithm, a decision tree or other related methods to evaluate the importance and interrelation of each factor, and generating an intelligent bluetooth connection decision, which may include using a graph, a thermodynamic diagram, etc. to show the weight, the relevance and the decision result of each factor, generating an interactive bluetooth connection decision graph by processing and presenting the visualized data of the intelligent bluetooth connection decision, which may be a static image file or a graph with interactivity, so that a user may interact with the graph and understand the basis of the bluetooth connection decision, performing an expansion convolution processing on the interactive visualized bluetooth connection decision graph, which is an image processing technique for enhancing or highlighting specific features in the image, generating a convolution graph of the bluetooth connection decision, which may highlight important areas or features related to the decision, so as to better understand the convolution of the decision, and analyze the bluetooth connection decision, by processing and presenting the visualized data of the bluetooth connection decision graph, which may be a graph, or a graph may be a graph with optimal connection model, a statistical model, or a predictive model, which may be used for the analysis of the bluetooth connection, may be a model, or a real-time connection model, may be set up according to the best-state, or a connection model, or a predictive model, and a connection may be set up.
In this embodiment, a method and a system for connecting a bluetooth headset are provided, including:
the environment signal module is used for carrying out data matching with the Bluetooth headset by using the mobile equipment and acquiring a Bluetooth headset connection signal; performing environmental signal spectrum analysis on the Bluetooth headset to generate environmental signal spectrum data;
the frequency adjustment module is used for carrying out signal disturbance analysis on the environmental signal spectrum data so as to generate signal interference data; performing adaptive frequency adjustment on the Bluetooth headset connection signal by utilizing the signal interference data to generate adaptive connection frequency data;
the signal characteristic module is used for detecting the distance between the mobile equipment and the Bluetooth headset so as to generate connection distance data; detecting the signal intensity of the Bluetooth headset connection signal based on the connection distance data to generate signal intensity data; performing transmission signal characteristic analysis on the signal intensity data through the environmental signal spectrum data to generate transmission signal characteristic data;
the dynamic signal adjustment module is used for carrying out signal adaptability analysis on the transmission signal characteristic data according to the signal intensity data so as to generate signal adaptability data; carrying out dynamic signal adjustment processing on the Bluetooth headset connection signal through the signal adaptability data so as to generate a dynamic connection signal;
The channel jump module is used for detecting the current connection channel of the Bluetooth headset connection signal so as to generate connection channel data; performing channel stability evaluation processing on the connection channel data through the transmission signal characteristic data to generate a channel stability evaluation index; comparing the channel stability evaluation index based on a preset channel stability evaluation threshold index, and performing intelligent channel skipping processing to generate intelligent skipping channel data when the preset channel stability evaluation threshold index is greater than or equal to the channel stability evaluation index; when the preset channel stability evaluation threshold value index is smaller than the channel stability evaluation index, carrying out channel stability optimization processing to generate intelligent jump channel data;
the Bluetooth connection model module is used for carrying out Bluetooth connection decision analysis on the self-adaptive connection frequency data, the dynamic connection signals and the intelligent skip channel data so as to generate an intelligent Bluetooth connection decision; and carrying out data mining modeling on the intelligent Bluetooth connection decision to construct an intelligent Bluetooth connection model.
The invention is through constructing the connection system of the bluetooth earphone, through carrying on the data match with the mobile device, obtain the environmental signal of the bluetooth earphone connection signal, carry on the environmental signal spectrum analysis to the bluetooth earphone, produce the environmental signal spectrum data, through the operation of the environmental signal module, can obtain the signal information of the environment where the bluetooth earphone connects, provide the data basis for the subsequent step, utilize the signal interference data to carry on the adaptive frequency adjustment to the bluetooth earphone connection signal, produce the adaptive connection frequency data, the frequency adjustment module can be according to the interference situation of the environmental signal, the connection frequency of the automatic adjustment bluetooth earphone, in order to reduce the signal interference, improve connection quality and stability, the signal characteristic module can provide key parameters such as the connection distance and signal intensity, signal analysis and optimization decision for the subsequent step, the dynamic signal adjustment module can be according to the signal adaptability data, adjust the connection signal of the bluetooth earphone in real time, in order to adapt to different signal environments and conditions, improve connection performance and stability, the channel hopping module can be according to the stability assessment of the connection channel, the connection of the more stable channel is selected intelligently, improve reliability and performance of the bluetooth earphone connection, the bluetooth connection can be considered comprehensively, the various parameters and the connection quality of the bluetooth earphone can be improved, the connection module can be provided with the signal quality and the signal of the connection can be optimized, the connection quality is improved through the signal of the connection module is optimized, the connection module is connected with the signal quality of the connection module is connected according to the signal of the signal with the signal of the connection, the invention, the operation of the signal characteristic module and the dynamic signal adjustment module can adjust the connection signal in real time according to the signal intensity and the adaptability data so as to adapt to different signal environments and conditions, improve connection performance and stability, and the channel hopping module can select a more stable channel for connection through channel stability evaluation and intelligent channel hopping processing, so that the reliability and performance of Bluetooth headset connection are improved, and the Bluetooth connection model module performs connection decision analysis and modeling by comprehensively considering various parameter data, and provides intelligent Bluetooth connection decision support so as to optimize the performance and user experience of Bluetooth headset connection.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
It will be understood that, although the terms "first," "second," etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of example embodiments. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
The foregoing is only a specific embodiment of the invention to enable those skilled in the art to understand or practice the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. The connection method of the Bluetooth headset is characterized by comprising the following steps of:
step S1: performing data matching with the Bluetooth headset by using the mobile equipment, and acquiring a Bluetooth headset connection signal; performing environmental signal spectrum analysis on the Bluetooth headset to generate environmental signal spectrum data;
step S2: performing signal disturbance analysis on the environmental signal spectrum data to generate signal disturbance data; performing adaptive frequency adjustment on the Bluetooth headset connection signal by utilizing the signal interference data to generate adaptive connection frequency data;
step S3: detecting the distance between the mobile equipment and the Bluetooth headset to generate connection distance data; detecting the signal intensity of the Bluetooth headset connection signal based on the connection distance data to generate signal intensity data; performing transmission signal characteristic analysis on the signal intensity data through the environmental signal spectrum data to generate transmission signal characteristic data;
step S4: performing signal adaptability analysis on the transmission signal characteristic data according to the signal intensity data to generate signal adaptability data; carrying out dynamic signal adjustment processing on the Bluetooth headset connection signal through the signal adaptability data so as to generate a dynamic connection signal;
Step S5: detecting a current connection channel of the Bluetooth headset connection signal to generate connection channel data; performing channel stability evaluation processing on the connection channel data through the transmission signal characteristic data to generate a channel stability evaluation index; comparing the channel stability evaluation index based on a preset channel stability evaluation threshold index, and performing intelligent channel skipping processing to generate intelligent skipping channel data when the preset channel stability evaluation threshold index is greater than or equal to the channel stability evaluation index; when the preset channel stability evaluation threshold value index is smaller than the channel stability evaluation index, carrying out channel stability optimization processing to generate intelligent jump channel data;
step S6: carrying out Bluetooth connection decision analysis on the self-adaptive connection frequency data, the dynamic connection signals and the intelligent skip channel data to generate an intelligent Bluetooth connection decision; and carrying out data mining modeling on the intelligent Bluetooth connection decision to construct an intelligent Bluetooth connection model.
2. The method according to claim 1, wherein the specific steps of step S1 are:
step S11: performing data matching with the Bluetooth headset by using the mobile equipment, and acquiring a Bluetooth headset connection signal;
Step S12: performing environmental signal intensity analysis on the Bluetooth headset connection signal to generate environmental signal intensity data;
step S13: calculating the signal frequency utilization rate of the Bluetooth headset connection signal according to the environmental signal intensity data, and generating the signal frequency utilization rate;
step S14: detecting signal fluctuation of the Bluetooth headset according to the signal frequency utilization rate to generate signal fluctuation data;
step S15: and carrying out spectrum analysis on the Bluetooth headset by using the signal fluctuation data to generate environmental signal spectrum data.
3. The method according to claim 1, wherein the specific steps of step S2 are:
step S21: performing signal frequency utilization analysis on the environmental signal spectrum data to generate signal frequency utilization data;
step S22: performing signal response detection on the signal frequency utilization rate data to generate signal packet loss rate data;
step S23: performing signal disturbance analysis on the environmental signal spectrum data by utilizing the signal packet loss rate data to generate signal interference data;
step S24: frequency conflict recognition is carried out on the Bluetooth headset connection signals based on the signal interference data so as to generate conflict frequencies;
step S25: and performing idle frequency self-adaptive adjustment processing on the Bluetooth headset connection signal through the conflict frequency to generate self-adaptive connection frequency data.
4. The method according to claim 1, wherein the specific step of step S3 is:
step S31: detecting the distance between the mobile equipment and the Bluetooth headset to generate connection distance data;
step S32: detecting the signal intensity of the Bluetooth headset connection signal based on the connection distance data to generate signal intensity data;
step S33: performing distance attenuation calculation on the signal intensity data to generate signal intensity attenuation data;
step S34: carrying out transmission rate analysis on the signal intensity data through the environmental signal spectrum data to generate signal transmission rate data;
step S35: carrying out noise power spectrum density calculation on the signal transmission rate data according to the signal intensity attenuation data so as to generate noise power spectrum density data;
step S36: and carrying out signal quality characteristic analysis on the signal transmission rate data and the noise power spectrum density data to generate transmission signal characteristic data.
5. The method according to claim 1, wherein the specific step of step S4 is:
step S41: performing stability detection on the transmission signal characteristic data according to the signal intensity data to obtain signal stability data;
step S42: performing error rate recognition on the signal stability data to generate error rate data;
Step S43: carrying out signal adaptability analysis on the transmission signal characteristic data according to the bit error rate data to generate signal adaptability data;
step S44: multipath attenuation compensation processing is carried out on the signal adaptability data, and multipath attenuation compensation data are generated;
step S45: and carrying out dynamic signal adjustment processing on the Bluetooth headset connection signal by utilizing the multipath attenuation compensation data so as to generate a dynamic connection signal.
6. The method according to claim 1, wherein the specific step of step S5 is:
step S51: performing test packet sending processing on the Bluetooth headset according to the Bluetooth headset connection signal, and collecting response detection of the Bluetooth headset on the test packet to generate test packet response data;
step S52: detecting the current connection channel of the test packet response data to generate connection channel data;
step S53: performing signal delay analysis on the connection channel data by transmitting signal characteristic data to generate signal delay data;
step S54: performing channel stability evaluation calculation on the connection channel data by using a Bluetooth headset channel stability evaluation calculation formula based on the signal delay data so as to generate a channel stability evaluation index;
step S55: comparing the channel stability evaluation index based on a preset channel stability evaluation threshold index, and performing intelligent channel skipping processing to generate intelligent skipping channel data when the preset channel stability evaluation threshold index is greater than or equal to the channel stability evaluation index;
Step S56: and when the preset channel stability evaluation threshold index is smaller than the channel stability evaluation index, performing channel stability optimization processing to generate intelligent skip channel data.
7. The method according to claim 6, wherein the bluetooth headset channel stability evaluation calculation formula in step S54 is specifically:
wherein, C is the stable evaluation index of the Bluetooth earphone channel, S is the packet loss rate, N is the jitter rate, d is the signal transmission distance between the Bluetooth earphone and the connecting device, lambda is the signal-to-noise ratio, R is the signal periodic oscillation frequency, N is the channel bandwidth, T is the data transmission rate, L is the signal interference intensity, f is the received power attenuation index, and x is the noise power.
8. The method according to claim 6, wherein the smart channel hopping process in step S55 and the channel stability optimization process in step S56 are specifically:
step S5501: surrounding channel scanning is carried out on the Bluetooth headset based on the environmental signal spectrum data so as to acquire an environmental available channel;
step S5502: performing channel stability evaluation calculation on the environment available channels to generate available channel stability evaluation indexes;
step S5503: when the available channel stability evaluation index is greater than or equal to a preset channel stability evaluation threshold index, performing channel skipping processing and generating intelligent skipping channel data;
Step S5504: when the available channel stability evaluation index is smaller than a preset channel stability evaluation threshold index, performing channel stability optimization processing to generate intelligent skip channel data;
step S5601: performing high-code rate optimization on the connection channel data to generate high-code rate channel data;
step S5602: performing channel frequency hopping anti-interference optimization on the high-code-rate channel data to generate anti-interference channel data;
step S5603: and carrying out multipath equalization optimization on the connection channel data based on the anti-interference channel data to generate intelligent skip channel data.
9. The method according to claim 1, wherein the specific step of step S6 is:
step S61: carrying out Bluetooth connection decision analysis on the self-adaptive connection frequency data, the dynamic connection signals and the intelligent skip channel data to generate an intelligent Bluetooth connection decision;
step S62: performing data interaction visualization processing on the intelligent Bluetooth connection decision to generate an interaction visualization Bluetooth connection decision diagram;
step S63: performing expansion convolution on the interactive visual Bluetooth connection decision graph to generate a Bluetooth connection decision convolution graph;
step S64: and carrying out data mining modeling on the Bluetooth connection decision convolution graph to construct an intelligent Bluetooth connection model.
10. A connection system of a bluetooth headset, for performing the connection method of a bluetooth headset according to claim 1, comprising:
the environment signal module is used for carrying out data matching with the Bluetooth headset by using the mobile equipment and acquiring a Bluetooth headset connection signal; performing environmental signal spectrum analysis on the Bluetooth headset to generate environmental signal spectrum data;
the frequency adjustment module is used for carrying out signal disturbance analysis on the environmental signal spectrum data so as to generate signal interference data; performing adaptive frequency adjustment on the Bluetooth headset connection signal by utilizing the signal interference data to generate adaptive connection frequency data;
the signal characteristic module is used for detecting the distance between the mobile equipment and the Bluetooth headset so as to generate connection distance data; detecting the signal intensity of the Bluetooth headset connection signal based on the connection distance data to generate signal intensity data; performing transmission signal characteristic analysis on the signal intensity data through the environmental signal spectrum data to generate transmission signal characteristic data;
the dynamic signal adjustment module is used for carrying out signal adaptability analysis on the transmission signal characteristic data according to the signal intensity data so as to generate signal adaptability data; carrying out dynamic signal adjustment processing on the Bluetooth headset connection signal through the signal adaptability data so as to generate a dynamic connection signal;
The channel jump module is used for detecting the current connection channel of the Bluetooth headset connection signal so as to generate connection channel data; performing channel stability evaluation processing on the connection channel data through the transmission signal characteristic data to generate a channel stability evaluation index; comparing the channel stability evaluation index based on a preset channel stability evaluation threshold index, and performing intelligent channel skipping processing to generate intelligent skipping channel data when the preset channel stability evaluation threshold index is greater than or equal to the channel stability evaluation index; when the preset channel stability evaluation threshold value index is smaller than the channel stability evaluation index, carrying out channel stability optimization processing to generate intelligent jump channel data;
the Bluetooth connection model module is used for carrying out Bluetooth connection decision analysis on the self-adaptive connection frequency data, the dynamic connection signals and the intelligent skip channel data so as to generate an intelligent Bluetooth connection decision; and carrying out data mining modeling on the intelligent Bluetooth connection decision to construct an intelligent Bluetooth connection model.
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