Voice call data stable transmission method and device, equipment, storage medium

Abstract

The application provides a voice call data stable transmission method and device, equipment and storage medium, and belongs to the technical field of wireless communication. The method comprises the following steps: obtaining voice call data to be transmitted, communication signal strength data, communication link quality data, signal-to-noise ratio and signal-to-interference ratio between a first device and a second device; determining a communication scene type based on the communication signal strength data and the communication link quality data, determining environmental interference intensity based on the communication scene type, the signal-to-noise ratio and the signal-to-interference ratio; determining a data transmission strategy based on the environmental interference intensity and the communication scene type, processing the voice call data based on the data transmission strategy to obtain target transmission data, and sending the target transmission data to the second device. The voice call data stable transmission method and device, equipment and storage medium provided by the application can improve the transmission stability of voice call data in a complex scene.

Description

Technical Field

[0001] This application belongs to the field of wireless communication technology, and more specifically, relates to methods, apparatus, devices, and storage media for stable transmission of voice call data. Background Technology

[0002] With the development of wearable device technology, such as smart glasses and smart helmets, voice interaction between these wearable devices and other devices has become an important application scenario. After the wearable device collects the user's voice, it transmits it to the wearer's device (such as a mobile phone) via a wireless link, and then the wearer's device forwards it to the device of the other party, realizing real-time voice calls.

[0003] During voice calls, the usage scenarios of smart wearable devices are complex and varied, with significant differences in signal characteristics and interference intensity across different scenarios. Current technologies often employ fixed parameters or adjust based on a single indicator, failing to adapt to dynamic changes in scenario type and interference intensity. For example, fixed encoding methods struggle to balance the need for packet loss resistance under strong interference with transmission efficiency under weak interference, leading to frequent voice stuttering, disconnections, or audio quality degradation in complex environments, particularly impacting the real-time interactive experience between the smart wearable device and the wearer's device. Therefore, improving the transmission stability of voice call data in this scenario has become a pressing technical challenge. Summary of the Invention

[0004] The purpose of this application is to provide a method, apparatus, device, and storage medium for stable transmission of voice call data, so as to improve the transmission stability of voice call data in complex scenarios.

[0005] A first aspect of this application provides a method for stable transmission of voice call data, executed by a first device, comprising:

[0006] Acquire the voice call data to be transmitted, as well as the communication signal strength data, communication link quality data, signal-to-noise ratio, and signal-to-interference ratio between the first and second devices;

[0007] The communication scenario type is determined based on communication signal strength data and communication link quality data, and the environmental interference intensity is determined based on the communication scenario type, signal-to-noise ratio, and signal-to-interference ratio.

[0008] The data transmission strategy is determined based on the intensity of environmental interference and the type of communication scenario. The voice call data is processed based on the data transmission strategy to obtain the target transmission data, and the target transmission data is sent to the second device.

[0009] A second aspect of this application provides a stable voice call data transmission device, executed by a first device, comprising:

[0010] The data acquisition module is used to acquire the voice call data to be transmitted, as well as the communication signal strength data, communication link quality data, signal-to-noise ratio and signal-to-interference ratio between the first device and the second device;

[0011] The scenario analysis module is used to determine the communication scenario type based on communication signal strength data and communication link quality data, and to determine the environmental interference intensity based on the communication scenario type, signal-to-noise ratio, and signal-to-interference ratio.

[0012] The data transmission module is used to determine the data transmission strategy based on the intensity of environmental interference and the type of communication scenario, process the voice call data based on the data transmission strategy to obtain the target transmission data, and send the target transmission data to the second device.

[0013] A third aspect of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of the above-described method for stable transmission of voice call data.

[0014] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described method for stable transmission of voice call data.

[0015] The beneficial effects of the stable voice call data transmission method, apparatus, device, and storage medium provided in this application embodiment are as follows: This application embodiment first clarifies the actual usage scenario by assessing the signal strength and transmission reliability between the smart wearable device and the wearer's device; then, it accurately determines the severity of interference by combining the scenario characteristics and surrounding interference; finally, it formulates differentiated transmission strategies based on the scenario type and interference intensity, improving the adaptability of data transmission parameters in complex scenarios, avoiding insufficient adaptation between complex scenarios and data transmission parameters, reducing disconnection problems from the root, improving the stability of voice call data transmission between the existing first device (smart wearable device) and the second device (wearer's device), and thus solving the problems of voice call stuttering, disconnection, and poor sound quality. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart illustrating a stable voice call data transmission method provided in an embodiment of this application;

[0018] Figure 2 This is a schematic diagram of device interaction provided in an embodiment of this application;

[0019] Figure 3 This is a structural block diagram of a stable voice call data transmission device provided in an embodiment of this application;

[0020] Figure 4 This is a schematic block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0021] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0022] To make the objectives, technical solutions, and advantages of this application clearer, the following description will be provided in conjunction with the accompanying drawings and specific embodiments.

[0023] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating a method for stable transmission of voice call data according to an embodiment of this application. The method can be executed by a first device, and specifically, the method may include S101 to S103.

[0024] S101: Acquire the voice call data to be transmitted, as well as the communication signal strength data, communication link quality data, signal-to-noise ratio, and signal-to-interference ratio between the first device and the second device.

[0025] like Figure 2As shown, in this embodiment, the first device is a smart wearable device, such as smart glasses or a smart helmet, and serves as the voice acquisition and data transmission initiator. The second device refers to a device that wirelessly communicates with the first device, such as a smartphone worn by the first user. The second device is a data receiver and forwarder, capable of forwarding data to the device of the second user (the call recipient) engaging in a voice call with the first user. The connection between the first and second devices can be Bluetooth or Wi-Fi. The voice call data to be transmitted refers to the voice data of the first user collected by the first device. Communication signal strength data characterizes the degree of wireless signal attenuation between the first and second devices, used to determine signal strength. Communication link quality data characterizes the reliability of the wireless transmission link, used to evaluate link transmission capability. Signal-to-noise ratio (SNR) is the ratio of useful signal power to background noise power, used to evaluate noise interference. Signal-to-interference ratio (SIR) is the ratio of useful signal power to co-channel interference signal power, used to evaluate co-channel interference.

[0026] Considering that voice transmission between smart glasses and mobile phones is affected by both communication scenarios and environmental interference, a single data source cannot fully characterize the communication environment. Relying solely on one type of data can easily lead to biased scenario judgments or inaccurate interference assessments. Therefore, it is necessary to acquire voice data along with multi-dimensional communication and interference data to ensure that the type of communication scenario and the intensity of environmental interference can be accurately determined. This provides a reliable basis for developing appropriate transmission strategies and avoids transmission problems caused by incomplete data.

[0027] For example, assume that the first device and the second device are connected via Bluetooth. In this embodiment, the user's voice can be collected through the built-in dual-microphone array of the first device, a noise reduction algorithm is activated to filter ambient noise such as wind noise, and the voice signal is segmented at a parameter of 20 milliseconds / frame to generate voice call data to be transmitted. The first device can collect communication signal strength data at a frequency of 100 milliseconds / time. After collection, outlier filtering is performed on 5 consecutive sample values, removing values ​​that deviate from the mean by more than 8 dB, and then the average value of the remaining sample values ​​is calculated to obtain smoothed communication signal strength data.

[0028] This embodiment can acquire raw communication link quality data in real time through the Bluetooth baseband chip of the first device, convert it into a link quality score from 0 to 10, and simultaneously count the number of voice frame losses in the past second, calculate the bit error rate and use it as supplementary data to constitute complete communication link quality data to comprehensively reflect the reliability of link transmission. The first device can separate the useful signal from the background noise in the received signal and calculate the signal-to-noise ratio at a frequency of 200 milliseconds / time. The first device can detect non-Bluetooth signals, such as Wi-Fi signals, microwave oven leakage signals, etc., within the currently operating Bluetooth channel, count the total power of these interfering signals, and calculate the signal-to-interference ratio at a frequency of 300 milliseconds / time.

[0029] S102: Determine the communication scenario type based on communication signal strength data and communication link quality data, and determine the environmental interference intensity based on the communication scenario type, signal-to-noise ratio, and signal-to-interference ratio.

[0030] In this embodiment, the environmental interference intensity is determined based on the communication scenario type, signal-to-noise ratio (SNR), and signal-to-interference ratio (SMI). Specifically, this includes: determining the interference weighting coefficient based on the communication scenario type; performing a homing preprocessing on the SNR and SMI; and performing a weighted summation on the preprocessed SNR and SMI based on the interference weighting coefficient to obtain the environmental interference intensity.

[0031] In this embodiment, the interference weighting coefficient refers to a pre-set coefficient based on the communication scenario type, used to adjust the influence of signal-to-noise ratio (SNR) and signal-to-interference ratio (SMI) in the calculation of environmental interference intensity. Its value is adapted to the scenario's sensitivity to different types of interference; for example, in a free-space scenario, the weighting coefficient for SMI can be higher than that for SNR. The alignment preprocessing refers to the processing operation performed on SNR and SMI to align their representational trends. This alignment preprocessing eliminates calculation deviations caused by differences in their original representational logic. The weighted summation refers to the calculation process of multiplying the alignment preprocessed SNR and SMI by their corresponding interference weighting coefficients, and then adding the two products. This process can fuse two types of interference assessment data to output an environmental interference intensity that comprehensively reflects the environmental interference situation.

[0032] The underlying consideration in this embodiment is that, under different communication scenarios, the impact of random noise interference reflected by the signal-to-noise ratio (SNR) and co-channel interference reflected by the signal-to-interference ratio (SIR) on Bluetooth transmission varies. Using fixed weights to calculate environmental interference intensity can easily lead to discrepancies between the interference assessment and the actual scenario. Furthermore, although both SNR and SIR are used to assess interference, they require unified characterization logic through preprocessing to avoid the calculation results being affected by differences in the trends of the original data. This embodiment determines the corresponding weights based on different scenarios, making the assessment of environmental interference intensity more closely reflect the actual communication environment. This provides a reliable basis for subsequently developing accurate transmission strategies and avoids transmission instability issues caused by inaccurate interference assessments.

[0033] For example, the specific implementation process for determining the intensity of environmental interference based on the communication scenario type, signal-to-noise ratio, and signal-to-interference ratio can be as follows:

[0034] The physical environment differences in different communication scenarios lead to varying degrees of impact from random noise and co-channel interference. The purpose of the interference weighting coefficient is to give higher weights to interference indicators (signal-to-noise ratio or signal-to-interference ratio) that have a more significant impact on the scenario, ensuring that the final calculated environmental interference intensity is more in line with the actual impact of interference on transmission.

[0035] Random noise interference is caused by irregular electromagnetic noise in the environment, such as wind noise and weak electromagnetic radiation from household appliances. It mainly affects signal clarity. The signal-to-noise ratio (SNR) can quantify random noise. The lower the SNR, the stronger the random noise interference.

[0036] Co-channel interference is caused by signal conflicts from other wireless devices operating on the same frequency band, such as WiFi and other Bluetooth devices. It mainly affects the stability of signal transmission. The signal-to-interference ratio (SINR) can quantify co-channel interference; the lower the SINR, the stronger the co-channel interference.

[0037] Based on the above considerations, this embodiment can preset the signal-to-noise ratio (W_SNR) weighting coefficient and the signal-to-interference ratio (W_SIR) weighting coefficient for different communication scenario types, and the sum of the two weighting coefficients is 1. The specific allocation method and basis are as follows:

[0038] Assume that there are two types of communication scenarios: free space scenarios and weak signal edge scenarios.

[0039] Considering that free space is unobstructed and has little random noise (weak impact of signal-to-noise ratio), but is susceptible to interference from surrounding WiFi, Bluetooth and other co-channel devices (stronger impact of signal interference ratio), W_SIR can be set to W_SNR, for example, W_SIR=0.7, W_SNR=0.3.

[0040] Considering that in weak signal edge scenarios, the signal strength itself is extremely low, and even weak random noise in the environment can significantly reduce signal clarity (signal-to-noise ratio has a strong impact), and these weak signal edge scenarios are usually far away from co-channel devices (such as far away from routers), the co-channel interference is relatively weak (signal interference ratio has a weak impact), so W_SNR>W_SIR can be set, for example, W_SIR=0.3, W_SNR=0.7.

[0041] After pre-setting the interference weight coefficients corresponding to each communication scenario type, this embodiment can match the interference weight coefficients corresponding to the signal-to-noise ratio (SNR) and signal-to-interference ratio (SNR) based on the currently determined communication scenario type and the pre-set correspondence between the communication scenario type and the interference weight coefficients. This embodiment can perform a homing preprocessing on the obtained SNR and SNR. For SNR, if its original value range is 0 to 40 dB, it is converted to a score of 0 to 10, with the higher the value, the higher the score. For example, an SNR of 40 dB is converted to 10 points, and an SNR of 0 dB is converted to 0 points. For SNR, if its original value range is -10 to 20 dB, it is also converted to a score of 0 to 10. An SNR of 20 dB is converted to 10 points, and an SNR of -10 dB is converted to 0 points, ensuring that both have a high score corresponding to low interference, thus achieving homing.

[0042] This embodiment can obtain the signal-to-noise ratio score and signal-to-interference ratio score after homing preprocessing, and perform weighted summation according to the set interference weight coefficient to finally obtain the environmental interference intensity, thus completing the determination of the environmental interference intensity. Subsequently, data transmission strategies can be further determined based on the results and the type of communication scenario.

[0043] S103: Determine the data transmission strategy based on the environmental interference intensity and communication scenario type, process the voice call data based on the data transmission strategy to obtain the target transmission data, and send the target transmission data to the second device.

[0044] In this embodiment, the data transmission strategy refers to a combination of parameters determined based on the intensity of environmental interference and the type of communication scenario, used to guide the processing and transmission of voice call data, and adapted to different communication environments to ensure stable transmission. The target transmission data refers to the transmittable data that, after processing by the data transmission strategy, meets the transmission requirements of the current communication environment, and is used to transmit the voice call data to the second device via a wireless link.

[0045] Considering the varying signal conditions across different communication scenarios and the differing impacts of environmental interference intensity on transmission, a strategy based solely on a single dimension may result in insufficient packet loss resistance in scenarios with strong interference or inefficient transmission in scenarios with weak interference. This embodiment ensures that voice data can be transmitted in an adaptable manner under various environments, avoiding transmission instability while maintaining both sound quality and efficiency, thus guaranteeing a superior voice interaction experience between smart glasses and mobile phones.

[0046] For example, this embodiment can first construct a policy mapping table with two dimensions: scenario and interference. This table pre-stores core data transmission policy parameters corresponding to different combinations of communication scenario types and environmental interference intensities. These data transmission policy parameters can include three types of core parameters: encoding mode, retransmission triggering conditions, and data frame encapsulation specifications. The first device can perform a matching query in the mapping table based on the determined communication scenario type and environmental interference intensity to determine the currently applicable data transmission policy.

[0047] This embodiment can process voice call data according to a determined data transmission strategy. First, the corresponding encoder is started according to the encoding mode in the strategy to compress the voice call data to be transmitted. If the strategy requires high anti-interference encoding, the encoder will add data redundancy check bits. This embodiment can encapsulate the encoded voice data according to the data frame encapsulation specifications specified by the strategy, and perform integrity verification on the encapsulated data frame. The data that passes the verification is the target transmission data and is temporarily stored in the transmission buffer of the first device.

[0048] This embodiment allows setting a timeout period and a maximum number of retransmissions if no acknowledgment signal is received from the second device, according to the retransmission trigger conditions in the data transmission strategy. Subsequently, this embodiment can read the target transmission data from the transmission buffer in frame sequence and send it to the second device via a wireless link. After transmission, the acknowledgment signal from the second device is monitored in real time. If no acknowledgment signal is received within the timeout period, a retransmission operation is performed according to the set retransmission rules until the data is successfully transmitted or the maximum number of retransmissions is reached, ensuring that the target transmission data is stably delivered to the second device.

[0049] As can be seen from the above, on the one hand, this embodiment first clarifies the actual usage scenario by assessing the signal strength and transmission reliability between the smart wearable device and the wearer's device; then, it accurately determines the severity of interference by combining the characteristics of the scenario and the surrounding interference; finally, it formulates differentiated transmission strategies based on the scenario type and interference intensity, avoiding insufficient adaptation of data transmission parameters to complex scenarios, reducing disconnection problems at the source, and ensuring the stability of data transmission. On the other hand, this embodiment can balance call stability with sound quality / efficiency. For example, in open scenarios with weak interference, a more efficient transmission method can be used to ensure clear voice; in scenarios with weak signals and strong interference, the strategy can be adjusted to prioritize ensuring uninterrupted calls. This solves the problem that existing fixed encoding methods cannot simultaneously address packet loss resistance and transmission efficiency, allowing users to enjoy continuous and clear voice interaction whether making calls indoors, walking outdoors, or in signal-edge areas, thus improving the practicality of smart wearable devices.

[0050] In summary, this embodiment can improve the stability of voice call data transmission between the existing first device (smart wearable device) and the second device (wearer device), thereby solving the problems of voice call stuttering, disconnection, and poor sound quality.

[0051] In one embodiment of this application, determining the communication scenario type based on communication signal strength data and communication link quality data includes:

[0052] Calculate the signal fluctuation index and signal strength index based on communication signal strength data;

[0053] Calculate the link quality score based on communication link quality data;

[0054] Calculate the correlation index between communication signal strength data and communication link quality data;

[0055] The communication scenario type is determined based on the correlation index, link quality score, signal fluctuation index, and signal strength index.

[0056] In this embodiment, the communication signal strength data includes multiple communication signal strength values; the calculation of the signal fluctuation index and the signal strength index based on the communication signal strength data specifically includes: calculating the mean and variance of the communication signal strength data; using the mean as the signal strength index; and calculating the signal fluctuation index based on the mean and variance.

[0057] In this embodiment, the signal fluctuation index is a parameter calculated based on the mean and variance, characterizing the degree of drastic change in communication signal strength. It is used to determine whether the signal is stable; a larger fluctuation index indicates a more unstable signal. The signal strength index is a parameter that directly uses the calculated mean as a characterizing parameter of the overall strength of the communication signal, reflecting the basic signal strength level. The correlation index is a parameter obtained by calculating the degree of correlation between communication signal strength data and communication link quality data. It is used to determine whether the trends of the two are consistent. For example, a positive correlation indicates that the link quality is good when the signal is strong, while a negative correlation indicates a contradiction between signal strength and quality.

[0058] The underlying consideration in this embodiment is that a single communication signal strength value is easily affected by transient interference and cannot accurately reflect the true state of the signal. Therefore, by collecting multiple communication signal strength values ​​and calculating the mean and variance, a signal strength index and a signal fluctuation index are calculated to quantify the strength and stability of the signal. Simultaneously, the communication scenario type needs to be comprehensively judged in conjunction with the correlation between signal characteristics and link quality. Relying solely on signal parameters can lead to misjudgments. Including the correlation index can distinguish between scenarios where signal and quality match and scenarios where signal and quality contradict each other, ensuring accurate scenario type determination. The overall logic of this embodiment is to construct a scenario determination system through multi-dimensional parameters, avoiding judgment bias caused by single data points, and laying a reliable foundation for subsequently determining environmental interference intensity and transmission strategies.

[0059] For example, the specific implementation process for determining the communication scenario type based on communication signal strength data and communication link quality data may include:

[0060] In this embodiment, the acquisition time period can be set to 1 second, and the communication signal strength data between the first device and the second device can be acquired at a sampling frequency of 100 milliseconds / time. A total of 10 communication signal strength values ​​are acquired within 1 second, and these values ​​are arranged into a data sequence according to the acquisition time order to ensure that the data coverage is sufficient for a sufficient duration to reflect the signal change trend.

[0061] This embodiment can calculate the mean and variance of communication signal strength data, and calculate a signal fluctuation index based on the mean and variance. For example, the ratio of variance to mean can be used as the signal fluctuation index; the smaller the ratio, the smoother the signal strength change. Simultaneously, this embodiment can use the mean as the signal strength index. If the mean is greater than -70 dB (a preset threshold), the signal is considered strong; otherwise, it is considered weak. This embodiment can align the collected communication link quality data with each other by timestamp, calculate the correlation between these two sets of data, and obtain a correlation index. If the index is greater than 0, it indicates a positive correlation between signal strength and link quality; if it is less than 0, it indicates a negative correlation.

[0062] This embodiment can determine the communication scenario type by comprehensively considering the correlation index, link quality score, signal fluctuation index, and signal strength index. If the signal strength index is high, the signal fluctuation index is low, the correlation index is positive, and the link quality score is high, it is determined to be a scenario with stable signal and excellent quality. If the signal strength index is medium, the signal fluctuation index is high, the correlation index is positive, and the link quality score is medium, it is determined to be a scenario with some interference but the signal and quality are matched. If the signal strength index is high, the signal fluctuation index is medium, the correlation index is negative, and the link quality score is low, it is determined to be a scenario with artificially high signal and poor quality, thus completing the determination of the communication scenario type.

[0063] This embodiment constructs a communication scenario type determination system through multi-dimensional parameters, which effectively improves the accuracy of scenario determination and lays a reliable foundation for stable transmission of subsequent voice call data. On the one hand, compared with the existing technology that relies on a single communication signal strength value to determine the scenario, this embodiment calculates the signal strength index and signal fluctuation index, which can simultaneously quantify signal strength and stability, avoiding misjudgment of signal status caused by instantaneous interference. On the other hand, this embodiment introduces a correlation index to link signal strength and link quality data, which can distinguish between scenarios where signal and quality match or contradict each other, solving the problem of easy misjudgment based solely on signal parameters. Accurate scenario determination ensures that subsequent environmental interference intensity assessment and data transmission strategy formulation are more in line with the actual communication environment, reducing problems such as voice stuttering and disconnection caused by scenario misjudgment, and improving the stability and user experience of voice calls between smart glasses and mobile phones.

[0064] In one embodiment of this application, the communication scenario type is determined based on the correlation index, link quality score, signal fluctuation index, and signal strength index, including:

[0065] If the signal strength index is less than the first strength threshold, the communication scenario type is determined to be a weak signal edge scenario.

[0066] If the signal strength index is greater than or equal to the first strength threshold, then:

[0067] When the correlation index is less than the first correlation threshold, the communication scenario type is determined to be a multipath effect scenario.

[0068] When the correlation index is greater than or equal to the first correlation threshold and the link quality score and signal fluctuation index meet the first judgment condition, the communication scenario type is determined to be a free space scenario.

[0069] When the correlation index is greater than or equal to the first correlation threshold and the link quality score and signal fluctuation index do not meet the first judgment condition, the communication scenario type is determined to be an indoor obstacle scenario.

[0070] The first criterion is that the link quality score is greater than or equal to the first quality score threshold, and the signal fluctuation index is less than the first signal fluctuation threshold.

[0071] In this embodiment, the data transmission strategy includes the target data retransmission coefficient and the target data encoding method;

[0072] Data transmission strategies are determined based on environmental interference intensity and communication scenario type, including:

[0073] The initial data retransmission coefficient and initial data encoding method are determined based on the type of communication scenario.

[0074] If the environmental interference intensity is greater than or equal to the first environmental interference intensity threshold, the initial data retransmission coefficient is updated based on the first step length to obtain the target data retransmission coefficient, and the initial data encoding method is updated based on the data encoding method sequence to obtain the target data encoding method; the data encoding method sequence includes multiple data encoding methods;

[0075] If the environmental interference intensity is less than the first environmental interference intensity threshold, the initial data retransmission coefficient is used as the target data retransmission coefficient, and the initial data encoding method is used as the target data encoding method.

[0076] In this embodiment, the free space scenario refers to a communication environment with no obstructions and a smooth signal transmission path. Its core characteristics are that the signal strength index is greater than or equal to a first strength threshold, the signal fluctuation index is less than a first signal fluctuation threshold, the correlation index is greater than or equal to a first correlation threshold, and the link quality score is greater than or equal to a first quality score threshold. For example, an open outdoor area has stable signals and excellent transmission quality, with no obvious interference or obstruction. The indoor obstacle scenario refers to an indoor communication environment with obstructions such as walls and furniture. Its signal strength index is greater than or equal to a first strength threshold, and the correlation index is greater than or equal to a first correlation threshold, but the link quality score is less than a first quality score threshold or the signal fluctuation index is greater than a first signal fluctuation threshold. The obstructions cause signal attenuation and decreased stability, resulting in moderate transmission quality, such as an indoor wall-connected communication scenario.

[0077] Multipath effect scenarios refer to communication environments where signals reach the receiver after multiple path reflections. The signal strength index is greater than or equal to the first strength threshold, but the correlation index is less than the first correlation threshold. Although the signal is relatively strong, multipath reflections cause a contradiction between the signal and link quality trends, resulting in a low link quality score. Examples include indoor areas with many glass or metal reflective surfaces, where signal strength is often artificially high but transmission is unstable. Weak signal edge scenarios refer to communication environments with severe signal attenuation and extremely low strength. The signal strength index is less than the first strength threshold, resulting in poor signal conditions and a high risk of connection drops. Examples include outdoor edge areas far from a second device (mobile phone) or indoor corners with strong signal shielding.

[0078] The first strength threshold refers to the critical value of signal strength used to distinguish weak signal edge scenarios from other scenarios. If the signal strength index is lower than this value, it is determined to be a weak signal edge scenario. For example, the first strength threshold can be set to -70 dB. The first correlation threshold refers to the critical value of correlation used to distinguish multipath effect scenarios from other scenarios. If the correlation index is lower than this value, it is determined to be a multipath effect scenario. For example, it can be set to 0. The first judgment condition refers to the composite condition for judging free space scenarios, which must simultaneously meet the link quality score and signal fluctuation index standards. It is the basis for distinguishing free space scenarios from indoor obstacle scenarios. The first quality score threshold refers to the critical value of the link quality score in the first judgment condition. If the link quality score is higher than or equal to this value, part of the requirements of the first judgment condition are met. The first signal fluctuation threshold refers to the critical value of the signal fluctuation index in the first judgment condition. If the signal fluctuation index is lower than this value, part of the requirements of the first judgment condition are met. The target data retransmission coefficient refers to the retransmission parameter ultimately used for data transmission, determining the number of retransmissions after data packet loss, and is one of the parameters of the data transmission strategy.

[0079] The target data encoding method refers to the encoding format ultimately used to process voice data. It determines the compression and anti-interference characteristics of the voice data and is one of the parameters of the data transmission strategy. The initial data retransmission coefficient refers to the retransmission parameters initially determined based on the communication scenario type. It is the basis of the target data retransmission coefficient, and different scenarios correspond to different initial values. The first environmental interference intensity threshold refers to the critical value of interference intensity used to adjust the transmission strategy. If the environmental interference intensity is higher than or equal to this value, the initial parameters need to be updated. The first step length refers to the adjustment range when updating the initial data retransmission coefficient. Each update increases or decreases the retransmission coefficient by this step length; for example, it can be set to 1. The data encoding sequence refers to a pre-stored set of encoding formats arranged in order of anti-interference capability gradient. It is used to update the initial data encoding method in high interference scenarios. For example, it may include Advanced Audio Coding-Low Complexity (AAC-LC), Sub-band Coding (SBC), Modified Sub-band Coding (mSBC), and Continuous Variable Slope Delta Modulation (CVSD).

[0080] In this embodiment, for determining the communication scenario type, weak signal edge scenarios are first filtered using a first strength threshold; for non-weak signal scenarios, multipath effect scenarios are then filtered using a first correlation threshold; the remaining scenarios are distinguished as free space scenarios and indoor obstacle scenarios using a first determination condition. For determining the data transmission strategy, this embodiment first matches the initial retransmission coefficient and encoding method according to the communication scenario type, and then determines whether to adjust based on a first environmental interference strength threshold. In cases of high interference (environmental interference strength exceeding the first environmental interference strength threshold), the retransmission coefficient is updated according to the first step length, and the encoding method is updated according to the data encoding method sequence. In cases of low interference (environmental interference strength not exceeding the first environmental interference strength threshold), the initial parameters are retained.

[0081] The considerations behind this embodiment are as follows: Weak signal edge scenarios have poor signal fundamentals, allowing for rapid identification using a first intensity threshold to avoid confusion with other scenarios; multipath effect scenarios are characterized by contradictory signal and quality (low correlation), which can be accurately identified using a first correlation threshold; free space scenarios exhibit high-quality and low-fluctuation communication signals, and this characteristic can be accurately captured by setting a first judgment condition, distinguishing them from indoor obstacle scenarios with obstructions. In the design of the data transmission strategy, this embodiment presets initial parameters to adapt to the basic characteristics of the scenario. Furthermore, if simultaneously in a high-interference scenario, the initial parameters are updated to enhance anti-interference capabilities and prevent data packet loss due to high interference; if in a low-interference scenario, the initial parameters can be retained to balance data transmission efficiency and avoid wasting computational resources.

[0082] For example, in this embodiment, various thresholds can be preset first, such as setting the first intensity threshold to -70 dB, the first correlation threshold to 0, the first quality score threshold to 8, the first signal fluctuation threshold to 5, the first environmental interference intensity threshold to 5, and the first step length to 1; at the same time, in this embodiment, the data encoding method sequence can be preset to AAC-LC, SBC, mSBC and CVSD, arranged from weakest to strongest in terms of anti-interference capability.

[0083] In this embodiment, the signal strength index is first determined. If the index is -75 dB (less than the first strength threshold of -70 dB), the communication scenario type is directly determined to be a weak signal edge scenario. If the signal strength index is -65 dB (greater than or equal to the first strength threshold), the correlation index is further determined. If the correlation index is -0.3 (less than the first correlation threshold of 0), it is determined to be a multipath effect scenario. If the correlation index is 0.5 (greater than the first correlation threshold), the link quality score and signal fluctuation index are determined. If the link quality score is 9 (greater than the first quality score threshold of 8) and the signal fluctuation index is 3 (less than the first signal fluctuation threshold of 5), the first determination condition is met, and it is determined to be a free space scenario. If the link quality score is 6 (less than the first quality score threshold) or the signal fluctuation index is 6 (greater than the first signal fluctuation threshold), the first determination condition is not met, and it is determined to be an indoor obstacle scenario.

[0084] This embodiment can determine the initial parameters based on the scenario. If it is a free space scenario, the initial data retransmission coefficient is set to 1 and the initial data encoding method is AAC-LC; if it is an indoor obstacle scenario, the initial data retransmission coefficient is set to 2 and the initial data encoding method is SBC; if it is a multipath effect scenario, the initial data retransmission coefficient is set to 3 and the initial data encoding method is mSBC; if it is a weak signal edge scenario, the initial data retransmission coefficient is set to 4 and the initial data encoding method is CVSD.

[0085] This embodiment can adjust parameters based on the intensity of environmental interference. It can determine the established environmental interference intensity. If the intensity is greater than or equal to a first environmental interference intensity threshold, the initial data retransmission coefficient is updated by a step length of 1 (e.g., from 1 to 2 in a free space scenario). The initial data encoding method is then switched down one level according to the data encoding method sequence (e.g., from AAC-LC to SBC in a free space scenario), thus obtaining the target data retransmission coefficient and the target data encoding method. If the environmental interference intensity is less than the first environmental interference intensity threshold, the initial data retransmission coefficient and the initial data encoding method are directly used as the target parameters to complete the determination of the data transmission strategy.

[0086] This embodiment can accurately determine the communication scenario type and adapt the data transmission strategy, improving the stability of voice calls. On the one hand, this embodiment determines the scenario through layered thresholds, first screening weak signals, then differentiating multipath effects, and finally distinguishing between free space and indoor obstacles, avoiding misjudgment based on a single parameter, and significantly improving the accuracy of scenario determination. On the other hand, this embodiment sets initial parameters to adapt to scenario characteristics, dynamically updates parameters to enhance anti-interference capabilities during high interference, and retains initial parameters to maintain efficiency during low interference, solving the problem of poor adaptability of fixed parameters in existing technologies, reducing voice stuttering and disconnections, and improving the user experience of voice calls between smart glasses and mobile phones.

[0087] In one embodiment of this application, determining the initial data retransmission coefficient and the initial data encoding method based on the communication scenario type includes:

[0088] If the communication scenario type is a free space scenario, then the initial data retransmission coefficient is determined to be the first retransmission coefficient, and the initial data encoding method is determined to be the first encoding method;

[0089] If the communication scenario type is an indoor obstacle scenario, then the initial data retransmission coefficient is determined to be the second retransmission coefficient, and the initial data encoding method is determined to be the second encoding method;

[0090] If the communication scenario is a multipath effect scenario, then the initial data retransmission coefficient is determined to be the third retransmission coefficient, and the initial data encoding method is determined to be the third encoding method.

[0091] If the communication scenario type is a weak signal edge scenario, then the initial data retransmission coefficient is determined to be the fourth retransmission coefficient, and the initial data encoding method is determined to be the fourth encoding method;

[0092] The first retransmission coefficient is less than the second retransmission coefficient, the second retransmission coefficient is less than the third retransmission coefficient, and the third retransmission coefficient is less than the fourth retransmission coefficient.

[0093] The encoding characteristic parameters of the first encoding method are higher than those of the second encoding method, the encoding characteristic parameters of the second encoding method are higher than those of the third encoding method, and the encoding characteristic parameters of the third encoding method are higher than those of the fourth encoding method; the encoding characteristic parameters include bit rate and encoding complexity.

[0094] In this embodiment, the first retransmission coefficient refers to the initial data retransmission coefficient corresponding to the communication scenario type of free space. It is the smallest among the four types of retransmission coefficients and is used to adapt to scenarios with stable signals, reducing unnecessary retransmissions. The second retransmission coefficient refers to the initial data retransmission coefficient corresponding to the communication scenario type of indoor obstacle scenario. Its value is greater than the first retransmission coefficient and is used to cope with signal fluctuations caused by obstruction. The third retransmission coefficient refers to the initial data retransmission coefficient corresponding to the communication scenario type of multipath effect scenario. Its value is greater than the second retransmission coefficient and is used to adapt to scenarios where signal and quality conflict, improving the ability to resist packet loss. The fourth retransmission coefficient refers to the initial data retransmission coefficient corresponding to the communication scenario type of weak signal edge scenario. It is the largest among the four types of retransmission coefficients and is used to cope with scenarios with extremely weak signals, ensuring the integrity of data transmission.

[0095] The first encoding method refers to the initial data encoding method corresponding to the communication scenario of free space. It has the highest encoding characteristic parameters (bit rate, encoding complexity) and balances sound quality and efficiency. The second encoding method refers to the initial data encoding method corresponding to the communication scenario of indoor obstacles. Its encoding characteristic parameters are lower than the first encoding method, balancing anti-interference and sound quality. The third encoding method refers to the initial data encoding method corresponding to the communication scenario of multipath effects. Its encoding characteristic parameters are lower than the second encoding method, prioritizing anti-interference capability. The fourth encoding method refers to the initial data encoding method corresponding to the communication scenario of weak signal edge. It has the lowest encoding characteristic parameters, simplifying complexity and reducing bit rate to ensure transmission feasibility under extremely weak signals.

[0096] Considering that the severity of the communication scenario is negatively correlated with signal quality, the signal in the free space scenario is stable and has little interference, so there is no need for frequent retransmissions, and high-characteristic coding can be used to ensure sound quality. In the weak signal edge scenario, the signal is extremely weak and prone to packet loss, so more retransmissions are needed to compensate for packet loss, and low-characteristic coding (low bit rate, low complexity) is more suitable for weak signal bandwidth limitations and device computing power. In the intermediate scenario, the parameters are adjusted according to the severity of the scenario, which can achieve accurate adaptation between the scenario and the initial transmission parameters, avoiding resource waste when the scenario is good or insufficient anti-interference when the scenario is poor.

[0097] For example, the specific implementation process of this embodiment may include:

[0098] In this embodiment, the specific values ​​of four types of initial data retransmission coefficients can be preset first. For example, the first retransmission coefficient is set to 1 (only 1 retransmission), the second retransmission coefficient is set to 2 (maximum 2 retransmissions), the third retransmission coefficient is set to 3 (maximum 3 retransmissions), and the fourth retransmission coefficient is set to 4 (maximum 4 retransmissions), ensuring that the values ​​satisfy the condition that the first retransmission coefficient < the second retransmission coefficient < the third retransmission coefficient < the fourth retransmission coefficient.

[0099] This embodiment can preset four initial data encoding methods and corresponding encoding characteristic parameters. For example, the first encoding method is set to AAC-LC with a bit rate of 320kbps and high encoding complexity; the second encoding method is SBC with a bit rate of 192kbps and medium encoding complexity; the third encoding method is mSBC with a bit rate of 64kbps and low encoding complexity; and the fourth encoding method is CVSD with a bit rate of 32kbps and the lowest encoding complexity, ensuring that the encoding characteristic parameters decrease sequentially from the first encoding method to the fourth encoding method.

[0100] In this embodiment, a mapping table of communication scenario types and data transmission strategy parameters can be constructed in the first device, corresponding the free space scenario to the first retransmission coefficient and the first encoding method, the indoor obstacle scenario to the second retransmission coefficient and the second encoding method, the multipath effect scenario to the third retransmission coefficient and the third encoding method, and the weak signal edge scenario to the fourth retransmission coefficient and the fourth encoding method.

[0101] Once the first device determines the communication scenario type, this embodiment can call the mapping table for matching. If it is determined to be a free space scenario, the first retransmission coefficient is extracted from the mapping table as the initial data retransmission coefficient, and the first encoding method is extracted as the initial data encoding method; if it is determined to be a weak signal edge scenario, the fourth retransmission coefficient and the fourth encoding method are extracted as initial parameters, thus completing the determination of the initial data retransmission coefficient and the initial data encoding method.

[0102] This embodiment ensures that the initial data retransmission coefficient and initial data encoding method are accurately adapted to different communication environments by gradient matching between the scenario and the initial transmission parameters, avoiding the shortcomings of existing technologies that rely on a single initial parameter to adapt to all scenarios. Reasonable initial parameters lay the foundation for subsequent interference intensity adjustment strategies, effectively reducing packet loss and stuttering in voice calls and improving the stability of voice transmission between smart glasses and mobile phones.

[0103] Corresponding to the stable transmission method of voice call data in the above embodiment, Figure 3 This is a structural block diagram of a stable voice call data transmission device provided according to an embodiment of this application. For ease of explanation, only the parts relevant to the embodiment of this application are shown. References Figure 3 The stable voice call data transmission device 20 includes: a data acquisition module 21, a scene analysis module 22, and a data transmission module 23.

[0104] The data acquisition module 21 is used to acquire the voice call data to be transmitted, as well as the communication signal strength data, communication link quality data, signal-to-noise ratio and signal-to-interference ratio between the first device and the second device.

[0105] Scene analysis module 22 is used to determine the communication scene type based on communication signal strength data and communication link quality data, and to determine the environmental interference intensity based on the communication scene type, signal-to-noise ratio and signal-to-interference ratio;

[0106] The data transmission module 23 is used to determine the data transmission strategy based on the intensity of environmental interference and the type of communication scenario, process the voice call data based on the data transmission strategy to obtain the target transmission data, and send the target transmission data to the second device.

[0107] In one embodiment of this application, when determining the communication scenario type based on communication signal strength data and communication link quality data, the scenario analysis module 22 is specifically used for:

[0108] Calculate the signal fluctuation index and signal strength index based on communication signal strength data;

[0109] Calculate the link quality score based on communication link quality data;

[0110] Calculate the correlation index between communication signal strength data and communication link quality data;

[0111] The communication scenario type is determined based on the correlation index, link quality score, signal fluctuation index, and signal strength index.

[0112] In one embodiment of this application, the communication signal strength data includes multiple communication signal strength values; when the scene analysis module 22 calculates the signal fluctuation index and the signal strength index based on the communication signal strength data, it is specifically used to: calculate the mean and variance of the communication signal strength data; use the mean as the signal strength index; and calculate the signal fluctuation index based on the mean and variance.

[0113] In one embodiment of this application, when determining the communication scenario type based on the correlation index, link quality score, signal fluctuation index, and signal strength index, the scenario analysis module 22 is specifically used for:

[0114] If the signal strength index is less than the first strength threshold, the communication scenario type is determined to be a weak signal edge scenario.

[0115] If the signal strength index is greater than or equal to the first strength threshold, then:

[0116] When the correlation index is less than the first correlation threshold, the communication scenario type is determined to be a multipath effect scenario.

[0117] When the correlation index is greater than or equal to the first correlation threshold and the link quality score and signal fluctuation index meet the first judgment condition, the communication scenario type is determined to be a free space scenario.

[0118] When the correlation index is greater than or equal to the first correlation threshold and the link quality score and signal fluctuation index do not meet the first judgment condition, the communication scenario type is determined to be an indoor obstacle scenario.

[0119] The first criterion is that the link quality score is greater than or equal to the first quality score threshold, and the signal fluctuation index is less than the first signal fluctuation threshold.

[0120] In one embodiment of this application, the data transmission strategy includes a target data retransmission coefficient and a target data encoding method; when determining the data transmission strategy based on environmental interference intensity and communication scenario type, the data transmission module 23 is specifically used for:

[0121] The initial data retransmission coefficient and initial data encoding method are determined based on the type of communication scenario.

[0122] If the environmental interference intensity is greater than or equal to the first environmental interference intensity threshold, the initial data retransmission coefficient is updated based on the first step length to obtain the target data retransmission coefficient, and the initial data encoding method is updated based on the data encoding method sequence to obtain the target data encoding method; the data encoding method sequence includes multiple data encoding methods;

[0123] If the environmental interference intensity is less than the first environmental interference intensity threshold, the initial data retransmission coefficient is used as the target data retransmission coefficient, and the initial data encoding method is used as the target data encoding method.

[0124] In one embodiment of this application, when determining the initial data retransmission coefficient and the initial data encoding method based on the communication scenario type, the data transmission module 23 is specifically used for:

[0125] If the communication scenario type is a free space scenario, then the initial data retransmission coefficient is determined to be the first retransmission coefficient, and the initial data encoding method is determined to be the first encoding method;

[0126] If the communication scenario type is an indoor obstacle scenario, then the initial data retransmission coefficient is determined to be the second retransmission coefficient, and the initial data encoding method is determined to be the second encoding method;

[0127] If the communication scenario is a multipath effect scenario, then the initial data retransmission coefficient is determined to be the third retransmission coefficient, and the initial data encoding method is determined to be the third encoding method.

[0128] If the communication scenario type is a weak signal edge scenario, then the initial data retransmission coefficient is determined to be the fourth retransmission coefficient, and the initial data encoding method is determined to be the fourth encoding method;

[0129] The first retransmission coefficient is less than the second retransmission coefficient, the second retransmission coefficient is less than the third retransmission coefficient, and the third retransmission coefficient is less than the fourth retransmission coefficient.

[0130] The encoding characteristic parameters of the first encoding method are higher than those of the second encoding method, the encoding characteristic parameters of the second encoding method are higher than those of the third encoding method, and the encoding characteristic parameters of the third encoding method are higher than those of the fourth encoding method; the encoding characteristic parameters include bit rate and encoding complexity.

[0131] In one embodiment of this application, when determining the environmental interference intensity based on the communication scenario type, signal-to-noise ratio (SNR), and signal-to-interference ratio (SMI), the scenario analysis module 22 is specifically used to: determine the interference weight coefficient based on the communication scenario type; perform homing preprocessing on the SNR and SMI; and perform weighted summation on the homing preprocessed SNR and SMI based on the interference weight coefficient to obtain the environmental interference intensity.

[0132] See Figure 4 , Figure 4 This is a schematic block diagram of an electronic device provided according to an embodiment of this application. In this embodiment, the electronic device can be the first device described in the above embodiments.

[0133] like Figure 4 The electronic device 300 in this embodiment may include one or more processors 301, one or more input devices 302, one or more output devices 303, and one or more memories 304. The processors 301, input devices 302, output devices 303, and memories 304 communicate with each other via a communication bus 305. The memories 304 store computer programs, including program instructions. The processors 301 execute the program instructions stored in the memories 304. Specifically, the processors 301 are configured to invoke the program instructions to perform the functions of the modules in the aforementioned device embodiments, for example... Figure 3 The functions of the data acquisition module 21, the scene analysis module 22, and the data transmission module 23 are shown.

[0134] It should be understood that, in the embodiments of this application, the processor 301 may be a central processing unit (CPU), but it may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0135] Input device 302 may include a touchpad, a fingerprint sensor (for collecting the user's fingerprint information and fingerprint orientation information), a microphone, etc., and output device 303 may include a display (LCD, etc.), a speaker, etc.

[0136] The memory 304 may include read-only memory and random access memory, and provides instructions and data to the processor 301. A portion of the memory 304 may also include non-volatile random access memory. For example, the memory 304 may also store call data.

[0137] In specific implementations, the processor 301, input device 302, and output device 303 described in the embodiments of this application can execute the implementation methods described in the embodiments of the stable voice call data transmission method provided in the embodiments of this application, or they can execute the implementation methods of the electronic device 300 described in the embodiments of this application, which will not be repeated here.

[0138] In another embodiment of this application, a computer-readable storage medium is provided. This computer-readable storage medium stores a computer program, which includes program instructions. When executed by a processor, the program instructions implement all or part of the processes in the methods described above. Alternatively, the computer program can instruct related hardware to complete the process. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0139] The computer-readable storage medium can be an internal storage unit of the electronic device in any of the foregoing embodiments, such as a hard disk or memory of the electronic device. The computer-readable storage medium can also be an external storage device of the electronic device, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD) card, flash card, etc., equipped on the electronic device. Furthermore, the computer-readable storage medium can include both internal and external storage units of the electronic device. The computer-readable storage medium is used to store computer programs and other programs and data required by the electronic device. The computer-readable storage medium can also be used to temporarily store data that has been output or will be output.

[0140] Those skilled in the art will recognize that the modules / units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0141] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the electronic devices and units described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0142] In the several embodiments provided in this application, it should be understood that the disclosed electronic devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of modules / units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules, units, or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces or modules / units, or it may be an electrical, mechanical, or other form of connection.

[0143] The modules / units described as separate components may or may not be physically separate. Similarly, the components shown as modules / units may or may not be physical modules / units; they may be located in one place or distributed across multiple network modules / units. Some or all of the modules / units can be selected to achieve the purpose of the embodiments of this application, depending on actual needs.

[0144] Furthermore, the functional modules / units in the various embodiments of this application can be integrated into one processing module / unit, or each module / unit can exist physically separately, or two or more modules / units can be integrated into one module / unit. The integrated modules / units described above can be implemented in hardware or in the form of software functional modules / units.

[0145] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for stable transmission of voice call data, characterized in that, Performed by the first device, including: Acquire the voice call data to be transmitted, as well as the communication signal strength data, communication link quality data, signal-to-noise ratio, and signal-to-interference ratio between the first and second devices; The communication scenario type is determined based on the communication signal strength data and the communication link quality data, and the environmental interference intensity is determined based on the communication scenario type, the signal-to-noise ratio, and the signal-to-interference ratio. Based on the environmental interference intensity and the communication scenario type, a data transmission strategy is determined. The voice call data is then processed based on the data transmission strategy to obtain target transmission data, which is then sent to the second device.

2. The method for stable transmission of voice call data as described in claim 1, characterized in that, The process of determining the communication scenario type based on the communication signal strength data and the communication link quality data includes: Calculate the signal fluctuation index and the signal strength index based on the communication signal strength data; Calculate the link quality score based on the communication link quality data; Calculate the correlation index between the communication signal strength data and the communication link quality data; The communication scenario type is determined based on the correlation index, the link quality score, the signal fluctuation index, and the signal strength index.

3. The method for stable transmission of voice call data as described in claim 2, characterized in that, The communication signal strength data includes multiple communication signal strength values; The calculation of the signal fluctuation index and signal strength index based on the communication signal strength data includes: Calculate the mean and variance of the communication signal strength data; The mean value is used as the signal strength index; The signal fluctuation index is calculated based on the mean and the variance.

4. The method for stable transmission of voice call data as described in claim 2, characterized in that, The determination of the communication scenario type based on the correlation index, the link quality score, the signal fluctuation index, and the signal strength index includes: If the signal strength index is less than the first strength threshold, then the communication scenario type is determined to be a weak signal edge scenario; If the signal strength index is greater than or equal to the first strength threshold, then: When the correlation index is less than the first correlation threshold, the communication scenario type is determined to be a multipath effect scenario. When the correlation index is greater than or equal to the first correlation threshold and the link quality score and the signal fluctuation index meet the first determination condition, the communication scenario type is determined to be a free space scenario. When the correlation index is greater than or equal to the first correlation threshold and the link quality score and the signal fluctuation index do not meet the first determination condition, the communication scenario type is determined to be an indoor obstacle scenario. The first determination condition is that the link quality score is greater than or equal to the first quality score threshold, and the signal fluctuation index is less than the first signal fluctuation threshold.

5. The method for stable transmission of voice call data as described in claim 4, characterized in that, The data transmission strategy includes the target data retransmission coefficient and the target data encoding method; The step of determining the data transmission strategy based on the environmental interference intensity and the communication scenario type includes: The initial data retransmission coefficient and the initial data encoding method are determined based on the communication scenario type. If the environmental interference intensity is greater than or equal to the first environmental interference intensity threshold, the initial data retransmission coefficient is updated based on the first step length to obtain the target data retransmission coefficient, and the initial data encoding method is updated based on the data encoding method sequence to obtain the target data encoding method; the data encoding method sequence includes multiple data encoding methods; If the environmental interference intensity is less than the first environmental interference intensity threshold, then the initial data retransmission coefficient is used as the target data retransmission coefficient, and the initial data encoding method is used as the target data encoding method.

6. The method for stable transmission of voice call data as described in claim 5, characterized in that, The determination of the initial data retransmission coefficient and the initial data encoding method based on the communication scenario type includes: If the communication scenario type is the free space scenario, then the initial data retransmission coefficient is determined to be the first retransmission coefficient, and the initial data encoding method is determined to be the first encoding method; If the communication scenario type is the indoor obstacle scenario, then the initial data retransmission coefficient is determined to be the second retransmission coefficient, and the initial data encoding method is determined to be the second encoding method; If the communication scenario type is the multipath effect scenario, then the initial data retransmission coefficient is determined to be the third retransmission coefficient, and the initial data encoding method is determined to be the third encoding method; If the communication scenario type is the weak signal edge scenario, then the initial data retransmission coefficient is determined to be the fourth retransmission coefficient, and the initial data encoding method is determined to be the fourth encoding method; The first retransmission coefficient is less than the second retransmission coefficient, the second retransmission coefficient is less than the third retransmission coefficient, and the third retransmission coefficient is less than the fourth retransmission coefficient. The encoding characteristic parameters of the first encoding method are higher than those of the second encoding method, the encoding characteristic parameters of the second encoding method are higher than those of the third encoding method, and the encoding characteristic parameters of the third encoding method are higher than those of the fourth encoding method; the encoding characteristic parameters include bit rate and encoding complexity.

7. The method for stable transmission of voice call data as described in claim 1, characterized in that, Determining the environmental interference intensity based on the communication scenario type, the signal-to-noise ratio, and the signal-to-interference ratio includes: Determine the interference weighting coefficient based on the communication scenario type; The signal-to-noise ratio and the signal-to-interference ratio are preprocessed to be aligned. The environmental interference intensity is obtained by weighting and summing the signal-to-noise ratio and signal-to-interference ratio after the homing preprocessing based on the interference weighting coefficient.

8. A device for stable transmission of voice call data, characterized in that, Performed by the first device, including: The data acquisition module is used to acquire the voice call data to be transmitted, as well as the communication signal strength data, communication link quality data, signal-to-noise ratio and signal-to-interference ratio between the first device and the second device; The scenario analysis module is used to determine the communication scenario type based on the communication signal strength data and the communication link quality data, and to determine the environmental interference intensity based on the communication scenario type, the signal-to-noise ratio, and the signal-to-interference ratio. The data transmission module is used to determine a data transmission strategy based on the environmental interference intensity and the communication scenario type, process the voice call data based on the data transmission strategy to obtain target transmission data, and send the target transmission data to the second device.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

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