Self-adaptive frequency jump method, device and equipment for low-power-consumption dual-mode Bluetooth chip

Abstract

The invention relates to the technical field of communication control, and discloses a self-adaptive frequency jump method, device and equipment for a low-power-consumption dual-mode Bluetooth chip, and the method comprises the steps: obtaining a current Bluetooth mode, detecting the channel quality of a communication environment, obtaining the basic characteristics of the channel quality, and constructing a channel decision management framework; the communication interference condition is detected in real time, the channel decision management framework is adjusted to avoid interference, and real-time channel quality monitoring and channel selection directivity analysis are carried out according to the adjusted channel decision management framework to obtain channel selection reference features. According to the method, channel selection and frequency hopping strategies are optimized through a self-adaptive frequency hopping mechanism, channel frequency hopping decision preprocessing of mode conversion is carried out on another Bluetooth mode on the basis of channel selection reference characteristics, collaborative decision of channel frequency hopping is carried out, and the dual-mode Bluetooth chip is driven to carry out channel frequency hopping processing. The problem that in the prior art, a fixed frequency hopping mechanism is difficult to adapt to the communication requirement of dual-mode Bluetooth is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of communication control, and in particular, to an adaptive frequency hopping method, device, and equipment for a low-power dual-mode Bluetooth chip. Background Art

[0002] A dual-mode Bluetooth chip refers to a chip that can simultaneously support two communication modes: classic Bluetooth (BR / EDR) and low-power Bluetooth (BLE). Classic Bluetooth is mainly used for applications with high data transfer rates, such as audio transmission and data synchronization, while low-power Bluetooth is more suitable for power-sensitive applications, such as Internet of Things devices and health monitoring devices. Channel hopping is an anti-interference technology in Bluetooth technology, which transmits data by quickly switching between different channels to reduce signal interference and improve communication reliability. Due to the differences in channel selection and hopping strategies between classic Bluetooth and low-power Bluetooth, as well as the complex and changing wireless communication environment, traditional fixed hopping mechanisms are difficult to meet the requirements of efficient and stable communication. Summary of the Invention

[0003] The purpose of the present invention is to provide an adaptive frequency hopping method, device, and equipment for a low-power dual-mode Bluetooth chip, aiming to solve the problem that the existing fixed hopping mechanism is difficult to adapt to the communication requirements of dual-mode Bluetooth.

[0004] The present invention is implemented as follows. In the first aspect, the present invention provides an adaptive frequency hopping method for a low-power dual-mode Bluetooth chip, including: Obtaining the Bluetooth mode currently running on the dual-mode Bluetooth chip, and detecting the channel quality of the communication environment where the dual-mode Bluetooth chip is currently located to obtain the basic channel quality characteristics of the dual-mode Bluetooth chip; wherein, the Bluetooth mode includes the classic Bluetooth mode and the low-power Bluetooth mode; Deploying the preliminary work parameters for chip hopping decision-making on the dual-mode Bluetooth chip according to the Bluetooth mode and the basic channel quality characteristics to construct a channel decision management framework; wherein, the channel decision management framework includes a weight factor decision framework corresponding to the classic Bluetooth mode and a priority gradient decision framework corresponding to the low-power Bluetooth mode; Real-time detecting the communication interference status of the dual-mode Bluetooth chip, performing temporal correlation analysis on the communication interference status of the dual-mode Bluetooth chip at each moment, and adjusting the parameters for interference avoidance of the channel decision management framework according to the analysis results; Performing real-time channel quality monitoring and channel selection directivity analysis on the communication environment where the dual-mode Bluetooth chip is located according to the channel decision management framework after the parameter adjustment for interference avoidance to obtain channel selection reference characteristics; Channel hopping decision preparation processing for mode conversion of another Bluetooth mode based on the channel selection reference feature is performed to obtain a mode conversion preparation feature, and collaborative decision-making on channel hopping for the channel selection reference feature is carried out according to the mode conversion preparation feature, so as to drive the dual-mode Bluetooth chip to perform channel hopping processing.

[0005] In a second aspect, the present invention provides an adaptive frequency hopping device for a low-power dual-mode Bluetooth chip, which is used to implement the adaptive frequency hopping method for a low-power dual-mode Bluetooth chip described in any one of the first aspects.

[0006] In a third aspect, the present invention provides a computer device, including a memory and a processor. The memory stores a computer program that can run on the processor, and when the processor executes the computer program, it implements the adaptive frequency hopping method for a low-power dual-mode Bluetooth chip described in any one of the first aspects.

[0007] The present invention provides an adaptive frequency hopping method for a low-power dual-mode Bluetooth chip, which has the following beneficial effects: The present invention obtains the current Bluetooth mode and detects the channel quality of the communication environment to obtain the basic channel quality feature to construct a channel decision management framework, real-time detects the communication interference situation and adjusts the channel decision management framework to avoid interference, performs real-time channel quality monitoring and channel selection directivity analysis according to the adjusted channel decision management framework to obtain a channel selection reference feature, performs channel hopping decision preparation processing for mode conversion of another Bluetooth mode based on the channel selection reference feature, and performs collaborative decision-making on channel hopping, driving the dual-mode Bluetooth chip to perform channel hopping processing. This method optimizes channel selection and hopping strategies through an adaptive frequency hopping mechanism, and solves the problem that the fixed hopping mechanism in the prior art is difficult to meet the communication requirements of dual-mode Bluetooth. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 is a schematic diagram of the steps of an adaptive frequency hopping method for a low-power dual-mode Bluetooth chip provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0009] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0010] The implementation of the present invention will be described in detail below with reference to specific embodiments.

[0011] Refer to Figure 1 as shown, which is a preferred embodiment provided by the present invention.

[0012] In a first aspect, the present invention provides an adaptive frequency hopping method for a low-power dual-mode Bluetooth chip, including: S1: Obtain the Bluetooth mode currently running on the dual-mode Bluetooth chip, and detect the channel quality of the communication environment where the dual-mode Bluetooth chip is currently located, so as to obtain the basic channel quality characteristics of the dual-mode Bluetooth chip; wherein, the Bluetooth mode includes the classic Bluetooth mode and the low-power Bluetooth mode; S2: Deploy the preliminary work parameters for chip frequency hopping decision-making on the dual-mode Bluetooth chip according to the Bluetooth mode and the basic channel quality characteristics, so as to construct a channel decision management framework; wherein, the channel decision management framework includes a weight factor decision framework corresponding to the classic Bluetooth mode and a priority gradient decision framework corresponding to the low-power Bluetooth mode; S3: Real-time detect the communication interference situation of the dual-mode Bluetooth chip, perform temporal correlation analysis on the communication interference situation of the dual-mode Bluetooth chip at each moment, and adjust the parameters for interference avoidance of the channel decision management framework according to the analysis results; S4: Perform real-time channel quality monitoring and channel selection directivity analysis on the communication environment where the dual-mode Bluetooth chip is located according to the channel decision management framework after the parameter adjustment for interference avoidance, so as to obtain channel selection reference characteristics; S5: Perform preliminary processing of channel hopping decision for mode conversion on another Bluetooth mode based on the channel selection reference characteristics, obtain mode conversion preliminary characteristics, and perform collaborative decision-making of channel hopping on the channel selection reference characteristics according to the mode conversion preliminary characteristics, so as to drive the dual-mode Bluetooth chip to perform channel hopping processing.

[0013] Specifically, in step S1 of the embodiment provided by the present invention, the chip reads the current operating mode (classic Bluetooth mode BR / EDR or low-power Bluetooth mode BLE) through an internal register or a firmware status word. The mode determination logic is based on the protocol stack type (such as the classic Bluetooth uses the ACL link, and BLE uses the GATT protocol) or the power consumption profile. The hardware layer identifies the mode through the configuration status of the baseband controller, and the software layer queries the current mode through the API of the Bluetooth protocol stack (such as BlueZ, Zephyr).

[0014] More specifically, call the set of selectable channels, select the corresponding physical channel list according to the current mode. The classic Bluetooth mode uses 79 1MHz frequency hopping channels (2.4GHz ISM band, 2402 - 2480MHz), and the low-power Bluetooth mode uses 40 2MHz channels (divided into 3 broadcast channels and 37 data channels). Dynamically adjust the available channel range according to regional regulations (such as FCC, ETSI), and call the channel map to load the predefined set of channels.

[0015] More specifically, detecting and analyzing the channel quality includes detecting the received signal strength indicator (RSSI), measuring the signal power (in dBm) of each channel through the radio frequency front-end (RF Frontend), and identifying high-noise channels; detecting the bit error rate (BER), and evaluating the channel reliability by statistically analyzing the packet error rate through the baseband processor.

[0016] More specifically, select representative channels of different types. In the classic Bluetooth mode, select representative channels in the high-frequency band, medium-frequency band, and low-frequency band (such as 2402 MHz, 2441 MHz, 2480 MHz). In the BLE mode, select the representative frequency points of the broadcast channels (37 / 38 / 39) and data channels, use the scan window to traverse the channels, periodically sample the RSSI and BER, and quantify the signal quality through the ADC module.

[0017] More specifically, construct a channel quality indicator matrix. Combine the RSSI and BER values of each representative channel into a vector. For example: [RSSI = -70 dBm, BER = 1e-4]. Through interpolation or regression algorithms, expand the sparse representative channel data into a quality matrix of the complete channel set. The matrix dimension includes N×M (N is the number of channels, and M is the dimension of the quality index). Use linear interpolation or Kalman filtering to predict the quality of undetected channels, and store the matrix in the chip memory or external EEPROM.

[0018] More specifically, adopt K-means or hierarchical clustering to divide the channels into several clusters according to the quality vectors (such as high-quality, medium-quality, and low-quality). The potential channels are the channel clusters with low BER and high RSSI, and the inferior channels are the channel clusters with high BER, low RSSI, or being interfered. Output the basic characteristics of the channel quality (such as the proportion of high-quality channels, interference distribution pattern). A lightweight clustering algorithm (such as Mini-Batch K-means) can be used to adapt to the low-power chip resources.

[0019] It can be understood that according to the channel characteristics of different Bluetooth modes (such as the hopping density of classic Bluetooth, the fixed broadcast channels of BLE), conduct targeted detection and optimization. Through the detection of representative channels and matrix interpolation, reduce the energy consumption of full-channel scanning (only need to detect 10%-20% of the channels). The clustering analysis quickly identifies the superior and inferior channels, reduces the complexity of real-time decision-making. Through the joint analysis of RSSI and BER, distinguish between the scenarios of signal attenuation (low RSSI) and noise interference (high BER). After separating the superior and inferior channels, preferentially select the channels in the high-quality cluster to reduce the data retransmission rate.

[0020] Specifically, in step S2 of the embodiment provided by the present invention, 79 hopping channels of classic Bluetooth are mapped to independent selection units (each unit contains metadata such as channel ID, frequency, weight factor, etc.). The mapping relationship between the channels and the selection units is established through a hash table or an array. Based on the basic characteristics of channel quality (such as the channels in the high-quality channel cluster), an initial priority weight is assigned to each selection unit (such as high-quality channel weight = 0.8, low-quality channel weight = 0.2). Through real-time interference detection (such as an increase in packet error rate), the weight of the interfered channel is dynamically reduced, and the quality weight factor adjusts the weight in real time according to the change of channel quality (such as RSSI fluctuation).

[0021] More specifically, the weight is updated once per second. The channels are sorted according to the total weight (initial weight + interference weight + quality weight), and the channel with the highest weight is selected as the current communication channel. A min-heap or a priority queue is used to achieve fast sorting.

[0022] More specifically, for the priority gradient decision framework of the low-power Bluetooth mode, 40 channels of BLE are divided into 3 - 5 priority gradients (such as gradient 1 being the highest priority). Based on the basic characteristics of channel quality (such as broadcast channels 37 / 38 / 39 being forced to gradient 1), an example grouping: the gradient level includes channel priority, gradient 1: 37, 38, 39 (broadcast channels) highest, gradient 2: 0 - 10 (high-quality data channels) high, gradient 3: 11 - 36 (ordinary data channels) medium.

[0023] More specifically, for gradient difference analysis, the internal difference calculates the quality standard deviation of the channels within the same gradient (such as the RSSI fluctuation of the channels within gradient 2 needs to be less than 5dBm), and the interaction difference compares the average quality difference between different gradients (such as the average RSSI of gradient 1 is 10dBm higher than that of gradient 2); 1 - 2 representative channels are selected for each gradient (such as channel 38 is selected for gradient 1). When the quality of the representative channel is lower than the gradient threshold, in-gradient replacement (selecting the sub-optimal channel of the same gradient) or inter-gradient replacement (degrading to the next gradient) is triggered.

[0024] More specifically, for the low-power optimization strategy, during the non-active communication period, only the high-priority gradient channels are monitored to reduce the scanning energy consumption, and the sleep and wake-up cycles of the radio frequency module are controlled by a timer.

[0025] More specifically, for the decision framework type weight factor decision framework (Classic Bluetooth) has a higher priority gradient than the decision framework (Low Energy Bluetooth). The core objective of the former is dynamic anti-interference to maximize real-time communication quality, while the latter is to reduce power consumption and ensure basic connection stability. The computational complexity of the former is relatively high (requiring real-time weight calculation and sorting), while the latter is relatively low (with fixed gradient priorities and limited replacement logic). The applicable scenarios of the former are high-interference environments (such as Wi-Fi dense areas), and the latter is for low-power demand scenarios (such as wearable devices and sensor networks). The typical performance improvements are that the bit error rate is reduced by 40% and the throughput is increased by 30% for the former, while the power consumption is reduced by 50% and the connection stability is increased by 20% for the latter. The former requires more memory to store the weight matrix, while the latter only needs to store the gradient grouping table. The real-time requirement of the former is high (millisecond-level response), and the latter is medium (hundred-millisecond-level response).

[0026] More specifically, for the mode adaptive switching, when the device switches from Classic Bluetooth (transferring large files) to BLE (standby state), the framework automatically transitions from the weight factor mode to the priority gradient mode to avoid channel conflicts. The dual-mode framework shares the channel quality database. Classic Bluetooth avoids the BLE broadcast channels (37 / 38 / 39) to reduce the mutual interference between the two modes of the same device. In the BLE mode, the computational amount is reduced by gradient staticization; in the Classic mode, complex interference is handled through dynamic weights to achieve global optimization.

[0027] More specifically, for application examples: When the smart speaker (Classic Bluetooth mode) is playing music, the weight factor framework dynamically avoids the 2.4GHz channel interfered by the microwave oven to ensure audio fluency. The smart watch (Low Energy Bluetooth mode) with the priority gradient framework always selects the broadcast channel of gradient 1 to ensure low-latency notification messages, and at the same time keeps the RF module in the sleep state 95% of the time.

[0028] It can be understood that through the differential design of the weight factor decision framework and the priority gradient decision framework, the dual-mode Bluetooth chip can achieve dynamic anti-interference with a relatively high computational overhead in the Classic Bluetooth mode, which is suitable for high-throughput scenarios. In the Low Energy Bluetooth mode, the power consumption is reduced by a fixed gradient strategy, which is suitable for resource-constrained IoT devices. The two frameworks achieve the optimal balance between performance and power consumption through a unified channel quality database and cooperative switching logic.

[0029] Specifically, in step S3 of the embodiment provided by the present invention, the built-in RF front-end ADC module of the dual-mode Bluetooth chip is used to capture I / Q signals at a high sampling rate (such as 2MHz) and convert them into digital signals in real time. When the received signal strength (RSSI) exceeds the dynamic threshold (such as -70dBm) or the bit error rate (BER) suddenly increases, interference detection is started.

[0030] More specifically, multi-dimensional interference feature extraction includes time-domain analysis, calculating the packet error rate (PER) to statistically analyze the proportion of data packets with CRC check failures per unit time, the signal occupancy time ratio, and the ratio of the duration of the interference signal to the detection window (e.g., a Wi-Fi duty cycle > 30% is considered strong interference); frequency-domain analysis, calculating the channel spectrum energy distribution through fast Fourier transform (FFT) to identify narrowband interference (such as a microwave oven) or broadband interference (such as Wi-Fi).

[0031] Example spectrum features: Microwave oven interference: Concentrated at 2.45 GHz ± 50 MHz, with energy in periodic pulses. Wi-Fi interference: Distributed across multiple 20 MHz channels in the 2.4 GHz band, with continuous energy.

[0032] More specifically, with a 10 ms time window, perform moving averages on the interference features (PER, spectrum energy) to extract short-term trends, detect periodic interference (such as a microwave oven starting every 30 seconds), and perform time series pattern recognition. Use a lightweight LSTM network or an autoregressive model (ARIMA) to predict the interference evolution trend.

[0033] More specifically, for interference source tracing and type classification, compare the time-frequency features of the current interference with a predefined interference fingerprint library (such as the typical features of Wi-Fi, ZigBee, and microwave ovens), and use cosine similarity or Euclidean distance for matching. If the matching degree > 0.8, it is determined as a known interference type; otherwise, it is marked as "unknown interference" and the fingerprint library is updated through online learning.

[0034] More specifically, for dynamic adjustment of decision framework parameters, in the interference avoidance strategy of the classic Bluetooth mode (weight factor framework), if Wi-Fi interference is detected, reduce the weights of the Bluetooth channels overlapping with the Wi-Fi channels (such as multiplying the weights of channels 1 - 13 in the 2.4 GHz band by 0.5), and temporarily freeze the option of the interfered channel for 10 hopping periods to resist burst interference; for the gradient priority reallocation in the low-power Bluetooth mode (priority gradient framework), if the broadcast channels (37 / 38 / 39) are interfered, promote the highest-quality subset of the data channels to the temporary gradient 1, and during the interference duration, extend the scanning interval of the low-priority channels (such as adjusting from 100 ms to 500 ms).

[0035] It is understandable that in the Wi-Fi coexistence scenario, through dynamic weight adjustment, the bit error rate of classic Bluetooth is reduced, and the average delay of interference response speed from interference detection to parameter adjustment is <5ms, which meets the real-time requirements, and reduces the RF activation time in BLE mode through adaptive adjustment of gradient scanning interval; through the closed-loop process of real-time interference capture → multi-dimensional analysis → timing modeling → dynamic parameter adjustment, this technology realizes precise interference response, classifies and identifies interference sources and adjusts strategies in a targeted manner, balances computing load and power consumption, adapts to embedded device limitations, and links dual-mode parameters to avoid internal conflicts and improve overall stability. This solution provides reliable anti-interference protection for dual-mode Bluetooth communications in complex wireless environments.

[0036] Specifically, in step S4 of the embodiment provided by the present invention, the RF module is activated to scan all available channels and collect quality indicators at fixed time windows (such as 100ms in classic mode and 500ms in BLE mode). The classic Bluetooth mode measures RSSI, BER, signal-to-noise ratio (SNR) and data packet transmission success rate (PDR). The BLE mode focuses on the receiving sensitivity and connection event success rate of the broadcast channel (37 / 38 / 39). The scoring rule uses a weighted formula to calculate the channel quality score (for example: Score = 0.4*RSSI + 0.3*(1-BER) + 0.3*PDR), and normalizes the score to a range of 0-1 (1 represents the best).

[0037] More specifically, dynamic parameters are injected into the decision framework, and real-time scores are input into the channel decision management framework. The classic mode (weight factor framework) updates the weight factors of each channel, triggers the weight sorting algorithm (such as quick sort), and generates the latest channel priority list. The BLE mode (priority gradient framework) re-divides the gradient according to the score. For example, if a channel score is >0.8 for three consecutive times, it is upgraded to a higher gradient. If the score is <0.3 for two consecutive times, it is downgraded or marked as "disabled". The updated gradient represents the channel selection logic.

[0038] More specifically, the channel selection directionality analysis and directionality rule generation include: the classic mode generates a channel hopping sequence based on a priority list (such as giving priority to polling the first five high-weight channels); the BLE mode generates a "primary-backup" channel switching strategy based on the gradient representing the channel quality (such as switching to backup channel 12 when the main channel 38 fails); the historical selection success rate (such as the effective proportion of the channel in the last 10 hops) is used as a confidence indicator; when the two modes coexist, the channels occupied by the other mode are marked to avoid internal interference (such as classic Bluetooth avoiding the BLE broadcast channel).

[0039] More specifically, channel selection reference features are generated. The output format in the classic mode is a dictionary of {channel ID: [weight, confidence, conflict flag]}, and the output format in the BLE mode is a hierarchical table of {gradient level: [representative channel ID, list of alternative channels, confidence]}.

[0040] It can be understood that through the closed-loop process of real-time monitoring → dynamic scoring → directional analysis → reference feature generation, this step combines real-time quality and historical confidence, optimizes the frequency hopping decision, dynamically responds to interference changes, balances performance and power consumption, maximizes the overall communication efficiency through conflict flags and resource sharing, and ultimately provides core decision support for the reliable communication of dual-mode Bluetooth in complex scenarios.

[0041] Specifically, in step S5 of the embodiment provided by the present invention, a dual-mode channel frequency band mapping table is established to identify the frequency band overlapping area (such as partial overlap between classic Bluetooth channel 6 and BLE channel 24). According to the channel selection reference features of the current mode (such as classic Bluetooth), predict the channels that may be affected in the other mode (such as BLE) (when a high-weight channel in classic Bluetooth overlaps with a BLE broadcast channel, it is marked as a potential conflict), and use linear regression or covariance analysis to quantify the correlation of the dual-mode channel quality (such as when the RSSI of classic channel A is high, the probability of the error rate increase of BLE channel B).

[0042] More specifically, based on the channel quality reference features of the current mode, predict the channel quality distribution of the target mode (such as switching from classic Bluetooth to BLE). If channel 6 (2402 MHz) has a high weight and no interference in the current classic mode, it is predicted that the quality of BLE channel 24 (2402 MHz) may be affected by the legacy signal, pre-load interference avoidance parameters (such as temporarily reducing the priority of the overlapping channel) for the channel decision framework of the target mode (such as the BLE priority gradient framework), and convert the reference features of the current mode into the frame input format of the target mode (such as mapping the classic mode weight to the BLE gradient level).

[0043] More specifically, if the dual-mode needs to run simultaneously (such as classic transmission + BLE broadcast), allocate channels according to the priority (such as classic mode preferentially uses non-overlapping channels). During the mode switching transition period, generate a joint priority list by integrating the dual-mode channel weights (such as classic channel weight × 0.7 + BLE gradient weight × 0.3). When the predicted value of the target mode channel quality is higher than the threshold (such as BLE channel score > 0.7) and the current mode channel quality decreases, trigger the mode switching, complete the radio frequency parameter reconfiguration within less than 1 frequency hopping period (such as 625 μs) to avoid communication interruption. After the switching, monitor the quality of the new channel in real time. If it does not meet the expectation, roll back or activate the alternative channel (such as enabling alternative channel 12 after the BLE switch to channel 15 fails), and use a hardware-accelerated frequency hopping sequence generator (such as an FSM state machine) to support nanosecond-level channel switching.

[0044] It is understandable that through the closed-loop process of cross-mode correlation analysis → preliminary feature generation → collaborative decision-making → rapid execution, this technology achieves minimizing communication interruption and guarantees the user experience. The dual-mode parameter linkage prevents conflicts and improves the adaptability to complex environments. Hardware acceleration and algorithm optimization reduce power consumption and extend the device's battery life. This solution provides key technical support for the reliable operation of the dual-mode Bluetooth chip in a dynamic wireless environment.

[0045] The present invention provides an adaptive frequency hopping method for a low-power dual-mode Bluetooth chip, which has the following beneficial effects: The present invention obtains the current Bluetooth mode and detects the channel quality of the communication environment to obtain the basic channel quality features to construct a channel decision management framework, detects the communication interference condition in real time to adjust the channel decision management framework to avoid interference, performs real-time channel quality monitoring and channel selection directivity analysis based on the adjusted channel decision management framework to obtain channel selection reference features, performs channel hopping decision preparation processing for mode conversion of another Bluetooth mode based on the channel selection reference features, and performs collaborative decision-making for channel hopping to drive the dual-mode Bluetooth chip to perform channel hopping processing. This method optimizes the channel selection and hopping strategy through an adaptive frequency hopping mechanism, and solves the problem that the fixed hopping mechanism in the prior art is difficult to meet the communication requirements of the dual-mode Bluetooth.

[0046] Preferably, the step of obtaining the Bluetooth mode currently operated by the dual-mode Bluetooth chip and detecting the channel quality of the communication environment where the dual-mode Bluetooth chip is currently located to obtain the basic channel quality features of the dual-mode Bluetooth chip includes: S11: Perform self-detection of the Bluetooth mode on the dual-mode Bluetooth chip to determine whether the Bluetooth mode currently operated by the dual-mode Bluetooth chip is the classic Bluetooth mode or the low-power Bluetooth mode; S12: Retrieve the corresponding set of available channels according to the Bluetooth mode currently operated by the dual-mode Bluetooth chip, and detect and analyze the received signal strength and signal error rate of several types of representative channels in the set of available channels through the channel quality detection mechanism pre-deployed in the dual-mode Bluetooth chip to obtain the channel quality indication vectors of each type of representative channel in the set of available channels; S13: Perform correlation extension prediction and overall distribution form expression of channel instructions for all channels in the set of available channels according to the channel quality indication vectors of each type of representative channel in the set of available channels to obtain the channel quality indication matrix of the set of available channels; S14: Perform vector clustering on the channel quality indication matrix to obtain the distribution of channel quality indication vector clusters, and based on the distribution of channel quality indication vector clusters, conduct feature analysis and combination of the dominant channels and the inferior channels of the dual-mode Bluetooth chip to obtain the basic channel quality features of the dual-mode Bluetooth chip.

[0047] Specifically, perform self-detection of the Bluetooth mode on the dual-mode Bluetooth chip to determine whether it is currently operating in the Classic Bluetooth mode or the Bluetooth Low Energy (BLE) mode. According to the current Bluetooth mode, retrieve the corresponding selectable channel set. Classic Bluetooth and Bluetooth Low Energy use different channel sets, so it is necessary to retrieve the corresponding channel set according to the specific mode. Through the channel quality detection mechanism deployed on the dual-mode Bluetooth chip, detect and analyze several types of representative channels in the selectable channel set. The main detection indicators include the Received Signal Strength Indicator (RSSI) and the Bit Error Rate (BER).

[0048] More specifically, after collecting these data, obtain the channel quality indication vectors of each type of representative channel. According to the channel quality indication vectors of each type of representative channel, conduct correlation expansion prediction and overall distribution form expression for all channels in the selectable channel set, and finally obtain the channel quality indication matrix of the selectable channel set.

[0049] More specifically, perform vector clustering on the channel quality indication matrix to obtain the distribution of channel quality indication vector clusters. This step can help identify the group characteristics and distribution rules of the channels. Based on the distribution of channel quality indication vector clusters, conduct feature analysis and combination of the dominant channels and the inferior channels of the dual-mode Bluetooth chip, and finally obtain the basic channel quality features of the dual-mode Bluetooth chip.

[0050] It can be understood that through self-detection and the channel quality detection mechanism, the current Bluetooth mode and its channel quality situation can be accurately identified, thus providing data support for communication optimization. Based on the channel quality indication matrix and the vector cluster distribution, the dominant channels can be effectively identified and selected, and the inferior channels can be avoided, improving the communication quality and stability. Through the analysis of the basic channel quality features, the channel usage strategy can be optimized, the overall communication performance can be improved, interference and data transmission errors can be reduced. This method can adaptively adjust in a dynamically changing communication environment and maintain good communication quality and efficiency. Generally speaking, this process can effectively improve the communication quality and reliability of the dual-mode Bluetooth chip in practical applications through accurate channel quality detection and analysis.

[0051] Preferably, the step of deploying the preliminary work parameters for chip hopping decision of the dual-mode Bluetooth chip according to the Bluetooth mode and the basic characteristics of the channel quality to construct a channel decision management framework includes: S211: When the Bluetooth mode is the classic Bluetooth mode, retrieve the set of selectable channels corresponding to the classic Bluetooth mode, and perform conversion processing of the selection unit on each channel in the set of selectable channels to obtain each selection unit corresponding one-to-one to each channel in the set of selectable channels; S212: Initially assign the priority selection weights to each of the selection units according to the basic characteristics of the channel quality to obtain the initial priority selection weights of each of the selection units, and perform priority sorting on each of the selection units according to the initial priority selection weights to obtain a priority selection sequence; S213: Use the channel corresponding to the selection unit ranked first in the priority selection sequence as the currently selected channel to drive the dual-mode Bluetooth chip to perform channel execution operations; S214: Simulate the conditions of communication interference influence and communication quality change influence on each of the selection units in the priority selection sequence, and generate communication interference weight factors and communication quality weight factors for each of the selection units in the priority selection sequence according to the results of the condition simulation to configure communication interference weight factors and communication quality weight factors for each of the selection units; S215: Perform weight association processing on the communication interference weight factors and communication quality weight factors configured for each of the selection units with respect to the initial priority selection weights, so that the initial priority selection weights of the selection units have a real-time correction mechanism that follows the weight adjustment of the communication interference weight factors and communication quality weight factors; S216: Based on the real-time correction mechanism of the initial priority selection weights of each of the selection units, construct a real-time adjustment mechanism for the arrangement order of the selection units in the priority selection sequence to obtain a channel decision management framework.

[0052] Specifically, when the Bluetooth mode is the classic Bluetooth mode, retrieve the set of selectable channels corresponding to this mode, perform conversion processing of the selection unit on each channel in the set of selectable channels, obtain the selection units corresponding one-to-one to each channel in the set of selectable channels, initially assign the priority selection weights to each of the selection units according to the basic characteristics of the channel quality, obtain the initial priority selection weights of each of the selection units, and perform priority sorting on each of the selection units according to the initial priority selection weights to obtain a priority selection sequence.

[0053] More specifically, the channel corresponding to the selection unit ranked first in the priority selection sequence is preferentially selected as the currently selected channel to drive the dual-mode Bluetooth chip to perform channel execution operations. The situation simulation of the communication interference impact and the communication quality change impact is carried out for each selection unit in the priority selection sequence. According to the results of the situation simulation, a communication interference weight factor and a communication quality weight factor are generated, and these factors are configured for each selection unit.

[0054] More specifically, the weight correlation processing of the communication interference weight factor and the communication quality weight factor configured for each selection unit is carried out with the initial priority selection weight. Through this processing, the initial priority selection weight of the selection unit has a real-time correction mechanism that follows the communication interference weight factor and the communication quality weight factor for weight adjustment. Based on the real-time correction mechanism of the initial priority selection weight of each selection unit, the framework of the real-time adjustment mechanism of the selection unit arrangement order in the priority selection sequence is constructed, and finally, a channel decision management framework is obtained.

[0055] It can be understood that by adjusting the channel selection strategy in real time, according to the current channel quality and communication interference situation, dynamically optimizing the channel selection, improving the communication quality and stability, through the real-time correction mechanism of the communication interference weight factor and the communication quality weight factor, an adaptive channel decision mechanism is formed to ensure that the best channel can be selected in different communication environments. By optimizing and adjusting the priority selection weight in real time, the retransmission and error codes caused by channel interference and poor quality are reduced, and the overall communication efficiency is improved. The channel decision management framework enables the dual-mode Bluetooth chip to still work stably in a complex and changeable communication environment, enhancing the system robustness, by comprehensively considering various influencing factors (such as channel quality, interference situation), and improves the accuracy and rationality of channel selection by finely analyzing the basic characteristics of the channel quality and carefully managing the selection units.

[0056] Preferably, the steps of deploying the preliminary work parameters for the chip hopping decision of the dual-mode Bluetooth chip according to the Bluetooth mode and the basic characteristics of the channel quality to construct a channel decision management framework include: S221: When the Bluetooth mode is the low-power Bluetooth mode, retrieve the set of available channels corresponding to the low-power Bluetooth mode, and perform conversion processing of the selection unit for each channel in the set of available channels to obtain each selection unit corresponding one-to-one to each channel in the set of available channels; S222: Allocate the priority gradient to each of the selection units according to the basic characteristics of the channel quality, so as to allocate each channel in the set of available channels into several priority gradients with a priority relationship; S223: Analyze the signals included in each of the priority gradients separately with different amplitudes to obtain the intra-gradient difference feature distribution and the inter-gradient interaction difference feature distribution of each of the priority gradients. Based on the intra-gradient difference feature distribution and the inter-gradient interaction difference feature distribution, select the gradient representative channels for each of the priority gradients to obtain the representative channels of each priority gradient, and use the gradient representative channel of the highest-priority gradient as the currently selected channel to drive the dual-mode Bluetooth chip to perform channel execution operations; S224: Simulate the communication interference impact and communication quality impact on the representative channels of each priority gradient, and deploy the calculation method of the gradient preference index for each of the representative channels according to the simulation results to obtain the gradient preference methods of each of the representative channels; S225: Configure the parameters of the gradient replacement execution conditions for each of the priority gradients based on the gradient preference methods of each of the representative channels, set the gradient priority replacement criteria for each of the priority gradients, and form a priority gradient decision framework through each priority gradient with a gradient preference method and a gradient priority replacement criterion.

[0057] Specifically, when the Bluetooth mode is the low-power Bluetooth mode, retrieve the set of selectable channels corresponding to the classic Bluetooth mode, perform conversion processing on each channel in the set of selectable channels through a selection unit to obtain a selection unit corresponding to each channel in the set of selectable channels, allocate priority gradients to each selection unit according to the basic characteristics of the channel quality, allocate each channel in the set of selectable channels into several priority gradients with a priority relationship, and analyze the signals included in each of the priority gradients separately with different amplitudes to obtain the intra-gradient difference feature distribution and the inter-gradient interaction difference feature distribution of each of the priority gradients.

[0058] More specifically, based on the intra-gradient difference feature distribution and the inter-gradient interaction difference feature distribution, select the gradient representative channels for each of the priority gradients to obtain the representative channels of each priority gradient, and use the gradient representative channel of the highest-priority gradient as the currently selected channel to drive the dual-mode Bluetooth chip to perform channel execution operations.

[0059] More specifically, simulate the communication interference impact and communication quality impact on the representative channels of each priority gradient, deploy the calculation method of the gradient preference index for each of the representative channels according to the simulation results to obtain the gradient preference methods of each of the representative channels, configure the parameters of the gradient replacement execution conditions for each of the priority gradients based on the gradient preference methods of each of the representative channels, set the gradient priority replacement criteria for each of the priority gradients, and form a priority gradient decision framework through each priority gradient with a gradient preference method and a gradient priority replacement criterion.

[0060] It is understandable that through the priority gradient allocation and the selection of gradient representative channels, the channel selection strategy is dynamically optimized according to the channel quality and interference situation, so as to improve the communication quality and stability. By analyzing the differential amplitude of the channels and the distribution of internal and interactive differential features of the gradients, the accuracy of the channel selection decision is improved. Through the simulation of the impact of communication interference and the impact of communication quality, the channel selection strategy is adjusted in real time, enabling the system to dynamically adapt to environmental changes. Based on the gradient preference index and the gradient priority replacement standard, a flexible and adaptive channel decision management framework is constructed, enhancing the robustness of the system in complex communication environments.

[0061] Preferably, the steps of real-time detecting the communication interference situation of the dual-mode Bluetooth chip, performing time-series correlation analysis on the communication interference situation of the dual-mode Bluetooth chip at each moment, and adjusting the parameters of interference avoidance for the channel decision management framework according to the analysis results include: S31: Sampling and analyzing the I / Q signals of the interference detection signal with a predetermined time resolution through the RF front-end ADC module pre-deployed in the dual-mode Bluetooth chip to capture the instantaneous interference waveform; S32: Performing multi-dimensional time-domain index analysis of packet error rate, signal strength, and signal occupancy time ratio on the instantaneous interference waveform to obtain time-domain interference characteristics; S33: Performing channel spectrum energy distribution analysis on the instantaneous interference waveform through FFT calculation, and performing signal interference mode analysis on the signal environment based on the analysis results to obtain frequency-domain interference characteristics; S34: Performing time-series arrangement and high-dimensional feature extraction on the time-domain interference characteristics and the frequency-domain interference characteristics at each moment to obtain interference event time-series characteristics; S35: Analyzing the type similarity of the interference event time-series characteristics according to the historical reference database to obtain the time-series characteristic similarity between the interference event time-series characteristics and several interference event types in the historical reference database; S36: Performing interference event traceability and location analysis on the dual-mode Bluetooth chip according to the time-series characteristic similarity between the interference event time-series characteristics and various interference event types in the historical reference database to obtain interference event traceability and location information composed of interference event type information, interference event specification information, and interference event fluctuation information; S37: Performing corresponding-form decision influence analysis on the weight factor decision framework or the priority gradient decision framework according to the interference event traceability and location information, and performing parameter corresponding configuration of priority elements on the weight factor decision framework or the priority gradient decision framework according to the decision influence analysis result to achieve interference avoidance of the weight factor decision framework or the priority gradient decision framework.

[0062] Specifically, a radio frequency front-end ADC module is deployed in the dual-mode Bluetooth chip to sample the I / Q (in-phase and quadrature) signals of the interference detection signal at a time resolution of a predetermined specification. Through the I / Q signal sampling, instantaneous interference waveforms can be captured, and these waveforms can reflect the intensity, frequency, and time-domain characteristics of the interference. The sampling with high time resolution can accurately record the occurrence and duration of interference events, facilitating subsequent analysis.

[0063] More specifically, multi-dimensional time-domain index analysis of packet error rate (PER), received signal strength indicator (RSSI), and duty cycle of the captured instantaneous interference waveforms is performed. The packet error rate can directly reflect the error rate in the communication process and reveal the severity of the interference. The received signal strength analysis helps to judge the strength of the interference, and the duty cycle analysis can understand the duration and frequency of the interference.

[0064] More specifically, channel spectrum energy distribution analysis of the instantaneous interference waveforms is performed through fast Fourier transform (FFT). The FFT analysis can convert the time-domain signal to the frequency domain, facilitating the identification of the frequency components and spectrum characteristics of the interference. The frequency-domain analysis helps to determine the frequency range of the interference and its distribution in the spectrum, facilitating the understanding of the nature and source of the interference.

[0065] More specifically, the time-domain interference characteristics and frequency-domain interference characteristics at each moment are arranged in sequence for high-dimensional feature extraction to form the time-sequence characteristics of the interference event. The sequential arrangement can reveal the occurrence pattern and rules of the interference event, and the high-dimensional feature extraction can integrate multi-dimensional information to form a more comprehensive and accurate description of the interference characteristics.

[0066] More specifically, according to the historical reference database, type similarity analysis of the time-sequence characteristics of the interference event is performed. By using the interference event characteristics in the historical database, the type of the current interference event can be identified through similarity analysis. The similarity analysis helps to predict the possible source and future trend of the interference.

[0067] More specifically, according to the similarity of the time-sequence characteristics between the interference event time-sequence characteristics and the time-sequence characteristics of the interference event types in the historical reference database, source tracing and location analysis of the interference event is performed. The source tracing and location analysis can identify the specific source, nature, and change trend of the interference, and this information is crucial for formulating effective interference avoidance strategies.

[0068] It is understandable that, based on the interference event traceability and positioning information, a decision impact analysis is performed on the weight factor decision framework or the priority gradient decision framework. According to the analysis results, the parameter configuration of the priority elements in the decision framework is adjusted. The adjustment of the decision framework can optimize the channel selection and communication strategy to avoid interference. The weight factor decision framework and the priority gradient decision framework can be dynamically adjusted according to different interference situations to ensure the stability and reliability of communication. Through these steps, the dual-mode Bluetooth chip can monitor and analyze the interference situation in real time and dynamically adjust the communication strategy according to the analysis results to effectively avoid interference and improve the communication quality and reliability.

[0069] Preferably, the steps of performing real-time channel quality monitoring and channel selection directivity analysis on the communication environment where the dual-mode Bluetooth chip is located according to the channel decision management framework after parameter adjustment for interference avoidance to obtain the channel selection reference characteristics include: S41: Collect and evaluate the communication quality of each specified channel corresponding to the current channel decision management framework for the dual-mode Bluetooth chip at a predetermined time interval to obtain the communication quality scores of each specified channel; S42: Substitute the communication quality scores of each specified channel into the channel decision management framework, and let the channel decision management framework perform adaptive parameter adjustment on the communication quality scores of each specified channel according to the framework decision mechanism that conforms to the channel decision management framework to obtain the channel priority distribution information after the channel decision management framework has undergone adaptive parameter adjustment; S43: According to the priority relationship of each channel reflected by the channel decision management framework for the channel priority distribution information, express the pointing information for adjusting the channel priority order to obtain the pointing information for adjusting the channel priority order of each channel; S44: Analyze the channel quality correlation characteristics of each channel through the channel decision management framework, and perform an analysis of the adjustment tendency conformity on the pointing information for adjusting the channel priority order of each channel based on the analysis results to obtain the adjustment tendency conformity between each channel. Assign a confidence index to the pointing information for adjusting the channel priority order of each channel through the adjustment tendency conformity between each channel; S45: According to the pointing information for adjusting the channel priority order and the confidence index corresponding to each channel, perform adjustment processing and overall combination on the existing priority order of each channel to obtain the channel selection reference characteristics.

[0070] Specifically, set an appropriate time interval (such as every second or every minute) to collect the communication quality of each specified channel currently used by the dual-mode Bluetooth chip, including but not limited to signal strength (RSSI), packet error rate (PER), latency, throughput, etc. Use a predetermined algorithm to evaluate the collected communication quality data to obtain the communication quality score of each channel, ensure the acquisition of the latest communication quality status within the predetermined time interval, collect multi-dimensional communication quality indicators, and ensure the accuracy and integrity of the evaluation results.

[0071] More specifically, substitute the communication quality scores of each specified channel into the channel decision management framework. The channel decision management framework adaptively adjusts parameters according to the current communication quality scores to optimize the decision-making mechanism. The channel decision management framework can dynamically adjust parameters based on the communication quality scores obtained in real time, improve the adaptability to environmental changes, and optimize the channel priority distribution through adaptive adjustment, enhancing the rationality and effectiveness of channel selection.

[0072] More specifically, after the adaptive parameter adjustment, the channel decision management framework generates the priority distribution information of each channel. According to the priority distribution information, adjust the priority order of each channel to form the priority order adjustment pointing information, clarify the priority of each channel, facilitate subsequent channel selection, and can dynamically adjust the channel priority according to real-time communication quality data to optimize the communication performance.

[0073] More specifically, based on the channel decision management framework, analyze the correlation characteristics of the channel quality of each channel. According to the analysis results, conduct an analysis of the adjustment tendency compliance of the priority order adjustment pointing information to evaluate the rationality of the adjustment. By analyzing the correlation characteristics of the channel quality, clarify the mutual influence relationship between each channel. Through the analysis of the adjustment tendency compliance, ensure the rationality and scientificity of the channel priority adjustment.

[0074] More specifically, according to the adjustment tendency compliance between each channel, assign a confidence index to the priority order adjustment pointing information of each channel, provide a confidence index for the channel priority order adjustment, evaluate the credibility of the adjustment result, and improve the reliability and accuracy of the channel selection decision.

[0075] More specifically, according to the priority order adjustment pointing information and confidence index corresponding to each channel, comprehensively adjust the existing priority order. Combine the adjusted priority order and confidence index to generate channel selection reference features. By overall combining the priority order and confidence index of different channels, optimize the channel selection strategy, generate reliable channel selection reference features, guide the actual channel selection operation, improve the communication efficiency and stability. Through the above steps, the dual-mode Bluetooth chip can achieve real-time channel quality monitoring and channel selection directional analysis in a complex communication environment, ensuring the stability and efficiency of communication.

[0076] Preferably, the step of performing channel hopping decision preparation processing on another Bluetooth mode based on the channel selection reference feature to obtain a mode conversion preparation feature, and making a collaborative decision on channel hopping for the channel selection reference feature according to the mode conversion preparation feature to drive the dual-mode Bluetooth chip to perform channel hopping processing includes: S51: Retrieve the selectable channel sets of the classic Bluetooth mode and the low-power Bluetooth mode, and perform channel quality correlation characteristic analysis on the selectable channel set of the classic Bluetooth mode and the selectable channel set of the low-power Bluetooth mode to obtain the channel quality correlation characteristic distribution of the selectable channel set of the classic Bluetooth mode and the selectable channel set of the low-power Bluetooth mode; S52: Perform information conversion on the channel selection reference feature according to the channel quality correlation characteristic distribution to obtain the predicted deployment status information of the selectable channel set of another Bluetooth mode, and perform label assignment and information integration of the frame position on the predicted deployment status information according to the frame construction form of the channel decision management framework corresponding to another Bluetooth mode to obtain a mode conversion preparation feature; S53: Perform the first-round adjustment of the channel priority relationship on the channel decision management framework according to the channel selection reference feature to obtain the frame management mode of the channel decision management framework after the priority relationship adjustment; S54: Perform spatio-temporal state simulation of the channel environment on the mode conversion preparation feature according to a pre-trained neural network model to obtain a spatio-temporal simulation map of the channel environment quality, and perform feasibility verification on the frame management mode based on the spatio-temporal simulation map of the channel environment quality to obtain the feasibility verification feature of the management framework mode; S55: Perform a correction tendency analysis on the channel configuration position of the management framework mode based on the feasibility verification feature, and perform an equilibrium analysis on the correction tendency of the channel configuration position of each channel under the management framework mode to perform parameter configuration for the specific execution of the correction tendency of the channel configuration position of each channel to obtain a collaborative decision on channel frequency modulation; S56: Drive the dual-mode Bluetooth chip to perform channel hopping processing according to the collaborative decision.

[0077] Specifically, retrieve the selectable channel sets of the classic Bluetooth mode and the low-power Bluetooth mode, perform channel quality correlation characteristic analysis on the selectable channel set of the classic Bluetooth mode and the selectable channel set of the low-power Bluetooth mode, and through the analysis, obtain the channel quality correlation characteristic distribution of the classic Bluetooth mode and the low-power Bluetooth mode.

[0078] More specifically, based on the channel quality correlation characteristic distribution, the channel selection reference features are transformed into the predicted deployment status information of the selectable channel set of another Bluetooth mode. According to the channel decision management framework of another Bluetooth mode, label assignment and information integration are performed on the predicted deployment status information to obtain the mode conversion preparation features.

[0079] More specifically, according to the channel selection reference features, the first-round adjustment of the channel priority relationship of the channel decision management framework is performed to obtain the framework management mode of the channel decision management framework after the priority relationship adjustment. The pre-trained neural network model is used to simulate the spatio-temporal state of the channel environment for the mode conversion preparation features, and the spatio-temporal simulation map of the channel environment quality is obtained. Based on the spatio-temporal simulation map, the feasibility verification of the framework management mode is performed to obtain the feasibility verification features of the management framework mode. According to the feasibility verification features, the correction tendency analysis of the channel configuration position of the management framework mode is performed, and the balance analysis of the channel configuration position correction tendency of each channel under the management framework mode is performed. The specific execution parameter configuration is formulated to form the collaborative decision of channel frequency modulation. According to the collaborative decision, the dual-mode Bluetooth chip is driven to perform channel hopping processing to realize the optimized channel selection and hopping mechanism.

[0080] It can be understood that by analyzing and making collaborative decisions on the channel quality correlation characteristic distribution of the classic Bluetooth and low-power Bluetooth modes, the channel utilization efficiency is improved, interference and conflicts are reduced. Based on the spatio-temporal simulation and feasibility verification of the channel environment quality, the scientificity and rationality of the channel selection and hopping decisions are ensured, the stability and reliability of the Bluetooth connection are improved. By optimizing the channel selection and hopping strategies, unnecessary channel switching and reconnection times are reduced, thereby reducing the power consumption of the dual-mode Bluetooth device and prolonging the battery life of the device.

[0081] In a second aspect, the present invention provides an adaptive frequency hopping device for a low-power dual-mode Bluetooth chip, which is used to implement the adaptive frequency hopping method for a low-power dual-mode Bluetooth chip described in any one of the first aspects.

[0082] In a third aspect, the present invention provides a computer device, including a memory and a processor. The memory stores a computer program that can run on the processor, and when the processor executes the computer program, it implements the adaptive frequency hopping method for a low-power dual-mode Bluetooth chip described in any one of the first aspects.

[0083] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An adaptive frequency hopping method for a low-power dual-mode Bluetooth chip, characterized in that Including: Obtain the Bluetooth mode currently running on the dual-mode Bluetooth chip, and detect the channel quality of the communication environment where the dual-mode Bluetooth chip is currently located, so as to obtain the basic channel quality characteristics of the dual-mode Bluetooth chip; wherein, the Bluetooth mode includes the classic Bluetooth mode and the low-power Bluetooth mode; Deploy the preliminary work parameters for chip hopping decision-making of the dual-mode Bluetooth chip according to the Bluetooth mode and the basic channel quality characteristics, so as to construct a channel decision management framework; wherein, the channel decision management framework includes a weight factor decision framework corresponding to the classic Bluetooth mode and a priority gradient decision framework corresponding to the low-power Bluetooth mode; Real-time detect the communication interference status of the dual-mode Bluetooth chip, perform time-series correlation analysis on the communication interference status of the dual-mode Bluetooth chip at each moment, and adjust the parameters for interference avoidance of the channel decision management framework according to the analysis results; Perform real-time channel quality monitoring and channel selection directivity analysis on the communication environment where the dual-mode Bluetooth chip is located according to the channel decision management framework after the interference avoidance parameter adjustment, and obtain the channel selection reference characteristics; Perform preliminary processing of channel hopping decision for mode conversion of another Bluetooth mode based on the channel selection reference characteristics, obtain the preliminary mode conversion characteristics, and perform collaborative decision-making of channel hopping on the channel selection reference characteristics according to the preliminary mode conversion characteristics, so as to drive the dual-mode Bluetooth chip to perform channel hopping processing.

2. The adaptive frequency hopping method of the low-power dual-mode Bluetooth chip according to claim 1, wherein, The steps of obtaining the Bluetooth mode currently running on the dual-mode Bluetooth chip and detecting the channel quality of the communication environment where the dual-mode Bluetooth chip is currently located, so as to obtain the basic channel quality characteristics of the dual-mode Bluetooth chip include: Perform self-detection of the Bluetooth mode on the dual-mode Bluetooth chip to determine that the Bluetooth mode currently running on the dual-mode Bluetooth chip is the classic Bluetooth mode or the low-power Bluetooth mode; Retrieve the corresponding set of selectable channels according to the Bluetooth mode currently running on the dual-mode Bluetooth chip, and detect and analyze the received signal strength and signal error rate of several types of representative channels in the set of selectable channels through the channel quality detection mechanism pre-deployed on the dual-mode Bluetooth chip, so as to obtain the channel quality indication vectors of each type of representative channel in the set of selectable channels; Perform correlation extension prediction of channel commands and overall distribution form expression on all channels in the set of selectable channels according to the channel quality indication vectors of each type of representative channel in the set of selectable channels, so as to obtain the channel quality indication matrix of the set of selectable channels; Perform vector clustering on the channel quality indication matrix to obtain the distribution of channel quality indication vector clusters, and perform characteristic analysis and combination of the dominant channels and inferior channels on the dual-mode Bluetooth chip based on the distribution of channel quality indication vector clusters, so as to obtain the basic channel quality characteristics of the dual-mode Bluetooth chip.

3. The adaptive frequency hopping method of the low-power dual-mode Bluetooth chip according to claim 1, characterized in that The steps of deploying the preliminary work parameters for chip hopping decision-making of the dual-mode Bluetooth chip according to the Bluetooth mode and the basic channel quality characteristics, so as to construct a channel decision management framework include: When the Bluetooth mode is the classic Bluetooth mode, retrieve the set of selectable channels corresponding to the classic Bluetooth mode, and perform conversion processing of the selection unit on each channel in the set of selectable channels to obtain each selection unit corresponding one-to-one to each channel in the set of selectable channels; Based on the basic channel quality characteristics, initially assign the priority selection weights to each of the selection units to obtain the initial priority selection weights of each of the selection units, and perform priority sorting on each of the selection units according to the initial priority selection weights to obtain a priority selection sequence; Use the channel corresponding to the selection unit ranked first in the priority selection sequence as the currently selected channel to drive the dual-mode Bluetooth chip to perform channel execution operations; Simulate the situation of communication interference influence and communication quality change influence on each of the selection units in the priority selection sequence, and generate a communication interference weight factor and a communication quality weight factor for each of the selection units in the priority selection sequence according to the results of the situation simulation, so as to configure a communication interference weight factor and a communication quality weight factor for each of the selection units; Perform weight association processing on the communication interference weight factor and the communication quality weight factor configured for each of the selection units with respect to the initial priority selection weight, so that the initial priority selection weight of the selection unit has a real-time correction mechanism that follows the weight adjustment of the communication interference weight factor and the communication quality weight factor; Based on the real-time correction mechanism of the initial priority selection weight of each of the selection units, construct a real-time adjustment mechanism for the arrangement order of the selection units in the priority selection sequence to obtain a channel decision management framework.

4. The adaptive frequency hopping method of the low-power dual-mode Bluetooth chip according to claim 1, characterized in that, The steps of deploying the preliminary work parameters for the chip frequency hopping decision of the dual-mode Bluetooth chip according to the Bluetooth mode and the basic channel quality characteristics to construct a channel decision management framework include: When the Bluetooth mode is the low-power Bluetooth mode, retrieve the set of selectable channels corresponding to the low-power Bluetooth mode, and perform conversion processing of the selection unit on each channel in the set of selectable channels to obtain each selection unit corresponding one-to-one to each channel in the set of selectable channels; Allocate priority gradients to each of the selection units according to the basic channel quality characteristics, so as to allocate each channel in the set of selectable channels into several priority gradients with priority relationships; Analyze the differential amplitudes of each signal included in each of the priority gradients to obtain the gradient internal difference feature distribution and the gradient interaction difference feature distribution of each of the priority gradients. Based on the gradient internal difference feature distribution and the gradient interaction difference feature distribution, select the representative channel of each of the priority gradients to obtain the representative channel of each priority gradient, and use the gradient representative channel of the highest priority gradient as the currently selected channel to drive the dual-mode Bluetooth chip to perform channel execution operations; Simulate the situation of communication interference impact and communication quality impact on the representative channels of each priority gradient, and deploy the calculation method of the gradient preference index for each of the representative channels according to the results of the situation simulation, so as to obtain the gradient preference method for each of the representative channels; Configure the parameters of the gradient replacement execution condition for each of the priority gradients based on the gradient preference method of each of the representative channels, so as to set the gradient priority replacement standard for each of the priority gradients, and form a priority gradient decision framework through each priority gradient with the gradient preference method and the gradient priority replacement standard.

5. The adaptive frequency hopping method of the low-power dual-mode Bluetooth chip according to claim 1, characterized in that The steps of real-time detecting the communication interference situation of the dual-mode Bluetooth chip, performing time-series correlation analysis on the communication interference situation of the dual-mode Bluetooth chip at each moment, and adjusting the parameters of interference avoidance for the channel decision management framework according to the analysis results include: Sampling and analyzing the I / Q signals of the interference detection signal with a predetermined specification of time resolution through the radio frequency front-end ADC module pre-deployed in the dual-mode Bluetooth chip to capture the instantaneous interference waveform; Perform multi-dimensional time-domain index analysis of packet error rate, signal strength, and signal occupancy time ratio on the instantaneous interference waveform to obtain time-domain interference characteristics; Perform channel spectrum energy distribution analysis on the instantaneous interference waveform through FFT calculation, and perform signal interference mode analysis on the signal environment based on the analysis results to obtain frequency-domain interference characteristics; Perform time-series arrangement and high-dimensional feature extraction on the time-domain interference characteristics and the frequency-domain interference characteristics at each moment to obtain interference event time-series characteristics; Analyze the type similarity of the interference event time-series characteristics according to the historical reference database to obtain the time-series characteristic similarity between the interference event time-series characteristics and several interference event types in the historical reference database; Perform interference event traceability and location analysis on the dual-mode Bluetooth chip according to the time-series characteristic similarity between the interference event time-series characteristics and various interference event types in the historical reference database to obtain interference event traceability and location information composed of interference event type information, interference event specification information, and interference event fluctuation information; Perform decision influence analysis of the corresponding form on the weight factor decision framework or the priority gradient decision framework according to the interference event traceability and location information, and perform parameter corresponding configuration of the priority elements on the weight factor decision framework or the priority gradient decision framework according to the decision influence analysis results, so as to achieve interference avoidance of the weight factor decision framework or the priority gradient decision framework.

6. The adaptive frequency hopping method of the low-power dual-mode Bluetooth chip according to claim 1, characterized in that, The steps of performing real-time channel quality monitoring and channel selection directivity analysis on the communication environment where the dual-mode Bluetooth chip is located according to the channel decision management framework after the parameter adjustment of interference avoidance to obtain channel selection reference characteristics include: Collect and evaluate the communication quality of each specified channel corresponding to the current channel decision management framework for the dual-mode Bluetooth chip at a predetermined interval to obtain the communication quality score of each specified channel; Substitute the communication quality scores of each of the specified channels into the channel decision management framework, and let the channel decision management framework perform adaptive parameter adjustment on the communication quality scores of each of the specified channels according to the framework decision mechanism of the channel decision management framework, so as to obtain the channel priority distribution information of the channel decision management framework after adaptive parameter adjustment; According to the indication information expression of the priority relationship of each channel fed back by the channel decision management framework for the channel priority distribution information, so as to obtain the priority order adjustment indication information of each channel; Analyze the channel quality correlation characteristics of each channel through the channel decision management framework, and perform an analysis of the adjustment tendency compliance on the priority order adjustment indication information of each channel based on the analysis results, so as to obtain the adjustment tendency compliance between each channel, and assign a confidence index to the priority order adjustment indication information of each channel through the adjustment tendency compliance between each channel; According to the priority order adjustment indication information and the confidence index corresponding to each channel, perform adjustment processing and overall combination on the existing priority order of each channel to obtain the channel selection reference characteristics.

7. The adaptive frequency hopping method for the low-power dual-mode Bluetooth chip according to claim 1, characterized in that, Based on the channel selection reference characteristics, perform preprocessing for channel hopping decision-making for mode conversion of another Bluetooth mode to obtain mode conversion preprocessing characteristics, and perform collaborative decision-making for channel hopping on the channel selection reference characteristics according to the mode conversion preprocessing characteristics, so as to drive the dual-mode Bluetooth chip to perform channel hopping processing. The steps include: Retrieve the selectable channel sets of the classic Bluetooth mode and the low-power Bluetooth mode, and perform an analysis of the channel quality correlation characteristics of the selectable channel set of the classic Bluetooth mode and the selectable channel set of the low-power Bluetooth mode, so as to obtain the channel quality correlation characteristic distribution of the selectable channel set of the classic Bluetooth mode and the selectable channel set of the low-power Bluetooth mode; Convert the channel selection reference characteristics according to the channel quality correlation characteristic distribution to obtain the predicted deployment status information of the selectable channel set of another Bluetooth mode, and perform label assignment and information integration of the frame position on the predicted deployment status information according to the frame construction form of the channel decision management framework corresponding to another Bluetooth mode to obtain mode conversion preprocessing characteristics; Perform the first round of channel priority relationship adjustment on the channel decision management framework according to the channel selection reference characteristics, so as to obtain the framework management mode of the channel decision management framework after the priority relationship adjustment; Simulate the spatio-temporal state of the channel environment for the mode conversion preprocessing characteristics according to the pre-trained neural network model to obtain the spatio-temporal simulation map of the channel environment quality, and perform a feasibility verification on the framework management mode based on the spatio-temporal simulation map of the channel environment quality to obtain the feasibility verification characteristics of the framework management mode; Based on the feasibility verification feature, perform a correction tendency analysis on the channel configuration position of the management framework mode, and perform a balance analysis on the correction tendency of the channel configuration positions of each channel under the management framework mode, so as to perform parameter configuration for the specific execution of the correction tendency of the channel configuration positions of each channel, and obtain a collaborative decision for channel frequency modulation; Drive the dual-mode Bluetooth chip to perform channel hopping processing according to the collaborative decision.

8. An adaptive frequency hopping device for a low-power dual-mode Bluetooth chip, characterized in that, A method for adaptive frequency hopping of a low-power dual-mode Bluetooth chip according to any one of claims 1-7.

9. A computer device, comprising a memory and a processor, the memory storing a computer program that can run on the processor, characterized in that, When the processor executes the computer program, it implements a method for adaptive frequency hopping of a low-power dual-mode Bluetooth chip according to any one of claims 1-7.

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