Data transmission optimization method for low-power-consumption Bluetooth equipment
By collecting key parameters to generate a set of candidate communication parameters, performing constraint verification and utility evaluation, and dynamically adjusting the transmission power and connection interval, the problem of power consumption and transmission efficiency imbalance of Bluetooth Low Energy devices in dynamic environments is solved, achieving high efficiency, reliability and low power consumption for real-time data transmission.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ZHENGZHOU JIACHEN ELECTRIC CO LTD
- Filing Date
- 2026-02-11
- Publication Date
- 2026-05-15
AI Technical Summary
Existing Bluetooth Low Energy devices cannot intelligently balance power consumption and transmission efficiency in dynamic environments, resulting in weak signals, high bit error rates, and a surge in data latency, which cannot meet the needs of near real-time applications.
By collecting key parameters, a set of candidate communication parameters is generated, and constraint verification and utility evaluation are performed. Transmission power and connection interval are dynamically adjusted to achieve the best balance between power consumption and transmission efficiency.
It enables real-time parameter adjustment of Bluetooth devices in dynamic environments, ensuring the timeliness and reliability of data transmission while minimizing device power consumption, achieving an intelligent balance between power consumption and transmission efficiency.
Smart Images
Figure CN122054112A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of low-power Bluetooth data transmission technology, and particularly relates to a data transmission optimization method for low-power Bluetooth devices. Background Technology
[0002] Currently, Bluetooth Low Energy (BLE) technology is widely used in the Internet of Things (IoT) field, with its core advantage being low power consumption. Devices typically achieve this through static configurations such as reducing transmit power and extending connection intervals. However, this static configuration has inherent drawbacks: when devices are in complex and changing wireless environments (such as those with obstructions or signal interference) or face dynamically changing application data traffic (such as sudden large data bursts), a fixed low-power mode severely sacrifices the timeliness and reliability of data transmission. Specifically, excessively low power consumption leads to weak signals and high bit error rates, with retransmissions for error correction actually increasing total power consumption; excessively long connection intervals result in a surge in data latency, failing to meet the demands of near-real-time applications. Therefore, current technology cannot intelligently balance power consumption and transmission efficiency in dynamic environments, either sacrificing battery life for performance or vice versa. This invention aims to solve the technical problem of how Bluetooth devices can autonomously and in real-time adjust communication parameters in dynamic environments to achieve the optimal balance between low power consumption and high transmission efficiency.
[0003] The prior art, with application number CN202411652397.2 and titled "Method and System for Reducing Packet Loss and Improving Transmission Efficiency in Bluetooth Low Energy Transmission," discloses a method and system for reducing packet loss and improving transmission efficiency in Bluetooth Low Energy transmission. This method adaptively updates the Bluetooth device's connection parameters by calculating the size of bytes to be sent each time, the number of transmissions, and the interval between each transmission based on the current status of the Bluetooth Low Energy peripheral device. However, this technical solution only addresses packet loss and transmission efficiency in fixed scenarios. It adjusts the central device's transmission parameters based on feedback from the peripheral device, resulting in a single-dimensional parameter adjustment that does not consider the multi-objective balance of transmission efficiency, power consumption, and latency. Summary of the Invention
[0004] The purpose of this invention is to provide a data transmission optimization method for low-power Bluetooth devices, which can solve the shortcomings of existing Bluetooth devices that use static parameter strategies and cannot adapt to dynamic environments.
[0005] The present invention provides a data transmission optimization method for a low-power Bluetooth device, which adopts the following technical solution and includes the following steps:
[0006] S1: Collect key parameters of the data transmission link of the Bluetooth Low Energy device in the current state. Key parameters include link quality indicators, application requirement indicators, and communication parameters of the Bluetooth Low Energy device.
[0007] S2: Based on the communication parameters of the low-power Bluetooth device in the key parameters of the current state, periodically generate a set of candidate parameters containing several sets of candidate communication parameters.
[0008] S3: In each decision cycle, evaluate the utility of candidate communication parameter combinations after constraint verification in the candidate parameter set to obtain the corresponding energy efficiency utility value. After comparing the values, obtain the maximum energy efficiency utility value. The candidate communication parameter combination corresponding to the maximum energy efficiency utility value is the optimal parameter combination.
[0009] S4: The utility improvement value obtained by comparing the maximum energy efficiency utility value with the energy efficiency utility value under the current state is used to determine whether to update the parameters, based on a set threshold.
[0010] If the set conditions are met, the current communication parameters will be updated to the optimal parameter combination, and the maximum energy efficiency utility value will be used as the utility comparison benchmark for the next decision cycle.
[0011] If the set conditions are not met, the current communication parameters will remain unchanged, and the process will proceed to the next decision cycle.
[0012] Furthermore, the communication parameters in S1 include the transmit power and connection interval of the Bluetooth Low Energy device; the link quality index is represented by the packet error rate; and the application requirement index includes the maximum transmission delay allowed by the application.
[0013] Furthermore, S2 uses gradient direction probing or random perturbation to generate a set of candidate parameters.
[0014] Furthermore, S3 performs constraint verification and utility evaluation on each combination of candidate communication parameters in the candidate parameter set.
[0015] S301: Predict the power consumption and transmission performance of all candidate communication parameter combinations in the candidate parameter set;
[0016] S302: Based on the application requirement indicators obtained in S1, obtain the candidate communication parameter combinations that meet the application requirement indicators in the transmission performance indicators;
[0017] S303: Calculate candidate communication parameter combinations that meet application requirements based on power consumption and transmission performance metrics. The energy efficiency value.
[0018] Furthermore, S301 predicts the power consumption index of candidate communication parameter combinations by establishing a power consumption prediction model. The power consumption index is represented by average current power consumption, and the average current power consumption is predicted based on the transmit power and connection interval of the low power Bluetooth device and the power consumption model coefficients.
[0019] Furthermore, S301 predicts the transmission performance indicators of candidate communication parameter combinations by establishing a transmission performance model. The transmission performance indicators include effective throughput and average data transmission delay. The effective throughput is obtained based on the connection interval of the Bluetooth Low Energy device, the number of data packets during data transmission, and the predicted packet error rate corresponding to the transmission power. The average data transmission delay is obtained based on the predicted packet error rate corresponding to the connection interval and transmission power of the Bluetooth Low Energy device.
[0020] Furthermore, the application requirement indicators in S302 include the maximum transmission delay allowed by the obtained application, and the candidate communication parameter combinations that meet the application requirement indicators, that is, the candidate communication parameter combinations in the predicted transmission performance indicators where the average data transmission delay is less than or equal to the maximum transmission delay.
[0021] Furthermore, in S303, the energy efficiency value is calculated based on the predicted effective throughput, average data transmission delay, and average current power consumption, combined with the configured weighting coefficients.
[0022] Furthermore, S4 determines whether to update the parameters based on the obtained utility improvement value, including:
[0023] If the utility improvement value is greater than or equal to the set threshold, the update procedure is executed to update the communication parameters, update the current communication parameters to the communication parameters corresponding to the maximum energy efficiency utility value, and use the maximum energy efficiency utility value as the utility comparison benchmark for the next decision cycle.
[0024] If the utility improvement is less than the threshold, the communication parameters of the current link remain unchanged, and the process proceeds to the next decision cycle.
[0025] Furthermore, the data transmission optimization method also includes updating parameters through the following steps: encapsulating the optimal parameter combination into a parameter configuration command and sending it to the module responsible for link parameter control, thereby dynamically updating the device's operating parameters.
[0026] This invention enables Bluetooth devices to dynamically adjust communication parameters based on real-time link status and application requirements, thereby minimizing device power consumption while ensuring data transmission timeliness and reliability, achieving an intelligent balance between power consumption and transmission efficiency. Before making a decision, the power consumption and performance of candidate communication parameters are predicted by a model, avoiding the overhead and latency of actual testing of all parameter combinations, thus improving the system's response speed and feasibility. Through this closed-loop control, the Bluetooth device always operates near the Pareto optimum in the current environment, achieving a dynamic balance between power consumption and transmission efficiency. Attached Figure Description
[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.
[0028] Figure 1 This is a flowchart of a data transmission optimization method for a low-power Bluetooth device according to the present invention. Detailed Implementation
[0029] To make the objectives, technical solutions, and advantages of the embodiments described herein clearer, the technical solutions in the embodiments will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments described herein, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments described herein without creative effort are within the scope of protection of this document. It should be noted that, unless otherwise specified, the embodiments and features described herein can be arbitrarily combined with each other.
[0030] The present invention will now be described in detail with reference to the accompanying drawings and embodiments:
[0031] A method for optimizing data transmission in a low-power Bluetooth device includes the following steps:
[0032] S1: Collect key parameters of the data transmission link of the Bluetooth Low Energy device in the current state. Key parameters include link quality index (LQ), application requirement index (AR), and communication parameters of the Bluetooth Low Energy device.
[0033] In the current state, the key parameters of the data transmission link for Bluetooth Low Energy devices include: communication parameters such as the transmit power of the Bluetooth Low Energy device. and connection interval Link quality metric (LQ) is represented by packet error rate, while application requirement metric (AR) includes the maximum allowable transmission delay for the application. .
[0034] In this invention, the link quality metric LQ includes the packet error rate (PER), which refers to the proportion of packets that have errors during data transmission. The packet error rate is a key indicator for measuring link quality.
[0035] In this embodiment, the connection interval refers to the time a Bluetooth Low Energy device sleeps between two connection events; a longer connection interval is generally more power-efficient, but data transmission latency is higher. Transmit power refers to the transmission strength of the Bluetooth device's radio frequency signal; a lower transmit power is generally more power-efficient, but communication distance and reliability will decrease.
[0036] S2: Transmit power of the low-power Bluetooth device in the current state (based on key parameters). and connection interval Based on this, a set of candidate parameters containing several sets of candidate communication parameters is periodically generated. .
[0037] Candidate parameter sets can be generated within an acceptable range using strategies such as gradient direction probing or random perturbation. .
[0038] In this embodiment, a candidate set is determined based on gradient direction probing. The utility enhancement gradient is calculated according to the current state. For example, if increasing P increases U, candidates are preferentially generated in the direction of increasing P; if decreasing CI increases U, candidates are probing in the direction of decreasing CI. Finally, N neighborhood candidate communication parameters are generated, forming a candidate parameter set. .
[0039] Candidate sets are determined based on random perturbations. The current parameters are periodically subjected to random perturbations to generate a set of candidate parameters. This process is existing technology in this field, therefore the process of determining the candidate set based on random perturbation will not be described in detail here. It is important to control the size of the candidate set to balance the breadth of exploration with the computational time.
[0040] S3: In each decision cycle, the utility of candidate communication parameter combinations after constraint verification in the candidate parameter set is evaluated to obtain the corresponding energy efficiency utility value. After comparing the values, the maximum energy efficiency utility value is obtained. The candidate communication parameters corresponding to the maximum energy efficiency utility value are the optimal parameter combinations.
[0041] For candidate parameter set Each set of candidate communication parameter combinations To obtain the maximum energy efficiency utility value, constraint verification and utility evaluation are performed, including the following processes:
[0042] S301: Predict all candidate communication parameter combinations in the candidate parameter set. The power consumption and transmission performance metrics TP.
[0043] In this invention, the power consumption indicator is expressed as average current power consumption. This indicates the average current power consumption. Obtained through current-model-based estimation or a dedicated hardware power consumption monitoring unit. Transmission performance metrics (TP) include effective throughput. and average data transmission delay .
[0044] Establish a power consumption prediction model to obtain communication parameters based on Bluetooth Low Energy devices. Average current power consumption predicted by link state The expression (1) is as follows:
[0045] (1)
[0046] in, Indicates communication parameters for Bluetooth Low Energy devices The average current power consumption predicted by the link state; a, b, and c represent the power consumption model coefficients.
[0047] In this embodiment, during the initial deployment or regular maintenance of the device, the power consumption model coefficients a, b, and c in Formula 1 are learned through linear regression based on the operating data over a period of time.
[0048] Establish a transmission performance model to obtain the transmission performance index TP, and obtain the communication parameters based on Bluetooth Low Energy devices. Effective throughput and link state prediction The expression (2) is as follows:
[0049] (2)
[0050] in, Indicates communication parameters for Bluetooth Low Energy devices Effective throughput based on link status prediction; Indicates the number of data packets during transmission; For transmission power The corresponding predicted packet error rate, Can be pre-stored Obtained by querying the mapping table.
[0051] In this embodiment, a mapping table of packet error rates (PER) for different transmit powers P under typical conditions is established through laboratory testing or initial network probing.
[0052] Obtain communication parameters based on Bluetooth Low Energy devices Average data transmission delay predicted by link state The expression (3) is as follows:
[0053] (3)
[0054] in, Indicates the communication parameters of Bluetooth Low Energy devices. The average data transmission delay predicted by link status.
[0055] S302: Based on the application requirement indicators obtained in S1, obtain the candidate communication parameter combinations that meet the application requirement indicators in the transmission performance indicators.
[0056] In this invention, the maximum allowable transmission delay of the application is obtained from the application requirement index AR. Communication parameters with Bluetooth Low Energy devices Average data transmission delay obtained from link state prediction Compare; remove average data transmission delay Greater than the maximum transmission delay The candidate communication parameter combinations corresponding to the given time are used to ultimately obtain the candidate communication parameter combinations that meet the application requirements, namely, the average data transmission delay in the predicted transmission performance indicators. Less than or equal to the maximum transmission delay The corresponding candidate communication parameter combination.
[0057] S303: Calculate candidate communication parameter combinations that meet application requirements based on power consumption and transmission performance metrics. The energy efficiency value.
[0058] For candidate communication parameter combinations that meet application requirements, use formula (4) based on effective throughput. Average data transmission delay and average current power consumption Candidate communication parameter combinations that meet the basic requirements of the application Predicted energy efficiency value .
[0059] The energy efficiency utility function expression (4) is as follows:
[0060] (4)
[0061] in, Indicates the energy efficiency utility value; Indicates based on candidate communication parameter combinations Effective throughput based on link status prediction; Indicates based on candidate communication parameter combinations The average data transmission delay predicted by link status; Indicates based on candidate communication parameter combinations Average current power consumption predicted by link state; , These are the weighting coefficients.
[0062] In this embodiment, the weights of the energy efficiency utility function are pre-defined by the developers or users based on the specific application scenario of the device, such as sensor reporting and audio transmission. and Increased real-time performance in high-performance scenarios Long-range battery life scenarios are increasing. .
[0063] S4: Based on maximum energy efficiency value Energy efficiency value under current conditions The utility improvement value obtained after comparison is used to determine whether to update the parameters based on the set threshold.
[0064] If the set conditions are met, the current communication parameters will be updated to the optimal parameter combination, and the maximum energy efficiency utility value will be used as the utility comparison benchmark for the next decision cycle.
[0065] If the set conditions are not met, the current communication parameters will remain unchanged, and the process will proceed to the next decision cycle.
[0066] The method of determining whether to update parameters based on the obtained utility improvement value includes:
[0067] If the utility improvement value is greater than or equal to the set threshold δ, then an update procedure is executed to update the communication parameters, replacing the current communication parameters with those corresponding to the maximum energy efficiency utility value, and setting the maximum energy efficiency utility value accordingly. As a benchmark for utility comparison in the next decision-making cycle;
[0068] If the utility improvement is less than the threshold δ, the communication parameters of the current link remain unchanged, and the process proceeds to the next decision cycle.
[0069] Utility Enhancement Value The calculation is as follows:
[0070] (5)
[0071] in, This represents the maximum energy efficiency value among candidate communication parameter combinations that meet application requirements. This represents the energy efficiency value under the current communication parameters.
[0072] In this invention, the execution update program updates the parameters to obtain the maximum energy efficiency value. The corresponding candidate communication parameter combinations are the optimal parameter combinations. This includes encapsulating the optimal parameter combination into parameter configuration instructions through the Bluetooth host control interface or a similar mechanism, sending them to the Bluetooth controller responsible for link parameter regulation, and dynamically updating the device's operating parameters.
[0073] In this embodiment, the actual transmit power of the BLE RF transmitter in the Bluetooth controller can be updated by encapsulating the optimal parameter combination into a parameter configuration instruction according to the BLE protocol specification. This overrides the current link's transmit power configuration and updates the BLE link layer's connection interval to... , and Synchronous updates are required to avoid link imbalance caused by adjusting only the transmit power without adjusting the connection interval. For example, if the power is reduced but the connection interval is too short, it will lead to an increase in packet loss rate.
[0074] This invention can also employ a set of simple "if-else" rules. For example, when the data queue length exceeds a threshold, the connection interval is automatically shortened; when the signal-to-noise ratio is below a threshold, the transmit power is automatically increased. This scheme is simple to implement and has low computational overhead, but its adjustment is local and single-objective. It cannot achieve a comprehensive optimal balance of multiple objectives (latency, throughput, and power consumption) from a global perspective like this invention, and its flexibility and optimization effect are poor.
[0075] Another alternative is table-based parameter selection. This involves pre-optimizing a set of optimal parameters (P, CI) offline through extensive experimentation for different combinations of (RSSI, queue length), and storing these parameters in the device. At runtime, the parameters are retrieved from the table based on the measured RSSI and queue length. This method is fast, but requires significant upfront work, cannot adapt to scenarios not predefined in the table, and lacks generalization ability.
[0076] This invention transforms the parameter adjustment process, which originally relied on engineer experience, into a calculable optimization objective by constructing a quantified energy efficiency utility function, thus achieving intelligent decision-making. It also introduces utility evaluation based on predictive models. Before making a decision, the power consumption and performance of candidate communication parameters are predicted by the model, avoiding the overhead and latency of actual testing of all parameter combinations, thereby improving the system's response speed and feasibility. Through this closed-loop control, the Bluetooth device always operates near the Pareto optimum in the current environment, achieving a dynamic balance between power consumption and transmission efficiency.
[0077] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.
Claims
1. A method for optimizing data transmission in a low-power Bluetooth device, characterized in that, Includes the following steps: S1: Collect key parameters of the data transmission link of the Bluetooth Low Energy device in the current state. Key parameters include link quality indicators, application requirement indicators, and communication parameters of the Bluetooth Low Energy device. S2: Based on the communication parameters of the low-power Bluetooth device in the key parameters of the current state, periodically generate a set of candidate parameters containing several sets of candidate communication parameters. S3: In each decision cycle, evaluate the utility of candidate communication parameter combinations after constraint verification in the candidate parameter set to obtain the corresponding energy efficiency utility value. After comparing the values, obtain the maximum energy efficiency utility value. The candidate communication parameter combination corresponding to the maximum energy efficiency utility value is the optimal parameter combination. S4: The utility improvement value obtained by comparing the maximum energy efficiency utility value with the energy efficiency utility value under the current state is used to determine whether to update the parameters, based on a set threshold. If the set conditions are met, the current communication parameters will be updated to the optimal parameter combination, and the maximum energy efficiency utility value will be used as the utility comparison benchmark for the next decision cycle. If the set conditions are not met, the current communication parameters will remain unchanged, and the process will proceed to the next decision cycle.
2. The data transmission optimization method according to claim 1, characterized in that, The communication parameters in S1 include the transmit power and connection interval of the Bluetooth Low Energy device; the link quality index is represented by the packet error rate; and the application requirement index includes the maximum transmission delay allowed by the application.
3. The data transmission optimization method according to claim 1, characterized in that: The S2 method uses gradient direction probing or random perturbation to generate a set of candidate parameters.
4. The data transmission optimization method according to claim 1, characterized in that: S3 performs constraint verification and utility evaluation on each combination of candidate communication parameters in the candidate parameter set. S301: Predict the power consumption and transmission performance of all candidate communication parameter combinations in the candidate parameter set; S302: Based on the application requirement indicators obtained in S1, obtain the candidate communication parameter combinations that meet the application requirement indicators in the transmission performance indicators; S303: Calculate candidate communication parameter combinations that meet application requirements based on power consumption and transmission performance metrics. The energy efficiency value.
5. The data transmission optimization method according to claim 4, characterized in that: S301 predicts the power consumption index of candidate communication parameter combinations by establishing a power consumption prediction model. The power consumption index is represented by average current power consumption. The average current power consumption is predicted based on the transmit power and connection interval of the low power Bluetooth device and the power consumption model coefficients.
6. The data transmission optimization method according to claim 5, characterized in that: S301 predicts the transmission performance indicators of candidate communication parameter combinations by establishing a transmission performance model. The transmission performance indicators include effective throughput and average data transmission delay. Effective throughput is obtained based on the connection interval of the Bluetooth Low Energy device, the number of data packets during data transmission, and the predicted packet error rate corresponding to the transmission power. Average data transmission delay is obtained based on the predicted packet error rate corresponding to the connection interval and transmission power of the Bluetooth Low Energy device.
7. The data transmission optimization method according to claim 4, characterized in that: The application requirement indicators in S302 include the maximum transmission delay allowed by the obtained application and the candidate communication parameter combinations that meet the application requirement indicators, that is, the candidate communication parameter combinations in the predicted transmission performance indicators where the average data transmission delay is less than or equal to the maximum transmission delay.
8. The data transmission optimization method according to claim 6, characterized in that: In S303, the energy efficiency value is calculated based on the predicted effective throughput, average data transmission delay, and average current power consumption, combined with the configured weighting coefficients.
9. The data transmission optimization method according to claim 1, characterized in that, S4, based on the obtained utility improvement value, determines whether to update the parameters, including: If the utility improvement value is greater than or equal to the set threshold, the update procedure is executed to update the communication parameters, update the current communication parameters to the communication parameters corresponding to the maximum energy efficiency utility value, and use the maximum energy efficiency utility value as the utility comparison benchmark for the next decision cycle. If the utility improvement is less than the threshold, the communication parameters of the current link remain unchanged, and the process proceeds to the next decision cycle.
10. The data transmission optimization method according to claim 1, characterized in that: The data transmission optimization method further includes updating parameters through the following steps: encapsulating the optimal parameter combination into a parameter configuration command and sending it to the module responsible for link parameter control, thereby dynamically updating the device's operating parameters.