Cold error compensation method for Internet communication

Abstract

The invention discloses a cold error compensation method for internet communication, which comprises the following steps of: installing high-precision temperature sensors at key parts of communication equipment and key transmission nodes and near a transmission medium, and acquiring temperature data at regular time; inputting the data into a temperature and communication error relation model, and predicting the type and degree of possible communication errors; whether the current communication state needs to be adjusted or not is judged according to the predicted communication error result, and when the result exceeds an error threshold value, an improved cold ice algorithm is adopted to dynamically optimize communication parameters; the optimized communication parameters are issued to the communication equipment by generating a control instruction; monitoring a communication quality index in real time, and collecting an operation state and performance data fed back by the communication equipment; and comparing the communication quality index with a preset requirement, if the communication quality index does not meet the preset requirement, returning to the step of dynamically optimizing the communication parameters, and continuing iterative optimization until the communication quality index meets the preset requirement.

Description

Technical Field

[0001] This invention relates to the technical field of communication error compensation and environment-adaptive communication, and in particular to a cold error compensation method for Internet communication. Background Technology

[0002] With the development of high-speed networks and the popularization of data-intensive applications, the demand for stable and error-free data communication is increasing. Traditional communication equipment and transmission media are usually designed and operated under standard environmental conditions. However, in low-temperature environments such as high latitudes, polar regions, high altitudes, and outer space, the performance of communication systems may be severely affected.

[0003] Low-temperature environments can alter the electrical and optical properties of materials, such as increasing the attenuation coefficient of optical fibers, decreasing the carrier mobility of electronic components, and changing the signal propagation speed. These factors can lead to signal distortion, increased delay jitter, and higher bit error rate, ultimately affecting communication quality and system reliability.

[0004] To address the impact of low-temperature environments on communication systems, existing technologies mainly focus on hardware improvements and environmental control measures. For example, they employ low-temperature resistant materials, add temperature control components to equipment (such as heaters and insulation layers), or use redundant designs and more robust error correction algorithms. However, these methods have many shortcomings.

[0005] Hardware improvements and environmental control measures typically increase equipment costs and energy consumption, hindering large-scale deployment, especially in remote or resource-constrained areas. While redundant designs and enhanced error correction algorithms can improve communication reliability to some extent, they may increase system complexity and data transmission latency. Furthermore, most of these methods are static and cannot be dynamically adjusted according to real-time changes in ambient temperature, making them difficult to adapt to rapidly changing low-temperature conditions. Summary of the Invention

[0006] The purpose of this section is to outline some aspects of the embodiments of the present invention and to briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section, as well as in the abstract and title of the present application, to avoid obscuring the purpose of this section, the abstract and title of the invention. Such simplifications or omissions shall not be used to limit the scope of the present invention.

[0007] In view of the aforementioned existing problems, the present invention is proposed.

[0008] Therefore, the technical problem solved by this invention is that existing Internet communication technologies cannot effectively compensate for communication errors in real time under low-temperature environments.

[0009] To solve the above-mentioned technical problems, the present invention provides the following technical solution: installing high-precision temperature sensors in key parts of communication equipment and key transmission nodes and near the transmission medium to monitor ambient temperature and equipment temperature in real time and collect temperature data periodically; The temperature data is input into a temperature-communication error relationship model constructed based on a support vector regression algorithm to predict the possible types and extent of communication errors. The current communication status needs to be adjusted based on the predicted communication error results. When the predicted communication error results exceed the error threshold, the improved IceFrost algorithm is used to dynamically optimize the communication parameters. By generating control commands, the optimized communication parameters are sent to the communication device; Real-time monitoring of communication quality indicators, and collection of operating status and performance data fed back by the communication equipment; The communication quality indicators are compared with the preset requirements. If the communication quality indicators meet the preset requirements, the parameter adjustment effect is evaluated as successful. If the requirements are not met, return to the step of dynamically optimizing the communication parameters and continue iterative optimization until the communication quality indicators meet the preset requirements.

[0010] As a preferred embodiment of the cold error compensation method for Internet communication described in this invention, the temperature data collected at regular intervals includes at least the current temperature value, the temperature change rate, and historical temperature data over a past period. The sampling frequency is dynamically adjusted according to the temperature change rate; when the temperature change rate is large, the sampling frequency is increased.

[0011] As a preferred embodiment of the cold error compensation method for Internet communication described in this invention, the collected temperature data is filtered and denoised using a moving average filter to obtain a smooth temperature curve.

[0012] As a preferred embodiment of the cold error compensation method for Internet communication described in this invention, the step of determining whether the current communication state needs adjustment based on the predicted communication error result includes: like Then parameter adjustments are required; in, The error threshold is preset to the maximum acceptable error for communication quality. The predicted communication error is expressed in terms of the change in bit error rate or signal-to-noise ratio.

[0013] As a preferred embodiment of the cold error compensation method for Internet communication described in this invention, when adjustments are required, an improved ice algorithm is used to adjust the communication parameters. Dynamic optimization is performed, and the objective function is: in, To optimize the objective function, The set of communication parameters to be optimized includes gain G, modulation scheme M, coding scheme C, and error correction strategy F. Bit error rate (BER) is used as a communication quality indicator. , The weighting coefficients reflect the degree of influence of bit error rate and prediction error on the optimization objective.

[0014] As a preferred embodiment of the cold error compensation method for Internet communication described in this invention, the control command is a parameter setting command specified by the communication protocol, which includes parameter type, value and range of application.

[0015] As a preferred embodiment of the cold error compensation method for Internet communication described in this invention, the communication quality indicator includes at least the bit error rate. Signal-to-noise ratio Delay D.

[0016] As a preferred embodiment of the cold error compensation method for Internet communication described in this invention, a comparison is made between communication quality indicators and preset requirements, wherein the preset requirements include: ; ; ; in, , , This is a preset threshold.

[0017] The beneficial effects of this invention are: 1. Real-time monitoring and high-precision data acquisition ensure that temperature changes are captured in a timely and accurate manner, providing a reliable data foundation for error prediction; 2. The error prediction model based on SVR improves the accuracy and reliability of error prediction and identifies potential communication problems in advance; 3. The improved IceFrost algorithm optimizes communication parameters, enabling dynamic and precise adjustment of communication parameters and suppressing the increase in bit error rate and latency; 4. The generation and issuance of automated control commands accelerate the response speed of parameter adjustments and reduce the delay and error caused by human intervention; 5. Real-time communication quality monitoring and closed-loop control ensure that the communication system can continuously meet quality requirements, enhancing the system's adaptability and robustness. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1 This is a flowchart illustrating the cold error compensation method for Internet communication as shown in this invention. Figure 2 This is a schematic diagram illustrating the delay comparison of the present invention; Figure 3 This is a schematic diagram illustrating the signal-to-noise ratio comparison of the present invention; Figure 4 This is a schematic diagram illustrating the comparison of bit error rates in this invention. Detailed Implementation

[0019] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0020] Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without inventive effort should fall within the scope of protection of this invention.

[0021] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0022] According to an embodiment of the present invention, in combination Figure 1 The flowchart shown illustrates a cold error compensation method for internet communication, which specifically includes the following steps: S1. Install high-precision temperature sensors in key parts of communication equipment and key transmission nodes and near the transmission medium to monitor ambient temperature and equipment temperature in real time and collect temperature data periodically. S2. Input the temperature data into the temperature-communication error relationship model built based on the support vector regression algorithm to predict the possible types and extent of communication errors; S3. Determine whether the current communication status needs to be adjusted based on the predicted communication error results. If the predicted communication error results exceed the error threshold, the improved IceFrost algorithm is used to dynamically optimize the communication parameters. S4. By generating control commands, the optimized communication parameters are sent to the communication device; S5. Monitor communication quality indicators in real time and collect operating status and performance data from communication equipment. S6. Compare the communication quality indicators with the preset requirements. If the communication quality indicators meet the preset requirements, the parameter adjustment effect is evaluated as successful. S7. If not satisfied, return to the step of dynamically optimizing communication parameters and continue iterative optimization until the communication quality indicators meet the preset requirements.

[0023] To better understand the implementation of the above technical solution, the following example illustrates each step in the context of deploying an internet communication system in a high-latitude region (such as near the Arctic Circle), where the ambient temperature may drop to -40℃:

Application Scenario Parameter Settings

[0024] [Communication parameter optimization and adjustment] When adjustments are needed, the improved Ice algorithm is used to modify the communication parameters. Dynamic optimization is performed, and the objective function is: in, To optimize the objective function, The set of communication parameters to be optimized includes gain G, modulation scheme M, coding scheme C, and error correction strategy F. Bit error rate (BER) is used as a communication quality indicator. , These are weighting coefficients, reflecting the degree of influence of bit error rate and prediction error on the optimization objective; The specific implementation steps of the improved IceFrost algorithm are as follows: Initialization: Set initial parameters for the population and corresponding speed , ; Temperature adaptability weight: Introducing temperature adaptability weight The update speed formula is: in, , For the range of weight values, , For the temperature range, , The acceleration constant, , A random number in the range [0,1]. This is the optimal position in the particle's history. The globally optimal position; Parameter update: Update communication parameters ; Evaluation of fitness: Calculating new fitness ,renew and ; Iteration: Repeat the above steps until the maximum number of iterations is reached or convergence; For example, initialization: number of particles Maximum number of iterations Initial communication parameter range: Gain G: 10 dB to 20 dB; Modulation method M: QPSK, 16QAM, 64QAM; Encoding method C: Convolutional code, LDPC code; Error correction strategies F: Automatic Repeat Request (ARQ), Forward Error Correction (FEC); Initial velocity and position: randomly generated within the parameter range; Temperature adaptability weight calculation: Current smoothing temperature: ; Weight calculation: definition , , , ; The calculation yielded: Optimize the objective function: Weighting coefficients: , ; Objective function: Optimization process: Iterative update: In each iteration, the particle velocity and position are updated, and the fitness is calculated. Update individual optimal and global optimal ; Example adjustment result: Optimized parameters Gain dB, modulation method QAM, encoding method C code, error correction strategy ; [Control Command Generation] Based on the optimization results Generate control commands that conform to the communication protocol; Command format example: Command header: Identifies the command type; Parameter types: gain, modulation method, coding method; Parameter value: The corresponding numerical value or mode; Checksum: Used to verify the integrity of instructions; Table 1. Command Format Table Fields content Command Header 0xAA Parameter type Gain, modulation scheme, coding scheme, and error correction strategy Parameter value G=18dB, M=16QAM, C=LDPC, F=FEC Verification code Calculated check code Command issuance and execution: The central control unit sends instructions to the communication equipment through the management channel; The communication equipment receives instructions, parses them, and performs parameter adjustments. [Evaluation of Communication Parameter Tuning Results] Real-time monitoring of communication quality indicators should include at least: Bit error rate : Indicates the percentage of errors in the transmitted data; Signal-to-noise ratio The ratio of signal power to noise power reflects signal quality. Delay D: The time interval from data transmission to reception; Based on a comparison between communication quality indicators and preset requirements, the preset requirements include: ; ; ; in, , , The preset threshold; For example, the collection results are as follows: , , ; Compare with preset thresholds: ; ; ; Evaluation results: All communication quality indicators met the preset requirements, and the parameter adjustment was successful; If the temperature drops to -35℃, the rate of temperature change increases to -1℃ / s, and the sampling frequency... Added to: The system re-predicts errors and optimizes parameters to ensure communication quality.

[0025] Furthermore, to verify the effectiveness and superiority of the cold error compensation method for Internet communication provided in this embodiment of the invention, this embodiment selects a real-world application environment located in a high-latitude cold region (such as near the Arctic Circle) for experimentation. The experimental environment simulates the extreme low-temperature conditions that may be encountered in actual applications, with the ambient temperature range set from -40℃ to 0℃. The experimental design uses two sets of communication devices for comparative testing: one set is a communication system using existing technology (without cold error compensation), and the other set is a communication system applying the cold error compensation method of this invention.

[0026] Equipment installation Communication equipment: Each group is equipped with two sets of fiber optic transmission equipment and two sets of wireless communication equipment to ensure the fairness of the comparison and the reliability of the data; Temperature sensor: Digital platinum resistance temperature sensors (PT1000) are installed near key parts of each communication system (such as fiber optic amplifiers and wireless transmitting antennas) and the transmission medium (fiber optic lines every 10 kilometers). The measurement range is -50℃ to +150℃, and the measurement accuracy is ±0.1℃. Monitoring and Control Unit: Configure a central control unit, connect all temperature sensors, build a support vector regression (SVR) model and an improved ice algorithm optimization module; Data Acquisition and Preprocessing Sampling frequency: The basic sampling frequency is set to 1 Hz, and the sampling frequency adjustment coefficient is... ; Temperature change rate calculation: Real-time calculation of temperature change rate Dynamically adjust the sampling frequency; Temperature data filtering: A moving average filter is used with a window size of 5 data points to smooth the temperature data and reduce noise interference; Error prediction and parameter optimization SVR model training: The SVR model was trained using historical temperature and communication error data, with a radial basis function (RBF) kernel selected and kernel parameter γ=0.1; Ice Algorithm Optimization: The improved Ice Algorithm is based on the Particle Swarm Optimization (PSO) algorithm and introduces a temperature-adaptive weight ω(T), with the weight range set to [0.4, 0.9], corresponding to a temperature range of -50℃ to +50℃; Implementation process Temperature monitoring and data acquisition: Each communication system collects ambient temperature and equipment temperature data at different time periods. The sampling frequency is dynamically adjusted according to the temperature change rate to ensure the timeliness and accuracy of the data. For example, when the temperature change rate is -0.5℃ / s, the sampling frequency is adjusted to 6 Hz. Error prediction: Input the collected temperature data into the SVR model to predict the type and extent of communication errors that may occur under the current temperature conditions (such as changes in bit error rate and signal-to-noise ratio). For example, when the current smoothing temperature is -30℃, the predicted bit error rate is... ; Communication status assessment and parameter optimization: Compare the prediction error with a preset threshold. If the threshold is exceeded, the improved Iceberg algorithm is activated to dynamically optimize communication parameters (gain, modulation scheme, coding scheme, and bit error correction strategy), generating control commands and sending them to the communication equipment. For example, if the predicted bit error rate is... Exceeding the threshold Then, parameter optimization is performed; Communication quality monitoring and performance evaluation: Real-time monitoring of communication quality indicators (bit error rate, signal-to-noise ratio, latency) and comparison of feedback data with preset requirements. If the requirements are met, the parameter adjustment is considered successful; otherwise, iterative optimization continues. For example, after optimization, the bit error rate is reduced to a certain level. This meets the preset requirements; Closed-loop control: The system continuously monitors and dynamically adjusts to form a closed-loop control, ensuring the stable operation of the communication system in extreme low-temperature environments. For example, if the ambient temperature drops further to -35℃, the system automatically adjusts the sampling frequency to 11 Hz and re-performs error prediction and parameter optimization.

[0027] Reference Figure 2 The latency of the prior art (dashed line) is higher than the preset threshold of 50ms. The latency of the method of the present invention (solid line) is significantly reduced and meets the preset requirements. It can be seen that the method of the present invention effectively reduces communication latency and ensures the real-time performance of data transmission, while the latency of the prior art is high, which affects the response speed and data transmission efficiency of the communication system.

[0028] Reference Figure 3 The signal-to-noise ratio (SNR) of the existing technology (dashed line) is lower than the preset threshold by 20dB. The SNR of the method of the present invention (solid line) is significantly improved, exceeding the preset threshold. Therefore, the method of the present invention significantly improves the SNR of the communication system and ensures good signal quality. In contrast, the SNR of the existing technology group is low, which can easily lead to signal distortion and data transmission errors.

[0029] Reference Figure 4 The existing technology (dashed line) shows a high bit error rate, all exceeding the preset threshold. The bit error rate of the method of the present invention (solid line) is significantly reduced and is lower than the preset threshold. The method of the present invention effectively reduced the bit error rate in all tests and kept it within an acceptable range, while the bit error rate of the prior art group was significantly higher, indicating that the prior art is difficult to guarantee communication quality in low temperature environment.

[0030] It should be noted that existing Internet communication technologies have many shortcomings in low-temperature environments, mainly manifested in high bit error rate, low signal-to-noise ratio, and high communication latency. Experimental data shows that the bit error rate of existing technologies under low-temperature conditions is significantly higher than the preset threshold, resulting in unreliable data transmission; the signal-to-noise ratio is lower than the standard requirements, affecting signal quality and data integrity; and the latency is higher than the preset limit, affecting real-time data transmission and system response speed. These shortcomings limit the application of existing communication technologies in extreme low-temperature environments and cannot meet the requirements for high reliability and high real-time data transmission.

[0031] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A cold error compensation method for Internet communication, characterized in that, include: High-precision temperature sensors are installed in key parts of communication equipment and critical transmission nodes and near the transmission medium to monitor ambient and equipment temperatures in real time and collect temperature data periodically. The temperature data is input into a temperature-communication error relationship model constructed based on a support vector regression algorithm to predict the possible types and extent of communication errors. The current communication status needs to be adjusted based on the predicted communication error results. When the predicted communication error results exceed the error threshold, the improved IceFrost algorithm is used to dynamically optimize the communication parameters. By generating control commands, the optimized communication parameters are sent to the communication device; Real-time monitoring of communication quality indicators, and collection of operating status and performance data fed back by the communication equipment; The communication quality indicators are compared with the preset requirements. If the communication quality indicators meet the preset requirements, the parameter adjustment effect is evaluated as successful. If the requirements are not met, return to the step of dynamically optimizing the communication parameters and continue iterative optimization until the communication quality indicators meet the preset requirements.

2. The cold error compensation method for Internet communication according to claim 1, characterized in that, The temperature data collected periodically includes at least the current temperature value, the rate of temperature change, and historical temperature data over a past period. The sampling frequency is dynamically adjusted according to the temperature change rate; when the temperature change rate is large, the sampling frequency is increased.

3. The cold error compensation method for Internet communication according to claims 1 and 2, characterized in that, The collected temperature data is filtered and denoised using a moving average filter to obtain a smooth temperature curve.

4. The cold error compensation method for Internet communication according to claim 1, characterized in that, The step of determining whether the current communication state needs adjustment based on the predicted communication error results includes: like Then parameter adjustments are required; in, The error threshold is preset to the maximum acceptable error for communication quality. The predicted communication error is expressed in terms of the change in bit error rate or signal-to-noise ratio.

5. The cold error compensation method for Internet communication according to claim 1, characterized in that, When adjustments are needed, the improved Ice algorithm is used to modify the communication parameters. Dynamic optimization is performed, and the objective function is: in, To optimize the objective function, The set of communication parameters to be optimized includes gain G, modulation scheme M, coding scheme C, and error correction strategy F. Bit error rate (BER) is used as a communication quality indicator. , The weighting coefficients reflect the degree of influence of bit error rate and prediction error on the optimization objective.

6. The cold error compensation method for Internet communication according to claim 1, characterized in that, The control command is a parameter setting command specified by the communication protocol, which includes parameter type, value and scope of application.

7. The cold error compensation method for Internet communication according to claim 1, characterized in that, The communication quality indicators include at least the bit error rate. Signal-to-noise ratio Delay D.

8. The cold error compensation method for Internet communication according to claim 1, characterized in that, The communication quality indicators are compared with preset requirements, which include: ； ； ； in, , , This is a preset threshold.

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