Satellite communication transmission equipment

Abstract

The invention discloses satellite communication transmission equipment, which relates to the field of communication transmission, and comprises a transmission control module used for providing access authority of a signal receiving end and a signal transmitting end and carrying out editing operation of operation instructions of all functional modules; the signal monitoring module is used for monitoring the signal-to-noise ratio, the bit error rate and the received signal strength of signal receiving according to a preset period, calculating a signal quality index in real time, and performing trend analysis and display on the signal quality index; the feedback generation module is used for aggregating the calculation signal quality indexes from the signal monitoring module and generating comprehensive feedback information; the method can quickly respond to the change of signal quality, compares the real-time signal quality with a preset standard threshold, generates a control signal, intelligently adjusts the transmitting power according to the environmental change, generates a missing report according to historical and current data, timely identifies and records a missing data packet, and uses a prediction model to predict the missing data based on the historical data and the real-time signal state. And intelligently analyzing a potential data missing trend, and generating a recovery scheme.

Description

Technical Field

[0001] The present invention relates to the technical field of communication transmission, and in particular to satellite communication transmission equipment. Background Art

[0002] With the acceleration of globalization, multinational enterprises and international organizations have an increasing demand for efficient and reliable communication tools. Satellite communications can cross national borders and provide services to users around the world. Many remote areas or oceans lack traditional ground communication infrastructure. Satellite communications can fill this gap, allowing users in these areas to enjoy communication services. Satellite communications are widely used in many industries such as navigation, aviation, oil exploration, agricultural monitoring, and environmental monitoring, supporting data transmission and real-time monitoring in these industries.

[0003] However, existing equipment lacks the ability to monitor and analyze data in real time during signal reception and transmission, resulting in failure to take timely measures when signal quality deteriorates, thus affecting communication effects. In existing equipment, static transmission power settings may not be able to adapt to real-time environmental changes, resulting in insufficient or excessive signal strength. Data packets may be lost during the signal process, but the processing and recovery mechanism for missing data is not perfect.

[0004] Traditional communication transmission equipment finds it difficult to integrate historical data with current conditions for intelligent prediction in order to identify possible signal problems in advance. Its ability to collect and analyze operating data is limited, making it difficult to fully evaluate equipment performance. Summary of the invention

[0005] 1. Technical issues to be solved

[0006] In view of the above-mentioned shortcomings of the prior art, the present invention provides a satellite communication transmission device, which can effectively solve the problems of the prior art.

[0007] (II) Technical solution

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0009] The present invention discloses a satellite communication transmission device, comprising:

[0010] The transmission control module is used to provide access rights to the signal receiving and transmitting ends, and to edit and run the operating instructions of each functional module;

[0011] The signal monitoring module is used to monitor the signal-to-noise ratio, bit error rate and received signal strength according to the preset period, calculate the signal quality index in real time, and perform trend analysis and display;

[0012] A feedback generation module for aggregating the calculated signal quality indicators from the signal monitoring module to generate comprehensive feedback information;

[0013] A feedback evaluation module is used to compare the monitored signal quality index with a preset standard threshold to determine the current signal status. If the signal quality drops below the threshold, a control signal to increase the transmit power is generated. If the signal quality is good, a control signal to maintain or reduce the transmit power is generated.

[0014] A power adjustment module dynamically adjusts the transmission power according to the control signal fed back by the feedback evaluation module;

[0015] A missing detection module is used to identify the feedback data of the feedback generation module in the next cycle after the power adjustment module is triggered, monitor and identify the missing signal data packets in the signal reception process, compare the received data of the previous cycle with the current received data, record the missing signal data packets, generate a missing report, and record the current operation status;

[0016] A signal prediction module is used to establish a prediction model based on historical reception data, current missing report data and current weather data, predict missing signal data according to historical patterns and current conditions, and generate a prediction report;

[0017] The retransmission control module is used to perform selective retransmission or batch retransmission selection according to the missing report and prediction results, perform signal retransmission operations, and submit the missing data packets to the transmission control module for retransmission through a preset channel.

[0018] Furthermore, the transmission control module is interactively connected to a storage module via a wireless network, and the storage module is interactively connected to the missing detection module via a wireless network. The storage module is used to collect operating data of each module, analyze the success rate, signal loss rate and efficiency indicators of power adjustment, and perform classified storage and cloud backup.

[0019] Furthermore, when the power adjustment module receives a signal to increase the transmission power, it increases the transmission power at a preset ratio according to the current feedback data, and if the signal is good, it maintains the current power or reduces the transmission power at a preset ratio.

[0020] Furthermore, the signal prediction module performs data collection and preprocessing during the establishment of the prediction model, extracts the features that affect the signal strength, and trains the model through samples through a machine learning algorithm. The specific representation of data collection is as follows:

[0021] Historical received data D = {d1, d2, ..., d n}, where d i represents the received signal strength at the i-th time point;

[0022] Missing report M = {m1,m2,…,m k},m j It means that at time point t j Missing packets;

[0023] Current weather conditions W = {w1, w2, ..., w u}, indicating several weather conditions.

[0024] Furthermore, in the process of extracting the features respectively, the historical signal strength feature calculation formula is:

[0025]

[0026] Where S h is the average value of historical signal strength;

[0027] The missing data feature calculation formula is:

[0028]

[0029] Where S m is the average number of missing signal packets;

[0030] The weather characteristics calculation formula is:

[0031]

[0032] Where S w Indicates current weather conditions.

[0033] Furthermore, during the model training process, the input of the model is set as a feature combination:

[0034]

[0035] The predicted output is the signal strength y at the next time point t +1;

[0036] Let the model be f(X;Q), where Q represents the model parameters and X represents the model input feature vector. The training set is used for optimization, and the expression formula is:

[0037]

[0038] In the formula, y i represents the observed value of the actual received signal strength at the i-th sample time point, X i represents the input feature vector of the i-th sample, and P represents the total number of samples.

[0039] Furthermore, the predicted output is the signal strength y at the next time point tThe specific calculation formula of +1 is:

[0040]

[0041] Where V0 represents the intercept term, V1, V2 and V3 represent the regression coefficients of historical reception data, current missing report data and current weather data, respectively, and e represents the error term.

[0042] Furthermore, the transmission control module is interactively connected to the signal monitoring module, the power adjustment module and the retransmission control module through a wireless network, the signal monitoring module is interactively connected to the feedback generation module through a wireless network, the feedback generation module is interactively connected to the feedback evaluation module and the missing detection module through a wireless network, the feedback evaluation module is interactively connected to the power adjustment module through a wireless network, the missing detection module is interactively connected to the signal prediction module through a wireless network, and the signal prediction module is interactively connected to the retransmission control module through a wireless network.

[0043] (III) Beneficial effects

[0044] Compared with the known prior art, the technical solution provided by the present invention has the following beneficial effects:

[0045] 1. By regularly monitoring the signal-to-noise ratio, bit error rate and received signal strength, and calculating the signal quality indicators in real time, the signal status can be understood in a timely manner, and the signal quality changes can be quickly responded to to ensure the stability of communication. The real-time signal quality is compared with the preset standard threshold, and a control signal is generated. The transmission power is intelligently adjusted according to environmental changes, thereby improving communication quality, reducing energy waste, and avoiding interference caused by excessive signal strength.

[0046] 2. By monitoring the loss of signal data packets, generating missing reports based on historical and current data, timely identifying and recording missing data packets, improving the efficiency of data recovery, and enhancing the reliability of the system, using predictive models based on historical data and real-time signal status, intelligently analyzing potential data loss trends, and generating recovery plans, reducing the occurrence of communication interruptions and improving the integrity and accuracy of data transmission through early prediction and remedial measures.

[0047] 3. By centrally managing all operating data, the system can conduct more comprehensive performance analysis, promote continuous optimization and fault tracking, improve equipment operating efficiency, dynamically adjust working parameters according to different environmental changes and needs, better adapt to various working conditions, and ensure stable communication quality. By comprehensively optimizing transmission power and signal quality, the system can work within the effective range, reduce energy consumption, implement real-time monitoring and precise management of data flow, so that users can obtain the required information faster. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0049] Figure 1 It is a schematic diagram of the framework of the present invention.

[0050] The numbers in the figure represent, respectively, 1. transmission control module; 2. signal monitoring module; 3. feedback generation module; 4. feedback evaluation module; 5. power adjustment module; 6. missing detection module; 7. signal prediction module; 8. retransmission control module; 9. storage module. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0052] The present invention will be further described below in conjunction with the embodiments.

[0053] Example 1

[0054] A satellite communication transmission device of this embodiment, such as Figure 1 As shown, including:

[0055] The transmission control module 1 is used to provide access rights for the signal receiving and transmitting ends, and to edit and operate the operation instructions of each functional module; the transmission control module 1 is interactively connected to the storage module 9 through a wireless network, and the storage module 9 is interactively connected to the missing detection module 6 through a wireless network. The storage module 9 is used to collect the operation data of each module, analyze the success rate, signal loss rate and efficiency index of power adjustment, and perform classified storage and cloud backup; so that the device can perform more comprehensive performance evaluation and analysis, and improve the efficiency and security of data management;

[0056] Signal monitoring module 2 is used to monitor the signal-to-noise ratio, bit error rate and received signal strength according to a preset period, calculate the signal quality index in real time, and perform trend analysis and display on it; it can grasp the signal quality in real time and identify problems in time;

[0057] Feedback generation module 3 is used to aggregate the calculated signal quality indicators from the signal monitoring module 2 to generate comprehensive feedback information. By aggregating various signal quality indicators, a global view is formed to facilitate operators to quickly understand the device status and reduce processing time;

[0058] Feedback evaluation module 4 is used to compare the monitored signal quality index with a preset standard threshold value to determine the current signal state. If the signal quality drops below the threshold, a control signal to increase the transmission power is generated. If the signal quality is good, a control signal to maintain or reduce the transmission power is generated. The signal quality change is detected in time to ensure the reliability of communication and avoid communication interruption caused by signal degradation.

[0059] The power adjustment module 5 dynamically adjusts the transmission power according to the control signal fed back by the feedback evaluation module 4; when the power adjustment module 5 receives a signal to increase the transmission power, it increases the transmission power according to the preset ratio based on the current feedback data, and if the signal is good, it maintains the current power or reduces the transmission power according to the preset ratio; it can automatically adjust the transmission power according to the actual signal quality, thereby realizing intelligent and flexible power management, improving the signal transmission effect, and avoiding excessively high or low signal strength;

[0060] The missing detection module 6 is used to identify the feedback data of the feedback generation module 3 in the next cycle after the power adjustment module 5 is triggered, monitor and identify the missing signal data packets in the signal reception process, compare the received data of the previous cycle with the current received data, record the missing signal data packets, generate a missing report, and record the current operation status; the monitoring mechanism combined with the missing report can efficiently record and handle the problem of data packet loss, while improving the efficiency and accuracy of data recovery, and providing guarantee for the stability of communication;

[0061] Signal prediction module 7, used to establish a prediction model based on historical reception data, current missing report data and current weather data, predict missing signal data according to historical patterns and current conditions, and generate a prediction report; use historical data and current conditions to predict possible signal problems, reduce the risk of communication interruption, and achieve more robust signal management;

[0062] The retransmission control module 8 is used to perform selective retransmission or batch retransmission selection according to the missing report and the prediction result, perform signal retransmission operation, and submit the missing data packets to the transmission control module 1 for retransmission through a preset channel.

[0063] As an implementation method in this embodiment, Figure 1As shown, the transmission control module 1 is interactively connected with the signal monitoring module 2, the power adjustment module 5 and the retransmission control module 8 through a wireless network, the signal monitoring module 2 is interactively connected with the feedback generation module 3 through a wireless network, the feedback generation module 3 is interactively connected with the feedback evaluation module 4 and the missing detection module 6 through a wireless network, the feedback evaluation module 4 is interactively connected with the power adjustment module 5 through a wireless network, the missing detection module 6 is interactively connected with the signal prediction module 7 through a wireless network, and the signal prediction module 7 is interactively connected with the retransmission control module 8 through a wireless network.

[0064] In this embodiment, signals are received and sent through the transmission control module 1, the data transmission process is monitored by the signal monitoring module 2, the abnormal state in the transmission process is fed back through the feedback generation module 3, the degree of abnormality is evaluated through the feedback evaluation module 4, and the power adjustment data of the power adjustment module 5 is used as power adjustment data. The missing data is detected by the missing detection module 6, the missing data is predicted and supplemented by the signal prediction module 7, and then re-received by the retransmission control module 8. This satellite communication transmission equipment can significantly improve the signal transmission quality, enhance the reliability and stability of the system, and at the same time improve the data processing capability, ultimately achieving a more efficient satellite communication experience.

[0065] Example 2

[0066] In other aspects, this embodiment also provides a prediction model. In the process of establishing the prediction model, data collection and preprocessing are performed to extract the features that affect the signal strength. The model is trained through samples through a machine learning algorithm. The specific representation of data collection is as follows:

[0067] Historical received data D = {d1, d2, ..., d n}, where d i represents the received signal strength at the i-th time point;

[0068] Missing report M = {m1,m2,…,m k},m j It means that at time point t j Missing packets;

[0069] Current weather conditions W = {w1, w2, ..., w u}, indicating several weather conditions;

[0070] During the feature extraction process, the historical signal strength feature calculation formula is:

[0071] Where S h is the average value of historical signal strength;

[0072] The missing data feature calculation formula is:

[0073] Where S m is the average number of missing signal packets;

[0074] The weather characteristics calculation formula is:

[0075] Where S w Indicates current weather conditions;

[0076] During model training, the model input is set as a feature combination:

[0077]

[0078] The predicted output is the signal strength y at the next time point t +1, indicating the model's predicted value of the received signal strength at a certain point in the future;

[0079] Let the model be f(X;Q), where Q represents the model parameters and X represents the model input feature vector. The training set is used for optimization, and the expression formula is:

[0080]

[0081] In the formula, y i represents the observed value of the actual received signal strength at the i-th sample time point, which is usually used to calculate the prediction error when training the model. i represents the input feature vector of the i-th sample, and P represents the total number of samples;

[0082] The predicted output is the signal strength y at the next time point t The specific calculation formula of +1 is:

[0083]

[0084] Where V0 represents the intercept term, V1, V2 and V3 represent the regression coefficients of historical received data, current missing report data and current weather data, respectively, indicating the impact of each feature on the signal strength, and e represents the error term, indicating the part not captured by the model. During operation, if the predicted signal strength is significantly lower than the preset threshold, the missing data can be retransmitted according to the prediction results. Through this construction and operation process, effective prediction and processing of signal data missing can be achieved, thereby improving the stability of satellite communications and the integrity of data transmission.

[0085] In summary, the present invention can improve the reliability of signal transmission, offset signal attenuation, and ensure good signal quality through real-time feedback and transmission power adjustment. It can automatically adjust the transmission power and retransmit the signal under poor signal receiving environment, thereby improving the adaptability of the system under various environmental conditions. Through historical data analysis and prediction technology, it can predict the situation of missing signals, further reduce the risk of communication interruption, and improve the integrity of data transmission.

[0086] By intelligently adjusting the transmission power according to the signal quality, it can effectively reduce unnecessary signal interference, optimize energy consumption, and extend the service life of the equipment. For lost data packets, it can quickly take retransmission measures to ensure the integrity and accuracy of data transmission. By dynamically adjusting the transmission power, it can reduce energy waste, reduce operating costs, and achieve higher economic benefits.

[0087] By integrating multiple intelligent controls and optimization measures, the stability and efficiency of communications are greatly improved, with strong adaptability and cost-effectiveness, providing users with high-quality communication services.

[0088] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A satellite communication transmission device, characterized in that: include: A transmission control module (1) is used to provide access rights to the signal receiving and transmitting ends and to edit and operate the operating instructions of each functional module; A signal monitoring module (2) is used to monitor the signal-to-noise ratio, bit error rate and received signal strength of the received signal according to a preset period, calculate the signal quality index in real time, and perform trend analysis and display thereof; A feedback generation module (3) for aggregating the calculated signal quality indicators from the signal monitoring module (2) to generate comprehensive feedback information; A feedback evaluation module (4) is used to compare the monitored signal quality index with a preset standard threshold value to determine the current signal state, and if the signal quality drops below the threshold, generate a control signal to increase the transmission power; if the signal quality is good, generate a control signal to maintain or reduce the transmission power; A power adjustment module (5) dynamically adjusts the transmission power according to the control signal fed back by the feedback evaluation module (4); A missing detection module (6) is used to identify feedback data of the feedback generation module (3) in the next cycle after the power adjustment module (5) is triggered, monitor and identify missing signal data packets in the signal reception process, compare the received data of the previous cycle with the current received data, record the missing signal data packets, generate a missing report, and record the current operation status; A signal prediction module (7), for establishing a prediction model based on historical reception data, current missing report data and current weather data, predicting missing signal data according to historical patterns and current conditions, and generating a prediction report; The retransmission control module (8) is used to perform selective retransmission or batch retransmission selection according to the missing report and the prediction result, perform signal retransmission operation, and submit the missing data packet to the transmission control module (1) for retransmission through a preset channel.

2. A satellite communication transmission device according to claim 1, characterized in that: The transmission control module (1) is interactively connected to a storage module (9) via a wireless network, and the storage module (9) is interactively connected to a missing detection module (6) via a wireless network. The storage module (9) is used to collect operation data of each module, analyze success rate, signal loss rate and efficiency index of power adjustment, and perform classified storage and cloud backup.

3. A satellite communication transmission device according to claim 1, characterized in that: When receiving a signal for increasing the transmission power, the power adjustment module (5) increases the transmission power at a preset ratio based on current feedback data; if the signal is good, the current power is maintained or the transmission power is reduced at a preset ratio.

4. A satellite communication transmission device according to claim 1, characterized in that: The signal prediction module (7) performs data collection and preprocessing during the process of establishing the prediction model, extracts the features that affect the signal strength, and uses machine learning algorithms and samples to train the model. The specific representation of data collection is as follows: Historical received data D = {D1, d2, ..., d n }, where d i represents the received signal strength at the i-th time point; Missing report M = {m1,m2,…,m k },m j It means that at time point t j Missing packets; Current weather conditions W = {w1, w2, ..., w u }, indicating several weather conditions.

5. A satellite communication transmission device according to claim 4, characterized in that: During the process of extracting the features respectively, the historical signal strength feature calculation formula is: Where S h is the average value of historical signal strength; The missing data feature calculation formula is: Where S m is the average number of missing signal packets; The weather characteristics calculation formula is: Where S w Indicates current weather conditions.

6. A satellite communication transmission device according to claim 4, characterized in that: During the model training process, the input of the model is set as a feature combination: The predicted output is the signal strength y at the next time point t +1; Let the model be f(X;Q), where Q represents the model parameters and X represents the model input feature vector. The training set is used for optimization, and the expression formula is: In the formula, y i represents the observed value of the actual received signal strength at the i-th sample time point, X i represents the input feature vector of the i-th sample, and P represents the total number of samples.

7. A satellite communication transmission device according to claim 6, characterized in that: The predicted output is the signal strength y at the next time point t The specific calculation formula of +1 is: Where V0 represents the intercept term, V1, V2 and V3 represent the regression coefficients of historical reception data, current missing report data and current weather data, respectively, and e represents the error term.

8. A satellite communication transmission device according to claim 1, characterized in that: The transmission control module (1) is interactively connected with the signal monitoring module (2), the power adjustment module (5) and the retransmission control module (8) via a wireless network; the signal monitoring module (2) is interactively connected with the feedback generation module (3) via a wireless network; the feedback generation module (3) is interactively connected with the feedback evaluation module (4) and the missing detection module (6) via a wireless network; the feedback evaluation module (4) is interactively connected with the power adjustment module (5) via a wireless network; the missing detection module (6) is interactively connected with the signal prediction module (7) via a wireless network; and the signal prediction module (7) is interactively connected with the retransmission control module (8) via a wireless network.

Images