Satellite communication transmission equipment

Abstract

The present invention discloses a satellite communication transmission device, which relates to the field of communication transmission and includes: a transmission control module, which is used to provide access rights for signal receiving and transmitting ends, and to edit and operate the operation instructions of each functional module; a signal monitoring module, which is used to monitor the signal-to-noise ratio, bit error rate and received signal strength of signal reception according to a preset period, calculate signal quality indicators in real time, and perform trend analysis and display thereof; a feedback generation module, which is used to aggregate the calculated signal quality indicators from the signal monitoring module and generate comprehensive feedback information; it can quickly respond to changes in signal quality, generate a control signal by comparing the real-time signal quality with a preset standard threshold, intelligently adjust the transmission power according to environmental changes, generate a missing report according to historical and current data, timely identify and record missing data packets, use a prediction model based on historical data and real-time signal status, intelligently analyze potential data missing trends, and generate a recovery plan.

Description

Technical Field

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

[0002] With the acceleration of globalization, multinational companies and international organizations are increasingly demanding efficient and reliable communication tools. Satellite communications can transcend national borders and provide services to users worldwide. Many remote areas or oceans lack traditional terrestrial communication infrastructure. Satellite communications can fill this gap, enabling users in these areas to enjoy communication services. Satellite communications are widely used in many industries, including 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. This results in a failure to take timely action when signal quality degrades, impacting communication quality. Static transmit power settings in existing equipment may not adapt to real-time environmental changes, resulting in insufficient or excessive signal strength. Data packets may be lost during signal transmission, but the mechanisms for processing and recovering lost data are inadequate.

[0004] Traditional communication transmission equipment has difficulty integrating 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 comprehensively evaluate equipment performance. Summary of the Invention

[0005] (1) Technical problems solved

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

[0007] (2) 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 at preset intervals, calculate signal quality indicators 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 is generated to increase the transmit power. If the signal quality is good, a control signal is generated to maintain or reduce the transmit power.

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

[0015] A missing detection module is used to identify feedback data from the feedback generation module in the next cycle after the power adjustment module is triggered, monitor and identify missing signal data packets during the signal reception process, compare the received data in 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 build 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 based on the missing report and prediction results, perform signal retransmission operations, and submit the missing data packets to the transmission control module for retransmission through the 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 power adjustment efficiency indicators, 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 according to a preset ratio based on the current feedback data. If the signal is good, it maintains the current power or reduces the transmission power according to 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 uses machine learning algorithms to train the model through samples. The specific representation of data collection is as follows:

[0021] Historical received data D = {d1, d2, ..., d h}, 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 represents the time point t j Missing data packets;

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

[0024] Furthermore, during the feature extraction process, the historical signal strength feature calculation formula is:

[0025]

[0026] Among them S h is the average value of historical signal strength, and n represents the total number of historical signal strength features;

[0027] The missing data feature calculation formula is:

[0028]

[0029] Among them S m is the average number of missing signal packets, k represents the total number of missing signal packets;

[0030] The weather characteristics calculation formula is:

[0031]

[0032] Among them S w represents the current weather conditions, and u represents the total number of weather conditions.

[0033] Furthermore, during the model training process, the model input 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] Where 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 t The specific calculation formula for +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, e represents the error term, and w j Represents the jth weather condition.

[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 absence detection module through a wireless network, the feedback evaluation module is interactively connected to the power adjustment module through a wireless network, the absence 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] (3) Beneficial effects

[0044] Compared with the 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 signal quality indicators in real time, the system can promptly understand the signal status and quickly respond to changes in signal quality to ensure communication stability. It compares the real-time signal quality with the preset standard threshold, generates a control signal, and intelligently adjusts the transmit power according to environmental changes, thereby improving communication quality, reducing energy waste, and avoiding interference caused by excessively strong signals.

[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 data recovery efficiency, and enhancing system reliability, 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 operating parameters according to different environmental changes and needs, better adapt to various working conditions, ensure stable communication quality, and through comprehensive optimization of transmission power and signal quality, enable the system to operate 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 more quickly. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] 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 description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort.

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

[0050] The numbers in the figure represent: 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] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only 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 efforts are within the scope of protection of the present invention.

[0052] The present invention will be further described below with reference to 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 to the signal receiving and transmitting terminals and to edit and execute the operating instructions of each functional module. The transmission control module 1 is interactively connected to the storage module 9 via a wireless network. The storage module 9 is interactively connected to the loss detection module 6 via a wireless network. The storage module 9 is used to collect the operating data of each module, analyze the success rate, signal loss rate and power adjustment efficiency indicators, classify and store them, and back them up in the cloud. This enables the device to perform more comprehensive performance evaluation and analysis, improving 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 at preset intervals, calculate signal quality indicators in real time, and perform trend analysis and display. This allows for real-time monitoring of signal quality and timely identification of problems.

[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, which makes it easier for 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 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. This module promptly detects changes in signal quality to ensure communication reliability and avoid communication interruptions caused by signal degradation.

[0059] The power adjustment module 5 dynamically adjusts the transmit power based on the control signal fed back by the feedback evaluation module 4. When receiving a signal to increase the transmit power, the power adjustment module 5 increases the transmit power by a preset ratio based on the current feedback data. If the signal is good, the current power is maintained or the transmit power is reduced by a preset ratio. The transmit power can be automatically adjusted according to the actual signal quality, thereby realizing intelligent and flexible power management, improving signal transmission quality, 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 signal data packets that are missing during 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 operating status. The monitoring mechanism combined with the missing report can efficiently record and handle data packet loss problems, while improving the efficiency and accuracy of data recovery, providing protection for communication stability.

[0061] Signal prediction module 7 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. It uses 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 the preset channel.

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

[0064] In this embodiment, signals are received and sent by 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 by the feedback generation module 3, the degree of abnormality is evaluated by the feedback evaluation module 4, and the power adjustment data is used as the power adjustment data of the power adjustment module 5. 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, and ultimately achieve a more efficient satellite communication experience.

[0065] Example 2

[0066] In other aspects, this embodiment also provides a prediction model. During the establishment of the prediction model, data collection and preprocessing are performed to extract features that affect signal strength. The model is trained using 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 jIt represents the time point t j Missing data 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] Among them S h is the average value of historical signal strength, and n represents the total number of historical signal strength features;

[0072] The missing data feature calculation formula is:

[0073] Among them S m is the average number of missing signal packets, k represents the total number of missing signal packets;

[0074] The weather characteristics calculation formula is:

[0075] Among them S w represents the current weather conditions, and u represents the total number of 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 indicates 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] Where 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 for +1 is:

[0083]

[0084] 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, indicating the impact of each feature on signal strength, e represents the error term, indicating the part not captured by the model, and w j Represents the jth weather condition. During operation, if the predicted signal strength is significantly lower than the preset threshold, the missing data can be retransmitted according to the prediction result. 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 improves signal transmission reliability, offsets signal attenuation, and ensures good signal quality through real-time feedback and transmit power adjustment. It can automatically adjust transmit power and retransmit signals even in poor signal reception environments, enhancing the system's adaptability to various environmental conditions. Through historical data analysis and prediction technology, it can predict signal loss, further reducing the risk of communication interruptions and improving data transmission integrity.

[0086] By intelligently adjusting the transmit power based on 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 transmit power, it can reduce energy waste, lower operating costs, and achieve higher economic benefits.

[0087] By integrating multiple intelligent control and optimization measures, the stability and efficiency of communications are greatly improved. It is highly adaptable and cost-effective, 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, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these 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 various embodiments of the present invention.

Claims

1. A satellite communication transmission device, characterized in that: include: The transmission control module (1) is used to provide access rights to the signal receiving and transmitting terminals and to edit and execute the operation 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 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) for identifying feedback data from the feedback generation module (3) in the next cycle after the power adjustment module (5) is triggered, monitoring and identifying missing signal data packets during the signal reception process, comparing the received data of the previous cycle with the current received data, recording the missing signal data packets, generating a missing report, and recording the current operation status; A signal prediction module (7) 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; 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.

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. 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 operating data of each module, analyze the success rate, signal loss rate and efficiency index of power adjustment, perform classified storage and back up in the cloud.

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

4. The 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 to train the model through samples. 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 represents the time point t j Missing data packets; Current weather conditions W = {w1, w2, ..., w u }, indicating several weather conditions.

5. The satellite communication transmission equipment according to claim 4, characterized in that: During the feature extraction process, the historical signal strength feature calculation formula is: Among them S h is the average value of historical signal strength, and n represents the total number of historical signal strength features; The missing data feature calculation formula is: Among them S m is the average number of missing signal packets, k represents the total number of missing signal packets; The weather characteristics calculation formula is: Among them S w represents the current weather conditions, and u represents the total number of weather conditions.

6. The satellite communication transmission equipment according to claim 4, characterized in that: During the model training process, the input of the model is set as the 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: Where 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. The satellite communication transmission equipment 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 for +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, e represents the error term, and w j Represents the jth weather condition.

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

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