Short-wave intelligent frequency selection communication system and method

Abstract

The embodiment of the invention provides a short-wave intelligent frequency selection communication system and method. The system comprises an ionosphere maximum available frequency prediction module, an optimal working frequency prediction module, a short-wave communication quality grade rapid evaluation module, a short-wave link frequency switching module and a short-wave link relay intelligent judgment module. Aiming at the problems that the traditional frequency selection technology is difficult to track the change of the ionized layer and is difficult to perceive the channel quality in real time, key technologies such as the maximum available frequency prediction of the ionized layer, the optimal working frequency prediction, the short-wave communication quality grade rapid evaluation, the short-wave link frequency switching, the short-wave link relay intelligent judgment and the like are utilized; short-wave intelligent frequency selection and relay enhancement which adapt to complex ionized layer changes and perceive channel quality in real time are achieved, and short-wave communication quality is effectively improved.

Description

Technical Field

[0001] This invention relates to the field of frequency selective communication technology, and in particular to a shortwave intelligent frequency selective communication system and method. Background Technology

[0002] In applications such as emergency rescue and disaster relief, and long-distance maritime command, shortwave communication has become a backup communication method for long-distance communication due to its long communication distance, concealment, and strong anti-interference capabilities. However, due to factors such as increasingly crowded shortwave spectrum and the significant impact of ionospheric fluctuations on shortwave frequencies, especially when solar flares or geomagnetic storms cause drastic changes in the ionosphere, the optimal operating frequency of shortwave can change, severely affecting communication quality and even leading to communication outages. Traditional methods for determining the optimal operating frequency of shortwave include long-term frequency prediction, short-term frequency prediction, and real-time frequency detection. Among these, long-term frequency prediction suffers from low prediction accuracy due to its large time scale. Short-term frequency prediction mainly relies on historical communication data and cannot adapt to dynamic changes in the ionosphere in real time. Real-time frequency detection is typically represented by the Chirp detection method, but it is highly dependent on the Chirp detection system and its frequency selection accuracy cannot be guaranteed under conditions of rapid ionospheric changes or strong interference. Summary of the Invention

[0003] In view of the above-mentioned problems in the prior art, the present invention provides a shortwave intelligent frequency selective communication system and method to solve the technical problems of insufficient real-time performance and accuracy of shortwave frequency selection under complex ionospheric background and poor quality of long-distance shortwave communication in the prior art.

[0004] This invention provides a shortwave intelligent frequency-selective communication system, comprising:

[0005] The ionospheric maximum available frequency prediction module, by real-time detection of the existing ionospheric state, utilizes the strong coupling relationship between the solar activity factor of the reflection point, the seasonal factor, the principal latitude factor, the daily time factor and the maximum available frequency of the E layer and F2 layer of the ionosphere to predict the maximum available frequency based on the input spatiotemporal data.

[0006] The optimal operating frequency prediction module is used to predict the optimal shortwave operating frequency to adapt to dynamic changes in the ionosphere.

[0007] The shortwave communication quality level rapid assessment module combines indicators including bit error rate, transmission rate, and latency to achieve real-time quality level assessment of the communication channel.

[0008] The shortwave link frequency switching module, based on the shortwave communication quality level assessment results, activates the optimal operating frequency prediction module when the communication quality deteriorates to below the threshold level, and re-predicts and switches the optimal operating frequency.

[0009] The shortwave link relay intelligent discrimination module is used to activate the shortwave link relay function and change the destination address to the shortwave link relay station when the number of optimal operating frequency switching exceeds the threshold and the shortwave communication quality level rapid assessment result still does not improve. This achieves shortwave link relay enhancement and improves shortwave communication quality under extremely poor channel conditions.

[0010] In one embodiment, the optimal operating frequency prediction module has two operating modes.

[0011] Mode 1: Based on the predicted maximum available frequency of each layer, predict the optimal operating frequency that can adapt to changes in the ionosphere in real time. At the same time, combine the historical optimal operating frequency dataset to train an optimal operating frequency prediction model based on a multi-head attention mechanism to predict the optimal shortwave operating frequency that adapts to the dynamic changes in the ionosphere.

[0012] Mode 2: Best operating frequency prediction based solely on the historical best operating frequency dataset.

[0013] In one embodiment, the ionospheric maximum available frequency prediction module includes,

[0014] The input module is used to input the geographical latitude and longitude of the transmitting point, the geographical latitude and longitude of the receiving point, the antenna elevation angle of the transmitting point, and the world time.

[0015] The control point parameter module is used to predict parameters including the geomagnetic latitude and longitude, geographic latitude and longitude, solar activity factor, solar inclination, and activity angle of the control point based on the input parameters from the input module.

[0016] The maximum available frequency prediction module is used to predict the maximum available frequency of layer E and layer F2 based on the input parameters of the input module and the prediction parameters of the control point parameter prediction module.

[0017] The output module is used to output and save the prediction parameters.

[0018] In one embodiment, the shortwave communication quality level rapid assessment module includes,

[0019] A shortwave communication quality level evaluation index system is constructed based on parameters including bit error rate, transmission rate, and latency, and a shortwave communication quality level evaluation dataset is generated based on the analytic hierarchy process and fuzzy comprehensive evaluation method.

[0020] A decision tree model is used to extract data features and train a module for rapid evaluation of shortwave communication quality levels.

[0021] In one embodiment, after the shortwave communication quality level rapid assessment module performs a rapid assessment of the current communication link level, the shortwave link frequency switching module determines the level. If the communication quality level is higher than the threshold, the optimal operating frequency prediction module mode two is activated; if the communication quality level is lower than the threshold, the optimal operating frequency prediction module mode one is activated.

[0022] In one embodiment, the control point parameter module utilizes a deep neural network to predict parameters.

[0023] In one embodiment, in Mode 1, the optimal operating frequency prediction module uses a recurrent neural network to predict the optimal operating frequency that can adapt to changes in the ionosphere in real time.

[0024] In addition, embodiments of the present invention also provide a shortwave intelligent frequency selective communication method, implemented based on the shortwave intelligent frequency selective communication system as described in some embodiments of the present invention, including the following steps:

[0025] Step S101: Input the geographical latitude and longitude of the transmitting point, the geographical latitude and longitude of the receiving point, the antenna elevation angle of the transmitting point, and the world time. Then, use the ionospheric maximum available frequency prediction module to output parameters including the geomagnetic latitude and longitude of the control point, the geographical latitude and longitude, the solar activity factor, the solar inclination angle, and the activity angle.

[0026] In step S102, combining the input parameters and predicted output parameters from step S101, the ionospheric maximum available frequency prediction module predicts the maximum available frequencies of the E layer, F1 layer, and F2 layer, and outputs and saves them.

[0027] Step S103: Utilize the optimal operating frequency prediction module in operating mode one to predict the optimal operating frequency.

[0028] Step S104: Establish and communicate based on the optimal operating frequency, and record indicators including link error rate, transmission rate, and latency.

[0029] Step S105: Use the shortwave communication quality level rapid evaluation module to evaluate the link quality level. If the evaluation level result is higher than the threshold, proceed to step S106; otherwise, proceed to step S107.

[0030] Step S106: Utilize the optimal operating frequency prediction module in operating mode two to predict the optimal operating frequency, and proceed to step S104.

[0031] In step S107, the shortwave link relay intelligent discrimination module determines whether to enable the relay enhancement function. If it needs to be enabled, the destination address is changed to the shortwave link relay station to achieve shortwave link relay enhancement. Otherwise, proceed to step S103.

[0032] Compared with existing technologies, the beneficial effects of the shortwave intelligent frequency selection communication system and method provided by the embodiments of the present invention are as follows: The embodiments of the present invention address the problems that traditional frequency selection technologies have difficulty in tracking ionospheric changes and in real-time sensing of channel quality. By utilizing key technologies such as prediction of the maximum available frequency of the ionosphere, prediction of the optimal operating frequency, rapid assessment of shortwave communication quality level, shortwave link frequency switching, and intelligent identification of shortwave link relays, the present invention achieves shortwave intelligent frequency selection and relay enhancement that adapts to complex ionospheric changes and senses channel quality in real time, effectively improving shortwave communication quality. Attached Figure Description

[0033] Figure 1 This is a schematic diagram of the composition of a shortwave intelligent frequency selective communication system provided in an embodiment of the present invention;

[0034] Figure 2 A schematic diagram of the composition of the ionospheric maximum available frequency prediction module in a shortwave intelligent frequency selective communication system provided in an embodiment of the present invention;

[0035] Figure 3 This is a schematic diagram illustrating the composition of an optimal operating frequency prediction module in a shortwave intelligent frequency selective communication system provided in an embodiment of the present invention.

[0036] Figure 4 A schematic diagram of the composition of a rapid evaluation module for shortwave communication quality level in a shortwave intelligent frequency selective communication system provided in an embodiment of the present invention;

[0037] Figure 5 This is a schematic diagram of the composition of a shortwave link frequency switching module in a shortwave intelligent frequency selective communication system provided in an embodiment of the present invention;

[0038] Figure 6 This is a schematic flowchart of a shortwave intelligent frequency-selective communication method provided in an embodiment of the present invention. Detailed Implementation

[0039] To enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0040] Various embodiments and features of this application are described herein with reference to the accompanying drawings.

[0041] These and other features of this application will become apparent from the following description of preferred forms of embodiments given as non-limiting examples, with reference to the accompanying drawings.

[0042] It should also be understood that although this application has been described with reference to some specific examples, those skilled in the art can certainly implement many other equivalent forms of this application, which have the features described in the claims and are therefore all within the scope of protection defined herein.

[0043] The above and other aspects, features and advantages of this application will become more apparent when taken in conjunction with the accompanying drawings and in view of the following detailed description.

[0044] Specific embodiments of this application are described below with reference to the accompanying drawings; however, it should be understood that the claimed embodiments are merely examples of this application, which can be implemented in various ways. Well-known and / or repeated functions and structures are not described in detail to ascertain the true intent based on the user's historical operations, and to avoid unnecessary or redundant details that would obscure this application. Therefore, the specific structural and functional details claimed herein are not intended to be limiting, but merely serve as the basis and representative basis for the claims to teach those skilled in the art to use this application in various ways with substantially any suitable detailed structure.

[0045] This specification may use the phrases “in one embodiment,” “in another embodiment,” “in yet another embodiment,” or “in other embodiments,” all of which may refer to one or more of the same or different embodiments according to this application.

[0046] The principles and features of the present invention are described below with reference to the accompanying drawings. The embodiments described are for illustrative purposes only and are not intended to limit the scope of the invention. The following description, in conjunction with... Figure 1-6 The preferred embodiments of the present invention will be described in further detail below:

[0047] like Figure 1-5 As shown, an embodiment of the present invention provides a shortwave intelligent frequency selective communication system, comprising:

[0048] The ionospheric maximum available frequency prediction module, by real-time detection of the existing ionospheric state, utilizes the strong coupling relationship between the solar activity factor of the reflection point, the seasonal factor, the principal latitude factor, the daily time factor and the maximum available frequency of the E layer and F2 layer of the ionosphere to predict the maximum available frequency based on the input spatiotemporal data.

[0049] The optimal operating frequency prediction module is used to predict the optimal shortwave operating frequency to adapt to dynamic changes in the ionosphere.

[0050] The shortwave communication quality level rapid assessment module combines indicators including bit error rate, transmission rate, and latency to achieve real-time quality level assessment of the communication channel.

[0051] The shortwave link frequency switching module, based on the shortwave communication quality level assessment results, activates the optimal operating frequency prediction module when the communication quality deteriorates to below the threshold level, and re-predicts and switches the optimal operating frequency.

[0052] The shortwave link relay intelligent discrimination module is used to activate the shortwave link relay function and change the destination address to the shortwave link relay station when the number of optimal operating frequency switching exceeds the threshold and the shortwave communication quality level rapid assessment result still does not improve. This achieves shortwave link relay enhancement and improves shortwave communication quality under extremely poor channel conditions.

[0053] In one embodiment, the optimal operating frequency prediction module has two operating modes.

[0054] Mode 1: Based on the predicted maximum available frequency of each layer, predict the optimal operating frequency that can adapt to changes in the ionosphere in real time. At the same time, combine the historical optimal operating frequency dataset to train an optimal operating frequency prediction model based on a multi-head attention mechanism to predict the optimal shortwave operating frequency that adapts to the dynamic changes in the ionosphere.

[0055] Mode 2: Best operating frequency prediction based solely on the historical best operating frequency dataset.

[0056] In one embodiment, the ionospheric maximum available frequency prediction module includes,

[0057] The input module is used to input the geographical latitude and longitude of the transmitting point, the geographical latitude and longitude of the receiving point, the antenna elevation angle of the transmitting point, and the world time.

[0058] The control point parameter module is used to predict parameters including the geomagnetic latitude and longitude, geographic latitude and longitude, solar activity factor, solar inclination, and activity angle of the control point based on the input parameters from the input module.

[0059] The maximum available frequency prediction module is used to predict the maximum available frequency of layer E and layer F2 based on the input parameters of the input module and the prediction parameters of the control point parameter prediction module.

[0060] The output module is used to output and save the prediction parameters.

[0061] In one embodiment, the shortwave communication quality level rapid assessment module includes,

[0062] A shortwave communication quality level evaluation index system is constructed based on parameters including bit error rate, transmission rate, and latency, and a shortwave communication quality level evaluation dataset is generated based on the analytic hierarchy process and fuzzy comprehensive evaluation method.

[0063] A decision tree model is used to extract data features and train a module for rapid evaluation of shortwave communication quality levels.

[0064] In one embodiment, after the shortwave communication quality level rapid assessment module performs a rapid assessment of the current communication link level, the shortwave link frequency switching module determines the level. If the communication quality level is higher than the threshold, the optimal operating frequency prediction module mode two is activated; if the communication quality level is lower than the threshold, the optimal operating frequency prediction module mode one is activated.

[0065] In one embodiment, the control point parameter module utilizes a deep neural network to predict parameters.

[0066] In one embodiment, in Mode 1, the optimal operating frequency prediction module uses a recurrent neural network to predict the optimal operating frequency that can adapt to changes in the ionosphere in real time.

[0067] like Figure 6 As shown, in addition, embodiments of the present invention also provide a shortwave intelligent frequency selective communication method, implemented based on the shortwave intelligent frequency selective communication system as described in some embodiments of the present invention, including the following steps:

[0068] Step S101: Input the geographical latitude and longitude of the transmitting point, the geographical latitude and longitude of the receiving point, the antenna elevation angle of the transmitting point, and the world time. Then, use the ionospheric maximum available frequency prediction module to output parameters including the geomagnetic latitude and longitude of the control point, the geographical latitude and longitude, the solar activity factor, the solar inclination angle, and the activity angle.

[0069] In step S102, combining the input parameters and predicted output parameters from step S101, the ionospheric maximum available frequency prediction module predicts the maximum available frequencies of the E layer, F1 layer, and F2 layer, and outputs and saves them.

[0070] Step S103: Utilize the optimal operating frequency prediction module in operating mode one to predict the optimal operating frequency.

[0071] Step S104: Establish and communicate based on the optimal operating frequency, and record indicators including link error rate, transmission rate, and latency.

[0072] Step S105: Use the shortwave communication quality level rapid evaluation module to evaluate the link quality level. If the evaluation level result is higher than the threshold, proceed to step S106; otherwise, proceed to step S107.

[0073] Step S106: Utilize the optimal operating frequency prediction module in operating mode two to predict the optimal operating frequency, and proceed to step S104.

[0074] In step S107, the shortwave link relay intelligent discrimination module determines whether to enable the relay enhancement function. If it needs to be enabled, the destination address is changed to the shortwave link relay station to achieve shortwave link relay enhancement. Otherwise, proceed to step S103.

[0075] Example 1

[0076] Based on the technical problems described in the background section, this invention proposes a shortwave intelligent frequency-selective communication system. It fully utilizes real-time ionospheric sensing and detection, and historical optimal operating frequency extraction. To alleviate the problems of reduced frequency selection efficiency and high resource consumption caused by real-time ionospheric sensing, two shortwave link frequency switching modes are proposed. When channel quality degradation is not significant, the optimal operating frequency is mainly predicted based on historical data. When the channel quality degradation threshold is below a certain level, both historical optimal operating frequency and real-time ionospheric sensing are used for prediction. Furthermore, to adapt to shortwave communication under extremely harsh channel conditions, a shortwave link relay intelligent discrimination module is used to enhance shortwave link relay capabilities. This invention addresses the difficulties of traditional frequency selection techniques in tracking ionospheric changes and sensing channel quality in real time. By combining deep neural networks, multi-attention mechanism algorithms, recurrent neural networks, and decision tree algorithms, it achieves shortwave frequency selection that adapts to complex ionospheric changes and senses channel quality in real time. This improves the real-time performance and accuracy of shortwave frequency selection under complex ionospheric conditions and enhances the quality of long-distance shortwave communication.

[0077] This invention discloses a shortwave intelligent frequency-selective communication system, mainly comprising an ionospheric maximum available frequency prediction module, an optimal operating frequency prediction module, a shortwave communication quality level rapid evaluation module, a shortwave link frequency switching module, and a shortwave link relay intelligent discrimination module. Shortwave communication is an important long-distance backup communication method, but it suffers from limited spectrum resources and channel disturbances caused by complex ionospheric changes, leading to changes in the optimal shortwave communication frequency. The prediction and selection of shortwave communication frequencies are crucial for the stability and reliability of shortwave communication. The system proposed in this invention mainly solves the problems of traditional frequency selection techniques struggling to track ionospheric changes and perceive channel quality in real time, improving the real-time performance and accuracy of shortwave frequency selection under complex ionospheric conditions, and enhancing the quality of long-distance shortwave communication.

[0078] A module for predicting the maximum available frequency of the ionosphere is constructed. By detecting the existing state of the ionosphere in real time, and utilizing the strong coupling relationship between the solar activity factor of the reflection point, the seasonal factor, the principal latitude factor, the daily time factor, and the maximum available frequency of the E and F2 layers of the ionosphere, a deep neural network is used to predict the maximum available frequency based on the input spatiotemporal data.

[0079] A module for predicting optimal operating frequencies is constructed, with two operating modes. Mode 1 uses a recurrent neural network (RNN) to predict the optimal operating frequency that can adapt to changes in the ionosphere in real time, based on the predicted maximum available frequencies of each layer. Simultaneously, a multi-head attention mechanism-based optimal operating frequency prediction model is trained using a historical optimal operating frequency dataset to achieve shortwave optimal operating frequency prediction that adapts to dynamic changes in the ionosphere. Mode 2 is the optimal operating frequency prediction based solely on a historical optimal operating frequency dataset.

[0080] A rapid evaluation module for shortwave communication quality level is constructed. Combining indicators such as bit error rate, transmission rate, and latency, and utilizing fuzzy comprehensive evaluation method, hierarchical analysis method, and decision tree algorithm, the real-time quality level evaluation of communication channels is realized.

[0081] A shortwave link frequency switching module is constructed. Based on the shortwave communication quality level assessment results, when the communication quality deteriorates to below the threshold level, the optimal operating frequency prediction module is activated. Combined with the mode one function of the optimal operating frequency prediction module, the optimal operating frequency is re-predicted and switched.

[0082] A shortwave link relay intelligent discrimination module is constructed. If the shortwave communication quality level does not improve after the number of optimal operating frequency switching exceeds the threshold, the shortwave link relay function is enabled, the destination address is changed to the shortwave link relay station, and shortwave link relay enhancement is achieved, thereby improving the shortwave communication quality under extremely poor channel conditions.

[0083] Specifically, the embodiments of the present invention mainly consist of an ionospheric maximum available frequency prediction module, an optimal operating frequency prediction module, a shortwave communication quality level rapid evaluation module, a shortwave link frequency switching module, and a shortwave link relay intelligent discrimination module, etc., and the system structure is as follows: Figure 1-5 As shown.

[0084] The ionospheric maximum available frequency prediction module consists of an input module, a control point parameter prediction module, a maximum available frequency prediction module, and an output module. The input module is used to input the geographic latitude and longitude of the transmitting and receiving points, the antenna elevation angle of the transmitting point, and UTC. The control point parameter module uses a deep neural network to predict parameters such as the geomagnetic latitude and longitude, geographic latitude and longitude, solar activity factor, solar inclination, and activity angle of the control points based on the parameters from the input module. The maximum available frequency prediction module predicts the maximum available frequencies of the E and F2 layers based on the outputs from the input module and the control point parameter prediction module. The output module outputs and saves the predicted parameters.

[0085] The optimal operating frequency prediction module has two operating modes. Mode 1 mainly consists of an RNN-based optimal operating frequency prediction module adapted to ionospheric changes and an optimal operating frequency prediction module 1 based on a multi-head attention mechanism. In Mode 1, the optimal operating frequency prediction module, which combines the real-time ionospheric state, predicts the optimal operating frequency that adapts to ionospheric changes based on a recurrent neural network (RNN). Optimal operating frequency prediction module 1 utilizes a multi-head attention mechanism, based on an encoder-decoder prediction model, to combine the real-time ionospheric state with historical best operating frequencies to achieve the final prediction of the optimal operating frequency. Mode 2 consists of an optimal operating frequency prediction module 2 based on a multi-head attention mechanism, which only predicts the optimal operating frequency based on the historical best operating frequency dataset.

[0086] The shortwave communication quality level rapid assessment module mainly consists of a shortwave channel quality level assessment index dataset and a shortwave communication quality level assessment module based on a decision tree model. A shortwave communication quality level assessment index system is constructed based on bit error rate, transmission rate, and latency. The shortwave communication quality level assessment dataset is generated using the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation method. Data feature extraction is performed using a decision tree model, which is then used to train and generate the shortwave communication quality level rapid assessment module.

[0087] Shortwave Link Frequency Switching Module: After the shortwave communication quality level rapid assessment module performs a rapid assessment of the current communication link level, the shortwave link frequency switching module determines the level. If the communication quality level is higher than the threshold, the optimal operating frequency prediction module (mode two) is activated. If the communication quality level is lower than the threshold, the optimal operating frequency prediction module (mode one) is activated.

[0088] Shortwave link relay intelligent discrimination module: When the shortwave link frequency switching module continuously selects mode 2 for more than the threshold number of times, but the output level of the shortwave communication quality level rapid evaluation module is still lower than the threshold level, shortwave link relay is enabled, the destination address is changed to the shortwave link relay station, the relay station receives the shortwave signal from the transmitting station, and forwards it to the receiving station after amplification, regeneration or remodulation.

[0089] like Figure 6 As shown, this embodiment of the invention also provides a shortwave intelligent frequency selective communication method, implemented based on a shortwave intelligent frequency selective communication system based on a multi-head attention mechanism as described in some embodiments of the invention, including the following steps:

[0090] In step S101, the geographical latitude and longitude of the transmitting point, the geographical latitude and longitude of the receiving point, the antenna elevation angle of the transmitting point, and the Universal Time are input. The control point parameter prediction module outputs parameters such as the geomagnetic latitude and longitude, geographical latitude and longitude, solar activity factor, solar inclination, and activity angle of the control point. The construction process of the control point parameter prediction module first obtains the control point parameters based on the relevant ITU-R parameters and a complex mathematical model according to the input transmitting point parameters, generating training and test sets. Based on these, the control point parameter prediction model is trained and obtained.

[0091] In step S102, combining the parameters from the input module and the control point parameter module, the maximum available frequency prediction module predicts the maximum available frequencies for layers E, F1, and F2, and outputs and saves them through the output module. The construction process of the maximum available frequency prediction module first obtains the maximum available frequency based on relevant ITU-R parameters and complex mathematical models, generates training and test sets, and then trains and obtains the maximum available frequency prediction model based on these sets.

[0092] In step S103, the optimal operating frequency prediction module is used in operating mode one to achieve the final prediction of the optimal operating frequency by combining the real-time ionospheric state with the historical best operating frequency.

[0093] The construction process of the RNN-based optimal operating frequency prediction module for adapting to ionospheric changes is as follows: First, training and test sets are generated based on the traditional optimal operating frequency calculation method. When the maximum available frequency is determined by the E layer, the optimal operating frequency = maximum available frequency × 0.95. When the maximum available frequency is determined by the F2 layer, ... in The value is affected by factors such as season, sunspot number, and latitude, and is obtained through a lookup table method. Based on training and testing sets, an optimal operating frequency prediction module is trained and tested to obtain the maximum available frequency sequence within the time interval t1-t2. 2+1 The optimal operating frequency at any given time.

[0094] Construction process of the optimal operating frequency prediction module 1 based on the multi-attention mechanism: A Transform encoder-decoder model is constructed. The prediction model is trained and tested based on the historical optimal operating frequency dataset and the optimal operating frequency prediction results adapted to ionospheric changes. The input is t1-t from the historical dataset. 2-1 The best operating frequency sequence within the time period and the best operating frequency at time t2 that adapts to real-time changes in the ionosphere are output as the best operating frequency at time t2 in the historical dataset.

[0095] In step S104, link establishment and communication are performed based on the optimal operating frequency, and indicators such as link error rate, transmission rate, and latency are recorded.

[0096] In step S105, the link quality level is evaluated using the shortwave communication quality level rapid evaluation module. When the evaluation level result is higher than the threshold, the process proceeds to step S106, where the optimal operating frequency prediction module (operating mode 2) is used to achieve the final prediction of the optimal operating frequency by combining historical optimal operating frequencies. The construction process of the optimal operating frequency prediction module 2 based on the multi-attention mechanism is as follows: a Transform encoder-decoder model is constructed, and the prediction model is trained and tested based on the historical optimal operating frequency dataset. The input is t1-t from the historical dataset. 2-1 The best operating frequency sequence within a time period is output as the best operating frequency at time t2 in the historical dataset.

[0097] When the evaluation result exceeds the threshold, proceed to step S107. The shortwave link relay intelligent discrimination module selects whether to enable the relay enhancement function based on the number of consecutive switches to mode one. If the number exceeds the threshold, proceed to step S108 to enable the shortwave link relay enhancement function and change the transmitter station's communication destination address to the relay station. Otherwise, proceed to step S103, where the optimal operating frequency prediction module operates in mode one to achieve the final prediction of the optimal operating frequency by combining real-time ionospheric conditions and historical best operating frequencies. This enables a frequency selection strategy that can sense real-time changes in the ionosphere when the perceived channel quality deteriorates.

[0098] The above embodiments are merely exemplary embodiments of the present invention and are not intended to limit the present invention. The scope of protection of the present invention is defined by the claims. Those skilled in the art can make various modifications or equivalent substitutions to the present invention within its spirit and scope of protection, and such modifications or equivalent substitutions should also be considered to fall within the scope of protection of the present invention.

Claims

1. A shortwave intelligent frequency-selective communication system, characterized in that, include: The ionospheric maximum available frequency prediction module, by real-time detection of the existing ionospheric state, utilizes the strong coupling relationship between the solar activity factor of the reflection point, the seasonal factor, the principal latitude factor, the daily time factor and the maximum available frequency of the E layer and F2 layer of the ionosphere to predict the maximum available frequency by inputting spatiotemporal data. The optimal operating frequency prediction module is used to predict the optimal shortwave operating frequency to adapt to dynamic changes in the ionosphere. The shortwave communication quality level rapid assessment module combines indicators including bit error rate, transmission rate, and latency to achieve real-time quality level assessment of the communication channel. The shortwave link frequency switching module, based on the shortwave communication quality level assessment results, activates the optimal operating frequency prediction module when the communication quality deteriorates to below the threshold level, and re-predicts and switches the optimal operating frequency. The shortwave link relay intelligent discrimination module is used to enable the shortwave link relay function and change the destination address to the shortwave link relay station when the number of optimal operating frequency switching exceeds the threshold and the shortwave communication quality level rapid assessment result still does not improve. This achieves shortwave link relay enhancement and improves shortwave communication quality under extremely poor channel conditions.

2. The shortwave intelligent frequency selective communication system according to claim 1, characterized in that: The optimal operating frequency prediction module has two operating modes. Mode 1: Based on the predicted maximum available frequency of each layer, predict the optimal operating frequency that can adapt to changes in the ionosphere in real time. At the same time, combine the historical optimal operating frequency dataset to train an optimal operating frequency prediction model based on a multi-head attention mechanism to predict the optimal shortwave operating frequency that adapts to the dynamic changes in the ionosphere. Mode 2: Best operating frequency prediction based solely on the historical best operating frequency dataset.

3. The shortwave intelligent frequency-selective communication system according to claim 2, characterized in that: The ionospheric maximum available frequency prediction module includes, The input module is used to input the geographical latitude and longitude of the transmitting point, the geographical latitude and longitude of the receiving point, the antenna elevation angle of the transmitting point, and the world time. The control point parameter module is used to predict parameters including the geomagnetic latitude and longitude, geographic latitude and longitude, solar activity factor, solar inclination, and activity angle of the control point based on the input parameters from the input module. The maximum available frequency prediction module is used to predict the maximum available frequency of layer E and layer F2 based on the input parameters of the input module and the prediction parameters of the control point parameter prediction module. The output module is used to output and save the prediction parameters.

4. A shortwave intelligent frequency-selective communication system according to claim 2, characterized in that: The shortwave communication quality level rapid assessment module includes: A shortwave communication quality level evaluation index system is constructed based on parameters including bit error rate, transmission rate, and latency, and a shortwave communication quality level evaluation dataset is generated based on the analytic hierarchy process and fuzzy comprehensive evaluation method. A decision tree model is used to extract data features and train a module for rapid evaluation of shortwave communication quality levels.

5. A shortwave intelligent frequency-selective communication system according to claim 2, characterized in that: After the shortwave communication quality level rapid assessment module quickly assesses the current communication link level, the shortwave link frequency switching module determines the level. If the communication quality level is higher than the threshold, the optimal operating frequency prediction module mode 2 is activated; if the communication quality level is lower than the threshold, the optimal operating frequency prediction module mode 1 is activated.

6. A shortwave intelligent frequency-selective communication system according to claim 3, characterized in that: The control point parameter module uses a deep neural network to predict parameters.

7. A shortwave intelligent frequency-selective communication system according to claim 2, characterized in that: In Mode 1, the optimal operating frequency prediction module uses a recurrent neural network to predict the optimal operating frequency that can adapt to changes in the ionosphere in real time.

8. A shortwave intelligent frequency selective communication method, implemented based on the shortwave intelligent frequency selective communication system based on the multi-head attention mechanism as described in any one of claims 2-7, characterized in that, Includes the following steps: Step S101: Input the geographical latitude and longitude of the transmitting point, the geographical latitude and longitude of the receiving point, the antenna elevation angle of the transmitting point, and the world time. Then, use the ionospheric maximum available frequency prediction module to output parameters including the geomagnetic latitude and longitude of the control point, the geographical latitude and longitude, the solar activity factor, the solar inclination angle, and the activity angle. In step S102, combining the input parameters and predicted output parameters from step S101, the ionospheric maximum available frequency prediction module predicts the maximum available frequencies of the E layer, F1 layer, and F2 layer, and outputs and saves them. Step S103: Utilize the optimal operating frequency prediction module in operating mode one to predict the optimal operating frequency. Step S104: Establish and communicate based on the optimal operating frequency, and record indicators including link error rate, transmission rate, and latency. Step S105: Use the shortwave communication quality level rapid evaluation module to evaluate the link quality level. If the evaluation level result is higher than the threshold, proceed to step S106; otherwise, proceed to step S107. Step S106: Utilize the optimal operating frequency prediction module in operating mode two to predict the optimal operating frequency, and proceed to step S104. In step S107, the shortwave link relay intelligent discrimination module determines whether to enable the relay enhancement function. If it needs to be enabled, the destination address is changed to the shortwave link relay station to achieve shortwave link relay enhancement. Otherwise, proceed to step S103.

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