An adaptive parameter adjustment method for a shortwave transmitter

Abstract

This invention relates to a method for adaptive parameter adjustment of a shortwave transmitter, belonging to the field of communication technology. The method includes: acquiring feedback messages uploaded by multiple shortwave receivers; based on the multiple feedback messages, acquiring a spatial region score corresponding to the current frequency point, and determining the adaptive adjustment range of parameters at the current frequency point; based on the acquired spatial region scores of the multiple frequency points and the adaptive adjustment range of parameters at each frequency point, solving a set objective optimization function to determine a joint control command; wherein the joint control command includes at least the adjustment frequency point and the adjustment value of the parameters corresponding to that adjustment frequency point; and sending the joint control command to the shortwave transmitter for adaptive parameter adjustment. This method enables the transmission parameters of the shortwave transmitter to be dynamically adjusted online in real time according to the quality of the shortwave receivers.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and in particular to a method for adaptive parameter adjustment of a shortwave transmitter. Background Technology

[0002] Shortwave communication plays an irreplaceable role in broadcasting, emergency communication, and communication in special fields due to its ability to achieve long-distance, beyond-line-of-sight transmission by utilizing ionospheric reflection. However, shortwave channels exhibit significant time-varying and spatial inhomogeneity. Changes in factors such as ionospheric state, multipath effects, and external interference can lead to drastic fluctuations in signal quality at the receiver, posing a significant challenge to maintaining a stable and reliable communication link.

[0003] Research has found that current parameter configuration and adjustment of shortwave transmitters mainly rely on two modes: First, a static preset mode based on historical experience. Before the mission begins, operators preset parameters such as the operating frequency and transmission power based on prior information such as season, time, and communication distance. When the preset frequency encounters sudden interference or deterioration of ionospheric conditions, communication quality will drop sharply or even be interrupted. Second, a remote manual intervention mode relying on network backhaul. Through remote monitoring links, operators can manually judge and issue parameter adjustment instructions based on quality reports from some receiving stations. This mode has a slow response, relies on human experience, and is difficult to match the rapid change rhythm of shortwave channels at the second or even millisecond level. Summary of the Invention

[0004] To address the aforementioned problems in the prior art, this invention provides a method for adaptive parameter adjustment of a shortwave transmitter, comprising: acquiring feedback messages uploaded by multiple shortwave receivers; wherein the feedback messages include reception quality data and location information; the reception quality data includes at least: a current frequency point and a demodulation signal-to-noise ratio score corresponding to the current frequency point; based on the multiple feedback messages, acquiring a spatial region score corresponding to the current frequency point, and determining an adaptive adjustment range for parameters at the current frequency point; the parameters include at least transmit power; based on the acquired spatial region scores of multiple frequency points and the adaptive adjustment range of parameters at each frequency point, solving a set objective optimization function to determine a joint control command; wherein the joint control command includes at least an adjustment frequency point and an adjustment value for the parameters corresponding to the adjustment frequency point; and sending the joint control command to the shortwave transmitter for adaptive parameter adjustment.

[0005] Optionally, obtaining the spatial region score corresponding to the current frequency point based on multiple feedback messages includes: determining the spatial weight corresponding to each feedback message based on the location information in each feedback message; wherein the spatial weight is set based on the service importance, population distribution and / or density of the shortwave receiver within the target coverage area of ​​the location information; and calculating a weighted average of all demodulation signal-to-noise ratio scores corresponding to the current frequency point based on the spatial weight to obtain the spatial region score corresponding to the current frequency point.

[0006] Optionally, the step of calculating a weighted average of all demodulated signal-to-noise ratio scores corresponding to the current frequency point based on the spatial weight to obtain a spatial region score corresponding to the current frequency point further includes: calculating a weighted average of all demodulated signal-to-noise ratio scores corresponding to the current frequency point based on the spatial weight to obtain an initial spatial region score corresponding to the current frequency point; and performing exponential smoothing on the initial spatial region score corresponding to the current frequency point in the time dimension to obtain a spatial region score corresponding to the current frequency point.

[0007] Optionally, the received quality data further includes interference strength information and / or speech intelligibility score; wherein the interference strength information is obtained by the shortwave receiver through spectrum analysis, and the interference strength information is used to characterize the energy proportion of unwanted signals; the speech intelligibility score is obtained by the shortwave receiver by comparing the demodulated audio with reference features; the feedback message also includes a precise timestamp for data time alignment.

[0008] Optionally, determining the adaptive adjustment range of parameters at the current frequency point includes: comparing the spatial region score of each current frequency point with a preset target quality score to obtain a score deviation; and determining the adaptive adjustment range of parameters at the current frequency point based on a pre-stored mapping relationship between the score deviation and the parameter adjustment amount.

[0009] Optionally, the objective optimization function is a pre-constructed objective function with a selected set of frequency points, the transmit power of each frequency point, and / or the dwell time of each frequency point as decision variables; the objective optimization function includes a first term, a second term, and / or a third term; the first term is used to maximize the sum of spatial region scores of the selected frequency points; the second term is used to minimize the deviation between the transmit power of each frequency point and its corresponding adaptive adjustment range; the third term is used to minimize the deviation between the dwell time of each frequency point and its corresponding adaptive adjustment range; the solution process of the objective optimization function is also constrained by constraints; the constraints include at least: the total transmit power does not exceed the dynamic safety power limit, and the change in transmit power of each frequency point does not exceed the power change rate limit.

[0010] Optionally, the dynamic safe power limit is calculated in real time by: obtaining the real-time temperature of the power amplifier module of the shortwave transmitter and the cumulative thermal stress index based on historical power load; calculating the temperature derating coefficient using a continuously decreasing function based on the relationship between the real-time temperature and a preset threshold; calculating the aging derating coefficient based on the cumulative thermal stress index; and multiplying the temperature derating coefficient, the aging derating coefficient, and the rated maximum power of the shortwave transmitter to obtain the dynamic safe power limit.

[0011] Optionally, a band health weighting factor is also introduced for each frequency point in the cost term of the objective optimization function; the band health weighting factor is pre-calibrated based on the difference in heat load generated by the shortwave transmitter due to different frequency bands; the band health weighting factor is used to suppress the use of frequency points that are not friendly to the equipment during optimization.

[0012] Optionally, when solving for the dwell time of the output adjustment frequency points through a set objective optimization function, the determination of the joint control instruction further includes: calculating the theoretical proportion of each adjustment frequency point within the frequency hopping cycle based on its precise dwell time; generating a pseudo-random frequency hopping sequence using a weighted random algorithm based on the theoretical proportion; and correspondingly, the joint control instruction includes the pseudo-random frequency hopping sequence.

[0013] Optionally, sending the joint control command to the shortwave transmitter for parameter adaptive adjustment further includes: generating gradual power control trajectory information for the transmit power in the joint control command using a first-order discrete smoothing algorithm; wherein the transmit power change of the shortwave transmitter is controlled by the power control trajectory information; and quantizing the dwell time in the joint control command to an integer multiple of the clock period of the internal timer of the shortwave transmitter, and generating hardware control timing accordingly.

[0014] The beneficial effects of this invention include: This application obtains quality feedback from multiple shortwave receivers, then performs a quantitative assessment of the overall link state, and finally combines this with target optimization decisions to generate joint control commands which are then sent to the shortwave transmitter for adjustment. This method allows the shortwave transmitter's transmission parameters to be dynamically adjusted online in real time based on the quality of the shortwave receivers. Specifically, this application actively collects feedback from multiple spatially distributed receivers, eliminating reliance on a single information source or human experience. Through quantitative calculations of spatial region scoring and adaptive parameter adjustment ranges, the complex link state is transformed into a definite, decision-making input. Finally, by solving the target optimization function, a globally optimal joint control command is generated. This method ensures that the final adjusted transmission parameters always match the current optimal link state, thereby significantly reducing the probability of communication interruptions due to channel degradation and improving the overall reliability and average quality of communication. Attached Figure Description

[0015] Figure 1 A flowchart illustrating the steps of an adaptive parameter adjustment method for a shortwave transmitter provided in an embodiment of the present invention;

[0016] Figure 2 This is a block diagram of a communication system provided in an embodiment of the present invention;

[0017] Figure 3 This is a block diagram of another communication system provided in an embodiment of the present invention;

[0018] Figure 4 A block diagram of a parameter adaptive adjustment system for a shortwave transmitter provided in an embodiment of the present invention;

[0019] Figure 5 This is a module block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0020] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application can also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0021] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0022] Research has found that current parameter configuration and adjustment of shortwave transmitters mainly rely on two modes: First, a static preset mode based on historical experience. Before the mission begins, operators preset parameters such as the operating frequency and transmission power based on prior information such as season, time, and communication distance. When the preset frequency encounters sudden interference or deterioration of ionospheric conditions, communication quality will drop sharply or even be interrupted. Second, a remote manual intervention mode relying on network backhaul. Through remote monitoring links, operators can manually judge and issue parameter adjustment instructions based on quality reports from some receiving stations. This mode has a slow response, relies on human experience, and is difficult to match the rapid change rhythm of shortwave channels at the second or even millisecond level.

[0023] In view of the above problems, this application proposes the following embodiments to solve the above technical problems.

[0024] Please see Figure 1This application provides a method for adaptive parameter adjustment of a shortwave transmitter, including steps 101 to 104.

[0025] Step 101: Obtain the feedback messages uploaded by each of the multiple shortwave receivers.

[0026] The feedback message includes reception quality data and location information; the reception quality data includes at least: the current frequency and the demodulation signal-to-noise ratio score corresponding to the current frequency.

[0027] It should be noted that the current frequency point refers to the specific shortwave frequency value that the receiver is tuned and demodulated at the moment the message is generated.

[0028] The demodulation signal-to-noise ratio score is generated by the shortwave receiver itself. After calculating the demodulation signal-to-noise ratio score, each shortwave receiver packages it into reception quality data and, together with its current frequency and location information, generates a feedback message for uploading.

[0029] The demodulated signal-to-noise ratio (SNR) score generation method can be specifically described as follows: The shortwave receiver first acquires the discrete-time baseband signal sequence from its demodulation unit and measures the average power of the received signal at the current frequency. Simultaneously, the average power of noise and interference is obtained through measurements during a quiet period or reference segment. The instantaneous estimate of the demodulated SNR is obtained by calculating the difference or ratio between the signal power and the noise / interference power. Due to the significant fast fading in shortwave channels, the instantaneous SNR fluctuates drastically, and direct use for control would lead to unstable decision-making. Therefore, the shortwave receiver performs time-smoothing processing on the instantaneous SNR at multiple consecutive moments locally (e.g., using a weighted moving average or exponential smoothing algorithm) to form a relatively stable demodulated SNR score that reflects short-term channel trends.

[0030] Step 102: Based on multiple feedback messages, obtain the spatial region score corresponding to the current frequency point, and determine the adaptive adjustment range of parameters at the current frequency point.

[0031] The above parameters include at least the transmission power.

[0032] It should be noted that the spatial region score is used to assess the overall link status of the current frequency point within the target geographical coverage area. Here, the overall reception quality is comprehensively scored regionally based on the location information of each shortwave receiver. The adaptive adjustment range of parameters at the current frequency point can be derived further from the spatial region score, such as determining the adjustment range for increasing or decreasing transmit power.

[0033] Step 103: Based on the spatial region scores of multiple frequency points and the adaptive adjustment range of parameters at each frequency point, the joint control command is determined by solving the set objective optimization function.

[0034] The joint control command includes at least the adjustment frequency and the adjustment value of the parameter corresponding to the adjustment frequency.

[0035] The core of this step is to find the globally optimal transmission strategy in the complex solution space consisting of all acquired frequency points and their adjustment regions through a set objective optimization function. This transmission strategy is a definite, specific, and immediately executable value.

[0036] Step 104: Send the joint control command to the shortwave transmitter for parameter adaptive adjustment.

[0037] Finally, after generating the joint control command, it is sent to the execution end of the shortwave transmitter so that it can dynamically optimize the signal transmission parameters according to the joint control command.

[0038] In one embodiment, the aforementioned adaptive parameter adjustment method for the shortwave transmitter can be executed by the shortwave transmitter, such as... Figure 2 As shown, in a shortwave communication system, a shortwave transmitter establishes a communication connection with each shortwave receiver. The shortwave transmitter can have a built-in network interface and a built-in main control chip to execute the above method.

[0039] In another embodiment, the above-described adaptive parameter adjustment method for the shortwave transmitter can be executed by a server, such as... Figure 3 As shown, the server acts as the intermediate processing node of the entire shortwave communication system. The server can receive feedback messages uploaded by multiple shortwave receivers, execute the above method, and finally send the joint control command to the shortwave transmitter for parameter adaptive adjustment.

[0040] In summary, the parameter adaptive adjustment method for a shortwave transmitter provided in this application has the following beneficial effects:

[0041] This application obtains quality feedback from multiple shortwave receivers, performs a quantitative assessment of the overall link state, and then combines this with target optimization decisions to generate joint control commands which are sent to the shortwave transmitter for adjustment. This method allows the shortwave transmitter's transmission parameters to be dynamically adjusted online in real time based on the quality of the shortwave receivers. Specifically, this application actively collects feedback from multiple spatially distributed receivers, eliminating reliance on a single information source or human experience. Through quantitative calculations of spatial region scoring and adaptive parameter adjustment ranges, the complex link state is transformed into a clear and decision-making input. Finally, by solving the target optimization function, a globally optimal joint control command is generated. This method ensures that the final adjusted transmission parameters always match the current optimal link state, thereby significantly reducing the probability of communication interruptions due to channel degradation and improving the overall reliability and average quality of communication.

[0042] Furthermore, this application optimizes the overall communication performance of the coverage area by introducing a spatial region scoring mechanism, avoiding decision-making biases arising from local optima. In existing technologies, adjustments based on shortwave receiver quality reports from a single point or a few points can easily lead to transmission parameters meeting only the needs of a few locations while sacrificing performance in other areas. This application generates a spatial region score by fusing shortwave receiver location information, enabling the evaluation results to reflect the overall quality status of the target coverage area. During optimization decisions, it guides the system to make decisions that serve the overall regional needs, thereby achieving better and more reasonable parameter adjustment effects in wide-area coverage scenarios.

[0043] Furthermore, in this embodiment, the decision-making process is divided into two steps: first, an adaptive adjustment range (such as a power adjustment interval) is output based on the analysis results of the feedback message; then, when solving the objective optimization function, the precise adjustment value is found within this adaptive adjustment range. This method can provide a clear optimization direction in advance, avoiding blind searching, and then ensures that the final instruction meets business constraints by solving the objective optimization function.

[0044] Optionally, the above steps, which obtain the spatial region score corresponding to the current frequency point based on multiple feedback messages, may specifically include: determining the spatial weight corresponding to each feedback message based on the location information in each feedback message; and calculating the weighted average of all demodulation signal-to-noise ratio scores corresponding to the current frequency point based on the spatial weights to obtain the spatial region score corresponding to the current frequency point.

[0045] The spatial weight is set based on the service importance, population distribution and / or shortwave receiver density of the location information within the target coverage area; that is, the location information is parsed from the feedback message and then the spatial weight corresponding to the location information is matched according to the system design mapping relationship.

[0046] In this context, business importance can be understood as follows: for example, receiving terminals in emergency command centers and important economic zones are given higher weight to ensure that communication quality in these key areas is prioritized.

[0047] Population distribution can be understood as follows: in broadcast scenarios, the reception experience is more important in densely populated areas, so the data received in these areas has a higher weight.

[0048] The density of shortwave receivers can be understood as follows: the distribution of shortwave receivers is uneven. For areas with sparse shortwave receivers, the data from a single shortwave receiver is more representative, and its weight needs to be adjusted accordingly to avoid the area being ignored in the evaluation.

[0049] After determining the spatial weights of all feedback messages at the same current frequency, a weighted average calculation is performed. Specifically, the demodulation signal-to-noise ratio score of each message is multiplied by its corresponding spatial weight, then all products are summed, and finally divided by the sum of all weights. The final value obtained is the spatial region score corresponding to the current frequency.

[0050] It should be noted that research has found that traditional methods simply calculate the signal-to-noise ratio (SNR) at the shortwave receiver using an arithmetic average. However, this is unreasonable in practical applications, as the traditional approach may lead the system to select frequencies with high SNR in remote areas but poor performance in core cities. Therefore, this application associates a spatial weight determined by factors such as service importance and population distribution with each feedback message. This amplifies the influence of quality data from key areas on the results when calculating the score. For example, a frequency with good SNR in densely populated areas but slightly worse in uninhabited areas will receive a significantly higher score than a frequency with excellent SNR in uninhabited areas but only average SNR in densely populated areas. When the system makes optimization decisions based on this score, it will naturally prioritize communication quality in key areas, thereby accurately allocating transmit power and spectrum resources where needed. This aligns network resources with service objectives, significantly improving the overall practical performance of the communication system.

[0051] Optionally, the above steps, based on spatial weights, calculate a weighted average of all demodulated signal-to-noise ratio scores corresponding to the current frequency point to obtain a spatial region score corresponding to the current frequency point. The steps also include: calculating a weighted average of all demodulated signal-to-noise ratio scores corresponding to the current frequency point to obtain an initial spatial region score corresponding to the current frequency point; and performing exponential smoothing on the initial spatial region score corresponding to the current frequency point in the time dimension to obtain the spatial region score corresponding to the current frequency point.

[0052] It should be noted that the initial spatial region score has already undergone spatial domain fusion, reflecting the overall quality of the frequency point at the current sampling time after being weighted geographically. However, shortwave channels are affected by ionospheric changes, interference fluctuations, etc., and their quality fluctuates drastically over time. The initial spatial region score may suddenly deteriorate due to a brief deep fading or instantaneous strong interference. If used directly for decision-making, it will cause frequent and drastic jitter of transmitter parameters. Based on this, this application's embodiment introduces a time smoothing step. Based on the current initial spatial region score, it is then subjected to exponential smoothing in the time dimension to obtain the final score.

[0053] For example, in one specific implementation, a smoothing coefficient β, which is between 0 and 1, can be introduced. This smoothing coefficient β can be multiplied by the current initial spatial region score, and then 1-β can be multiplied by the smoothing result from the previous time step. Finally, a weighted sum is taken to obtain the final spatial region score corresponding to the current frequency point. It should be noted that when β is close to 1, the new initial score is more trusted, resulting in a fast response, but the smoothing effect is weak, and the score is still prone to fluctuation. When β is close to 0, the system relies more on historical trends, resulting in a good smoothing effect and stable score, but the response to actual channel changes is slow.

[0054] The instantaneous quality of shortwave channels can fluctuate drastically within milliseconds due to multipath effects. Directly using this fluctuating data (i.e., the initial spatial region score) for decision-making will result in a series of abrupt changes: such as a significant power increase or emergency frequency switching due to a temporary quality degradation, only to revert to the previous state as quality recovers. Such adjustments accelerate equipment wear and tear and may cause service interruptions due to frequent switching. This invention uses an exponential smoothing algorithm to fuse current instantaneous observations with historical smoothing trends. Optimization decisions based on this smoothed score avoid overreacting to temporary deteriorations and also do not miss the true trend of continuous deterioration, thus ensuring long-term stable adjustment of the communication link.

[0055] Optionally, the reception quality data also includes interference strength information and / or speech intelligibility score; wherein, the interference strength information is obtained by the shortwave receiver through spectrum analysis, and the interference strength information is used to characterize the energy proportion of unwanted signals; the speech intelligibility score is obtained by the shortwave receiver by comparing the demodulated audio with reference features; the feedback message also includes a precise timestamp for time alignment of the data.

[0056] It should be noted that the interference intensity information is generated locally at the shortwave receiver. The shortwave receiver samples a predetermined length of baseband signal near its current frequency and converts it to the frequency domain using a Discrete Fourier Transform. Then, based on the known signal bandwidth and modulation type, it determines the frequency range primarily occupied by the desired signal. The interference intensity information is obtained by calculating the proportion of spectral energy outside this desired range to the total received energy.

[0057] The demodulated signal-to-noise ratio primarily reflects the contrast between the signal and background noise, but it is not sensitive to structural interference existing within the signal band (such as channel interference and narrowband interference). Interference intensity information, on the other hand, is specifically designed to detect and quantify this type of interference.

[0058] The speech intelligibility score is also generated locally at the shortwave receiver. In a voice broadcasting scenario, the shortwave receiver processes the demodulated and recovered digital audio signal. First, it extracts acoustic features that reflect speech clarity, such as short-time energy, spectral envelope, and pitch period. Then, these features are compared and matched with a pre-stored reference feature representing clear speech, resulting in a speech intelligibility score with a value between 0 and 1, which directly reflects the listening experience.

[0059] It should be noted that when the received quality data includes at least two of the following: demodulation signal-to-noise ratio score, interference intensity information, and speech intelligibility score, the subsequent calculation of the spatial region score can be a comprehensive score that takes all the data into account. Alternatively, it can be a separate spatial region score; for example, a first spatial region score can be generated for the demodulation signal-to-noise ratio score, and a second spatial region score can be generated for the speech intelligibility score.

[0060] The introduction of timestamps provides a unified time reference for all data, enabling subsequent evaluations to accurately time-align data on channel status reported by different receivers at the same (or similar) time.

[0061] In summary, by incorporating interference intensity information and speech intelligibility scores into the feedback data, this invention breaks through the limitations of traditional single-data quality analysis and constructs a comprehensive evaluation system for transmission, environment, and experience, thereby achieving a fundamental improvement in anti-interference capability and user experience.

[0062] Optionally, determining the adaptive adjustment range of parameters at the current frequency point includes: comparing the spatial region score of each current frequency point with the preset target quality score to obtain the score deviation; and determining the adaptive adjustment range of parameters at the current frequency point based on the pre-stored mapping relationship between the score deviation and the parameter adjustment amount.

[0063] Specifically, a clear and quantifiable target quality score is preset for the current business scenario. This target quality score represents the minimum link quality threshold required to maintain satisfactory services (such as understandable voice broadcasting), and can be configured according to different service types (such as emergency broadcasting, high-fidelity music). After obtaining the spatial area score for a certain frequency point, the system subtracts it from the target quality score to obtain the score deviation.

[0064] A score deviation greater than 0 indicates that the current link quality is better than the target requirement, and there is a quality margin. This represents the potential to reduce transmit power to save energy and reduce equipment thermal load without resulting in poor service quality.

[0065] When the score deviation is less than 0, it indicates that the current link quality does not meet the target requirements. This means that compensation is needed by adjusting transmission parameters (such as increasing power) to improve quality.

[0066] The system internally stores one or more mapping tables or functions. The mapping relationship describes the correspondence between the scoring deviation and the parameter adjustment amount required to compensate for this deviation. After the scoring deviation is calculated, it is used as input to query the pre-stored mapping relationship, and the output result is the adaptive adjustment range of the parameters at that frequency point.

[0067] For example, when the scoring deviation is -2, the mapping relationship may output a range suggesting that the transmit power be increased by more than 3dB or the modulation be increased by more than 15%.

[0068] In summary, this application clarifies the magnitude and direction of the gap between the current state and the desired state by comparing the spatial region score with the preset target score. This deviation signal directly reveals the directionality of parameter adjustment. Then, by querying pre-stored mapping relationships, an adjustment range suggestion based on historical data or a physical model is immediately obtained. This narrows the subsequent search range from the entire parameter space to a smaller region. This approach significantly reduces the computational load and iteration time required for optimization decisions, achieving faster adaptive response speeds and thus enabling more efficient and robust performance optimization in complex environments.

[0069] Optionally, the objective optimization function is a pre-constructed objective function with the selected set of frequency points, the transmit power of each frequency point, and / or the dwell time of each frequency point as decision variables.

[0070] The objective optimization function includes a first term, a second term, and / or a third term; the first term is used to maximize the sum of the spatial region scores of the selected frequency points; the second term is used to minimize the deviation between the transmit power of each frequency point and its corresponding adaptive adjustment range; and the third term is used to minimize the deviation between the dwell time of each frequency point and its corresponding adaptive adjustment range.

[0071] It should be noted that when the objective optimization function includes the first, second, and third terms simultaneously, the optimal frequency, power, and dwell time can be determined. The first term specifically maximizes the sum of the spatial region scores of the selected frequency points, serving as a positive incentive. It can be expressed as summing (or weighted summing) the scores of each selected frequency point and seeking its maximum value, guiding the system to prioritize frequencies with better link quality (spatial region score). The second term specifically minimizes the deviation between the transmit power of each frequency point and its corresponding adaptive adjustment range, serving as a negative penalty. Here, deviation refers to the difference between the decided power value and the generated power adjustment suggestion or range. It is used to utilize the results of previous evaluations to prevent the optimization result from completely deviating from the reasonable range based on real-time channel evaluation. The third term specifically minimizes the deviation between the dwell time of each frequency point and its corresponding adaptive adjustment range. It is used to ensure that the generated frequency hopping pattern matches the quality evaluation of each frequency point in terms of time allocation, ensuring that high-quality frequencies obtain more communication time.

[0072] The process of solving the objective optimization function is also constrained by constraints; the constraints include at least: the total transmit power does not exceed the dynamic safe power limit and the change in transmit power at each frequency does not exceed the power change rate limit.

[0073] It should be noted that the total transmit power does not exceed the dynamic safety power limit to ensure that the sum of the transmit power of all selected frequency points does not exceed the maximum value calculated in real time.

[0074] The change in transmit power at each frequency does not exceed the upper limit of the power change rate, ensuring that the absolute value of the change between the new power value allocated to each frequency and the actual power value of that frequency in the previous cycle cannot exceed an upper limit. This is a smoothness constraint to prevent large jumps in power commands and protect power amplifiers and other hardware from transient currents and thermal shocks.

[0075] In summary, this invention jointly defines frequency, power, and dwell time as decision variables, and ensures the selection of high-quality spectrum through the first term of the objective function, fundamentally improving communication quality. Simultaneously, the second and third terms ensure that the optimization results fully absorb and follow the adjustment recommendation range derived from real-time channel assessment. Furthermore, by introducing dynamic safe power limits and power change rate limits as hard constraints, the thermal and electrical safety of the equipment is embedded into performance optimization. This transforms the system into an active, collaborative system that pursues optimal performance within a safe range. This approach achieves a globally integrated allocation of frequency, power, and time resources while strictly ensuring equipment safety and stable operation, thereby achieving a balance between overall system performance, reliability, and lifespan.

[0076] Optionally, the dynamic safe power limit is calculated in real time by: obtaining the real-time temperature of the power amplifier module of the shortwave transmitter and the cumulative thermal stress index based on historical power load; calculating the temperature derating factor through a continuously decreasing function based on the relationship between the real-time temperature and a preset threshold; calculating the aging derating factor based on the cumulative thermal stress index; and multiplying the temperature derating factor and the aging derating factor by the rated maximum power of the shortwave transmitter to obtain the dynamic safe power limit.

[0077] The real-time temperature can be read in real time by temperature sensors installed at key locations on the shortwave transmitter. The cumulative thermal stress index is used to quantify the thermal fatigue history that the equipment has endured over a period of time. Specifically, it can be obtained by weighted integration of historical operating conditions. Specifically, the output power and temperature in each past control cycle are recorded, the thermal stress intensity of each cycle is calculated using a stress function, and then the stress of all cycles is accumulated.

[0078] A continuously decreasing function can be expressed as:

[0079] in, This represents the temperature derating factor. , where is the temperature sensitivity coefficient; This indicates the current real-time temperature; This indicates the preset temperature safety threshold.

[0080] ; This represents the derating factor, which increases with the cumulative heat load. The increase is monotonically decreasing. This is the heat load sensitivity coefficient.

[0081] It should be noted that the core of this invention is to change the equipment protection strategy from passive hard shutdown to predictive derating, by introducing a dynamic safe power limit based on real-time temperature and accumulated thermal stress and using a continuously decreasing function. This ensures the absolute safety of the equipment, avoids business interruption to the greatest extent, and significantly extends the service life of the equipment.

[0082] Optionally, a band health weight factor is introduced for each frequency point in the cost term of the objective optimization function; the band health weight factor is pre-calibrated based on the difference in thermal load generated by different frequency bands on the shortwave transmitter; the band health weight factor is used to suppress the use of frequencies that are not friendly to the equipment during optimization.

[0083] Since the antenna feed line, combiner, and part of the power amplifier stage may exhibit different VSWR and loss characteristics at different frequency bands, the internal heat load generated by the same output power at different frequency points is not exactly the same. Therefore, the relationship between frequency, loss, and heat load obtained during the system design and calibration phases is simplified to a frequency band health weighting factor h.

[0084] In one embodiment, in the term penalizing transmit power deviation (the second term), each frequency term is multiplied by (1+λh), where λ is an adjustment coefficient. Thus, for unfriendly frequencies with high health weights h, any form of use (especially high-power use) incurs an amplified cost in the objective function.

[0085] In other words, this approach means that when the objective optimization function tries to maximize communication performance (such as selecting high-scoring frequency points), it will simultaneously be subject to a resistance from the device's physical layer, causing the output to tend to avoid those frequency points that, even if the communication quality is acceptable, will put a lot of stress on the device.

[0086] As can be seen, this application pre-calibrates the frequency band health weight factor for each frequency point and embeds it as a penalty term into the optimization objective function. Its purpose is to embed the imbalance of the device physical layer, guide the system to automatically achieve load balancing in spectrum utilization, thereby effectively avoiding premature aging of local devices caused by long-term use of specific frequency bands, and greatly improving the overall reliability and service life of complex shortwave transmission systems.

[0087] Optionally, when solving for the dwell time of the output adjustment frequency points through the set objective optimization function, determining the joint control command further includes: calculating the theoretical proportion of each adjustment frequency point in the frequency hopping cycle based on its precise dwell time; generating a pseudo-random frequency hopping sequence using a weighted random algorithm based on the theoretical proportion; and correspondingly, the joint control command includes the pseudo-random frequency hopping sequence.

[0088] It should be noted that the theoretical proportion directly reflects the relative importance of the optimization results to each frequency point. The pseudo-random algorithm can be specifically described as follows: when constructing the sequence, frequency points are selected sequentially according to the time step index. At each step, a frequency point with remaining quota is randomly or pseudo-randomly selected based on the proportion of remaining quota, allocated to the current time step, and its remaining quota is reduced. Alternatively, it can be understood as calculating temporary weights based on the remaining, unallocated duration quotas of each frequency point, according to the proportion of remaining quotas, then randomly selecting a frequency point based on the temporary weights, allocating it to the current time unit, and decrementing the remaining quota of that frequency point by 1. This process is repeated until all time units are allocated.

[0089] In the weighted random algorithm, once a frequency point is selected, its remaining quota decreases, and the probability of it being selected again drops instantaneously. This mechanism tends to distribute the chances of multiple occurrences of the same frequency point over time, avoiding excessively long continuous stays. Statistically, this sequence ensures that the total duration of each frequency point's occurrence strictly conforms to its theoretical proportion, but the specific order and segmentation of occurrences on the timeline are pseudo-random and unpredictable. In other words, while ensuring high-quality frequency points obtain core communication resources, the introduction of unpredictable randomness achieves a simultaneous leap in communication efficiency and transmission security.

[0090] Optionally, the above steps of sending the joint control command to the shortwave transmitter for parameter adaptive adjustment also include: generating gradual power control trajectory information for the transmit power in the joint control command using a first-order discrete smoothing algorithm; wherein the transmit power change of the shortwave transmitter is controlled by the power control trajectory information; and quantizing the dwell time in the joint control command into an integer multiple of the clock period of the internal timer of the shortwave transmitter, and generating hardware control timing accordingly.

[0091] The power setting that ultimately affects the hardware is denoted as... The calculation formula using the first-order discrete smoothing algorithm is as follows:

[0092] ;

[0093] in, This represents the adjusted parameter value of the transmit power at frequency point i within the previous control cycle k-1, i.e., the power setting value adopted by the hardware. This represents the power value originally calculated at frequency point i during control period k; This is the power smoothing coefficient, used to balance response speed and smoothness.

[0094] Regarding frequency and modulation execution, let The minimum configurable time step supported by the internal clock of the shortwave signal transmitting equipment, for example, consistent with the timer interrupt period, represents the theoretical dwell time at a certain frequency. quantify it as :

[0095] ;

[0096] in, To use the nearest integer operator, This represents the number of time steps allocated to frequency point i within one frequency hopping cycle. The corresponding actual dwell time. for .

[0097] Since the sum of the theoretical dwell times of all frequencies equals the preset frequency hopping period length, a total time deviation may occur after rounding. To ensure that the total frequency hopping period length is strictly equal to the target value, [further measures are needed]. For all Perform normalization adjustments to make ,in, This represents the total number of time steps corresponding to one frequency hopping cycle.

[0098] In summary, this application utilizes a first-order discrete smoothing algorithm to transform rigid digital commands into continuous analog control trajectories. This completely avoids the electrical stress and thermal shock caused by sudden power fluctuations to fragile components such as power amplifiers, significantly improving the long-term operational reliability of the equipment. Furthermore, it ensures smooth and controllable power regulation, eliminating service jitter caused by hardware overshoot or protection malfunctions. Simultaneously, by quantizing time to an integer multiple of the hardware clock cycle, this invention ensures that every microsecond-level resident control command can be unambiguously recognized and executed by the underlying timer, resolving the synchronization accuracy issue between software and hardware. This allows complex adaptive frequency hopping patterns to be reproduced with high fidelity at the physical level.

[0099] Please see Figure 4 Based on the same inventive concept, embodiments of this application also provide a parameter adaptive adjustment system 40 for a shortwave transmitter, comprising:

[0100] The acquisition module 401 is used to acquire feedback messages uploaded by multiple shortwave receivers; wherein, the feedback message includes reception quality data and location information; the reception quality data includes at least: the current frequency and the demodulation signal-to-noise ratio score corresponding to the current frequency;

[0101] The first processing module 402 is used to obtain a spatial region score corresponding to the current frequency point based on multiple feedback messages, and to determine the adaptive adjustment range of parameters at the current frequency point; the parameters include at least the transmit power;

[0102] The second processing module 403 is used to determine the joint control command by solving a set target optimization function based on the spatial region scores of multiple frequency points and the adaptive adjustment range of parameters under each frequency point; wherein, the joint control command includes at least the adjustment frequency point and the adjustment value of the parameter corresponding to the adjustment frequency point;

[0103] The adaptive adjustment module 404 is used to send the joint control command to the shortwave transmitter for adaptive parameter adjustment.

[0104] Please see Figure 5 Based on the same inventive concept, this application provides a module frame for an electronic device 500 that applies the above-described method. The electronic device 500 includes: at least one processor 501 (… Figure 5 (Only one is shown in the image), memory 502, computer program 503 stored in memory 502 and executable on at least one processor 501, processor 501 executing computer program 503 to implement the steps of the method in any of the foregoing embodiments.

[0105] The electronic device 500 can be a server, a shortwave transmitter, etc.

[0106] Those skilled in the art will understand that Figure 5 This is merely an example of electronic device 500 and does not constitute a limitation on electronic device 500. It may include more or fewer components than shown, or combine certain components, or use different components.

[0107] The processor 501 may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0108] In some embodiments, the memory 502 may be an internal storage unit of the electronic device 500, such as a hard disk or memory of the electronic device 500. In other embodiments, the memory 502 may also be an external storage device of the electronic device 500, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the electronic device 500. Furthermore, the memory 502 may include both internal storage units and external storage devices of the electronic device 500.

[0109] It should be noted that the above-mentioned systems, devices, etc. are based on the same concept as the method embodiments of this application. The modules designed in the system, as well as the steps performed by the device and the resulting technical effects, can all be found in the method embodiments section, and will not be repeated here.

[0110] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps described in the various method embodiments above.

[0111] This application provides a computer program product that, when run on a mobile terminal, enables the mobile terminal to implement the steps described in the above-described method embodiments.

[0112] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0113] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0114] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for adaptive parameter adjustment of a shortwave transmitter, characterized in that, include: The system acquires feedback messages uploaded by multiple shortwave receivers; wherein the feedback messages include reception quality data and location information; the reception quality data includes at least: the current frequency and the demodulation signal-to-noise ratio score corresponding to the current frequency. Based on multiple feedback messages, a spatial region score corresponding to the current frequency point is obtained, and an adaptive adjustment range of parameters at the current frequency point is determined; the parameters include at least the transmit power. Based on the spatial region scores of multiple frequency points and the adaptive adjustment range of parameters at each frequency point, the joint control command is determined by solving the set objective optimization function; wherein, the joint control command includes at least the adjustment frequency point and the adjustment value of the parameter corresponding to the adjustment frequency point. The joint control command is sent to the shortwave transmitter for adaptive parameter adjustment; The objective optimization function is a pre-constructed objective function with a selected set of frequency points, the transmit power of each frequency point, and / or the dwell time of each frequency point as decision variables. The objective optimization function includes a first term, a second term, and / or a third term. The first term is used to maximize the sum of the spatial region scores of the selected frequency points. The second term is used to minimize the deviation between the transmit power of each frequency point and its corresponding adaptive adjustment range. The third term is used to minimize the deviation between the dwell time of each frequency point and its corresponding adaptive adjustment range. The solution process of the objective optimization function is also constrained by constraints. The constraints include at least: the total transmit power does not exceed the dynamic safety power limit, and the change in transmit power of each frequency point does not exceed the power change rate limit.

2. The parameter adaptive adjustment method for a shortwave transmitter according to claim 1, characterized in that, The step of obtaining a spatial region score corresponding to the current frequency point based on multiple feedback messages includes: Based on the location information in each feedback message, a spatial weight corresponding to each feedback message is determined; wherein, the spatial weight is set based on the service importance, population distribution and / or density of the shortwave receiver within the target coverage area; Based on the spatial weights, a weighted average of all demodulation signal-to-noise ratio scores corresponding to the current frequency point is calculated to obtain the spatial region score corresponding to the current frequency point.

3. The parameter adaptive adjustment method for a shortwave transmitter according to claim 2, characterized in that, The step of calculating a weighted average of all demodulation signal-to-noise ratio scores corresponding to the current frequency point based on the spatial weights to obtain the spatial region score corresponding to the current frequency point also includes: Based on the spatial weights, a weighted average of all demodulation signal-to-noise ratio scores corresponding to the current frequency point is calculated to obtain the initial spatial region score corresponding to the current frequency point. The initial spatial region score corresponding to the current frequency point is subjected to exponential smoothing in the time dimension to obtain the spatial region score corresponding to the current frequency point.

4. The parameter adaptive adjustment method for a shortwave transmitter according to claim 1, characterized in that, The received quality data also includes interference intensity information and / or speech intelligibility score; The interference intensity information is obtained by the shortwave receiver through spectrum analysis, and the interference intensity information is used to characterize the energy proportion of the undesired signal. The speech intelligibility score is obtained by the shortwave receiver by comparing the demodulated audio with reference features. The feedback message also includes a precise timestamp for time alignment of the data.

5. The parameter adaptive adjustment method for a shortwave transmitter according to claim 1, characterized in that, Determining the adaptive adjustment range of parameters at the current frequency point includes: The spatial region score for each current frequency point is compared with the preset target quality score to obtain the score deviation. Based on the pre-stored mapping relationship between scoring deviation and parameter adjustment amount, the adaptive adjustment range of parameters at the current frequency point is determined.

6. The parameter adaptive adjustment method for a shortwave transmitter according to claim 1, characterized in that, The dynamic safety power limit is calculated in real time using the following methods: The real-time temperature of the power amplifier module of the shortwave transmitter and the cumulative thermal stress index based on historical power load are obtained. Based on the relationship between the real-time temperature and the preset threshold, the temperature derating coefficient is calculated using a continuously decreasing function. Calculate the aging derating factor based on the cumulative thermal stress index; The dynamic safe power limit is obtained by multiplying the temperature derating factor, the aging derating factor, and the rated maximum power of the shortwave transmitter.

7. The parameter adaptive adjustment method for a shortwave transmitter according to claim 6, characterized in that, In the cost term of the objective optimization function, a frequency band health weight factor is also introduced for each frequency point; The frequency band health weighting factor is pre-calibrated based on the difference in heat load generated by the shortwave transmitter when operating at different frequency bands; The frequency band health weighting factor is used to suppress the use of frequency points that are unfriendly to the device during optimization.

8. The parameter adaptive adjustment method for a shortwave transmitter according to claim 1, characterized in that, When determining the dwell time of the output adjustment frequency point during the solution process using the set objective optimization function, the determination of the joint control command further includes: Calculate the theoretical proportion of each frequency point in the frequency hopping cycle based on the precise dwell time of each adjusted frequency point; A pseudo-random frequency hopping sequence is generated using a weighted random algorithm based on the theoretical proportions. Accordingly, the joint control command includes the pseudo-random frequency hopping sequence.

9. The parameter adaptive adjustment method for a shortwave transmitter according to claim 1, characterized in that, The step of sending the joint control command to the shortwave transmitter for parameter adaptive adjustment also includes: For the transmit power in the joint control command, a first-order discrete smoothing algorithm is used to generate gradually changing power control trajectory information; wherein, the transmit power of the shortwave transmitter is controlled by the power control trajectory information. The dwell time in the joint control command is quantized into an integer multiple of the clock period of the internal timer of the shortwave transmitter, and the hardware control timing is generated accordingly.

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