A miniaturized multi-channel up-conversion module for satellite internet

Abstract

This invention provides a miniaturized multi-channel up-conversion module for satellite internet, belonging to the technical field of miniaturized up-conversion modules. By collecting and analyzing various parameters of the up-conversion module, this invention can effectively sense environmental disturbances and equipment state changes, and optimize the overall signal of the up-conversion module accordingly. Through the construction of a multi-dimensional control model, it can predict the internal state of the local oscillator unit, which is difficult to measure directly, and use this as an intermediate variable to achieve precise adjustment of its control parameters, thus forming a complete closed-loop control logic. The overall solution avoids the black-box phenomenon in the control parameter adjustment process, greatly enhancing the interpretability of the control process and improving the signal quality of the up-conversion module in complex environments, thereby providing the up-conversion module with the capability to support high-precision miniaturized design.

Description

Technical Field

[0001] This invention relates to the field of miniaturized up and down frequency conversion module technology, specifically a miniaturized multi-channel up and down frequency conversion module for use in satellite internet. Background Technology

[0002] In satellite internet terminals and base station systems, high-performance up-conversion modules are crucial for achieving efficient conversion between radio frequency (RF) and intermediate frequency (IF) signals. However, existing multi-channel up-conversion modules generally suffer from problems such as large size, insufficient frequency stability, and high phase noise, and lack effective dynamic adaptive control methods to cope with complex and changing environmental factors and component performance fluctuations.

[0003] In the prior art, CN108400785A discloses a miniaturized microwave broadband fast-mode up-conversion system and calibration method. This system includes an up-conversion channel and a down-conversion channel using the same local oscillator signal; it also includes a redundant calibration mixing channel. This redundant calibration mixing channel is connected to the up-conversion system composed of the up-conversion and down-conversion channels using a directional coupler and a switching network. Up-conversion or down-conversion is achieved by mixing the local oscillator signal used by either the up-conversion or down-conversion channel. This method utilizes the redundant calibration mixing channel to calculate the phase offset value of the up-conversion and down-conversion circuits in the current state by detecting the associated offset. While this scheme can achieve adjustment and calibration of the up-conversion and down-conversion modules, it does not consider the influence of the environment and component performance on the adjustment process, resulting in insufficient adjustment accuracy and difficulty in meeting the higher signal accuracy requirements after miniaturization.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a miniaturized multi-channel up-conversion module for satellite internet applications, in order to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A miniaturized multi-channel up-conversion module for satellite internet applications, specifically comprising: Local oscillator generation unit, which is electrically connected to frequency conversion unit, is used to generate a frequency-adjustable local oscillator signal and send it to frequency conversion unit respectively; The frequency conversion unit includes an up-conversion unit and a down-conversion unit, both of which are electrically connected to the communication unit. The up-conversion unit receives the input signal sent by the communication unit, combines it with the local oscillator signal to perform up-conversion or down-conversion processing, and sends the processed output signal to the communication unit. The communication unit includes a radio frequency communication unit and an intermediate frequency communication unit, which are used to communicate with satellite Internet and external devices respectively, to receive different types of input signals and to send different types of output signals. The data acquisition unit is electrically connected to the local oscillator generation unit and the frequency conversion unit respectively. It is used to acquire the control parameters of the local oscillator generation unit, the environmental parameters of its environment, and the signal parameters of the output signal, and send the three to the control unit. The control unit is electrically connected to the local oscillator generation unit and is used to execute a preset multi-dimensional control model. It combines environmental parameters and signal parameters to jointly adjust the control parameters of the local oscillator generation unit in order to minimize the phase noise of the local oscillator generation unit.

[0007] Preferably, the local oscillator generation unit includes: a temperature-controlled crystal oscillator, an integrated phase-locked loop (PLL), a ceramic resonator, an RF amplifier, and a power divider. Its working logic is as follows: the temperature-controlled crystal oscillator generates a reference signal, which is input into the integrated PLL. The integrated PLL locks the reference signal and sends it to the ceramic resonator to adjust the frequency and generate the local oscillator signal. The local oscillator signal is then amplified by the RF amplifier and divided into two paths by the power divider, and sent to the up-conversion unit and the down-conversion unit respectively.

[0008] Preferably, the input signal includes a radio frequency input signal and an intermediate frequency input signal, and the output signal includes a radio frequency output signal and an intermediate frequency output signal; The upconversion unit has two input terminals and one output terminal. The two input terminals are electrically connected to the intermediate frequency communication unit and the local oscillator generation unit, respectively, and the output terminal is electrically connected to the radio frequency communication unit. The upconversion unit includes a first bandpass filter, a driver amplifier, and a first mixer. Its working logic is as follows: the first bandpass filter receives the intermediate frequency input signal sent by the intermediate frequency communication unit, performs band-limited filtering on it, and then sends it to the driver amplifier for gain adjustment. Then, in the first mixer, it is upconverted together with the local oscillator signal to generate a radio frequency output signal. Finally, the radio frequency output signal is sent to the radio frequency communication unit. The downconversion unit has two input terminals and one output terminal. The two input terminals are electrically connected to the radio frequency communication unit and the local oscillator generation unit, respectively, and the output terminal is electrically connected to the intermediate frequency communication unit. The downconversion unit includes a second bandpass filter, a low-noise amplifier, and a second mixer. Its working logic is as follows: the second bandpass filter receives the radio frequency input signal sent by the radio frequency communication unit, performs band-limited filtering on it, and then sends it to the low-noise amplifier for low-noise amplification. Then, in the second mixer, it is downconverted together with the local oscillator signal to generate an intermediate frequency output signal. Finally, the intermediate frequency output signal is sent to the intermediate frequency communication unit.

[0009] Preferably, the data acquisition unit includes an environmental sensor and an analog-to-digital converter; the control parameters include voltage-controlled voltage and charge pump current; the environmental parameters include ambient temperature and electromagnetic interference intensity; and the signal parameter is phase detection error voltage.

[0010] Preferably, the multidimensional control model is obtained by coupling a state-space model with an extended Kalman filter method and a model predictive control method, and its initial model parameters are determined by modeling and simulating the local oscillator generation unit.

[0011] Preferably, the working logic of the multidimensional regulation model is as follows: By using environmental parameters and control parameters as inputs to the state-space model, and combining its state equations and output equations, prior predictions of state parameters and signal parameters are obtained. The state parameters include the resonant frequency offset of the local oscillator generation unit, the loop voltage deviation, and the local oscillator output power. The extended Kalman filter method is used to process the prior predictions of state parameters and signal parameters to obtain the posterior predictions of state parameters. These posterior predictions are then substituted into the output equation of the state-space model to obtain the posterior predictions of signal parameters. The control objective is to minimize the error between the posterior prediction and the preset value of the signal parameters. The physical properties of the local oscillator generator are used as constraints to jointly construct the control objective function. A model predictive control method is then used to generate the change in control parameters.

[0012] Preferably, the state equation and output equation of the state-space model are obtained by fitting simulation data from the local oscillator generation unit in the simulation analysis. The state equation is used to represent the mapping relationship between the state parameters, control parameters, and environmental parameters at the current time and the state parameters at the next time. The output equation is used to represent the mapping relationship between the state parameters, control parameters, and environmental parameters at the current time and the signal parameters at the current time.

[0013] Preferably, the generation logic for the posterior prediction of the state parameters is as follows: Find the partial derivatives of the state equation and the output equation with respect to the state parameters to obtain the Jacobian matrix and the observation Jacobian matrix. The Jacobian matrix and the preset first noise are combined to obtain the prediction covariance matrix at any time. The predicted covariance matrix is ​​combined with the observed Jacobian matrix and the preset second noise to obtain the innovation covariance matrix at the corresponding time. Then, the predicted covariance matrix and the observed Jacobian matrix are combined to calculate the Kalman gain. The difference between the actual value and the prior prediction of the signal parameters is calculated, multiplied by the Kalman gain, and then the product is added to the prior prediction of the state parameters to obtain the posterior prediction of the state parameters.

[0014] Preferably, both the first noise and the second noise are obtained by fitting the simulation data of the local oscillator generation unit in the modeling and simulation. The acquisition logic is as follows: during the simulation process, several sets of state parameters at different times are generated using the Monte Carlo method, and the prediction covariance matrix at the corresponding time is calculated. Based on the prediction covariance matrix at different times, the first noise and the second noise are deduced by the least squares method.

[0015] Compared with the prior art, the beneficial effects of the present invention are: This invention effectively senses environmental disturbances and equipment status changes by collecting and analyzing various parameters of the up and down frequency converter modules, and optimizes the overall signal of the up and down frequency converter modules accordingly. By constructing a multi-dimensional control model, it can predict the internal state of the local oscillator unit, which is difficult to measure directly, and use it as an intermediate variable to accurately adjust its control parameters, thus forming a complete closed-loop control logic. The overall solution avoids the black box phenomenon in the control parameter adjustment process, which not only greatly enhances the interpretability of the control process, but also improves the signal quality of the up and down frequency converter modules in complex environments, thereby providing the up and down frequency converter modules with the ability to support high-precision miniaturized design. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the overall module structure of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0018] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0019] Example: Please see Figure 1 The present invention provides a technical solution: A miniaturized multi-channel up-conversion module for satellite internet is provided, comprising: a local oscillator generation unit, a frequency conversion unit, a communication unit, a data acquisition unit, and a control unit, with each sub-unit using a standard interface.

[0020] The local oscillator generation unit is electrically connected to the frequency conversion unit to generate a local oscillator signal with an adjustable frequency, and then sends it to the frequency conversion unit.

[0021] The local oscillator generation unit includes: a temperature-controlled crystal oscillator, an integrated phase-locked loop (PLL), a ceramic resonator, an RF amplifier, and a power divider. Its operating logic is as follows: the temperature-controlled crystal oscillator generates a reference signal, which is input into the integrated PLL. The PLL locks the reference signal and sends it to the ceramic resonator to adjust the frequency and generate the local oscillator signal. The local oscillator signal is then amplified by the RF amplifier and split into two paths by the power divider, which are then sent to the up-conversion unit and the down-conversion unit respectively.

[0022] Here, the temperature-controlled crystal oscillator is used as a reference signal source. Temperature control is used to ensure frequency stability, thereby reducing frequency drift and noise. The integrated phase-locked loop can select the appropriate number of channels according to actual needs. Combined with the resonant characteristics of the ceramic resonator, it can achieve fine adjustment of the local oscillator signal to maintain its frequency stability, thereby reducing signal distortion and transmission loss.

[0023] The frequency conversion unit includes an up-conversion unit and a down-conversion unit, both of which are electrically connected to the communication unit. They are used to receive the input signals sent by the communication unit, combine them with the local oscillator signal to perform up-conversion or down-conversion processing, and send the processed output signal to the communication unit.

[0024] The input signals include radio frequency (RF) input signals and intermediate frequency (IF) input signals, and the output signals include RF output signals and intermediate frequency (IF) output signals. The upconversion unit has two input terminals and one output terminal. The two input terminals are electrically connected to the intermediate frequency communication unit and the local oscillator generation unit, respectively, and the output terminal is electrically connected to the radio frequency communication unit. The upconversion unit includes a first bandpass filter, a driver amplifier, and a first mixer. Its working logic is as follows: the first bandpass filter receives the intermediate frequency input signal sent by the intermediate frequency communication unit, performs band-limited filtering on it, and then sends it to the driver amplifier for gain adjustment. Then, in the first mixer, it is upconverted together with the local oscillator signal to generate a radio frequency output signal. Finally, the radio frequency output signal is sent to the radio frequency communication unit. The downconversion unit has two input terminals and one output terminal. The two input terminals are electrically connected to the radio frequency communication unit and the local oscillator generation unit, respectively, and the output terminal is electrically connected to the intermediate frequency communication unit. The downconversion unit includes a second bandpass filter, a low-noise amplifier, and a second mixer. Its working logic is as follows: the second bandpass filter receives the radio frequency input signal sent by the radio frequency communication unit, performs band-limited filtering on it, and then sends it to the low-noise amplifier for low-noise amplification. Then, in the second mixer, it is downconverted together with the local oscillator signal to generate an intermediate frequency output signal. Finally, the intermediate frequency output signal is sent to the intermediate frequency communication unit.

[0025] Both the up-conversion and down-conversion units are connected to the communication unit and the local oscillator generation unit, which can ensure frequency synchronization of each channel and is beneficial to the collaborative processing and phase consistency of the multi-channel system.

[0026] The communication unit includes a radio frequency communication unit and an intermediate frequency communication unit, which are used to communicate with satellite internet and external devices, respectively, to receive different types of input signals and to send different types of output signals.

[0027] The external devices here refer to downstream devices or local communication terminals in the signal processing process, such as network switches and computers. Simply put, the communication unit communicates with the satellite internet via radio frequency (RF) signals and with external devices via intermediate frequency (IF) signals. In the uplink, the input signal is an IF signal, and the output signal is an RF signal; in the downlink, the opposite is true: the input signal is an RF signal, and the output signal is an IF signal.

[0028] The data acquisition unit is electrically connected to the local oscillator generation unit and the frequency conversion unit respectively. It is used to collect the control parameters of the local oscillator generation unit, the environmental parameters of its environment, and the signal parameters of the output signal, and send all three to the control unit.

[0029] The data acquisition unit includes environmental sensors (including temperature sensors, electromagnetic sensors, etc.), an analog-to-digital converter, control parameters including voltage control voltage and charge pump current, environmental parameters including ambient temperature and electromagnetic interference intensity, and signal parameters including phase detection error voltage.

[0030] The phase detection error voltage is collected here because it reflects the phase difference between the input signal and the reference signal in the phase-locked loop (PLL). It can be obtained simply by collecting the voltage at the output of the phase detector within the PLL loop. Furthermore, during stable PLL operation, the short-time fluctuations and noise distribution of the phase detection error voltage are highly correlated with the loop's phase noise, especially within the loop bandwidth, directly reflecting the short-term frequency stability of the local oscillator signal. Since measuring phase noise is complex and cumbersome, the phase detection error voltage is used as an approximate indicator for quantifying phase noise; minimizing the phase detection error voltage is equivalent to minimizing the phase noise of the up-converter and down-converter modules. Moreover, compared to up-converter modules of the same size, the up-converter and down-converter modules in this solution have significantly reduced phase noise. Therefore, even with smaller dimensions and more compact internal component arrangement, a low phase noise can be maintained, achieving miniaturization of the up-converter and down-converter modules.

[0031] The control unit is electrically connected to the local oscillator generation unit and is used to execute a preset multi-dimensional control model. It also combines environmental parameters and signal parameters to jointly adjust the control parameters of the local oscillator generation unit in order to minimize the phase noise of the local oscillator generation unit.

[0032] The multidimensional control model is obtained by coupling a state-space model with an extended Kalman filter and a model predictive control method. Its initial model parameters are determined by modeling and simulating the local oscillator generator. In simple terms, the local oscillator generator is modeled and simulated in advance during the design phase. The multidimensional control model is then trained and optimized based on this simulation data. The trained multidimensional control model is then burned into the control unit as a preset. In subsequent practical applications, the preset multidimensional control model is used for calculations.

[0033] Understandably, control parameters are quantities that can be directly set and applied to the local oscillator generation unit; environmental parameters are disturbances caused by changes in the environment in which the local oscillator generation unit operates; signal parameters are indicators reflecting the overall performance of the up and down converter modules; and state parameters reflect the internal operating state of the up and down converter modules. For these parameters, control and environmental parameters are the inputs to the multi-dimensional control model, signal parameters are the model's output, and state parameters are intermediate variables used to prevent the model from being in a "black box" state. Furthermore, in actual operation, state parameters are difficult to directly measure by sensors; therefore, it is necessary to combine the extended Kalman filter (EKF) method to predict them. Simultaneously, since the state parameters can be observed during simulation, modeling and simulating them provides data for subsequent fitting.

[0034] The working logic of the multidimensional regulation model is as follows: By using environmental parameters and control parameters as inputs to the state-space model and combining them with its state equations and output equations, prior predictions of state parameters and signal parameters are obtained. The state parameters include the resonant frequency offset of the local oscillator generation unit, the loop voltage deviation, and the local oscillator output power.

[0035] The state equations and output equations of the state-space model are obtained by fitting simulation data from the local oscillator generator in the simulation analysis. The state equations represent the mapping relationship between the current state parameters, control parameters, environmental parameters, and the state parameters at the next time step. The output equations represent the mapping relationship between the current state parameters, control parameters, environmental parameters, and the signal parameters at the current time step. The expressions for the state equations and output equations are as follows: In the formula , , , They represent the first The vector form of state parameters, control parameters, environmental parameters, and signal parameters at each time point. Indicates the first State parameters at time t, index Index representing time, , Let represent the fitting functions for the state equation and the output equation, respectively. When fitting the state equation and the output equation, methods such as multinomial regression or neural networks can be used. The state equation can be fitted using discrete nonlinear dynamic equations, while the output equation can be fitted using multivariate nonlinear equations.

[0036] Therefore, the formula for calculating the prior prediction of state parameters and signal parameters can be expressed as: In the formula , They represent the first Prior predictions of state parameters and signal parameters at each time step. Indicates the first The posterior prediction of the state parameters at time t, index In the middle, the first half This indicates the time point at which the prediction is made, the latter half. This indicates the cutoff time for the data used in the forecast; in other words, it is the time specified in the forecast table. Based on all the data at time t, for the t The prediction made at time t is the prior prediction, while the prediction received at time t is the prediction made at time t. After obtaining the data at each time point, the prior prediction is updated to obtain the corresponding posterior prediction.

[0037] The extended Kalman filter method is used to process the prior predictions of state parameters and signal parameters to obtain the posterior predictions of state parameters. These posterior predictions are then substituted into the output equation of the state-space model to obtain the posterior predictions of signal parameters.

[0038] The logic for generating the posterior prediction of the state parameters is as follows: By taking the partial derivatives of the state equation and the output equation with respect to the state parameters, the Jacobian matrix can be obtained. and the observed Jacobian matrix ; By combining the Jacobian matrix and the preset first noise, the prediction covariance matrix at any time is obtained. The functional expression of the prediction covariance matrix is ​​as follows: In the formula Indicates the first Prior prediction of the predicted covariance matrix at time step n. The first noise level indicates the noise inherent in the component or random disturbances caused by the environment; the superscript indicates this. This represents the transpose of the matrix. The prediction covariance matrix contains the error covariance information caused by the state-space model in making prediction estimates, as well as the first noise generated randomly. It represents a statistical estimate of the prediction error of the current state and is used to reflect the uncertainty of the prediction of state parameters.

[0039] The predicted covariance matrix is ​​combined with the observed Jacobian matrix and the preset second noise to obtain the innovation covariance matrix at the corresponding time. Then, the predicted covariance matrix and the observed Jacobian matrix are combined to calculate the Kalman gain. The formula for calculating the new covariance matrix can be expressed as: In the formula Indicates the first The new information covariance matrix at time t This represents the second type of noise, indicating the error caused by the component's precision.

[0040] The formula for calculating Kalman gain can be expressed as: In the formula Indicates Kalman gain, This represents the inverse of the new information covariance matrix.

[0041] The difference between the actual value and the prior prediction of the signal parameters is calculated, multiplied by the Kalman gain, and then the product is added to the prior prediction of the state parameters to obtain the posterior prediction of the state parameters.

[0042] The posterior prediction formula for the state parameters is: In the formula Represents the posterior prediction of state parameters. Indicates the first The actual values ​​of the signal parameters at each time point.

[0043] Substituting this into the output equation of the state-space model, we obtain the posterior prediction of the signal parameters. Its calculation formula can be expressed as: Simultaneously, the predicted covariance matrix is ​​also updated, and its posterior prediction can be expressed as: In the formula Represents the identity matrix. Indicates the first Posterior prediction of the predicted covariance matrix at time t.

[0044] The control objective is to minimize the error between the posterior prediction and the preset value of the signal parameters. The physical properties of the local oscillator generator are used as constraints to jointly construct the control objective function. A model predictive control method is employed to generate the changes in the control parameters. The functional expression of the control objective function is as follows: The constraint can then be expressed as: .

[0045] In the formula This represents the function value of the control objective function. Indicates the preset value of the signal parameter, subscript Indicates the control step size. , These represent the time lengths for prediction and control, respectively. Then it means in the first The change in control parameters at each time point is used to adjust the control parameters at the current time point. , These represent the upper and lower limits of the change in the control parameter, respectively.

[0046] Specifically, the preset values ​​of signal parameters are usually determined by the application frequency band and performance requirements. , The upper and lower limits are determined by the specifications of each component. Generally speaking, the voltage control voltage is set between 0 and 10V, and the charge pump current is set between 1 and 5mA. , A value that is too large will increase computational complexity, while a value that is too small will affect the control effect. It is usually determined based on actual needs. Set between 10 and 30. Set between 5 and 20.

[0047] For the control objective function, the first part is equivalent to an error penalty term, aiming to ensure that the model's output (i.e., the posterior prediction of the signal parameters) closely follows the predicted value used as a reference, thus guaranteeing signal quality. The second part is equivalent to a control change smoothing term, used to constrain drastic changes in control commands, ensuring smooth changes in control parameters and avoiding system instability or actuator wear caused by over-adjustment. The control objective is to minimize the error between the posterior prediction of the signal parameters and the preset value, which is equivalent to minimizing the function value of the control objective function. This construction method balances accuracy and control energy consumption. Simply put, if only the output is considered to closely follow the objective, it may lead to significant fluctuations in control parameters, causing the actual hardware to become unresponsive and shorten its lifespan. Adding a penalty for control changes can suppress unreasonable drastic adjustments, making the system run more smoothly.

[0048] Once the change in the control parameter is obtained, the control parameter can be adjusted as follows: The first and second noises are both obtained by fitting simulation data from the local oscillator generation unit in the modeling and simulation. The acquisition logic is as follows: during the simulation, several sets of state parameters at different times are generated using the Monte Carlo method, and the prediction covariance matrix at the corresponding time is calculated. Based on the prediction covariance matrix at different times, the first and second noises are deduced by the least squares method.

[0049] Since the prediction covariance matrix is ​​essentially the statistical distribution of the error for state estimation, its calculation formula can be expressed as: In the formula Represents the mathematical expectation. Indicates the first The actual value of the state parameter at a given moment. This value is difficult to measure directly when the up and down frequency converter modules are working normally, so it needs to be obtained through modeling and simulation to infer the first and second noise.

[0050] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0051] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. 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 by 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.

[0052] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0053] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A miniaturized multi-channel up-conversion / down-conversion module for satellite internet, characterized in that, Specifically, it includes: Local oscillator generation unit, which is electrically connected to frequency conversion unit, is used to generate a frequency-adjustable local oscillator signal and send it to frequency conversion unit respectively; The frequency conversion unit includes an up-conversion unit and a down-conversion unit, both of which are electrically connected to the communication unit. The up-conversion unit receives the input signal sent by the communication unit, combines it with the local oscillator signal to perform up-conversion or down-conversion processing, and sends the processed output signal to the communication unit. The communication unit includes a radio frequency communication unit and an intermediate frequency communication unit, which are used to communicate with satellite Internet and external devices respectively, to receive different types of input signals and to send different types of output signals. The data acquisition unit is electrically connected to the local oscillator generation unit and the frequency conversion unit respectively. It is used to acquire the control parameters of the local oscillator generation unit, the environmental parameters of its environment, and the signal parameters of the output signal, and send the three to the control unit. The control unit is electrically connected to the local oscillator generation unit and is used to execute a preset multi-dimensional control model. It combines environmental parameters and signal parameters to jointly adjust the control parameters of the local oscillator generation unit in order to minimize the phase noise of the local oscillator generation unit.

2. The miniaturized multi-channel up-conversion / down-conversion module for satellite internet according to claim 1, characterized in that: The local oscillator generation unit includes: a temperature-controlled crystal oscillator, an integrated phase-locked loop (PLL), a ceramic resonator, an RF amplifier, and a power divider. Its working logic is as follows: the temperature-controlled crystal oscillator generates a reference signal, which is input into the integrated PLL. The integrated PLL locks the reference signal and sends it to the ceramic resonator to adjust the frequency and generate the local oscillator signal. The local oscillator signal is then amplified by the RF amplifier and split into two paths by the power divider, and sent to the up-conversion unit and the down-conversion unit respectively.

3. A miniaturized multi-channel up-conversion / down-conversion module for satellite internet according to claim 1, characterized in that: The input signals include radio frequency input signals and intermediate frequency input signals, and the output signals include radio frequency output signals and intermediate frequency output signals; The upconversion unit has two input terminals and one output terminal. The two input terminals are electrically connected to the intermediate frequency communication unit and the local oscillator generation unit, respectively, and the output terminal is electrically connected to the radio frequency communication unit. The upconversion unit includes a first bandpass filter, a driver amplifier, and a first mixer. Its working logic is as follows: the first bandpass filter receives the intermediate frequency input signal sent by the intermediate frequency communication unit, performs band-limited filtering on it, and then sends it to the driver amplifier for gain adjustment. Then, in the first mixer, it is upconverted together with the local oscillator signal to generate a radio frequency output signal. Finally, the radio frequency output signal is sent to the radio frequency communication unit. The downconversion unit has two input terminals and one output terminal. The two input terminals are electrically connected to the radio frequency communication unit and the local oscillator generation unit, respectively, and the output terminal is electrically connected to the intermediate frequency communication unit. The downconversion unit includes a second bandpass filter, a low-noise amplifier, and a second mixer. Its working logic is as follows: the second bandpass filter receives the radio frequency input signal sent by the radio frequency communication unit, performs band-limited filtering on it, and then sends it to the low-noise amplifier for low-noise amplification. Then, in the second mixer, it is downconverted together with the local oscillator signal to generate an intermediate frequency output signal. Finally, the intermediate frequency output signal is sent to the intermediate frequency communication unit.

4. A miniaturized multi-channel up-conversion / down-conversion module for satellite internet according to claim 1, characterized in that: The data acquisition unit includes an environmental sensor and an analog-to-digital converter. The control parameters include voltage-controlled voltage and charge pump current. The environmental parameters include ambient temperature and electromagnetic interference intensity. The signal parameter is phase detection error voltage.

5. A miniaturized multi-channel up-conversion / down-conversion module for satellite internet according to claim 4, characterized in that: The multidimensional control model is obtained by coupling the state-space model with the extended Kalman filter method and the model predictive control method, and its initial model parameters are determined by modeling and simulating the local oscillator generation unit.

6. A miniaturized multi-channel up-conversion / down-conversion module for satellite internet according to claim 5, characterized in that: The working logic of the multidimensional regulation model is as follows: By using environmental parameters and control parameters as inputs to the state-space model, and combining its state equations and output equations, prior predictions of state parameters and signal parameters are obtained. The state parameters include the resonant frequency offset of the local oscillator generation unit, the loop voltage deviation, and the local oscillator output power. The extended Kalman filter method is used to process the prior predictions of state parameters and signal parameters to obtain the posterior predictions of state parameters. These posterior predictions are then substituted into the output equation of the state-space model to obtain the posterior predictions of signal parameters. The control objective is to minimize the error between the posterior prediction and the preset value of the signal parameters. The physical properties of the local oscillator generator are used as constraints to jointly construct the control objective function. A model predictive control method is then used to generate the change in control parameters.

7. A miniaturized multi-channel up-conversion / down-conversion module for satellite internet according to claim 6, characterized in that: The state equations and output equations of the state-space model are obtained by fitting simulation data from the local oscillator generation unit in the simulation analysis. The state equations represent the mapping relationship between the state parameters, control parameters, and environmental parameters at the current time and the state parameters at the next time. The output equations represent the mapping relationship between the state parameters, control parameters, and environmental parameters at the current time and the signal parameters at the current time.

8. A miniaturized multi-channel up-conversion / down-conversion module for satellite internet according to claim 6, characterized in that: The generation logic for the posterior prediction of the state parameters is as follows: Find the partial derivatives of the state equation and the output equation with respect to the state parameters to obtain the Jacobian matrix and the observation Jacobian matrix. The Jacobian matrix and the preset first noise are combined to obtain the prediction covariance matrix at any time. The predicted covariance matrix is ​​combined with the observed Jacobian matrix and the preset second noise to obtain the innovation covariance matrix at the corresponding time. Then, the predicted covariance matrix and the observed Jacobian matrix are combined to calculate the Kalman gain. The difference between the actual value and the prior prediction of the signal parameters is calculated, multiplied by the Kalman gain, and then the product is added to the prior prediction of the state parameters to obtain the posterior prediction of the state parameters.

9. A miniaturized multi-channel up-conversion / down-conversion module for satellite internet according to claim 8, characterized in that: The first and second noises are both obtained by fitting simulation data from the local oscillator generation unit in the modeling and simulation. The acquisition logic is as follows: during the simulation, several sets of state parameters at different times are generated using the Monte Carlo method, and the prediction covariance matrix at the corresponding time is calculated. Based on the prediction covariance matrix at different times, the first and second noises are fitted using the least squares method.

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