Special high-throughput satellite communication terminal for electric power

Abstract

The invention provides a special high-throughput satellite communication terminal for electric power, and relates to the technical field of electric power communication, and the special high-throughput satellite communication terminal comprises a baseband processing module which is used for carrying out differential encryption processing on different types of electric power data; the high-throughput satellite radio frequency module is used for suppressing sidelobe interference while realizing automatic satellite beam tracking through a beam forming algorithm during satellite communication, and calculating the optimal transmitting power through a self-adaptive power regulation algorithm; the communication transmission module is used for presetting a data priority based on a priority mapping table during data transmission and preempting satellite beam resources according to the data priority; the electric power Internet of Things protocol adaptation layer is used for realizing conversion between an electric power dedicated protocol and a satellite IP protocol, differential coding compression of electric power data and interrupted transmission in a link; and the beam optimization module is used for dynamically optimizing the beam pointing angle based on the satellite orbit parameters and the terminal geographic position. According to the scheme, the coverage degree of electric power communication in remote areas can be improved, and the safety and reliability of data transmission are improved.

Description

Technical Field

[0001] This invention relates to the field of power communication technology, and in particular to a high-throughput satellite communication terminal specifically for power applications. Background Technology

[0002] Power communication serves as the nerve center supporting the safe and stable operation of new power systems. Its core function is to achieve reliable data transmission and real-time command interaction across the entire power generation, transmission, distribution, and consumption chain, providing crucial technical support for grid dispatching, equipment monitoring, and fault response. With the large-scale grid connection of new energy sources and the accelerated construction of smart grids, power communication has evolved from a traditional means of ensuring basic grid operation to a core infrastructure enabling the digital transformation of the grid. It plays an increasingly important role in grid operation, monitoring, and management, and its technical system and business requirements exhibit significant industry characteristics.

[0003] However, traditional power communication methods primarily rely on terrestrial fiber optic networks and wireless communication technologies. In remote areas, mountains, deserts, and other complex terrains, terrestrial communication network coverage is insufficient, making it difficult to guarantee the reliability and real-time performance of power data transmission. Furthermore, power communication data involves a large amount of sensitive information, such as fault alarm data, video surveillance data, and sensor sampling data, requiring extremely high data security. Existing communication methods are inadequate in terms of encryption processing, anti-interference capabilities, and resource allocation, making it difficult to meet the power system's requirements for high-throughput, high-reliability, and high-security communication. Summary of the Invention

[0004] In view of this, and to address the above shortcomings, it is necessary to propose a high-throughput satellite communication terminal specifically for power systems, in order to improve the coverage of power communication in remote areas, as well as to enhance the security and reliability of data transmission.

[0005] This invention provides a high-throughput satellite communication terminal for power applications, comprising:

[0006] The baseband processing module is used to perform differentiated encryption processing on different types of power data to ensure the security of power-sensitive data transmission; wherein, the power data includes fault alarm data, video surveillance data and sensor sampling data;

[0007] The high-throughput satellite radio frequency module is used to achieve automatic satellite beam tracking and suppress sidelobe interference during satellite communication through beamforming algorithms, and to calculate the optimal transmit power through adaptive power adjustment algorithms to balance communication quality and power consumption, and adapt to channel fluctuations in extreme scenarios.

[0008] The communication transmission module is used to preset data priorities based on a priority mapping table during data transmission, and to preempt satellite beam resources according to data priorities to ensure that high-priority data is transmitted first.

[0009] The power IoT protocol adaptation layer is used to realize the conversion between power-specific protocols and satellite IP protocols, differential coding compression of power data, and link interruption resumption, so as to solve the protocol compatibility problem between power IoT devices and satellite communication.

[0010] The beam optimization module is used to dynamically optimize the beam pointing angle based on satellite orbit parameters and terminal geographical location in order to reduce beam switching delay.

[0011] Preferably, the baseband processing module includes a State Grid security encryption chip and a communication type identification unit, a communication feature training unit, and a dynamic key generation unit connected thereto;

[0012] The State Grid security encryption chip is used to perform differentiated encryption processing on different types of power data; the communication type identification unit is used to distinguish fault alarm data, video monitoring data, and sensor sampling data by parsing the data frame header feature code; the communication feature training unit is used to automatically identify newly added power communication types by training with historical data; the dynamic key generation unit is used to dynamically generate encryption keys based on real-time channel quality parameters and service security levels, and realize real-time key updates and secure distribution through the key negotiation interface with the State Grid security encryption chip.

[0013] Preferably, the high-throughput satellite radio frequency module includes a phased array antenna array, a tunable power amplifier, a dual-band switching unit, and a dynamic power adaptation unit; the phased array antenna array is used to achieve automatic satellite beam tracking and suppress sidelobe interference through beamforming algorithms; the tunable power amplifier is used to dynamically adjust the output power according to channel quality feedback; the dual-band switching unit is configured with a Ka-band primary link and a Ku-band backup link, and supports seamless link switching; the dynamic power adaptation unit is used to dynamically calculate the optimal transmit power based on parameters fed back by the channel quality sensing module through an adaptive power adjustment algorithm.

[0014] Preferably, when the phased array antenna array achieves automatic satellite beam tracking and suppresses sidelobe interference through beamforming algorithms, it is configured to perform the following operations:

[0015] Acquire high-throughput satellite orbital parameters, terminal latitude, longitude and altitude data, and correct the initial azimuth angle by combining them with a digital terrain model;

[0016] Three-dimensional real-time parameters are collected synchronously, and a timestamp alignment algorithm is used to eliminate transmission delay to ensure spatiotemporal consistency of the parameters; wherein, the three-dimensional real-time parameters include: satellite beacon signal strength, terrain obscuration change rate, azimuth and elevation angles of interference sources, and communication priority weights;

[0017] The beam pointing trend is predicted by LSTM, and the prediction error caused by sudden interference is corrected in real time by Kalman filtering. The optimal beam pointing angle prediction value is output to achieve dynamic satellite beam tracking.

[0018] An improved linear minimum mean square error algorithm is used to calculate the weighting coefficients of each antenna element, construct a three-dimensional objective function, and iteratively update the weights using a gradient method to achieve synergistic optimization of main beam gain and low power consumption.

[0019] For strong interference at close range, the zero-point depth is enhanced by a two-dimensional spatial spectrum algorithm; and for sudden interference, a temporary weight correction function is used to form a zero-point that meets the preset signal loudness requirement within a preset time to quickly attenuate the sudden interference signal.

[0020] Preferably, the dynamic power adaptation unit calculates the optimal transmit power using a pre-built global power correction model, and the method for constructing the global power correction model includes:

[0021] The raw parameters characterizing channel quality are obtained, and a dynamic feature space is constructed through three-dimensional feature engineering; wherein, the three-dimensional feature engineering includes: memory feature extraction, service timeliness quantification, and interference dynamic modeling;

[0022] The communication data is trained and learned by a deep Q-network decision model, and the weight allocation is optimized by integrating a feature attention mechanism to generate a preliminary power adjustment strategy.

[0023] A dynamic power baseline is determined based on a fusion physical model and a spatiotemporal attention LSTM model.

[0024] The temperature and humidity coupling coefficient is determined based on environmental factors, and the dynamic power reference is then used to perform accuracy correction based on the temperature and humidity coupling coefficient.

[0025] After each terminal completes its training, the cloud aggregates the federated parameters to generate a global power correction model.

[0026] Preferably, the communication transmission module includes a priority mapping table unit, a dynamic beam hopping control unit, and a traffic monitoring unit;

[0027] The priority mapping table unit is configured with a priority mapping table; wherein, the priority mapping table presets fault alarm data as the highest transmission priority, video surveillance data as the medium transmission priority, and sensor sampling data as the background transmission priority.

[0028] The dynamic beam hopping control unit is used to preempt satellite beam resources based on transmission priority;

[0029] The traffic monitoring unit is used to predict next-hourly communication needs based on historical transmission data.

[0030] Preferably, the dynamic beam hopping control unit includes a beam preemption subunit, a conflict resolution subunit, and a data continuation subunit;

[0031] The beam preemption subunit is used to interrupt the transmission of current medium and background transmission priority data when the highest transmission priority fault alarm data is detected, and to send a beam switching request to the satellite gateway to obtain idle beam resources.

[0032] The conflict resolution subunit is used to coordinate and allocate beam resources based on terminal priority and communication urgency when there is a multi-terminal beam preemption conflict.

[0033] The data continuation subunit is used to resume the transmission of interrupted data after the fault alarm data transmission is completed.

[0034] Preferably, the power Internet of Things protocol adaptation layer integrates a non-IP to IPv6 conversion gateway, a data compression engine, a breakpoint resume unit, and a device identity binding unit;

[0035] The non-IP-IPv6 conversion gateway is used to convert between the power-specific Modbus / 104 protocol and the satellite IP protocol, while retaining the original time stamp information;

[0036] The data compression engine includes an adaptive threshold generator, a differential coding accelerator, and a compression quality adjuster; wherein, the adaptive threshold generator is used to dynamically adjust the difference threshold according to the sensor type and sampling frequency; the differential coding accelerator is used to calculate the difference between adjacent data for continuously sampled sensor data, and transmit the data whose difference exceeds the preset threshold and the corresponding sampling time; the compression quality adjuster is used to dynamically adjust the compression ratio according to the channel quality.

[0037] The device identity binding unit is used to uniquely bind the terminal hardware fingerprint, the transmission line tower ID, and the satellite card number, and is set to allow access to the satellite communication link only after hardware identity authentication.

[0038] Preferably, the satellite communication terminal further includes an energy management module, which includes a solar interface, a battery pack, a low-temperature start-up unit, and an intelligent power consumption adjustment unit;

[0039] The solar interface and battery pack are used to power the device;

[0040] The low-temperature start-up unit is used to perform low-power start-up according to preset parameters when the temperature is lower than the first temperature threshold in order to preheat the core components.

[0041] The intelligent power consumption adjustment unit includes a sleep control subunit, a power amplifier derating subunit, and an extreme environment power consumption control subunit. The sleep control subunit is used to power a preset number of auxiliary array elements in the wall-mounted phased antenna array when the terminal load is lower than a preset load threshold, and to reduce the static power consumption of the tunable power amplifier through the power amplifier derating subunit. The extreme environment power consumption control subunit is used to reduce the power consumption of key modules when the ambient temperature is lower than a first temperature threshold or higher than a second temperature threshold, so as to reduce the standby power consumption to no more than a preset power threshold.

[0042] Preferably, the satellite communication terminal further includes a blockchain-assisted verification module, which includes a hash generation unit and a latency recording unit;

[0043] The hash generation unit is used to generate hash values ​​for fault alarm data after transmission is completed, and write them into the blockchain node to verify the data integrity through on-chain timestamps and node consensus mechanisms.

[0044] The delay recording unit is used to record the delay from data acquisition to the completion of transmission.

[0045] As can be seen from the above technical solutions, in the power-specific high-throughput satellite communication terminal provided by this invention, the baseband processing module can perform differentiated encryption processing on different types of data, ensuring data security, especially for important data such as fault alarms, video monitoring, and sensor sampling. The high-throughput satellite radio frequency module achieves automatic satellite beam tracking through beamforming algorithms and effectively suppresses sidelobe interference, improving communication reliability and anti-interference capabilities. Simultaneously, the high-throughput satellite radio frequency module calculates the optimal transmission power through an adaptive power adjustment algorithm, further optimizing communication efficiency and adapting to channel fluctuations in extreme scenarios. The communication transmission module ensures priority transmission of critical data by pre-setting different data transmission priorities, and simultaneously preempts satellite beam resources based on priority, achieving intelligent resource allocation and management, and improving communication efficiency. The power IoT protocol adaptation layer can convert between power-specific protocols and satellite IP protocols, retaining the original timestamp information, performing differential encoding compression on sensor sampling data, and storing transmitted data during link interruptions, which greatly improves data transmission efficiency and reliability. The beam optimization module can dynamically optimize the beam pointing angle based on satellite orbit parameters and the terminal's geographical location, reducing beam switching latency and further improving the real-time performance and stability of communication. Therefore, this solution can improve the coverage of power communication in remote areas, while also enhancing the security and reliability of data transmission. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of a high-throughput satellite communication terminal for power applications provided in an embodiment of the present invention.

[0047] Figure 2 This is a schematic diagram of a baseband processing module.

[0048] Figure 3 This is a schematic diagram of a high-throughput satellite radio frequency module.

[0049] Figure 4 This is a schematic diagram of a communication transmission module.

[0050] Figure 5 This is a schematic diagram of a power Internet of Things (IoT) protocol adaptation layer.

[0051] Figure 6 This is a schematic diagram of an energy management module.

[0052] Figure 7 This is a schematic diagram of a blockchain-assisted verification module. Detailed Implementation

[0053] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0054] like Figure 1 As shown, the present invention provides a high-throughput satellite communication terminal for power applications, comprising:

[0055] The baseband processing module 1 is used to perform differentiated encryption processing on different types of power data to ensure the security of power-sensitive data transmission; wherein, the power data includes fault alarm data, video surveillance data and sensor sampling data;

[0056] The high-throughput satellite radio frequency module 2 is used to achieve automatic satellite beam tracking and suppress sidelobe interference through beamforming algorithm during satellite communication, and to calculate the optimal transmit power through adaptive power adjustment algorithm to balance communication quality and power consumption and adapt to channel fluctuations in extreme scenarios.

[0057] The communication transmission module 3 is used to preset data priority based on the priority mapping table during data transmission, and to preempt satellite beam resources according to the data priority to ensure that high-priority data is transmitted first.

[0058] The Power Internet of Things Protocol Adaptation Layer 4 is used to realize the conversion between power-specific protocols and satellite IP protocols, differential coding compression of power data, and link interruption resumption, so as to solve the protocol compatibility problem between power Internet of Things devices and satellite communication.

[0059] Beam optimization module 6 is used to dynamically optimize the beam pointing angle based on satellite orbit parameters and terminal geographical location in order to reduce beam switching delay.

[0060] In one embodiment, the baseband processing module 1 may include a State Grid security encryption chip 11 and a communication type identification unit 12, a communication feature training unit 13, and a dynamic key generation unit 14 connected thereto.

[0061] The State Grid security encryption chip 11 is used to perform differentiated encryption processing on different types of power data; the communication type identification unit 12 is used to distinguish fault alarm data, video monitoring data, and sensor sampling data by parsing the data frame header feature code; the communication feature training unit 13 is used to automatically identify newly added power communication types by training with historical data; the dynamic key generation unit 14 is used to dynamically generate encryption keys based on real-time channel quality parameters and service security levels, and realize real-time key updates and secure distribution through the key negotiation interface with the State Grid security encryption chip 11. Specifically, the State Grid security encryption chip 11 is a dedicated security chip integrating a hardware encryption engine and key management functions. It implements power data encryption protection based on national cryptographic standards. The State Grid security encryption chip 11 incorporates an improved SM4 symmetric encryption algorithm 111, an acceleration subunit 112, a data mapping table 113, an automatic matching subunit 114, a fault alarm subunit 115, and a dynamic key scheduling subunit 116. The communication type identification unit 12 is a high-speed data classification hardware module adapted to multiple service scenarios in the power Internet of Things. The communication type identification unit 12 includes a frame header feature parser 121, a time-series feature accelerator 122, a dynamic feature code storage array 123, and an anti-interference verification circuit 124. The system includes a type identifier output interface 125 and a multi-interface protocol adaptation subunit 126; the communication feature training unit 13 is a lightweight hardware training unit that supports adaptive learning of power service types, including a DSP computing subunit 131 and a connected neural network accelerator 132, a storage chip 133, an incremental learning control circuit 134, a channel quality detection subunit 135, and a model update interface 136; the dynamic key generation unit 14 is a key dynamic management hardware unit adapted to satellite channel characteristics, including a channel parameter acquisition interface 141, a true random number generator 142, a key strength adjustment circuit 143, a dedicated key negotiation interface 144, and a lifecycle management timer 145.

[0062] In this embodiment, the State Grid security encryption chip 11 serves as the core security component, integrating a hardware encryption engine and key management functions to achieve encrypted protection of power data based on national cryptographic standards. It incorporates an improved SM4 symmetric encryption algorithm 111 for efficient data encryption processing; an acceleration subunit 112 enhances encryption speed; a data mapping table 113 and an automated matching subunit 114 enable rapid data mapping and matching; a fault alarm subunit 115 monitors and processes fault alarm data in real time; and a dynamic key scheduling subunit 116 dynamically updates keys according to business needs, ensuring dynamic security of communication. The communication type identification unit 12 is designed for multi-service scenarios in the power IoT, identifying data frame header feature codes through a frame header feature parser 121 to distinguish different types of data such as fault alarms, video surveillance, and sensor sampling. A timing feature accelerator 122 accelerates data processing, a dynamic feature code storage array 123 stores feature codes, an anti-interference verification circuit 124 ensures the accuracy of data transmission, a type identifier output interface 125 outputs data type identifiers, and a multi-interface protocol adaptation subunit 126 adapts to various communication protocols. The communication feature training unit 13 supports adaptive learning for power service types. Data is processed by the DSP computing subunit 131 and the neural network accelerator 132, training data is stored by the storage chip 133, incremental learning control circuit 134 implements incremental learning, channel quality detection subunit 135 monitors channel quality, and model update interface 136 synchronously updates the training model. The dynamic key generation unit 14 dynamically manages keys based on satellite channel characteristics. Channel parameter acquisition interface 141 acquires channel parameters, true random number generator 142 generates random numbers, key strength adjustment circuit 143 adjusts key strength, dedicated key negotiation interface 144 implements key negotiation, and lifecycle management timer 145 manages the key lifecycle. These modules work together to ensure high security and efficiency of power communication in complex environments.

[0063] In one embodiment, the workflow of baseband processing module 1 may include: receiving power data such as fault alarms and video surveillance; then, communication type identification unit 12 parses the data frame header to distinguish data types. Dynamic key generation unit 14 generates encryption keys based on channel quality and security level; and State Grid security encryption chip 11 performs differentiated encryption on different types of data. Further, it detects whether there is a new communication type; if so, communication feature training unit 13 trains and updates the identification model using historical data; if not, it outputs the encrypted data to communication transmission module 3.

[0064] In one embodiment, the high-throughput satellite radio frequency module 2 may include a phased array antenna array 21, a tunable power amplifier 22, a dual-band switching unit 23, and a dynamic power adaptation unit 24. The phased array antenna array 21 achieves automatic satellite beam tracking and suppresses sidelobe interference through a beamforming algorithm. The tunable power amplifier 22 dynamically adjusts its output power based on channel quality feedback. The dual-band switching unit 23 is configured with a Ka-band primary link and a Ku-band backup link, and supports seamless link switching. The dynamic power adaptation unit 24 dynamically calculates the optimal transmit power based on parameters fed back by the channel quality sensing module through an adaptive power adjustment algorithm.

[0065] In one embodiment, the phased array antenna array 21 may include 8-16 antenna elements 211, an intelligent beamforming network 212, and an array fault self-testing subunit 213. The intelligent beamforming network 212 calculates the element weighting coefficients using an improved LMMSE adaptive algorithm, forming a main beam in the satellite direction while generating nulls in the interference direction, with a sidelobe suppression ratio ≥25dB, and supports dynamic adjustment of beamwidth to match the satellite coverage range. The array fault self-testing subunit 213 monitors the working status of the antenna elements 211 in real time.

[0066] The phased array antenna array 21 of this invention achieves efficient communication through an intelligent beamforming network 212 and an array fault self-testing subunit 213. The core technology lies in using an improved LMMSE adaptive algorithm to dynamically calculate the weighting coefficients of the antenna elements 211, forming a main beam pointing towards the satellite while simultaneously generating nulls in the interference direction, effectively suppressing sidelobe interference with a sidelobe suppression ratio exceeding 25dB, significantly improving signal quality and anti-interference capability. Simultaneously, the network supports dynamic adjustment of beamwidth, flexibly matching according to satellite coverage to ensure communication stability and efficiency. During operation, the phased array antenna array 21 contains 8 to 16 antenna elements 211. The intelligent beamforming network 212 calculates the weighting coefficients in real time, dynamically adjusting the beam direction and width. The array fault self-testing subunit 213 monitors the operating status of each antenna element 211 in real time. Once a fault is detected, it immediately provides feedback and initiates the corresponding fault handling mechanism to ensure the stable operation of the entire antenna array. This design not only improves the reliability and flexibility of communication but also enhances the system's adaptability, enabling it to maintain high-performance communication in complex and changing environments.

[0067] Specifically, when the phased array antenna array 21 achieves automatic satellite beam tracking and suppresses sidelobe interference through beamforming algorithms, it is configured to perform the following steps:

[0068] S11: Acquire high-throughput satellite orbital parameters, terminal latitude and longitude and altitude data, and correct the initial azimuth angle by combining digital terrain model;

[0069] In this step, high-throughput satellite orbital parameters, terminal latitude and longitude, and altitude data are acquired. A terrain shielding index is generated using a digital terrain model, and the initial azimuth angle is further corrected using a terrain-altitude fusion model. The specific formula is: θ azimuth =θ azimuth,0 +k h h+k T T shadow (α-λ)cosδ; where θ azimuth The corrected initial azimuth angle, θ azimuth,0 The initial values ​​are: α is the satellite's right ascension, λ is the terminal longitude, δ is the satellite's declination; k h Here, h is the altitude correction factor, and h is the final altitude; k T T is the terrain correction factor. shadow This is the terrain shading index.

[0070] S12: Synchronously acquire three-dimensional real-time parameters and use a timestamp alignment algorithm to eliminate transmission delay to ensure spatiotemporal consistency of parameters; wherein, the three-dimensional real-time parameters include: satellite beacon signal strength, terrain obscuration change rate, azimuth and elevation angles of interference sources, and communication priority weight;

[0071] S13: Predict the beam pointing trend using LSTM and correct the prediction error caused by sudden interference in real time using Kalman filtering, output the optimal beam pointing angle prediction value, and realize dynamic satellite beam tracking.

[0072] In this step, a state vector containing beam pointing angle, terrain obscuration degree, and interference power is constructed. The trend in the next 50ms is predicted by LSTM and then dynamically corrected by Kalman filtering. LSTM prediction captures the slow change pattern of terrain, and Kalman filtering corrects sudden interference errors in real time through a 4×4 order state transition matrix, outputting the optimal beam pointing angle prediction value. The tracking error is initially controlled within ≤0.05°.

[0073] S14: An improved linear minimum mean square error algorithm is used to calculate the weighting coefficients of each antenna element 211, construct a three-dimensional objective function, and iteratively update the weights through a gradient method to achieve coordinated optimization of main beam gain and low power consumption.

[0074] Simply pursuing higher main beam gain leads to a surge in power consumption, while simply reducing power consumption results in weak signal and poor anti-interference capabilities. This step employs multi-objective optimization to control power consumption while ensuring communication quality, making it suitable for energy-limited scenarios such as high-altitude mountains and deserts. Specifically, the LMMSE algorithm is used to calculate the weighting coefficients of each antenna element 211, with the core being the construction of a three-dimensional objective function. In the formula, Let H be the array element weighting vector, H denote the conjugate transpose, x(t) be the received signal vector, s(t) be the desired signal, and ŋ be the energy efficiency weighting factor. G represents the total power consumption of the array; γ is the main beam gain weight, and G... main Main beam gain; As a factor to suppress interference, Let be the power of the i-th interference source. To determine the distance to the interference source, the weights are iteratively updated using gradient descent to achieve a synergistic optimization of main beam gain ≥33dBi and low power consumption. For example, this reduces power consumption of redundant array elements while maintaining signal strength.

[0075] S15: For strong interference at close range, the zero-point depth is enhanced by a two-dimensional spatial spectrum algorithm; and for sudden interference, a zero-point that meets the preset signal loudness requirement is formed within a preset time by a temporary weight correction function, so as to quickly attenuate the sudden interference signal.

[0076] In this step, the zero-point scheme is dynamically adjusted according to different interference characteristics. For strong near-range interference, the zero-point depth is enhanced using a two-dimensional spatial spectrum algorithm, with the spatial piling function being... In the formula, E is the direction array manifold vector. N Let d be the noise subspace matrix. i Where is the distance to the interference source. For sudden interference, a zero point ≥30dB is formed within 100μs using a temporary weighted correction function, with the correction amount being: In the formula, For sudden response coefficient, The manifold vector is the direction of interference. For the duration of the interference, This is the attenuation constant, ensuring that the weights automatically recover after the interference disappears.

[0077] Furthermore, a multi-satellite prediction mechanism based on satellite obstruction prediction is considered. Specifically, when the primary satellite's obstruction is ≥60%, the switching beam pointing is quickly calculated based on the pre-stored backup satellite orbit parameters, with a switching time ≤80ms; a closed-loop control for communication priorities is established, with the high-priority communication optimization cycle fixed at 10ms and the low-priority communication cycle dynamically adjusted; the pointing deviation is continuously calibrated through a real-time accuracy verification module, ultimately achieving a beam pointing deviation ≤0.03°, increasing the number of concurrent multi-terminal supports to 6, and achieving a high-priority communication transmission latency ≤150ms, adapting to the high-reliability communication requirements of power grid high-mountain / desert scenarios.

[0078] In this embodiment, the phased array antenna array 21 achieves high-precision automatic tracking and strong interference suppression of satellite beams through an optimized beamforming algorithm. The beam pointing deviation is ≤0.03°, interference suppression capability is ≥35dB, and multi-satellite switching time is ≤80ms, fully meeting the high-reliability communication requirements of high-throughput satellite communication terminals for power grids and providing core technical support for remote monitoring and fault alarms of the power grid. The phased array antenna array 21 of this invention achieves automatic satellite beam tracking and interference suppression through a series of complex steps. First, multi-source data fusion initialization is performed, combining satellite orbit parameters, terminal position, and terrain model to generate a terrain occlusion index and correct the initial azimuth angle. Next, parameters including satellite beacon signal strength and terrain occlusion change rate are dynamically acquired, and a timestamp alignment algorithm is used to ensure the spatiotemporal consistency of parameters. Tracking prediction is performed by fusing data information using an LSTM-Kalman model. LSTM captures terrain change patterns, and Kalman filtering corrects sudden interference errors, achieving accurate beam pointing prediction. An improved LMMSE algorithm is used for distance-energy efficiency dual-objective weight optimization, achieving synergistic optimization of main beam gain and low power consumption. The zero-point scheme is dynamically adjusted to address different interference characteristics, enhancing the zero-point depth for strong near-field interference and rapidly forming zero points for sudden interference. Finally, through a multi-satellite prediction mechanism and communication closed-loop optimization, the switching beam direction is quickly calculated to ensure the stability and low latency of high-priority communication, meeting the high-reliability communication requirements of the power grid in complex scenarios.

[0079] In one embodiment, the tunable power amplifier 22 may include a channel quality dynamic sensing subunit 221, a reinforcement learning power mapping subunit 222, a communication data adaptive prediction subunit 223, a wide-temperature-range linear correction subunit 224, a multi-mode energy efficiency management subunit 225, and an interference adaptive enhancement subunit 226. The dual-band switching unit 23 may include a dual-band quality real-time monitoring subunit 231, an intelligent switching subunit 232, a frequency band synchronization pre-calibration subunit 233, a soft switching execution subunit 234, a wide-temperature-range switching compensation subunit 235, and a switching effect closed-loop optimization subunit 236. The working method of the dynamic power adaptation unit 24 may include:

[0080] S21: Obtain the original parameters characterizing the channel quality and construct a dynamic feature space through three-dimensional feature engineering; wherein, the three-dimensional feature engineering includes: memory feature extraction, service timeliness quantification and interference dynamic modeling.

[0081] This step aims to achieve spatiotemporal memory-based channel feature enhancement and quantization. Specifically, the original parameters from the received channel quality sensing module are used to construct a dynamic feature space through three-dimensional feature engineering, including: memory feature extraction: calculating the sliding window variance σ of the SNR. SNR To identify channel stability, define the channel memory factor M = exp(-λσ).SNR The closer M is to 1, the more stable the channel; Service timeliness quantification: Introduce service delay sensitivity τ to generate timeliness weight W. τ =1-exp(-τ0 / τ) Interference dynamic modeling: Optimize the interference threat index as T int =P int ×exp(-k×d int ), where k = 0.2km -1 d is the distance attenuation coefficient. int This represents the distance to the interference source.

[0082] S22: The communication data is trained and learned through a deep Q-network decision model, and the weight allocation is optimized by integrating a feature attention mechanism to generate a preliminary power adjustment strategy.

[0083] This step aims to leverage deep reinforcement learning and feature attention decision-making. Specifically, it trains and learns from communication data using a deep Q-network decision model, optimizes weight allocation by incorporating a feature attention mechanism, and expands the state space. Attention weight calculation: Attention weights are calculated based on the output features of a multilayer perceptron (MLP). ,satisfy ,right and W τ Assign high weights; the reward function output is ,in =1.2, β=0.8, γ=0.5, the action is selected through the Softmax scheme, and QoS margin is the service quality margin, which is the core indicator for measuring the difference between the actual service quality of the satellite communication link and the service requirements.

[0084] S23: Determine the dynamic power benchmark based on the fusion of the physical model and the spatiotemporal attention LSTM model.

[0085] In this step, we consider fusing the physical model with the spatiotemporal attention LSTM model to output a dynamic power benchmark. The physical model optimization is expressed as: In the formula, The initial power reference value, L, is calculated for the physical model. total G represents the total link loss. tx For the transmit antenna gain, G rx For the receiver antenna gain, SNR target The target signal-to-noise ratio is dynamically adjusted according to the service type. rain For rain fading loss, T int The interference threat index is used. Data-driven enhancement employs a spatiotemporal attention LSTM to predict the correction factor ΔP. dataThe input is a channel feature sequence of the past 30 seconds, and the attention layer focuses on the moment of abrupt rain attenuation; the confidence-based dynamic fusion output is, in the formula... , .

[0086] S24: Determine the temperature and humidity coupling coefficient based on environmental factors, and use the temperature and humidity coupling coefficient to perform accuracy correction on the dynamic power reference.

[0087] This step aims to achieve power accuracy correction based on temperature and humidity coupling. Specifically, it considers introducing a multi-factor environmental coupling correction mechanism to address power deviations under extreme conditions. The temperature and humidity coupling coefficient is expressed as... In the formula, T j H represents the junction temperature, and H represents the ambient humidity. , , These are divided into 0.002 / ℃, 0.001 / ℃, and 0.00001 / ℃. When T... j When the temperature exceeds 65℃ and H > 80, the composite protection is activated to ensure device safety. After calibration, .

[0088] S25: After each terminal completes its training, the cloud generates a global power correction model by aggregating federated parameters.

[0089] This step aims to achieve closed-loop federated learning and collaborative parameter optimization. Specifically, it constructs a multi-terminal federated learning framework to achieve global model iterative optimization. Local residual modeling: Each terminal calculates and adjusts the residuals. Improve local corrections by optimizing ELM fitting; Federated parameter aggregation: aggregate model parameters and weights from various terminals in the cloud. , where N i For the terminal sample size, Acc i To improve the accuracy of the local model, a globally corrected model is generated; real-time parameter updates: the local model is updated every 5 minutes through incremental learning, and new samples are introduced through a sliding window.

[0090] In this embodiment, the workflow of each subunit of the tunable power amplifier 22 and the dynamic power adaptation unit 24 achieves precise power adjustment, high efficiency, and reliable switching through channel feature quantization, reinforcement learning decision-making, multi-factor correction, and federated learning optimization. This significantly improves the adaptability and stability of satellite communication terminals in complex scenarios, providing core technical support for remote communication in power systems. The dynamic power adaptation unit 24 of this invention achieves intelligent power adjustment and optimization through a series of complex steps. First, through spatiotemporal memory-type channel feature enhancement and quantization, it receives the original parameters from the channel quality perception module, constructs a dynamic feature space, calculates the channel memory factor to identify channel stability, quantifies the service timeliness weight, and dynamically models the interference threat index. Next, using deep reinforcement learning and feature attention decision-making, it trains and learns the communication data through a deep Q-network decision model, integrates the feature attention mechanism to optimize weight allocation, expands the state space, and calculates the reward function output. Then, through spatiotemporal fusion power benchmark value calculation, it integrates the physical model and the spatiotemporal attention LSTM model to dynamically adjust the power benchmark value. In the temperature and humidity coupled power accuracy calibration, a multi-factor environmental coupling calibration mechanism is introduced to solve the power deviation problem under extreme environments, and a composite protection is activated to ensure device safety. Finally, through federated learning closed-loop and parameter collaborative optimization, a multi-terminal federated learning framework is constructed to achieve global model iterative optimization. Through local residual modeling, federated parameter aggregation, and real-time parameter updates, the accuracy and adaptability of power regulation are ensured.

[0091] In one embodiment, the workflow of the high-throughput satellite radio frequency module 2 may include: initializing the phased array antenna array 21 and adjusting the beam pointing based on satellite orbit parameters and terminal position; the dual-band switching unit 23 monitoring the quality of the Ka and Ku bands; the dynamic power video unit calculating the optimal transmit power based on channel quality; and the tunable power amplifier 22 adjusting the output power according to the calculation results. Then, it is further determined whether the Ka band quality meets the standard; if so, the main link communication is maintained, and beam tracking accuracy is continuously monitored; if not, a soft handover to the Ku band backup link is initiated to ensure a seamless transition, and then the current link communication is maintained, while beam tracking accuracy is continuously monitored.

[0092] The communication transmission module 3 may include a priority mapping table unit 31, a dynamic beam hopping control unit 32, and a traffic monitoring unit 33. The priority mapping table unit 31 is configured with a priority mapping table. In the priority mapping table, fault alarm data is preset as the highest transmission priority, video monitoring data is preset as the medium transmission priority, and sensor sampling data is preset as the background transmission priority. The dynamic beam hopping control unit 32 is used to preempt satellite beam resources according to the transmission priority. The traffic monitoring unit 33 is used to predict the next hourly communication demand based on historical transmission data. Specifically, the dynamic beam hopping control unit 32 includes a beam preemption subunit 321, a conflict resolution subunit 322, and a data resumption subunit 323. The beam preemption subunit 321 is used to interrupt the transmission of current medium and background transmission priority data when the highest transmission priority fault alarm data is detected, and send a beam switching request to the satellite gateway to obtain idle beam resources. The conflict resolution subunit 322 is used to coordinate and allocate beam resources based on terminal priority and communication urgency when there is a beam preemption conflict among multiple terminals. The data resumption subunit 323 is used to resume the transmission of interrupted data after the fault alarm data transmission is completed, and retain the original data frame sequence number during resumption to ensure integrity.

[0093] In this embodiment, the dynamic beam hopping control unit 32 of the communication transmission module 3, through the coordinated operation of the beam preemption subunit 321, the conflict resolution subunit 322, and the data continuation subunit 323, achieves rapid transmission of high-priority data, efficient allocation of beam resources, and complete continuation of interrupted data. This significantly improves the data transmission performance and reliability of the power-specific high-throughput satellite communication terminal, providing key technical support for remote monitoring and fault alarms in power systems. The essence of the communication transmission module 3 in this invention lies in prioritizing the transmission of high-priority data while ensuring the integrity of data transmission and efficient system operation. During operation, when the highest priority fault alarm data is detected, the beam preemption subunit 321 immediately interrupts the transmission of current medium-priority and background-priority data and sends a beam switching request to the satellite gateway to obtain idle beam resources. If there is a beam preemption conflict among multiple terminals, the conflict resolution subunit 322 coordinates and allocates resources according to terminal priority and communication urgency to ensure priority transmission of critical data. After the fault alarm data transmission is completed, the data continuation subunit 323 resumes the transmission of interrupted data and retains the original data frame sequence number to ensure data integrity. This mechanism effectively improves the reliability and response speed of communication systems, and is particularly suitable for scenarios with high requirements for real-time performance and data integrity in power communication.

[0094] In one embodiment, the flow monitoring unit 33 may employ an improved long short-term memory neural network model 331 and a periodic feature extraction subunit 332. The periodic feature extraction unit extracts power communication periodic features such as transmission line inspection cycle and equipment maintenance cycle. The input parameters include historical transmission rate, communication type ratio, channel quality fluctuation value and periodic feature data. The output is a next-hour level communication bandwidth demand prediction value. The communication transmission module 3 sends a resource reservation request to the satellite gateway based on the prediction value. After the reservation response times out, a dynamic bandwidth application mechanism is automatically triggered.

[0095] In this embodiment, the flow monitoring unit 33 achieves accurate prediction of communication bandwidth demand through an improved long short-term memory neural network model 331 and a periodic feature extraction subunit 332. The essence of the technology lies in using a neural network model to perform deep learning on historical data, combined with the periodic feature extraction subunit 332 analyzing the periodic characteristics of power communication, thereby accurately predicting future communication bandwidth demand. During operation, the periodic feature extraction subunit 332 extracts periodic features such as transmission line inspection cycles and equipment maintenance cycles. Input parameters include historical transmission rates, communication type proportions, and channel quality fluctuation values. This data is fed into the improved long short-term memory neural network model 331 for processing. The model learns patterns and trends from historical data and outputs a next-hourly predicted value for communication bandwidth demand. The communication transmission module 3 sends a resource reservation request to the satellite gateway based on this prediction. If the reservation response times out, a dynamic bandwidth application mechanism is automatically triggered to ensure the rational allocation and efficient utilization of communication resources. This mechanism effectively improves the resource utilization efficiency of the communication system, reduces resource waste, and ensures the stability and reliability of power communication.

[0096] In one embodiment, the workflow of the communication transmission module 3 may include: receiving encrypted data and marking data priorities according to a priority mapping table. The traffic monitoring unit 33 predicts next-hourly communication demand and sends a resource reservation request to the satellite gateway. The dynamic beam control unit preempts satellite beam resources based on data priorities. Then, it monitors for beam resource conflicts. If no conflict exists, data is transmitted in priority order, with higher-priority data sent first. After transmission is complete, a data continuation flag is set. If a conflict exists, the conflict resolution subunit 322 coordinates resource allocation based on terminal priority and urgency, transmits data in priority order, with higher-priority data sent first, and a data continuation flag is set after transmission is complete.

[0097] For the power IoT protocol adaptation layer 4, it integrates a non-IP to IPv6 conversion gateway 41, a data compression engine 42, a breakpoint resume unit 43, and a device identity binding unit 44; the non-IP to IPv6 conversion gateway 41 is used to convert between the power-specific Modbus / 104 protocol and the satellite IP protocol, while retaining the original timestamp information; the data compression engine 42 includes an adaptive threshold generator 421, a differential coding accelerator 422, and a compression quality regulator 423; wherein, the adaptive threshold generator 421 is used to adjust the threshold based on the sensor type. The differential coding accelerator 422 is used to calculate the difference between adjacent data of continuously sampled sensor data and transmit data with a difference exceeding a preset threshold and the corresponding sampling time. The compression quality regulator 423 is used to dynamically adjust the compression ratio according to the channel quality, with a compression ratio ≥ 5:1, and it supports real-time decompression and verification of compressed data. The device identity binding unit 44 is used to uniquely bind the terminal hardware fingerprint, transmission line tower ID, and satellite card number, and is set to allow access to the satellite communication link only after passing hardware identity authentication. Specifically, the device identity binding unit 44 may include a hardware fingerprint extraction subunit 441 and a binding information update subunit 442. The hardware fingerprint extraction subunit 441 uniquely binds the terminal hardware fingerprint, transmission line tower ID, and satellite card number, and allows access to the satellite communication link only after passing hardware-level identity authentication. The binding information update subunit 442 supports updating the binding relationship through authorization commands, which is convenient for device maintenance and replacement. When an unbound device accesses the network, an alarm is triggered and the communication link is cut off.

[0098] In this embodiment, the data compression engine 42 and the power IoT protocol adaptation layer 4 achieve efficient data processing and secure communication through a series of modules. The core technology lies in ensuring the efficiency and security of data transmission by dynamically adjusting data compression and authentication mechanisms. During operation, the adaptive threshold generator 421 dynamically adjusts the difference threshold based on the sensor type and sampling frequency. The differential coding accelerator 422 calculates the difference between adjacent data in continuously sampled sensor data, transmitting only data whose absolute difference exceeds the threshold and the corresponding sampling time, thereby reducing the amount of data transmitted. The compression quality regulator 423 dynamically adjusts the compression ratio based on channel quality, increasing the compression ratio when channel quality is poor to prioritize data transmission. The compression ratio can reach 5:1 or higher, and real-time decompression verification is supported to ensure data integrity. The device identity binding unit 44 in the power Internet of Things protocol adaptation layer 4 uniquely binds the terminal hardware fingerprint, transmission line tower ID and satellite card number through the hardware fingerprint extraction subunit 441. Only devices that pass hardware-level identity authentication are allowed to access the communication link. The binding information update subunit 442 supports updating the binding relationship through authorized commands, which facilitates device maintenance and replacement. When an unbound device accesses the network, an alarm is triggered and the communication link is cut off to ensure the security of the communication link.

[0099] In one embodiment, the workflow of the power IoT protocol adaptation layer 4 may include: receiving data from the communication transmission module 3; converting the power-specific protocol to the satellite IP protocol using a non-IP to IPv6 conversion gateway 41; performing differential encoding compression on the sensor sampling data using a data compression engine 42; then monitoring whether a link interruption occurs during transmission; if not, data transmission proceeds normally. If so, the breakpoint resumption unit 43 starts a local cache to store the transmission data during the interruption; after the link is restored, breakpoint resumption is performed based on the cached data; and the device identity binding unit 44 verifies the terminal identity to ensure legitimate access.

[0100] The beam optimization module 6 communicates bidirectionally with the phased array antenna array 21 and the satellite gateway, and dynamically optimizes the beam pointing angle based on satellite orbit parameters and terminal geographical location to reduce beam switching latency.

[0101] In one embodiment, the dedicated high-throughput satellite communication terminal may further include an energy management module 5, which includes a solar interface 51, a battery pack 52, a low-temperature start-up unit 53, and an intelligent power consumption adjustment unit 54. The solar interface 51 and the battery pack 52 are used to supply power to the device, forming an energy complementarity. The low-temperature start-up unit 53 is used to perform low-power start-up according to preset parameters when the temperature is lower than a first temperature threshold, in order to preheat the core components. For example, the first temperature threshold may be -30°C. The intelligent power consumption adjustment unit 54 includes a sleep control subunit 541, a power amplifier derating subunit 542, and an extreme environment power consumption control subunit 543. The sleep control subunit 541 is used to shut down the power supply to a preset number of auxiliary array elements in the phased antenna array (e.g., shutting down 60% of the auxiliary array elements) when the terminal load is detected to be below a preset load threshold, and to reduce the static power consumption of the tunable power amplifier 22 through the power amplifier derating subunit 542. The extreme environment power consumption control subunit 543 is used to reduce the power consumption of key modules when the ambient temperature is below a first temperature threshold or above a second temperature threshold (e.g., when the ambient temperature exceeds 60°C or is below 30°C), so as to reduce the standby power consumption to no more than a preset power threshold. The preset power threshold can be 1W.

[0102] In this embodiment, the energy management module 5 achieves efficient energy management through the intelligent power consumption adjustment unit 54. The essence of this technology lies in dynamically adjusting power consumption to adapt to different loads and environmental conditions by monitoring the power consumption data of each unit in real time, ensuring low-power operation of the terminal under low load and extreme environments. During operation, the intelligent power consumption adjustment unit 54 monitors the power consumption data of each unit in real time. When the terminal is detected to be in a low-load state, the sleep controller automatically shuts off the power supply to 60% of the auxiliary array elements in the phased array antenna array 21, reducing unnecessary energy consumption. Simultaneously, the power amplifier derating subunit 542 reduces the static power consumption of the tunable power amplifier 22, further optimizing energy use. The extreme environment power consumption control subunit 543 automatically reduces the power consumption of non-critical modules when the ambient temperature exceeds 60°C or falls below -30°C, ensuring that the terminal's standby power consumption is reduced to less than 1 watt. This intelligent adjustment mechanism not only extends the terminal's battery life but also improves its stability and reliability in extreme environments.

[0103] In one embodiment, the workflow of the energy management module 5 may include: after the terminal is powered on, the energy management module 5 starts up, the low-temperature start-up unit 53 detects the ambient temperature and determines whether the ambient temperature is too low; if the ambient temperature is normal, it directly enters the energy supply state; if the ambient temperature is too low, the preheating module is started to activate the core components, and the preheating stops after the temperature returns to normal, and then it enters the energy supply state. Furthermore, the solar interface 51 and the battery pack 52 form a complementary power supply, and the power consumption adjustment unit monitors the terminal load status to determine whether it is in a low-load period. If it is not in a low-load state, it maintains normal power supply to each module; if it is in a low-load period, the sleep control subunit 541 shuts down the redundant antenna array element 211, and the power amplifier derating subunit 542 reduces the power amplifier power consumption.

[0104] In one embodiment, the power-dedicated high-throughput satellite communication terminal may further include a blockchain-assisted verification module 7, which includes a hash generation unit 71 and a latency recording unit 72. The blockchain-assisted verification module 7 is linked with the baseband processing module 1. The hash generation unit 71 is used to generate a hash value for the fault alarm data after transmission is completed and write it into the power blockchain node to verify the data integrity through on-chain timestamps and node consensus mechanisms. The latency recording unit 72 is used to record the latency from data acquisition to transmission completion.

[0105] In this embodiment, the blockchain-assisted verification module 7, through the hash generation unit 71 and the delay recording unit 72, works in conjunction with the baseband processing module 1 to ensure data integrity and transmission efficiency. The core technology leverages the immutability and distributed ledger characteristics of blockchain to provide a highly secure verification mechanism for power communication data. During operation, the hash generation unit 71 generates a hash value for the completed fault alarm data and writes this hash value to the power blockchain node. Through the timestamp and node consensus mechanism on the blockchain, the integrity and authenticity of the data can be verified, preventing data tampering during transmission. Simultaneously, the delay recording unit 72 records the delay from data acquisition to transmission completion, providing a basis for communication quality assessment and optimization. This mechanism not only enhances data security but also improves system transparency and traceability, making it suitable for scenarios in power communication with high requirements for data integrity and transmission efficiency.

[0106] Furthermore, the present invention also provides a communication method based on a power-dedicated high-throughput satellite communication terminal, which may specifically include the following steps:

[0107] Step (1): Multi-domain collaborative initialization and quantum-enhanced security authentication:

[0108] After the terminal is powered on, the low-temperature start-up unit 53 of the energy management module 5 activates the core components through the preheating module, and the sleep control subunit 541 of the intelligent power consumption adjustment unit 54 shuts down the power supply to auxiliary peripherals, achieving low-power start-up in extreme low-temperature environments; the baseband processing module 1 constructs a three-dimensional security system of "hardware-satellite-tower": the hardware fingerprint extraction subunit 441 of the device identity binding unit 44 collects the terminal's radio frequency characteristics and circuit parameters, generates a binding vector with the transmission line tower ID and satellite card number, and ensures that the binding information cannot be tampered with through the anti-interference verification circuit 124; the channel parameter acquisition interface 141 of the dynamic key generation unit 14 acquires real-time channel characteristics, generates a session key in combination with the true random number generator 142, and completes key synchronization with the State Grid security encryption chip 11 through the key negotiation dedicated interface 144. The beam optimization module 6 is linked with the array fault self-test subunit 213 of the phased array antenna array 21;

[0109] Step (II): Business Feature Transfer Learning and Dynamic Encryption Scheme Adaptation:

[0110] The communication type identification unit 12 initiates a full-process identification process of "parsing-verification-learning": the frame header feature parser 121 extracts the data frame header identifier, and the dynamic feature code storage array 123 matches known service types; the anti-interference verification circuit 124 performs CRC verification on the parsing results to reduce identification errors caused by noise; the incremental learning control circuit 134 of the communication feature training unit 13 is linked with the channel quality detection subunit 135. When the channel quality is stable, the neural network accelerator 132 fine-tunes the training of new service features, and the training model is synchronized to the dynamic feature code storage array 123 through the model update interface 136; the automatic matching subunit 114 of the State Grid security encryption chip 11 calls the improved SM4 symmetric encryption algorithm 111 or a lightweight encryption scheme according to the output of the communication type identification unit 12: the dynamic key scheduling subunit 116 is enabled for fault alarm data, and the key is updated for each transmission batch; the acceleration subunit 112 achieves a balance between segmented encryption and fast decryption for video data to ensure real-time requirements;

[0111] Step (3): Federated Learning Drives Channel Awareness and Intelligent Resource Reservation:

[0112] The dynamic power adaptation unit 24 is linked with the priority mapping table of the communication transmission module 3. The periodic feature extraction subunit 332 of the flow monitoring unit 33 mines the regularity of transmission line inspection cycles and other patterns, and predicts bandwidth requirements by combining the improved long short-term memory neural network model 331. The prediction results are synchronized to the dynamic beam hopping control unit 32. The resource reservation mechanism adopts a dual mode of "dedicated + shared": the beam preemption subunit 321 reserves dedicated beam resources for fault alarm data; low-priority services adopt a dynamic sharing mode. When resources are insufficient, the conflict resolution subunit 322 coordinates the allocation based on terminal priority to ensure that the transmission of critical services is not affected.

[0113] Step (4): Space-time joint anti-interference beamforming and multi-satellite prediction switching;

[0114] The intelligent beamforming network 212 of the phased array antenna array 21 performs interference directional suppression: based on the azimuth information of the interference source collected by the distributed sensing module, the array element weighting coefficients are calculated by the improved LMMSE algorithm to generate a deep null in the interference direction; the dual-band quality real-time monitoring subunit 231 of the dual-band switching unit 23 feeds back the frequency band quality data to the intelligent beamforming network 212; the beam optimization module 6 monitors the main satellite's obscuration in real time, and when the obscuration risk exceeds the threshold, it calls the pre-stored backup satellite orbit parameters and completes the backup link frequency calibration in advance through the frequency band synchronization pre-calibration subunit 233 of the dual-band switching unit; before the switch, the backup link quality is verified by short message to ensure the effectiveness of the switch, and the switch process is completed seamlessly by the soft switch execution subunit 234 of the dual-band switching unit;

[0115] Step (5): Power-beam coordinated adjustment and dual-band soft handover optimization;

[0116] The channel quality dynamic sensing module of the tunable power amplifier 22 distinguishes between rain attenuation and electromagnetic interference types, and the reinforcement learning power mapping module outputs a power adjustment scheme. The scheme parameters are synchronized to the intelligent beamforming network 212 to achieve coordinated optimization of power and beam. The wide temperature range linear correction subunit 224 collects the junction temperature of the power amplifier tube in real time, corrects the power output deviation through a temperature and humidity coupling compensation algorithm, and feeds the correction data back to the multi-mode energy efficiency management subunit to dynamically adjust the power amplifier's operating mode. The wide temperature range switching compensation subunit 235 of the dual-band switching unit 23 compensates for the influence of ambient temperature on frequency stability during the switching process. The switching effect closed-loop optimization subunit 236 records the packet loss rate and delay data for each switching and further reduces switching loss by iteratively optimizing the switching parameters.

[0117] Step (Six): AI-driven data optimization and end-to-end blockchain traceability;

[0118] The non-IP-IPv6 conversion gateway 41 of the power IoT protocol adaptation layer 4 retains the time stamp information of the Modbus / 104 protocol. The converted data is processed by the data compression engine 42: the adaptive threshold generator 421 sets the difference threshold according to the sensor type, the differential coding accelerator 422 only transmits data exceeding the threshold, and the compression quality regulator 423 dynamically adjusts the compression ratio in conjunction with the predicted bandwidth of the flow monitoring unit 33. After transmission, the hash generation unit 71 of the blockchain auxiliary verification module 7 generates a hash value for the fault alarm data, which is linked with the encryption result of the State Grid security encryption chip 11 and written into the power blockchain. The latency recording unit 72 records the latency of the entire link, providing a basis for communication quality optimization. During low-load periods, the power amplifier derating subunit 542 of the intelligent power consumption adjustment unit 54 reduces the power consumption of the tunable power amplifier 22, and the sleep control subunit 541 shuts down the power supply of the auxiliary array elements to extend the terminal's battery life.

[0119] In summary, the power-specific high-throughput satellite communication terminal provided by this invention integrates a baseband processing module 1 (including a State Grid security encryption chip 11 and a communication type identification unit 12), a high-throughput satellite radio frequency module 2 (including a phased array antenna array 21 and a dynamic power adaptation unit 24), a communication transmission module 3, a power IoT protocol adaptation layer 4 (including a non-IP-IPv6 conversion gateway 41, a data compression engine 42, and a breakpoint resume unit 43), an energy management module 5, and a beam optimization module 6. It can achieve: differentiated encryption and accurate classification of different types of power data; automatic satellite beam tracking, interference suppression, and dynamic adjustment of output power; preemption of satellite resources based on service priority and prediction of next-hourly communication needs; power-specific protocol conversion, data compression, and link interruption resume; stable power supply to the terminal in extreme environments; and dynamic optimization of beam pointing and reduction of switching latency. It effectively solves the problem of insufficient power communication coverage in remote / complex terrains, improves data transmission security, reliability, real-time performance, and communication efficiency, and meets the high-throughput, high-reliability, and high-security communication requirements in complex power grid scenarios.

[0120] Specifically, the State Grid security encryption chip 11 in the baseband processing module 1 can perform differentiated encryption processing on different types of data, ensuring data security, especially for important data such as fault alarms, video surveillance, and sensor sampling. The communication type identification unit 12 can accurately identify different types of data, while the communication feature training unit 13 can automatically identify newly added power communication types through training with historical data, which greatly enhances the system's adaptability and flexibility. The dynamic key generation unit 14 dynamically generates encryption keys based on real-time channel quality and service security levels, further improving the security of data transmission.

[0121] Secondly, the phased array antenna array 21 in the high-throughput satellite RF module 2 achieves automatic satellite beam tracking and effectively suppresses sidelobe interference through beamforming algorithms, improving communication reliability and anti-interference capability. The tunable power amplifier 22 dynamically adjusts its output power based on channel quality feedback, ensuring communication quality in different environments. The dual-band switching unit 23 is configured with a Ka-band primary link and a Ku-band backup link, supporting seamless transition, which provides higher reliability and flexibility for communication. The dynamic power adaptation unit 24 dynamically calculates the optimal transmit power based on parameters fed back from the channel quality sensing module through an adaptive power adjustment algorithm, further optimizing communication efficiency. Furthermore, the priority mapping table in the communication transmission module 3 presets the transmission priorities of different data, ensuring priority transmission of critical data. The dynamic beam hopping control unit 32 preempts satellite beam resources based on priority, while the traffic monitoring unit 33 predicts next-hourly communication needs based on historical transmission data, realizing intelligent resource allocation and management, and improving communication efficiency. The power IoT protocol adaptation layer 4 integrates a non-IP to IPv6 conversion gateway 41, a data compression engine 42, and a breakpoint resume unit 43. This enables the conversion between power-specific protocols and satellite IP protocols, preserving original timestamp information, performing differential encoding compression on sensor sampling data, and storing transmitted data during link interruptions. This significantly improves data transmission efficiency and reliability. The energy management module 5 includes a solar interface 51, a lithium battery pack 52, and a low-temperature start-up unit 53, forming a complementary energy system that ensures stable terminal operation in various environments, especially achieving low-power start-up even in extreme low-temperature environments. Finally, the beam optimization module 6 communicates bidirectionally with the phased array antenna array 21 and the satellite gateway. Based on satellite orbit parameters and the terminal's geographical location, it dynamically optimizes the beam pointing angle, reducing beam switching latency and further improving communication real-time performance and stability. Through these technical solutions, this invention effectively solves the problems of insufficient coverage in remote areas, difficulty in guaranteeing data transmission reliability and real-time performance, and insufficient data security in existing power communication systems, providing a high-throughput, high-reliability, and high-security communication solution for power systems.

[0122] The modules or units in the device of this invention can be merged, divided, and deleted according to actual needs. The above-disclosed embodiments are merely preferred embodiments of the present invention and should not be construed as limiting the scope of the invention. Those skilled in the art will understand that implementing all or part of the processes of the above embodiments and making equivalent changes according to the claims of this invention still fall within the scope of the invention.

Claims

1. A power dedicated high-throughput satellite communication terminal, characterized by, Comprise: a baseband processing module for performing differentiated encryption processing on different types of power data to ensure the security of power-sensitive data transmission; wherein the power data includes fault alarm data, video monitoring data and sensor sampling data; a high-throughput satellite radio frequency module for suppressing sidelobe interference while achieving automatic tracking of satellite beams through beamforming algorithms during satellite communication, and for balancing communication quality and power consumption through adaptive power adjustment algorithms to calculate the optimal transmission power to adapt to channel fluctuations in extreme scenarios; a communication transmission module for presetting data priority based on a priority mapping table during data transmission, and for preempting satellite beam resources according to data priority to ensure high-priority data transmission; a power Internet of Things protocol adaptation layer for converting power-specific protocols and satellite IP protocols, differentially encoding and compressing power data, and for link interrupting and continuous transmission to solve the protocol compatibility problem of power Internet of Things devices and satellite communication; a beam optimization module for dynamically optimizing beam pointing angles based on satellite orbit parameters and terminal geographic location to reduce beam switching delay.

2. The power dedicated high throughput satellite communication terminal of claim 1, wherein, The baseband processing module includes a State Grid security encryption chip and a communication type identification unit, a communication feature training unit, and a dynamic key generation unit connected thereto; The State Grid security encryption chip is used for differentiated encryption processing on different types of power data; the communication type identification unit is used for distinguishing fault alarm data, video monitoring data and sensor sampling data by analyzing data frame header feature codes; the communication feature training unit is used for automatically identifying new power communication types through historical data training; the dynamic key generation unit is used for dynamically generating encryption keys based on real-time channel quality parameters and business security levels, and for realizing real-time updating and secure distribution of keys through a key negotiation interface with the State Grid security encryption chip.

3. The power dedicated high throughput satellite communication terminal of claim 1, wherein, The high-throughput satellite radio frequency module includes a phased array antenna array, a tunable power amplifier, a dual-band switching unit, and a dynamic power adaptation unit; the phased array antenna array is used for automatic tracking of satellite beams and suppression of sidelobe interference through beamforming algorithms; the tunable power amplifier is used for dynamically adjusting output power according to channel quality feedback; the dual-band switching unit is configured with a Ka-band main link and a Ku-band backup link, and supports seamless transition during link switching; the dynamic power adaptation unit is used for dynamically calculating the optimal transmission power based on parameters fed back by the channel quality sensing module through an adaptive power adjustment algorithm.

4. The power dedicated high throughput satellite communication terminal of claim 3, wherein, When the phased array antenna array realizes automatic tracking of satellite beams and suppression of sidelobe interference through beamforming algorithms, it is configured to perform the following operations: Obtain high-throughput satellite orbit parameters, terminal latitude and longitude, and altitude data, and correct the initial azimuth angle in combination with a digital terrain model; Synchronously collect three-dimensional real-time parameters and use a timestamp alignment algorithm to eliminate transmission delay to ensure temporal and spatial consistency of the parameters; wherein the three-dimensional real-time parameters include satellite beacon signal strength, terrain shielding degree change rate, interference source azimuth and elevation, and communication priority weight; The beam pointing trend is predicted by the LSTM, and the prediction error caused by sudden interference is corrected in real time by Kalman filtering, so as to output an optimal beam pointing angle prediction value and realize dynamic tracking of a satellite beam; The improved linear least mean square error algorithm is used to calculate the weighting coefficients of each antenna array element, a three-dimensional target function is constructed, and the weight is iteratively updated by the gradient descent method, so as to realize the collaborative optimization of the main beam gain and low power consumption. For close-range strong interference, the two-dimensional spatial spectrum algorithm is used to strengthen the depth of the zero point; and for sudden interference, a temporary weight correction function is used to form a zero point that meets the preset signal loudness requirement within a preset time, so as to quickly attenuate the sudden interference signal.

5. The power dedicated high throughput satellite communication terminal of claim 3, wherein, The dynamic power adaptation unit is given by a pre-constructed global power correction model when dynamically calculating the optimal transmission power, and the construction method of the global power correction model comprises: An original parameter representing channel quality is obtained, and a dynamic feature space is constructed through three-dimensional feature engineering; wherein the three-dimensional feature engineering comprises memory feature extraction, service timeliness quantification and interference dynamic modeling; The communication data is trained and learned by a deep Q network decision model, and a feature attention mechanism is fused to optimize weight distribution, so as to generate a preliminary power adjustment strategy; Based on the fusion of a physical model and a spatiotemporal attention LSTM model, a dynamic power reference is determined; The temperature and humidity coupling coefficient is determined according to environmental factors, and the dynamic power reference is accuracy corrected by using the temperature and humidity coupling coefficient; After the training of each terminal is completed, the cloud generates a global power correction model through federated parameter aggregation.

6. The power dedicated high throughput satellite communication terminal of claim 1, wherein, The communication transmission module comprises a priority mapping table unit, a dynamic beam hopping control unit and a traffic monitoring unit; The priority mapping table unit is configured with a priority mapping table; wherein the preset fault alarm data in the priority mapping table has the highest transmission priority, the video monitoring data has medium transmission priority, and the sensor sampling data has background transmission priority; The dynamic beam hopping control unit is used to preempt satellite beam resources according to transmission priority; The traffic monitoring unit is used to predict hourly-level communication demand based on historical transmission data.

7. The power dedicated high throughput satellite communication terminal according to claim 6, characterized in that, The dynamic beam hopping control unit comprises a beam preemption subunit, a conflict resolution subunit and a data continuation subunit; The beam preemption subunit is used to interrupt the transmission of data with medium transmission priority and background transmission priority when detecting fault alarm data with the highest transmission priority, and send a beam switching request to a satellite gateway to obtain idle beam resources; The conflict resolution subunit is used to coordinate the allocation of beam resources based on terminal priority and communication urgency when there is a beam preemption conflict among multiple terminals; The data continuation subunit is used to restore the transmission of interrupted data after the transmission of fault alarm data is completed.

8. The power dedicated high throughput satellite communication terminal of claim 1, wherein, The power internet of things protocol adaptation layer is integrated with a non-IP-IPV6 conversion gateway, a data compression engine, a breakpoint continuation unit and a device identity binding unit; The non-IP-IPV6 conversion gateway is used to realize the conversion of power special Modbus / 104 protocol and satellite IP protocol, and to retain original time tag information. The data compression engine comprises an adaptive threshold generator, a differential encoding accelerator and a compression quality regulator, wherein the adaptive threshold generator is configured to dynamically adjust a difference threshold according to a sensor type and a sampling frequency; the differential encoding accelerator is configured to calculate a difference value of adjacent data for the sensor data of continuous sampling, and transmit data and a corresponding sampling time point whose difference value exceeds a preset threshold; and the compression quality regulator is configured to dynamically adjust a compression ratio according to a channel quality. The device identity binding unit is configured to uniquely bind the terminal hardware fingerprint, the power transmission line tower ID and the satellite card number, and set to allow access to the satellite communication link only after hardware identity authentication.

9. The power dedicated high throughput satellite communication terminal of claim 3, wherein, The satellite communication terminal further comprises an energy management module, which comprises a solar interface, a battery pack, a low-temperature starting unit and an intelligent power consumption adjustment unit. The solar interface and the battery pack are configured to supply power to the device. The low-temperature starting unit is configured to perform low-power starting according to preset parameters to preheat core devices when the temperature is lower than a first temperature threshold. The intelligent power consumption adjustment unit comprises a sleep control subunit, a power amplifier power reduction subunit and an extreme environment power consumption control subunit, wherein the sleep control subunit is configured to monitor when the terminal load is lower than a preset load threshold, and to turn off power supply of a preset number of auxiliary array elements in the phased antenna array, and to reduce the static power consumption of the tunable power amplifier through the power amplifier power reduction subunit; and the extreme environment power consumption control subunit is configured to reduce the power consumption of the key modules when the environmental temperature is lower than the first temperature threshold or higher than a second temperature threshold, so as to reduce the standby power consumption to not more than a preset power threshold.

10. The power dedicated high throughput satellite communication terminal of claim 1, wherein, The satellite communication terminal further comprises a blockchain auxiliary verification module, which comprises a hash generation unit and a time delay recording unit. The hash generation unit is configured to generate a hash value for the completed fault alarm data, and write the hash value into a blockchain node, and verify the data integrity through an on-chain timestamp and a node consensus mechanism. The time delay recording unit is configured to record the time delay from data collection to transmission completion.

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