Offshore long-distance cooperative signal transmission method based on multifunctional floating platform

Abstract

The present application relates to the technical field of marine communication, and discloses a near-shore long-distance cooperative signal transmission method based on a multifunctional floating platform, which comprises the following steps: extracting the spatial coordinates, kinematic vectors and instantaneous power generation data of the multifunctional floating platform and reporting the source node; reconstructing a local sea wave micro-topological function based on the spatial coordinates, screening out an active node cluster set in the wave-crest face; predicting the micro-physical displacement vector of the active node, implementing radial projection mapping into a predicted phase shift amount and evaluating the prediction confidence; based on the prediction confidence and the instantaneous power generation, non-equivalent allocation of modulation order and cooperative radio frequency transmission power is performed for the active node; after reverse time sequence pre-compensation of the baseband signal by using the predicted phase shift amount, each active node synchronously transmits to a remote receiving node, completely offsets the radio frequency phase distortion caused by the sea wave displacement, realizes energy balance matching, and improves the overall reliability of the system cooperative communication.

Description

Technical Field

[0001] This invention relates to the field of marine communication technology, specifically to a near-shore long-distance collaborative signal transmission method based on a multi-functional floating platform. Background Technology

[0002] In the fields of marine environmental monitoring and offshore communication, floating platforms deployed on the nearshore sea surface are often used as communication nodes to build a basic wireless network. In order to overcome the physical limitations of single-node transmission power and the complex electromagnetic multipath fading on the sea surface, multi-node cooperative transmission technology is usually adopted. Multiple floating platforms scattered on the sea surface are constructed into a virtual distributed antenna array, which enables them to synchronously send data streams to remote receiving nodes. It is hoped that communication gain and demodulation reliability can be obtained through the spatial superposition of radio frequency signals.

[0003] However, distributed cooperative communication systems operating in real marine environments face severe hydrodynamic interference. Directly driven by complex wave fluctuations and ocean currents, floating platforms undergo continuous and random three-dimensional spatial physical displacements during operation. Considering that modern wireless communication systems generally use high-frequency microwave carriers, short-distance displacements at the micrometer to centimeter level at the mechanical level are amplified into severe phase distortions on the propagation path of radio frequency signals. This causes severe phase loss when the radio frequency signals emitted by each node reach the remote receiving node across the sea surface. The disordered arrival phase makes it difficult for multiple signals to achieve the expected in-phase superposition. Instead, it is very easy to generate algebraic subtraction and destructive interference at the remote antenna, resulting in a sharp deterioration of the system's signal-to-noise ratio. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a near-shore long-distance collaborative signal transmission method based on a multifunctional floating platform, which solves the problem of phase loss when collaborative transmission signals reach the far end due to physical displacement caused by wave-driven floating nodes on the sea surface.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a near-shore long-distance collaborative signal transmission method based on a multi-functional floating platform, which is executed collaboratively between a source node and multiple multi-functional floating platforms. This method includes the following steps: Each multi-functional floating platform extracts instantaneous hydrodynamic state data containing spatial coordinates, kinematic vectors, and instantaneous power generation and reports it to the source node; The source node reconstructs the local wave micro-topology function based on the spatial coordinates, and selects an active node cluster set accordingly; The source node predicts the microscopic physical displacement vector of each multifunctional floating platform in the active node cluster set based on the kinematic vector, maps it to the predicted phase drift, and evaluates the prediction confidence. The source node distributes data by allocating modulation order to each multifunctional floating platform in the active node cluster set based on the predicted confidence level, and allocates coordinated radio frequency transmission power based on the instantaneous power generation. Each multifunctional floating platform in the active node cluster receives and distributes data and the allocated transmission power, performs inverse timing pre-compensation on the baseband signal corresponding to the data based on the predicted phase drift, and synchronously transmits it to the remote receiving node.

[0006] Furthermore, when extracting instantaneous hydrodynamic state data, the three-dimensional absolute coordinates are extracted as the spatial coordinates through the inertial measurement unit, waterline pressure sensor and wave energy monitoring module mounted on each multi-functional floating platform, the three-axis attitude angles are extracted, the kinematic vector including linear velocity and linear acceleration is extracted, and the instantaneous power generation is extracted.

[0007] Furthermore, the source node reconstructs the local wave micro-topology function by fusing the three-dimensional absolute coordinates through a spatial surface interpolation algorithm, calculates the wave propagation velocity vector by comparing the local wave micro-topology functions of multiple consecutive historical time slots, and calculates the two-dimensional surface height gradient of each multifunctional floating platform.

[0008] Furthermore, the source node will include multifunctional floating platforms that meet the following conditions into the active node cluster set: the vertical height component of its three-dimensional absolute coordinates is not less than a preset vertical height threshold set according to the historical seasonal wave height statistics of the deployment sea area, and the dot product of its two-dimensional surface height gradient and the wave propagation speed vector is greater than zero.

[0009] In predicting the microscopic physical displacement vector, the source node performs time-domain extrapolation by combining the linear velocity and the linear acceleration. (Microscopic physical displacement vector of the floating platform) The calculation formula is:

[0010] In the formula, It is a positive integer, representing the index number of the multifunctional floating platform within the active node cluster set; This refers to the current instantaneous moment in the system. This represents the linear velocity vector calculated based on the differential displacement term sampled by the sensor and combined with the error calibration matrix; This represents the linear acceleration vector obtained by converting the differential electrical signal output from the inertial measurement unit. The time difference is extracted based on a fixed constant sum of the instruction cycle inside the source node baseband processing chip and the inherent delay of the RF hardware link transmission.

[0011] After calculating the microscopic physical displacement vector, the system calculates the projection of the microscopic physical displacement vector in the direction pointing to the remote receiving node, and converts it into an electromagnetic wave phase angle according to the preset radio frequency carrier center wavelength to obtain the predicted phase drift.

[0012] Further, the source node calculates the unbiased sample variance of the error sequence between the predicted phase drift and the actual phase offset reported by the remote receiving node within a preset time window, obtaining the phase prediction dispersion as the prediction confidence. When the phase prediction dispersion is less than a preset judgment threshold set based on historical bit error rate empirical data, the source node distributes a data stream using the first modulation order; when the phase prediction dispersion is not less than the preset judgment threshold, the source node distributes a data stream using the second modulation order, wherein the first modulation order is higher than the second modulation order.

[0013] Furthermore, the source node uses the ratio of the instantaneous power generation of a single multi-functional floating platform to the sum of the instantaneous power generation within the active node cluster as the allocation weight, and multiplies the allocation weight by the system's preset total transmit power to obtain the cooperative radio frequency transmit power specific to each multi-functional floating platform.

[0014] Furthermore, each multifunctional floating platform uses a digital baseband complex multiplier to multiply the initial symbol sequence of the baseband signal by a complex term with a modulus of 1 and a phase angle that is the opposite of the predicted phase drift, generating a pre-compensated baseband signal. Subsequently, the pre-compensated baseband signal undergoes up-conversion processing and is radiated into physical space under the trigger of the system synchronization clock, allowing the remote receiving nodes to receive it in phase in physical space and perform joint demodulation output.

[0015] This invention provides a near-shore long-distance cooperative signal transmission method based on a multifunctional floating platform. It has the following beneficial effects: 1. This invention screens wave crest and wave-facing surface nodes by reconstructing micro-topology, and combines kinematic vector deduction to map micro-physical displacements to predict phase drift. Inverse pre-compensation is performed in the baseband domain to cancel out the phase distortion caused by physical displacement, supporting in-phase superposition reception by the far-end antenna and solving the problem of phase out of synchronization in node cooperative communication.

[0016] 2. This invention extracts instantaneous power generation as a weight to implement asymmetrical allocation of radio frequency transmission power, and combines phase prediction confidence to issue the corresponding modulation order, so that nodes with more captured energy can bear higher radio frequency loads, thus solving the problem of uneven allocation of system resources. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the near-shore long-distance collaborative signal transmission system based on a multi-functional floating platform according to the present invention; Figure 2This is a flowchart of the near-shore long-distance collaborative signal transmission method based on a multifunctional floating platform according to the present invention; Figure 3 This is a block diagram of the internal hardware component architecture of the multifunctional floating platform of the present invention; Figure 4 This is a schematic diagram illustrating the principle of local wave micro-topology reconstruction and active node selection in this invention. Figure 5 This is a geometrical spatial diagram of the microscopic physical displacement prediction and radial projection dimensionality reduction of the present invention. Figure 6 This is a block diagram of the processing logic of the baseband reverse timing pre-compensation and RF transceiver module of the present invention. Detailed Implementation

[0018] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see the appendix Figure 1 To be continued Figure 6 This invention provides a near-shore long-distance collaborative signal transmission method based on a multi-functional floating platform. The method is executed collaboratively between a source node and multiple multi-functional floating platforms. The source node is deployed in a near-shore fixed facility, and the multiple multi-functional floating platforms are scattered on the near-shore sea surface. The remote receiving node is located in the offshore area.

[0020] The multi-functional floating platform integrates sensor components, a baseband processing module, an RF transceiver module, and a timing module. The sensor components include an inertial measurement unit, a waterline pressure sensor, and a wave energy monitoring module. The baseband processing module contains a digital baseband complex multiplier. The RF transceiver module is connected to a communication antenna. The timing module of each multi-functional floating platform is connected to a system synchronization clock source, which is a globally unified clock signal sent from the master control terminal or provided by a satellite positioning system. In this embodiment, the source node and the multi-functional floating platform adopt an orthogonal frequency division multiplexing (OFDM) communication architecture. Control signaling and status data reporting between the two operate within a dedicated control channel, while baseband data stream distribution operates on a high-bandwidth fronthaul wireless data link. All underlying signal transmissions follow 5G NR or a customized cellular IoT underlying physical frame structure.

[0021] The near-shore long-distance collaborative signal transmission method based on a multi-functional floating platform may include the following steps: Each multi-functional floating platform extracts instantaneous hydrodynamic state data including spatial coordinates, three-axis attitude angles, kinematic vectors, and instantaneous power generation and reports it to the source node; The source node reconstructs the local wave micro-topology function based on the spatial coordinates, and selects an active node cluster set accordingly; The source node predicts the microscopic physical displacement vector of each multifunctional floating platform in the active node cluster set based on the kinematic vector, maps it to the predicted phase drift, and evaluates the prediction confidence. The source node distributes data by allocating modulation order to each multifunctional floating platform in the active node cluster set based on the predicted confidence level, and allocates coordinated radio frequency transmission power based on the instantaneous power generation. Each multifunctional floating platform in the active node cluster receives and distributes data and the allocated transmission power, performs inverse timing pre-compensation on the baseband signal corresponding to the data based on the predicted phase drift, and synchronously transmits it to the remote receiving node.

[0022] The source node and all multi-functional floating platforms are located in a unified three-dimensional Cartesian global coordinate system. Let... For the current instantaneous moment of the system, the source node divides the communication time slots into consecutive communication time slots with a preset period of time, and triggers the status extraction and reporting operations of each multi-functional floating platform at the beginning of each communication time slot.

[0023] For any third party participating in the collaboration A multi-functional floating platform, which in The instantaneous hydrodynamic state data extracted at each moment is represented as a multidimensional physical feature matrix, which integrates spatial position attributes, three-axis attitude attributes, motion attributes, and energy attributes.

[0024] Spatial coordinates are defined as position vectors This is used to characterize the absolute three-dimensional position of the multi-functional floating platform in the global coordinate system, and its expression is:

[0025] In the formula, A positive integer representing the index number of the multi-functional floating platform; represent The relative distance coordinate components along the longitude direction at any given time; represent The relative distance coordinate components along the latitude direction at any given time; represent The absolute height coordinate components perpendicular to the sea level at all times. These coordinate components are calculated based on the raw parameters collected by the built-in sensors of each multi-functional floating platform and a reference benchmark, which is set as the static global positioning system absolute coordinate point of the source node deployment location.

[0026] The kinematic vector is defined as the instantaneous dynamic state of a multi-functional floating platform, which is determined by the linear velocity vector. With linear acceleration vector Together they constitute the linear velocity vector. The three-axis motion rate of a multi-functional floating platform under the thrust of ocean waves is described by the following expression:

[0027] In the formula, , , The instantaneous velocity values ​​correspond to the three orthogonal axes of the spatial coordinate system. Each instantaneous velocity value is calculated by multiplying and adding the displacement differential term sampled by the sensor and the error calibration matrix set by combining historical experience data. The error calibration matrix is ​​a 3×3 diagonal compensation matrix that has been trained and calibrated in physical simulation experiments in still water and standard wave pools using the Kalman filter algorithm. The typical value range of its main diagonal elements is limited to between 0.95 and 1.05.

[0028] Linear acceleration vector The expression describing the three-axis velocity variation rate of a multi-functional floating platform under the translational thrust of ocean waves is as follows:

[0029] In the formula, , , The instantaneous acceleration values ​​correspond to the three orthogonal axes of the spatial coordinate system, and each instantaneous acceleration value is obtained by converting the differential electrical signal output in real time by the built-in inertial measurement unit.

[0030] Instantaneous power generation is defined as a scalar , used to characterize the The real-time electrical power output of a multi-functional floating platform by capturing wave kinetic energy and converting it into electrical power at the present moment. Instantaneous power generation. Based on the wave energy monitoring module The instantaneous voltage and current samples at the output ports of the internal generator sets are continuously multiplied to obtain the power factor. The source node extracts and aggregates the instantaneous power generation data of the entire network, providing the physical energy basis data for the system to perform asymmetric allocation of radio frequency transmission power. The source node aggregates the physical feature matrices returned by all multifunctional floating platforms through the uplink control channel to construct the underlying data source system under the current communication time slot.

[0031] In this embodiment, the internal hardware components on each multifunctional floating platform work together to extract the underlying instantaneous hydrodynamic state data, providing raw physical parameters for topology reconstruction and resource allocation.

[0032] In this invention, the multi-functional floating platform extracts three-axis attitude angles and preliminary horizontal position information through an inertial measurement unit. Let the... A multi-functional floating platform The three-axis attitude angle matrix at time t is Its mathematical expression is:

[0033] In the formula, Represents the roll angle parameter. Represents the pitch angle parameter. The yaw angle parameter is represented by the three-axis gyroscope built into the inertial measurement unit, which samples the instantaneous angular velocity in the platform's body coordinate system in real time. The processing unit of the multi-functional floating platform performs discrete-time integration on this instantaneous angular velocity and fuses it with the gravity vector reference using a state observer matrix designed based on the extended Kalman filter algorithm. The low-frequency gravity acceleration vector extracted by the three-axis accelerometer is used as the observation boundary condition of the state equation to correct the low-frequency drift accumulation error of the gyroscope in roll and pitch angles in real time, thus obtaining the three-axis attitude angle matrix in the global Cartesian coordinate system. .

[0034] The inertial measurement unit (IMU) uses a built-in triaxial accelerometer to acquire raw acceleration signals in the body coordinate system. The processing unit then utilizes the triaxial attitude angle matrix... A direction cosine matrix is ​​constructed, and the original acceleration signal is rotated and transformed to the global coordinate system. After clearing the initial integral value to zero at the beginning of each communication time slot, a second time integration operation is performed using the fourth-order Runge-Kutta method with an integration step size of 10ms to obtain the relative distance coordinate components along the longitude direction at that moment. Relative distance coordinate components along the latitudinal direction This effectively suppressed integral drift.

[0035] For the vertical height component in the three-dimensional absolute coordinates, the system employs a complementary filtering algorithm to fuse data from the waterline pressure sensor. The fusion weighting coefficient for low-frequency barometric altitude data is set to 0.05, and the fusion weighting coefficient for high-frequency inertial navigation integral altitude data is set to 0.95. Using the low-frequency altitude data calculated by the waterline pressure sensor, the system real-time corrects the integral divergence error of the inertial measurement unit in the high-frequency vertical direction. The waterline pressure sensor is installed at the reference waterline position on the hull of the multi-functional floating platform, and it collects ambient seawater pressure data outside the platform in real time. The instantaneous seawater pressure collected at any time is Vertical height component The calculation formula is:

[0036] In the formula, This represents the system's preset static sea level reference height, which is calibrated to 0 meters based on historical marine survey data from the system's initialization phase. Represents standard atmospheric pressure at sea level; This parameter represents the seawater density of the area where the multi-functional floating platform is located. It is extracted from historical empirical constants in a marine hydrological database, with a typical value of 1025 kg / m³. 3 ; This represents the gravitational acceleration constant. The processing unit will integrate the obtained value. , Compared with calculations based on pressure Perform vector concatenation to generate three-dimensional absolute coordinates. .

[0037] For the extraction of kinematic vectors, the processing unit also relies on the global coordinate system acceleration signal output by the inertial measurement unit. After removing the constant gravitational acceleration component from this global coordinate system acceleration signal in the vertical direction, it is directly used as the current... Linear acceleration vector at time t Combining historical velocity information from the previous time slot, the linear velocity vector at the current moment is calculated using the sliding time window integration method. Its recursive integral formula is:

[0038] In the formula, This represents the preset sampling time slot interval duration of the system, which is set based on the inherent periodic parameters of the communication system frame structure; This represents the initial value of the linear velocity vector recorded in the previous time slot node; This represents the time integration variable within the integration operation.

[0039] Regarding the extraction mechanism of instantaneous power generation from the multi-functional floating platform, the wave energy monitoring module is connected to the power output port of the wave energy conversion generator set inside the platform. The wave energy monitoring module contains a voltage sampling circuit and a Hall current sensor to acquire in real time the instantaneous electrical parameters generated by the generator set due to capturing the kinetic energy of wave undulations. Let... The instantaneous terminal voltage collected by the wave energy monitoring module is The instantaneous loop current is Instantaneous power generation The calculation formula is:

[0040] In the formula, This represents the inherent power factor of the generator set, which is set based on historical experience data from the generator set's factory hardware test records. The processing unit will calculate the spatial coordinates within each time slot. Attitude angle matrix Linear velocity vector Linear acceleration vector and instantaneous power generation The data is encapsulated as instantaneous hydrodynamic state data packets and reported to the source node for aggregation using an independent control channel.

[0041] In this embodiment, the source node aggregates the three-dimensional absolute coordinates reported by each multi-functional floating platform and initiates a spatial surface interpolation algorithm to reconstruct the local wave micro-topology function of the sea area, thereby establishing a digital geometric mapping of the underlying hydrodynamic environment.

[0042] In this invention, source node extraction A multi-functional floating platform The set of spatial coordinates at time points is used to fit a continuous sea-level surface using a Kriging space interpolation model. Let the coordinates of any point in the spatial plane be... Local ocean wave micro-topological functions The calculation formula is:

[0043] In the formula, The total number of multi-functional floating platforms participating in the collaboration; To sum the indices; The spatial distance weighting coefficients are represented by the semi-variance variogram. In this embodiment, an exponential variogram is selected to fit the spatial correlation of ocean waves. The nugget effect constant of this variogram is set to 0. The range parameter is set to 50m based on the typical wavelength of the deployment area, and the sill value parameter is set to 2.5m based on the typical wave height variance. 2 The weighting coefficient is based on the current position of each multi-functional floating platform and the point to be interpolated. The Euclidean distance matrix between them is obtained by solving the unbiased optimal estimation equation system (i.e., the Lagrange multiplier condition equation system that satisfies the condition that the sum of all weight coefficients is 1 and the estimation variance is minimized). Representing the A multi-functional floating platform The vertical height component of the three-dimensional absolute coordinates at time t.

[0044] Obtaining local ocean wave micro-topology functions Subsequently, the source node compares the function surface changes across multiple consecutive historical time slots to calculate the wave propagation velocity vector. The source node is extracted using a two-dimensional local maximum search algorithm. Time and the previous time slot The set of peak extrema on the time-space surface is used to associate corresponding extrema between two consecutive time slots using the nearest neighbor Euclidean distance matching rule. The spatial displacement vector of the matched extrema in the two-dimensional plane is then calculated. (Wave propagation speed vector) The calculation formula is:

[0045] In the formula, and These represent the propagation speed components of the main wave along the longitude and latitude directions, respectively. represent Time-topology function Two-dimensional coordinate vectors of wave crest extreme points; This represents the system's preset sampling time slot interval duration.

[0046] The source nodes then calculate the two-dimensional surface height gradient for each location of the multi-functional floating platform. The source nodes use the central difference method to discretize the topological function grid data along... shaft and Find the numerical first-order partial derivative of the axis and substitute it into the... The planar position coordinates of the multi-functional floating platform . No. Two-dimensional surface height gradient of a multi-functional floating platform The calculation formula is:

[0047] In the formula, and These represent the spatial rate of change of the surface function in the orthogonal direction, respectively, and are used to characterize the inclination and spatial orientation of the wave surface where the multifunctional floating platform is located.

[0048] After completing topology reconstruction and parameter calculation, the source node selects the set of active node clusters based on spatial location and hydrodynamic characteristics. The source node performs a dual numerical thresholding operation on all multi-functional floating platforms in the entire network. The source node then calculates the vertical height component of the multi-functional floating platforms. With preset vertical height threshold Numerical comparison was performed, and the preset vertical height threshold was determined. Based on calibrating to 0.5 times the effective wave height of historical seasonal wave height statistics in the deployment sea area, this preset vertical height threshold is obtained under typical sea conditions in this embodiment. The specific setting is 1.5 meters to ensure that the selected nodes are stably located in the upper half of the wave surface.

[0049] Source node extracts 2D surface height gradient With the propagation speed vector of ocean waves Perform vector dot product operation. When the source node determines that the vertical height component satisfies... And the dot product result satisfies At that time, the source node confirmed that the multi-functional floating platform was located on the wave crest and wave-facing side, and was moving in the direction of the main wave propagation.

[0050] The source node includes multifunctional floating platforms that simultaneously meet both height and dot product conditions into the active node cluster set, and removes useless nodes that are located in trough positions and cause communication obstruction. Based on the selected active node cluster set, the source node generates a candidate array system to participate in communication coordination and resource allocation in this time slot.

[0051] In this embodiment, the source node initiates a microscopic physical displacement prediction algorithm to perform a hydrodynamic-to-electromagnetic cross-domain mapping mechanism for the selected set of active node clusters. The source node extracts the current... linear velocity vector at time t With linear acceleration vector The microscopic physical displacement vector is calculated based on the system's set processing delay constant. Let the time difference between system processing and synchronous waiting for instructions be denoted as . , No. Microphysical displacement vector of a multifunctional floating platform The calculation formula is:

[0052] In the formula, It is extracted based on a fixed constant sum of the instruction cycle inside the source node baseband processing chip and the inherent delay of the RF hardware link transmission, with a typical value range of 2ms to 5ms. It includes displacement components in three spatial axes, used to characterize the spatial position drift of the multifunctional floating platform from the start of state sampling to the actual radiation time of the radio frequency signal.

[0053] In this invention, the source node constructs spatial direction vectors pointing from each multifunctional floating platform to the remote receiving node based on the global coordinate system, achieving a dimensionality-reduced mapping of physical displacement to the communication link direction. Let the static absolute three-dimensional coordinates of the remote receiving node be... The absolute three-dimensional coordinates are periodically sent from the remote receiving node to the source node via the Automatic Identification System (AIS) or the initial signaling interaction link for updating and storage. The source node extracts the first... Spatial coordinates of a multifunctional floating platform Construct unit direction vector :

[0054] In the formula, The operator represents the Euclidean norm calculation operation for a vector. The source node represents the microscopic physical displacement vector. Mapped to unit direction vector The radial projection distance is obtained by vector dot product operation on the axis in question. :

[0055] radial projection distance It is a one-dimensional scalar that reflects the microscopic change in the spatial link distance between the multifunctional floating platform and the remote receiving node caused by wave-driven forces.

[0056] The source node converts the microscopic change in spatial link distance into a predicted phase drift in the electromagnetic field based on a preset radio frequency carrier center wavelength. Let the preset radio frequency carrier center wavelength agreed upon by the transmitting and receiving parties in the communication system be... Predicting phase drift The calculation formula is:

[0057] In the formula, Pi is a constant. The spatial phase constant of the carrier is used to linearly map the physical length scale to a radian angle parameter. This predicts the phase drift. The reference feedforward input values ​​constitute the baseband signal pre-compensation of the system.

[0058] The source node quantizes and evaluates the state prediction parameters, constructs and calculates the prediction confidence within a preset time window. The remote receiving node extracts the orthogonal pilot sequence from the received signal through the baseband channel estimation module, demodulates the phase deflection angle of the pilot symbols based on the least squares (LS) algorithm, calculates the spatial phase offset distortion of the actual arrived signal, and uses a low-frequency band control dedicated reverse link for periodic feedback. The source node receives the actual phase offset of this feedback and compares it with the prediction output result of the corresponding time slot. Let the remote receiving node be in the... The actual phase offset calculated and fed back for each historical time slot is: The source node calculates the phase prediction error for this historical time slot. :

[0059] The source node is selected from the consecutive nodes before the current time. A preset time window is formed by 10 historical time slots, and all error samples within this time window are aggregated to form an error sequence. The source node calculates the unbiased sample variance of this error sequence to obtain the phase prediction dispersion. :

[0060] In the formula, This represents the total number of time slots included in the preset time window. This total number is set based on historical empirical parameters of the coherence time of the sea surface radio channel. In this embodiment, the preset time window includes the total number of time slots. The typical value is set to 20; This represents the arithmetic mean of the error sequence within a preset time window. The source node is based on the inverse proportional characteristic function formula:

[0061] Phase prediction dispersion Mapped to normalized prediction confidence index parameters That is, phase prediction dispersion The smaller the value, the more accurate the displacement prediction and the higher the prediction confidence. This parameter directly triggers the logic for determining the adaptive modulation order in the RF and baseband cross-domain resource allocation module.

[0062] In this embodiment, the source node integrates various physical and statistical parameters output by the front-end module to perform cross-domain asymmetric resource allocation actions for baseband data distribution and RF power control. The source node changes the conventional logic of uniformly allocating system resources in traditional cooperative communication, implementing a heterogeneous resource allocation mechanism based on the node's physical environment state.

[0063] In this invention, within the baseband data distribution processing flow, the source node predicts the dispersion based on the phase of each multi-functional floating platform. Develop a modulation mapping strategy. The source node has a pre-defined threshold value embedded within it. The preset judgment threshold is set based on historical bit error rate experience data accumulated by the system during long-term operation under similar sea conditions. In this embodiment, the preset judgment threshold is... A typical value is 0.15 rad. 2 It is used as a benchmark boundary for measuring the channel's immunity to phase noise.

[0064] The source node will extract the phase prediction dispersion. Compared with the preset judgment threshold The comparison operations are performed sequentially. When the numerical comparison result satisfies... At this time, the source node invokes the higher-order constellation mapping rules of the internal communication protocol stack, such as 16-QAM or 64-QAM modulation, and distributes the signal using the first modulation order. The data stream indicates that the corresponding multi-functional floating platform is in a stable hydrodynamic state and the displacement prediction error is within a controllable range.

[0065] When the numerical comparison result satisfies At this time, the source node invokes the low-order constellation mapping rules of the internal communication protocol stack, such as BPSK or QPSK modulation, and distributes the signal using the second modulation order. The data stream; the above modulation order strictly satisfies numerical logic... Inequality constraints, second modulation order It has a wider phase noise immunity margin. The source node then uses the fronthaul link to transmit baseband data streams carrying different modulation orders to various multi-functional floating platforms within the active node cluster.

[0066] Within the radio frequency transmit power control process, source nodes implement asymmetric power allocation based on the instantaneous wave energy generation power. The source nodes aggregate the active node cluster set. The instantaneous power generation parameters of all internal multi-functional floating platforms are uploaded synchronously to construct the underlying energy base pool.

[0067] Source node extraction Instantaneous power generation of a multi-functional floating platform The ratio of this ratio to the sum of instantaneous power generation within the active node cluster set is calculated. Let the source node be the th... The weights allocated to each multi-functional floating platform are calculated as follows: Its mathematical expression is:

[0068] In the formula, This represents the set of active node clusters selected based on local ocean wave micro-topological functions. A positive integer representing the traversal index of the multifunctional floating platform within the active node cluster set; The scalar value obtained by summing all instantaneous power generation within the set is the weighting factor. This allows Wave Capture to achieve a higher resource allocation ratio across more platforms.

[0069] The source node calculates the final physical layer cooperative radio frequency transmit power according to the aforementioned weight allocation mechanism. Let the system's preset total transmit power for a single cooperative transmit mission be... The source node calculates the first Coordinated RF transmission power of a multi-functional floating platform The formula is:

[0070] In the formula, the system presets the total transmit power. Based on the path loss and receiver sensitivity parameters defined in the communication system link budget equation, and after comprehensive calculation and fixation, the typical setting value in this embodiment is 40W. The source node will use the dedicated cooperative radio frequency transmit power of each multi-functional floating platform. Encapsulated within downlink control commands and sent along with the baseband data stream, these commands guide the power amplifier gain bias adjustment actions of the RF front-end hardware at each node.

[0071] In this embodiment, after receiving the baseband data stream and downlink control commands sent by the source node, each multifunctional floating platform uses the underlying hardware link to perform baseband reverse timing pre-compensation and physical layer synchronous transmission actions to complete the signal mapping from the mathematical algorithm space to the physical electromagnetic space.

[0072] In this invention, the first active node cluster set... A multi-functional floating platform uses a baseband processing module to perform symbol mapping operations on the received baseband data stream to generate a digital domain initial signal. This digital domain initial signal is represented as a sequence of initial symbols in complex form. The sequence contains in-phase and quadrature data branches with orthogonal relationships. The multi-functional floating platform extracts the predicted phase drift from the feedforward input in the downlink control command. Furthermore, a rotation factor parameter is constructed within the digital baseband complex multiplier to counteract the effects of spatial displacement.

[0073] The digital baseband complex multiplier constructs a complex term with a modulus of 1 and whose phase angle is the opposite of the predicted phase drift, based on the rules of complex number arithmetic. According to Euler's expansion formula for complex functions, the algebraic expression of this complex term is:

[0074] In the formula, It is the base of the natural logarithm, a constant. For the imaginary unit of the complex plane, satisfying ; complex terms This represents a mathematical operator that produces a reverse rotation at a specific angle in the complex plane.

[0075] Subsequently, the digital baseband complex multiplier initializes the symbol sequence. With complex terms Perform bit-by-bit complex multiplication to generate a pre-compensated baseband signal. The calculation formula is:

[0076] This bit-by-bit complex multiplication operation introduces a reverse phase offset into the signal at the digital baseband level in advance. The multi-functional floating platform transmits the pre-compensated baseband signal, which includes this reverse phase offset, to the transmit data link of the RF transceiver module.

[0077] The RF transceiver module internally includes a digital-to-analog converter chip and a local oscillator mixer circuit. It converts the digital pre-compensated baseband signal into an analog baseband voltage waveform and then performs analog mixing with a high-frequency RF carrier generated by the local oscillator, completing the up-conversion process. An RF power amplifier is cascaded at the end of the RF transceiver module. The multi-functional floating platform reads the allocated cooperative RF transmit power from the control commands. By utilizing the internally preset control word and output power mapping lookup table, the physical amplitude of the input RF signal is precisely adjusted through the digitally controlled attenuator, and the gate bias voltage parameter of the RF power amplifier is independently adjusted through the digital-to-analog conversion circuit to maintain the power amplifier working in the optimal linear range, so that the RF energy intensity output by the RF transceiver module precisely matches the cooperative RF transmission power setting value.

[0078] The timing module utilizes the IEEE 1588 precision time protocol or satellite second pulse mechanism to continuously receive global timestamp information and periodic pulse trigger signals from the system synchronization clock source. In this embodiment, the pulse transmission period of the system synchronization clock source is set to 1 second. The timing module uses an internally integrated voltage-controlled cryogenic crystal oscillator to perform linear interpolation compensation for clock deviations during pulse gaps, achieving microsecond-level internal clock synchronization across all network nodes. When the global time reaches the predetermined physical layer radiation time slot boundary and the hardware layer deducts the internal trace delay errors of each node, the rising edge trigger signal of the system synchronization clock synchronously activates the RF front-end switches of all active multi-functional floating platforms. The RF signal carrying the inverse pre-compensated phase is instantaneously radiated into physical space via the communication antenna.

[0079] Space electromagnetic waves propagate across the physical link on the sea surface to the remote receiving node. During this propagation process, the microscopic physical displacement of the multifunctional floating platform caused by the actual wave motion on the sea surface generates a positive phase accumulation distortion on the space physical link. This positive phase accumulation distortion and the inverse compensation phase preset in the baseband of the radio frequency signal undergo an algebraic addition cancellation effect at the remote receiving node. The spatial arrival phases of each radio frequency signal are perfectly aligned, allowing the front-end antenna of the remote receiving node to complete the spatial in-phase superposition reception of multiple electromagnetic wave signals in physical space. Subsequently, the baseband processing unit of the remote receiving node uses a maximum ratio combining algorithm to jointly demodulate and output the superimposed signal, greatly improving the signal-to-noise ratio of the received signal.

Claims

1. A near-shore long-distance cooperative signal transmission method based on multi-functional floating platforms, characterized by cooperative execution between a source node and multiple multi-functional floating platforms, wherein... include: Each multi-functional floating platform extracts instantaneous hydrodynamic state data containing spatial coordinates, kinematic vectors, and instantaneous power generation and reports it to the source node; The source node reconstructs the local wave micro-topology function based on the spatial coordinates, and selects an active node cluster set accordingly; The source node predicts the microscopic physical displacement vector of each multifunctional floating platform in the active node cluster set based on the kinematic vector, maps it to the predicted phase drift, and evaluates the prediction confidence. The source node distributes data by allocating modulation order to each multifunctional floating platform in the active node cluster set based on the predicted confidence level, and allocates coordinated radio frequency transmission power based on the instantaneous power generation. Each multifunctional floating platform in the active node cluster receives and distributes data and the allocated transmission power, performs inverse timing pre-compensation on the baseband signal corresponding to the data based on the predicted phase drift, and synchronously transmits it to the remote receiving node.

2. The near-shore long-distance collaborative signal transmission method based on a multifunctional floating platform according to claim 1, characterized in that, Extracting the instantaneous hydrodynamic state data specifically includes: Using the inertial measurement unit, waterline pressure sensor, and wave energy monitoring module mounted on each multi-functional floating platform, the three-dimensional absolute coordinates are extracted as the spatial coordinates, the three-axis attitude angles are extracted, the kinematic vector including linear velocity and linear acceleration is extracted, and the instantaneous power generation is extracted.

3. The near-shore long-distance collaborative signal transmission method based on a multifunctional floating platform according to claim 2, characterized in that, The reconstructed local wave microtopology function specifically includes: The local ocean wave micro-topology function is reconstructed by fusing the three-dimensional absolute coordinates using a spatial surface interpolation algorithm. By comparing the local wave micro-topological functions of multiple consecutive historical time slots, the wave propagation velocity vector is calculated, and the two-dimensional surface height gradient of each multifunctional floating platform is calculated.

4. The near-shore long-distance collaborative signal transmission method based on a multifunctional floating platform according to claim 3, characterized in that, The specific steps involved in selecting the set of active node clusters are: Multifunctional floating platforms that meet the following conditions will be included in the set of active nodes: the vertical height component of their three-dimensional absolute coordinates is not less than a preset vertical height threshold, and the dot product of their two-dimensional surface height gradient and the wave propagation speed vector is greater than zero.

5. The near-shore long-distance collaborative signal transmission method based on a multifunctional floating platform according to claim 2, characterized in that, Predicting the microscopic physical displacement vector and mapping it to a predicted phase drift specifically includes: The microscopic physical displacement vector is calculated by combining the linear velocity and the linear acceleration; The projection of the microscopic physical displacement vector onto the direction pointing to the remote receiving node is calculated, and converted into an electromagnetic wave phase angle based on the preset radio frequency carrier center wavelength to obtain the predicted phase drift.

6. The near-shore long-distance collaborative signal transmission method based on a multifunctional floating platform according to claim 1, characterized in that, The assessment prediction confidence level specifically includes: Calculate the statistical variance of the error sequence between the predicted phase drift and the actual phase offset fed back by the remote receiving node within a preset time window, and obtain the phase prediction dispersion as the prediction confidence.

7. The near-shore long-distance collaborative signal transmission method based on a multifunctional floating platform according to claim 6, characterized in that, The specific steps of allocating modulation order for data distribution include: When the phase prediction dispersion is less than a preset judgment threshold, a data stream using the first modulation order is distributed. When the phase prediction dispersion is not less than the preset judgment threshold, a data stream using the second modulation order is distributed, wherein the first modulation order is higher than the second modulation order.

8. The near-shore long-distance collaborative signal transmission method based on a multifunctional floating platform according to claim 1, characterized in that, The allocation of coordinated radio frequency transmission power specifically includes: The ratio of the instantaneous power generation of a single multi-functional floating platform to the sum of the instantaneous power generation within the active node cluster is used as the allocation weight. The allocation weight is then multiplied by the system's preset total transmission power to obtain the cooperative radio frequency transmission power.

9. The near-shore long-distance collaborative signal transmission method based on a multifunctional floating platform according to claim 1, characterized in that, The reverse timing pre-compensation specifically includes: The initial symbol sequence of the baseband signal is multiplied by a complex term with a modulus of 1 and a phase angle that is the opposite of the predicted phase drift by a digital baseband complex multiplier to generate a pre-compensated baseband signal.

10. The near-shore long-distance collaborative signal transmission method based on a multifunctional floating platform according to claim 9, characterized in that, The synchronous transmission to the remote receiving node specifically includes: The pre-compensated baseband signal is up-converted and radiated into the physical space under the trigger of the system synchronous clock, so that the remote receiving node can receive it in phase.

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