612 results about "Channel models" patented technology

The invention relates to a control method of a digital ultrasonic flaw detector calibrating device. The control method comprises the following steps: acquiring shape data and material parameters of a to-be-detected material, calling a matched standard test block, calculating adaptive ultrasonic frequency and flaw detector parameters, creating and solving a multi-objective optimization model, and planning a detection path of the to-be-detected material based on an optimal solution; emitting ultrasonic waves with matched frequency to implant the quantum dot mark array to carry out fluorescence-ultrasonic dual-mode signal correlation calibration; scanning according to a planned detection path, establishing a time-varying channel model to predict a current time delay variation, extracting a fundamental frequency and a harmonic component of a probe excitation pulse by adopting an autocorrelation algorithm to serve as a reference, constructing a state vector of a filter based on the predicted current time delay variation, and performing phase correction on a received signal to obtain a phase correction signal; and analyzing the defect of the to-be-detected material based on the corrected receiving signal. By integrating material parameter dynamic modeling, multi-modal signal collaborative calibration and adaptive path optimization, the detection precision and efficiency under complex working conditions are improved.

The invention provides a low-orbit satellite resource allocation method and device based on beam and frequency domain collaborative optimization, and the method comprises the steps: dividing the overall bandwidth of a user region into a central sub-band and an edge sub-band through employing a dynamic soft frequency reuse scheme; all ground users are subjected to spatial clustering according to geographic positions and traffic demands, coverage cells are dynamically divided according to clustering results, and balanced service is achieved; on the basis of dynamic cell division, user clusters with high service volume are selected according to priorities, a beam activation set is generated, and a hopping beam matrix is updated; establishing a channel model between a user and a beam and a switching matrix between satellites; constructing a system utility target, and constructing a multi-target optimization problem model by taking the system utility target as a main part and integrating interference, switching overhead and delay penalty; and the multi-dimensional resource collaborative optimization framework based on deep reinforcement learning reconstructs a multi-objective optimization problem model, and outputs a solution of the multi-objective optimization problem model, including an optimal bandwidth and a power allocation result. According to the invention, resource allocation can be carried out on low-orbit satellites.

The invention belongs to the field of flight path prediction, and discloses a flight path stability optimization method and system, a storage medium and equipment, and the method comprises the steps: responding to aircraft kinetic parameters, pilot physiological state parameters and three-dimensional space environment parameters which are synchronously collected from multiple sources, and constructing a dynamic fusion data set through timestamp alignment; based on a pre-constructed dual-channel feature extraction architecture, dual-channel features of the dynamic fusion data set are extracted, a first channel analyzes a dynamic coupling relationship in a time dimension through a sparse attention mechanism, and a second channel models a spatial correlation topology of environmental parameters through a graph neural network; a deep reinforcement learning decision engine is constructed by fusing dual-channel features, an environment state-control action-flight path stability mapping strategy is established, and control strategy optimization is driven through a reward mechanism; and generating a multi-parameter collaborative optimization instruction of the flight control plane based on the real-time decision engine. According to the method, the efficiency and precision during flight path prediction can be improved, and then the flight path is optimized.

The invention relates to the technical field of microwave communication, and discloses a microwave communication data transmission method, which comprises the following steps: S1, sensing real-time rainfall intensity and atmospheric turbulence intensity parameters through combination of a multi-band radar and a meteorological sensor; s2, establishing a fractional order random channel model of a rainfall and turbulence coupling effect; s3, generating a dynamic coded modulation control strategy based on deep fractional order reinforcement learning; s4, optimizing a programmable metasurface reflection coefficient matrix according to the dynamic coded modulation control strategy and a channel state to reconstruct an electromagnetic propagation path; s5, executing power-codebook joint optimization of space-time coding and non-orthogonal multiple access; and S6, the system stability is monitored on line, and a degradation fault-tolerant mechanism is triggered. According to the invention, a Ku / W dual-band radar and meteorological sensor variational Kalman fusion technical scheme is adopted, and compared with a single-band radar or sparse meteorological station isolated observation scheme in the prior art, the problem of signal sudden drop misjudgment in a rainstorm scene is solved.

The invention relates to a channel estimation method based on frequency domain deviation compensation and dynamic DCT denoising, and belongs to the technical field of wireless communication. The method comprises the following steps: establishing a wireless channel model and an OFDM system model; estimating the frequency offset in the received signal by using the phase rotation characteristic of the pilot signal; calculating a preliminary channel frequency domain response # imgabs2 # at a pilot frequency position through a least square criterion based on the compensation signal # imgabs1 #; obtaining a receiving pilot frequency signal # imgabs4 # according to the sending pilot frequency Xp and the roughly estimated channel frequency response # imgabs3 #; estimating a current signal-to-noise ratio SNRest based on the pilot frequency signal # imgabs5 # and a noise power ratio; and establishing an adaptive DCT denoising strategy based on a signal-to-noise ratio threshold, and selecting different denoising strategies according to different signal-to-noise ratios to perform denoising processing on # imgabs6 # to obtain final channel estimation # imgabs7 #. The adaptive denoising strategy design of the invention effectively balances the relationship between noise suppression and channel structure fidelity, and improves the precision and stability of overall channel estimation.

The invention discloses a digital twinning synchronization-oriented queue sensing cloud edge collaborative reasoning method, which comprises the following steps of: S1, establishing a reasoning task model according to a processing requirement of data acquired by sensing equipment; s2, establishing a wireless channel model according to a wireless communication process between the sensing device and the edge server and a wireless communication process between the edge server and the cloud server; s3, establishing a task queue model according to the processing process of each task in the queue buffer area of the edge server; s4, establishing a collaborative reasoning model according to the collaborative reasoning process of the reasoning task on the edge server and the cloud server; s5, constructing an optimized objective function and a Markov model according to the low-delay demand of digital twin synchronization; and S6, a sensing device intelligent agent and an edge server intelligent agent are established by using an MAPPO algorithm, the two intelligent agents are trained based on a Markov model, and a current strategy is updated. According to the invention, the waiting time delay of priority tasks can be reduced, and the digital twinning synchronization efficiency is improved.

The invention relates to the technical field of intelligent communication, and discloses an end-to-end optimization method, a signal constellation geometry and probability joint shaping optimization method in an end-to-end intelligent communication system, and a communication device based on a neural network. According to the method, a transmitter is constructed by using a neural network, and a received signal passes through a two-stage equalization processing system to form an end-to-end optimization framework without assistance of a channel model. The transmitter adopts a modular design, can realize joint optimization of constellation probability shaping (PS) and geometric shaping (GS), and performs joint updating on all trainable parameters of the system based on a total loss function containing an equilibrium error and a decoding error through a back propagation algorithm. According to the invention, computing resources are effectively saved; the two-stage equalization system can accurately compensate channel damage, the realized PS and GS joint optimization can significantly improve the performance of the communication system and reduce the bit error rate, and the method has good performance advantages and practical value in an actual optical fiber communication system.

The invention relates to the technical field of three-dimensional model design of molds, and provides a mold three-dimensional high-precision modeling method and system based on multi-modal data fusion, and the method comprises the steps: collecting an RGB image, a high dynamic range image and a structured light depth image of an entity mold, and carrying out the reconstruction to obtain a globally consistent dense point cloud; denoising and semantic segmentation are carried out on the point cloud, and a cavity function area, a core function area and a runner function area are recognized; performing differential parametric modeling based on an identification result: performing geometric primitive fitting on regular geometric features, performing NURBS curved surface reconstruction on a free-form surface, and performing swept volume or rotator fitting on a flow channel to obtain a parameterized geometry, a parameterized curved surface and a parameterized channel model; and applying boundary continuity constraint to fuse the parameterized geometry, the parameterized curved surface and the parameterized channel model, and constructing a hybrid parameterized three-dimensional model. According to the method, rapid reconstruction of a high-precision, high-semantic and full-parameterized three-dimensional model of an entity mold can be realized.

The invention discloses a communication data transmission method and system for an intelligent charging pile, and relates to the technical field of intelligent charging pile communication, and the method comprises the steps: constructing a reverse power line transmission channel model based on an equivalent channel response matrix, extracting channel frequency response, generating a channel equalization configuration parameter set through a joint optimization equalization algorithm, and transmitting the channel equalization configuration parameter set to a communication module. Subcarrier modulation orders are dynamically allocated according to the signal-to-noise ratio parameter, and a pre-balanced OFDM time domain signal is generated; on the basis of the channel equalization configuration parameter set and the pre-equalization OFDM time domain signal, dynamically monitoring power frequency harmonic noise of the cable, and inhibiting interference through a filtering algorithm to generate a clean power line carrier signal; and generating a verified V2G communication control instruction through a cyclic redundancy check method based on the clean power line carrier signal in combination with the main polarization direction feature vector. According to the method, an accurate channel model is constructed by combining an equivalent channel response matrix and cable characteristics, and dynamic subcarrier distribution is realized based on signal-to-noise ratio parameters.

The invention discloses a dynamic channel transmission characteristic optimization method for a boundary layer meteorological observation aircraft, and the method comprises the steps: supposing that a direct path between a transmitting end and a receiving end is shielded by an obstacle in the air-to-ground communication in a boundary layer in which the meteorological observation aircraft participates; and one part of the signal sent by the transmitting end is reflected to the receiving end through the moving scatterer, and the other part of the signal directly reaches the receiving end without interference. According to the invention, a communication environment between a mobile transmitting terminal and a mobile receiving terminal is described by adopting a geometric stochastic modeling mode, a DRL enabling boundary layer meteorological observation aircraft channel transmission characteristic dynamic optimization method based on geometric characteristics is established, and a nonlinear relationship between motion characteristics of a meteorological observation aircraft and a channel model is revealed. The method has important application value for evaluating the performance of the air-to-ground wireless communication system in the DRL auxiliary boundary layer.

The invention relates to an Internet of Vehicles channel selection method based on a multi-agent depth deterministic strategy gradient algorithm, and belongs to the technical field of communication. The method comprises the following steps: establishing an Internet of Vehicles system model, and setting local and global environment variables, a vehicle action space and a reward function of the Internet of Vehicles system model; establishing a dynamic channel model of the Internet of Vehicles based on the system model of the Internet of Vehicles, and determining a state space and steady-state probability distribution under multi-channel combination; a graph neural network GNN is introduced into a multi-agent depth deterministic strategy gradient algorithm, and a GNN-Critic network is established to process dynamic vehicle input information; the intelligent body vehicle learns a channel selection strategy by using a global environment state so as to complete centralized training; and after training is completed, the intelligent body vehicle observes local channel state distribution and executes channel selection. According to the method, the channel utilization rate can be remarkably improved, the vehicle can make a better channel selection decision according to the global environment information, the channel idle time is reduced, and the overall network performance is improved.

The invention discloses a multi-antenna joint precoding Gbit wireless transmission system, which relates to the technical field of wireless communication and comprises a frequency spectrum channel acquisition module, a signal preprocessing module, a precoding joint optimization module, a transmission performance evaluation module and a closed-loop parameter control module. The spectrum channel acquisition module acquires signal data and evaluates a transmission bit error rate and a signal-to-noise ratio by using a spectrum analyzer; the signal preprocessing module performs denoising and normalization and constructs a channel model; the precoding joint optimization module dynamically adjusts precoding and suppresses bit error diffusion; the transmission performance evaluation module calculates a data rate and optimizes protocol design; and the closed-loop parameter control module dynamically configures system parameters to guarantee closed-loop optimization. According to the method, the transmission efficiency and the stability of a Gbit wireless transmission system are remarkably improved, a complex channel environment is effectively dealt with, the bit error rate is reduced, the data rate is improved, a transmission protocol is optimized, intelligent dynamic adjustment of system parameters is realized, and the optimal performance of a multi-antenna joint precoding technology is ensured to be exerted.

The invention provides a multi-user near-field secure communication method based on stacked intelligent metasurfaces, and relates to the technical field of wireless communication. The method comprises the following steps: obtaining an equivalent beamforming matrix and a first-layer channel transmission matrix of an SIM according to parameters of the SIM in a base station; according to the transmission distance between the SIM and the user and the transmission distance between the SIM and the eavesdropper and the parameters of the SIM, modeling a near-field channel to obtain a near-field channel model; obtaining a data transmission rate in combination with a beamforming vector of the base station, and further determining the security and the rate; and by taking maximization of the safety and the rate as a target, constructing an optimization model and decomposing the optimization model into two sub-problems to carry out alternate iterative optimization so as to obtain an optimized equivalent beam forming matrix and an optimized beam forming vector. An SIM is introduced, the freedom degree of beam regulation and control is increased, optimization is carried out on the basis of a near-field channel model by taking maximization of safety and rate as targets, legal users and eavesdroppers are effectively distinguished, signal energy is accurately guided to the legal users, and the communication safety is improved.

The invention discloses an Internet of Vehicles channel modeling method considering antenna attitude vibration, and the method comprises the steps: building an accurate vibration model of an antenna three-dimensional attitude through precisely modeling vehicle body tiny vibration caused by bumping, steering and other factors in vehicle driving into micro-motion of an antenna attitude at three time-varying Euler angles of pitching, rolling and yawing; the time-varying attitude is introduced into a coordinate system rotation matrix, the random vibration characteristic parameterization of the antenna in a three-dimensional space is realized, and then the random vibration characteristic parameterization is coupled to the evolution of key parameters of a channel model, so that the channel rapid fluctuation and beam mismatch effect caused by the antenna attitude jitter can be more accurately reproduced; the method can effectively solve the problems that in the prior art, due to the fact that microcosmic vibration of an antenna is ignored, the fidelity of a model is low, and characterization of a key beam mismatch effect in millimeter wave communication is seriously insufficient, and can provide theoretical basis and data support for performance evaluation and beam management algorithm design of a high-dynamic and high-reliability car networking system.

The invention relates to the technical field of radar reflectivity factor calibration, and discloses a terahertz cloud measurement radar calibration method based on channel perception, which comprises the following steps: S1, acquiring two types of input data; s2, constructing a multi-scale channel model; s3, constructing a distance error estimation model; s4, constructing a dynamic time correction model; and S5, constructing a calibration module. According to the method, a high-precision physical channel model is constructed to independently predict path attenuation of signals, the concepts of gain deviation and path attenuation factors are put forward, the influence of thermal noise attenuated by radar on radar waves in the atmospheric environment is reflected respectively, and a Kalman filtering algorithm is used to estimate the path attenuation of the signals. And filtering errors generated in the time direction, and finally, calibrating the radar reflectivity factor by using the channel data by means of a calibration formula.

Disclosed are a channel estimation method, apparatus and device, and a storage medium, which relate to the technical field of communications, comprising: acquiring a channel parameter and a channel coefficient matrix of a pilot symbol based on received signal data, the channel parameter being a channel model parameter of non-ground network communication; determining a first wiener filter tap coefficient from a preset typical wiener filter tap coefficient set according to the position combination of the channel parameter and the pilot symbol; and determining a time domain channel estimation result of the received signal data according to the first wiener filter tap coefficient and a channel coefficient matrix of a pilot symbol. According to the technical scheme, the channel estimation process in a non-ground network communication scene is simplified, and the real-time performance of time domain channel estimation is improved on the premise of ensuring the accuracy of a channel estimation result.

The invention relates to the technical field of beam forming, in particular to a flow antenna assisted communication sensing integrated beam forming method and device, and the method comprises the steps: building a flow antenna FAS communication channel model, and constructing a radar sensing model employing multiple input multiple output (MIMO) at a base station end; the method comprises the following steps of: establishing an optimization problem of combining port selection and beamforming under the constraint of meeting a minimum communication SNR (Signal to Noise Ratio) requirement, a minimum sensing SNR requirement and a limited port activation number by taking minimization of system transmitting power as a target; and setting constraint conditions, solving a target problem, and obtaining a communication-sensing integrated beam forming matrix. Therefore, the problems that performance coupling is aggravated and the joint design complexity is high due to the fact that the tradeoff of the communication rate and the sensing precision in the ISAC and optimization variables are increased through FAS dynamic port switching, and the performance potential is difficult to play due to the fact that the FAS extra freedom degree is not effectively combined with ISAC beam forming and waveform design are solved.

The invention belongs to the technical field of wireless communication, and particularly relates to a communication method and device based on MQAM-OFDM modulation, a medium and equipment, and the method comprises the steps: generating a random data source, carrying out MQAM modulation, generating a serial modulation signal, carrying out serial-parallel conversion and subcarrier mapping, and obtaining frequency domain subcarrier data; performing inverse fast Fourier transform on the frequency domain subcarrier data to generate a time domain OFDM symbol, and adding a cyclic prefix to obtain a sending signal; transmitting the sending signal based on a multipath channel model; receiving a sending signal and removing a cyclic prefix part in the sending signal to obtain an effective OFDM signal; performing fast Fourier transform on the effective OFDM signal to recover frequency domain data, and obtaining a frequency domain receiving symbol sequence; performing channel estimation and equalization on the frequency domain receiving symbol sequence to obtain a frequency domain symbol estimation value; and performing MQAM demodulation on the frequency domain symbol estimation value, and recovering the parallel data stream into the serial bit stream to complete data recovery.

The invention relates to the technical field of wireless communication, in particular to a reachable rate optimization method based on an intelligent reflecting surface, which comprises the following steps of: firstly, constructing a channel model in an application scene, namely designing a system reachable rate optimization model on the basis of establishing a base station-user, base station-IRS and IRS-user three-link model; then, a phase shift matrix of the IRS and an emission covariance matrix of a base station serve as joint optimization variables, a population is divided into an elite subpopulation, a suboptimal population and a common population through a subpopulation grouping strategy of an improved particle swarm algorithm, each particle represents the composed variable, a dynamic cooperation strategy is proposed to calculate the speed in each subpopulation, and the speed in each subpopulation is calculated; and updating individual optimization and group optimization, and continuously carrying out iteration to search a reachable rate optimal solution of the user. According to the method, local search can be finely carried out while large-range global search can be carried out, the calculation complexity is remarkably reduced, and the IRS transmission effect is improved.

The invention relates to the technical field of wireless communication networks, and discloses a communication optimization method and system for a wireless energy-carrying safety communication system in a far and near mixed field. The method comprises the following specific steps: constructing a wireless energy-carrying safety communication system in a far-near hybrid field, wherein the wireless energy-carrying safety communication system comprises a base station, an energy collection receiver with K near-field single antennas and an information decoding receiver with M far-field single antennas; constructing a mixed field channel model; constructing a signal model comprising the information signal and the digital beam forming matrix thereof, and the artificial noise and the digital beam forming matrix thereof; based on the signal model and the mixed field channel model, a maximization problem objective function of the minimum safety rate weighted sum of the information decoding receiver is formulated; and solving a maximization problem to obtain an optimal communication scheme. The method solves the problem that vector optimization of beam forming is lacked in the prior art, and has the characteristic that the information transmission security of the system can be improved.

The invention discloses an unmanned aerial vehicle data collection trajectory optimization method based on a customized channel. According to the method, a customized channel model in a fixed scene is obtained through machine learning and ray tracing simulation, the model is applied to unmanned aerial vehicle data collection, variables such as an unmanned aerial vehicle flight path and signal transmitting power are considered, the unmanned aerial vehicle data collection task completion time is optimized, the time is minimized, solving is performed through a reinforcement learning Optimized PPO algorithm, and the accuracy of the unmanned aerial vehicle data collection task is improved. Compared with the prior art, the method has the following beneficial effects: the channels in different scenes can be accurately modeled by designing the customized channels in combination with ray tracing and machine learning; a more reasonable reward function with faster convergence is designed; the convergence of the Optimized PPO algorithm is superior to that of the traditional PPO algorithm.

The invention discloses a 5G-TSN network resource scheduling method based on a near-end strategy optimization algorithm, which completes 5G-TSN network resource scheduling by establishing a 5G wireless channel model, constructing a Markov decision process model and realizing action value output and strategy optimization through the near-end strategy optimization algorithm. According to the network resource scheduling method provided by the invention, a dynamic resource allocation strategy is realized based on gating state sensing, ultralow delay services such as robot control instructions and the like can be preferentially scheduled when gating of a time-sensitive network is started, and non-real-time services such as resource transmission video monitoring and the like can be intelligently multiplexed when the gating of the time-sensitive network is closed; the wireless resource utilization rate is effectively improved, meanwhile, it is ensured that data with high real-time performance can be transmitted as soon as possible in a short time, reliable transmission of equipment data in an industrial scene is ensured, scheduling mechanisms of a 5G wireless network and a time-sensitive network are fused, resource scheduling is efficiently carried out, and the real-time performance, reliability and resource utilization rate of data transmission are balanced.

The invention discloses a relay unmanned aerial vehicle track optimization method, which comprises the following steps of: firstly, constructing a lossy relay unmanned aerial vehicle communication system model under finite length coding, and covering communication time slot division, unmanned aerial vehicle flight constraint and a channel model; deducing outage probability expressions of two communication strategies under finite length coding, wherein the outage probability expressions are an independent decoding strategy and a joint decoding strategy respectively; then, a trajectory optimization problem is converted into a Markov decision process (MDP), and a state space, an action space, a reward function and a state transition mechanism are clarified; solving by adopting a joint optimization algorithm based on depth deterministic strategy gradient (DDPG) to realize joint optimization of the unmanned aerial vehicle track and the communication strategy; and finally, outputting an optimal unmanned aerial vehicle track and strategy configuration to provide reference for actual system deployment. The method can effectively reduce the outage probability of the system and improve the communication reliability under the condition of limited length coding, and is suitable for various scenes in 6G and future air-ground cooperative communication networks.

The invention discloses an unmanned aerial vehicle air-to-air channel modeling simulation method for an urban low-altitude scene, and the method comprises the steps: calculating the time delay, total phase and power of a sight distance path of an unmanned aerial vehicle transmitting and receiving end in a channel model according to the input position parameters of the transmitting and receiving end; calculating to obtain a channel impulse response of the sight distance path by combining a sight distance path antenna pattern function related to the attitude; calculating the time delay, the total phase and the power of a roof reflection path in the channel model in combination with communication scene parameters; in combination with a non-line-of-sight path antenna pattern function related to the attitude, calculating to obtain a channel impulse response of a roof reflection path; calculating the time delay, the total phase and the power of a non-line-of-sight path in the channel model in combination with geometrical relationship parameters limiting scatterer distribution; calculating to obtain a channel impulse response of a non-line-of-sight path in combination with an antenna pattern function related to the attitude; and establishing an unmanned aerial vehicle air-to-air channel model, and outputting a channel coefficient. According to the invention, efficient and accurate reproduction of the air-to-air channel of the unmanned aerial vehicle is realized.

The invention discloses narrowband communication equipment detection equipment and a detection method. The method comprises the steps that a pre-established wireless channel model data set is acquired, and the data set comprises attenuation values and interference intensity distribution data in different environments; constructing a multipath propagation simulation model according to the attenuation value and the interference intensity distribution data, obtaining a time delay extension range value by adopting time domain analysis, and obtaining an amplitude distortion range value by combining frequency domain analysis; and inputting actual measurement data of the environmental noise, the time delay extension range value and the amplitude distortion range value into an adaptive filtering algorithm to generate signal quality evaluation data after filtering processing, and the like. According to the method, through analysis and simulation of channel model data in different environments, various test means and algorithms are combined, and the performance of the equipment under various conditions, including signal quality, bit error rate, stability, risk and the like, is comprehensively evaluated, so that the reliability of the equipment in practical application is ensured.

The invention discloses an unmanned aerial vehicle relay route planning method based on photoelectric hybrid switching. The method comprises the following steps: establishing a free space optical channel model, and focusing a flicker effect caused by turbulence and attenuation caused by weather; when a radio frequency channel model is constructed, line-of-sight and non-line-of-sight large-scale fading are fused, and downlink multi-user interference is quantized; establishing a hybrid obstacle model based on a Ray-AABB algorithm, fusing ground static and air dynamic obstacles, and determining a sight distance connection feasible position set; a boundary reflection type random walk model is adopted to describe user movement, and a speed and direction two-parameter updating mechanism and a boundary elastic collision rule are defined; the user throughput is dynamically optimized in combination with fractional order power distribution and non-orthogonal multiple access technologies; a deep reinforcement learning framework is provided, and a three-dimensional track, photoelectric switching and resource allocation are jointly optimized by using a dual deep Q network. According to the invention, the challenge of a low-altitude spectrum rejection environment can be effectively handled, and the robustness and adaptive capacity of the system are ensured.

The invention relates to the field of communication, in particular to a multipath channel enhancement method and system based on AoA filtering in a communication and inductance integrated system. Constructing an uplink communication scene, and generating a transmitting signal, a receiving signal and a channel model based on the uplink communication scene; performing channel estimation on the transmitting signal and the receiving signal based on a least square algorithm to obtain a channel response estimation value; sensing and acquiring AoA information of each communication path, and constructing a channel transfer factor based on the AoA information and a channel model; and performing Kalman filtering processing on the channel response estimation value based on the channel transfer factor, and outputting a filtered channel vector. According to the method, the communication path angle information obtained by sensing is combined with Doppler information, and the channel response estimation value is dynamically optimized by adopting Kalman filtering, so that the estimation precision and real-time performance of the channel state information in the multipath environment are improved.

The invention provides a satellite resource pre-allocation method and system and a computer readable medium, and relates to the field of satellite communication, and the method comprises the steps: building a channel model of a downlink during the transit period of a beam-hopping multi-beam satellite based on downlink information from the beam-hopping multi-beam satellite to a user, setting a model constraint for the channel model, modeling is carried out for optimizing the queue length of a waiting queue of the last time slot in the transit period of the beam-hopping multi-beam satellite, and a queue length optimization model is obtained; simplifying the queue length optimization model to obtain a simplified queue length optimization model; and dividing the simplified queue length optimization model into two independent sub-problems, and solving to obtain an optimal solution of time slot allocation, an optimal solution of power allocation and an optimal solution of frequency band allocation of the beam. The resource scheduling difficulty of the satellite can be reduced, the delay can be reduced, the communication efficiency can be improved, the adverse effect of the highly dynamic performance of the channel environment can be reduced, and the real-time communication requirement can be met.

The invention belongs to the technical field of short-wave communication channel modeling, and discloses a short-wave channel modeling method and system based on signal wavefront recovery, and the method comprises the steps: projecting standard plane waves to an antenna array from different angles through a cooperative target radiation source, collecting antenna array signals in different directions under the condition of no disturbance, and storing the signals as calibration data; calculating the time delay of each antenna before receiving the wavefront relative to the center of the antenna array, calculating the relative time delay of the time delay and the calibration data, and multiplying the relative time delay by the wavelength to realize the time domain-space domain conversion of wavefront distortion to obtain wavefront slope distribution; and calculating the size of a Zernike polynomial coefficient of each order based on wavefront slope distribution, analyzing specific components of aberration contained in signal wavefront, and performing wavefront fitting reconstruction so as to complete short-wave channel modeling. According to the method, the Zernike polynomial is adopted to fit the wavefront disturbance quantity, the influence of the ionized layer on the wavefront of the short-wave signal is quantified in real time, and a high-precision channel model is constructed.

The invention belongs to the technical field of communication, and relates to an unmanned aerial vehicle user association and 3D flight path optimization method for anti-interference communication. The method comprises the steps of firstly obtaining information of the unmanned aerial vehicle, each ground node and an interference node to establish a system model, then establishing a 3D trajectory operation model, a user association strategy model and a sight distance probability channel model of the unmanned aerial vehicle, defining a communication rate, and finally establishing an optimization problem of maximizing the total throughput of the system. An optimization problem is modeled as a Markov decision process, finally a user association and unmanned aerial vehicle 3D trajectory planning network is constructed, and an unmanned aerial vehicle learning optimal strategy and an unmanned aerial vehicle 3D trajectory and user association strategy are obtained through a deep learning framework. According to the method, while the lightweight characteristic is maintained, user scheduling and unmanned aerial vehicle 3D trajectory control are dynamically realized, and the communication performance of an unmanned aerial vehicle auxiliary communication system in a malicious interference environment is remarkably improved.