152 results about "Outage probability" patented technology

The present invention discloses a disaster prevention, early warning and production decision support method and system for a power distribution network, and relates to the technical field of the power distribution network. Various data is fused, a maximum wind load, a lightning trip-out rate, a maximum carrying capacity at a highest operation temperature and an average failure frequency and time under an environmental factor are calculated, and a power outage risk is evaluated and classified; and after an emergency, a power grid topology is analyzed, and a device outage probability is calculated to obtain a load power outage probability and risk and provide disaster early warning, monitoring and rush repair decision support.

The invention discloses a network access permission dynamic management and control method and system based on behavior analysis, particularly relates to the technical field of network security, and is used for solving the problem of systematic service interruption caused by neglecting implicit association between permission and service logic in the existing dynamic permission strategy. The method comprises the following steps: constructing a permission dependency graph by collecting real-time behavior data of a user and equipment in real time, identifying hidden dependency nodes which have indirect data streams with a target interface but are not explicitly called, and generating a hidden path weight coefficient in combination with a historical behavior log; based on the real-time behavior characteristics and the map topological structure, quantizing the outage probability of permission adjustment on dominant and hidden dependency paths, and dynamically generating an alternative access interface and a data transfer interface; when an alternative path abnormal operation is detected, an original path is traced back through a permission dependency graph, and permission configuration is iteratively optimized; the continuity of the business data flow is maintained while the dynamic contraction of the authority is ensured, and the interruption of the associated service caused by local authority change is avoided.

The invention relates to the technical field of smart power grids, and provides a power distribution network power failure probability analysis and resource scheduling optimization method based on a knowledge graph, which realizes minute-level node association weight updating through a streaming updating mechanism, and remarkably improves the power failure risk identification accuracy in extreme weather by combining with dynamic adjustment of a meteorological risk function. A topology / environment double-attention architecture is adopted to fuse multi-source features, so that the fusion efficiency of equipment node features and environment node features is improved; and a fault deduction model with dynamic weight constraint is introduced, so that the secondary fault early warning capability is enhanced. In a resource scheduling link, a mixed integer programming model of a carbon emission factor and island power balance constraint is integrated, and Pareto optimization of first-aid repair efficiency and an environmental protection target is realized. Through transfer learning, knowledge graph cross-region adaptation is realized, and the novel transformer area access error is controlled to be reduced in a distribution network reconstruction scene. The method supports minute-level topology reconstruction and second-level weight updating, has low delay and high expansion capability, and is suitable for provincial power grid real-time deployment.

According to the robust beam forming method for the AN enhanced RIS assisted physical layer security communication, the transmitting power of a base station is minimized on the premise that the system service quality requirement and the security rate outage probability constraint are met. The method comprises the following steps: firstly, constructing a security rate interruption constraint based on a base station-RIS-eavesdropper cascade channel transmitting end imperfect CSI model, and then approaching a security rate interruption probability constraint by using a Bernstein inequality, thereby reexpressing an original problem as a processable convex constraint. Under an alternating iterative optimization framework, positive semi-definite relaxation is utilized to convert a sub-problem into a convex problem, a sub-optimization problem of a given beam forming vector optimization RIS phase shift matrix is rewritten, a slack variable is introduced to re-express an original feasibility verification problem, and finally a base station transmitting beam forming vector is iteratively optimized. The AN beam forming vector and the RIS reflection beam forming matrix improve the system safety rate and the system robustness.

The invention discloses a DC / DC converter reliability evaluation method and a related device, and the method comprises the steps: constructing an electrothermal coupling model of a power switch module of a Boost full-bridge boost isolation converter BFBIC combined DC / DC converter topological structure, and obtaining the power loss and junction temperature change conditions; constructing a life prediction model based on the junction temperature change condition, and calculating a failure rate in combination with a fatigue damage accumulation model; and establishing a calculation model of the outage probability of the series / parallel module based on the fault rate, and evaluating the reliability of the Boost full-bridge boost isolation converter combined DC / DC converter by using an improved reliability block diagram method. The method provided by the invention is helpful for reducing the evaluation error of the equipment reliability, and can provide data support for the construction and development of a novel power system.

The invention discloses an unmanned aerial vehicle cluster relay system optimization method, and aims to significantly reduce the overall outage probability of the system by performing adaptive optimization on cooperative position deployment and flight trajectories of multiple unmanned aerial vehicles under multiple actual constraint conditions of flight speed, safety distance, flight boundary and the like. Therefore, the reliability and the service quality of the multi-unmanned aerial vehicle relay communication network are improved. According to the method, a Markov decision process (MDP) model is constructed, a multi-unmanned aerial vehicle trajectory optimization problem is converted into a multi-agent reinforcement learning problem, and efficient optimization of unmanned aerial vehicle trajectories is realized by using a centralized training-distributed execution framework, so that the outage probability of a communication system is minimized.

The present invention discloses a device-to-device covert communication system assisted by a drone and an intelligent reflecting surface, establishes a drone and intelligent reflecting surface UIRS joint-assisted D2D covert communication model, including communication links between various entities, calculates the average minimum error detection probability and the maximum communication rate; the sender sends a covert signal to the UIRS, and the UIRS forwards it to the receiver. Among them, the UIRS changes the angles of the corresponding incident covert signal and the reflected covert signal through its constituent elements; the spectrum-sharing cellular user sends a cellular signal to the base station, and at the same time the base station sends an interference signal, introducing an uncertainty factor at the receiver of the eavesdropper Willie to achieve the covertness of the UIRS joint-assisted D2D communication link; the eavesdropper Willie monitors whether the UIRS joint-assisted D2D communication link transmits a covert signal; the covertness is measured by the average minimum error detection probability; under the multiple constraints of satisfying the average minimum error detection probability, the cellular communication link outage probability, the transmission power, and the transmission power of the interference signal, etc., the maximum communication rate of the UIRS joint-assisted D2D communication link is obtained, and the communication rate of the system is effectively improved under the joint assistance of the drone and the intelligent reflecting surface UIRS.

The invention discloses a secure communication method for eavesdropping a D2D relay NOMA network. The communication process has two time slots; in the first time slot, the information source equipment sends an NOMA signal, and the multi-antenna relay equipment selects one antenna to send an interference signal to resist eavesdropping attack; in the second time slot, the relay equipment adopts the digital network coding technology to mix the interference signal of the first time slot and the decoded information source message, then adopts the NOMA technology to construct a novel NOMA signal, and re-selects one antenna to send the NOMA signal, and meanwhile, the information source sends another interference signal to weaken the eavesdropper; the NOMA user equipment and the eavesdropper calculate a required signal-to-noise ratio and a required signal-to-interference-and-noise ratio, and calculate a system outage probability and an eavesdropping probability; according to the invention, the two NOMA users can realize physical layer security communication in the D2D network, and the security of the physical layer is far better than that of a security communication scheme based on non-cooperative interference and a traditional security communication scheme based on cooperative interference.

The invention discloses a resource allocation method of STAR-RIS assisted cellular-free mMIMO (multiple input multiple output). The method comprises the following steps: acquiring position information of UE, AP and STAR-RIS, acquiring channel state information (CSI) of each communication link, and constructing a state information set of a current system based on the position information and the CSI; based on the state information set, utilizing an Actor network in a depth deterministic policy gradient (DDPG) algorithm to generate an optimization action; adjusting resources among the UE, the AP and the STAR-RIS on the basis of the optimization action, performing downlink signal transmission on the basis of the adjusted resources, and calculating the outage probability, the SINR and the information transmission rate per unit time of the UE; and outputting an instant reward value under the optimization action based on the outage probability, the SINR and the information transmission rate, and performing updating optimization based on the instant reward value. According to the invention, the technical problem of poor performance of a traditional cellular-free large-scale MIMO communication system is solved.

The invention discloses a start-stop channel decision-making method and system based on reinforcement learning, and the method comprises the steps: constructing a traffic flow interruption probability model through employing a Brilon model, and depicting a relation between a congestion probability and a traffic flow parameter; converting a start-stop channel decision problem into a Markov decision process, and determining a state space, an action space and a state transition probability of the Markov decision process; and solving the Markov decision process by adopting a Q-Learning algorithm to obtain a start-stop channel decision. According to the invention, the traffic condition in a period of time in the future can be accurately pre-judged, and the use strategy of the emergency lane is planned in advance; by optimizing the start-stop decision logic, unnecessary resource waste is reduced, meanwhile, the use reasonability and efficiency of the emergency lane are improved, and it is ensured that the lifeline is unobstructed at the key time.

The invention provides a performance evaluation method and system of an LEO satellite assisted deep space communication system, the LEO satellite assisted deep space communication system comprises a detector, an LEO satellite and a ground terminal, the detector and the LEO satellite communicate through an FSO link, the LEO satellite and the ground terminal communicate through an RF link, and the LEO satellite is connected with the ground terminal. The method comprises the following steps: in a design stage of an LEO satellite-assisted deep space communication system, obtaining index parameters influencing FSO link communication quality, including a corona turbulence intensity parameter, a pointing error parameter and a solar noise parameter; the index parameters comprise a shadow intensity parameter, an LEO satellite position parameter and a molecular absorption coefficient; the index parameters are input into a constructed deep space communication system performance evaluation model, performance indexes are obtained, and the performance indexes comprise the outage probability, the channel capacity and the bit error rate; and evaluating the performance of the deep space communication system according to the performance index. The method can evaluate the performance of the deep space communication system more comprehensively and accurately.

The invention relates to a mobile antenna communication system robust resource optimization method based on angle information uncertainty, and belongs to the field of wireless communication. The method comprises the following steps: constructing a mobile antenna communication system model, and establishing a system energy efficiency maximization resource allocation model based on bounded angle information uncertainty by considering base station transmitting power constraint, user rate constraint, channel uncertainty constraint and mobile antenna spacing constraint; a non-convex original problem is equivalently converted into a convex subproblem about base station beam forming and movable antenna positioning by using transformation replacement, Bukbach, exponential conversion, continuous convex approximation, an S process, a subgradient inequality, singular value decomposition and a block coordinate descent method; and solving a plurality of convex sub-problems by using the CVX to obtain an optimal beam forming matrix and a movable antenna position vector, namely an optimal resource allocation strategy. The energy efficiency of the mobile antenna system can be effectively improved, and compared with a traditional method, the communication outage probability can be effectively reduced.

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 a turbulence model for underwater wireless optical communication and a communication system performance calculation method, and the method comprises the steps: building a new turbulence statistical distribution model under the condition of ocean turbulence, and obtaining an expression of a flicker index of the model in combination with model parameters; and a Meijer-G function and a Fox-H function are utilized to obtain a closed expression of the outage probability and the bit error rate under the model condition, so that the influence on the transmission performance of the system under different scene parameters can be researched. Compared with an existing turbulence model, the method is closer to the complex turbulence environment of the ocean, and especially under the complex turbulence scene of bimodal distribution, simulation research on the real ocean environment can be better achieved.

The invention provides a communication system resource allocation method and system based on semantic information, and relates to the technical field of wireless communication. According to the method provided by the invention, a to-be-transmitted image is processed to obtain a semantic importance score of each semantic feature vector corresponding to the to-be-transmitted image; then determining the semantic importance weighted information amount of each semantic feature vector; sorting the plurality of semantic feature vectors from large to small according to the semantic importance weighted information amount to obtain a first sequence; and according to the first sequence, sequentially determining a channel with the minimum communication interruption probability corresponding to each semantic feature vector, wherein the available transmission information amount of the channel is greater than the required transmission information amount. According to the method provided by the invention, the importance scores of the plurality of semantic vectors included in the to-be-transmitted image are determined, and then the channels with small interruption probability are allocated to the semantic vectors with high importance based on the importance scores of the plurality of semantic vectors, so that the information transmission efficiency can be improved.

The invention discloses an optimal concealment rate optimization method based on a time slot cognitive star-air-ground fusion network, and the method comprises the steps: firstly, enabling a satellite to select an unmanned aerial vehicle relay with the maximum channel gain as a forwarding unmanned aerial vehicle relay through the instantaneous channel state information of a link between an unmanned aerial vehicle relay and a satellite; in a second time slot, by means of a main link between the forwarding unmanned aerial vehicle relay and the main user, the forwarding unmanned aerial vehicle relay overlays the hidden message sent by the satellite to the NOMA secondary user with the message of the main user and then forwards the message downwards; a closed expression of a detection error probability, an interruption probability and an effective hiding rate of an eavesdropper is deduced, a power optimization problem is constructed and solved, and the effective hiding rate of two-hop hiding transmission is maximized by optimizing a power distribution factor. According to the method, the concealment performance of the cognitive star-sky-ground fusion network can be remarkably improved.

The invention discloses a secure communication method based on artificial noise in an unmanned aerial vehicle NOMA network. The communication process has two time slots. In a first time slot, a base station adopts an NOMA mechanism to send a signal to an unmanned aerial vehicle, meanwhile, the unmanned aerial vehicle selects one antenna to send an artificial noise signal to interfere with an untrusted remote user, the remaining antennas receive the signal, and a near user also sends the artificial noise signal; in a second time slot, the unmanned aerial vehicle adds the artificial noise signal and the near user signal of the first time slot by means of exclusive OR, then superposes the obtained signal and the far user signal by means of an NOMA mechanism, and finally reselects one antenna to send the superposed signal; then the NOMA user obtains a corresponding signal to interference plus noise ratio or a signal to noise ratio according to the received signal, and calculates a system outage probability and an eavesdropping probability; the method can effectively weaken the eavesdropping capability of the untrusted user, basically does not affect the untrusted user to receive the own message, and helps to solve the problem of potential safety hazards in an actual unmanned aerial vehicle cooperative NOMA network communication scene.

The invention discloses an unmanned aerial vehicle auxiliary relay system power control method based on statistical knowledge, and belongs to the technical field of wireless communication, and the method comprises the steps: initializing the peak transmitting power and average transmitting power of a source node A and an air unmanned aerial vehicle relay R, initializing the outage probability limit and the rate at which the A transmits data information to a destination node B through the R, dividing the flight time delta of the unmanned aerial vehicle into 2I time slots; the unmanned aerial vehicle relay and the ground source node obtain statistical knowledge of the system; solving the optimization problem to obtain an identification vector of a time slot capable of being used for communication from A to B, the transmitting power of A and the transmitting power of R; and finally, controlling the transmitting power of the source node and the transmitting power of the aerial unmanned aerial vehicle relay according to the obtained result. The probability line-of-sight link condition between the unmanned aerial vehicle and the ground node and the large-scale and small-scale fading effects are jointly considered, the transmitting power of the source node and the unmanned aerial vehicle relay is optimally controlled, and more data information can be transmitted.

The invention discloses a transformer substation risk prediction method and device, equipment and a storage medium, and belongs to the technical field of transformer substation risk prediction, and the method comprises the steps: receiving target multi-source data of a transformer substation; on the basis of the risk prediction model, the accumulated water depth, the damage degree and the outage probability of the transformer substation are predicted according to the target multi-source data; the risk prediction model is used for extracting time features and spatial position features of target multi-source data to obtain spatio-temporal features; embedding the spatio-temporal features into dynamic data to obtain spatio-temporal dynamic data; key features are screened out after the space-time dynamic data and the static data are coded and fused; extracting a semantic vector of the text data; and carrying out coding fusion on the key features and the semantic vectors to obtain fusion features, and carrying out multi-branch decoding identification on the fusion features to obtain a risk prediction result of the transformer substation. According to the method, after time and space features of multi-source data are embedded, dynamic features, static features and text features are extracted to predict risks of multiple different dimensions.

The invention discloses an air-space-ground Internet of Things performance analysis method and system based on SWIPT and NOMA, and belongs to the technical field of air-space-ground integrated Internet of Things. Comprising the following steps: constructing an air-space-ground Internet of Things system model comprising an LEO satellite, an unmanned aerial vehicle relay and a ground user, and considering heterogeneous channel characteristics and node dynamics; deducing a closed-form solution of the outage probability of the system through joint transformation of a moment generation function and a characteristic function of a random variable; a high-order Taylor expansion and moment matching method is adopted to carry out approximation on the closed-form solution, a first-order approximate solution and a second-order approximate solution are obtained, and an upper bound of an approximate error is deduced. According to the method, the problem of accurate modeling of the outage probability under heterogeneous link coupling in the air-space-ground Internet of Things is solved, theoretical preciseness and engineering practicability are both achieved, and an effective tool is provided for network reliability analysis and optimization.

The invention discloses a device-to-device covert communication system jointly assisted by an unmanned aerial vehicle (UAV) and an intelligent reflector (UIRS), and the system comprises the steps: building a D2D covert communication model jointly assisted by the UAV and the UIRS, including communication links between entities, and calculating an average minimum error detection probability and a maximum communication rate; the sender sends the hidden signals to the UIRS, the UIRS forwards the hidden signals to the receiver, and the UIRS changes the angles of the corresponding incident hidden signals and the angles of the corresponding reflected hidden signals through component elements; a frequency spectrum sharing cellular user sends a cellular signal to a base station, meanwhile, the base station sends an interference signal, an uncertain factor is introduced at a Willie receiving end of an eavesdropper, and the concealment of a UIRS combined auxiliary D2D communication link is realized; the eavesdropper Willie monitors whether the UIRS combined auxiliary D2D communication link transmits the hidden signal or not; the concealment is measured through the average minimum error detection probability; the maximum communication rate of the UIRS combined auxiliary D2D communication link is obtained under multiple constraints such as the average minimum error detection probability, the cellular communication link outage probability, the sending power and the sending power of interference signals, and the communication rate of the system is effectively improved under the combined assistance of the unmanned aerial vehicle and the intelligent reflector UIRS.

The invention provides a hidden NOMA communication method based on STAR-RIS partition cooperative interference, and the method comprises the steps: building a STAR-RIS assisted hidden communication system, and enabling the STAR-RIS to be virtually divided into an enhanced transmission region and a cooperative interference region; calculating the communication interruption probability of the hidden user, and simplifying the communication interruption probability by utilizing the probability distribution of the intermediate variable; based on a binary hypothesis testing problem, determining a receiving signal and average receiving power of a malicious monitor, determining a minimum detection error probability of the malicious monitor adopting an optimal detection strategy, and calculating a lower bound of the minimum detection error probability; determining a concealment constraint; and establishing an optimization problem according to the communication interruption probability and the concealment constraint of the concealed user, and solving the optimization problem by adopting an alternating iterative optimization algorithm to obtain the optimal values of the power distribution coefficient and the area unit number of the enhanced transmission area. According to the invention, the transmission reliability and concealment can be improved by using the information relay and interference dual functions of STAR-RIS, and the spectrum utilization rate can be improved through regional cooperation.

The invention discloses a comprehensive assessment method for weak links of a power system involving multi-dimensional indexes in extreme weather. The method comprises the following steps: firstly, establishing a multi-dimensional index system containing safety and optimized operation, wherein the system covers the line outage probability, the load loss probability, the electric energy insufficiency expectation, the line heavy load rate and the network loss rate; secondly, constructing a line fault model and a cascading fault model under extreme storm weather, describing fault probability change in combination with a Gaussian function and Weibull distribution, and simulating line segment failure by adopting Poisson distribution; a system state after a fault is calculated through a direct-current optimal power flow model, and a large amount of simulation data is obtained in combination with a non-sequential Monte Carlo method. Furthermore, a fuzzy analytic hierarchy process and a CRITIC method are adopted to calculate subjective and objective weights respectively, subjective and objective comprehensive evaluation is realized through weight fusion, and weak links of the system are identified. The method gives consideration to evaluation scientificity and calculation efficiency, and is suitable for real-time risk evaluation and weak link identification of a large-scale power system in extreme weather.

The invention provides an RIS-assisted cellular-free large-scale MIMO system performance analysis method. The RIS-assisted cellular-free large-scale MIMO system performance analysis method comprises the following steps: establishing an RIS-assisted cellular-free large-scale MIMO system model under a spatial correlation Rayleigh fading channel; performing uplink training based on the constructed cellular-free large-scale MIMO system model; performing uplink channel data transmission based on the trained uplink; designing a probability density function of an expected signal and an interference signal from other users according to the uplink channel data; according to the probability density function of the expected signal and the interference signal from other users, designing the probability density function of a single signal to interference plus noise ratio of different users; and based on a signal to interference plus noise ratio probability density function, accurately analyzing the outage probability, the coverage probability and the traversal capacity. According to the method, the accuracy of the performance index is verified through a numerical result, the potential advantage of integrating the RIS into the existing cellular-free large-scale MIMO system is shown, and theoretical support is provided for deployment of the RIS-assisted cellular-free large-scale MIMO system in a 6G scene.

A double-lane millimeter wave vehicle networking safety transmission method, system, device and medium based on STAR-RIS, the method comprising: constructing a STAR-RIS assisted double-lane millimeter wave vehicle networking communication scene; based on the propagation characteristics of millimeter wave signals, combining the channel fading characteristics under the conditions of line-of-sight and non-line-of-sight transmission and the transmission and reflection functions of STAR-RIS, calculating the channel gain of the cascaded channel of the STAR-RIS assisted link; based on the random geometry theory, respectively calculating the probability density functions of the associated distances of the direct link, the STAR-RIS reflection link and the STAR-RIS transmission link; constructing a dynamic link association strategy supporting ternary selection; establishing a signal-to-interference-and-noise ratio model under three association modes; combining the physical layer security performance index definition, calculating the closed-form analytical expressions of the connection interruption probability and the secrecy interruption probability, and verifying the security gain of STAR-RIS; the present application has the advantages of effectively overcoming the half-space coverage blind area of the traditional reflective RIS, and improving the link connection reliability and physical layer safety transmission performance under the double-lane complex shielding environment.

Techniques are described for implementing free space optical (FSO) ground-to-satellite communications. In general, an optical ground station communicates optically with a satellite via a ground-to-satellite FSO communication link. Embodiments described herein deploy at least two FSO relays at one or more aerial platform altitudes to effectively segment the ground-to-satellite FSO communication link into three or more FSO sub-links. Each FSO sub-link has better optical link performance (e.g., lower outage probability) than a single direct link. The FSO relays can include tropospheric FSO relays on low-altitude platforms and / or stratospheric FSO relays on high-altitude platforms, and architectures can use the FSO relays in a serial and / or parallel manner.

The present invention belongs to the field of intelligent transportation technology, and specifically discloses a channel resource allocation method and system based on hierarchical reinforcement learning. The present invention proposes a fairness model based on Jain's fairness index, which is used to measure the fairness of resource allocation and ensure that the resource allocation between different vehicles is relatively balanced; a reliability model is established, which measures the probability of successful transmission of information within a specified time by introducing the concept of interruption probability, thereby ensuring the communication needs of the V2V link; a delay model is designed based on the information age AOI model, which is used to evaluate the time it takes for information to be generated and received, so as to ensure timely transmission of information. The present invention also constructs a cellular vehicle network channel resource allocation model based on hierarchical reinforcement learning. Through hierarchical design, the model decomposes the cellular vehicle network channel resource allocation problem into an upper-layer clustering problem and a lower-layer intra-cluster channel resource optimization problem, thereby ensuring fair and efficient resource allocation in a complex environment.

The invention provides a performance analysis method of a multi-RIS-assisted underwater wireless optical communication system under an RIS selection scheme. The performance analysis method comprises the following steps: establishing a multi-RIS-assisted underwater wireless optical communication system model under the RIS selection scheme; the method comprises the following steps: deriving a cumulative distribution function expression of an instantaneous signal-to-noise ratio between a source node and a destination node based on a multi-RIS-assisted underwater wireless optical communication system model under an RIS selection scheme; deriving a probability density function expression of an instantaneous signal-to-noise ratio between a source node and a destination node; based on the cumulative distribution function and the probability density function expression of the instantaneous signal-to-noise ratio, deriving to obtain an analytical expression of the outage probability and the M-PAM average bit error rate, and based on the obtained analytical expression, analyzing the performance of the outage probability and the M-PAM average bit error rate of the multi-RIS-assisted underwater wireless optical communication system under the RIS selection scheme. The invention shows the potential advantage of integrating multiple RISs into an underwater wireless optical communication system.

This invention discloses a method for adjusting the active port, calculating the interruption probability, and calculating the interruption rate of shortwave communication based on a manifold antenna system in the field of wireless communication technology. The method includes: obtaining the architectural parameters of the target manifold antenna system, which include N ports uniformly distributed along a linear dimension W, each port sharing a common radio frequency link; calculating the instantaneous channel gain of each port; and selecting the port with the maximum instantaneous channel gain as the active port for shortwave communication. By introducing a manifold antenna, this invention achieves dynamic spatial adaptability within a limited area. Unlike traditional arrays with static elements, the FAS utilizes spatial diversity through real-time reconfiguration of antenna positions, eliminating the need for multiple radio frequency links. It also utilizes ionospheric reflection to establish beyond-line-of-sight connections. The FAS dynamically adjusts its active port to optimize reception from different refraction points, mitigating the inherent fading and signal attenuation of high-frequency skywave channels.

The invention discloses an uplink outage probability analysis method and system for an unmanned aerial vehicle cooperating with a wolfberry picking trolley, and the method comprises the steps: constructing a joint effect model in a non-static multi-input multi-output scene, and determining an unmanned aerial vehicle and wolfberry picking trolley uplink cooperative communication scheme for achieving the maximum channel gain; deducing to obtain an uplink outage probability closed expression containing transmitting power, interference statistical characteristics and mobility parameters by adopting an interference statistic calculation method based on Laplacian transformation; based on the obtained uplink outage probability closed expression, an improved Gaussian approximation method is adopted, and an uplink outage probability approximate expression is obtained through a dynamic truncation criterion; and based on the obtained uplink outage probability approximate expression, obtaining the total error upper bound of approximate errors by using Gaussian approximation errors and space average errors, and realizing efficient and accurate evaluation and guaranteeing the reliability of agricultural automation communication through dynamic interference modeling and improved Gaussian approximation.