333 results about "Self-organizing network" patented technology

The invention discloses an emergency communication and positioning system and method based on a Beidou satellite. The method comprises the following steps: S1, collecting data in real time; s2, analyzing the emergency state of the user by using a context awareness algorithm; s3, under the condition that the satellite communication signal is stable, transmitting the emergency information to a rescue center according to the calculated priority, if the satellite signal is unstable or interrupted, constructing a self-organizing network, and continuing to transmit the emergency information; s4, dynamically selecting an optimal path based on an adaptive path optimization algorithm inspired by an immune system, and further optimizing path selection through a space-time perception algorithm; s5, according to a priority management mechanism, the emergency information with high priority is processed preferentially, and feedback information is sent; s6, if the first emergency information transmission fails, the system starts a redundant data transmission mechanism; and S7, continuously tracking the state change of the user, and dynamically adjusting the rescue scheme. According to the invention, the situation awareness and immune system optimization algorithm is combined to realize efficient transmission and feedback of emergency information.

The invention provides an unmanned aerial vehicle detection tracking method and system based on combination of a laser radar and vision, and the method comprises the steps: obtaining timestamp information through employing a distributed calculation framework, generating a multi-source data set according to the timestamp information, carrying out the data fusion based on the multi-source data set through employing a deep reinforcement learning algorithm, and obtaining multi-source heterogeneous data, the method comprises the steps of obtaining an unmanned aerial vehicle behavior mode and a predicted motion trail by using multi-source heterogeneous data, performing analysis through an intelligent task allocation protocol under a self-organizing network according to the unmanned aerial vehicle behavior mode and the predicted motion trail, generating an optimal sensing resource allocation scheme, and performing resource allocation on the basis of the optimal sensing resource allocation scheme. Processing the intelligent visual sensing node to obtain an emergency correction program, and according to the emergency correction program, integrating edge computing power to generate an unmanned aerial vehicle detection and tracking instruction; according to the technical scheme provided by the invention, the quality and accuracy of data fusion are improved, and the perception capability is enhanced.

The invention relates to the field of wireless communication and intelligent networks, in particular to a software defined radio-based ad hoc network dynamic slicing architecture and a management and control method, comprising a basic communication layer, an intelligent control layer and a service execution layer. The basic communication layer adopts a multi-distribution multi-center clustering architecture; the intelligent control layer is responsible for intelligent management and resource scheduling of the self-organizing network, and the intelligent control layer comprises a plurality of command and control nodes; and the service execution layer adopts a micro-service-based architecture, and encapsulates different network functions and service logics into independent micro-service modules. According to the method, the technical problems of high plane coupling, resource scheduling rigidness, insufficient survivability and high hardware dependency in the prior art are solved.

The invention discloses a sensing node communication system and method with a self-healing mechanism. The sensing node communication system comprises a node detection module, a node communication module, a preprocessing module, a mixed training module and a self-healing control module. The system realizes periodic acquisition of multi-dimensional environmental parameters by configuring a plurality of sensing nodes, shares state information based on a self-organizing network, and constructs a local network health state map. The preprocessed data is used for training a hybrid neural network, and long-term dependency features and local abnormal fluctuation features of node states are extracted from the data to assess fault risks. When the risk score exceeds a threshold value, the system automatically executes self-healing operations such as dynamic route reconstruction and standby link activation. According to the invention, the stability and the adaptive capability of the underwater sensor network are improved, and the method has wide application value.

A personal tactical system including a load-bearing garment, a pouch with one or more batteries enclosed in the pouch, at least one power distribution and data hub, and at least one camera. The camera is incorporated into or removably attachable to the load-bearing garment, the pouch is removably attachable to the load-bearing garment and the one or more batteries are operable to supply power to the at least one power distribution and data hub. The at least one power distribution and data hub is operable to supply power to at least one peripheral device. A plurality of personal tactical systems is operable to form an ad hoc network to share images and other information for determining object direction, location, and movement.

The invention provides a cooperative reconnaissance and electronic countermeasure control system and method based on multiple unmanned aerial vehicles. The cooperative reconnaissance and electronic countermeasure control system comprises five modules: a communication module, a task decomposition module, a reinforcement learning decision module, a cooperative optimization module and a task evaluation module. The communication module ensures data synchronization and safe communication between the unmanned aerial vehicles through a self-organizing network and an encryption anti-interference technology. And the task decomposition module is used for refining the electronic confrontation task into reconnaissance and interference subtasks according to the task type, and adjusting the priority in real time according to the battlefield environment. The reinforcement learning decision module adopts a DQN and PPO deep reinforcement learning algorithm to optimize a reconnaissance and interference strategy, and ensures optimal task execution. And the collaborative optimization module coordinates task allocation and flight paths of the unmanned aerial vehicle through multi-agent reinforcement learning and a bee colony algorithm, and solves the problem of task conflict. And the task evaluation module monitors a task state in real time and feeds back an adjustment strategy. According to the method, battlefield changes can be flexibly coped with, resource scheduling is optimized, task execution efficiency is improved, anti-interference capability is enhanced, and stability and safety of tasks are guaranteed.

The invention provides a virtual power plant dynamic response scheduling method and system based on a cognitive spectrum network, which can improve the reliability, self-adaptive capability calculation efficiency and risk management and control capability of a virtual power plant communication system, and relates to the technical field of virtual power plants, the method comprises the following steps: establishing a cognitive spectrum self-organizing network; collecting current operation state data of each power resource under the virtual power plant and historical operation state data under different working conditions; obtaining a resource response characteristic of each power resource; outputting a preliminary optimization result; converting the preliminary optimization result into a credible optimization result; generating a system risk partition topology report; a market risk hedging strategy capable of being automatically executed is generated; and generating a final scheduling instruction containing the power set value, the execution time, the hedging operation and the risk constraint condition of each resource. According to the method, a feasible technical path is provided for large-scale efficient utilization of distributed resources under the background of the energy internet.

The invention discloses a topographic surveying and mapping method and system based on unmanned aerial vehicle cluster collaboration, and belongs to the technical field of unmanned aerial vehicle cluster collaboration topographic surveying and mapping, and the method comprises the following steps: a ground control center plans a flight route for each unmanned aerial vehicle in a cluster according to the topography and precision requirements of a surveying and mapping area, a theoretical processing sequence of data of each unmanned aerial vehicle is calculated in advance; and the unmanned aerial vehicle cluster autonomously takes off to a predetermined airspace according to the instruction, and dynamically establishes a multi-hop relay communication network based on a mobile ad hoc network technology in a flight surveying and mapping process so as to evaluate and use the fastest signal transmission path. Through the combination of the steps, the data processing and transmission efficiency is improved, reliable communication and collision prevention are guaranteed, weather interference can be dealt with, and efficient and accurate topographic surveying and mapping are achieved.

A personal tactical system including a load-bearing garment, a pouch with one or more batteries enclosed in the pouch, at least one power distribution and data hub, and at least one camera. The camera is incorporated into or removably attachable to the load-bearing garment, the pouch is removably attachable to the load-bearing garment and the one or more batteries are operable to supply power to the at least one power distribution and data hub. The at least one power distribution and data hub is operable to supply power to at least one peripheral device. A plurality of personal tactical systems is operable to form an ad hoc network to share images and other information for determining object direction, location, and movement.

State of the art systems used for industrial plant monitoring have the disadvantage that they fail to correctly assess reason for dip in performance of the plant and in turn trigger appropriate corrective measures. The disclosure herein generally relates to industrial plant monitoring, and, more particularly, to a system and method for development and deployment of self-organizing cyber-physical systems for manufacturing industries. The system monitors and collects data with respect to various parameters, from the industrial plant. If any performance dip is detected, the system determines corresponding cause, and also triggers one or more corrective actions to improve performance of the plant and different plant components to a desired performance level.

The embodiment of the invention provides an industrial automation system. The industrial automation system comprises an edge layer and an equipment layer, wherein the equipment layer comprises one or more pieces of industrial equipment deployed on a production line system, and sensors and actuators deployed on the one or more pieces of industrial equipment, the sensors are used for collecting monitoring data of the industrial equipment, and the actuators are used for executing control actions of the industrial equipment; the edge layer comprises a plurality of edge control units, and the edge control units acquire monitoring data of the one or more industrial devices and adjust actuators of the one or more industrial devices according to the monitoring data to execute control actions; wherein the plurality of edge control units are in communication connection through a self-organizing network or a point-to-point network.

The invention provides a breast milk feeding amount intelligent calculation and dynamic adjustment method and system, and relates to the technical field of intelligent feeding, and the method comprises the steps: collecting real-time physiological parameters of an infant, constructing an infant digital model through a multi-scale morphological neural network, calculating a basic energy consumption value through combining with a biological rhythm prediction model, and calculating the feeding amount of the infant. The standard breast milk feeding amount is calculated through the self-adaptive fuzzy neural network; the method comprises the following steps: collecting mother physiological state data and breast milk component data, calculating a breast milk nutrition density coefficient by using a deep mixing cognitive network and an immune evolution self-organizing network, correcting a breast milk reference feeding amount, and finally calculating an actual breast milk feeding amount through a self-adaptive resonance theory network; growth and development data of an infant after breast milk intake are collected, a multi-layer spiral pulse neural network is used for extracting development feature vectors, a development deviation value is calculated based on a fractal dynamics model, network parameters are dynamically adjusted through a biological group intelligent optimization system, and dynamic optimization of breast milk feeding amount is achieved.

The invention relates to the technical field of Internet of Vehicles, and discloses an Internet of Vehicles device scheduling method based on a LoRa ad hoc network and a Prophet algorithm, comprising the following steps: deploying LoRa nodes to form an ad hoc network, adopting a star-shaped or mesh topology structure, and setting transmission rate, signal bandwidth and spreading factor parameters; information such as the position, the speed and the direction of a vehicle is obtained through GPS or V2X communication, and interference, noise level and signal strength of a LoRa channel are monitored in real time for dynamically adjusting transmission parameters; designing an adaptation and scheduling strategy based on a Prophet algorithm; and dynamically updating the encounter frequency and the encounter duration, and selecting an optimal forwarding node in combination with the probability of Prophet and the transmission parameter of LoRa. According to the method, the interference, the noise level and the signal strength of the LoRa channel are monitored in real time, and the spreading factor (SF), the bandwidth and the power are dynamically adjusted, for example, the SF12 and 125kHz bandwidths are adopted during long-distance transmission, and the SF7 and 500kHz bandwidths are switched to a high-speed scene, so that the transmission efficiency is improved by more than 20%.

The invention relates to the technical field of earthquake monitoring and early warning, in particular to an earthquake early warning analysis system and method based on intelligent equipment. The system comprises a terminal sensing and initial judgment module which collects data through a sensor array, identifies P-wave features by using a dynamic weight adjustment model and generates an encrypted initial alarm; the adaptive network transmission module is used for establishing a dynamic self-organizing network based on a D2D protocol and realizing multi-hop relay transmission of alarms by electing relay nodes; the edge aggregation and verification module is used for executing space-time matching and cross verification on a plurality of alarms in a specific area, judging the authenticity of an event and generating graded early warning information; and the cloud control fusion and actuarial module is used for fusing the regional event data and the professional network data, executing high-precision positioning and earthquake magnitude calculation, and issuing a final early warning instruction. According to the invention, a high-density sensing network is constructed by using massive intelligent devices, the early warning blind area is effectively eliminated, and faster, more accurate and more robust earthquake early warning is realized.

The invention discloses a low-altitude unmanned aerial vehicle cluster communication method based on a self-organizing network, and the method comprises the steps: obtaining neighbor information through broadcasting the ID, the current state and the flight intention of an unmanned aerial vehicle node, carrying out the prospective evaluation of the future topology stability and centrality of each node, intelligently electing a cluster head, dynamically forming and maintaining a cluster, and then, carrying out the cluster communication through the self-organizing network. And generating a layered intra-cluster routing table and an inter-cluster forwarding rule by using a cluster structure, and finally realizing efficient layered forwarding of the data packet. In this way, the routing storm problem in large-scale unmanned aerial vehicle cluster communication is solved, and the expansibility and robustness of the network are remarkably improved.

The invention relates to a multi-network convergence gateway system supporting a satellite, a cellular and a wide-narrow band ad hoc network, and the system comprises a satellite communication module which is used for carrying out the communication connection with a satellite, and receiving and transmitting a satellite signal; the cellular communication module is used for communicating with a cellular network base station; the wide-narrow band ad hoc network module is used for constructing an ad hoc network in a local area to realize communication between nodes; the data processing module is used for uniformly processing data from the satellite communication module, the cellular communication module and the wide-narrow band ad hoc network module; and the power management module is used for managing and controlling a power supply of the whole system. The method has the beneficial effects that fusion of various communication networks can be realized, communication requirements in different scenes are met, and the power consumption of the system is reduced.

A method performed by a communication device (12) is disclosed. The communication device (12) stores, at the communication device (12), a self-organizing network, SON, report (16) associated with a non-public network, NPN, including storing the SON report (16) in association with an NPN identifier of the NPN with which the SON report (16) is associated. The communication device (12) also transmits a message to the serving network indicating that the SON report (16) is available at the communication device (12), if a serving network of the communication device (12) is an NPN identified by an NPN identifier which matches the NPN identifier associated with the SON report (16).

The invention provides a 5G self-organizing network coarse synchronization segmentation design method based on a domestic chip, and relates to the technical field of mobile communication, and the method comprises the following steps: S1, according to a sampling rate issued by OAM, capturing an air interface signal according to an NRSSB common period; s2, according to the central frequency point of the receiving end bandwidth, calculating a frequency point difference and carrying out zero frequency shift; s3, segmenting the signal after zero-frequency shift, combining the segmented signal into a window, and carrying out down-sampling processing on the signal; s4, performing AGC gain processing on the signal; s5, performing intra-window judgment on the signals; s6, after the in-window judgment of all the in-window signals is completed, inter-window judgment is carried out; and S7, setting an overtime threshold, and dynamically adjusting the window length. The method has the beneficial effects that the calculation complexity is reduced, calculation resources are efficiently utilized, the calculation efficiency is improved, and the accuracy and reliability of signal detection are high.

The invention relates to the technical field of collaborative response management, and provides a business system collaborative response method and platform driven by a video AI analysis result, and the method comprises the steps: receiving a frame sequence generated by aligning a multi-source heterogeneous video stream, carrying out the parallelization AI reasoning to extract multi-dimensional features into an event feature set, carrying out the association mapping with a business strategy library to generate a collaborative instruction packet, and carrying out the collaborative response of the business system. The information is distributed to an unmanned aerial vehicle cluster through a distributed message bus and the like according to a route, and a terminal linkage response is triggered. The technical problem that communication among unmanned aerial vehicle clusters is unstable due to the fact that a communication network is prone to being interfered or interrupted in complex environments such as a disaster site is solved, events in a video are analyzed and processed, the cooperative instruction packet is generated and distributed to the target unmanned aerial vehicle cluster, the unmanned aerial vehicle clusters can efficiently execute tasks, and the efficiency of the unmanned aerial vehicle clusters is improved. And a self-organizing network protocol is deployed to carry out distributed collaborative decision making, so that the communication stability of the unmanned aerial vehicle cluster is improved.

The invention relates to the technical field of wireless communication, in particular to a Bluetooth mesh-based riding helmet earphone multi-terminal talkback synchronization method and system, and the method comprises the steps: constructing a self-organizing network through a plurality of terminal nodes, carrying out the error detection of the self-organizing network, obtaining an error value, carrying out the time compensation of the terminal nodes, and obtaining a calibration terminal node, carrying out voice activity monitoring on the plurality of calibration terminal nodes to obtain a plurality of marked terminal nodes, carrying out time slot allocation on the plurality of ordered voice requests to obtain a plurality of voice frames with timestamps, carrying out multi-hop forwarding on the plurality of voice frames with timestamps to obtain a plurality of verification voice frames, carrying out timestamp sorting to obtain a plurality of sorted voice frames, and sending the sorted voice frames to a server; and performing synchronous error correction to obtain a plurality of synchronous voice frames, decoding and playing the plurality of synchronous voice frames to obtain a synchronous voice stream, and realizing multi-terminal synchronous talkback. According to the invention, the problems of difficult network establishment, asynchronous voice and speaking right conflict in the application of the riding helmet Bluetooth earphone can be solved.

The invention provides a distributed anti-unmanned aerial vehicle collaborative decision-making system and method. The distributed anti-unmanned aerial vehicle collaborative decision-making system comprises at least one heterogeneous anti-unmanned aerial vehicle module, a self-organizing network module and a distributed collaborative decision-making module, the self-organizing network module is used for constructing a decentralized network topology structure and supporting communication connection among the functional modules; the heterogeneous anti-unmanned aerial vehicle module is used for detecting, tracking and acquiring related information of an unmanned aerial vehicle target, and sharing the related information to the distributed collaborative decision-making module in real time through the self-organizing network module; the target countering module receives a target countering instruction from the distributed collaborative decision-making module and counters the unmanned aerial vehicle target; and the distributed collaborative decision module is used for receiving the real-time shared data from the self-organizing network module, analyzing the real-time shared data based on a swarm intelligence algorithm, generating a target countering instruction for each heterogeneous anti-unmanned aerial vehicle module, and sending the target countering instruction to the corresponding heterogeneous anti-unmanned aerial vehicle module. Therefore, countering resource collaboration and optimization of multiple unmanned aerial vehicle targets in a complex airspace environment are realized.

The invention discloses a three-phase imbalance phase-change switch switching control system based on a graph neural network, and relates to the technical field of phase-change switch control. In order to solve the problems that in the prior art, deep analysis of load dynamic association and time sequence laws is lacked, so that a control strategy lags behind, switching actions are frequent, the treatment effect is limited, instruction time delay is large, the packet loss rate is high, and accurate synchronization of a commutation moment is difficult to guarantee. According to the method, the accuracy and efficiency of load characteristic analysis are greatly improved by constructing the load association graph structure and identifying the dynamic association mode, the graph neural network is utilized to extract the space-time sequence characteristics of the power grid topology and the load change, and the multi-dimensional and refined optimization of the commutation strategy is realized in combination with the multi-target optimization model, so that the method is suitable for large-scale popularization and application. The Mesh self-organizing network based on the power TD-LTE private network ensures that the instruction can be synchronized in millisecond and accurately sent to the phase-change switch, and provides a solid communication guarantee for effective execution of the strategy.

Reporting of events in non-terrestrial network, NTN, coverage. An example method, in a wireless device operating in a wireless communication network, comprises detecting (310) one of one or more pre-determined triggering events and, responsive to the detected triggering event, determining (320) whether the triggering event occurred while the wireless device was operating under non-terrestrial network coverage or under terrestrial network coverage, and / or determining whether the triggering event was due to wireless device mobility or non-terrestrial network cell mobility. The method further comprises saving (330), for reporting to the wireless communication network, information corresponding to this determining.

A method of a hyperparameter server improves hyper-parameter search efficiency for devices in a self-organizing network (SON) includes sending configuration for data feature collection to at least one edge device in the self-organizing network, receiving hyper-parameter performance data from the at least one edge device, and training a shared hyperparameter machine learning model using a global training database including the hyperparameter performance data to identify optimal hyperparameters for use by the at least one edge device. A further method of an edge device improves hyperparameter search efficiency for devices in a SON includes receiving configuration for data feature collection from a hyperparameter server, training an edge machine learning model using local training data and selected hyperparameters, and sending performance data to the hyperparameter server obtained from the training of the edge machine learning model.

A multi-room audio synchronous playback method, a system, a device and a storage medium are provided. The multi-room audio synchronous playback method includes: creating an ad-hoc network using a plurality of audio devices supporting a target wireless communication protocol via point-to-point connection, the ad-hoc network covering a plurality of rooms, the target wireless communication protocol operating at a frequency band of 5 GHz to 7 GHz; dynamically analyzing link quality to select an optimum transmission path, and dynamically optimizing a network topology of the ad-hoc network via multi-hop relay; transmitting target audio data between the audio devices of the ad-hoc network based on the optimum transmission path, and performing real-time interaction and dynamic compensation based on a synchronization signal to obtain a synchronization parameter; and controlling each audio device of the ad-hoc network based on the synchronization parameter to synchronously play the target audio data.

Embodiments of the disclosed technology are directed to spatially multiplexing different digital data streams which are generated within a distributed network (e.g., MANET, cellular, or Wi-Fi) and are simultaneously transmitted towards a destination radio with multiple antenna elements. An example method for collaborative communication includes clustering the plurality of nodes into a plurality of clusters such that each of the plurality of clusters communicates with a distinct antenna of the plurality of antennas, and performing distributed beamforming in each of the plurality of clusters to transmit a corresponding message of multiple messages directed to the distinct antenna. The described embodiments enable improved performance over existing systems, e.g., increased outage capacity with increasing cluster size.

The invention belongs to the technical field of ad hoc networks of Internet of Vehicles, and particularly relates to a vehicle ad hoc network local exploration routing method for event information transmission, which comprises the following steps: firstly, a vehicle periodically exchanges state information and monitors an event, and performs priority identification on event information based on a security level; positioning a nearest vehicle as an information source vehicle and creating an initial routing table; secondly, combining the Manhattan distance between vehicles, the link life, the transmission period and the distance limit to calculate heuristic cost and actual movement cost to construct a routing cost function, dynamically selecting relay nodes through a local exploration strategy, and updating the initial routing table into a relay routing table; and finally, updating the heuristic cost by taking a time slot as a unit to realize predictive maintenance optimization of the optimal routing table. Simulation shows that in a high-density scene, compared with a traditional Mozo method, the routing overhead of the method is reduced by 30.77%, and the long-distance transmission routing operation time is shortened by 24.55%.

The invention relates to the technical field of wireless communication, and particularly discloses a flight ad hoc network link evaluation method, which comprises the following steps: constructing an antenna model, a transmitter model, a receiver model and an interference model; determining a topological structure according to the real poses and the deviation poses of any two communication nodes in the flight ad hoc network; corresponding antennas are determined according to the real poses and the deviation poses of any two communication nodes in the topological structure, and antenna gains are obtained according to the antennas and antenna directional diagrams in the antenna model; respectively confirming link loss, receiving signal power and interference power according to the transmitter model, the receiver model and the interference model, and calculating a signal-to-noise ratio according to the link loss, the receiving signal power and the interference power; and determining a bit error rate according to the signal-to-noise ratio and the state of the flight ad hoc network, so as to evaluate the flight ad hoc network according to the signal-to-noise ratio and the bit error rate. The method can be used for analyzing the influence of the navigation deviation on the link performance and helping to optimize a flight ad hoc network protocol.

The invention discloses an unmanned aerial vehicle group positioning method based on inertial navigation and group sensing distance measurement fusion. The method comprises the following steps: acquiring SINS data obtained by strapdown inertial navigation equipment carried by unmanned aerial vehicles and distance measurement data between anchor nodes and each unmanned aerial vehicle and between the unmanned aerial vehicles obtained through self-organizing network communication; the air-ground module establishes an error model to obtain a distance measurement correction value, the distance between the anchor node and each unmanned aerial vehicle is corrected based on the distance measurement correction value, and the corrected distance between the anchor node and each unmanned aerial vehicle and SINS data are subjected to Kalman filtering to obtain a combined navigation positioning result; the aerial group module performs data conversion on the ranging data between the unmanned aerial vehicles to obtain the distance between every two unmanned aerial vehicles at the same moment; and performing nonlinear optimization on the combined navigation positioning result and the distance between every two unmanned aerial vehicles at the same moment by using a least square method to obtain an unmanned aerial vehicle group positioning result. According to the invention, the robustness and accuracy of positioning are further improved.

The present disclosure relates wireless communication, more particularly to systems and methods for enabling self-organizing networks in an Open Radio Access Network (O-RAN). A system via Near-RT RIC assigns at least one of one or more time-sensitive SON functional elements and one or more time-sensitive RRM functional elements in at least one of the Near-RT RIC and the EMS entity associated with the SMO module. The system via a Near-RT RIC may assign at least one of one or more time-sensitive SON functional elements and one or more time-sensitive RRM functional elements in at least one of the Near-RT RIC and the EMS entity associated with the SMO module. The Near-RT RIC may access via at least one of the xAPPs associated with the O-RAN and the EMN entity or the NMS entity, one or more Performance Monitoring (PM) counters, by requesting respective E2 Nodes via the E2 interface or via the O1 interface, respectively.