6602 results about "Wireless network" patented technology

A wind energy plant with a nacelle, a rotor, which features at least one rotor blade adjustable in its blade pitch angle, a central control device for controlling the wind energy plant and a control unit disposed in the rotor for controlling the blade pitch angle of the at least one rotor blade, wherein the central control device and the control unit in the rotor can exchange data with each other via a data link, which comprises at least one first sending and receiving device at the nacelle side and at least one second sending and receiving device at the rotor side, wherein a wireless network connection with a safety-oriented communication protocol is provided between the at least one first sending and receiving device and the at least one second sending and receiving device, and that one monitoring- and communication device at a time is associated to the first and / or the second sending and receiving device, which can monitor the function of the sending and receiving device and initiate a predetermined action in the case of an error.

This disclosure provides systems and methods for provisioning resources in a wireless network. In some implementations, an apparatus obtains, from a first station (STA) on a first communication link associated with an access point (AP) multi-link device (MLD), a request for association all communication links of the AP MLD, and provisions either a single communication link or multiple communication links of the AP MLD for communications with the first STA based on at least one of a latency, a level of interference, or a traffic load associated with each of the communication links of the AP MLD. The apparatus generates a frame indicating whether the single communication link or the multiple communication links of the AP MLD are provisioned to the first STA for communications with the AP MLD, and outputs the frame for transmission to the first STA.

Systems, devices, and methods for wireless intrusion detection based on deep learning are provided. A network device collects legitimate network traffic over a time period and learns a first set of features that represents the legitimate network traffic. The network device generates synthetic network traffic based on the learned first set of features and trains a machine learning model based on the learned first set of features and the synthetic network traffic. Based on the training, the machine learning model learns a second set of features that differentiates the synthetic network traffic from the legitimate network traffic. The devices and methods precisely detect potential security threats, while reducing false positives, thereby ensuring a sensitive and accurate response to genuine anomalies. Further, the devices and methods improve accuracy of detection of potential security threats including known and new attacks in wireless networks, while adapting to evolving attack techniques and network dynamics.

The invention discloses a heterogeneous multi-agent entropy regularization resource allocation method for dynamic spectrum sharing, which belongs to the technical field of wireless network communication, and comprises the following steps: loading a basic trainer, and managing subsequent reinforcement learning; the method comprises the following steps: constructing a simulation environment, establishing a mathematical model, initializing parameter analysis, constructing a training environment and an evaluation environment, and creating an intelligent agent; generating initial empirical data by using a random strategy, filling an empirical playback buffer area, returning to a final state after a preset preheating step number is reached, and performing formal training to sample data from the empirical playback buffer area to update a network; starting a formal training process, interacting the intelligent agent with the environment, and storing empirical data to a buffer area; the strategy network is optimized through the strategy gradient, and the evaluation network is optimized through the TD error. By the adoption of the method, the problem of performance bottleneck caused by the fact that the strategy is converged to be suboptimal in spectrum allocation of a traditional DRL method is solved, and resource allocation efficiency close to global optimum is achieved through random strategy optimization.

The invention discloses a property maintenance prediction system based on big data, and the system comprises the steps: monitoring equipment and environment in real time through an intelligent sensor, transmitting the data to a cloud or local storage through a wireless network, and carrying out the historical data processing and cleaning through a distributed architecture; predicting the equipment fault risk through machine learning, establishing a customized prediction model for different equipment, analyzing the life cycle and predicting the service life of the equipment; for old equipment, constructing a life extension model by using historical fault data; the system generates intelligent decision suggestions, pushes equipment health states to property management personnel, automatically formulates maintenance plans and priorities, and dispatches maintenance personnel; during fault prediction, early warning is given out in real time, related personnel are reminded through a short message or an APP, meanwhile, maintenance operation is recorded, historical data are analyzed, and future maintenance plans and budget are optimized; the system dynamically adjusts the life prediction model of the old equipment by accumulating historical data, and ensures the accuracy and efficiency of equipment health management.

Systems, apparatuses, methods, and computer-readable media are provided for use in a wireless network for dynamic port discovery. Some embodiments are directed to an originator device that includes processor circuitry and radio front circuitry. The processor circuitry can be configured to generate a command frame for dynamic port discovery for communicating with a receiver device using a Reliable Data Service (RDS) protocol. The processor circuitry can be further configured to transmit, using the radio front end circuitry, the command frame to the receiver device and receive, using the radio front end circuitry, a response frame from the receiver device. The processor circuitry can be further configured to assign, using the received response frame, a source port number and a destination port number to an application identifier. The application identifier can be associated with an application on the originator device communicating with a corresponding application on the receiver device.

The invention relates to the technical field of water conservancy system design, in particular to a water conservancy informatization data collection and transmission system and method based on a distributed ad hoc network, and the method comprises the steps: deploying monitoring nodes at each monitoring point of a water conservancy project to collect hydrological data and environmental data; peripheral monitoring nodes are automatically found and connected through a distributed ad hoc network module, a multi-hop wireless network is formed, and communication between the monitoring nodes and gateway nodes is achieved. Specifically, a dynamic routing algorithm is adopted to monitor the delay and signal stability of a link in real time and monitor node residual energy, and an optimal transmission path is calculated; when a node or a link has a fault, a routing path is automatically recalculated according to a fault processing strategy, and disaster recovery transmission is realized; the energy consumption of the monitoring node is reduced through a sleep wake-up mode and an energy-aware routing algorithm; and converging the data of each monitoring node at the gateway node, and uploading the data to a cloud data center. And the flexibility and reliability of data transmission are enhanced.

A method, an apparatus, and a computer readable medium for storing instructions are described for a user terminal and a base station for updating an AI / ML configuration in case of a handover. The method performed by a user equipment comprising operating a first AI / ML configuration in a coverage area of a first base station; receiving an AI / ML configuration information indicating a second AI / ML configuration; operating the second AI / ML configuration indicated by the AI / ML configuration information in the coverage area of a second base station. Operating a first AI / ML configuration comprises operating a first AI / ML Model or a first AI / ML Model with a first AI / ML Model configuration in the coverage area of the first base station. The first AI / ML Model is associated with a first AI / ML Model identifier and the first AI / ML Model configuration is associated with a first AI / ML Model configuration identifier. Operating the second AI / ML configuration comprises operating a second AI / ML Model or the first AI / ML Model with a second configuration in the coverage area of the second base station. The second AI / ML Model is associated with a second AI / ML Model identifier and the second AI / ML Model configuration is associated with a second AI / ML Model configuration identifier. Indicating the second AI / ML configuration comprises indicating a second AI / ML Model identifier and / or a second AI / ML Model configuration identifier.

The invention provides a full-coverage cleaning modular control method and system for a photovoltaic cleaning robot. According to the method, a photovoltaic panel three-dimensional terrain model is constructed by collecting laser ranging, photovoltaic panel surface temperature distribution, environment airflow and position relation data; and generating an obstacle distribution map based on the model, and dynamically analyzing gap width and attachment height parameters of the cleaning area. Therefore, the bending angle and the telescopic amplitude of a connecting part of the cleaning module are adjusted in real time, and robot pose information is synchronously updated. And in combination with the position data, the obstacle map and the pose of the whole robot, an uncleaned area identifier and a dynamic coverage path are generated, and information is shared through a wireless network. The system dynamically distributes working areas and advancing directions of the multiple robots, and efficient cooperative full-coverage cleaning of the photovoltaic array is achieved. According to the technical scheme provided by the invention, through multi-source environment perception and dynamic pose adjustment, intelligent path cooperation and full-coverage operation of multiple cleaning robots are realized.

The present invention relates to the technical field of communication anti-interference, and relates to an interference confrontation method, system, device and medium for a wireless communication network, the method comprising: obtaining spectrum data, the spectrum data comprising spectrum data deployed and collected by a wireless network according to an initial deployment scheme; performing feature extraction and fusion processing on the spectrum data to generate a spectrum situation map; performing reinforcement learning decision processing according to the frequency spectrum situation map to generate a dynamic anti-interference strategy; according to transmitting node combination parameters in the dynamic anti-interference strategy, a collaborative bait node group is obtained through distributed consensus algorithm processing; sending a virtual signal to an interference source according to the dynamic anti-interference strategy and the collaborative bait node group; and calculating the strategy effect of the virtual signal by using a reinforcement learning reward function to obtain an optimized anti-interference strategy, thereby breaking through the limitation of insufficient static coping and cooperation of a traditional anti-interference method, and realizing communication reliability and anti-interference adaptability in a complex dynamic interference environment.

This disclosure describes systems, methods, and devices for quality of service (QOS)-level security configuration in a packet data unit (PDU) session. A device may identify a first user plane security indication received from an application function of a wireless network; identify a second user plane security indication received from the application function; generate, based on the first user plane security indication, a first security configuration for a first QoS flow of a PDU session; generate, based on the second user plane security indication, a second security configuration for a second QoS flow of the PDU session, the first security configuration different than the second security configuration; decode a first packet received, from the UE, in the first QoS flow using the first security configuration; and decode a second packet received, from the UE, in the second QoS flow using the second security configuration.

Embodiments described herein relate to wireless communications, including methods and apparatus for dynamically selecting subscriber identity module (SIM) profiles, electronic SIM (eSIM) profiles, multi-SIM operating modes, and / or wireless access networks for network slice based applications of wireless devices. A wireless device can include at least two SIM / eSIM profiles and switch use of SIM / eSIM profiles, change between dual SIM operating modes, and / or select a registration mode based on requirements of one or more applications in use and availability of network slices via different wireless networks.

An operation mode from a plurality of operation modes can be determined (310) based on at least one traffic type originated from a UE. The plurality of operation modes can include at least one group operation mode and an individual operation mode. The at least one group operation mode can support a plurality of UEs grouped into a group of UEs. The at least one group operation mode can support at least one network entity communicating associated messages with the group of UEs including the UE. The associated messages can be associated with the group of UEs. A network entity can be informed (320) of the determined operation mode.

The invention relates to the technical field of wireless communication and edge computing fusion, in particular to a wireless network resource allocation method based on edge intelligence, which comprises the following steps: S1, collecting a multi-dimensional parameter set of network edge nodes in real time; s2, converting node position coordinates into a network topological structure map, and mapping service type labels and bandwidth requirements into service requirement feature vectors; s3, generating a domain division matrix based on weight distribution of the network topological structure atlas; s4, outputting a resource block configuration tensor according to the time-frequency feature of the business demand feature vector; s5, generating a resource allocation mapping relation table; and S6, generating and executing a node-level resource scheduling instruction set. According to the invention, by constructing a resource scheduling mechanism fusing a topological structure and service features, precise resource allocation and dynamic load balancing of a cooperative domain level and a node level are realized, and the efficiency and the resource utilization rate of multi-task concurrent processing in an edge computing environment are improved.

Some embodiments include systems, apparatuses, methods, and computer-readable media for use in a wireless network for determining a reception (Rx) beam sweep scale factor, N, that enables a user equipment (UE) to perform Rx beam refinement. Some embodiments are directed to a 5G Node B (gNB) that includes processor circuitry and radio front end circuitry. The processor circuitry can be configured to receive, using the radio front end circuitry, a MaxNumberRxB cam capability of the UE. The processor circuitry can determine based at least on the MaxNumberRxBeam capability of the UE and / or a Channel-State Information (CSI)-reference signal (RS) set with a repetition parameter configured to be ‘ON’, the value of N. The processor circuitry can generate a message comprising the value N, and encode the message for transmission to the UE, where N Rx beam sweeps enable the UE to perform Rx beam refinement.

The disclosure relates to a 5G or 6G communication system for supporting a higher data transmission rate. Embodiments herein provide methods for handling disaster roaming service in network by UE. The method includes determining whether the UE receives a NAS message without integrity protection from a combination of first PLMN and second PLMN upon sending a registration request message to combination of first PLMN and second PLMN after expiry of a timer. In an embodiment, the method includes determining a count of attempt to combination of first PLMN and second PLMN meets a predefined threshold and determining that first PLMN is genuine network in which UE is not allowed to get disaster roaming service and blocking to retry on combination of first PLMN and second PLMN in response to receiving NAS message without integrity protection from combination of first PLMN and second PLMN upon sending a registration request message to the combination of first PLMN and second PLMN after expiry of timer.

The present invention relates to the technical field of wireless network optimization operations and maintenance, and provides a two-stage optimized wireless network optimization field long entity recognition method and system. The method comprises: using a pretrained long entity recognition model to process acquired text content to be recognized to obtain a long entity recognition result; by means of a first-stage predecessor task, acquiring a pretrained model TelBert having domain knowledge; and in a second stage, introducing semantic information related to an entity to obtain a machine reading comprehension framework-based long entity recognition model, and decoding the entity by means of a dual-pointer network. According to the present invention, knowledge in a specific field is learned by adding an entity type prediction task, the text representation learning capability of a base model is enhanced, and the difficulty of model tuning in a few-shot scenario is alleviated; the entity recognition model is improved to obtain an MRC-LER model suitable for document-level long entity recognition; and a semantic similarity-based evaluation index is proposed, and the effective extraction rate of entity key information is reasonably evaluated.

In some implementations, a device may identify a network node that supports a first radio access technology (RAT), wherein the network node is associated with sessions with user equipments (UEs). The device may calculate a percentage of traffic from the sessions that is associated with the first RAT and not a second RAT. The device may determine that the network node is associated with a score based on the percentage of traffic associated with the first RAT not satisfying a threshold. The device may collect, based on the network node being associated with the score, device data associated with the UEs. The device may determine a network issue associated with the network node based on the device data. The device may determine a root cause for the network issue. The server may transmit an indication of the root cause.

A method for MCCH acquisition in a 5G wireless network (1000) by a UE (100) includes: receiving, by the UE, a MCCH change notification from the gNodeB over a PDCCH. Further, the method includes detecting whether at least one of the UE is interested to receive a new MBS and the UE is already receiving an MBS. Further, the method includes determining the start of the new MBS session for the new MBS by reading the first bit of the MCCH change notification in response to detecting that the UE is interested to receive the new MBS, or determining the modification to the MBS session configuration of the ongoing MBS session by reading the second bit of the MCCH change notification in response to detecting that the UE is already receiving the MBS.

The invention provides a gas extraction multi-parameter monitoring method and system based on edge calculation, and relates to the technical field of coal mine gas extraction. The method comprises the following steps: arranging multi-parameter sensor nodes in drill holes, pipelines and gas gathering stations, and accessing an edge calculation unit; performing time synchronization, zero drift correction, outlier elimination and normalization on the data of the gas concentration, the negative pressure, the flow, the temperature, the humidity and the hydrogen sulfide concentration to generate feature vectors; calling a lightweight neural network model for reasoning, and outputting an extraction efficiency score and a leakage risk degree; when the risk degree exceeds the limit, an acousto-optic alarm is triggered and a speed reduction instruction is issued; when the efficiency is insufficient, the negative pressure is adjusted; compressing and encrypting the result, and reporting the result to a cloud platform through a wireless network at regular time; and the cloud performs model incremental training based on historical data and feedback, and issues an update model through hot replacement. According to the invention, local intelligent analysis, rapid early warning and dynamic adaptive optimization are realized.

The disclosure relates to a 5G or 6G communication system for supporting a higher data transmission rate. Embodiments disclose methods for managing a condition in a UE. The method includes initiating a timer for disaster wait range; in case that the UE is switched off while the timer is running, and that the UE is switched on after the UE is switched off, wherein a universal subscriber identity module (USIM) in the UE remains as same, and the UE selects a public land mobile network (PLMN) for a disaster roaming: identifying a first time remaining for the timer for timeout at switch off, identifying a second time related to a time between switching off and switching on, and determining whether to restart the timer based on the first time and the second time.

According to example embodiments, a method may include transmitting, by a user device to a network node, a first random access preamble; receiving, by the user device from the network node, a random access procedure message that includes a random access preamble reception error indication; and performing, by the user device based on the received random access procedure message, at least one of a time adjustment or a frequency adjustment to improve time and / or frequency synchronization between the user device and the network node for transmission of a second random access preamble.

The invention discloses an air federated learning realization method for collaborative optimization of client scheduling and model compression. The invention realizes the air federated learning realization method for collaborative optimization of client scheduling and model compression. Along with rapid development of federated learning in a wireless network, air computing based on a multiple-input-multiple-output technology is widely concerned due to high communication efficiency of the air computing. However, in a resource-limited large-scale device scene, channel interference, device heterogeneity and limited spectrum resources significantly restrict the convergence rate and model performance of federated learning. In order to deal with the challenges, the invention provides an air federated learning framework combining compressed sensing and client scheduling, and by collaborative design of model parameter compression, multi-antenna beam forming and dynamic equipment selection strategies, the total communication overhead of each round of training is minimized, and meanwhile, the convergence of a global model is guaranteed. In order to balance training cost and model quality, a joint optimization problem based on calculation-communication cost and model precision loss is provided. In order to solve the non-convex optimization problem, an original problem is decoupled into two sub-problems. Firstly, an optimization problem of a pre-coding and post-processing matrix is designed for a given user scheduling result to minimize a gradient aggregation error. Then, a novel user scheduling algorithm based on channels and data is provided to obtain an air aggregation result.

The invention discloses a general cargo transportation background business management system and method and electronic equipment, the system comprises a data acquisition module, an information management module, a position tracking module and a scheduling management module, and automatic acquisition of cargo position, attribute and safety inspection information is realized through an integrated sensor, an RFID tag technology and an image identification device; the GPS positioning and local wireless network complementary correction technology is utilized to break through the positioning precision limitation in the indoor and outdoor complex environment; based on a distributed database and a real-time data processing engine, high-concurrency query and dynamic information updating are supported; in combination with cargo state and position data, an optimization scheduling instruction is generated through an algorithm, empty driving waiting of loading and unloading equipment is reduced, the method covers intelligent scheduling processes of multi-source data acquisition, standardized processing, real-time tracking and cloud driving, full-life-cycle automatic management of cargos is realized, and electronic equipment realizes full-life-cycle automatic management through a software and hardware collaborative architecture. An existing port management system is compatible, and deployment cost is reduced.

The invention discloses a wireless network high-speed switching automatic test optimization method based on edge computing, and relates to the field of wireless network switching. An improved gravitational search algorithm is combined with a GIS deployment node, multi-dimensional data is collected through an intelligent heterogeneous sensor and reinforcement learning, preprocessing is carried out through a denoising auto-encoder based on a GAN, modeling is carried out through space-time diagram convolution and an LSTM mixed model, a test case is generated through reinforcement learning Monte Carlo tree search, and testing is carried out on edge nodes in a distributed mode. And an optimization strategy is formulated through multi-agent deep reinforcement learning, and strategy implementation and feedback are realized through SDN and a block chain. According to the method, multi-dimensional acquisition, intelligent modeling, automatic testing and deep reinforcement learning optimization are realized, the high-speed switching performance is improved, the time delay and failure rate are reduced, the testing efficiency is improved, resource allocation is optimized, the network security is enhanced, and stable and efficient operation of the wireless network is guaranteed in an omnibearing manner.

Seamless roaming in seamless mobile domain (SMD) of a wireless network includes receiving from an access point multi-link device (AP MLD) in the wireless network information of one or more candidate target AP MLDs to seamlessly roam to, the information including a seamless roaming domain element that identifies the seamless roaming domain of the one or more candidate target AP MLDs; selecting a target AP MLD from the one or more candidate AP MLDs based on the information; and roaming to the target AP MLD.

This disclosure above describes a method, a device, and a system for encrypting / decrypting physical channels in a wireless communication network. Among various embodiments are: pre-allocating a key, dynamically granting a key, encrypting the physical channel based on key in various levels, dividing the spectrum into two categories, or dividing a network into an initial access network and a private network. In one embodiment, a method for physical channel encryption is disclosed. Performed by a UE, the method may include obtaining a first key for decrypting a first physical channel, the first physical channel being encrypted; and decrypting the first physical channel based on the first key to obtain a signal or data transmitted by a first network element, the signal or the data being carried in the first physical channel.

The invention discloses an industrial channel test method and system based on a serial port communication protocol, relates to the field of industrial control, and aims to solve the problems that an existing channel test system is single in connection mode, complex in deployment and low in efficiency due to dependence on manpower. According to the invention, the deployment process is simplified by supporting dual-protocol adaptive switching between an RTU mode (direct connection through a 485-to-USB converter) and a TCP / IP mode (wired / wireless network access); driving test logic by using a spreadsheet, pre-defining a Modbus address, a measuring range and a precision threshold value, automatically generating an instruction and acquiring data; and the integrated voice broadcast module feeds back a test result in real time, and prompts an abnormal channel and a processing suggestion when the precision exceeds the limit, so that single-person closed-loop operation is realized. The test result is automatically recorded to the spreadsheet, a structured report is generated, historical tracing and cross-platform data integration are supported, the test efficiency and reliability are remarkably improved, and the method is suitable for high-frequency channel verification of the industrial control system.