7730 results about "Wireless network" patented technology

An electronic device according to various embodiments comprises: a memory including instructions; and a processor that is electrically connected to the memory and executes the instructions. When the instructions are executed by the processor, the processor may: acquire a first traffic feature vector and a second traffic feature vector on the basis of traffic data generated in a wireless network device during a plurality of time intervals; generate a combined feature vector by combining the first traffic feature vector and the second traffic feature vector; and acquire predicted traffic data, to be generated in the wireless network device, on the basis of the combined feature vector. Various other embodiments are possible.

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.

An improved system and method of defining speeding severity levels, receiving over a wireless network from a vehicle device speed data and metadata, determining associated speeding severity levels, based at least in part on the determined associated speeding severity levels, determining whether an alert communication is to be transmitted the vehicle device, and in response to determining that an alert communication is to be transmitted the vehicle device, transmitting the alert communication via a wireless interface to the vehicle device, the alert communication configured to cause the vehicle device to provide a corresponding in-vehicle alert.

Enhanced ranging and positioning services in wireless networks The invention relates to a wireless system and methods for configuring ranging capable devices to form a ranging constellation to support ranging-based positioning services. Multiple challenges in improving location accuracy when using ranging measurements to derive the location coordinates are addressed. In particular, timing at which the location information can be derived from ranging measurements and methods used for ranging-based location estimation are described.

The invention relates to a wireless system and methods for managing and / or configuring ranging capable devices to form a ranging constellation to support ranging-based positioning services. Multiple challenges in improving configuration and management of the ranging constellation are described.

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.

Wireless networks with plural nodes having a respective transceiver and a processor configured to, and methods to, obtain current state data, calculate a reward, store such state data and rewards in a collected parameters database, provide such current state data and data from such collected parameters database to a reinforced neural network, select an action using the reinforced neural network, and output the action to the respective transceiver so as to selective modify its transmit power level.

Disclosed are systems, apparatuses, methods, and computer-readable media for use in a wireless network for facilitating radio access synchronization. The method includes receiving, from a user equipment (UE) a message having a media access control (MAC) control element (CE) format and comprising a MAC protocol data unit (PDU) structure, the message being formed by multiplexing one or more MAC service data units (SDUs). The method further includes generating a response message to the received message by multiplexing a MAC random access response (RAR) with one or more MAC SDUs. The method then transmits the response message to the UE.

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.

Techniques are provided for enabling on-demand positioning reference signals (PRS) with a user equipment (UE). An example method for determining a location of a mobile device includes sending a request for downlink positioning reference signals to a network server, where the request includes positioning reference signal configuration information, receiving assistance data based on the positioning reference signal configuration information, measuring one or more downlink positioning reference signals based at least in part on the positioning reference signal configuration information, and determining a location of the mobile device based at least on part on the measurements obtained from the one or more downlink positioning reference signals and the assistance data.

The invention discloses an optimization method for spatial distribution of garden plants, which comprises the following steps: generating a high-precision 3D model of a garden terrain by adopting a plant spatial adaptive layout algorithm and utilizing a laser radar or unmanned aerial vehicle technology, generating a weight matrix according to soil types, illumination intensity and drainage characteristics, and applying a dynamic weight Voronoi algorithm in the terrain model to optimize the spatial distribution of the garden plants. The method comprises the following steps: generating a planting range of each plant, establishing a root distribution model by using an underground imaging technology, simulating distribution dynamic of moisture and nutrients among root systems in combination with underground hydrological data, collecting sensor data in real time by using a wireless network, designing a dynamic irrigation scheme, and optimizing the planting density and irrigation range of the plants. Data such as terrain and climate are integrated into a virtual garden, the virtual garden is ensured to be consistent with an actual state through interaction of a sensor and a digital twinborn model, plant growth, ecological benefit changes and disaster risks are predicted by using the digital model, and a user is allowed to modify and optimize the garden layout in real time through a visual interface.

The invention discloses an oil field power distribution network operation safety violation behavior deep learning recognition system. The system comprises a video acquisition module, a data preprocessing module, an improved YOLO model module, a violation behavior judgment module and a result output module. The video acquisition equipment is distributed in a key area of an oil field site and transmits video data to the server through a wireless network; the data preprocessing module adopts histogram equalization and sharpening operation to enhance the image contrast. The improved YOLO algorithm model is subjected to customized training, and behavior actions of operators and equipment can be accurately recognized. And the illegal behavior judgment module performs matching judgment on the result output by the model in combination with the safety specification of the oil field operation. According to the method, the difficult case mining technology and the multi-stage training strategy are adopted, the judgment capability of the model on illegal behaviors under complex conditions is improved, the OpenCV technology is combined, the capability of the system for coping with light changes and severe weather conditions is enhanced, and the recognition accuracy under different illumination intensities is ensured.

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 discloses a wireless network high-reliability transmission method based on double-link redundancy, which relates to the technical field of wireless communication, and comprises the following steps: establishing double communication links, and collecting link quality data of the double communication links; performing weighting operation on the link quality data according to a preset weighting coefficient to obtain a first link score and a second link score, and judging the first link score and the second link score; issuing an original data packet and a backup data packet of the original data packet to the dual communication link according to a judgment result, and collecting a data transmission state in a receiving time window; and when it is monitored that the original data packet is lost in the receiving time window, extracting a backup data packet of the original data packet for data recovery, and recalculating the link score of the original data packet. Through organic combination of multi-dimensional link quality evaluation, link selection of weighted calculation, double-link parallel transmission and rapid data recovery, the network resource utilization efficiency is improved while the data transmission reliability is guaranteed.

The invention relates to the technical field of wireless communication network optimization, in particular to a wireless network neighbor cell interference optimization method and system based on self-supervised learning. Federal learning and global model updating; performing deep reinforcement learning spectrum allocation decision; advanced wireless communication technology application; the block chain guarantees execution of the smart contract; closed-loop feedback optimization driven by user experience; the method has the beneficial effects that the interference mode between the cells is automatically identified and predicted through the self-supervised learning model, and the spectrum allocation strategy is dynamically optimized in combination with deep reinforcement learning, so that the signal interference between the cells is effectively reduced, and the overall stability of the network is improved. Especially in a high-density user scene, the system can respond to interference changes in real time, and the problem of performance reduction caused by adjacent cell interference is reduced.

Calibration of ranging constellations in wireless networks The invention relates to a wireless system and methods for managing and / or configuring ranging capable devices to form a ranging constellation to support ranging-based positioning services. Multiple challenges in determining a need for calibration in ranging services to improve accuracy and / or reduce power consumption are addressed.

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 discloses an energy storage method and system for base station management, and the method comprises the steps: carrying out the multi-modal data fusion processing according to the historical business volume data, real-time user movement mode data and meteorological data of each virtual base station in a target region, and obtaining a dynamic load prediction result of each virtual base station in a target time period; based on a dynamic load prediction result, adopting a distributed constraint optimization algorithm to dynamically allocate energy storage resources, and generating an optimal allocation strategy containing a cross-base-station energy scheduling path; and according to the wireless network topology structure characteristics of the target area, constructing an energy scheduling decision model based on a graph theory, optimizing an energy storage scheduling time sequence, and generating a dynamic energy storage scheduling scheme with a fault-tolerant mechanism so as to realize energy storage for base station management. By utilizing the embodiment of the invention, the energy efficiency of the base station can be improved, energy waste is reduced, and efficient configuration and real-time scheduling of energy storage resources are realized.

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.

Aspects of the present disclosure provide methods and apparatuses for protecting a reference signal (RS) and / or adjusting timing advance (TA) values to be used for timing synchronization between an apparatus (e.g. user equipment (UE))) and a device (e.g. transmit-and-receive point (TRP)) in a wireless network. The device operates in full-duplex (FD) mode and the apparatus operates in half-duplex (HD) or FD mode. In some embodiments, RSs transmitted in uplink and downlink directions are protected by puncturing one or more portions of time-frequency resources so that interference from other signals can be avoided or mitigated. The punctured portion of the time-frequency resources may be one or more symbols that together overlaps with a symbol at which the RS is to be received or sent. The device may send information indicating the portion to puncture using a higher-layer signaling, a dynamic signaling, or a preconfiguration by the network.

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.