3467 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.

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 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.

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.

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.

The present application relates to devices and components including apparatus, systems, and methods for congestion signaling in wireless networks.

This application relates to wireless communications, including methods and apparatus to monitor radio link conditions of a cellular wireless network adaptively using a low-power wake-up signal (LP-WUS) burst received by a low-power wake-up radio (LP-WUR) of a wireless device when possible and switching to using legacy reference signals received by a main radio only when required. The LP-WUS burst is processed by the LP-WUR to determine a block error rate (BLER) value and / or a signal-to-noise-plus-interference ratio (SINR) value to determine whether the wireless device is in an out-of-sync (OOS) condition. The main radio can be awakened, including when directed to sleep by the cellular wireless network, to perform radio link monitoring when the OOS condition is determined.

A system for micro-segmented networking is provided. A system controller is programmed to a) store a plurality of micro-segmented network accounts and a plurality of subscriber accounts, b) receive a request from a user device to activate a first micro-segmented network associated with a first subscriber account, c) authenticate the first subscriber account based on the subscriber information, d) activate the first micro-segmented network, including a plurality of device slots for a plurality of devices, e) transmit, to the user device, first device slot authentication information for a first device slot of the plurality of device slots; f) receive, from a first device connecting to the wireless network, the first device slot authentication information; g) authenticate the first device slot authentication information; and h) in response to authenticating the first device slot authentication information, connect the first device to the first micro-segmented network.

The invention relates to the technical field of network communication, in particular to a 5G-A network slice dynamic adjustment and resource allocation system oriented to low-altitude economy. The system comprises a mobility management feature integration module, a network slice service level protocol evaluation module, a mobility management demand prediction benchmark construction module, a multi-dimensional trend prediction module, a joint optimization decision generation module and a strategy verification and execution module, and is used for acquiring a mobility management feature data set of a wireless network; performing network slice service level protocol evaluation on the wireless network to obtain a network slice state evaluation result; constructing a mobility management demand prediction benchmark; performing multi-dimensional trend analysis on the network slice state evaluation result to obtain a prediction result; performing joint optimization decision on the standard network slice configuration strategy to obtain a network slice adjustment strategy; and executing the verified slice adjustment strategy to realize dynamic adjustment and resource allocation of the network slice. According to the invention, the efficiency of network slice dynamic adjustment and resource allocation can be improved.

The invention discloses a ground resistance remote online monitoring method and system based on a mobile terminal, and relates to the technical field of ground resistance monitoring, and the method comprises the steps: obtaining a natural electromagnetic noise signal collected by the mobile terminal through a built-in sensor, and calculating a preliminary estimation value of ground resistance according to a preset model; according to the preliminary estimation value and the environmental parameters, using a machine learning algorithm to predict the optimal sampling frequency and time window under the current monitoring condition, and forming a dynamic adjustment mechanism; based on a dynamic adjustment mechanism, multiple mobile terminals are used for cooperative measurement, position information is synchronized and shared through a wireless network, and a virtual quadrupole measurement topological structure is constructed; based on the virtual quadrupole measurement topological structure, one part of the mobile terminals transmit test signals, the other part of the mobile terminals receive response signals, and the optimal sampling frequency and time window are combined to invert and generate a space resistance distribution diagram of the grounding grid; historical monitoring data, a space resistance distribution diagram and real-time environment parameters are combined.

Technologies for providing energy efficiency technology in extreme mMIMO systems in a cellular network cellular network (e.g., 5G wireless network, 6G wireless network) are described. The method collects data representing conditions for potential energy saving (ES) modes, comprising morphology data and traffic pattern data. The method determines, using the collected data, one or more energy saving (ES) modes for one or more components of a cellular network in at least one of a time (T) domain, a frequency (F) domain, or a space (S) domain, wherein the one or more ES modes cause at least one adjustment to the one or more components in the at least one of the time (T) domain, the frequency (F) domain, or the space (S) domain.

A method is performed by a user equipment. The method comprises logging information related to a small-data transmissions procedure performed by the user equipment in a report. The method further comprises transmitting the report to a network node.

The invention relates to the technical field of communication, and discloses a sea area wireless network coverage method and device and a computer readable storage medium, and the method comprises the steps: obtaining the historical link performance, real-time marine environment data and business load information of a target sea area; constructing a sea surface electromagnetic wave propagation attenuation dynamic prediction model based on a gated circulation unit; and in combination with the prediction result and the service demand, jointly optimizing the base station transmitting power, the antenna beam pointing angle and the subcarrier resource allocation, and issuing a regulation and control instruction. The system comprises a data acquisition module, a propagation modeling module, a resource scheduling module and an instruction execution module. According to the invention, through deep fusion of marine environment physical field perception and wireless communication system control, a dynamic coverage regulation and control mechanism driven by a sea condition is established; the provided sea surface electromagnetic wave propagation attenuation dynamic prediction model can pre-judge the signal attenuation trend under the complex sea condition in advance, so that network resource scheduling has perspectiveness.

Embodiments include methods for a user equipment (UE), particularly for performing quality of experience (QoE) measurements configured by a wireless network. Such methods include receiving, from a radio access network node (RNN) in the wireless network, a request for QoE measurement reports that are available at the UE and that are associated with one or more services provided by the UE application layer. Such methods also include sending one or more QoE measurement reports to the RNN in accordance with the request. Other embodiments include complementary methods for a RNN, as well as UEs and RNNs configured to perform such methods.

The invention belongs to the technical field of wireless network communication, and discloses a dual-time-scale optimization method for multi-unmanned aerial vehicle cooperative auxiliary task unloading and caching, which comprises the following steps: setting an updating time slot of an unmanned aerial vehicle service caching decision as a first time slot, updating time slots of the unmanned aerial vehicle flight path decision, the computing resource allocation decision and the user unloading decision are second time slots; wherein the first time slot is composed of a plurality of second time slots; constructing a first optimization objective function and a second optimization objective function; in each first time slot, obtaining requirements of a user task for various service resources, and updating a service cache decision of the unmanned aerial vehicle according to the first optimization objective function; and in each second time slot, obtaining an unmanned aerial vehicle position, a user task and an unmanned aerial vehicle service cache, and updating an unmanned aerial vehicle flight path decision, a computing resource allocation decision and a user unloading decision according to the second optimization objective function.

The invention relates to the technical field of electric power communication and information, in particular to a substation wireless network performance optimization method based on the Internet of Things, which comprises a data acquisition module, a data transmission and preprocessing module, an intelligent analysis module, a strategy generation module, a strategy execution and feedback module and an effect evaluation and abnormity alarm module. The data acquisition module is used for acquiring operation data and environment parameters of a wireless network of the transformer substation in real time; and the data transmission and preprocessing module is used for performing low-power-consumption transmission, cleaning, normalization and feature extraction processing on the operation data and the environment parameters. According to the application, wireless signal quality (signal intensity, signal-to-noise ratio and the like), equipment operation states (CPU / memory utilization rate and connection number), service load characteristics (flow peak value and protocol type) and environmental parameters (electromagnetic interference intensity, temperature and humidity) are synchronously acquired through the data acquisition module, multi-dimensional data fusion is realized, and a more complete information basis is provided for subsequent analysis.

The invention provides a directional network adaptive radiation control method and system, and relates to the technical field of wireless network control, and the method comprises the steps: obtaining real-time high-frequency motion data, relative distance data and environment interference intensity data of a wireless network; motion state continuous quantization is carried out according to the real-time high-frequency motion data, and motion characteristic quantities are constructed and obtained; performing multi-step track prediction processing according to the motion characteristic quantity, and outputting a track prediction sequence; performing prediction reliability evaluation according to the trajectory prediction sequence, and generating a trajectory uncertainty index; generating a radiation control signal according to the motion characteristic quantity and the trajectory uncertainty index to obtain the radiation control signal; and performing beam forming and power adaptive processing according to the radiation control signal and the real-time relative distance data to obtain a final beam form and power parameter combination. According to the method, the communication quality and the anti-interference capability of the directional network in a complex environment are remarkably improved.

The invention relates to the technical field of network slicing, and discloses a wireless network multi-link communication method based on dynamic link configuration. The method comprises the following steps: collecting state data of heterogeneous links such as cellular links, Wi-Fi links and satellites in real time, and constructing a global network state view; analyzing the network slice SLA and converting the network slice SLA into a quantitative performance constraint; predicting the future performance of the link by using a gating circulation unit neural network; generating a global optimal data flow routing and distribution strategy meeting the QoS (Quality of Service) requirements of the slices in the central controller based on reinforcement learning; and compiling the strategy into a configuration instruction and issuing the configuration instruction to the terminal and the access point for execution. The system comprises a state sensing module, a strategy analysis module, a prediction modeling module, a strategy generation module and a configuration execution module. By means of predictive planning and intelligent decision making, dynamic, fine and on-demand scheduling of heterogeneous resources is achieved, and the network resource utilization rate and the multi-service service quality guarantee capacity are remarkably improved.

Systems and methods are provided for providing sensing features. A WTRU receives first configuration information indicative of a CSI-RS sub-band configuration, at least one first criterion and at least one second criterion. The WTRU performs channel state estimation measurements on a plurality of CSI-RS resources, identifies a set of sub-band options from the CSI-RS resources that satisfy the at least one first criterion based at least in part on the channel state estimation measurements and on the CSI-RS sub-band configuration, identifies a subset of the identified set of sub-band options that satisfy the at least one second criterion, and transmits, to the wireless network, a sub-band request. The WTRU receives, from the wireless network based on the sub-band request, second configuration information indicative of which of the plurality of CSI-RS resources are to be used for sensing measurements and performs the sensing measurements based on the second configuration information.

Embodiments of the present disclosure relate to method and apparatus for handing over a UE in an IAB network. According to some embodiments of the disclosure, a UE may: communicate with a first BS via a wireless network node; receive an RRC reconfiguration message for handing over the UE from the first BS to a second BS together with the wireless network node; and in response to receiving the RRC reconfiguration message, maintain an air interface between the UE and the wireless network node while performing the handover from the first BS to the second BS.

The disclosure relates to a 5G or 6G communication system for supporting a higher data transmission rate. Embodiments herein provide higher priority PLMN selection method during disaster situation in a wireless network (1000) by MS (100). In an embodiment, when MS (100) is registered for the disaster roaming service, the method includes selecting a higher priority PLMN in a priority order when the higher priority PLMN is available in the network and other non-forbidden PLMN when the higher priority PLMN is unavailable in the network, and registering the MS to receive the service in the network on one of the selected higher priority PLMN, and the selected other non-forbidden PLMN. In another embodiment, when the MS is not registered for the disaster roaming service, the method includes selecting a higher priority PLMN in a priority order when the higher priority PLMN is available in network, and registering the MS on the selected higher priority PLMN to receive the service in network.

Procedures, methods, architectures, apparatuses, systems, devices, and computer program products for handover procedures which use network predicted measurements. For example, a wireless transmit / receive unit (WTRU) may receive a handover command. The WTRU may receive a first set of measurements from a network. For example, the first set may be predicted measurements. The network may use artificial intelligence and / or machine learning models to generate the first set. The WTRU may obtain (e.g., measure and / or predict) a second set of measurements. The first and / or second set of measurements may be associated with a (e.g., same) first time interval and / or confidence level. Based on a comparison between the first set and second set, the WTRU may determine (i) to execute a handover, in a second time interval, and / or (ii) send feedback information. For example, the WTRU may determine an ideal time to actually execute the handover.

The invention belongs to the field of unmanned surface vessels, and discloses an unmanned cluster defense control platform and method based on a mooring aerial vehicle, and the platform comprises an aerial vehicle and unmanned vessel flexible cooperative control module, and an intelligent decision and tactical optimization module. The aerial carrier and unmanned ship flexible cooperative control module is used for constructing a closed command and control system independent of a wireless network on the basis of a mooring type coupling control technology, and the unmanned ship-unmanned aerial vehicle rigid connection requirement in a marine high dynamic environment is met; and the intelligent decision and tactical optimization module is used for constructing a virtual-real mapping marine combat experiment field based on a digital twin confrontation deduction technology, restoring a complex marine environment and a confrontation scene through digital modeling, and forming a closed-loop capability improvement mode.

The present application relates to devices and components including apparatus, systems, and methods for detecting congestion in wireless networks.

A wireless communication method for use in a wireless terminal is disclosed. The method comprises transmitting, to a wireless network node, a channel occupancy time (COT) sharing indication associated with sharing a COT initiated by the wireless terminal, wherein the COT sharing indication comprises at least one of: a starting point, a duration or an available resource block set of the COT.

A method performed by UE for reducing latency. The method includes receiving first configuration information for at least a first uplink (UL) resource, the first UL resource used to access a wireless network and associated with a network node operating in discontinuous transmission and reception (DTRX). The method also includes receiving second configuration information for at least a second UL resource, the second UL resource also used to access the wireless network. The method further includes accessing the wireless network using the second UL resource when the first UL resource is in an off period of the DTRX.

The invention discloses a multipath channel parameter reconstruction and beam coverage prediction method, and relates to the technical field of wireless communication. Aiming at the problems of low data utilization efficiency, limited environment modeling precision, strong coupling of measured data and antenna beam configuration and the like in the prior art, the method comprises the steps of configuring antenna beams and orientation parameters, collecting reference signal receiving strength, performing deterministic channel modeling simulation, establishing a mapping model, performing sparse recovery, constructing a channel propagation model, evaluating a channel map and the like. In combination with a coherence perception weighting network (CARE-Net) algorithm and ray tracing (RT) physical prior guidance, accurate reconstruction from a low-dimensional reference signal receiving strength (RSRP) measurement value to a high-dimensional multipath parameter is realized. The method has the advantages that the reconstructed multi-path parameters are decoupled from the antenna configuration, the method has the cross-beam / cross-configuration generalization prediction capability, the channel coverage performance under different antenna configurations can be accurately predicted, a reliable basis is provided for wireless network optimization, and the method is low in cost, high in precision and strong in generalization.

The disclosure relates to a 5G or 6G communication system for supporting a higher data transmission rate. A method performed by a vertical application layer (VAL) server in a wireless communication system is provided. The method comprises transmitting, to a location management server, a user equipment (UE) information request message including a first VAL service area identity (ID) of a first VAL service area and receiving, from the location management server, UE information as a response to the UE information request message. The UE information includes a list of at least one UE whose location is within an application defined proximity range of the first VAL service area corresponding to the first VAL service area ID, and the application defined proximity range includes a range in which the UE information is required.

The present application relates to the technical field of transmission scheduling in the industrial Internet, and discloses a trusted scheduling method and apparatus for a dynamic blockchain-based industrial wireless network. The method comprises: constructing a dynamic blockchain mechanism-based industrial wireless network system; on the basis of preset constraint conditions respectively corresponding to a scheduling stage and a consensus stage, performing model construction with the goal of maximizing the trusted processing efficiency of tasks, and obtaining an optimization model, the optimization model carrying parameters to be optimized; on the basis of a preset multi-agent Markov decision process model, performing model reconstruction on the optimization model, and obtaining a target optimization model; and, on the basis of observation information acquired in real time of each industrial device in the industrial wireless network system, using a preset rotation multi-agent deep reinforcement learning algorithm model to optimize the target optimization model, and obtaining a target parameter value corresponding to each parameter to be optimized. The method of the present application improves the trusted processing efficiency of tasks in an industrial wireless network system.