16443 results about "Base station" patented technology

The present disclosure relates to a communication technique which combines a 5th generation (5G) communication system for supporting a higher data transmission rate beyond a 4G system with an internet of things (IoT) technique and a system thereof. The present disclosure may be applied to intelligent services (e.g., a smart home, a smart building, a smart city, a smart car or a connected car, health care, digital education, retail business, security and safety related services, etc.) based on 5G communication technology and IoT related technology. According to various embodiments of the present disclosure, in a wireless communication system, a terminal may include at least one transceiver and at least one processor coupled with the at least one transceiver, the at least one processor may be configured to receive system information from a cell of a base station, determine whether the cell supports new radio (NR) lite, based on the system information, and if the cell supports the NR lite, perform a random access procedure for the cell, and for the terminal performing the NR lite, at least one of a subcarrier spacing (SCS), a transport block (TB) size, or a bandwidth part (BWP) is reduced to a designated value, compared to other terminal not performing the NR lite.

The invention provides an intelligent short message scheduling method and device based on multi-dimensional dynamic optimization, and the method comprises the steps: obtaining the performance data of a plurality of short message channels, and calculating a channel health score based on a weight dynamic adjustment model; determining a scheduling strategy according to the priority identifier of the to-be-sent message, and performing channel screening and optimal matching; executing message sending and monitoring a sending state; terminal state detection is carried out on the failure message through operator base station signaling, and a decision tree model is applied to determine a retry strategy; and performing Huffman coding compression processing on the P2-level marketing messages which fail in retry, and performing batch sending in an idle window. According to the method, a comprehensive performance evaluation index and reward function model is also constructed, and parameter optimization is performed by applying a reinforcement learning algorithm. According to the invention, multi-dimensional dynamic channel scoring, intelligent retry decision making based on terminal state perception, batch processing with balanced cost-time efficiency and a closed-loop self-optimization system are realized, the short message delivery rate is obviously improved, and the invalid retry rate and the sending cost are reduced.

A wireless communication method and system enabling dynamic multi-path data transmission and reception across heterogeneous radio access networks. The method includes selecting between sequential, concurrent, or redundant multipath transmission strategies based on real-time measurements of link quality parameters, including signal-to-interference-plus-noise ratio (SINR), reference signal received power (RSRP), delay, and spectrum availability. The system further enables adaptive transmission power control, modulation scheme selection, and carrier configuration based on physical layer feedback, minimizing interference and optimizing spectral efficiency. Peer-to-peer communication between terminals is supported without base station mediation, reducing RAN load. Multi-base station connectivity is enabled, allowing terminals to simultaneously transmit through multiple nodes and aggregate at the core network. The architecture supports real-time topology control, dynamic link adaptation, and transmission parameter adjustment based on physical-layer constraints.

The invention relates to a wireless communication test method and system based on a portable frequency spectrograph and a medium, and belongs to the technical field of radio frequency spectrum analysis, and the wireless communication test method comprises the steps: collecting electromagnetic signal original data of a target area; constructing a dynamic electromagnetic environment baseline model; performing filtering and background subtraction processing on the original data of the electromagnetic signal; carrying out modulation mode identification, protocol analysis and terminal identification extraction on the preprocessed signal matrix, generating a multi-dimensional feature vector, carrying out convolution similarity matching on the multi-dimensional feature vector and a legal signal feature template, and distributing a threat level label; dynamically reconstructing scanning parameters of the portable spectrum analyzer according to the threat level label, generating an equipment parameter adjustment record and updating the electromagnetic fingerprint database; and generating a spectrum optimization control instruction based on the threat level label and the equipment parameter adjustment record, and issuing the spectrum optimization control instruction to the target base station or the terminal equipment. According to the application, the identification precision of the threat signal and the control closed-loop linkage capability in a complex electromagnetic environment are improved.

A wireless device receives, from a base station, a radio resource control (RRC) reconfiguration message comprising a layer 1 / layer 2 triggered mobility (LTM) configuration. The LTM configuration comprises an LTM candidate configuration of a candidate cell and a value of a time alignment timer for determining whether a timing advance (TA) value of the candidate cell is valid. The wireless device receives, from the base station, a downlink control information (DCI) indicating the candidate cell and to transmit a random access preamble for acquiring the TA value of the candidate cell. Based on the DCI, the wireless device transmits, via the candidate cell, the random access preamble for acquiring the TA value of the candidate cell. The wireless device receives, from the base station, a medium access control (MAC) control element (CE) indicating an identifier of the LTM candidate configuration of the candidate cell and the TA value.

The invention discloses a low-altitude unmanned aerial vehicle trajectory tracking and monitoring method based on a 5G-A communication sensing integrated base station, and relates to the technical field of low-altitude traffic management and communication sensing fusion, and the method comprises the steps: firstly collecting multi-source data such as a communication sensing fusion signal, environment interference and unmanned aerial vehicle attributes, and carrying out the alignment and packaging of a unified timestamp and a coordinate system into a synchronous data frame; then, deep fusion and anti-interference processing are carried out on the data frames, noise is filtered out, and pure fusion data is generated; and furthermore, real-time track calculation and motion trend prediction are carried out on pure data by utilizing multi-base-station cooperative calculation and prediction. Based on this, through a multi-target feature recognition and clustering separation mechanism, independent individual trajectories are accurately stripped from a complex mixed data stream, and compliance verification and anomaly judgment are performed on the trajectories in combination with an airspace rule base. In this way, the problems of signal interference and multi-target aliasing in a complex environment can be effectively solved, and therefore high-precision global tracking of the low-altitude unmanned aerial vehicle and real-time monitoring of abnormal behaviors are achieved.

Methods and apparatuses for power control and beam management to enable coexistence of radar sensing and wireless communication. A method for a UE includes determining a sensing category or characteristics for a sensing application, and selecting a spatial filter for radar sensing transmission or reception based on determined sensing category or characteristics. The method further includes identifying a radar sensing transmission power and transmitting or receiving radar sensing signals using the spatial filter and the identified radar sensing transmission power. The method further includes reporting one of communication blockage, radar sensing beam information, or CSI adapted to the radar sensing beam information to a base station or neighboring UEs.

The invention provides an ultra-low-altitude-domain three-dimensional radio map generation system, and the system comprises a three-dimensional grid division and data preprocessing module which is used for dividing a target region into voxel grids containing latitude and longitude and height coordinates; the satellite remote sensing image feature extraction module is used for generating environment high-dimensional image features of the target area; the communication base station parameter encoder is used for generating base station space propagation characteristics of the target area; the two-dimensional feature migration and three-dimensional feature generation module is used for generating initial three-dimensional feature representation; the three-dimensional interpolation and height correction module is used for outputting corrected three-dimensional RSRP features; and the multi-modal fusion and decoding module is used for fusing the corrected three-dimensional RSRP features, the environment high-dimensional image features and the base station space propagation features, and inputting a fusion result into a three-dimensional decoding network to generate a final three-dimensional radio signal power distribution diagram. The three-dimensional radio map is generated for the urban low-altitude scene.

The invention discloses a multi-unmanned aerial vehicle adaptive control distribution method based on a mobile nest, and belongs to the technical field of unmanned aerial vehicle control, and the method comprises the following steps: S1, information collection and fusion, S2, dynamic task priority evaluation, S3, task matching, S4, cooperative control strategy generation, S5, detection and adjustment, and S6, management and optimization. By constructing a system architecture with a mobile nest as a core and combining an adaptive task allocation algorithm and reinforcement learning cooperative control, efficient cooperation of multiple unmanned aerial vehicles in a complex scene can be realized, and the mobile nest senses task requirements and environmental changes in real time, dynamically allocates tasks and adjusts a control strategy by virtue of strong calculation and communication capabilities, so that the system is more efficient and efficient. The unmanned aerial vehicle resources are accurately matched, and idling or overload is avoided.

The invention relates to the technical field of wind power generation, discloses an intelligent safety early warning method for wind power hoisting operation, and aims to solve the technical problems of insufficient perception and lack of data fusion and intelligent analysis decision in existing operation safety management. The method is characterized by comprising the following steps: constructing an intelligent terminal integrated with a UWB / IMU / safety belt / environment sensor; deploying a positioning base station network and a signal relay system; a multi-source data fusion intelligent analysis platform is established, and high-precision positioning, behavior recognition and deep learning risk prediction are achieved; and a closed-loop intelligent decision-making and execution system is constructed, and graded early warning, electronic fence, environment linkage and one-key help calling are realized. According to the method, a traditional experience driving mode is innovated into a data driving mode, the safety level and the operation efficiency of wind power hoisting operation are remarkably improved, and the defects of insufficient perception, information isolation and the like are overcome.

The invention relates to the technical field of network load prediction, and particularly discloses a power supply energy saving system and method based on a load prediction intelligent dormancy strategy, and the method comprises the steps: collecting base station service load and power supply power data, and employing a neural network to accurately fit the nonlinear relation between the two for adjusting the power; constructing a multi-mode service load prediction model, generating a power supply power adjustment instruction in advance, and adjusting the power in time when the load prediction deviation exceeds a threshold value; frequent power fluctuation is avoided through a dynamic threshold mechanism based on hysteresis comparison; a sleep and wake-up strategy and a buffer mechanism are established to ensure that the state of the power supply is switched only when the load changes continuously, so that the switching accuracy and stability are improved; self-adaptive sleep duration and progressive wake-up adjustment are introduced, so that smooth transition and intelligent energy conservation of power supply operation are realized; the method can improve the energy efficiency of the power supply and reduce the energy consumption.

The invention discloses a resource allocation method and system for 5G communication in an underground coal mine, and relates to the technical field of communication information processing, and the method comprises the steps: obtaining data information of an underground coal mine roadway, building a digital twin communication model through combining a synchronous positioning and map building algorithm and a wireless fingerprint matching algorithm, generating a channel profile map according to real-time data, and transmitting the channel profile map to a server; extracting channel data of each space node; constructing a computing resource pool for the 5G base station and the edge computing node, and packaging different service types into a plurality of network slice containers; according to the channel data, carrying out initial allocation on each container through a resource composer, and carrying out dynamic task migration among different MEC nodes to obtain a resource allocation state; dividing scheduling time according to a channel profile and a resource allocation state, and dynamically adjusting a duration proportion and bandwidth occupation of each window according to a task migration state; according to the invention, through digital twinning and dynamic scheduling, the problems of 5G communication coverage and interference in the underground coal mine are solved.

Disclosed are a method and apparatus for transmitting and receiving a wireless signal in a wireless communication system. The method according to an embodiment of the present disclosure may comprise the steps of: receiving, from a base station, first configuration information including a list of TCI states, the list of TCI states providing a reference signal for a QCL for a downlink channel and / or a reference for determining an uplink transmission spatial filter for an uplink channel; receiving, from the base station, second configuration information related to a CORESET, a plurality of CORESETs, which have different CORESET full indexes, being configured by the second configuration information; and receiving DCI from the base station.

A method can include transmitting, by a wireless device to a base station, via a first cell of the wireless device, an uplink signal based on determining a radio link failure of a second cell, the second cell being configured for early timing advance (TA) acquisition. The transmitting the uplink signal can be at least one of: based on the second cell being configured for early timing advance acquisition of the wireless device; or after receiving, by the wireless device, an indication to at least one of acquire a TA value of the second cell; start to acquire the TA value of the second cell; or transmit, by the wireless device via the second cell, a reference signal.

The invention discloses an Internet of Vehicles network selection and switching decision system supporting access of multiple operators. According to the method and the device, the timeliness and the continuity of network switching are remarkably improved through prediction and planning in advance. The module depends on a trajectory-network matching prediction sub-module, combines a vehicle navigation trajectory and a global digital twinborn model, identifies a base station coverage area in a future driving path and the network service quality of each operator in advance, and avoids the lag problem that switching is triggered only after signals are weakened in traditional passive switching. The pre-switching resource reservation sub-module further sends a resource request to a target operator base station and confirms reservation before the vehicle enters a new road section, ensures that resources such as bandwidth and time slot required during switching are in place, reduces switching failure or interruption caused by resource competition, avoids common communication interruption after signal sudden drop in traditional switching, and improves the switching efficiency. And continuous transmission of key businesses such as automatic driving control instructions and real-time road conditions is ensured.

The invention discloses a hospital Internet of Things equipment intelligent monitoring and fault early warning system based on edge computing, relates to the technical field of equipment monitoring and early warning, and aims to solve the technical problem that fault discovery lags in a high-real-time scene of an existing intelligent monitoring and fault early warning system. The system is used for collecting various data of hospital Internet of Things equipment and sending the data to a preset storage position, and comprises a local database, a data processing module and an abnormal data judgment unit; the Internet of Things base station is used for being connected with Internet of Things equipment, collecting equipment data and achieving intelligent monitoring and fault early warning through an algorithm model, and the algorithm model is constructed based on a core algorithm and rules; and the hospital Internet of Things edge computing platform is used for carrying out edge computing management on the data sent by the Internet of Things base station, feeding back an analysis result and storing the data. The method has the advantage of improving the fault discovery speed of the Internet of Things equipment.

The invention discloses a low-altitude airway flow field sensitive area dynamic identification optimization method based on set simulation, and the method comprises the steps: building a low-altitude flow field preprocessing data base with consistent time and space based on Beidou subdivision grids and multi-source heterogeneous data fusion; constructing a low-altitude airspace digital twinning environment based on the data; based on the low-altitude airspace digital twin environment and the cellular automaton-fluid coupling model, generating a diversified flow field evolution scene covering extreme weather and equipment faults; based on a set simulation result, extracting a high-conflict probability region through a spatio-temporal clustering algorithm and quantifying region risk features; generating an air route planning scheme meeting security constraints through a multi-objective evolutionary algorithm based on the quantitative regional risk features; on the basis of a low-altitude airspace digital twin environment and an air route planning scheme, verifying the feasibility of the air route planning scheme through historical data playback and virtual-real fusion test; and according to a verification feedback result, carrying out dynamic feedback optimization on the low-altitude air route flow field sensitive area identification and air route planning scheme.

The invention relates to a space-ground integrated Beidou high-precision positioning method applied to urban canyons, and belongs to the technical field of navigation positioning. The method comprises the following steps: deploying a pseudo satellite base station, calibrating coordinates of the base station through carrier phase difference, and monitoring the number of Beidou visible satellites; a master pseudo-satellite is determined, timestamps and ephemeris data are broadcasted to slave pseudo-satellites through Beidou short messages, and the slave pseudo-satellites are combined with bidirectional ranging data to correct a local clock to realize high-precision synchronization; receiving Beidou and pseudo-satellite signals by a user terminal, screening effective observation values through a shielding judgment mechanism, substituting the effective observation values into a non-difference observation equation in combination with pseudo-satellite reference difference data, and resolving a fusion result through an elastic coupling mode; and finally, multi-path interference is identified by using pseudo-satellite double antennas, and historical data is called to construct an error model to correct a fusion result. The space-ground integrated positioning of Beidou and pseudo satellites in an urban canyon scene is realized, the centimeter-level positioning precision is stably output, and the high-precision positioning requirements of urban traffic, surveying and mapping and the like are met.

A terminal according to an aspect of the present disclosure includes a receiving section that receives information related to first random access procedure including a repetition of a message 1, and a control section that, based on the information, uses, for the first random access procedure, a first random access resource and uses, for second random access procedure not including the repetition of the message 1, a second random access resource different from the first random access resource. According to an aspect of the present disclosure, it is possible to enhance coverage in random access procedure.

A method performed by a wireless transmit / receive unit (WTRU) may compromise: transmitting, to a base station, Rx beam capability information; determining a Rx beam ID for each of one or more Rx beams of the WTRU; receiving, from the base station, information indicating a first reference signal (RS) resource set and a second RS resource set; determining an association between the first RS resource set and second RS resource set and one or more Tx beam IDs; determining a preferred beam pair, including a preferred Rx beam and preferred Tx beam; and transmitting, to the base station, information indicating a beam pair ID of the preferred beam pair.

The invention discloses a multi-base-station AOA cooperative low-altitude target rapid positioning system. The system comprises an AOA measurement base station network, an AOA data preprocessing module, an adaptive weighted intersection positioning module, an extended Kalman filtering state estimation module and a data fusion and system integration module. The system synchronously measures the arrival angle of a target signal through multiple base stations, removes noise in combination with smoothing filtering and an anomaly rejection algorithm, and then solves the initial position of a target by using a self-adaptive weighted intersection algorithm based on measurement quality and geometric distribution. And then, fusing the target motion model and the measurement model by adopting an extended Kalman filtering algorithm to realize dynamic estimation and prediction of the position, the speed and the course. The system can realize high-precision and real-time positioning and continuous tracking of targets such as low-altitude unmanned aerial vehicles, small aircrafts and the like in a complex electromagnetic environment and a sight distance limited scene, and has visual display and regional alarm functions.

The invention relates to the technical field of dam safety monitoring, in particular to a method and system for improving dam GNSS deformation monitoring precision through base station and observation station combined network adjustment. The method comprises the following steps: arranging base stations and monitoring points to form a GNSS monitoring network; gNSS original observation data are collected in real time and preprocessed; constructing a joint network adjustment model, and taking base station coordinates as constraints and monitoring point coordinates as to-be-estimated parameters; performing baseline resolving based on the double-difference carrier phase observed quantity to obtain a baseline vector and a covariance matrix thereof; carrying out overall adjustment on the baseline vector by adopting a robust estimation method, and solving an optimal coordinate estimated value and precision information of the monitoring point; carrying out deformation analysis on the basis of the adjusted coordinate time sequence, and extracting tendency, periodicity and abnormal deformation; and outputting a deformation monitoring result, and carrying out visual display and early warning. According to the method, the precision and reliability of dam deformation monitoring are effectively improved through combination of network adjustment and robust estimation.

A first base station node receives, from a second base station node, a request to setup a context of a wireless device, wherein the request indicates that a packet flow is associated with a PDU set.

The invention discloses an unmanned aerial vehicle centimeter-level hovering control system based on single Beidou differential positioning, and particularly relates to the technical field of unmanned aerial vehicle high-precision positioning and control. The system comprises a Beidou RTK positioning module, a multi-sensor fusion module, a flight control module, a motor driving module, an exception handling module and a ground base station module. Centimeter-level positioning data are obtained through Beidou RTK, and a high-precision pose is output through tight coupling filtering by combining an IMU and a barometer; the flight control module adopts a model prediction algorithm to generate an instruction; the motor driving module realizes quick response; the exception handling module guarantees the reliability of the system; the ground base station provides differential correction. The single Beidou differential positioning and multi-sensor fusion technology is innovatively adopted, centimeter-level precision autonomous hovering control of the unmanned aerial vehicle is achieved, and the unmanned aerial vehicle hovering control system has the advantages of being high in precision, high in interference resistance and rapid in response and is suitable for industrial unmanned aerial vehicle application scenes such as precision agriculture and electric power inspection.

A terminal according to one aspect of the present disclosure includes: a receiving section that receives, when the terminal includes eight antenna ports, downlink control information (DCI) including a plurality of fields of at least one of a precoding information and number of layers field and a transmission precoding matrix indicator (TPMI) field for codebook-based physical uplink shared channel (PUSCH) transmission; and a control section that controls uplink transmission, based on the DCI. According to one aspect of the present disclosure, UL transmission using more than four antenna ports can be appropriately controlled.

The invention provides a dual-unmanned aerial vehicle cooperative obstacle avoidance and communication link reconstruction system and method, and belongs to the technical field of wireless communication and unmanned aerial vehicle cooperative control. The system is composed of two unmanned aerial vehicles, serves as a mobile base station to provide relay communication for users, and cooperatively perceives an aerial target. The method comprises the following steps: establishing an integrated model integrating tracks, NOMA signals and layered continuous interference cancellation; calculating communication and sensing key indexes; constructing an optimization problem which takes maximization of the minimum average interaction rate between the unmanned aerial vehicles as a target and takes power, QoS, perception and security constraints into consideration; a distributed architecture is adopted to decompose problems, and a Dual-TD3 algorithm is proposed to collaboratively optimize beam forming and a flight path. According to the dual-unmanned aerial vehicle cooperative obstacle avoidance and communication link reconstruction system and method, dynamic intelligent distribution of communication and sensing resources is realized, and the interaction rate, the robustness and the resource utilization rate of the system in a dynamic scene are remarkably improved.

The invention relates to the technical field of underwater robots and high-precision positioning, and particularly discloses a high-precision positioning system for collaborative operation of an underwater robot cluster. The system comprises a multi-source fusion positioning base station network module, a cross-medium cooperative positioning engine module, a cluster relative positioning subsystem module, a dynamic environment perception compensation module, an elastic positioning fault-tolerant system module and a cooperative positioning decision center module. An absolute positioning reference is constructed through a multi-source fusion positioning reference station network, a cross-medium cooperative positioning engine is combined to realize accurate pose calculation, a cluster relative positioning subsystem is utilized to establish a dynamic topological relation between robots, an environment perception compensation and elastic fault-tolerant mechanism is introduced, and finally resource configuration is optimized through a cooperative decision center. The method solves the problem of high-precision positioning of robot cluster collaborative operation in a complex underwater environment, and can be widely applied to the fields of ocean exploration, underwater engineering and the like.

The invention provides a 5G communication-based vehicle state sensing and intelligent traffic cooperative scheduling method, and relates to the technical field of intelligent traffic, and the method comprises the steps: receiving high-frequency vehicle state sensing data transmitted by a vehicle-mounted unit in a target road section in real time through a 5G base station cluster; collecting traffic environment sensing data of a target road section through a roadside sensing unit, fusing the high-frequency vehicle state sensing data with the traffic environment sensing data, and constructing a multi-dimensional real-time traffic situation map; performing collaborative analysis based on the multi-dimensional real-time traffic situation map to generate a traffic control instruction set; and issuing to a road side execution unit and a vehicle-mounted unit for cooperative scheduling control of the traffic flow. The technical problems that a traffic system in the prior art often depends on periodic data acquisition and a fixed signal control scheme, traffic control adjustment cannot be carried out in real time according to changing traffic conditions, traffic flow fluctuation or emergencies cannot be rapidly coped with, and then the traffic system is low in efficiency and unstable are solved.

A method performed by an integrated access backhaul (IAB) node in a wireless communication system is provided. The method comprises: receiving, from a base station, configuration information regarding an uplink (UL) grant, receiving, from the base station, configuration information regarding backhaul (BH) radio link control (RLC) channel via higher layer signaling, identifying, based on the configuration information regarding BH RLC channel, whether an extended logical channel identifier (eLCID) is used, in case that the eLCID is not used and a UL grant size is equal to or larger than a first size, not transmitting only a padding buffer status report (BSR) or not transmitting only padding or not transmitting only the padding BSR and the padding, and in case that the eLCID is used and the UL grant size is equal to or larger than a second size, not transmitting only the padding BSR or not transmitting only the padding or not transmitting only the padding BSR and the padding.

The invention relates to the technical field of backhaul monitoring, in particular to a backhaul link monitoring method and system applied to a 5G base station, and the method comprises the steps: collecting physical signal statistical data, backhaul service data and network topology data of a backhaul link in real time; according to physical signal statistical data, a physical layer entropy value is calculated through a Shannon entropy formula, and recessive degradation characteristics of a physical layer are quantified; a pulse neural network space-time coding mechanism is used to generate business layer anomaly prediction parameters, and cross-layer anomaly prediction is realized; according to service types and priorities, constructing a time-varying service awareness reference model by adopting a chaos kinetic equation to serve as a dynamic judgment reference; when the return state is abnormal, combining the physical layer entropy and the network topology data to construct a feedback correction loop, and generating a self-adaptive protection strategy; according to the method, advanced prediction and accurate positioning of recessive degradation of the backhaul link are realized, and the self-healing capability and the service quality guarantee level of the backhaul link in a multi-service scene are improved.