17097results about "Network planning" 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.

Systems, methods, and apparatuses for providing optimization of network resources. The system is operable to monitor the electromagnetic environment, analyze the electromagnetic environment, and extract environmental awareness of the electromagnetic environment. The system extracts the environmental awareness of the electromagnetic environment by including customer goals. The system is operable to use the environmental awareness with the customer goals and / or user defined policies and rules to extract actionable information to help the customer optimize the network resources.

Systems, methods, and apparatuses for providing optimization of network resources. The system is operable to monitor the electromagnetic environment, analyze the electromagnetic environment, and extract environmental awareness of the electromagnetic environment. The system extracts the environmental awareness of the electromagnetic environment by including customer goals. The system is operable to use the environmental awareness with the customer goals and / or user defined policies and rules to extract actionable information to help the customer optimize the network resources.

Systems, methods, and apparatuses for providing dynamic, prioritized spectrum utilization management. The system includes at least one monitoring sensor, at least one data analysis engine, at least one application, a semantic engine, a programmable rules and policy editor, a tip and cue server, and / or a control panel. The tip and cue server is operable utilize the environmental awareness from the data processed by the at least one data analysis engine in combination with additional information to create actionable data.

Systems, methods, and apparatuses for providing optimization of network resources. The system is operable to monitor the electromagnetic environment, analyze the electromagnetic environment, and extract environmental awareness of the electromagnetic environment. The system extracts the environmental awareness of the electromagnetic environment by including customer goals. The system is operable to use the environmental awareness with the customer goals and / or user defined policies and rules to extract actionable information to help the customer optimize the network resources.

The invention relates to the technical field of communication management, and provides a communication base station traffic prediction management system based on deep learning, which comprises a multi-source data acquisition module used for acquiring base station space-time traffic data, user behavior data, network state data, external influence factors and data set slice service parameters; the spatio-temporal feature processing module is used for performing spatio-temporal alignment, noise filtering and slice feature coding on the multi-source data; and the dynamic model prediction module is used for constructing a multi-modal prediction network of a space-time Transform, a graph neural network and a slice exclusive sub-model. A base station association graph based on geographical distance and service correlation is constructed, spatial features are extracted through a multilayer graph convolutional network, slice features and spatial-temporal features are fused by using a gating mechanism, a Pareto optimal strategy is generated by using a multi-objective optimization algorithm, and a strategy library is updated in combination with a forgetting factor, so that the probability of forgetting is reduced. The response time of the system in an abnormal scene is shortened, and the strategy optimization efficiency is improved.

The invention relates to the technical field of artificial intelligence rescue, and discloses an unmanned aerial vehicle and robot dog rescue emergency system and method, and the system comprises an unmanned aerial vehicle cluster module which is used for air data collection, communication guarantee and emergency material distribution; the robot dog cluster module is used for ground environment detection, sample collection and special task execution; the communication cooperation module is used for ensuring information intercommunication and task cooperation between air-ground equipment; the central control module provides task instructions for the unmanned aerial vehicle cluster and the robot dog cluster; the human-computer interaction interface module is used for realizing effective communication between rescue workers and the system; the modules work cooperatively, multi-source data acquisition, three-dimensional scene reconstruction, semantic segmentation, risk assessment, fire spreading prediction and decision support information generation of a disaster site are realized, and a reliable basis is provided for rescue command decision.

Devices and methods enable optimizing a signal of interest based on identifying and analyzing the signal of interest based on radio frequency energy measurements. Signal data is compared with stored data to identify the signal of interest. Signal degradation data is calculated based on noise figure parameters, hardware parameters and environment parameters. The signal of interest is optimized based on the signal degradation data. Terrain data is also operable to be used for optimizing the signal of interest.

In wireless communication, a device may change, add, or handover between cells of network access for inter-cell mobility. This may include Layer 1 and / or Layer 2 (L1 / L2) signaling for a user equipment (UE) moving between cells in a network. There may be a configuration message that includes configurations for one or more Layer 1 (“L1”) or Layer 2 (“L2”) Triggered Mobility (“LTM”) candidate cells. A measurement report with L1 measurements for the LTM candidate cells is used for a cell switch command to indicate a target LTM candidate cell to trigger execution of a LTM cell switch to the target LTM candidate cell. The LTM cell switch is from a source cell to the target LTM candidate cell.

Resource allocation is provided for an integrated access and backhaul (IAB) network, such as a distributed unit (DU) of an IAB. Methods and systems for allocating resources include allocating a first cell-specific pattern of downlink-flexible-uplink (DL-F-UL) availability for one or more slots, allocating a second cell-specific pattern of DL-F-UL availability for the one or more slots. The IAB DU can signal one or more of the first and second cell-specific patterns to an other IAB DU. At least one of the first cell-specific pattern and the second cell-specific pattern defines a slot format different from a DL-F-UL format. Slot format configuration (e.g., semi-static or dynamic SFI) are provided to support space division multiplexing / spatial multiplexing (SDM).

According to the 5G portable WiFi signal enhancement method and system provided by the invention, surrounding environment data are collected through an environment sensing sensor, and a device placement scheme is optimized in combination with a deep learning algorithm, so that the signal coverage range is expanded; the strategy of dynamically adjusting the transmitting power, the signal frequency and the modulation mode can optimize the signal strength according to the environmental change; interference signals are analyzed through quantum calculation, null is formed through the beam forming technology, interference signal receiving is effectively restrained, and the signal strength in the target direction is enhanced. In combination with the Internet of Things technology, uploading equipment state data to an edge server in real time for big data analysis, and pushing a personalized signal enhancement scheme according to different user use environments; through precise placement guidance and a dynamic frequency band switching strategy, a user can enjoy smoother network connection in a use process, and good signal quality is ensured to be kept in a complex environment. According to the invention, not only can the signal quality of 5G portable WiFi be improved, but also more intelligent and personalized network experience can be provided for users.

A communication device that performs sidelink communication using an unlicensed band includes an acquisition unit that acquires information of a resource pool including one or a plurality of sidelink BWPs (Sidelink Bandwidth Parts) and a communication control unit that performs, based on the information of the resource pool, the sidelink communication using the unlicensed band. The one or the plurality of sidelink BWPs are set to correspond to one or a plurality of LBT bandwidths (Listen Before Talk Bandwidths).

The invention discloses a low-orbit satellite beam resource allocation method based on deep reinforcement learning, and the method comprises the steps: firstly building a satellite system model according to a low-orbit satellite system hopping beam scene, obtaining the communication traffic demand and geographic position of a ground user through a satellite traffic monitoring facility, and carrying out the preprocessing; secondly, carrying out user clustering on information of communication traffic demands of ground users, and dividing a ground cell into a hot spot area and a non-hot spot area; and then based on a satellite system model, establishing an optimization problem of multi-beam resource allocation and control, adopting a deep reinforcement learning method, dynamically adjusting a beam resource allocation strategy, allocating narrow beam resources to a hot spot area, and allocating wide beam resources to a non-hot spot area to realize system throughput maximization and user fairness. According to the method, the resource allocation problem in the low-orbit satellite hopping beam scene is effectively solved, and the throughput of a satellite system is improved while the user fairness is ensured.

The invention relates to a digital twinning dynamic deployment and migration optimization method based on vehicle-infrastructure collaborative awareness, and belongs to the technical field of Internet of Vehicles and digital twinning. The method comprises the following steps: constructing a digital twin network oriented to the Internet of Vehicles; a three-party utility model driven by heterogeneous sensing resources is constructed, and sensing quality, task completion time and node energy consumption are comprehensively considered; the sensing area overlapping degree of the vehicle and the road side unit is dynamically quantified, and the data acquisition redundancy rate is reduced in combination with a preset threshold value; a parallel pre-migration mechanism is designed according to the computing load, the storage capacity and the communication resource state of the edge server, and independent fragmentation transmission of the digital twin model is achieved through a multi-path concurrent transmission strategy; establishing a joint optimization model with maximized comprehensive utility; a multi-agent near-end strategy optimization algorithm is adopted to realize collaborative optimization of a digital twin deployment strategy, migration path selection and perception task distribution. According to the invention, the real-time performance and reliability of the digital twinning service in the Internet of Vehicles scene are improved.

The invention provides a low-orbit satellite resource allocation method and device based on beam and frequency domain collaborative optimization, and the method comprises the steps: dividing the overall bandwidth of a user region into a central sub-band and an edge sub-band through employing a dynamic soft frequency reuse scheme; all ground users are subjected to spatial clustering according to geographic positions and traffic demands, coverage cells are dynamically divided according to clustering results, and balanced service is achieved; on the basis of dynamic cell division, user clusters with high service volume are selected according to priorities, a beam activation set is generated, and a hopping beam matrix is updated; establishing a channel model between a user and a beam and a switching matrix between satellites; constructing a system utility target, and constructing a multi-target optimization problem model by taking the system utility target as a main part and integrating interference, switching overhead and delay penalty; and the multi-dimensional resource collaborative optimization framework based on deep reinforcement learning reconstructs a multi-objective optimization problem model, and outputs a solution of the multi-objective optimization problem model, including an optimal bandwidth and a power allocation result. According to the invention, resource allocation can be carried out on low-orbit satellites.

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 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 present application relates to devices and components including apparatus, systems, and methods to perform beam measurements and beam reporting. In an example, a beam measurement may exist and can be used to generate a predicted dwelling time of a UE in a beam of a base station. The dwelling time represents a time duration during which the beam is expected to have the best beam quality for the UE among the beams of the base station. Given the predicted dwelling time, the base station can send a reference signal to the UE, or the UE can perform a measurement on the reference signal and / or send information about this measurement to the base station. This information can be sent as a beam report.

Systems, methods, and apparatuses for providing optimization of network resources. The system is operable to monitor the electromagnetic environment, analyze the electromagnetic environment, and extract environmental awareness of the electromagnetic environment. The system extracts the environmental awareness of the electromagnetic environment by including customer goals. The system is operable to use the environmental awareness with the customer goals and / or user defined policies and rules to extract actionable information to help the customer optimize the network resources.

The invention relates to the technical field of Beidou positioning, and discloses a Beidou positioning inspection method and system. The method comprises the following steps: acquiring geographic information and equipment state parameters of an inspection area, and generating a structured task queue according to dimensions such as equipment types and fault levels; constructing a Beidou positioning dynamic model containing a position axis, a time axis and an environment factor axis; determining an initial inspection constraint condition according to the equipment type and the fault level, and performing path planning simulation to generate an initial inspection route; detecting a route anomaly, and adjusting an abnormal node by using a hybrid optimization algorithm to generate a stable route; model parameters are updated in combination with real-time environment data, and a final inspection instruction set containing information such as equipment moving time sequence is generated. The system comprises a data processing module, a model construction module, a constraint determination module, a path planning module, an anomaly detection module, an optimization adjustment module and the like. The inspection efficiency and precision are improved, the stability and reliability are enhanced, and the inspection requirements of complex environments can be effectively met.

The invention discloses a wireless communication anti-interference method and system based on data analysis, and belongs to the technical field of communication anti-interference, in the wireless communication anti-interference method and system based on data analysis, the active defense capability of the system to unknown interference is improved through virtual interference generation and physical suppression by linkage cooperation of a generative adversarial network and an adaptive beam forming algorithm. The generator continuously simulates a novel interference signal injection training environment, so that a beam forming algorithm learns in advance to form accurate null in an interference direction, and the response time when actual interference occurs is greatly shortened. Meanwhile, interference space features detected by the beam forming module in an actual scene reversely optimize a signal construction rule of the generator, and the matching degree of a generated sample and a real electromagnetic environment is enhanced. The dynamic mutual promotion mechanism not only enhances the timeliness of interference suppression, but also reduces the problems of signal quality fluctuation and excessive consumption of hardware resources caused by passive response in the traditional scheme.

Various embodiments herein relate to identifying an indication of a channel access priority class (CAPC); identifying, based on the CAPC and a table related to the CAPC, a length of a channel occupancy time (COT); and participating in a sidelink (SL) communication in the unlicensed spectrum based on the COT. Other embodiments may be described and / or claimed.

The invention discloses a broadcast type radio positioning system base station site selection analysis and evaluation method and system, and relates to the technical field of wireless positioning, and the method comprises the steps: building a radio ground base station deployment sample database and an elevation model database; based on a combined optimization strategy of a greedy algorithm and a genetic algorithm, selecting an optimal base station set covering a pre-working area from the database; constructing a three-dimensional evaluation system, and comprehensively evaluating the optimal base station set from three dimensions of deployment cost, system robustness and positioning precision; optimizing the base station set based on a digital twinning technology, wherein the optimization comprises multi-band signal emission modeling and machine learning recommendation of a historical case library; and dynamic presentation and parameter adjustment of a base station deployment effect are realized through a three-dimensional visual interface and an interactive sand table system. According to the method, a large-range working area can be well covered, the situation that a signal coverage blind area exists is avoided, then the working efficiency is improved, and flexible and efficient site selection evaluation on the radio ground base station in a local sudden battlefield can be achieved.

Systems, methods, and apparatuses for providing optimization of network resources. The system is operable to monitor the electromagnetic environment, analyze the electromagnetic environment, and extract environmental awareness of the electromagnetic environment. The system extracts the environmental awareness of the electromagnetic environment by including customer goals. The system is operable to use the environmental awareness with the customer goals and / or user defined policies and rules to extract actionable information to help the customer optimize the network resources.

The invention relates to the technical field of industrial Internet of Things, and discloses a low-delay industrial Internet of Things data transmission system based on a 5G network. The system comprises a plurality of functional modules such as a data acquisition module, a data preprocessing module, a network transmission optimization module and a congestion control module. The data acquisition module acquires a heterogeneous data set, the preprocessing module performs standardization processing, the network transmission optimization module selects an optimal channel and node, and the congestion control module predicts flow and adjusts a transmission strategy. In addition, the system also has the functions of security encryption, heterogeneous data synchronization, dynamic spectrum allocation and the like. Through cooperative work of the modules, the system realizes low-delay and high-reliability transmission of industrial Internet of Things data, effectively processes heterogeneous data, guarantees data security, improves spectrum utilization efficiency and energy efficiency, enhances fault tolerance and compatibility of the system, and is suitable for various industrial scenes.

The invention relates to a signal detection and accurate positioning method for a lift-off platform unmanned aerial vehicle, and the method comprises the steps: deploying an unmanned aerial vehicle-mounted platform, capturing a global electromagnetic signal in real time, outputting multichannel original signal data, carrying out the time-frequency domain joint analysis, extracting a frequency hopping period, a modulation mode and pseudo-random code features, and recognizing a target unmanned aerial vehicle signal. A control instruction link signal and an image transmission link signal are separated; the arrival time difference and the arrival phase difference of the target unmanned aerial vehicle signal are converted into a dynamic space coordinate system, a three-dimensional positioning equation set is constructed, and real-time space position coordinates of the target unmanned aerial vehicle are obtained through calculation; and extracting transmitting end characteristic parameters of control instruction link signals, constructing a control signal propagation path model in combination with the real-time position of the target unmanned aerial vehicle, and positioning geographic coordinates of an unmanned aerial vehicle control source by reversely tracking a signal transmitting direction and an attenuation law. The terrain shielding influence is effectively avoided, the target identification accuracy and positioning precision are improved, and the unmanned aerial vehicle control source traceability is realized.

This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for adapting a radar transmission based on a congestion level. A wireless device, such as a radar device, a UE, a base station, a vehicle, etc., may detect a congestion level of a wireless communication environment that includes the wireless device. The wireless device may have at least one of a first FOV or a first range within the wireless communication environment. The wireless device may transmit, based on the congestion level exceeding a threshold, a radar signal that corresponds to the wireless device having at least one of a second FOV or a second range in the wireless communication environment that is smaller than the at least one of the first FOV or the first range.

Aspects of the subject disclosure may include, for example, causing radio frequency (RF) signals to be transmitted via an antenna system in a plurality of directions, and responsive to transmission of the RF signals, monitoring signals that are received by the antenna system to detect an interference signal that originates from a passive intermodulation (PIM) source. Other embodiments are disclosed.

Systems, methods, and apparatuses for providing optimization of network resources. The system is operable to monitor the electromagnetic environment, analyze the electromagnetic environment, and extract environmental awareness of the electromagnetic environment. The system extracts the environmental awareness of the electromagnetic environment by including customer goals. The system is operable to use the environmental awareness with the customer goals and / or user defined policies and rules to extract actionable information to help the customer optimize the network resources.

Systems, methods, and apparatuses for providing optimization of network resources. The system is operable to monitor the electromagnetic environment, analyze the electromagnetic environment, and extract environmental awareness of the electromagnetic environment. The system extracts the environmental awareness of the electromagnetic environment by including customer goals. The system is operable to use the environmental awareness with the customer goals and / or user defined policies and rules to extract actionable information to help the customer optimize the network resources.