24 results about "Smart antenna" patented technology

Implementations of the present disclosure relate to a method implemented at a wireless device. In this method, the wireless device transmits first information related to the position, orientation and a part number of the antenna of the wireless device to an automatic frequency coordination (AFC) system, and the part number is related to the radiation pattern envelope (RPE) of the antenna. Then, the wireless device can receive second information related to the RF signal coverage of the antenna from the AFC system, wherein the RF signal coverage is determined by the AFC system based on the received first information and the transmitting power of the wireless device. Then, the wireless device can adjust at least one angle and / or transmitting power of the antenna based on the second information so that the RF signal coverage of the antenna does not overlap with the RF signal coverage of the adjacent antenna.

The present invention provides a real-time location tracking antenna configured to locate tags, the real-time location tracking antenna is a single locator switched lobe antenna for 2D positioning which at least comprises: at least three patch antenna elements in an antenna, means configured to set up at least three overlapping lobes in desired 2D FOV where the means is one of: i. one first controller including one phase shifter module ii. one second controller including one switching device. It is also disclosed a real-time location tracking antenna system for 3D positioning.

The application provides an active smart antenna, wherein a LAN amplification unit is in a distributed integrated structure; compared with a structure design of a distributed LAN amplification unit, the distributed integrated LAN amplification unit has simple wiring, good reliability, low cost, greatly shortened length of a radio frequency coaxial cable, reduced radio frequency loss, simple wiring, strong manufacturability, and low radio frequency heat loss, and does not need special heat dissipation devices, thereby facilitating product miniaturization and weight reduction of the active smart antenna; that is, the structure design of the distributed integrated LAN amplification unit in the application considers performance, reliability, manufacturability and cost of the active smart antenna.

The application discloses a kind of based on phased array antenna beam guidance method and system, belong to wireless communication and intelligent antenna control technical field.The method obtains array state information, terminal state information, pilot measurement information, environment perception information and historical guidance feedback information, constructs joint state vector;Based on the joint state vector, scene interaction graph is constructed, and interference risk representation quantity is obtained using graph neural network;Parallel rehearsal is carried out on candidate beam control action in digital twin environment, and link quality prediction result, beam mismatch risk prediction result and constraint feasibility prediction result are obtained;Target beam control action is generated using reinforcement learning guidance strategy model, and is corrected by safety constraint predictive control;According to the action after correction, phased array antenna forms target guidance beam, and according to real-time feedback, reinforcement learning guidance strategy model, graph neural network and digital twin environment parameters are updated online.The application can improve the accuracy, reliability, safety and self-adaptive ability of beam guidance in complex dynamic scene.

A smart antenna system is configured to generate an initial weight set from an indication of desired azimuth and elevation steering angle and from an indication of frequency, to generate a plurality of further weight sets from the initial weight set, the further weight sets each being for the same azimuth and elevation steering angle, and for the initial weight set and for each of the plurality of further weight sets, generating a respective quantised wight set and generating an indication of side lobe level for each respective quantised weight set. A weight set is selected from the generated quantised weight sets for application to an antenna array on the basis of the indications of side lobe level.

This invention discloses a smart antenna array structure based on integrated power supply, control, and communication, comprising: a radio frequency (RF) power divider network; the RF power divider network divides the RF signal into multiple paths, feeding each RF signal into a coupler, which further divides the RF signal according to the coupling coefficient; the output of the coupler outputs a first RF signal, which is fed into the antenna link; the coupling end of the coupler outputs a second RF signal, which is fed into a passive on-chip system. In terms of power supply, the antenna utilizes the rectified RF signal to power the low-power antenna link; in terms of control, it uses a communication protocol to network-control the RF unit, completing functions such as beam control and shaping; in terms of communication, it implements a communication protocol and integrates communication sensing.

The utility model relates to the field of television station engineering, and discloses a radio and television engineering intelligent antenna supporting structure which comprises a base, the top end of the base is fixedly connected with a supporting round block, the inside of the supporting round block is fixedly connected with a stretching mechanism, and the top of the base is fixedly connected with a buffering mechanism. The stretching mechanism comprises a motor, the exterior of the motor is fixedly connected to the interior of the supporting round block, the driving end of the motor is fixedly connected with a guiding round plate, a round plate is fixedly connected to the inner wall of the bottom of the base, long-strip-shaped grooves are formed in the four corners of the top of the round plate, and sliding plates are slidably connected to the inner walls of the long-strip-shaped grooves. According to the utility model, by connecting the expansion board, the supporting effect of the expansion board on the whole structure is further enhanced. The cross-shaped sliding groove provides a sliding track for the sliding block, it is guaranteed that the expansion board is effectively supported in the sliding process, and therefore the stability of the antenna supporting structure in the long-term using process is guaranteed.

The invention relates to the technical field of mobile communication, and discloses a beam switching device and an antenna. The beam switching device comprises a supporting medium and a metasurface structure. The supporting medium is used for being movably arranged above the antenna array. The metasurface structure is connected with the supporting medium, and the supporting medium can drive the metasurface structure to move to the position opposite to the antenna array in the vertical direction or the position completely staggered from the antenna array in the vertical direction. According to the beam switching device and the antenna, the antenna array can be switched among various beams in a mode that the supporting medium drives the metasurface structure to move and adjust the position, so that the beam switching device and the antenna can adapt to different service scenes. Moreover, compared with a multi-beam antenna and an intelligent antenna, the antenna array only comprises one column of radiation units to achieve the effect of variable beams, and does not need to configure two or more columns of radiation units to change the beams, so that the product is small in size and lower in cost.

This application discloses an adaptive smart antenna, a distributed remote radio unit (RRU), and a wireless communication system, relating to the field of antenna technology. It can expand the overlap area between RRUs, improving capacity and data transmission rate while ensuring a certain backward coverage area of ​​the RRUs, thereby enhancing the user experience at the edge. In this application, the RRU controls multiple diodes in the directional unit according to control signals from the baseband unit (BBU) to control the coupling state of the directional unit, flexibly switching the RRU antenna beams and selecting the optimal beam combination. This includes a combination of omnidirectional radiation patterns and directional radiation patterns that meet a preset range, expanding the overlap area between RRUs, improving capacity and data transmission rate while ensuring a certain backward coverage area of ​​the RRUs, thus enhancing the user experience at the edge.

Techniques are described for an antenna (e.g., an over the air (OTA) antenna) to be intelligently configured so as to adjust itself according to dynamic parameters, such as weather changes. Mechanisms are described that enable the end user to set preferences data (e.g., preferred channels) so that the OTA antenna automatically adjusts its placement to satisfy these preferences (e.g., to catch some preferred channels and with the highest quality available). Also described are techniques that include artificial intelligence (AI) and / or machine learning (ML) for learning the end user's patterns (e.g., patterns of viewership) and, subsequently, automatically adjusting the OTA antenna's position in accordance with the learned patterns. For example, the system may steer the OTA antenna to catch the best signal strength of a favorite channel of an end user, so that the end user can watch that channel with the highest quality, without any hassles, and at any time.

The application discloses a compact high-gain passive multi-frequency intelligent fusion antenna array layout, in which FDD multi-frequency antenna array and TDD intelligent antenna array adopt an up-down layout, and through a dual-frequency combiner and an ultra-wide frequency dipole, the FDD multi-frequency array and the TDD intelligent antenna array share radiation units at the joint, so that the length of the antenna is shortened while the gain of the FDD multi-frequency array and the TDD intelligent antenna array is basically kept unchanged. The application can be used alone to shorten the length of the fusion antenna and improve the gain, and can also be combined with other methods to further shorten the length of the antenna or improve the gain of the FDD multi-frequency array and the TDD intelligent antenna array.

The invention discloses a sparse antenna array synthesis method based on kernel density estimation, which belongs to the technical field of intelligent antenna design, is used for sparse antenna array synthesis, and comprises the following steps: based on a sparse antenna array, obtaining an active unit directional diagram under different array element position distribution through full-wave electromagnetic simulation to form an initial data set; modeling distribution of active unit directional diagrams in the initial data set by using a kernel density estimation method, and setting a threshold value to divide the training data set into a sparse subset and a dense subset; the method comprises the following steps: constructing two sub-networks with completely consistent structures, training based on a sparse subset and a dense subset, and setting different weight loss functions; the method identifies and focuses on the data sparse region through kernel density estimation, and effectively improves the fitting ability and prediction generalization performance of the model in the data sparse region in combination with weighted loss and curriculum learning, so that the training process is more stable and better in convergence.

This invention discloses a multimodal terminal antenna intelligent scheduling system, method, and terminal with AI scene recognition. The system includes: a multimodal perception module for collecting perception data from four layers: radio frequency, attitude, application, and positioning; an AI scene recognition module for identifying the current scene of the terminal through an AI model; an intelligent antenna scheduling engine for calling preset antenna scheduling strategies according to the scene; and an antenna hardware execution layer for executing the strategy and configuring radio frequency hardware. The method integrates multi-dimensional information to enable the terminal to "understand" that it is in a specific scene such as a call, game, or weak field, and dynamically matches the optimal antenna configuration. For example, it avoids obstructed antennas during calls, switches to unobstructed antennas and tunes in real time during games, and enables high-gain antennas and uplink beam pre-switching in weak fields. This invention solves the problems of slow response, mis-switching, and inability to deeply optimize traditional antenna scheduling that relies solely on signal strength switching, and achieves adaptive improvement of terminal antenna performance and energy efficiency.

A single-feed smart antenna includes an antenna board with several antennas embedded within it, forming an overlapping area between adjacent antennas. A controller is fixed externally to the antenna board, with an antenna interface on one side electrically connected to each of the antennas and a reader / writer interface on the other side. Several antenna slots are formed within the antenna board's identification plane, and antennas are installed within these slots, forming a common area between adjacent slots, which are interconnected. The shape of the antenna slots matches the antenna structure, being rectangular in shape but not forming a closed loop. Several PCB board slots are formed within the antenna board, each located within the rectangular plane enclosed by the antenna slots, with both ends of each antenna slot opening into the PCB board slot. PCB boards are installed within the PCB board slots, and the two ends of each antenna are connected to the corresponding PCB board. This invention has the advantage of eliminating antenna identification blind spots.

The application relates to the technical field of mobile communication, and discloses a beam switching device and an antenna. The beam switching device comprises a support medium and a metasurface structure. The support medium is arranged above an antenna array in a movable manner. The metasurface structure is connected with the support medium, and the support medium can drive the metasurface structure to move to a position opposite to the antenna array in a vertical direction or a completely staggered position. The beam switching device and the antenna can switch the antenna array between multiple beams in the mode that the support medium drives the metasurface structure to move and adjust the position, thereby adapting to different service scenarios. Compared with a multi-beam antenna and a smart antenna, the antenna array only comprises one column of radiation units, and the effect of variable beams can be achieved, so that the product volume is small, and the cost is lower.

The invention discloses an intelligent antenna control method based on a microsystem, and the method comprises the steps: S1, setting system control parameters in the microsystem, generating a wave body, and distributing a discrete phase value and initial energy; s2, collecting and storing communication performance indexes of the antenna array; s3, calling an improved water wave optimization algorithm to execute phase optimization when the communication performance index declines and exceeds a threshold value or the silence time reaches a set threshold value; s4, discrete disturbance is carried out on the wave individuals, and communication performance indexes are calculated; s5, updating the phase according to the difference between the communication performance indexes before and after disturbance, performing rupture operation on the wave individuals with reduced performance, and dynamically adjusting the disturbance step length; s6, when the energy of the wave individual is lower than an energy threshold value, a phase vector is regenerated with the global optimal wave individual phase as the center, and energy is recovered; and S7, finally outputting a phase control signal to realize array adaptive adjustment. According to the invention, the antenna pattern control precision and the communication stability are improved.

An optimal arrangement for a configurable smart antenna in a wireless (e.g., Wi-Fi) network having zero, one, or more other mesh nodes is determined by characterizing the network performance for each possible arrangement by determining a number of connected devices (e.g., either client devices or mesh nodes) and one or more other performance parameters. If one arrangement has more connected devices than any other, then that arrangement is selected. If two or more arrangements have the same greatest number of connected devices, then one or more other performance parameters are applied either serially or in parallel to select the optimal arrangement. In some implementations, the other performance parameters are sums or averages for all connected devices. In other implementations, the other performance parameters are for only a selected priority device, where the selected arrangement must connect to the priority device.

The application discloses an intelligent antenna array control method, system, device and storage medium, relates to the technical field of communication, and aims to solve the problems of insufficient beamforming precision and low energy consumption ratio of a traditional antenna array. The method comprises the following steps: collecting multi-dimensional parameters of a communication environment in real time and generating a dynamic data set, wherein the dynamic data set comprises a user distribution heat map, a channel interference matrix and a multipath characteristic vector; obtaining a regulation and control instruction set of the phase and amplitude of each antenna unit in the antenna array based on the dynamic data set and preset beam adjustment parameters; calling a beam template library to generate a radiation pattern control signal based on the regulation and control instruction set and current scene characteristics, wherein the current scene characteristics comprise a geographical environment type and a user distribution density, and the radiation pattern control signal is used for indicating the adjustment of a radiation power level.

The utility model relates to an intelligent antenna electronic bridging device and a guarantee system, which are applied to a guarantee device of a mobile machine tool and are used for receiving verification information from a mobile device in a near field communication range. The intelligent antenna electronic bridging device comprises a near field communication tag and a microprocessor. The near field communication tag is provided with an induction coil antenna and a memory, and the induction coil antenna is used for inducing with the mobile device to generate induction current to be started, receiving verification information, writing the verification information into the memory, generating a notification signal and sending out the notification signal. The microprocessor is actuated by the induced current, accesses the verification information in the memory after receiving the notification signal, encrypts the verification information, and transmits the encrypted verification information to the assurance device. Through the passive near field communication tag and the memory in the tag, the functions of energy conservation and instant transmission can be achieved.

The invention relates to the technical field of intelligent antenna arrays, in particular to a self-adaptive intelligent antenna system based on deep learning, which marks and converts a super-threshold array element pair into an adjacency relation through a screening mode of combining an array element amplitude difference and a phase difference with a space coordinate distance, and utilizes a multi-layer iterative combined topological structure to obtain a super-threshold array element pair. The method comprises the following steps: selecting a set with relatively low difference through successive iteration until a stable condition is reached, thereby obtaining a weighting parameter with relatively high convergence, differentiating a main signal vector and a residual vector term by term and comparing with a threshold value, realizing systematic compression of interference components in a signal, and realizing the systematic compression of the interference components in the signal through a signal time expansion stage. The multi-dimensional matrix structure bears frequency components and extracts trend factors, a factor sequence is combined with weighting parameters after extending in a time dimension, a parameter set capable of expressing dynamic evolution of a channel is generated, and a result has higher anti-interference performance and better dynamic tracking performance.

The application discloses a design method and system of a wireless energy transmission high-power focusing transmitting antenna, and belongs to the technical field of wireless energy transmission and intelligent antenna design. The method obtains a target energy transmission area, a working frequency, an energy transmission distance, a transmitting power boundary, a safety radiation limit and a manufacturing constraint, and represents a to-be-designed transmitting antenna as an antenna graph topology containing an array element, a feed, a matching and a heat dissipation relationship; a graph conditional diffusion model and a joint prediction model are trained based on multi-fidelity electromagnetic simulation data, thermal simulation data and prototype test data, a candidate antenna graph topology is generated, and constraint correction is performed according to focusing performance, sidelobe leakage, temperature rise distribution, mismatch loss and safety risk; then, electromagnetic, thermal and matching checking are performed, the model is updated in feedback, and a transmitting antenna design result meeting focusing energy transmission performance, thermal stability, safety and manufacturing constraints is output.

Multi-antenna transmission method for providing downlink radio coverage from a radio base station to a mobile terminal in a mobile communications network by means of a transmission system, comprising: - at least one multi-radiator transmitting antenna directed towards at least one mobile device, in particular a smart antenna or an array antenna, - at least one database that is associated with at least one coverage cell of the mobile communications network and contains information about the position of the mobile device; - Method means that interact with the at least one multi-radiator transmission antenna and the at least one database, wherein the method means are configured to connect a transmission direction with the position of the mobile device, wherein the transmission direction is suitable for reaching the mobile device, comprise the steps: a) Detecting the position of the mobile device; b) Storing the position in at least one database; c) Determining at least one transmission direction of at least one transmission beam from the at least one multiple-radiator transmission antenna to the mobile device, depending on the position stored in the at least one database, wherein at least one of the transmission parameters, which must be determined in order to transmit in the transmission direction in the at least one multiple-radiator transmission antenna, is linked to the stored position of the mobile device, and d) Comparing reception quality information signaled by the mobile device with the reception quality expected for the position achieved by the mobile device and stored in the database.

The application discloses an adaptive anti-interference beam forming method based on pre-processing deep reinforcement learning and belongs to the technical field of navigation, comprising the following steps: constructing a GPS terminal signal model, including a 2*2 dual-polarized antenna array, a control variable, a time-varying gain interference variable and Gaussian noise; constructing a deep learning convolutional neural network CNN, including a data feature extraction network layer, a convolution network layer, a pooling layer, an activation function layer and a full link layer; performing reinforcement learning processing and decision implementation on the deep learning convolutional neural network to obtain a deep reinforcement learning Q network; and training the deep reinforcement learning Q network to obtain a trained deep reinforcement learning convolutional neural network. The application controls array signals by beams, realizes beam main lobe positioning and simultaneously traps interference signals by side lobe, learns interference data features by the deep Q network to automatically determine the next execution action, and does not need human intervention, thereby greatly improving the autonomy of the intelligent antenna.