84 results about "Mobile antennas" patented technology

The invention discloses a high-speed rail tunnel communication sensing integrated information transmission method based on a movable antenna, and belongs to the technical field of wireless communication, and the method comprises the steps: constructing a high-speed rail tunnel communication sensing integrated system architecture assisted by the movable antenna for a high-speed rail tunnel scene, and designing an information transmission protocol; mathematical modeling is carried out according to movable antenna model features and tunnel scene channel features, a communication transmission model and a sensing transmission model are fused, and a communication and sensing integrated information transmission model is established. Aiming at the problems that the communication stability is limited and spectrum resources are deficient in a tunnel scene, a movable antenna and communication sensing integrated technology is adopted, dual-function coordination of base station communication and radar sensing in the tunnel is realized, and the spectrum utilization rate is improved and the total communication transmission rate of a train is maximized on the premise of meeting a sensing interference power threshold value.

The invention relates to the technical field of wireless communication technology, and provides a rate division multiple access communication method and system assisted by a movable antenna, and the method comprises the steps: firstly constructing a rate division multiple access communication model, the model comprises a base station equipped with a linear movable antenna array and a plurality of users, and the base station communicates with each user; in the model, a user is split into a plurality of clusters, and a beam forming vector corresponding to an inter-cluster public stream, a beam forming vector corresponding to an intra-cluster public stream and a beam forming vector corresponding to a user private stream are formed according to the split clusters; and constructing a maximized minimum user rate optimization model according to the rate segmentation multiple access communication model, disassembling the optimization model into three sub-models, and solving the three sub-models by using an iterative optimization algorithm based on internal and external double loops. According to the invention, through a two-layer rate segmentation multiple access mode, the mobile antenna is introduced to carry out channel reconstruction and the intra-cluster common stream is compensated, so that the maximization of the minimum user rate is realized, and the communication performance is improved.

The invention provides a method for assisting a movable antenna to realize secure communication by STAR-RIS, and relates to the technical field of wireless communication. According to the method, the safety and the rate of the system are maximized by jointly optimizing the beam forming of the base station, the position of the movable antenna and the STAR-RIS coefficient matrix. The method specifically comprises the following steps: constructing a downlink MIMO system and establishing a joint optimization problem; decomposing the joint optimization problem into three sub-problems by adopting an alternate optimization framework; respectively utilizing a particle swarm optimization algorithm and a weighted minimum mean square error method to be combined with a Majoritization-Minimalization algorithm to solve each sub-problem, and respectively utilizing the particle swarm optimization algorithm and the weighted minimum mean square error method to be combined with the Majoritization-Minimalization algorithm to solve each sub-problem; and alternately executing related steps until system security and rate convergence to obtain a solution of the joint optimization problem. By the adoption of the method, the safety communication performance of the system is remarkably improved, full-space coverage and precise beam regulation are achieved, the algorithm convergence is high, the solving efficiency is high, and the method is suitable for a downlink system with multiple users and multiple eavesdropping nodes.

The invention relates to a mobile antenna communication system robust resource optimization method based on angle information uncertainty, and belongs to the field of wireless communication. The method comprises the following steps: constructing a mobile antenna communication system model, and establishing a system energy efficiency maximization resource allocation model based on bounded angle information uncertainty by considering base station transmitting power constraint, user rate constraint, channel uncertainty constraint and mobile antenna spacing constraint; a non-convex original problem is equivalently converted into a convex subproblem about base station beam forming and movable antenna positioning by using transformation replacement, Bukbach, exponential conversion, continuous convex approximation, an S process, a subgradient inequality, singular value decomposition and a block coordinate descent method; and solving a plurality of convex sub-problems by using the CVX to obtain an optimal beam forming matrix and a movable antenna position vector, namely an optimal resource allocation strategy. The energy efficiency of the mobile antenna system can be effectively improved, and compared with a traditional method, the communication outage probability can be effectively reduced.

The invention belongs to the technical field of wireless communication physical layer secure transmission, and relates to an RIS-assisted mobile antenna security ISAC system and a joint scheduling optimization method, the RIS-assisted mobile antenna security ISAC system comprises a base station, an RIS, an eavesdropper and a plurality of legal users, the base station is used for sending signals to the legal users, a radar senses the eavesdropper, and the RIS is used for assisting secure communication; the base station is a dual-function base station MA-BS; the base station is provided with a transmitting array and a receiving array of movable antennas, and the legal user and the eavesdropper are provided with single antennas; no line-of-sight link exists between the base station and the legal user and between the eavesdroppers, the base station points the beam to the RIS through beam forming, and the RIS carries out phase modulation on the beam and then points the beam to the legal user and the eavesdroppers respectively; the beam pointing to the eavesdropper is reflected from the eavesdropper, is subjected to RIS phase modulation, and is returned to the base station for sensing the position of the eavesdropper; according to the system disclosed by the invention, the safety communication performance between the base station and the user in different scenes is ensured by utilizing the high spatial freedom degree of the movable antenna.

The invention provides a cooperative interference processing method for a movable antenna enabling and inductance integrated network. The method comprises the following steps: constructing an optimization problem under the movable antenna enabling and inductance integrated network; wherein the optimization problem is that the sum of the data rates of all the cells is maximized by alternately iteratively optimizing the transmitting beam forming of all the base stations and the position of the movable antenna, and the rate profile technology is utilized to depict the Pareto boundary between the data rates of the cells; decomposing two optimization sub-problems based on the optimization problem, and carrying out alternate iteration solution on the two optimization sub-problems until a total objective function of the optimization problem is converged; the first optimization sub-problem is used for optimizing transmitting beam forming of the base station under the condition that the positions of all the movable antennas are determined, and the second optimization sub-problem is used for optimizing the positions of the movable antennas under the condition that the transmitting beam forming of the base station is determined. According to the invention, the sum of data rates of all cells is maximized through transmitting beam forming and antenna position regulation and control, and the communication and sensing performance is improved.

The invention provides a communication coverage enhancement system based on cooperation of a movable antenna and an intelligent metasurface and an optimization method. The communication coverage enhancement system comprises a base station, a plurality of RIS systems and a plurality of target areas. The base station is equipped with an MA system for flexibly controlling the position of a transmitting antenna and executing active beam forming; the plurality of RIS systems are used for executing passive beamforming so as to cooperatively improve the communication performance of the MA system; in the embodiment of the invention, communication service is only provided for one target area at any moment, and the plurality of target areas are covered in sequence according to a polling sequence or a preset sequence, so that efficient resource scheduling and dynamic communication guarantee for each target area are realized. The adaptive capacity of the system to channel space characteristics is remarkably improved, and stable and reliable communication guarantee can be achieved even in a channel deep fading scene.

The invention discloses a 6DMA-assisted high-speed railway communication resource collaborative optimization method based on reinforcement learning, and belongs to the technical field of high-speed railway movable antenna communication resource scheduling. The 6DMA-assisted high-speed railway communication resource collaborative optimization method comprises the main steps of constructing a system model, designing a joint optimization problem, solving the joint optimization problem and the like. According to the invention, through a six-degree-of-freedom reconstruction radiation mode, compared with traditional MA / FAs, the spatial degree of freedom is further released, and blind area formation and double near-far effect can be significantly reduced; meanwhile, static precoding and step-by-step search are replaced by an active-passive beam + array surface motion linkage decision through the TTD3, end-to-end control is achieved, and the time delay requirement of the high-speed rail is met; in addition, the collaborative optimization mechanism gives consideration to exploration efficiency and convergence stability, so that the system can keep a link reliable, and the method has relatively high practical application value.

The invention discloses a covert communication method and system assisted by a movable antenna in a communication-inductance integrated network, and the system comprises an ISAC base station which is provided with Nt movable transmitting antennas and Nr fixed receiving antenna arrays; k communication nodes, each of which is configured with a single antenna and is used for receiving a communication signal sent by the ISAC base station; the point-like sensing nodes are used for receiving the sensing signals sent by the ISAC base station; the eavesdropping node is provided with a single antenna and is used for trying to detect a signal sent by the ISAC base station; according to the invention, the movable antenna array is deployed in the covert communication system, so that the space coverage limitation of a traditional fixed antenna system can be broken through, and the wide-area coverage and deep penetration capabilities of communication services can be improved. The mobile antenna array network significantly enhances the transmission efficiency and link robustness of covert communication through multi-dimensional degree-of-freedom cooperative regulation and control such as precoding vector optimization, three-dimensional space position dynamic configuration and the like.

The embodiment of the invention provides a signal transmission method and device of a movable antenna array and electronic equipment, and belongs to the technical field of antenna communication. The method comprises the following steps: determining a plurality of monitoring parties and at least two target receiving ends; one target receiving end is in a near-field communication scene, and the other target receiving end is in a far-field communication scene; constructing a communication model based on the movable antenna array, the plurality of monitoring parties and the target receiving end; performing reachable rate analysis and concealment analysis based on the communication model to obtain reachable rate related data and concealment related data, and then constructing a target optimization problem; the position of each movable sub-array of the movable antenna array is adjusted, power distribution of the movable antenna array is adjusted, a target optimization problem is processed, target optimization information is obtained, and therefore signal transmission operation of the movable antenna array is adjusted. According to the embodiment of the invention, joint optimization of the covert communication rate and the concealment can be realized under the condition of a mixed field domain channel.

This invention discloses a communication energy efficiency optimization method assisted by a smart metasurface and a movable antenna. This method is applicable to a downlink wireless communication system consisting of a base station, a smart metasurface, and a user terminal equipped with a movable antenna. To improve the energy efficiency of this communication system, this invention proposes a joint optimization method for base station beamforming, RIS reflection coefficient, and MA spatial location. Specifically, considering the energy consumption of base station transmission signals and MA movement, the proposed method constructs a communication system energy efficiency maximization problem under constraints of user communication service quality and MA movement range, and designs an alternating optimization algorithm based on continuous convex approximation. Simulation results show that, compared with traditional fixed antenna schemes and system throughput maximization schemes, the proposed scheme can effectively improve the system's energy efficiency.

The application discloses a kind of wideband signal-oriented distributed movable antenna layout optimization method, comprising: based on swarm intelligence algorithm, antenna layout scheme is iteratively optimized until reaching iteration stop condition, the best fitness of population corresponding antenna layout scheme is regarded as the optimal scheme of antenna layout output;Wherein, the fitness of population is determined according to the wideband cumulative Cramer-Rao bound of its corresponding antenna layout scheme.The present application can directly construct the bottom mapping relationship between continuous position variable and wideband signal direction finding error lower limit by introducing wideband Cramer-Rao bound as fitness function.Because the index itself represents the theoretical minimum direction finding error of antenna layout, it can accurately quantify the spatial spectrum coupling effect of full frequency band;As fitness function, it can make the optimization directly towards the most essential optimization goal, ensure that the output physical array theoretically approximates the wideband direction finding physical limit under this degree of freedom.

A system is disclosed and comprises a mobile platform, an antenna configured to receive a signal from a remote source in a first direction, a movement mechanism mounted to the platform, wherein the antenna is mounted to the movement mechanism, the movement mechanism being configured to move the antenna relative to the platform, and a controller configured to: generate a local signal, determine a component of motion of the antenna in the first direction, correlate the local signal with the received signal to provide a correlation signal, and motion compensating at least one of the local signal, the signal from the remote source, and the correlation signal based on the determined motion of the antenna in the first direction.

The invention particularly relates to an unmanned aerial vehicle covert communication resource optimization method for flexible position antenna enabling. The method comprises the following steps: constructing a joint optimization problem of transmitting beam forming, an unmanned aerial vehicle track and a movable antenna position; a joint optimization problem of transmitting beam forming, an unmanned aerial vehicle track and a movable antenna position is decomposed into three sub-optimization problems, and the three sub-optimization problems include that the transmitting beam forming of the unmanned aerial vehicle is optimized by fixing the unmanned aerial vehicle track and the movable antenna position; the trajectory of the unmanned aerial vehicle is optimized by fixing the transmitting beam forming of the unmanned aerial vehicle and moving the position of the antenna; the position of the movable antenna is optimized by fixing transmitting beam forming of the unmanned aerial vehicle and the track of the unmanned aerial vehicle; and solving the three sub-optimization problems by adopting an alternating optimization algorithm to realize the solving of the joint optimization problem of the transmitted beam forming, the unmanned aerial vehicle track and the movable antenna position. The method provided by the invention has better effectiveness, wider universality and better covert communication performance.

The invention discloses an MA-assisted RSMA-RIS system neutralization rate optimization method, and the method comprises the steps: firstly giving an algorithm for updating the position of a mobile antenna (MA), and then giving an algorithm for obtaining the optimal sum rate of a system based on AO iteration. According to the method, the problems of precoding design, antenna position, RIS reflection matrix design and public rate segmentation scheme design of the multi-user downlink RSMA-RIS system under MA assistance can be solved, the optimal solutions of the system and the rate are obtained through iteration, and the optimal solutions can be rapidly converged.

The application discloses a kind of movable antenna cooperation NOMA's user downlink system optimization method and system, belong to wireless communication technical field.Its method includes: obtaining the position of user movable antenna and the receiving path of user to base station link;Calculate the channel gain between user and base station;Calculate the signal-to-noise ratio of user, calculate the mobile energy consumption of user movable antenna;According to the mobile energy consumption of user movable antenna and the transmission power allocated to user, the objective function of system total energy consumption model is constructed, according to the signal-to-noise ratio of user, user mobile area, the channel gain order between user and base station, the transmission power order allocated to user, the constraint of system energy consumption model is constructed;System total energy consumption model is converted into convex optimization problem, and the transmission power allocated to user after optimization and the position of user movable antenna after optimization are obtained.The application can realize the performance improvement of system, and solve the complexity brought by optimization problem simultaneously.

The application provides a movable antenna array pattern synthesis method based on an improved fish eagle optimization algorithm, converts antenna positions and antenna weights into a joint variable vector, improves an update strategy on the basis of an original fish eagle optimization algorithm, introduces global search exploration based on levy flight in a first stage, and adds an adaptive probability mechanism to dynamically guide a search scheme for selecting between a global optimal value and a same-generation optimal value to strengthen exploration diversity, adopts Gaussian disturbance in a second stage to perform local fine exploration and dynamically attenuate an update step to further optimize a solution in the first stage, prevent premature convergence, and be applied to a pattern synthesis problem in a movable antenna array, consider engineering practical constraints such as a minimum spacing between antenna arrays and a maximum aperture range, and can effectively realize target enhancement, interference suppression and various practical application scenarios such as a shaped beam.

An antenna assembly includes a lens, a guide rail, an antenna array, and a phase shifter. The lens has a first refractive surface. The guide rail is a linear guide rail and is located on one side of the first refractive surface of the lens. The antenna array includes a plurality of radiating elements. The antenna array is slidingly connected to the guide rail. As the antenna array moves on the guide rail, a beam pointing direction of the antenna assembly moves in an extension direction of the guide rail, to perform mechanical beam sweeping within a first sweeping range in the extension direction of the guide rail. The phase shifter is connected to the plurality of radiating elements and is configured to adjust feed phases of the plurality of radiating elements, to perform phase modulation sweeping within a second sweeping range.

An embodiment of the present application provides a method for optimizing a non-orthogonal multiple access communication system based on a movable antenna, which is applied to a computer device. The method creates a channel model of the movable antenna communication system, creates a decoding strategy, calculates the minimum reachable rate from the base station to multiple user terminals through the decoding strategy, creates an optimization model for the minimum reachable rate, and splits the optimization problem of the minimum reachable rate into multiple sub-problems. The precoding matrix of the base station, the decoding indicator matrix, and the position vector of the movable antenna are optimized respectively. In an inner loop, the precoding matrix and the decoding indicator matrix of the base station are optimized through an alternating optimization algorithm. In an outer loop, the position vector of the movable antenna is optimized through an improved Hippo algorithm. The cyclic optimization of the sub-problems is realized through the inner and outer double loops. The optimized decoding indicator matrix, the precoding matrix of the base station, and the position vector of the movable antenna are obtained, the performance of the movable antenna communication system is optimized, and the minimum reachable rate between users is improved.

In some implementations, a user equipment (UE) may transmit communication state information for multiple antenna panels of the UE, wherein the multiple antenna panels are mechanically displaceable relative to each other, and wherein the communication state information is based on relative mechanical displacements between the multiple antenna panels. The UE may communicate, via at least one antenna panel of the multiple antenna panels, one or more signals in accordance with the communication state information.

The antenna driving mechanism is provided with: an antenna shaft that supports the rotating antenna; a motor shaft that can rotate integrally with the antenna shaft and is rotationally driven in a first rotational direction or a second rotational direction; and a first rotation restricting portion and a second rotation restricting portion, the antenna shaft relatively moving in the axial direction from a first position where the rotation restriction is received to a second position where the rotation restriction is released in response to rotation of the motor shaft in the first rotation direction in a state where the antenna shaft is subjected to the rotation restriction by the first rotation restricting portion. The antenna shaft relatively moves in the axial direction from a second position where the rotation restriction is received to a first position where the rotation restriction is released in response to the rotation of the motor shaft in the second rotation direction in a state where the rotation restriction by the second rotation restriction portion is received.

The invention provides a gain phase error calibration DOA (direction of arrival) estimation method for a movable antenna array, and aims to optimize local gain and phase error problems caused by calibration errors in an actual system. On the basis of a two-stage structure, firstly, a rotation-invariant signal subspace is constructed, an estimation problem of a gain phase error is converted into a constrained least square problem, a closed-form solution is obtained by using a Lagrangian multiplier method, and joint estimation and compensation of the error are realized. And then, in the second stage, constructing a noise reduction covariance matrix and introducing an estimated gain phase error for compensation, and finishing high-precision direction-of-arrival estimation in combination with a MUSIC algorithm. A simulation experiment shows that compared with an existing method, the self-calibration method provided by the invention shows more excellent direction of arrival estimation performance in a movable antenna array. The method does not need extra error distribution priori knowledge, has good practicability, and is suitable for application scenes needing accurate DOA estimation, such as wireless sensing and radar.

The invention relates to a mobile antenna beam forming method and a wireless data energy integration system, and the method comprises the steps: building a large-scale fading channel model, and obtaining a data transmission rate expression and an energy signal power expression; linear precoding transmission is adopted at a base station, and a channel vector matrix from all positions of a movable antenna to all users is defined to obtain a constraint condition; constructing an optimization problem taking the energy signal power as a main target and taking the data transmission rate as a secondary target, and decomposing the optimization problem through a Pareto epsilon-constraint method to obtain a solvable single-target optimization problem; and through a generalized Benders decomposition algorithm and an alternating optimization algorithm, carrying out splitting solution on the solvable single-target optimization problem, and carrying out iterative convergence to obtain a final optimization result. According to the technical scheme provided by the invention, the transmission signal-to-noise ratio and the energy efficiency can be improved through the optimization of the movable antenna and the design of beam forming, and the flexible balance of data-energy cooperative transmission and the optimal design of system parameters are realized.

The invention relates to a perception auxiliary safety communication method of a movable antenna auxiliary safety communication system, and belongs to the field of wireless communication. The method comprises the following steps: in an eavesdropper sensing stage, a base station adjusts the positions of a transmitting movable antenna and a receiving movable antenna, transmits L sensing beams and collects all echo signals to obtain an estimated value of a space arrival angle of an eavesdropper; in the secure communication stage, the range of the eavesdropper is obtained based on the sensing stage, a robust beam forming vector transmitted by a base station is designed, and the transmission security rate of a legal user and the eavesdropping rate of the eavesdropper are determined; establishing a two-stage joint optimization problem to maximize the transmission security rate of the legal user under the worst condition and meet the joint optimization problem of perception constraint; and solving the established joint optimization problem to realize safe communication of the legal users. According to the invention, the joint optimization of the position of the movable antenna and the safe beamforming is realized, and the safety and robustness of the perception auxiliary communication system are improved.

The invention discloses an active tracking and covering method based on a channel knowledge map in a mobile antenna system, which aims to maximize the total spectrum efficiency in a service period by expressing an active tracking and covering task of mobile user equipment as a long-term trajectory optimization problem of a mobile antenna. Accurately modeling a dependency relationship of a channel on each surface freedom degree of the antenna by using a control parameter obtained based on a Rodrigues rotation matrix; key physical feasibility constraint conditions are systematically integrated, so that the feasibility of an optimization result in engineering is ensured; a channel knowledge map is introduced to realize proactive planning, and traditional reactive control is converted into active planning by utilizing prediction information, so that performance loss caused by channel information lag is reduced; on the basis of a manifold optimization framework, rotation parameters of the movable antenna system are mapped to a special orthogonal group manifold for optimization, rotation constraints are processed through Lie group operation, and singularity and calculation redundancy caused by traditional parameterization are avoided.

The invention discloses a sum rate optimization method of an MA and RIS combined auxiliary NOMA uplink transmission system, which is suitable for an uplink transmission system consisting of a multi-antenna base station, an RIS and two communication users, and each communication user is provided with a single movable antenna. In order to effectively improve the transmission capability of the proposed system, the invention provides a sum rate optimization method of an MA and RIS combined auxiliary NOMA uplink transmission system. Specifically, the sum rate of the NOMA uplink transmission system is maximized by jointly optimizing a base station to receive a beam forming vector, an RIS phase shift matrix and an MA position. For the provided complex non-convex problem, a positive semidefinite relaxation algorithm is utilized to optimize receiving beam forming and an RIS phase shift matrix of a base station, a continuous convex approximation algorithm is utilized to optimize an MA position, and alternate iteration is carried out until a convergence condition is met. A simulation result shows that compared with a traditional fixed position antenna and RIS combined auxiliary NOMA uplink transmission scheme, the scheme provided by the invention remarkably improves the sum rate of an NOMA uplink transmission system.

A deployable space antenna may include a housing and a first telescoping boom and a second telescoping boom extendable from the housing in opposite directions from a stowed position to a deployed position. Each of the first and second telescoping booms may include telescoping boom segments. Each of a plurality of deployable, steerable antennas is carried by respective telescoping boom segment and movable between a stowed position and a deployed position. An antenna controller is configured to steer the deployable, steerable antennas.

In some implementations, a user equipment (UE) may transmit communication state information for multiple antenna panels of the UE, wherein the multiple antenna panels are mechanically displaceable relative to each other, and wherein the communication state information is based on relative mechanical displacements between the multiple antenna panels. The UE may communicate, via at least one antenna panel of the multiple antenna panels, one or more signals in accordance with the communication state information.

To improve the accuracy of determining the location of wireless tags. [Solution] The communication device of the embodiment includes an antenna, a drive unit, a first acquisition unit, an input unit, and a second acquisition unit. The drive unit moves the position of the antenna. The first acquisition unit acquires tag data for each radio tag based on the radio waves of each radio tag received by the antenna at multiple positions on the antenna. The input unit inputs the tag data for each radio tag at multiple positions on the antenna to a trained model. Based on the input of the tag data for each radio tag to the trained model, the second acquisition unit acquires data from the trained model indicating whether each radio tag falls within a first range or a second range.