95 results about "MIMO" patented technology

Embodiments of the present disclosure are related an open radio access network (ORAN) based base station (BS). The BS comprising at least one radio unit (RU) comprising a plurality of antenna ports, at least one distributed unit (DU) and an interface for a communication between said RU and said DU. The RU is configured to support one or more virtual sub-sectors simultaneously, wherein each virtual sub-sector cover a pre-defined geographical area in both horizontal and vertical directions. Each virtual sub-sector is associated with a specific set of antenna ports of the RU. Each virtual sub-sector provides a coverage for one of distinct geographical areas and partially overlapping geographical areas. The DU associates a UE with a virtual sub-sector. The DU performs at least one of a SU-MIMO within a virtual sub-sector for a UE associated with said virtual sub-sector, and a MU-MIMO across the UEs in different virtual sub-sectors.

The application provides a hybrid user unlicensed random access method in a cell-free massive MIMO, comprising the following steps: deploying a cell-free massive MIMO system and calculating an optimal backoff parameter; after obtaining the optimal backoff parameter, an access point broadcasts the optimal backoff parameter to all users; the users randomly activate according to the optimal backoff parameter broadcast by the access point; the users successfully activated randomly select a pilot from a predefined pilot pool and send the pilot to the access point; the access point judges whether the signal-to-interference ratio of the user with the maximum signal strength among the users selecting the same pilot is greater than a threshold value; if yes, the access point identifies the user with the maximum signal strength and accesses the user; otherwise, all the users in conflict are considered to have failed to access and wait for the next reinitiation of access. The application can significantly improve the problem of poor performance of edge users, improve the access efficiency of various types of users in an Internet of Things scene, has high feasibility and can be applied to an actual communication scene.

The application relates to the technical field of space optical communication, and discloses a MIMO optical transmission system for a cluster unmanned aerial vehicle and a method thereof, which comprises a flight control computer, a transmitting array, a receiving array and a baseband processing unit. The baseband processing unit acquires the three-dimensional position and attitude matrix of a transceiving node, carries out coordinate system transformation, screens out candidate transmitting arrays satisfying geometric alignment conditions, reconstructs an aerodynamic wake turbulence field in combination with a motor rotating speed parameter, carries out integral of refractive index disturbance along a path to eliminate arrays blocked by air flow, drives a flight control loop to perform attitude biasing when the effective array is limited, carries out channel optimization, then splits data into spatial mapping bits and light intensity modulation bits, selects a specific array to send optical pulses, and the receiving end uses a lens to carry out spatial isolation and focusing on incident light beams, and demodulates and restores data in reverse according to the photoelectric current characteristics. The application realizes feedforward avoidance of complex air flow interference and dynamic optimization of limited channels, reduces line transmission crosstalk, and guarantees communication quality.

The application discloses a kind of angle, distance and speed joint estimation method for MIMO-AFDM ISAC system, constructs single base MIMO-ISAC system based on AFDM, pilot and QPSK data are mapped to DAF domain by transmitting end, and ISAC waveform of adaptive high mobility is generated by IDAFT and CPP insertion;Establish echo three-dimensional DAF domain tensor model, after removing the chirp cycle prefix of echo signal by receiving end, execute discrete affine Fourier transform and fast Fourier transform processing;Data cube is projected in beam domain, time delay compensation and matching normalization are carried out, and parameter decoupling is realized;Three-dimensional power cube is constructed, and target detection is completed by 3D CA-CFAR detection, non-maximum suppression and secondary interpolation;Mapping target angle, distance, speed parameter, estimating complex reflection coefficient and output.The application can obtain lower angle, distance and speed estimation root mean square error under the condition of different receiving array aperture, different coherent processing time length and different target quantity.

The application relates to a room division covering system and method based on frequency shift MIMO technology, which comprises a signal source access layer, a frequency shift MIMO core processing layer and a distributed covering layer. The signal source access layer is used for acquiring multi-system signal sources; the frequency shift MIMO core processing layer is connected with the signal source access layer and the distributed covering layer respectively, is used for receiving the multi-system signal sources and the real-time feedback of channel parameters of indoor areas of the distributed covering layer, performing cooperative detection of channels and scenes, combining frequency shift MIMO technology to perform cooperative processing, and obtaining frequency shift-MIMO cooperative signals; and the distributed covering layer is used for receiving the frequency shift-MIMO cooperative signals, forming a radio frequency covering field based on frequency shift MIMO technology, accessing adaptive terminals, and collecting real-time channel parameters of indoor areas. Compared with the prior art, the application has the advantages of high covering rate and adaptive environmental change.

The application provides a channel estimation method and device of a MIMO system, electronic equipment and a storage medium, and relates to the technical field of wireless communication. The method comprises: inputting a quantized received signal of a receiving end of the MIMO system into a channel estimation model to obtain a predicted channel of the quantized received signal output by the channel estimation model; wherein the channel estimation model is used for denoising and correcting the quantized received signal to obtain a preprocessed quantized received signal; and iteratively calculating the predicted channel according to the preprocessed quantized received signal, an initial virtual angle basis matrix of a transmitting end, an initial virtual angle basis matrix of a receiving end, an initial residual error, an initial channel estimation value and an initial loss value. The application can effectively suppress nonlinear quantization distortion and improve the accuracy of channel estimation by iteratively solving the predicted channel. The statistical characteristics contained in the quantized received signal can be fully tapped by denoising and correcting the quantized received signal, and the quantization error can be eliminated.

This invention discloses a method and system for LEO satellite communication resource allocation based on dynamic weighted graph segmentation, relating to the field of satellite communication technology. Addressing the co-channel interference problem in large-scale MIMO satellite systems, this invention models the resource allocation optimization problem to maximize system sum rate as a partitioning optimization problem on a complete user graph. The weights of the edges in the graph are configured to represent the potential interference cost when two users reuse the same time-frequency resource. The optimization objective is to maximize the sum of edge weights between different partition groups. A dynamic weighted graph segmentation algorithm is employed, utilizing physical layer channel quality index feedback to introduce auxiliary weight variables. The edge weights of the graph are dynamically updated iteratively, and graph segmentation is performed until the algorithm converges. Finally, time-frequency resource allocation is completed based on the graph segmentation results. This invention can achieve near-optimal solution performance with low complexity and fast convergence speed, significantly improving the sum rate in highly dynamic satellite communication environments.

This invention belongs to the field of wireless communication technology and discloses a dual inverted "L" broadband low-coupling MIMO mobile phone antenna based on a parasitic grounded stub. This invention proposes a novel antenna structure. This design effectively solves the contradiction between broadband performance and high isolation while maintaining a simple and compact structure. The decoupling and broadband principle of this invention is as follows: an inverted L-shaped parasitic grounded stub with a bent end is introduced below the inner side of the radiating arm. This stub can generate a new coupling path, and the reverse current induced in it exactly cancels the coupling current received by the main radiating arm, achieving decoupling between ports. By slotting on the horizontal arm of the inverted L-shaped radiating stub, a new resonant point is generated in the antenna, effectively widening the antenna's operating bandwidth.

A gas well data processing method based on MIMO technology, belonging to the field of gas well development, includes: data acquisition and preprocessing; classification and processing of multiple gas well data; multiple gas well data retransmission mechanism; step S4: data interaction status verification and processing; using MIMO multi-antenna technology to achieve parallel reception and processing of multiple gas well data packets; data security verification and processing; classification and processing of gas well center control and management data; gas well command processing verification; and gas well data management. This invention effectively solves the problems of increased wellhead measures, large data volume, and limited transmission bandwidth in existing gas well data transmission, improving the transmission efficiency of gas well data and enhancing the management and operational efficiency of gas well production. Simultaneously, this invention combines wireless communication technology and the characteristics of multiple gas wells to design a scheme that enables refined management of gas wells, significantly improving the production capacity and economic benefits of gas wells.

This invention discloses a method, electronic device, and storage medium for ultra-large-scale MIMO synchronization, relating to the fields of wireless communication and channel measurement technology. The method includes: first, estimating the delay and direction parameters of at least one strong path as an anchor path based on reference subarray channel data; then, for each pair of adjacent subarrays, extracting the phase of the same path on the boundary elements based on the anchor path parameters, calculating the observed phase difference, and thus obtaining the observed value of the common phase drift between subarrays; next, fusing multiple observations to obtain a robust estimate of the common phase difference between adjacent subarrays; finally, accumulating the estimated values ​​of each segment with the first subarray as a reference to obtain the common phase drift of each subarray, performing phase compensation, and then stitching the data of each subarray according to coordinates into an equivalent ultra-large-scale array to achieve ultra-large-scale MIMO synchronization. Therefore, this invention can estimate and compensate for the common phase drift of subarrays without additional hardware time synchronization.

The application provides a near-field channel parameter estimation method considering spatial non-stationary characteristics, which comprises the following steps: obtaining a multipath parameter initial value by using a far-field SAGE algorithm; calculating propagation distances of array elements at a transmitting end and a receiving end to scattering points, constructing a near-field channel response, and performing refined estimation on angle and distance parameters, time delay parameters and complex gain parameters of the multipath. Correlation operation is performed on a current residual signal and the near-field channel response in a frequency domain to obtain an array element level correlation metric. Continuous spatial non-stationary coefficients with a value of 0 to 1 are updated based on the correlation metric, and weighting iteration is performed on residual construction and parameter updating until a stop criterion is met, and near-field geometric parameters, time delay parameters, complex gain parameters of each multipath and spatial non-stationary coefficients of both transmitting and receiving ends are output. The method solves the problem of inconsistent multipath visible domains under XL-MIMO arrays, can suppress the influence of invisible array elements on parameter estimation, and improves the estimation accuracy and stability of the SAGE algorithm under the condition of near-field spatial non-stationary channels.

The application discloses a new energy empowerment non-cell large-scale MIMO intelligent AP deployment method based on K-means and DDPG, which comprises the following steps: constructing an AP deployment optimization problem in a new energy empowerment scene, selecting a specified number of APs from all AP candidate positions in non-uniform distribution, cooperating with UEs in a service network, and realizing an optimization target of maximizing average power grid energy efficiency under the condition of battery energy storage; adopting a geographic-energy dual-dimensional clustering mechanism, clustering all AP candidate positions based on a K-means algorithm, and selecting multiple AP candidate positions with the highest statistical EH efficiency in each group to form a new AP candidate position set, so as to reduce the action dimension of a DDPG algorithm; and solving the AP deployment optimization problem based on the DDPG algorithm, wherein the action is designed as the selection state of the new AP candidate positions selected by the K-means algorithm. Results show that the proposed AP deployment method has great energy-saving advantages in the new energy empowerment non-cell large-scale MIMO scene with uneven traffic distribution.

This invention provides a dual-channel MIMO indoor distributed network system and a dual-channel signal transceiver method. In the downlink direction, a first RRU converts the signal transmitted by the BBU into a first radio frequency (RF) signal and a first intermediate frequency (IF) signal to generate a local oscillator (LOS) signal; it outputs power; a frequency combiner combines the signal and power supply into a first signal; an antenna separates the first signal; a power-powered active mixer converts the first IF signal into a second RF signal; a power amplifier amplifies the signal power; the first RF signal and the second RF signal are transmitted; in the uplink direction, a third RF signal and a fourth RF signal are received; a power-powered low-noise amplifier amplifies the signal, converting the third RF signal into a second IF signal; the signals are combined into a second signal; a frequency combiner separates the second signal; and the first RRU converts the signal into a baseband signal and transmits it to the BBU. The solution provided by this invention can reduce the construction cost of an indoor distributed network system.

Systems and methods are provided for providing explicit MU-MIMO pairing indicator. Methods include maintaining a profile of one or more wireless devices in a wireless network using MU-MIMO. Methods further include receiving an indicator from one or more access nodes identifying MU-MIMO pairing for one or more wireless devices. Methods further include adjusting one or more of beamforming, layer assignment or throughput of the wireless network.

Disclosed are a CF mMIMO-based SWIPT communication system and method. A specific embodiment of this technology may involve: generating an optimization problem P0 by optimizing a problem P0 that minimizes total transmission power energy on the basis of a linear programming method; generating, from the generated optimization problem P0, optimization problems P1, P2 that respectively minimize downlink transmission power and uplink transmission power including a nonlinear SINR; deriving uplink optimal transmission power and an optimal power division coefficient as a solution of the generated optimization problem P1; and converting an inequality constraint of the generated optimization problem P2 into an equation, and then deriving the downlink optimal transmission power as a solution of the optimization problem P2. Accordingly, the energy efficiency of a user terminal may be maximized while a QoS constraint condition is satisfied, and stable communication may be performed at lower power.

Apparatuses, methods, and systems for computing an EVM of a transmitter are disclosed. One apparatus includes a processor and a receiver that receives a multi-layer MIMO signal from a transmitter via a propagation channel. The processor measures the received multi-layer MIMO signal using an unbiased linear MMSE MIMO equalizer and computes an EVM of the transmitter, where the EVM of each transmission layer is computed as 100 times the square root of a mean square error of a layer estimate at an output of the unbiased linear MMSE MIMO equalizer.

The present disclosure relates to an active-passive antenna system for wireless telecommunication networks. The system integrates active and passive antenna elements into a single unit, with the active portion capable of selecting between different frequency bands and adjusting transmission power to mitigate thermal noise. Advanced components enable dynamic beamforming and MIMO functionality, while the passive portion provides consistent coverage at lower frequencies. The unitary radome design simplifies installation, reduces tower lease costs, and improves aesthetic integration. Computer processing components determine trigger events and modify the active portion's transmission profile, ensuring optimal performance and reliable connectivity across various deployment scenarios.

The present application relates to a kind of system for realizing large-scale MIMO transceiver phase calibration function, including MIMO transceiver, signal source and vector network analyzer, when the transmitting phase of MIMO transceiver is calibrated, the output end of signal source is connected with first port, and transmitting channel TX1-TXn of MIMO transceiver is connected to second port one by one;When the receiving phase of MIMO transceiver is calibrated, one-way output of two-way power divider is connected to first port, and other-way output is connected to receiving channel RX1-RXn of MIMO transceiver one by one.The present application also relates to a kind of method for realizing large-scale MIMO transceiver phase calibration processing, device, processor and storage medium.The system for realizing large-scale MIMO transceiver phase calibration function, method, device, processor and its computer readable storage medium of the present application solve that the phase error caused by large-scale MIMO system itself reference channel phase jitter is larger, and the reliability problem of phase calibration value, ensure the phase consistency of large-scale MIMO transceiver system.

A communication method and apparatus are disclosed, relating to the field of communication technology. In this method, a first communication device performs phase calibration on a first vector to be calibrated in a first precoding matrix based on a first reference vector in the first precoding matrix to obtain a second precoding matrix; compresses the second precoding matrix to obtain second information; and transmits the second information. This method can improve the compression efficiency of the precoding matrix and meet the requirements of ultra-large-scale MIMO.

This invention relates to a mapping-based MIMO vibration testing zero-response control method and system, belonging to the field of vibration testing technology. It includes: acquiring the frequency response matrix, response degrees of freedom, current response vector, and driving spectrum vector of the vibration testing system; constructing an unmapped error vector based on the difference between the current response vector and a preset target response vector; determining the active degrees of freedom and zero degrees of freedom based on the response degrees of freedom; determining a zero-mapping operator by combining the active and zero degrees of freedom; obtaining an effective error vector by combining the zero-mapping operator and the unmapped error vector; and iteratively updating the driving spectrum vector by combining the effective error vector and the frequency response matrix. This invention improves system stability, reduces sensitivity to noise, and minimizes unnecessary actuator output.

A wireless device and method configured to operate as a neighbor aware network (NAN) device enable enhanced multi-link single radio (EMLSR) operation in a neighbor aware network (NAN) environment by exchanging capability information and mapping information. The wireless device controls the radio frequency (RF) transceiver module to alternate between a monitoring configuration during a listening period and an aggregated configuration during an active period. During the listening period, the device monitors a mapping link associated with a NAN mapping identifier (Map ID) using a 1x1 configuration that employs a single RF chain. Upon detecting a trigger frame on the monitored mapping link, the device switches to the aggregated configuration during the active period. In the aggregated configuration, at least two RF chains are aggregated to communicate data using a multiple-input multiple-output (MIMO) configuration on a target link associated with the trigger frame.

Provided is a control apparatus comprising: a storage unit for storing sub-area information that indicates the respective ranges of a plurality of sub-areas into which a coverage area to be covered by an array antenna having a plurality of antenna elements is divided on the basis of an interference relationship between a plurality of beams that are generated by the array antenna; a positional information acquisition unit for acquiring positional information regarding a plurality of user terminals that are positioned within the coverage area; a terminal selection unit for using the positional information regarding the plurality of user terminals and the sub-area information to select a plurality of user terminals to be provided with MU-MIMO such that no more than one user terminal is selected for each of the plurality of sub-areas; and a control unit for performing control so as to provide MU-MIMO to the plurality of user terminals selected by the terminal selection unit.

A signal processing circuit includes a MIMO demodulation unit that includes a first MIMO filter and performs MIMO demodulation processing on a plurality of signals, a signal extraction unit that extracts a signal of a predetermined time slot from an output signal of the MIMO demodulation unit, a removal component generation unit that includes a second MIMO filter and generates a signal component to be removed including an interference component generated between modes, an interference cancellation unit that generates a signal in which the signal component to be removed has been removed from the signal extracted by the signal extraction unit, and a coefficient control unit that adaptively controls coefficients of the first MIMO filter and the second MIMO filter using a magnitude of a difference between the signal in which the signal component to be removed has been removed and a reference signal as a loss function.

An embodiment may include an example method, which may involve scheduling circular beam's downlink and uplink in-phase and quadrature (I / Q) signals, converting massive MIMO beam I / Q signals without actually performing beamforming, maintaining a beams-to-radio-heads mapping where the mapping is either statically configured during installation or dynamically updated using various algorithms, routing a beam's digital downlink signals to radio heads or broadcasting all beams' digital downlink signals to radio heads, digitally summing the digital uplink signals belonging to the same beam, A / D and D / A converting, and transmitting or receiving via antennas to form circular beams.

The application provides an mMIMO detection preprocessing and parameter pre-training method for a correlated channel, and the preprocessing method comprises the following steps: a1, modeling uplink of a large-scale MIMO system; a2, calculating a Gram matrix W; a3, obtaining a preprocessing matrix P according to the Gram matrix W; a4, preprocessing the Gram matrix W by using the preprocessing matrix P to obtain a new Gram matrix W1: W1=PW; and a5, processing the matrix W1 by using an iterative algorithm instead of a matrix inversion algorithm. The method can be applied to various iterative algorithms instead of matrix inversion, thereby accelerating the convergence of the algorithms and improving the detection performance by more than 2dB under the correlated channel.

The application provides a sorting QR decomposition method for a MIMO system, comprising: determining an initial matrix to be sorted according to a channel matrix of a MIMO system to be detected; determining column vectors to be sorted of the matrix and a column number thereof, denoted as a target number; if the target number is greater than a preset value, performing a first sorting strategy: in a first round of iteration, exchanging column orders of a column vector to be sorted with a smallest norm value and a first column vector to be sorted, and in each subsequent round of iteration, exchanging column orders of a column vector to be sorted with a second smallest norm value and a column vector to be sorted in a current round, to obtain a first target matrix; and a last column vector of the first target matrix corresponds to a highest layer traversal constellation point of an FSD algorithm. The above scheme can obtain an optimized target matrix. The application also provides an FSD-based signal detection method, which performs FSD signal detection by using the above optimized target matrix, so that the number of highest layer traversal constellation points is reduced, and the detection accuracy and reliability are still ensured.

A user equipment (UE) receives control signaling for an uplink MIMO transmission, the control signaling including a first TPMI field and a second TPMI field and an SRS resource set indicator and transmits the uplink MIMO transmission precoded with an 8 port uplink MIMO precoder, the 8 port uplink MIMO precoder being based on a 4 port uplink MIMO codebook with a mapping indicated by one or more of the first TPMI field, the second TPMI field, or the SRS resource set indicator.

This invention discloses a 5G MIMO combined antenna and terminal. The 5G MIMO combined antenna includes a substrate, a first antenna element, a second antenna element, and an isolation slot. A conductive layer is disposed on one side of the substrate. The first and second antenna elements have identical structures and each includes a first radiating part, a second radiating part, a third radiating part, and a feed part. The isolation slot is disposed near the centerline of the conductive layer in the width direction. The first and second antenna elements are symmetrically arranged about the isolation slot. This 5G MIMO combined antenna supports all current 5G frequency bands (sub-6GHz bands) globally, except for millimeter wave bands. It has the advantages of flexible operating frequency bands and large network capacity. The antenna structure is simple and compact, with good isolation between array elements, and good antenna electrical performance within the operating frequency band.

This application proposes a near-field three-dimensional imaging method for sparse MIMO arrays based on efficient spectrum reconstruction. The method includes: establishing a two-dimensional MIMO array imaging model, assuming that the receiving antennas of the two-dimensional MIMO array are fully arranged, and analyzing the imaging process of a single transmitter; further assuming that the receiving antennas of the two-dimensional MIMO array are sparsely arranged along the X-axis, and determining the actual recoverable spatial scattering signal based on the imaging process of a single transmitter; performing a Fourier transform on the actual recoverable spatial scattering signal first along the Y-axis and then along the X-axis to obtain a uniform wavenumber spectrum; performing a two-dimensional inverse Fourier transform on the uniform wavenumber spectrum to obtain the target spatial scattering signal, and then converting it to the frequency domain; extracting the component corresponding to the frequency of the target distance in the frequency domain, and performing phase compensation to recover the sub-image corresponding to a single transmitter; and finally accumulating the sub-images corresponding to all transmitters to obtain a complete three-dimensional imaging result.

A target detection method according to the present disclosure includes generating a range-velocity map from a radar signal of an MPSK-MIMO FMCW radar, detecting a plurality of target signals including a real target signal and a ghost target signal for a target with respect to a velocity axis, estimating an angle of arrival of the target by applying a Capon beamforming algorithm to a target detection result, configuring a phase sequence by extracting phase values for the plurality of target signals from the range-velocity map and arranging the phase values in descending order of velocity value, and arranging differently a plurality of prediction phase values derived using the angle of arrival according to a preset rule to obtain a plurality of candidate phase sequences, and calculating a correlation coefficient between the phase sequence and the plurality of candidate phase sequences and identifying a real target signal in the range-velocity map.