60 results about "Mimo systems" patented technology

Examples pertaining to repeater gain control for device collaboration in distributed MIMO systems are described. An apparatus (e.g., a repeater) may determine a first compensation value for a first path loss on a first link between the apparatus and a UE, and determine a second compensation value for a second path loss on a second link between the apparatus and a network node of a wireless network. The apparatus may also determine a repeater gain for uplink power control according to the first compensation value and the second compensation value. The apparatus may further forward a radio signal from the UE to the network node according to the repeater gain.

This invention discloses a monostatic symmetric nested array MIMO system and a near-field positioning method, belonging to the field of monostatic MIMO near-field positioning technology. This invention can effectively improve the positioning performance during near-field estimation. The monostatic symmetric nested array MIMO system proposed in this invention has a symmetrically distributed transmit and receive arrays. Compared to other symmetric MIMO systems, its differential array is a positionally continuous array with more degrees of freedom. With the same physical array aperture, fewer physical array elements are actually used, reducing costs. The near-field positioning method proposed in this invention calculates the fourth-order statistics of the signal and quantizes them to obtain a virtual differential array of the differential array, achieving accurate near-field positioning of sparse MIMO structure arrays. Furthermore, it can be extended to more sparse MIMO symmetric systems.

A method for compressing Sounding Reference Signal (SRS) channel information in massive MIMO systems is disclosed. When SRS channel estimation is performed in a Radio Unit (RU), the resulting channel estimates create significant fronthaul bandwidth demands. The method transforms SRS channel estimates from antenna space to domains with superior energy compacting properties, enabling transmission of only a subset of channel values while preserving information quality. The method includes beam space compression using mathematical transforms such as DFT, SVD, or EVD to convert channel estimates to beam space, followed by selection of the most significant beams. Alternative embodiments include tap domain compression using DCT or DFT, and delay-Doppler domain compression. The methods support static beam space compression using predefined beam bases and dynamic compression employing adaptive beam bases. O-RAN C-Plane implementations extend Section Type 6 to support the compression methods. The methods significantly reduce fronthaul bandwidth requirements while maintaining channel estimation accuracy, enabling improved system capacity in massive MIMO deployments.

This application provides a method, apparatus, medium, and product for ultra-large-scale MIMO channel modeling, relating to the field of wireless communication technology. The method includes: obtaining the cluster power of each cluster according to a preset channel model; determining the spatially non-stationary SnS state of each cluster according to the cluster power or a preset statistical distribution model; determining a first power attenuation factor for different clusters at the base station based on the SnS state of each cluster; determining a second power attenuation factor for each element of the user equipment; and generating channel coefficients based on the first and second power attenuation factors. The solution of this application provides a simple, physically meaningful, and efficient channel modeling method, effectively overcoming the shortcomings of existing technologies and providing reliable theoretical support for the design and optimization of ultra-large-scale MIMO systems.

The invention presents an innovative antenna panel design for Massive MIMO systems, aimed at achieving 180-degree cell coverage in 5G networks. The design incorporates a split-panel configuration, dividing the antenna array into two perpendicular panels, each covering a 90-degree sector. This approach minimizes the number of antennas needed per cell, reducing from three to two while maintaining full coverage. The split-panel design enhances beamforming precision and improves signal quality by effectively directing beams across a wide area, optimizing coverage and reducing interference. The antenna panels can be dynamically reconfigured to adapt to varying user distributions and environmental conditions, ensuring efficient network performance. The invention is particularly suitable for deployment in urban and suburban settings, offering a scalable and cost-effective solution to enhance network capacity and coverage.

This invention discloses a prediction-aided channel estimation method suitable for TDD Massive MIMO systems, including an online model training step and an aging channel prediction step. This invention uses a Latent ODE model to continuously model the channel, solving the problem of not being able to directly obtain the CSI at aging time points within a time slot, thus breaking away from the paradigm of "discrete time series prediction model + interpolation function". The online training prediction architecture proposed in this invention avoids the model aging problem caused by the high latency of complex model training by decoupling the MIMO channel using SISO. Furthermore, online training enables the prediction model to track the dynamic changes in the propagation environment in real time, thereby improving model inference performance.

This invention provides a novel transceiver design to control / compensate for the spatial-wideband effect in wideband massive multiple-input multiple-output (MIMO) systems for both sensing and communication networks. The proposed design aims to divide the ultra-wideband signal into narrowband beams and control them with a simplified exhaustive search-based precoding to align the beam angle to the target direction.

This invention provides a method, apparatus, and terminal device for estimating transmitted signals, belonging to the field of wireless communication technology. The method includes determining a received signal vector, a channel matrix, and a noise variance; inputting the received signal vector, channel matrix, and noise variance into a signal estimation model to obtain an estimated transmitted signal value output by the signal estimation model; wherein, the signal estimation model is obtained by optimizing a minimum mean square error detector based on a Fourier transform algorithm and a pre-determined weighting factor, and the weighting factor is used to adjust the convergence step size. This invention uses the Fourier transform algorithm to replace matrix inversion in the minimum mean square error detector, avoiding explicit matrix operations, reducing computational complexity, and can be used in M-MIMO systems with large-scale antennas. Furthermore, adjusting the convergence step size based on the weighting factor is beneficial for stable convergence and prevents severe degradation of bit error rate performance under high-dimensional and high-order modulation conditions.

Procedures, methods, architectures, apparatuses, systems, devices, and computer program products that may be implemented in a wireless transmit / receive unit (WTRU) and / or a network access point (NAP) with respect to MIMO precoding using a precoding neural network (NN) at the NAP. Training of the NN may use artificial and / or measured channel state information (CSI). In one embodiment, the WTRU may provide feedback to the NAP in the form of CSI statistics, time correlation, and / or bit error rate (BER) regarding a channel. The NAP may inform the WTRU of information for extracting training samples which are fed back from the WTRU to the NAP. The NAP may perform retraining of the NN using the training samples to adjust and / or recalibrate the NN weights. The information for extracting training samples may include CSI reference signal (CSI-RS) density and / or CSI-RS transmission time slots for extracting the training samples at the WTRU.

The application provides a joint structured OFDM modulation and precoding design method of a large-scale MIMO system, and relates to the technical field of MIMO communication.In the application, a point-to-point large-scale MIMO structured OFDM (mMIMO-SOFDM) system is constructed by using a structured OFDM modulation method; and based on a joint spatial precoding and structured frequency domain equalization scheme, a closed-form solution of each subcarrier frequency domain equalizer, transmission precoding and reception precoding of the mMIMO-SOFDM system is solved.By proposing the structured OFDM scheme, the excessive cyclic prefix overhead caused by the double wideband effect of the large-scale MIMO system is reduced.In addition, the proposed joint spatial precoding and structured frequency domain equalization scheme further improves the spectral efficiency of the system and reduces the peak-to-average ratio.

The invention provides an improved channel estimation method based on combination of an RIP criterion and an SOMP algorithm, relates to the technical field of channel estimation of an RIS auxiliary system, is suitable for a channel estimation algorithm of an RIS auxiliary millimeter wave large-scale MIMO system, and aims to solve the problems that a traditional SOMP algorithm lacks sparseness priori information and an atom selection strategy is rigid. According to the method, a sparseness estimation method based on the RIP criterion is innovatively designed when atom number selection of initial iteration is set in the SOMP algorithm, a result serves as the initial atom selection number, and the atom number in the subsequent iteration process is dynamically adjusted by using the residual energy ratio of two iterations of the SOMP algorithm; experiments show that compared with traditional matching pursuit algorithms such as an OMP algorithm, an SOMP algorithm and an StOMP algorithm, the method has obvious advantages, and support is provided for the SOMP algorithm to be more suitable for practical application.

Methods and wireless communication devices for MIMO packet detection, include receiving input data by a receiver, performing peak detection by a two-tiered approach including an outer loop and an inner loop to generate candidates composing of detected peaks from correlation outputs, and driving final start of packet and carrier frequency offset measurements from the candidates as a final packet detection result. The outer loop iterates on (Rx, STS) combination pairs, and the inner loop runs peak detection on the input data by one or more correlators for each of the (Rx, STS) combination pairs. Rx is one of the receiving antennas of the receiver and STS is one of space-time streams received by the receiver. In some embodiments, one or more winning candidates are selected from the candidates based on a score computed from information related to the detected peaks for each candidate, and the final packet detection result is derived from the winning candidates.

The application relates to the communication field and discloses a channel data decoding method, device and equipment for a MIMO system, wherein the method comprises the following steps: acquiring a receiving signal matrix output by a MIMO channel; determining an estimated matrix of a sending signal matrix based on the receiving signal matrix; acquiring soft information of each estimated symbol in the estimated matrix to construct a soft information matrix of the estimated matrix; iteratively updating the soft information matrix; in any iteration round, decoding and updating the soft information matrix of the current iteration round to obtain a candidate codeword list set of the current iteration round; after the iterative updating is completed, determining a target codeword matrix based on the candidate codeword list set of the last iteration round; checking the target codeword matrix; and outputting information corresponding to the target codeword matrix as a decoding result when the checking result represents that the target codeword matrix is correct. The technical scheme provided by the application can reduce the bit error rate and the missing detection rate of channel transmission and significantly improve the decoding performance.

The present disclosure relates to a 5G or 6G communication system for supporting a higher data transmission rate. A hybrid MIMO system includes N digital transceiver chains and N analog beamformers, each analog beamformer coupled to one of the digital transceiver chains and including M analog TX chains and M analog RX chains. One of the simulated RX chains is an RX reference node, and one of the simulated TX chains is a TX reference node. For each beamformer, the processor measures TX and RX phase responses and TX and RX amplitude responses of TX and RX reference nodes, respectively, using a transceiver chain and a calibration transceiver; determining a reciprocity calibration based on a phase difference between the TX and RX phase responses and an amplitude difference between the TX and RX amplitude responses; and applying a reciprocity calibration to the stored beam definition to correct the phase and amplitude difference.

This disclosure relates to the field of multiple-input multiple-output (MIMO) systems, and proposes a signal detection method, apparatus, and device for MIMO systems. The method includes: determining an iterative weight matrix based on an iterative reference variance, a system channel matrix, and system noise power; performing Newton iteration on the iterative weight matrix to generate an iterative covariance matrix; determining the iterative distribution variance based on the iterative covariance matrix; determining the iterative distribution expectation based on the iterative covariance matrix, an iterative reference expectation, the system output signal, the channel matrix, and noise power; updating the iterative reference expectation and iterative reference variance according to the iterative distribution expectation and iterative distribution variance, and proceeding to the next iteration cycle; when the iteration reaches a preset cycle, determining the iterative distribution expectation as the target distribution expectation, which is used to estimate the system's input signal. The technical solutions provided by one or more embodiments of this disclosure can reduce the computational complexity of the detection process and ensure the accuracy of the signal detection results.

This invention discloses an active user detection method based on covariance-based nonorthogonal pilots for non-cellular massive MIMO systems, applicable to the communications field. A mathematical model for nonorthogonal random access based on non-cellular massive MIMO is established. By utilizing the block diagonal characteristics of the received signal covariance matrix, the active user detection problem is reconstructed into a maximum likelihood estimation problem. The coordinate descent algorithm is used to solve the reconstructed maximum likelihood estimation problem, and a parallel estimation algorithm is proposed to reduce computation time. This invention achieves a good trade-off between performance and complexity in active user detection, meeting the needs of scenarios with massive terminal random access and showing great application potential.

This invention proposes a collaborative uplink / downlink channel extrapolation method for large-scale MIMO systems. Addressing the issues of limited uplink pilot bandwidth and uplink / downlink timing asynchrony in time-division duplex systems, this method proposes a collaborative channel reconstruction scheme between the User Equipment (UE) and the Base Station (BS). Specifically, the method includes: at the UE, extracting downlink propagation delay parameters from a small number of high-energy downlink beam observations using a smoothed MUSIC algorithm, and feeding back only the low-dimensional delay parameters to the base station; at the BS, estimating the uplink / downlink delay offset using uplink narrowband pilot observations, and calibrating the fed-back delay parameters; at the BS, using complementary subspace projection technology, further estimating the lost delay paths in the downlink observations from the uplink observations, and merging them to obtain a complete delay set; based on the complete delay set, reconstructing the full-band uplink channel using a compressed sensing algorithm. This method significantly reduces computational complexity while maintaining channel extrapolation accuracy.

Techniques of using interferometry for sensing movement of an object in a communications network operating at high frequency are provided. The distance between slits does not need to be large to achieve high resolution due to the short wavelength (λ) at high frequency. Therefore, considering multi-panel, or multi-portion panel transmission, the distance between panels, or portions of a panel, may be sufficient to achieve high accuracy, even considering the case of the single panel that is virtually divided into two or more subpanels by controlling the phase shifts in each subpanel. Methods of signaling associated with an over-the-air (OTA) interferometer between a transmitter and receiver for measuring movement of an object are provided.

A method for realized by a extra large multiple input multiple output (XL-MIMO) system comprising at least an access point (100) comprising extra-large antenna array having antenna elements (111) and multiple user equipment (200) configured to communicate with the access point (100), the method is suitable for detecting visibility regions of user equipment (200) on antenna array (110).

According to an aspect, there is provided an apparatus configured to perform the following. The apparatus obtains an approximate effective channel matrix for a radio channel between the apparatus, acting as a transmitter, and a receiver. The apparatus calculates an eigenvalue decomposition, EVD, of a matrix product of the approximate effective channel matrix and a conjugate transpose of the approximate effective channel matrix and determines, based on the EVD, a left singular matrix of a singular value decomposition, SVD, of the approximate effective channel matrix and a diagonal matrix of singular values of the SVD of the approximate effective channel matrix. The apparatus calculates eigenvectors of the approximate effective channel matrix based on the approximate effective channel matrix and the left singular matrix of the SVD.

The present invention describes a method, system, and a non-transitory computer readable storage medium to mitigate the side effects of imperfect channel estimation, analog processing imperfections, beamforming misalignment, and other imperfections present in massive MIMO wireless communications systems. Through the present invention, the user will have a better communication experience regarding data rate transmission, spectrum efficiency, and, specially, communication reliability. The core of the present invention relies on how the imperfections present in massive MIMO systems are modeled and faced by adding more robustness to the proposed baseband precoder. In addition, the present invention has the capacity to be implemented in any hybrid hardware architecture, where the number of radiofrequency (RF) chains is lower than the number of antennas. This feature is crucial for massive MIMO devices because having an expensive and energy-intensive RF chain per antenna would be impractical or even prohibit when the number of antennas is large.

The present invention provides a method which is suitable for being used within a communication network comprising at least one main communication device (1) having at least one antenna array (1a), which is able to provide service by broadcasting directional signal beams by generating serving lobes (4) and non-serving lobes (5), and having at least two RF chain (1b) ensuring generation of the lobes, at least one user device (3) which is capable of communicating with the main communication device (1) through the serving lobes (4), at least one secondary device (2) which is capable of communicating with the main communication device (1) through the non-serving lobes (5). The method is configured to provide physical layer security with spatial aliasing in wireless networks comprising MIMO systems which ensure usage of grating lobes for various processes such as back-scattered communication, energy harvesting and identification. The method comprises generation of overlapping non-serving lobes (5) to provide service to the secondary devices (2).

The invention discloses an intelligent AP (access point) management method for a new energy enabling cellular-free large-scale MIMO (multiple input multiple output) system based on TD3 (time domain 3). The method comprises the following steps: firstly, by taking maximization of power grid energy efficiency as a target, constructing a cellular-free large-scale MIMO system AP management optimization problem under a new energy enabling scene of dynamically adjusting AP dormancy and an AP clustering strategy; wherein the connection strength of the AP and the UE is measured through an energy-channel state information index of a new energy enabling scene, and AP clustering control is carried out through comparison with a set threshold value; modeling an AP dormancy and AP clustering joint optimization problem into an MDP process, and setting a state space, an action space and a reward function; and the energy state and the communication state of the network are learned by using a TD3 algorithm, so that the optimization of an AP management strategy is realized. Experiments show that the method shows better performance in the aspect of improving the energy efficiency of the power grid, and especially can obtain higher energy efficiency of the power grid in a network with rich new energy.

The application provides a method and device for dividing a propagation mechanism area of a super large-scale MIMO system. The method provided by the application comprises: acquiring channel delay domain data corresponding to a dual polarization mode of a MIMO system in a dynamic indoor scene with a receiving end moving; constructing a dynamic time delay heat map with a transmitting end antenna serial number and a measurement time as two-dimensional dimensions based on the channel delay domain data, wherein the dynamic time delay heat map represents delay distribution differences in different polarization modes; performing noise smoothing and edge preserving processing on the dynamic time delay heat map, and then performing area segmentation, boundary positioning of different propagation mechanisms, edge detection and morphological optimization; extracting delay distribution features of the segmented areas for unsupervised quantitative clustering to obtain different time delay levels; and based on a combination mode of the time delay levels, combining the physical nature of the propagation mechanism, dividing an occluded line of sight into a transition state subclass to obtain a classified propagation mechanism.

The application discloses a near-field target positioning method based on atomic norm space frequency modeling. The method establishes a near-field array receiving signal model, then carries out a space frequency structural representation of the near-field signal, then carries out a meshless sparse space frequency representation based on atomic norm minimization, then carries out frequency ridge line extraction and linear fitting, and finally realizes joint estimation of angles and distances and system output. The application fully utilizes the space frequency variation law of the near-field signal, obtains the angle and distance information of the target by extracting the main frequency ridge line and carrying out linear fitting, can realize high-precision and low-complexity joint estimation of angles and distances, has significant advantages in parameter estimation precision, robustness and calculation efficiency, and can reduce the influence of noise and window effect on the estimation precision, thereby providing a high-precision and easy-to-implement technical scheme for near-field target positioning in large-scale MIMO systems and 6G communication.

A communications network system including antenna elements and a processor coupled with the antenna elements, the processor executing instructions to perform operations including establishing a first data communication link over a first frequency band between the CPU and the first AP of a first group of APs, causing the first AP to establish a second data communications link over a second frequency band between the first AP and a first UE, transmitting, via beamforming by the antenna elements, data to the first AP over the first data communications link, the data configured to be relayed via the first AP to the first UE over the second data communications link, obtaining an end-to-end data rate of the data communication between the CPU and the first UE, and achieving a higher end-to-end data rate than the obtained end-to-end data rate by adjusting beamforming vectors.

This invention belongs to the field of wireless communication technology, specifically relating to a SIM-enabled massive MIMO communication system. The system employs a single-RF link transmitter architecture, replacing traditional antenna arrays and single-layer reconfigurable smart surfaces with a SIM, enabling efficient signal transmission in multi-user communication scenarios. Specifically, the stacked smart metasurface applies controllable phase modulation to the incident single-frequency carrier signal, achieving signal modulation and precoding without the need for traditional baseband modulation. This allows different users to receive their desired signals with low mutual interference. Compared to traditional massive MIMO systems, this system architecture effectively alleviates the engineering challenges of high hardware complexity, high integration density, increased power consumption, and limited heat dissipation faced by high-frequency communication, while significantly reducing reliance on high-precision digital-to-analog converters and multiple RF links.

The application discloses a millimeter wave movable array beam training method based on quantum correlation simulated annealing, and relates to the technical field of wireless communication.The application proposes a quantum correlation simulated annealing (QCSA) algorithm aiming at the high-dimensional, non-convex and strongly coupled beam-array position joint optimization problem caused by the movable array, and adopts an alternating optimization framework to decompose the joint optimization problem into iterative solving of the transmitting and receiving subspaces; in each subspace optimization, the physical correlation between parameters is learned through Gaussian sampling based on an adaptive covariance matrix, the global search capability is enhanced by using an acceptance criterion containing a thermodynamic term and a quantum tunneling term to escape from a local optimum, and a periodic oscillation thermal scheduling strategy is adopted to dynamically balance exploration and utilization, so that the application has the characteristics of low overhead, fast convergence and high robustness, and is suitable for 6G millimeter wave and terahertz movable array MIMO systems.

The invention provides a method and a device for dividing propagation mechanism regions of an ultra-large-scale MIMO (Multiple Input Multiple Output) system. The method provided by the invention comprises the following steps: acquiring channel delay domain data corresponding to a dual polarization mode of an MIMO system in a dynamic indoor scene in which a receiving end moves; based on the channel delay domain data, constructing a dynamic time delay heat map taking a transmitting end antenna sequence number and measurement time as two dimensions, the dynamic time delay heat map representing delay distribution differences in different polarization modes; performing noise smoothing and edge preservation processing on the dynamic time delay heat map, performing region segmentation through edge detection and morphological optimization, and positioning boundaries of different propagation mechanisms; extracting delay distribution characteristics of the segmented regions and carrying out unsupervised quantitative clustering to obtain different delay levels; and based on the combination mode of the time delay level, combining the physical nature of the propagation mechanism, dividing the shielding sight distance into transition state subclasses, and obtaining a classified propagation mechanism.