1407 results about "MIMO" patented technology

The invention belongs to the technical field of wireless communication, and particularly relates to a channel state information acquisition method based on a conditional generative adversarial network. The method is based on CSI fusion and a conditional generative adversarial network (GAN), and serves a large-scale MIMO scene; according to the method, firstly, CSI based on an uplink reference signal (SRS) and CSI of a downlink feedback channel are fused, a generator generates predicted CSI of another frequency band after receiving the fused CSI, and a discriminator optimizes the performance of the generator by comparing the real CSI with the generated predicted CSI, so that the prediction accuracy is improved. Experimental results show that the acquisition precision of the channel state information in the FDD system can be effectively improved, and the fusion of the SRS and the downlink feedback and the conversion of the CSI between the frequency bands are realized. The method is suitable for wireless communication, a 5G / 6G MIMO system and other application scenes needing efficient CSI transmission.

Apparatuses and methods for dynamic MIMO operations. A method performed by a user equipment (UE) includes receiving information about N ports and a report; based on the information, determining γ port selection hypotheses, where a port selection hypothesis with index l selects a group of n1 ports from the N ports; and transmitting the report including at least one indicator indicating the γ port selection hypotheses, where γ≥1, l ∈{1, . . . , γ}, and 1≤nl≤N.

The invention discloses a self-adaptive safety control method of a nonlinear MIMO system under intermittent DoS attack, which comprises the following steps: establishing a nonlinear MIMO system model suffered from intermittent DoS attack, and the system model is in a strict feedback form and comprises an unknown nonlinear function and bounded external disturbance; the DoS attack causes periodic interruption of a communication link from a sensor to a controller, so that actual measurement data is unavailable in an attack activation period; designing a switching type adaptive state estimator; coordinate transformation is carried out by introducing a filter, and a system error is decomposed into a tracking error and a dynamic surface filtering error; a Lyapunov function is constructed; performing stability analysis in stages; designing an adaptive law to update unknown parameter estimation values of the FLS; and a final event triggering controller is designed, and the event triggering controller is combined with a virtual controller to track an error compensation term and an FLS approximation term. The problem that the state cannot be measured is solved.

The invention provides a covert communication method based on near-field broadband super-large-scale array beam splitting. Comprising the following steps: S1, according to an applied near-field covert communication scene, constructing a corresponding communication model by using a beam splitting effect in a broadband XL-MIMO system, carrying out beam training, and describing a received signal expression of the communication model; s2, constructing a signal detection model of a listener according to a near-field covert communication scene, and describing a detection error probability expression and a covert constraint expression; and step S3, the hidden transmission rate is maximized by optimizing the transmitting power and the subcarrier number of the transmitter. According to the method, the two-dimensional optimization problem related to the transmitting power and the subcarriers is converted into the one-dimensional optimization problem related to the discrete variable quantum carrier number, and the concealment rate of a legal receiver is maximized.

The invention relates to the technical field of wireless communication, in particular to a joint pilot frequency data transmission authorization-free random access method, which comprises the following steps of: constructing a joint pilot frequency data transmission system model in cellular-free large-scale MIMO (Multiple Input Multiple Output), deducing a user spectrum efficiency closed expression, and establishing a maximum and minimum user power allocation optimization problem; reconstructing an objective function and constraint conditions in the optimization problem, constructing an inter-AP power distribution optimization problem model, converting the inter-AP power distribution optimization problem model into an equivalent convex feasibility problem by adopting a bisection method, and performing optimal power distribution; and constructing a constraint condition by using the optimally allocated spectrum efficiency, and solving by using a successive approximation method and an iterative algorithm model by using a maximum non-conflict user number as a target function to obtain a configuration parameter of maximum user number access of the joint pilot frequency data transmission system model. According to the method, multiple scenes of simultaneous access of large-scale users are met, the signal processing overhead is low, the time delay is low, the signal processing complexity is low, the optimal configuration scheme can be optimized, and the feasibility is good.

The invention discloses a large-scale MIMO user scheduling and beamforming method and system based on MAB, and belongs to the technical field of wireless communication. The method comprises the following steps: establishing a TSB scheme communication model to obtain a design problem of maximizing spectrum efficiency; a design problem is converted into a two-dimensional space combined type multi-arm bandit problem; dividing an objective function of the combined multi-arm gambling machine problem into two sub-problems, selecting a gambling arm in the first sub-problem to find a zero value in a power angular spectrum, and selecting a gambling arm in the second sub-problem to maximize received energy; according to the two sub-problems, an optimal linear UCB algorithm and a suboptimal linear UCB algorithm are adopted to solve the combined multi-arm bandit problem of the two-dimensional space, and a beam forming matrix is obtained; according to the method, the problem is further divided into two sub-problems, the gambling arm is firstly selected to find a zero value in the power angular spectrum, and then the gambling arm is selected to maximize the received energy, so that the spectrum efficiency is improved.

Methods, apparatuses, and computer readable medium for UL TCI are provided. An example method may include receiving, from a base station, at least one transmission TCI, the at least one TCI indicating a single UL TCI or two UL TCIs. The example method may further include receiving, from the base station, a first SRS resource set and a second SRS resource set for UL MIMO, the first SRS resource set or the second SRS resource set being associated with the at least one TCI. The example method may further include receiving DCI scheduling one or more uplink transmissions associated with at least one of a first TRP or a second TRP. The example method may further include transmitting the one or more uplink transmissions to the base station based on the DCI, the at least one TCI, the first SRS resource set, and the second SRS resource set.

A user equipment (UE) reports channel state information (CSI) to a base station in multiple-input multiple-output (MIMO) transmissions. The UE constructs a CSI matrix based on a CSI reference signal (CSI-RS) received from the base station. The CSI matrix is at least three-dimensional in a transmit (Tx) antenna domain, a frequency domain, and a time domain. The UE transforms the CSI matrix into a transformed matrix in at least a Tx beam domain, a delay domain, and a Doppler domain. The UE encodes the transformed CSI matrix into a one-dimensional feature vector using a multi-layered neural network, and sends the one-dimensional feature vector to the base station.

The invention provides a power line MIMO system receiving end filtering coefficient generation method. The accuracy of channel estimation is optimized based on subcarrier design. The method comprises the following steps: firstly, selecting a subcarrier index to represent the frequency domain response of a channel to be filtered, and then carrying out sub-band region division on the whole bandwidth to capture the difference and fading characteristics of the frequency domain channel. Then, time-domain characteristic parameters, such as a signal-to-noise ratio and a power delay spectrum, are calculated using the frequency-domain channel response. Finally, a filtering coefficient matrix is generated based on the time-domain characteristic parameters, so that the accuracy of channel estimation is improved. According to the method, differences of channels on different frequencies are considered, so that time domain characteristic parameter estimation is more accurate, a solid technical basis is provided for filter coefficient generation, and the performance of a whole communication system is improved.

Aspects presented herein may improve the performance of a JCS system by providing various resource mapping for the sensing and communication of the JCS system. Aspects presented herein may enable a base station to use PDSCH for MIMO sensing with FDM based waveform orthogonality, and may also enable a UE to support DMRS channel estimation when PDSCH is used for MIMO sensing with FDM based waveform orthogonality. In one aspect, a UE receives a plurality of PDSCHs on a plurality of ports, each PDSCH of the plurality of PDSCHs being received through a different port of the plurality of ports, each PDSCH of the plurality of PDSCHs being received on a different set of non-overlapping REs within each RB of a set of RBs. The UE demodulates each PDSCH of a port based on DMRS received through the port.

The invention discloses a time domain channel estimation method and device based on a multi-antenna diversity technology, and the method comprises the steps: mapping a bit stream into a symbol stream to construct a transmitting signal matrix, carrying out the STBC coding, inserting a time domain pilot signal, obtaining a matrix after insertion, selecting a vector in the matrix after insertion, and carrying out the time domain channel estimation. The method comprises the steps of obtaining a frequency domain receiving signal by combining with relevant parameters of Gaussian white noise and a Rayleigh fading channel, then performing matrix transformation to obtain an STBC decoding matrix, introducing a weight matrix to update an established MIMO-OFDM system input and output model to obtain a time domain channel estimation value, and finally performing FFT transformation on the time domain channel estimation value to obtain a frequency domain channel matrix estimation value. And substituting the frequency domain channel matrix estimation value into the STBC decoding matrix and then carrying out ML signal detection to obtain a final estimation value. A channel estimation algorithm is introduced to improve the estimation of a dynamic channel, a space-time block coding technology is combined to improve the demodulation signal precision of a MIMO system, and the full-state channel of the MIMO system is estimated.

A radar system may include transmitter modules configured to transmit multiple transmit signals in accordance with a Doppler Domain Multiplexing (DDM) scheme, receiver modules configured to receive reflections from the plurality of transmit signals reflected off an object and to generate corresponding digital signals, and a signal processor configured to generate a range-Doppler antenna cube representing the digital signals, and, for each of range bin of the cube, to generate a decoded range-Doppler bit map (RDBM) from the range-Doppler antenna cube by generating decoded RDBM rows by extracting a range bin matrix, performing a Discrete Fourier Transform on range bin matrix to generate an output matrix, determining peak locations in the output matrix, comparing associated peak locations across transmit channels of the output matrix to identify location-matched peaks associated with the Doppler bin, and generating a decoded RDBM row based on the location-matched peaks.

Techniques are described for providing satellite communications via a relay-assisted hybrid radio frequency / free-space-optical (RF / FSO) ground-satellite link. A high-altitude platform station (HAPS) splits the ground-to-satellite link into a ground-to-HAPS line-of-sight (LoS) multiple-in-multiple-out (MIMO) radio frequency (RF) link, and a HAPS-to-satellite FSO link. The approach mitigates the effects of atmospheric impairments on the FSO link, while also appreciably reducing adverse effects of bandwidth and propagation disparity between the RF and FSO links.

Certain disclosed embodiments pertain to suppressing interference in a wireless communication system. For example, a method of suppressing interference can include receiving one, two, or more first signals including components from a plurality of sub-channels. Each of the first signals can be processed by a Finite Impulse Response filter adapted using an LMS update algorithm.

Systems and methods for wireless simultaneous transmit and receive (STAR) using multi-input multi-output (MIMO) radiofrequency (RF) front-ends are provided. A MIMO front-end can be based on the use of a symmetrical pair of arrays, in which one is used for communication while the other is used inside an RF-shielded chamber to act as a reference for subtracting self-interference between transmitters and receivers. In addition to the two arrays, the system can include two identical passive microwave multi-beam beamforming networks. The beamformer networks can be, for example, Butler Matrix based, true-time delay microwave networks, or Rotman lens based.

A method for estimating a beam domain channel in a spatial non-stationary massive MIMO system includes constructing a beam domain channel model for the spatial non-stationary massive MIMO system by using a visibility region; transforming a problem for estimating the beam domain channel into a problem for reconstructing a sparse channel based on a sparsity of beam domain channel and an influence of power leakage; proposing a beam domain structure-based sparsity adaptive matching pursuit scheme according to a cross-block sparse structure and a power ratio threshold of the beam domain channel; and verifying that the proposed scheme has a lower pilot overhead, a higher accuracy and a higher effectiveness compared to the traditional schemes in simulation results. The method can be effectively applied to communication channel estimation with non-stationary characteristics, and has obvious advantages in estimation accuracy and complexity.

The invention relates to the technical field of wireless communication and underground coal mine safety, and discloses an explosion-proof wireless 4G / 5G base station for underground coal mining, which comprises a communication module integrated with a 4G / 5G communication protocol and supporting wireless signal transmission; the antenna array comprises a multi-band antenna capable of adjusting the direction; the intelligent reflecting surface module is deployed in a roadway and is used for dynamically optimizing an electromagnetic wave propagation path; the distributed MIMO system comprises a plurality of distributed antenna units and a centralized control unit. And the ultra-reliable low-delay communication module supports a 5G network slicing technology. According to the invention, a signal path is dynamically optimized through the intelligent reflecting surface, and cooperative transmission with millimeter wave-distributed MIMO is realized, so that the signal coverage quality and the high-capacity data transmission capability in an underground complex environment are remarkably improved; and meanwhile, based on a 5GURLLC protocol, edge computing and a wireless charging technology, ultra-low time delay and high reliability of a key task are guaranteed, and long-term endurance and intelligent maintenance of equipment are realized.

The invention relates to a target off-grid parameter estimation method for an MIMO-OTFS radar communication integrated system, and belongs to the field of radar communication integration. Comprising the following steps: constructing a receiving signal model of the MIMO-OTFS radar communication integrated system; transforming the received signal matrix, and expressing a target parameter estimation problem as a sparse signal recovery problem; carrying out rough estimation on the target parameters by adopting a 3D-OMP algorithm based on a grid; establishing an off-grid initial search interval according to the parameter rough estimation value; and realizing accurate estimation of target distance, speed and azimuth angle parameters from the grid by combining a three-dimensional golden section thought. The method has the advantages that an off-grid 3D-OGOMP algorithm is provided, the problem of grid mismatch existing in a traditional compressed sensing algorithm can be solved, and the operation efficiency can be improved by combining three-dimensional golden section search. When the method is applied to an MIMO-OTFS radar communication integrated system, high-precision and low-complexity target parameter estimation can be realized, and reference is provided for intelligent traffic application.

Methods and systems are disclosed for enhancements to multicast beamforming to support PTM multicast service, concurrent multicast and unicast service, MBS, or group side-link service at the physical layer. A base station or multicast UEs of a wireless communication network may enhance reporting of the channel state information of a link between the base station and the UE and adaptation of the link for multicast beamforming. Enhancements to multicast beamforming may include techniques such as CQI table optimization and SSB-based early CQI reporting, consideration of UE preferences such as the preferred number of retransmissions and frequency-hopping preference for retransmission when designing a time-domain or frequency-domain retransmission scheme common to the multicast UEs, and multi-layer MIMO beamforming for 2-layer multicast transmissions over the horizontal and vertical polarizations and for concurrent multicast and unicast transmissions. The enhancements improve multicast service performance and efficiently allow a UE to gain access to multicast service.

In order to solve the problems of short weak target detection distance, long detection time, few detection cycles and the like of the existing traditional active sonar, the invention provides a weak target robust high-gain detection method by using continuous wave MIMO sonar and Doppler filtering. According to the method, frequency diversity continuous wave pulse signals with low cross correlation are designed according to the number of transmitting transducers and the number of detection periods of the MIMO sonar, then the designed frequency diversity continuous wave pulse signals are continuously transmitted by using the MIMO sonar and a multi-period transmitting mode, then Doppler filtering processing is performed on echoes, and the frequency diversity continuous wave pulse signals with low cross correlation are obtained. Doppler filtering output of all frequency diversity continuous wave pulse signals is obtained, coherent accumulation and non-coherent accumulation are carried out on the Doppler filtering output, stable high-gain accumulation output is obtained, in the process, Doppler filtering of the continuous wave pulse signals can be fully utilized to suppress reverberation, multi-period accumulation is utilized to suppress noise, and the noise suppression effect is improved. And the weak target detection performance superior to that of the traditional active sonar is obtained.

The invention discloses a resource allocation method and system for a non-cellular large-scale system, and a storage medium. The method comprises the following steps: constructing a non-orthogonal multiple access-based non-cellular large-scale MIMO system model; determining a downlink data transmission rate model of the cellular-free large-scale MIMO-NOMA system; determining an optimization problem model based on the downlink data transmission rate model, wherein the objective of the optimization problem model is to maximize the rate of the cellular-free large-scale MIMO-NOMA system; based on the optimization problem model, obtaining a layered depth deterministic strategy gradient framework; according to a hierarchical depth deterministic strategy gradient framework, the networks are iteratively and mutually updated to obtain an optimal strategy; and carrying out resource allocation on the non-cellular large-scale MIMO-NOMA system based on the optimal strategy. By adopting the technical scheme provided by the invention, joint optimization is carried out on user pairing and power distribution in the cellular-free large-scale MIMO-NOMA system.

The invention provides a multi-antenna MIMO architecture synchronization method and device, a program product and a storage medium, and relates to the technical field of wireless communication. Receiving sampling signals through a plurality of receiving channels; performing down-sampling on each sampling signal to obtain a down-sampling signal; determining a plurality of cache regions to store each downsampling signal, and performing cross-correlation operation on each downsampling signal and a local synchronous time domain signal; when any receiving channel detects an effective peak value, determining the position of the effective peak value as a preliminary synchronization position; determining a corresponding search window range, and performing weighted stacking on the target cross-correlation results to obtain an overall correlation peak value; searching a maximum value in all the total correlation peak values, and determining a position corresponding to the maximum value as a final synchronization position; and calculating a frequency offset estimation value of each receiving channel according to each pilot signal, and carrying out weighted average on each frequency offset estimation value to obtain a final frequency offset estimation value. By adopting the method, the wireless frame synchronization precision can be improved.

A dual-polarization (DP) intensity-modulated direct detection (IMDD) receiver includes an input port configured to receive input light; an optical polarization splitter configured to split the input light into a pair of optical transmission paths; a pair of photodetectors including (i) a first photodetector configured to detect light at a first carrier frequency and output an electrical signal into a first electrical transmission path, (ii) a second photodetector configured to detect light at a second carrier frequency and output an electrical signal into a second electrical transmission path, wherein the first carrier frequency and the second carrier frequency are separated by a frequency difference; and an electrical 2×2 multi-input-multi-output (MIMO) polarization demultiplexer configured to input the first electrical transmission path and the second electrical transmission path and perform electrical 2×2 MIMO polarization demultiplexing to output a first demultiplexed signal and a second demultiplexed signal.

Certain disclosed embodiments pertain to suppressing interference in a wireless communication system. For example, a method of suppressing interference can include receiving one, two, or more first signals including components from a plurality of sub-channels. Each of the first signals can be processed by a Finite Impulse Response filter adapted using an LMS update algorithm,

Embodiments of the present disclosure provide method and apparatus for determining DL MU-MIMO SINR. A method performed by a network node comprises determining DLSU SINR for a layer of two or more co-scheduled layers. The method further comprises determining a correlation matrix among the two or more co-scheduled layers. The method further comprises determining a penalty for the layer of the two or more co-scheduled layers based on the correlation matrix. The method further comprises determining DL MU SINR for the layer of the two or more co-scheduled layers based on the DL SU SINR and the penalty.

The invention belongs to the technical field of wireless optical communication, and discloses a cross-domain relay type radio frequency-laser communication module and a communication method, and the cross-domain relay type radio frequency-laser communication module is provided with a node construction module, a relay module, a synchronous control module, a modulation-demodulation module and a situation awareness module. According to the invention, a large-scale MIMO technology, DMD structure light modulation and AWI signal modulation and demodulation technology are utilized to autonomously design a large-bandwidth and high-secrecy radio-light transmission conversion module; a high-precision synchronous control module is designed by using a GD32 chip, and low-delay and low-error-code relay type cross-domain information interconnection is ensured. Meanwhile, a high-sensitivity area array CCD detector is combined to sense the position of a light spot, an underwater speckle recognition alignment algorithm is developed based on YoLoV8, azimuth information is output to assist semi-active alignment, and then low-cost, low-time-delay, high-speed, long-distance and large-capacity all-weather cross-domain communication in complex water areas is achieved.

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.

Embodiments of the present disclosure are related, in general to communication, but exclusively related to methods and systems methods for transmitting a waveform. The waveform is a pre-DFT RS and data multiplexed DFT-S-OFDM with excess bandwidth shaping and MIMO. Also, embodiments of the present disclosure relate to methods of detecting the received data. The method for transmitting a waveform, comprising generating, by one or more transmitters, at least one data sequence and at least one reference sequence (RS). Also, the method comprises time-multiplexing the at least one data sequence with the at least one RS, to generate a multiplexed sequence. Further, the method comprises generating a filtered-extended bandwidth DFT-s-OFDM symbol using the multiplexed sequence. The filtered-extended bandwidth DFT-s-OFDM symbol generated by the one or more transmitters is transmitted in an OFDM symbol.

The application discloses a channel estimation method for a millimeter wave frequency division duplex massive MIMO system based on compressed sensing and deep learning, and belongs to the technical field of wireless communication.The technical scheme is as follows: a received pilot signal is processed by using a compressed sensing method to extract a preliminary CSI matrix; a convolutional neural network and a long short-term memory network are combined to extract spatial features and capture time correlation; the preliminary estimated CSI matrix is input into a ConvLSTM layer, and the ConvLSTM network fuses time correlation information to improve the estimation accuracy of the CSI; the same padding, ReLU activation function and filter with appropriate size are used to obtain the same size as the input data; and dimension transformation and inverse normalization are used to obtain the final CSI estimation result.The application has the beneficial effects that the method for channel estimation by using compressed sensing and deep learning aims at reducing the overhead of channel estimation and improving the estimation accuracy in a time-varying channel, reduces the overhead of downlink training and uplink feedback, and improves the channel estimation accuracy in the time-varying channel.