961 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.

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.

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.

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.

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.

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.

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.

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.

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 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.

Embodiments contemplate methods, systems, and apparatuses for interference measurement in a wireless communication network, including wireless communication networks the employ MIMO in uplink and / or downlink communication. Embodiments contemplate identifying one or more interference measurement resource elements that may be received from one or more transmission points. Embodiments also contemplate performing interference measurement estimation based at least in part on the identified one or more interference measurement resource elements. Channel state information (CSI) perhaps in the form of reports may be generated based at least in part on the one or more interference measurement estimation. Embodiments also contemplate that the CSI report may be transmitted to one or more nodes. In some embodiments, the one or more interference measurement resource elements may be received as part of a set of resource elements.

The present invention relates to the technical field of wireless communications. Disclosed are a deep learning-based CSI compression feedback method and system for a multi-antenna MIMO system. The method comprises: acquiring raw CSI data, and preparing a neural network model training set; on the basis of the acquired data, constructing a U-Net neural network model integrated with a Transformer; training the neural network model offline to obtain a trained neural network model; and performing metric evaluation on the trained neural network model. The present invention improves the CSI compression efficiency and reconstruction accuracy of the multi-antenna MIMO system, accelerates data processing and feedback speed, enhances model adaptability, and achieves accurate restoration of compressed data. In addition, the multi-scale convolution and skip connection design of the network preserves more details, thereby improving reconstruction quality. An optimized network structure not only reduces the amount of calculation, but also improves processing speed, so that the model can adapt to various channel environments and communication scenarios.

The invention provides an unmanned aerial vehicle three-dimensional coordinate positioning method and system based on distributed MIMO nodes. The method comprises the following steps: firstly, constructing a three-dimensional space layout covering an active area of an unmanned aerial vehicle, secondly, acquiring a characteristic parameter set, then, compensating a transmitted signal according to a height fall relationship, generating a directional beam group, then, converting a multipath time delay difference value and a phase deviation correlation value in the characteristic parameter set into a three-dimensional space vector component, and finally, constructing a three-dimensional space layout covering the active area of the unmanned aerial vehicle. And finally, resolving real-time three-dimensional coordinate data of the unmanned aerial vehicle in the target airspace through a spatial overlapping relationship of the three-dimensional space vector components in the three-dimensional space layout. According to the technical scheme provided by the invention, the positioning precision and the anti-interference capability in a dynamic obstacle environment are improved, centimeter-level three-dimensional positioning is realized in a GPS-free scene, the calculation complexity and the power consumption are reduced, and light-weight deployment and stable beam coverage in a complex scene are realized.

A base station may perform a beamforming for a UE group including UEs that are disposed spatially close to each other for MU-MIMO. The base station may generate group common DCI including a beam indication and / or a PL-RS indication for the UE group. The ID included in the group common DCI may be group specific for the UE group or UE specific for a specific UE. The beam indication for different channels may be indicated by an RNTI or an RRC.

The present invention discloses a MIMO-OFDM channel estimation method and device based on natural interpolation. The method comprises: obtaining a channel coefficient at a pilot signal based on least squares channel estimation; assigning weights to the channel coefficients at several pilot signals near each interpolation point according to the size of the Voronoi diagram grid area based on the natural interpolation method, and obtaining an interpolation formula at the interpolation point by weighted summation; and performing natural interpolation on each interpolation point using the interpolation formula to obtain a MIMO-OFDM channel estimation result. The method applies natural interpolation to channel estimation, and obtains a channel frequency response estimate at the interpolation point by weighting the values ​​at several pilot signals near the interpolation point. This method can simultaneously utilize the time and frequency correlation of the channel, significantly improve the channel estimation accuracy, reduce the channel estimation error, and have a smoother interpolation effect and better interpolation performance.

A wireless transmit receive unit (WTRU) and methods are disclosed for mitigating radar interference on PUSCH transmission. The method may include: transmitting a message informing a network of PUSCH MIMO layer aggregation capability; receiving a MIMO rank; receiving an indication to use PUSCH MIMO layer aggregation; determining a PUSCH layer aggregation level based on the MIMO rank; and transmitting multiple redundancy versions of a PUSCH codeword comprising one or more code blocks based on the PUSCH layer aggregation level. The WTRU may be configured to transmit a message informing a network of PUSCH MIMO layer aggregation capability; receive a MIMO rank; receive an indication to use PUSCH MIMO layer aggregation; determine a PUSCH layer aggregation level based on the MIMO rank; and transmit multiple redundancy versions of a PUSCH codeword comprising one or more code blocks based on the PUSCH layer aggregation level.

The invention provides a method for optimizing the energy efficiency of an uplink of an RIS-assisted cellular-removed large-scale MIMO (Multiple-Input Multiple-Output) system. Based on a Rayleigh channel fading model, the method firstly derives an expression of the energy efficiency of an uplink under perfect channel state information, and provides a method for jointly optimizing the user transmitting power and the RIS phase shift matrix with the purpose of maximizing the energy efficiency. In view of the non-convexity of the optimization problem, the user transmitting power is optimized by utilizing a water injection method, and the RIS phase shift matrix is optimized by adopting a genetic algorithm, so that the energy efficiency is quickly improved. According to the invention, the total power consumption of the system is effectively reduced, the wireless resource utilization rate of the system is improved, and green communication requirements are met.

The US DoD is moving to incorporate 5G, particularly for sidelinks networks. 5G sidelink network are desired to operate at company, platoon, and squad levels independent of connection to 5G base stations (gNB). The 5G sidelink standards, as defined by 3GPP, cannot operate under active jamming at expected threat levels. The sidelink standards are defined for commercial use and cannot withstand active jamming. Various prior art uses beamforming, directionally beamformed MIMO, and even distributed MIMO as potential options to address active jamming. The SWAP-C and standards of the 5G UEs are not conducive to these anti-jamming techniques. A solution is described that uses the 5G sidelink physical layer with modifications at the control layer to avoid denial of the S-SSB. Intra-, inter-squad, and squad-to-command post communications may use the solution to avoid denial of the 5G sidelink.

The invention discloses a K-band-based close-range end-to-end sparse MIMO FMCW radar system. The method comprises the following steps: performing range-fast Fourier transform on an intermediate frequency signal acquired by a sparse MIMO FMCW millimeter wave radar system to obtain a frequency domain signal; after strong leakage interference targets in the frequency domain signals are filtered through a frequency domain leakage filtering technology and intermediate frequency signals of interested targets are reserved, speed-fast Fourier transform is carried out to obtain a distance-Doppler graph, and distance and speed information of the interested targets is extracted; performing sparse array traditional beam forming on the obtained target signal to estimate angle information of the target, and matching angle and distance information by using a digital beam forming technology to obtain the distance, the speed and the angle of each interested target so as to form a spatial point cloud; and finally, for multi-frame acquisition of the spatial point clouds formed by the above steps, carrying out angle averaging on the point clouds at the same distance to smooth the trajectory, and forming the motion point cloud trajectory of the target. The method is suitable for synchronous and asynchronous systems, solves the existing multipath leakage problem, and is high in robustness.

The invention relates to a 92GHz MIMO roadside radar radio frequency system based on a frequency conversion assembly, and the radar radio frequency system comprises a baseband processing layer which comprises at least two cascaded millimeter wave system-level SoC chips; the frequency conversion layer is a frequency conversion module FCM, and the FCM comprises a local oscillator synthesis unit, an upper mixer group and a lower mixer group; the local oscillation synthesis unit is used for generating a 13GHz local oscillation signal; the input end of the upper mixer group is connected with the output end of the baseband processing layer, the local oscillation end of the upper mixer group is connected with the local oscillation synthesis unit, the output end of the lower mixer group is connected with the input end of the baseband processing layer, and the local oscillation end of the lower mixer group is connected with the local oscillation synthesis unit; and the down-conversion layer is used for down-converting 92-94 GHz echo signals received by the antenna array to 79-81 GHz and then outputting the echo signals to the baseband processing layer. According to the invention, 92-94 GHz frequency conversion can be realized.

The invention discloses an evaporator energy storage process control method and system based on fractional order MIMO nonlinearity. Historical operation data of the evaporator are obtained, and corresponding fractional order MIMO nonlinear system models are constructed according to different dryness intervals; operating data containing dryness is collected in real time, the fractional order MIMO model of the current dryness is input, and a prediction result is generated; comparing the prediction result with the real-time data, and if the deviation exceeds a threshold value, adjusting the parameters and re-executing; otherwise, calculating a dynamic weight to optimize the model in the next stage; real-time data are analyzed through fractional order MIMO models under different dryness degrees, abnormal stages are identified, and early warning is carried out; and comparing real-time analysis results of different dryness interval models, identifying dryness fluctuation amplitude and pressure oscillation frequency data, and then judging an anomaly type. According to the method, reliable control over the energy storage process of the evaporator is achieved.

The invention provides an advanced XL-MIMO design method and system for enhancing wireless augmented reality communication. The advanced XL-MIMO design method comprises the steps of S1, selecting and designing a required frequency band and determining system parameters; s2, a centimetre wave frequency band centralized mMIMO system is designed according to the parameters, the system comprises a base station BS and a plurality of multi-user MUs, the base station adopts hybrid beam forming, and a zero-forcing equalization technology is used for digital beam forming; s3, designing a distributed XL-MIMO system under the millimeter wave and sub-terahertz frequency bands according to the parameters; s4, establishing a channel model, acquiring 3GPP and BUPT channel data, and verifying the accuracy of the data; s5, performing simulation in the UMi scene of the urban micro cell; and S6, according to the simulation result, obtaining the maximum achievable data rate in the augmented reality XR scene. According to the invention, smooth and immersive experience is ensured, and a more efficient and more stable communication effect is realized in the aspect of selecting proper architecture and frequency band.

Embodiments of the present disclosure relate to modulation-specific components for reconfigurable neural network-based receivers. A neural receiver (NRX) may be used in a wireless communication systems and method. The NRX performs symbol demapping simultaneously in a reconfigurable multi-user multiple-input multiple-output (MU-MIMO) system, where one or more of the modulation and coding (MCS) schemes are different and variable. The reconfigurable MU-MIMO NRX includes MCS-specific components at an input and output layer and modulation independent intermediate layers between the input and output layers. The reconfigurable MU-MIMO NRX may be jointly trained for multiple MCSs and for system property variations (different learned weights for each system property variation).

The invention discloses a super-resolution communication perception integration method and system based on sparse MIMO, and belongs to the field of wireless communication and signal processing. Signals emitted by all users are received through a sparse array, and signal processing is carried out to estimate the two-dimensional angle of arrival of the users; pairing the two-dimensional angles by using a permutation matrix; a beam forming matrix is constructed by matching the estimated angle, and channel gain is estimated by using a small amount of pilot frequency, so that super-resolution two-dimensional sensing and efficient channel estimation of users in the system are realized. According to the method, the characteristic of large array aperture of the sparse array is combined, the problem of low positioning precision of dense distribution of multiple users is solved under the condition of not increasing hardware loss, a large amount of pilot frequency resources are saved, and the channel estimation precision is further improved.

A microstrip antenna which includes a substrate, a ground on a second side of the substrate, a first patch on a first side of the substrate, and a second patch on the first side of the substrate. The first patch is connected to a first port. The second patch is separated from the first patch and connected to a second port. Each of the first and second patches is further formed with a plurality of shorting vias connected to the ground. The radiation patterns of each element also feature the RPD characteristic, which is promising for large-scale MIMO or array antennas.