50 results about "Channel feedback" patented technology

The invention discloses a power distribution switchgear remote monitoring and maintenance method based on the Internet of Things, relates to the technical field of power system operation and maintenance, and solves the problems that in an existing power distribution system, the edge anomaly recognition capability is weak, a control feedback chain is not closed, and multi-terminal control conflicts occur frequently. According to the scheme, a structured time sequence index of multi-source data is constructed on edge equipment, and equipment state drift is judged based on residual function included angle change; a control command management mechanism of a unique transaction identifier is introduced, a dual-channel feedback structure and a control mutual exclusion stack are combined, and a remote command consistency control chain is established; a hidden danger propagation chain is constructed on the cloud based on the abnormal Boolean bitmap and the topological relation, and a multi-node state linkage analysis and risk priority intervention strategy is achieved; according to the invention, the abnormity identification accuracy, the remote control stability and the system-level operation and maintenance response efficiency of the power distribution switch equipment are obviously improved.

The invention relates to a self-adaptive voice semantic communication method based on hierarchy time sequence importance, which belongs to the field of voice analysis, and comprises the following steps: a sending end performs priority division on a discrete feature matrix according to hierarchy and time sequence attributes of voice features, and screens the features according to importance scores in a feature matrix packaging and selecting link; the method comprises the following steps: interacting with wireless communication through a channel adaptive scheduling module, introducing a channel feedback mechanism, and dynamically adjusting transmission power and a resource allocation strategy by sensing current channel state information; and after completing signal demodulation, a receiving end inputs the acquired sparse feature flow into a voice restoration module, and globally reconstructs the received features by using voice priori knowledge of deep pre-training. According to the method, a hierarchical speech feature extraction technology based on a discrete codebook and a generative semantic repair technology are combined, so that the speech word error rate in a severe channel environment is reduced to the maximum extent, and the semantic intelligibility of a receiving end is improved.

Provided are a channel feedback method, apparatus and device, the method comprising: a first station receiving a first frame sent by a first access point, the first frame being used for indicating the first station to feed back compressed channel information, the first station being associated with the first access point; the first station receives a second frame sent by the first access point, wherein the second frame is used for the first station to perform channel estimation to obtain first data channel information; the first station sends a third frame to the first access point, the third frame comprises compressed data channel information, the compressed data channel information is obtained by compressing first equivalent data channel information, and the first equivalent data channel information is determined according to the first data channel information and a first smooth left singular vector matrix; the first smooth left singular vector matrix is obtained by smoothing a first left singular vector matrix, and the first left singular vector matrix is obtained by performing singular value decomposition on the first data channel information.

A channel feedback method, apparatus and system. The method comprises: acquiring multipath component information of a communication channel between a first device and a second device; on the basis of a self-supervised neural network, performing processing on the multipath component information and second channel information, so as to obtain intermediate information; and sending the intermediate information, wherein the second channel information is determined on the basis of first channel information and multipath delay information, the second channel information comprises a variable channel impulse response (CIR), the first channel information comprises a channel frequency response (CFR), which is obtained by means of a measurement, and the intermediate information and the multipath component information are used for determining a reconstructed CIR. By means of the solution, channel feedback is performed in combination with multipath component information and a self-supervised neural network, thereby reducing measurement overheads and feedback overheads.

This invention discloses a multimodal perception-based immersive digital interaction system and method, relating to the field of digital interaction technology. The system includes generating user state representations; constructing a dynamic contextual framework; and optimizing interaction strategies through a multi-channel feedback mechanism. This invention achieves deep fusion and dynamic understanding of the user's multidimensional human state and environmental context, significantly improving the system's accuracy in recognizing user intentions and its real-time response; enhancing the naturalness and immersion of the interaction; and enabling the system to continuously adapt and optimize, generating highly personalized, smooth, and context-consistent immersive interactive experiences. This comprehensively solves the key problems of mechanical interaction, delayed feedback, and insufficient immersion in existing technologies.

The invention provides a power module dynamic protection system and method based on multi-parameter real-time monitoring, and relates to the technical field of power module parameter monitoring, and the system comprises a temperature monitoring unit, a stress monitoring unit, a dual-channel feedback control circuit and an execution unit. Monitoring temperature and stress data of the power module in real time through the temperature monitoring unit and the stress monitoring unit; the dual-channel feedback control circuit independently processes the temperature data and the stress data to obtain absolute values and change rates of the temperature and the stress, and threshold values are set according to the absolute values and the change rates of the temperature and the stress to carry out dynamic protection judgment on the power module; and the execution unit executes dynamic protection on the power module according to a judgment result fed back by the dual-channel feedback control circuit. According to the invention, cooperative monitoring means of temperature and stress are fused, layered guarantee of soft protection and hard protection is adopted, and timely and intelligent dynamic protection of the power module is realized.

The invention belongs to the technical field of mobile communication, and particularly discloses a communication and sensing integrated RIS intelligent coverage optimization system and method, and the system comprises an intelligent cooperative control center, a train signal terminal disposed on a train, a plurality of 6G communication and sensing integrated base stations disposed at intervals along a train route, and a plurality of RIS array modules disposed at intervals along the train route. Through collaborative optimization of the 6G communication and induction integrated base station and the RIS array, a 6G signal propagation path can be accurately remodeled, the problem of signal attenuation in a weak coverage area is effectively solved, the 6G signal receiving power of a train is improved, and continuous coverage of 6G high-bandwidth services is guaranteed; doppler frequency shift can be accurately offset through dynamic phase adjustment, so that the signal distortion rate is reduced, and the stability of 6G communication of a train in a high-speed running state is ensured; and the channel feedback time delay of traditional base station switching can be eliminated, the success rate of uninterrupted signal switching is improved, and the continuity of 6G key services such as train control and passenger service is guaranteed.

The invention provides a 5G NTN waveform anti-rotor-shielding method suitable for helicopter communication, and the method comprises the steps: setting a switching threshold value of an adaptive modulation code and a fountain code, and carrying out the switching according to the channel quality; when the channel quality is good, adaptive modulation and coding are adopted, channel feedback CQI is obtained, and according to the adaptive modulation and coding technology, a proper modulation mode and coding efficiency are selected, and uplink and downlink waveforms of a 5G NTN system conforming to a target modulation mode and a target code rate are constructed; and when the channel quality is poor, using a fountain code, taking the LDPC code under the 5G NTN specification as an outer code, and taking the LT code as an inner code, and constructing uplink and downlink waveforms of the 5G NTN system conforming to the target modulation mode and the target code rate. According to the method, the adaptive modulation coding technology and the Raptor fountain code are utilized, so that the communication quality is ensured under the condition that the helicopter rotor is shielded, and the rotor shielding resistance of helicopter communication is improved.

The application discloses a mixed multi-resolution channel state information feedback method and device, relates to the technical field of channel state information feedback in a large-scale multiple-input multiple-output system, and comprises the following steps: obtaining an angle-time delay domain channel state information matrix, performing feature embedding on the angle-time delay domain channel state information matrix through an initial feedforward network to obtain initial features; inputting the initial features into a multi-resolution convolution model and a multi-head sharpening attention model in parallel, respectively extracting multi-scale local features and long-distance dependent features, adaptively weighting and fusing the multi-scale local features and the long-distance dependent features through learnable weights to obtain fused features; converting the fused features into low-dimensional feedback code words through a feedforward network, an activation function and a compression mapping, and then adopting local uniform quantization segmentation processing to generate quantized code words, and feeding back the quantized code words to a receiving end to reconstruct channel state information. The application reduces the calculation complexity of channel feedback and quantization loss, and can realize low-latency and high-fidelity channel reconstruction on a resource-limited device.

The application relates to a feedback method for an intelligent metasurface time correlation cascade channel, comprising the following steps: S1, constructing a reconfigurable intelligent metasurface assisted multiple-input multiple-output communication system, comprising a base station, a reconfigurable intelligent metasurface and a single user terminal, determining a cascade channel model of the system, and establishing a cascade channel time-varying model; S2, constructing a channel state information compression and recovery network model based on deep learning, comprising an encoder and a decoder; after the user terminal obtains the cascade channel state information, the channel state information is compressed into code word information through the encoder, and after the base station receives the code word information, the code word is recovered into the cascade channel state information through the decoder. Compared with the prior art, the application solves the channel feedback problem of the time-varying cascade channel of the reconfigurable intelligent metasurface assisted multiple-input multiple-output system, has high information transmission accuracy, reduces the channel feedback overhead, has wide application scenarios, good applicability, lower complexity and better network performance.

The invention relates to the technical field of information interaction, and discloses a post-operation follow-up visit information interaction system supporting multi-channel feedback, which is used for solving the problem of multi-channel information conflict during multi-channel post-operation return visit, and comprises the following steps: performing multi-channel conflict identification on feedback data to identify conflict feedback data; conflict feedback content information of conflict fields in each piece of conflict feedback data is obtained, a priority integration index is obtained through evaluation according to the conflict feedback content information, final field feedback data is selected according to the priority integration index of the conflict fields in each piece of conflict feedback data, all conflict feedback data sets are traversed, and a final field feedback data set is obtained; and the final feedback data and the feedback data of the non-conflict fields are integrated to obtain feedback integration data, so that the accuracy of information integration of the post-operation follow-up visit system is effectively improved, and the nursing quality and the treatment effect of the patient are improved.

Methods, systems, and devices for wireless communications are described. For example, a user equipment (UE) may receive one or more reference signals from a base station. In some examples, the UE may receive the one or more reference signals over a channel for communications between the UE and the base station. The UE may measure a response of the channel based on the one or more reference signals received over the channel. In some examples, the UE may transmit a message indicating a set of channel coefficients. The set of channel coefficients may correspond to a two-dimensional (2D) model representative of the response. In some examples, the 2D model may include a spatial model and a time domain response of the channel.

Certain aspects of the present disclosure provides a method for wireless communication utilizing coordinated beamforming (CoBF). According to certain aspects, an apparatus (e.g., a non-AP STA) obtain a joint packet output simultaneously from a first wireless node and a second wireless node, wherein the first wireless node is associated with a first basic service set (BSS) and the apparatus and second wireless node are associated with a second BSS and the joint packet has a training field with one or more first spatial streams from the first wireless node and one or more second spatial streams from the second wireless node; generates channel feedback, based on the first spatial streams, for a first channel between the first wireless node and the apparatus; and provides the channel feedback to at least one of the first wireless node or the second wireless node.

Examples related to beam management in mobile communications are described. A user equipment (UE) measures a beamformed reference signal (RS) from a network node and determines channel information for at least one channel between the network node and the UE based on the beamformed RS and a predefined beamformer for transmitting the beamformed RS. The UE also determines channel feedback information related to the at least one channel according to the channel information about the at least one channel, and reports the channel feedback information to the network node.

This application provides a communication method, apparatus, access point, site, and system, belonging to the field of communication technology. In this method, different sets of communication parameters are used to send probe frames to a site to receive channel feedback information sent by the site. This channel feedback information indicates one or more of the following: air interface occupancy information, RSSI information of the probe frame, signal-to-noise ratio of the probe frame, or packet error rate of the probe frame. Based on this channel feedback information and the channel-related information of the site determined by the access point, the communication parameters used for communication with the site are determined, and these communication parameters are sent to the site to enable communication between the site and the access point. Thus, in determining the communication parameters, not only the channel-related information of the site detected by the access point is used, but also the channel feedback information of the site's received data is used, which is equivalent to obtaining the channel information of both the uplink and downlink channels. Therefore, the determined communication parameters are more suitable for the current operating environment, thereby improving network performance.

The application discloses a channel information compression feedback method using frequency division duplex channel implicit reciprocity. For the frequency division duplex channel information data with implicit reciprocity, the application firstly converts the spatial frequency domain channel matrix to the angle delay domain and performs clipping, and then splits and splices the real part and the imaginary part of the channel matrix into two real number matrices; three encoder networks are used for decoupling characterization learning of the downlink channel, and the downlink channel unique information, the uplink and downlink channel common information and the virtual uplink and downlink channel common information are extracted respectively; the decoder network recovers the original channel information by using the downlink channel unique information and the uplink and downlink channel common information during training, and recovers the original channel information by using the downlink channel unique information and the virtual uplink and downlink channel common information during testing; in the application, the user only needs to feed back the downlink channel unique information, the channel feedback load is effectively reduced, the channel information recovery performance is improved, and the application has a significant performance advantage.

The embodiments of the present application relate to the technical field of wireless communications. Provided are a channel information feedback method, and an electronic device and a computer-readable medium. The channel information feedback method comprises: performing channel estimation according to a first pilot signal sent by a first communication node, so as to acquire first channel information; according to the first channel information, determining a codebook set for quantized channel feedback; selecting an optimal codeword from the codebook set, wherein the optimal codeword is used for quantitatively characterizing the first channel information; and feeding back target instruction information to the first communication node, wherein the target instruction information is used for instructing the first communication node to determine the optimal codeword, and codewords in the codebook set conform to a corresponding model.

The information transmission method and the communication device provided by the embodiments of the present application relate to the field of communication. The method comprises the following steps: a terminal device can feed back coding information to a base station, wherein the coding information can be difference information between channel characteristic information obtained by the terminal device by measuring a reference signal at a time t and predicted channel characteristic information corresponding to the time t and obtained according to channel characteristic information corresponding to at least one time point before the time t. Correspondingly, after receiving the coding information of the difference information from the terminal device, the base station can decode the coding information to obtain decoded information, and recover the channel characteristic information of the time t according to the predicted channel information and the decoded information. In this way, the feedback amount of channel feedback can be reduced, the transmission resource can be saved, and the transmission efficiency can be improved without reducing the feedback performance.

The application discloses a communication transmission control method and system based on channel state feedback, and the method comprises the following steps: deploying a lightweight link sensing module on the terminal side, collecting link environment sensing data, classifying the channel characteristics of the link environment sensing data, and obtaining the channel characteristic type; constructing a differentiated compression feedback strategy double channel, matching and switching the channel characteristic type, determining the target channel feedback strategy channel; collecting channel state feedback data, selecting pre-coding for the channel state feedback data, and obtaining the base station side pre-coding matrix; based on the base station side pre-coding matrix and the link environment sensing data, the communication transmission scheduling is analyzed, the target communication transmission parameter is determined, and the communication closed-loop control is carried out through the target communication transmission parameter. The application achieves the optimal balance of feedback overhead, calculation complexity and system transmission performance, and can fully adapt to the communication transmission requirements of different mobile speeds and service types.

Various aspects of the present disclosure relate to methods, apparatuses, and systems that support error detection and correction in channel state information. For instance, implementations provide ways for utilizing attributes of channel feedback information (e.g., CSI) in encoding and decoding the channel feedback information. Implementations, for example, enable encoding and decoding of CSI where the CSI is represented using vectors such as singular vectors and / or eigenvectors. Further, implementations can utilize a channel covariance matrix for encoding and decoding CSI.

The application discloses a kind of intelligent channel state information feedback methods for intelligent metasurface wireless communication.First, construct the model RIS-CsiNet based on neural network, wherein the two encoders located at user end respectively compress and channel G between base station-intelligent metasurface and channel h between intelligent metasurface-user, two network modules are deployed at base station end, the first module input is the feedback information of channel h, output is the beamforming vector of base station and the phase shift of each unit in intelligent metasurface, in order to introduce the information of channel G into the design of base station end, its corresponding feedback information is input to super network, and the output is the network parameter of the last layer of the first network;Then, the model RIS-CsiNet is trained, and the user reachable rate is maximized;Finally, the trained RIS-CsiNet is used in communication system.The application can reduce the feedback overhead of intelligent metasurface assisted communication system, jointly carry out channel feedback and active / passive beamforming design, and reduce complexity.

The application discloses a power device self-current-sharing control system, which is used for controlling at least two parallel power devices in a parallel system and specifically comprises the following parts: a multi-channel feedback module, which is used for acquiring differential signals representing current imbalance states among the power devices in real time; a control unit, which is used for receiving the differential signals output by the multi-channel feedback module and generating a first group of control signals for controlling the turn-on or turn-off of the power devices and a second group of control signals for controlling the gate voltages of the power devices; at least one active gate drive module, which is connected between the control unit and the gates of the power devices, is used for receiving the first group of control signals and the second group of control signals; and based on the feedback of at least two gate voltages, the active gate drive module outputs dynamically adjustable differential drive signals to the power devices in a closed loop, thereby effectively realizing the self-current-sharing control of the power devices in the parallel system.

The invention relates to the technical field of document review, and particularly discloses a quality document self-adaptive review system and method. The system comprises a workflow and rule strategy configuration module which is used for constructing an examination strategy space; the input module is used for inputting a to-be-examined quality document; the task state sensing module is used for identifying a current input quality document and generating a task embedding vector; the multi-channel feedback generation module executes feedback from three channels of model evaluation, business income and manual review; the unified reward fusion module is used for performing unified calculation on the multi-dimensional feedback signals; the reinforcement learning strategy optimization and online self-calibration module is used for performing self-adaptive optimization of an examination strategy; the strategy updating and publishing module is used for updating the optimization strategy parameters to an examination strategy space; the document review module is used for executing a review process; and the output module outputs a review result. The method is oriented to the equipment manufacturing industry and the energy industry, and has the technical characteristics of self-adaptive optimization examination strategy and high intelligent degree.

The application relates to an adaptive voice semantic communication method based on hierarchical time sequence importance, and belongs to the voice analysis field, which comprises the following steps: a sending end divides a discrete feature matrix according to the priority of voice features and time sequence attributes, and filters the features according to the importance score in the feature matrix encapsulation and selection link; a channel adaptive scheduling module is interacted with wireless communication, a channel feedback mechanism is introduced, the current channel state information is perceived, and the transmission power and resource allocation strategy are dynamically adjusted; after signal demodulation is completed, a receiving end inputs the obtained sparse feature stream to a voice repair module, and global reconstruction is performed on the received features by using deep pre-trained voice prior knowledge. The application combines a hierarchical voice feature extraction technology based on a discrete codebook and a generative semantic repair technology, so that the voice word error rate in a severe channel environment is maximally reduced, and the semantic intelligibility of a receiving end is improved.

This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for updating a ML prediction module configuration in wireless communication systems. A UE (102) receives (204), from a network entity (104), a first indication of a first configuration for CSI prediction. The first configuration is associated with a first set of reference signals. The UE (102) receives (206), from the network entity (104), a downlink reference signal. The UE (102) transmits (208), to the network entity (104), a report for channel feedback based on the downlink reference signal. The report is associated with updating (211) to a second configuration for CSI prediction different from the first configuration for CSI prediction. The second configuration is associated with a second set of reference signals.

The application discloses an improved circuit of a PLL phase-locked loop based on a multi-channel feedback loop, and the whole PLL system circuit comprises a low-pass filter, a voltage-controlled oscillator, an improved high-order frequency divider, a multi-channel retiming circuit, a three-way frequency discriminator and a phase discriminator and a charge pump; the improved high-order frequency divider comprises an improved high-order modulator based on a traditional mash1-1-1 and a multi-mode frequency divider. The application multiplies a set fractional frequency division ratio by 4, takes the fractional part of the obtained result as the input of the mash1-1-1, adds the integer part and the output sequence of the mash1-1-1 to obtain a new output sequence, divides the new output sequence by 4, and converts the positive fractional part into a two-bit binary control code s<1:0>. The remaining integer is taken as the output of the modulator and added to the multi-mode frequency divider to control the change of the frequency division ratio. The multi-channel retiming circuit selects CK1 and CK2 generated based on the output clock of the voltage-controlled oscillator according to s<1:0>, the clock periods of the two clocks are different by 1Tvco, and the quantization step is reduced from 1*Tvco to 0.25*Tvco.

The invention discloses a data management method and device, electronic equipment and a nonvolatile storage medium. The method comprises the following steps: acquiring initial arrearage disassembly list data; according to a target screening rule, the initial arrearage disassembly list data are screened, candidate arrearage disassembly list data are obtained, the target screening rule is used for screening the initial arrearage disassembly list data according to the user attribute information and the arrearage information, and the target screening rule is determined by a plurality of basic condition factors; acquiring multi-channel feedback list data provided by a disassembly interface person, and verifying the candidate arrearage disassembly list data according to the multi-channel feedback list data; and according to the verified candidate arrearage disassembly list data, a disassembly work order is generated, and an execution result of the disassembly work order is determined. According to the method and the device, the technical problems of low data management efficiency and insufficient user service quality under the scene of arrearage and airport disassembly in the prior art are solved.

The invention relates to a channel feedback method and system, which is applied to a user side, and comprises the following steps: establishing a multi-cluster channel response matrix of a downlink channel, and carrying out decoupling processing on the multi-cluster channel response matrix to obtain a plurality of single-cluster responses; wherein each single cluster response comprises a plurality of path responses; for each single-cluster response, acquiring a peak position index in the single-cluster response, determining a target path response in the single-cluster response according to the peak position index, and performing phase compensation on all path responses in the single-cluster response according to the phase of the target path response to obtain a target single-cluster response corresponding to the single-cluster response; and obtaining an encoding processing result of the target single-cluster response corresponding to each single-cluster response, and sending each encoding processing result to the base station end to instruct the base station end to decode each encoding processing result to obtain a channel feedback result corresponding to the multi-cluster channel response matrix. According to the invention, the generalization of the channel feedback technology in different application scenes can be improved.

The application discloses a kind of equipment simulation training modeling methods for whole war position process, specifically relates to equipment simulation training process management field, for solving the problem that instruction disordered retransmission and multi-channel feedback gap or conflict coexist in whole war position collaborative training cause node to advance difficult to determine and lack of available evidence in review;By decomposing training process into training process nodes and generating process tokens binding node metadata for nodes, organize instruction delivery and feedback collection with process tokens, perform semantic regulation to generate semantic skeleton for inbound instruction, and conduct double-domain fingerprint comparison, map closure evidence with expected feedback closure structure and sequentially fuse to update replay decision coefficient, output decision results such as discard, merge, complete or derive new node, then assemble closure evidence to generate node completion proof according to process token and write into process evidence chain, realize node-level traceable modeling.

The invention discloses a self-diagnosis and analysis device for the running state of network equipment, and relates to the technical field of network communication. The device comprises a time sequence characteristic acquisition module which is connected to a console serial interface of target equipment, and a hardware counter is used for acquiring a time interval variance of physical level interruption so as to perceive time sequence entropy increase; the arbitration control module calculates an arbitration decision value based on nonlinear logic of logarithmic damping and index recovery, and triggers detection only when a safe cooling condition is met; the abnormal injection module responds to the trigger instruction, constructs a serial number border-crossing transmission control protocol confirmation message and sends the message to the target device; and the state judgment module monitors physical and network dual-channel feedback to confirm the kernel deadlock state. According to the method, kernel-level reverse verification is triggered through physical layer side channel characteristics, resource consumption of high-load equipment caused by periodic detection is avoided, and accurate judgment of the kernel deadlock state is achieved.