58 results about "Channel correlation" patented technology

A method and apparatus may collect information related to dynamically allocating an optimal channel for a plurality of wireless networks. The plurality of wireless networks may be grouped together based on one or more criteria. A channel allocation may be determined based on one or more factors, including an assessment of an optimization algorithm.

A communication device includes a processor, a primary radio, a scanning radio, and a storage device. The primary radio provides wireless communication services to one or more client devices in a radio frequency (RF) environment and manages the wireless communication services to comply with a predetermined wireless network protocol. The scanning radio scans a plurality of channels provided in the RF environment in one or more frequency bands to comply with the predetermined wireless network protocol. The storage device stores calibration data associated with the plurality of channels. The predetermined wireless network protocol is a Wi-Fi protocol. The primary radio is a Wi-Fi access point (AP) chipset and the scanning radio is a Wi-Fi client chipset.

This application provides a communication method and a communication apparatus. The method may include: a first apparatus receiving first indication information from a second apparatus, the first indication information being used to instruct the first apparatus to transmit a precoding of a first reference signal, the precoding of the first reference signal being associated with channel-related information of multiple first apparatuses served by the second apparatus. In this method, the precoding of the first reference signal transmitted by a terminal device may be indicated by a network device, and the precoding is associated with channel-related information of multiple terminal devices served by the network device. Therefore, the network device can determine the precoding of the first reference signal based on the channel-related information of the multiple terminal devices served by the network device. Through the design of the precoding by the network device, the first reference signal transmitted by each terminal device can be distinguished during transmission. Based on this, pilot interference between the first reference signals of different terminal devices can be avoided, and the accuracy of channel measurement can be improved.

The application relates to the technical field of industrial Internet of Things, and discloses a multi-channel time sequence data error bound quantification method and system based on dynamic graph grouping and error distribution, which comprises the following steps: S1: acquiring multi-channel time sequence data collected at the same collection point; S2: determining a scale factor, a point-by-point maximum absolute error upper bound, normalized channel time sequence data, and normalized error bounds of all channels; S3: calculating correlation measurement values of any two channels, and constructing a channel correlation graph; S4: determining a grouping threshold value, and forming an anchor point set from selected anchor point channels; S5: constructing a cross-channel correlation prediction model, and constructing an innovation sequence; S6: determining an error sensitivity coefficient, and determining a quantified error bound; S7: obtaining normalized reconstruction values of the anchor point channels and the innovation sequence; and S8: obtaining normalized reconstruction values of non-anchor point channels, and performing inverse normalization on the normalized reconstruction values according to the scale factor to obtain reconstruction values of the channels under the original dimension. The application can limit compress and highly restore original data.

This invention discloses a multi-channel electromagnetic induction detection method and system based on uniform magnetic field constraint. A uniform magnetic field is constructed within the detection area of ​​the structure under test. Electromagnetic induction response signals are acquired through multiple channels under the constraint of the uniform magnetic field, and the spatial coordinates of each acquisition channel are marked. The raw electromagnetic induction signals acquired by each channel are preprocessed, including noise reduction filtering, envelope extraction, and amplitude normalization. A deep learning model is then used to extract structural features from the preprocessed multi-channel electromagnetic response signals. Based on the spatial position information of each acquisition channel, magnetic field uniformity parameters, and response characteristics, a channel correlation weight matrix is ​​constructed to describe the spatial consistency and physical coupling relationships between channels. A multi-channel joint optimization model is constructed, and the equivalent electromagnetic parameter distribution inside the structure under test is reconstructed through iterative solution. This invention improves the reliability, repeatability, and engineering applicability of electromagnetic induction detection results.

In an electronic device and an operating method thereof according to an embodiment, the electronic device may include a communication circuitry supporting short-range wireless communication and neighbor awareness network (NAN) communication; a memory storing at least one computer program; and at least one processor. The at least one computer program may include instructions that cause, when executed by the at least one processor individually or collectively, the electronic device to connect to a first access point (AP) through a non-dynamic frequency selection (non-DFS) channel, transmit, to an external electronic device, a first service discovery frame including information related to a DFS channel and information indicating a maximum bandwidth supportable by the electronic device, in a process of discovering the external electronic device to be connected via an NAN data path (NDP), connect to a second AP supporting the DFS through the DFS channel while maintaining a connection between the first AP and the electronic device, upon identifying, based on a second service discovery frame received from the external electronic device, that the external electronic device supports the DFS and a maximum bandwidth supportable by the external electronic device is greater than a bandwidth of the non-DFS channel, establish the NDP with the external electronic device, based on the first service discovery frame and / or the second service discovery frame, and perform NAN communication with the external electronic device, based on first schedule information related to performing the NAN communication through a frequency band of the non-DFS channel and a frequency band of the DFS channel. The first schedule information may enable the external electronic device and the electronic device to perform the NAN communication through the frequency band of the non-DFS channel and the frequency band of the DFS channel during a first period between discovery windows.

A method is disclosed of selecting users for multi user multiple-input multiple-output (MU-MIMO) communication from an initial set of potential users. The method comprises repeating the following steps in successive iterations until a stopping criterion is met: determining a channel correlation metric for each user in the set of potential users, reducing the set of potential users by exclusion of a user based on the channel correlation metric, and calculating a performance metric of the set of potential users. The method also comprises selecting users corresponding to one of the sets of potential users, wherein the selection is based on a comparison of the calculated performance metrics of the sets of potential users. The channel correlation metric for a user may comprise one or more of: a channel filter norm for the user, a channel norm for the user, a channel gain for the user, pair-wise correlations between the user and one or more other users of the set of potential users, and a channel eigenvalue for the user. The performance metric may comprise one or more of: a sum-rate, a per-user-rate, an average error rate, a maximum error rate, a per-user error rate, and a sum-correlation. Corresponding apparatus, network node and computer program product are also disclosed.

The present application relates to a kind of time series prediction methods under multi-scale double clustering, the present application can simultaneously capture the data pattern and relevance under different time scales by multi-scale input mechanism, improve the modeling ability to complex real-world signal.Effective decoupling and modeling TDS and CCT: by parallel patch intra-domain clustering module and mask attention module, respectively, special modeling is carried out on two core challenges of time distribution drift and channel correlation conversion, avoids causal confusion, and improves the robustness and generalization ability of the model.The model carries out twice dynamic, hybrid expert-based dependency filtering at patch level, can accurately capture instantaneous and time-varying correlation, avoids the information loss or noise interference caused by traditional coarse-grained or static dependency modeling.

The application discloses a kind of based on deep manifold's electroencephalogram motor intention decoding method, system and device, it is related to brain-computer interface technical field.The method includes the following steps: obtaining original motor imagery electroencephalogram signal, and motor imagery electroencephalogram signal is preprocessed and feature extraction;Utilize spatial attention mechanism under the premise of keeping manifold geometric structure to the electroencephalogram channel correlation is weighted, then from time and spatial dimension respectively to the weighted covariance matrix sequence is mixed with information, simultaneously utilize symmetric positive definite residual link to retain underlying geometric information, obtain high-level geometric feature;Utilize tangent space mapping to convert high-level geometric feature to Euclidean space, and obtain the recognition result of motor imagery by classifier.The application can realize the adaptive weighting of electroencephalogram channel importance, can also retain electroencephalogram geometric feature while aggregating electroencephalogram time information, improves the robustness and accuracy of electroencephalogram decoding.

Some aspects of the present disclosure provide techniques for user equipment (UE) autonomous sidelink resource selection. A method that can be performed by a UE includes performing autonomous sidelink resource selection. The selection includes excluding, from a first set of resources, resources associated with transmissions having a signal strength above a signal strength threshold to form a second set of resources. The selection includes determining an amount of resources in the second set of resources is equal to or above a threshold percentage of an amount of resources in the first set of resources. The selection includes excluding, from the second set of resources, resources associated with a physical sidelink control channel (PSCCH) without excluding resources associated with a physical sidelink shared channel associated with the PSCCH to form a third set of resources. The selection includes randomly selecting a resource for a PSCCH transmission from the third set of resources. The method includes transmitting the PSCCH transmission using the randomly selected resource.

Disclosed in the present application are a communication method and a communication device. The method comprises: a first device sending first information to a second device, wherein the first information is configured to indicate channel information of a first uplink channel and / or channel information of a first downlink channel, and the first uplink channel is associated with the first downlink channel. In the embodiments of the present application, first information is introduced, the first information being configured to indicate channel information of a first uplink channel and / or channel information of a first downlink channel, which is conducive to the exchange of channel-related information between a first device and a second device, thereby improving the communication efficiency.

Methods, systems, and devices for line of sight (LOS) multiple input multiple output (MIMO) signaling aspects for wireless communication. A wireless device may transmit, to a network device, a capability message indicating that the wireless device supports a LOS mode. The wireless device may receive, from the network device in response to the capability message, a control message indicating activation of the LOS mode and at least one LOS mode parameter based at least in part on a channel measurement associated with a wireless channel between the wireless device and the network device indicating that the wireless channel satisfies a LOS path criterion. The wireless device may communicate a message with the network device in accordance with the LOS mode parameter.

This invention discloses a wireless telemetry transmission system with time-series synchronous encoding of multi-channel monitoring signals. A multi-source acquisition module collects multiple monitoring signals along the flood control wall of an urban waterfront space, including water level, wall seepage pressure, wall displacement, the status of the electrically controlled locks on flood control material storage seats, and the in-situ status of flood control components. A time-window synchronous encoding module uses water level change trigger points as the primary trigger reference, and combines seepage pressure response lag, wall displacement changes, and wireless link feedback delay to generate dynamic monitoring time windows. This generates time-series synchronization and cross-channel correlation for the multiple signals, forming a status combination data set and encapsulating it into a telemetry synchronous encoding frame. A wireless telemetry transmission module adjusts the transmission strategy according to linkage priority. A remote parsing and restoration module generates flood control risk levels and material activation determination results. A material linkage module activates the electrically controlled locks on the storage seats and outputs a flood control component assembly prompt, thereby improving the timeliness and reliability of flood control wall monitoring, transmission, and emergency response.

This invention discloses a physical layer key generation method and system based on a polarization-reconfigurable antenna, belonging to the field of wireless communication technology. The method includes: establishing a polarization channel model jointly considering polarization correlation, spatial correlation, and channel depolarization effects, and deriving a closed-form expression for the key generation rate; constructing a joint optimization problem of beamforming vector and PRA phase shift vector under base station transmit power constraints and antenna phase modulation constraints, with the goal of maximizing the key generation rate; solving the problem using an alternating optimization method to obtain the optimal beamforming solution based on the Rayleigh quotient and the analytical closed-form solution for polarization phase modulation jointly determined by the polarization channel correlation coefficient, inverse cross-polarization discrimination, and receiver polarization vector. This invention requires no additional RF link, has low hardware complexity, effectively mitigates performance loss caused by polarization mismatch, and significantly improves key generation efficiency and system security in complex polarization environments.

This invention belongs to the field of medical monitoring image processing technology, and discloses a method and system for comparative analysis of multi-channel drainage fluid characteristics images. The method includes: a multi-channel synchronous acquisition step, in which multiple drainage fluid acquisition terminals are controlled by a central processing unit to synchronously acquire image data and perform time alignment; a color feature extraction step, in which image color features are mapped to a standardized chromaticity coordinate system; a multi-channel comparative analysis step, in which chromaticity differences are calculated and color change trends are compared; a dual-mode anomaly detection step, in which single-channel longitudinal change detection and multi-channel lateral correlation detection are performed; and a report generation and output step, in which a comprehensive monitoring report is generated. This invention solves the problems of existing technologies that cannot simultaneously monitor drainage fluid from multiple tubes and lack cross-channel correlation analysis capabilities.

A communication device includes a processor, a primary radio device, a scanning radio device and a memory device. The primary radio device provides a wireless communication service to one or more client devices in a radio frequency (RF) environment and manages the wireless communication service in compliance with a predetermined wireless network protocol. The scanning radio device scans a plurality of channels in one or more frequency bands provided in the RF environment in compliance with the predetermined wireless network protocol. The memory device stores calibration data associated with the channels. The predetermined wireless network protocol is a Wi-Fi protocol. The primary radio device is a Wi-Fi access point chipset and the scanning radio device is a Wi-Fi client chipset.

Various aspects of this disclosure relate to a method and apparatus for supporting data collection. An exemplary method performed by a UE includes: receiving a PRS based on configuration information associated with PRS reception; reporting channel-related information based on at least one PRS received at a PRS timing, wherein the channel-related information includes: timing information, power information, amplitude information, phase information, or any combination thereof; and reporting location-related information, wherein the location-related information includes: location information, Doppler information, time difference information based on the at least one PRS, RTT information based on the at least one PRS, RSRP information based on the at least one PRS, carrier phase information based on the at least one PRS, or any combination thereof; wherein the channel-related information is associated with the location-related information based on a first time instance associated with the PRS timing and a second time instance associated with the location-related information.

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.

This invention discloses a cross-subject EEG signal classification method based on channel correlation reconstruction. The steps include: 1. Preprocessing EEG signal data from subjects in multiple source domains to form a source domain dataset; 2. Building a neural network model; 3. Randomly selecting mini-batch samples from the source domain data during training; 4. Reconstructing the mini-batch samples using a data augmentation method based on channel correlation reconstruction; 5. Using the reconstructed samples as input to the model to update the model parameters until convergence. This invention enhances the diversity of source domain data through a data augmentation method based on channel correlation reconstruction, thereby improving the domain generalization ability of the cross-subject classification model and enhancing its cross-subject classification performance on new subject data, thus promoting the real-world application of brain-computer interfaces.

The present disclosure relates to a 5th generation (5G) or pre-5G communication system for supporting a higher data transmission rate than a 4th generation (4G) communication system such as long-term evolution (LTE). Disclosed is a method performed by a terminal that may comprise: receiving configuration information for a CSI report from a base station; acquiring a channel quality indicator (CQI) table on the basis of the configuration information for the CSI report; and transmitting CSI including a CQI according to the CQI table to the base station, wherein the CQI table is configured on the basis of a first CQI table of a case where transport block error probability is 0.1 and a second CQI table for a case where transport block error probability is 0.00001. The method performed by the terminal may further comprise: receiving configuration information relating to a physical uplink shared channel (PUSCH) or a physical downlink shared channel (PDSCH) from the base station; identifying a modulation and coding scheme (MCS) table on the basis of the configuration information relating to the PUSCH or PDSCH; and acquiring a transport block size (TBS) on the basis of the MCS table, wherein the MCS table is configured on the basis of a first MCS table configured by default and a second MCS table configured for low spectral efficiency (SE) in the base station.

The application provides a ship noise sequence generation method based on frequency domain mask guided diffusion, multi-granularity frequency information is constructed by introducing a frequency domain random mask to guide the diffusion process, thereby improving the quality and diversity of the generated samples. Traditional diffusion methods usually rely on complete initial information for generation, and less explore the use of incomplete intermediate information as guidance. Existing methods mostly use time domain fixed filters to construct multi-granularity data as intermediate information, but ignore the randomness of the data, limiting the flexibility and diversity of the generation process. Therefore, the application proposes to apply a random mask in the frequency domain to construct multi-granularity guide information as intermediate information to guide diffusion, and combine the correlation coefficient matrix embedding as a condition to supplement, to supplement the channel correlation information lost due to the mask operation.

This application belongs to the field of twisting equipment control technology, and particularly relates to an adaptive control system for the operating state of twisting equipment. The system includes: acquiring operating signals from the twisting equipment; constructing a state observation sequence using a sliding window and extracting phase lag, vibration envelope skewness, tension gradient, spectral energy difference, sign change density, and multi-channel correlation disorder; dividing the operating state to establish a discrete state set; statistically analyzing the dwell length of each discrete state to construct a semi-Markov transfer model; combining the winding diameter range and tension gradient with piecewise correction to obtain a time-varying state transfer model; adjusting the prediction time domain length based on the expected remaining dwell time of each discrete state; predicting future state paths and solving the objective function to obtain the control increment; and outputting the control increment to the actuator to complete the operating state control. This application can improve the adjustment accuracy and reliability of the operating state control of twisting equipment.

The application discloses a semi-dynamic scheduling method based on time-varying frequency hopping. For DL SPS and UL CG services, a base station introduces a semi-dynamic scheduling mechanism, taking a Hopping Pattern four-tuple model as the core, to jointly control time domain, frequency domain, space domain and MCS. The base station predicts CSI, beams and QoS based on an AI / ML module, autonomously decides whether to update the Hopping Pattern, and can classify UEs with weak channel correlation into the same multicast group for unified distribution, to realize space division multiplexing and free hopping of intra-group UEs in a frequency domain resource pool. The Hopping Pattern is carried by a semi-dynamic scheduling SDS dedicated MAC CE, a bitmap is used to indicate the hopping dimension on demand, and the semi-dynamic scheduling overhead is reduced. After receiving the SDS dedicated MAC CE, a UE performs multi-dimensional resource hopping from a specified period, and uses the latest valid Hopping Pattern before receiving a new indication.

Systems, methods, and devices improve medium usage by wireless devices. Methods include determining, using one or more processing elements, a wireless channel switch operation should be performed by a first wireless device and a second wireless device communicating using a first wireless channel, and identifying, using the one or more processing elements, one or more mitigation operations based on data packet activity associated with the wireless channel. Methods further include generating, using the one or more processing elements, a mitigation signal responsive to identifying medium reservation activity within the data packet activity, and initiating, using the one or more processing elements, the wireless channel switch operation to switch to a second wireless channel.

This application proposes a channel measurement method, apparatus, terminal, chip, and storage medium, relating to the field of communications. The method includes: performing channel estimation based on CSI-RS to obtain a target channel estimation result; determining an equivalent channel correlation matrix and channel quality metric parameters for at least one precoding matrix based on the target channel estimation result; classifying channel correlations based on the equivalent channel correlation matrix, channel quality metric parameters, and communication configuration parameters of the communication scenario in which the CSI-RS is located, obtaining a classification result; wherein the classification result is used to indicate the spatial correlation of the communication channel corresponding to the precoding matrix. Therefore, it eliminates the need for pre-discretization of the communication scenario or manually setting a universal threshold, avoiding correlation judgment bias caused by overly coarse scenario division granularity or insufficient threshold adaptability. This allows the classification result to adapt to the dynamic changes of the actual channel environment, significantly improving the accuracy and robustness of channel spatial correlation identification.

Disclosed is a method comprising receiving a first reference signal transmission associated with a radio channel, predicting future conditions of the radio channel based at least partly on the first reference signal transmission, receiving one or more verification tones associated with the radio channel, and determining, based at least partly on the one or more verification tones, an estimation error associated with the predicted future conditions of the radio channel.

A wireless communication method, apparatus, device, and storage medium relate to communication technology. The method includes: a terminal device receiving first configuration information sent by a network device in a first cell, the first configuration information including configuration information related to a paging channel (510); and the terminal device listening for a paging channel in a second cell according to the first configuration information (520). This method enables the terminal device to obtain paging messages through the second cell even when the first cell does not send a paging channel. In other words, by enhancing the paging mechanism, network device power consumption can be saved while ensuring network communication performance.

The application provides a channel parameter determination method, device, equipment and system, and belongs to the technical field of wireless communication. In the method, an access point collects channel related information of a station, uses the channel related information and an AI model to determine and issue channel parameters used by the access point and the station when communicating to the station to the station. In this way, the channel related information is closely related to the channel parameters, the AI model can directly determine all the channel parameters using the channel related information without iteration, so that the channel parameters can be quickly obtained, and the efficiency of determining the channel parameters is improved.

A WTRU monitors a sidelink (SL) channel for communicating with a second WTRU in unlicensed SL mode-1 and collects SL assistance information relating to the SL channel. The WTRU transmits to a base station, over an unlicensed Uu band, one or more of a SL scheduling request (SR) or a SL buffer status report (BSR) and the SL channel assistance information. The WTRU receives downlink control information (DCI) from the base station indicating SL resource scheduling, performs listen-before-talk (LBT) on the SL channel associated with the indicated SL resource scheduling and sends a transmission: (1) to the base station, on a condition LBT is unsuccessful, at least one of indication of LBT failure or a request for new SL resource scheduling; or (2) to the second WTRU, on a condition LBT is successful, SL data using the indicated SL resource scheduling. Additional embodiments are disclosed.

This invention discloses a method and device for industrial robot streaming anomaly detection based on dynamic graph-enhanced normalized flow, belonging to the interdisciplinary field of industrial control and artificial intelligence. Addressing the problems of high latency and difficulty in capturing cross-sensor dynamic dependencies caused by existing flow-based models relying on offline full-trajectory evaluation, this invention employs a fixed-length sliding window to perform online partitioning of high-frequency multi-channel sensor data. A dynamic graph enhancement module is introduced into the coupled sub-network of the normalized flow to adaptively calculate channel correlations within the current window, constructing a soft adjacency matrix and jointly extracting local temporal patterns and dynamic cross-sensor dependencies. Finally, a Causal-Max strategy is used, combining causal smoothing and maximum value extraction, to convert window-level scores into stable trajectory-level anomaly scores. This invention achieves low-latency, low-resource-consumption online anomaly early warning, significantly improving the accuracy of multivariate temporal anomaly detection in complex industrial environments.