1989results about "Channel estimation" patented technology

The invention discloses a pilot optimization method for large-scale MIMO channel estimation based on structural compressed sensing. The method comprises the steps of establishing a channel estimation model for a large-scale MIMO-OFDM (Multiple-Input-Multiple-Output-Orthogonal Frequency Division Multiplexing) system when pilots are placed in an overlapping mode; simplifying the channel estimation model for the large-scale MIMO-OFDM system, thereby enabling the channel estimation model to correspond to a structural compressed sensing model; and obtaining an optimum pilot matrix through utilization of a pilot optimization algorithm. Through adoption of the optimum pilot matrix, according to the channel estimation of the large-scale MIMO system based on structural compressed sensing, the mean square errors MSEs of the channel estimation are clearly reduced, and the channel estimation performance is improved.

A reconfigurable intelligent surface (RIS) includes one or more radio frequency identification (RFID) tags. The one or more RFID tags may perform functions of a controller of the RIS. The one or more RFID tags receive a reference signal from a wireless communications device. The RIS may process the received reference signal and the one or more RFID tags backscatter a response signal to the wireless communications device. The wireless communications device may also perform processing of the backscattered response. Processing includes measuring channels from the wireless communication to the RFID tags. Processing also includes estimating channels from the wireless communication to elements of the RIS. Based on the estimated channels, a beam matrix corresponding to optimized weights of the RIS elements is determined and transmitted to the RIS.

A system and method of targeting spatialized audio to ears of a listener, comprising sensing characteristics of an environment comprising at least one human by receiving radio frequency signals with a radio receiver; using the sensed characteristics in at least one automated processor to analyze at least one human dynamic physiological pattern of each human and estimate a body pose and head position within the environment of each human based on the sensed characteristics and the at least one human dynamic physiological pattern; and using an estimated position of the ears of each human in conjunction with a head-related transfer function in a spatial audio system to generate spatialized audio.

The apparatus may be a wireless device configured to estimate, for a first transmission in a first slot, a first channel associated with the first transmission, wherein the first transmission is associated with a first precoding, receive, in a second slot following the first slot, a second transmission associated with a second precoding, and estimate, based on the received second transmission and at least one of the received first transmission or the estimated first channel, a second channel associated with the second transmission.

The invention provides an Internet of Vehicles broadcast frame radio frequency fingerprint identification method based on LMMSE channel estimation. The method comprises the following steps: obtaining subcarrier data in a resource grid based on an obtained signal of a physical side link broadcast channel; performing root-mean-square delay expansion and channel autocorrelation matrix construction based on the subcarrier data, and combining priori signal-to-noise ratio regularization and time domain windowing operation to obtain a channel estimation value; initial radio frequency fingerprint features are obtained through the channel equalization and the channel estimation value, and the improved neural network and the initial radio frequency fingerprint features are utilized to carry out classification identification on the Internet of Vehicles equipment. Influences of noise and channels on fingerprints are effectively considered, and the purpose of extracting fingerprints of different devices in a complex environment more accurately is achieved.

The invention relates to a channel estimation method based on frequency domain deviation compensation and dynamic DCT denoising, and belongs to the technical field of wireless communication. The method comprises the following steps: establishing a wireless channel model and an OFDM system model; estimating the frequency offset in the received signal by using the phase rotation characteristic of the pilot signal; calculating a preliminary channel frequency domain response # imgabs2 # at a pilot frequency position through a least square criterion based on the compensation signal # imgabs1 #; obtaining a receiving pilot frequency signal # imgabs4 # according to the sending pilot frequency Xp and the roughly estimated channel frequency response # imgabs3 #; estimating a current signal-to-noise ratio SNRest based on the pilot frequency signal # imgabs5 # and a noise power ratio; and establishing an adaptive DCT denoising strategy based on a signal-to-noise ratio threshold, and selecting different denoising strategies according to different signal-to-noise ratios to perform denoising processing on # imgabs6 # to obtain final channel estimation # imgabs7 #. The adaptive denoising strategy design of the invention effectively balances the relationship between noise suppression and channel structure fidelity, and improves the precision and stability of overall channel estimation.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a signal processing method, device, equipment and medium based on mixed experts. And generating routing information based on the channel information, dynamically fusing expert output, generating a first task processing result by using the first task processing network, generating a second task processing result by using the second task processing network, jointly optimizing all network parameters, and generating a hybrid expert model for a to-be-processed signal. According to the method, the hybrid expert architecture aiming at the multi-channel characteristic is introduced, and the gating network is combined to dynamically allocate the characteristic processing path, so that the self-adaptive optimization aiming at different channel environments is realized, the accuracy of cross-channel identification and the resource utilization efficiency of the whole model are effectively improved, and the robustness of the cross-channel identification is improved. And high-precision, high-robustness and efficient signal identification can be realized in a complex and changeable environment.

The invention is suitable for the technical field of unmanned aerial vehicle information transmission, and provides a self-adaptive multi-unmanned aerial vehicle information transmission system and method based on channel estimation, and the system comprises a channel modeling module, a communication scheduling module, a topology control module and a terminal sensing layer. The channel modeling module is used for estimating and predicting a wireless link state in a complex environment in real time through an improved Kalman filtering method; the communication scheduling module constructs a transmission decision module based on a reinforcement learning strategy, and realizes joint dynamic optimization of a communication link and a task execution path by introducing a Q-learning algorithm; the topology control module introduces a multi-objective optimization strategy based on a utility function to realize dynamic reconstruction of the network topology; the terminal sensing layer is used for multi-unmanned aerial vehicle distributed cooperative detection and multi-modal sensing data fusion; according to the invention, the edge collaborative fusion perception of multiple unmanned aerial vehicles replaces the traditional single-point detection, and the target recognition precision and the shielding robustness are significantly improved.

A communication device for providing a channel state information, CSI, feedback in a wireless communication system includes a transceiver to receive, from a transmitter a radio signal via a time-variant, frequency-selective MIMO channel, the radio signal including downlink reference signals according to a reference signal configuration including a number of antenna ports, and downlink signals including the reference signal configuration; and a processor. The processor estimates an explicit CSI in the frequency domain using measurements on the downlink reference signals on the radio channel, selects a Doppler-delay precoder matrix (W) for a composite Doppler-delay-beam three-stage precoder, calculates either one or more of a channel quality indicator, CQI, and / or a precoder matrix indicator, PMI, and / or a rank indicator, RI, and reports to the transmitter the CSI feedback including either one or more of the CQI, and / or the PMI and / or the RI.

A method of MIMO channel estimation is provided that involves the transmission of MIMO reference signals that use a non-uniform pattern of resources in space, time, frequency, and / or code and is calculated from a prior knowledge. The prior knowledge is obtained from a plurality of MIMO channel samples associated to a region. In a receiver, MIMO reference signal are received based on a receiver-MIMO-reference-signal-placement is also a non-uniform pattern of resources in space, time, frequency, and / or code and is calculated from the prior knowledge. A MIMO channel is estimated from channel measurement on the reference signals and the prior knowledge.

The invention belongs to the technical field of information and communication, and relates to an active user detection and data decoding method of an asynchronous massive machine type communication system. Aiming at the problem that the detection and estimation performance is reduced due to unknown user time delay in asynchronous transmission, the method comprises the following steps: initial estimation and preprocessing: detecting initial active users and transmission time delay thereof through correlation peaks, and whitening received signals; the iterative joint detection and channel estimation module is used for iteratively updating channel information and data symbol information for multiple rounds based on a factor graph and a message passing algorithm; the data decoding module is used for decoding data based on a soft decision device; the detection and decoding performance is improved by transmitting external information among the modules; and the time delay parameter updating adopts a greedy search algorithm to obtain the optimal time delay. According to the method, the active user detection rate, the channel estimation precision and the data decoding accuracy under the condition that the receiving and transmitting ends are completely asynchronous are improved.

The present disclosure relates to a 5G communication system or a 6G communication system for supporting higher data rates beyond a 4G communication system such as long term evolution (LTE). The present disclosure provides a method performed by a second node in a communication system, comprising: receiving first configuration information for first data from a first node; obtaining first predicted data signals of various layers of the first data based on the first configuration information; determining a first set including the first predicted data signal of at least one layer of the various layers and a second set including the first predicted data signals of one or more layers of multiple layers based on an accuracy of the first predicted data signals of the various layers; obtaining a third set based on the first configuration information and the first set, wherein the third set includes second predicted data signals corresponding to the one or more layers; obtaining a fourth set based on the second set and the third set, wherein the fourth set includes third predicted data signals corresponding to the one or more layers; obtaining soft bits of the first data based on the first set and the fourth set.

The invention provides an unmanned aerial vehicle dual-polarized antenna multipath interference suppression and polarization mismatch joint optimization algorithm, and relates to the technical field of low-altitude communication, and the algorithm carries out the coupling modeling of a multipath interference problem and a polarization mismatch problem through building a unified dual-polarized channel model which considers multipath propagation and time-varying polarization characteristics; an adaptive polarization state estimation method based on received signal covariance matrix feature analysis is provided; a combined space-time-polarization domain adaptive filter structure is designed; a joint optimization objective function containing a minimum mean square error and a maximum polarization matching degree (MPM) is constructed; a low-complexity adaptive weight updating rule based on a recursive least square (RLS) thought and integrated with polarization constraints is deduced. According to the algorithm, interference suppression and polarization matching are collaboratively optimized through a unified framework, the complexity is reduced by adopting recursive calculation, rapid convergence and strong environmental adaptability are realized, and the low-altitude communication performance of the unmanned aerial vehicle is remarkably improved.

The invention discloses an inter-body area network and intra-network joint optimization interference mitigation method based on channel prediction, which comprises the following steps of: firstly, predicting channel quality between each node and a coordinator in a body area network under different frequencies by using an autoregression model, classifying the body area network according to neighbor information among the body area networks, and dividing the channel quality of each node in the body area network according to neighbor information; secondly, distributing channels with different frequencies to various body area networks according to the principle of maximizing the average signal receiving strength of the nodes so as to avoid inter-network interference; in each body area network, the number of required time slots is calculated according to the service volume of each node, and when the number of time slots is not enough, the number of time slots of the nodes is reduced according to the principle that the total utility of the nodes is maximized; and then, according to the predicted channel quality condition of the nodes in the network under the allocated frequency, allocating time slots to the nodes by taking the minimum average packet loss probability as a principle. The method provided by the invention can be used for the scene of coexistence interference of the semi-dynamic body area network, and inter-network and intra-network interference can be avoided.

The present application provides a channel estimation method and a related apparatus, improving the accuracy of channel estimation. The method comprises: a terminal device receiving a first signal, the first signal being a signal received by the terminal device after a second signal sent by a network device passes through a wireless channel; receiving first information, the first information being used for indicating a first channel estimation parameter, and the first channel estimation parameter including at least one of the following: a matrix norm of a first expression and an iteration step size, wherein the first expression is determined by a precoding matrix, the first signal, and a kth channel estimation value, at least one of the matrix norm and the iteration step size is determined on the basis of the precoding matrix, k is a positive integer less than or equal to T, T is a positive integer, and T is the number of iterations of channel estimation; and on the basis of the first signal and the first channel estimation parameter, performing channel estimation T times to obtain a channel estimation result.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive configuration information for a sounding reference signal (SRS) resource set, the configuration information indicating a usage type for the SRS resource set associated with Doppler tracking and a configuration for one or more associated SRS resource identifiers. Some configuration parameters of the SRS resource set and the associated SRS resource identifiers can be dynamically reconfigured in order to allow adaptive SRS time domain pattern for enhanced Doppler parameter estimation and / or synchronization loop tracking, among other examples. The UE may transmit one or more SRSs in accordance with the configuration or dynamic reconfiguration information for the SRS resource set and the associated SRS resources based at least in part on receiving the configuration and / or reconfiguration information. Numerous other aspects are described.

A one way ranging method estimates a distance between first and second wireless devices using a technique that involves exchanging dual tone RF signals between the devices and, at each of the first and second devices, maintaining “baseband coherence” between baseband signals carried by the RF signals transmitted and received by each respective device.

The invention relates to a satellite network semantic communication method based on reliable joint source channel coding. The satellite network semantic communication method comprises a signal transmitting method and a signal receiving method. The method comprises the following steps of: 1, extracting features of an image by utilizing a Vision Transform model to obtain semantic representation of the image; 2, constructing a channel estimation and joint loss function; 3, encoding the semantic representation in the step 1 by using a joint source channel encoder and combining the channel estimation in the step 2 and the joint loss function; 4, NOMA power distribution is carried out on the coding result in the step 3, and the coding result is transmitted through a wireless link; the signal receiving method comprises the following steps: step 5, a receiving end receives a signal transmitted in step 4 from a link; and 6, recovering the original user data from the noise by using a joint source channel decoder. According to the method, the semantic information is extracted from the image by using the pre-trained Vision Transform model, so that the amount of data to be transmitted is remarkably reduced, and meanwhile, the communication efficiency is kept.

A method for reporting channel status information (CSI) is performed by a terminal. The method includes: transmitting an uplink reference signal to a network device; receiving beamformed downlink pilot signals transmitted by the network device at T consecutive time points; estimating downlink effective channel information corresponding to the T consecutive time points according to the beamformed downlink pilot signals of the T consecutive time points; determining CSI corresponding to the T consecutive time points according to the downlink effective channel information corresponding to the T consecutive time points; and reporting the CSI to the network device.

The present disclosure provides a method performed by a second node in a communication system, the method comprising: receiving first configuration information for first data from a first node; obtaining a first prediction data signal of each layer of the first data based on the first configuration information; determining a first set comprising the first prediction data signals of at least one of the layers and a second set comprising the first prediction data signals of one or more of the layers based on the accuracy of the first prediction data signals of the layers; obtaining a third set based on the first configuration information and the first set, the third set comprising second prediction data signals corresponding to the one or more layers; obtaining a fourth set based on the second set and the third set, the fourth set comprising third prediction data signals corresponding to the one or more layers; and obtaining soft bits of the first data based on the first set and the fourth set.

Methods, systems, and devices for wireless communications are described. A wireless communication device may receive a communication signal that includes multiple layers. The signal may include at least one layer that is associated with a probabilistic shaping signal. The wireless communication device may apply one or more probabilistic shaping parameters to the communication signal and obtain a preprocessed signal. The application of the one or more probabilistic shaping parameters may include performing one or more matrix decomposition operations to obtain the preprocessed signal and a preprocessed channel estimate. The preprocessed signal and the preprocessed channel estimate may include probability information associated with the probabilistic shaping signal based on the application of the one or more probabilistic shaping parameters. Accordingly, the wireless communication device may demodulate the communication signal based on the preprocessed signal information.

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.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive a configuration associated with transmitting acknowledgment (ACK) or negative ACK (NACK) feedback in a pilot symbol, wherein the pilot symbol is associated with an uplink reference signal. The UE may receive a communication. The UE may transmit the ACK or NACK feedback regarding the communication in the pilot symbol in accordance with the configuration. Numerous other aspects are described.

The invention discloses an underwater sound environment sensing method based on multi-array-element sparse channel estimation. An underwater sound receiving end receives signals transmitted through an underwater sound multipath channel through a multi-array-element array; performing Hilbert transform on the receiving signal of each array element to obtain an analysis signal, and calculating a cross-correlation function of the analysis signal and the transmitting signal; based on the cross-correlation function, sparse channel parameters, including path amplitude and time delay, of each array element are estimated by adopting an orthogonal matching pursuit algorithm combined with a constant false alarm detection dynamic threshold value; the method comprises the following steps: constructing an array response vector by using sparse channel parameters of a multi-array element array, and searching and estimating angles of arrival, including a direction angle and a pitch angle, of a multipath signal through a spatial spectrum peak value; and based on the arrival angles, amplitudes and time delays of the direct path and the reflection path, inverting an underwater environment structure through a ray acoustic theory, including a reflection point distance and a reflection surface normal vector, so as to realize three-dimensional perception of the underwater reflector. According to the invention, multipath resolution can be improved, and false alarm and missing detection can be effectively reduced.

The invention discloses a data full-link dynamic anti-interference optimization transmission method. The method comprises the following steps: S1, constructing a data transmission system architecture comprising a sending end, a transmission link and a receiving end; the sending end detects environment disturbance characteristics in real time, and the receiving end collects receiving signals containing background noise and link distortion; s2, designing a self-adaptive waveform coding strategy at a sending end; s3, performing active channel compensation on a transmission link; channel characteristics are extracted, and channel interference is counteracted in real time through pre-distortion waveform adjustment; s4, deploying an intelligent noise reduction decoding algorithm at a receiving end; a depth feature separation network is constructed, and link residual interference is filtered out by analyzing the time-frequency domain difference between a target signal and a noise component. Through a three-level anti-interference mechanism of adaptive coding of the sending end, active compensation of a transmission link and intelligent noise reduction of the receiving end, the problem that the transmission reliability of signals is reduced due to environment disturbance, channel distortion and noise pollution in a complex environment is solved.

Embodiments of the application disclose a communication method and device. The method comprises: a first network device generates a first signal according to a first sequence, the first sequence being a product of a second sequence and a third sequence; the second sequence carrying data; an i-th element in the second sequence corresponding to an i-th subcarrier of N subcarriers in a first frequency domain resource, an i-th element in the third sequence corresponding to the i-th subcarrier in the first frequency domain resource, an i-th element in the first sequence being carried on the i-th subcarrier in the first frequency domain resource; the first frequency domain resource comprising M non-overlapping sub-frequency domain resources; the third sequence comprising M sub-sequences; a t-th sub-sequence in the M sub-sequences corresponding to a t-th sub-frequency domain resource in the M sub-frequency domain resources; a t-th relationship in M relationships being satisfied by the t-th sub-sequence in the M sub-sequences; and the first signal being sent. The ranging accuracy of the sensor-fusion signal is improved by using the embodiments of the application.

The invention provides a method for transmitting a binary data sequence on an OTFS communication channel influenced by Doppler spread. According to the method, the optimization of the pilot signal power ratio can be realized only by using the existing information of the transmitter end, and end-to-end simulation or test is not needed. A corresponding receiver executes two-stage iterative channel estimation, signal detection, demapping and data decoding, and iteratively feeds back information obtained from decoded data to channel estimation, signal detection, demapping and data decoding.

The apparatus may be a wireless device configured to estimate, for a first transmission in a first slot, a first channel associated with the first transmission, wherein the first transmission is associated with a first precoding, receive, in a second slot following the first slot, a second transmission associated with a second precoding, and estimate, based on the received second transmission and at least one of the received first transmission or the estimated first channel, a second channel associated with the second transmission.

The invention provides an RLS channel estimation method, device, equipment and medium for a single-carrier underwater acoustic communication system, and the RLS channel estimation algorithm combines the sparsity characteristic of an underwater acoustic channel and the diversity gain of bidirectional estimation, and can significantly improve the precision and convergence rate of channel estimation. The method is especially suitable for an underwater acoustic communication system in a complex time-varying and multi-path sparse environment.

Wireless communication devices, systems, and methods related to bundling of uplink communication signals under timing advance (TA) conditions are provided. For example, a method of wireless communication performed by a user equipment can include receiving, from a base station, a timing advance (TA), wherein the TA is scheduled to be implemented by the user equipment at a first time, the first time being after a start of a first uplink communication of a group of bundled uplink communications scheduled with phase coherence and before a start of a second uplink communication of the group of bundled uplink communications; determining whether to implement the TA at the first time or a second time, the second time being after transmission of the second uplink communication; and implementing the TA based on the determining.