37 results about "Convolutional code" patented technology

The invention belongs to the related technical field of image processing, and discloses a texture surface defect generation method and system based on a mask perception image redrawing network, and the method comprises the steps: (1) obtaining a low-frequency structure feature based on a defect sample image of a to-be-processed product category, a binary mask for marking a defect position, and a convolutional coding module; (2) a context sliding window attention modeling module carries out long-range dependence modeling on the feature sequence, and attention calculation is carried out between effective feature marks to obtain high-frequency detail features; (3) inputting the low-frequency structural features and the high-frequency detail features into a collaborative feature fusion module for fusion to obtain fusion features; (4) a style modulation decoding module performs up-sampling on the fusion features based on the comprehensive style tensor; and (5) generating a defect image based on the trained generator network model, the defect-free sample image of the to-be-processed product category and a user-defined defect mask. According to the invention, the authenticity of defect generation is improved.

The present application discloses a method and apparatus for use in a terminal and an Internet of Things device for wireless communication. The method comprises: a terminal sends a first PRDCH, OOK being used for the first PRDCH; and the terminal receives a first PDRCH, a convolutional code being used for channel coding of the first PDRCH, a constraint length of the convolutional code used for channel coding of the first PDRCH being equal to a first constraint length, and a code rate of a mother code of the convolutional code used for channel coding of the first PDRCH being equal to a first code rate. At least one of the first constraint length and the first code rate belongs to a first coding scheme, the first coding scheme belongs to a set of candidate coding schemes, and the set of candidate coding schemes comprises at least one coding scheme. The set of candidate coding schemes depends on a device type of a sender of the first PDRCH. When the set of candidate coding schemes comprises a plurality of coding schemes, the first PRDCH indicates the first coding scheme in the set of candidate coding schemes. The present application improves transmission quality.

The present disclosure relates to a 5G or 6G communication system for supporting a higher data transmission rate than a 4G communication system such as LTE. An encoding method performed by a transmission device of a communication system according to an embodiment of the present disclosure may comprise the steps of: identifying at least one parameter related to a convolutional code associated with a polarization-adjusted convolutional (PAC) code; on the basis of the at least one parameter, identifying a parity check matrix for an input binary vector of a polar code associated with the PAC code; on the basis of the parity check matrix, encoding a polar code concatenated with an outer code; and transmitting a codeword vector generated on the basis of the encoding.

The application discloses a convolution code parallel pipeline decoding acceleration system and method based on a memory-compute integrated architecture, comprising: a global data scheduling module, which is used for slicing convolution code data from a magnetic tape storage device according to a set rule and scheduling the data through a multi-level cache mechanism; a memory-compute integrated unit array, which is used for storing data tiles and intermediate results output from the global data scheduling module and performing convolution operation, path metric calculation and surviving path selection through a reconfigurable computing unit; a parallel pipeline controller, which is used for dynamically allocating decoding tasks and controlling the pipeline beat of the memory-compute integrated unit array; an adaptive resource configuration module, which is used for monitoring the system load in real time and dynamically adjusting data distribution strategies and computing resource scheduling; and a check and error correction unit, which is used for checking and correcting the decoding results output from the memory-compute integrated unit array and then outputting the results; the decoding acceleration system and method realize efficient and low-delay convolution code decoding.

The invention discloses a parallel stepped convolutional code space coupling coding and decoding (PSCBCC) method and device, belongs to the technical field of channel coding, and is suitable for a large-bandwidth communication scene. According to the method, a frame of data is divided into multiple groups of sub-data, parallel convolutional coding of three paths of input of current sub-data, interleaved previous sub-data and an interleaved previous check sequence is realized by utilizing a parallel coding unit, a current check sequence is generated, and the sub-data and the check sequence are respectively reserved to different subsequent moments to form asymmetric coupling; and during decoding, a parallel decoding unit is matched with a coding structure, and a plurality of groups of log-likelihood ratios are input to realize iterative updating. The throughput rate is improved through parallel processing, the bit error rate performance is enhanced through asymmetric coupling, multi-code-rate adaptation is supported, and the performance is superior to that of existing BCC and 4G / 5G standard codes.

The invention discloses an unsupervised engineering structure damage identification method, apparatus and device, and a medium. The method comprises the steps of obtaining a structure vibration signal of a to-be-identified engineering structure; reconstructing the structural vibration signal through the damage identification model to obtain a reconstructed vibration signal; and on the basis of a reconstruction error between the vibration signal and the reconstructed vibration signal, identifying the structure state of the to-be-identified engineering structure. According to the method, the local feature extraction capability of the convolutional coding module and the overall evolution rule of the signal captured by the Transform coding module along the time dimension are fused, and the features are compulsively compressed and reconstructed by using the bottleneck layer, so that the damage identification model learns the essential feature representation of the structural vibration signal, the reconstruction accuracy of the healthy vibration signal is improved, and the reconstruction accuracy of the healthy vibration signal is improved. Therefore, the accuracy of the structure state identified on the basis of the reconstruction error between the vibration signal and the reconstructed vibration signal can be improved.

The invention belongs to the technical field of communication signal processing and code identification, and solves the problem of channel code identification when a non-cooperative communication system lacks coding parameter prior information and training data with labels. According to the technical scheme, the method is characterized in that a unified recognition framework is constructed based on five features, namely, a rank fluctuation feature is used for distinguishing convolutional codes and linear block codes, a continuous zero spectrum feature is used for recognizing BCH codes, a multi-dimensional structure feature is used for detecting Turbo product codes, a bit distribution deviation feature is used for recognizing polarization codes, and an average absolute column correlation feature is used for distinguishing LDPC codes and non-LDPC codes; blind recognition of five types of channel codes including BCH codes, LDPC codes, convolutional codes, Turbo product codes and polarization codes is achieved. The method does not depend on coding parameter prior information, does not need training, is high in recognition rate under a low signal-to-noise ratio, is high in generalization capability, and is suitable for real-time and resource-limited scenes.

An apparatus configured to apply a convolutional precoder with a time-varying polynomial to an information vector to generate a precoded vector, wherein coefficients of the time-varying polynomial are generated by a pseudo-random number generator (PRNG) using a radio network temporary identifier (RNTI) as an initialization seed, generate a polarization-adjusted convolution (PAC) codeword based on the precoded vector and transmit the PAC codeword.

The invention relates to the technical field of channel coding and decoding. The invention discloses a pre-transformation method and device of a polarization adjustment convolutional code, a terminal and a storage medium, which can reduce the computation complexity of optimizing a convolution multiform and reduce the optimization difficulty of code redistribution of a PAC code. The pre-transformation method of the polarization adjustment convolutional code comprises the following steps: setting a first convolution formula and a plurality of to-be-processed formulas; a tree structure modeling mode is adopted to carry out convolution multi-mode modeling processing on the first convolution formula and the multiple to-be-processed formulas to obtain a target convolution polynomial of the polarization adjustment convolution code, the tree structure modeling mode sets a coefficient in a target to-be-processed formula as 0 or 1, and when the coefficient of the target to-be-processed formula is 0, the polarization adjustment convolution code is obtained. The to-be-processed formula corresponding to the target to-be-processed formula is not used for constructing the target convolutional polynomial, and the target to-be-processed formula is any to-be-processed formula in the multiple to-be-processed formulas.

The application discloses a convolutional decoder, a decoding method and an electronic device, relates to the technical field of communication, and is used for reducing time overhead of convolutional code decoding. The application is used for decoding an encoded sequence, the encoded sequence is divided into P first sub-sequences, tail sequences of the P first sub-sequences are P second sub-sequences, and the convolutional decoder comprises the following steps: for first round decoding, P Viterbi decoders decode the P second sub-sequences respectively, and update cumulative score vectors of the P second sub-sequences; from second round decoding, a pth Viterbi decoder starts to perform cyclic decoding on the encoded sequence from a starting position of a pth first sub-sequence, and update cumulative score vectors of the P first sub-sequences; P comparators compare the cumulative score vectors of two sub-sequences with the same ending position in the last two rounds of decoding, and if the maximum probability state transition paths of the two sub-sequences with the same ending position are the same, the decoding sequence of the maximum probability state transition path is output.

The present application relates to the technical field of communications, and discloses a Bluetooth communication method and apparatus, an electronic device, a storage medium, and a program product. The method comprises: when a Bluetooth connection exists between a first electronic device and a second electronic device, acquiring a first parameter, the first parameter comprising at least one of the following: a signal strength between the first electronic device and the second electronic device, and a number of data packets lost between the first electronic device and the second electronic device. On the basis of the first parameter, adjusting signal transmission power and / or a convolutional code of the first electronic device, the convolutional code being a convolutional code used when the first electronic device encodes transmitted data.

Communication systems that utilize receivers for decoding short block length messages are disclosed. In many embodiments, the receiver includes an antenna for receiving encoded data, via RF signals, a demodulator for obtaining symbols from the RF signal, a demapper for generating symbol metrics, and a parallel list decoder. In several embodiments, the parallel list decoder processes multiple trellis stages simultaneously, enabling efficient decoding of the symbol metrics to obtain received, bits. In certain embodiments, the parallel list decoder divides the decoding trellis into segments, processes these segments independently, and combines them pairwise to form new segments. This parallel processing approach can allow for reduced decoding latency and improved efficiency in handling short block length messages. making it particularly suitable for applications requiring rapid data exchange and low-latency communication.

The invention discloses a prediction-based Internet of Vehicles code retransmission method and system and electronic equipment, and is applied to the field of Internet of Vehicles network transmission. The method comprises the following steps: collecting network states and vehicle motion characteristics of a plurality of transmission paths, and constructing a multi-modal tensor; constructing a prediction model by using a time sequence convolution encoder and an attention mechanism, and predicting a link state; a main path and an auxiliary path are screened according to the prediction result, the main path sends an original data packet, and the auxiliary path sends a polarization adjustment convolutional coding check packet generated based on the predicted packet loss rate; and the edge server carries out decoding by using the verification packet during packet loss, and feeds back a transmission result to update prediction model parameters. According to the method, the problems of high packet loss rate and retransmission delay jitter of the Internet of Vehicles in a high dynamic scene can be relieved by utilizing heterogeneous path cooperative transmission and a prediction-based polarization adjustment convolutional code coding retransmission mechanism, and technical support is provided for Internet of Vehicles services such as automatic driving.

The application discloses a QPSK phase ambiguity identification method based on convolution code, and comprises the following steps: firstly, 8 sequences are spliced from 8 kinds of phase ambiguities existing in QPSK demodulation according to demodulated I and Q data; secondly, an equation is established according to the coding constraint relationship of the convolution code; finally, the probability of the equation being established is taken as a standard for measurement, and 8 sequences are screened to reduce the number of phase ambiguities. According to the method, one sub-checking element of one code rate of the convolution code only needs to be stored, and the number of 8 kinds of phase ambiguities is reduced to two, so that the consumption of resources is reduced compared with a traditional phase ambiguity elimination mode. Meanwhile, the application can be realized only by binary multiplication and accumulation, and the calculation complexity is low and the algorithm structure is simple compared with a traditional method.

The invention discloses a method for preventing tampering of electric power internet of things sensing data of cascaded codes, and belongs to the field of data processing. According to the method, the characteristic advantages of cascade connection of the RS codes and the convolutional codes are fused, the grading strategy of triggering the RS codes on demand is adopted, the optimized convolutional decoding algorithm is matched, and on the premise that calculation and transmission expenses are not remarkably increased, the requirement of an electric power internet-of-things scene for real-time transmission and the core target of data reliability are considered. Meanwhile, the improved Viterbi algorithm is used, values of other branch metrics are rapidly calculated through symmetry and a logic relation, and therefore the convolutional code decoding efficiency is improved. Besides, an optimized search algorithm is used, and based on path measurement characteristics of Viterbi decoding, error positions are subjected to probability sorting and a search sequence is optimized, so that the efficiency of RS code decoding error correction is improved.

The invention discloses a stepped convolutional code (HSCBCC) coding and decoding method and device for high-speed large-bandwidth data transmission, and belongs to the technical field of communication channel coding. According to the coding method, a frame of data is divided into a plurality of groups of sub-data, a convolutional code coder is adopted to code a combined sequence of current sub-data and previous specific sub-data and a previous specific check sequence subjected to interleaving processing, and a current check sequence is generated; respectively retaining the current sub-data and the verification sequence to different subsequent moments as input; the decoding method comprises the following steps: iteratively processing channel information and extrinsic information of the corresponding sub-data and the check sequence, and outputting a decoding result. According to the invention, an asymmetric double-coupling structure is adopted, the bit error rate performance is superior to that of an existing space coupling coding scheme under the same resource consumption, and the method is adaptive to a multi-code-rate scene and is suitable for the technical field of large-bandwidth wireless communication or optical fiber communication.

m1km1kcmkc+1km1kcm1Ncm1Ncv1Ncv1Ncmkc+1ku1Nu1Nc1Ny1Nu1Nu1NThe invention provides a coding method, a decoding method and a communication device. A coding end device divides an information vector m1k into a first information vector m1kc and a second information vector mkc + 1k, code rate configuration I is carried out on the first information vector m1kc, a vector m '1Nc is obtained, convolution transformation is carried out on the vector m' 1Nc, and a code word vector v1Nc of a convolution code is obtained; and performing code rate configuration II on the code word vector v1Nc and the second information vector mkc + 1k to obtain a message vector u1N, and performing polarization transformation on the message u1N to obtain a code word vector c1N. The decoding end equipment receives the symbol vector y1N and determines a message vector u1N to be estimated; and according to the node position i of the decoding node ui, calling a continuous elimination decoding algorithm or a Fano decoding algorithm to decode the decoding node u1N. Therefore, the number of the nodes allowed to be fallback in the decoding process is reduced, and the overall decoding complexity can be reduced.

The application belongs to the technical field of communication, and discloses a stack decoding method, system, device, medium and terminal based on a soft output, which comprises the following steps: creating a structure and a stack and initializing; repeatedly judging the size of the path length in the structure at the top of the stack and the depth of a decoding tree, if the path length in the structure at the top of the stack is smaller than the depth of the decoding tree, recalculating the path metric, and sorting the stack according to the size of the path metric until the path length in the structure at the top of the stack is equal to the depth of the decoding tree, and counting the soft output probability of each decoding result; and correcting the decoding result according to a preset threshold to obtain a final decoding result. The method disclosed by the application can effectively reduce the calculation complexity under the premise of a low signal-to-noise ratio. In the case of (128, 64), compared with the traditional stack decoding, the stack decoding method of the polar adjustment convolution code based on the soft output can reduce the calculation amount by 82%.

The invention relates to a construction method and device of a polarization adjustment convolutional code, a terminal and a storage medium. The method comprises the following steps: calculating a first minimum code weight, a first error coefficient and a first dominant index of the polarization adjustment convolutional code; constructing a candidate frozen set according to the code length, the information bit number and the initial information set, and obtaining a target information set without the first dominant index according to the initial information set and the first dominant index; performing iterative optimization on the initial information set, the first minimum code weight and the first error coefficient based on each frozen bit in the target information set and the candidate frozen set to obtain an optimized information set, an optimized minimum code weight and an optimized error coefficient; and obtaining a polarization adjustment convolutional code based on the optimization information set, the optimization minimum code weight and the optimization error coefficient. According to the method, the minimum code weight and the error coefficient of the polarization adjustment convolutional code are remarkably improved, so that the certainty, the effectiveness and the calculation efficiency of the polarization adjustment convolutional code are improved.

The invention discloses a high-speed parallel Viterbi decoder based on a CUDA (Compute Unified Device Architecture) and a decoding method. The decoder comprises an input cache module, a parallel data de-puncturing module, a parallel measurement calculation module, a backtracking path processing module and an output control module, and multi-level parallel processing is realized by utilizing a CUDA (Compute Unified Device Architecture) of a GPU (Graphics Processing Unit). The method comprises the following steps: segmenting a receiving sequence and then distributing the segmented receiving sequence to GPU thread blocks; rapidly reading a state transition matrix and an output matrix by adopting a pre-calculation table look-up strategy; adopting a parallel prefix scanning algorithm to accelerate state measurement calculation; and reducing the global memory access delay by using the shared memory. According to the invention, the performance bottleneck of the traditional serial Viterbi algorithm is broken through, on the premise of keeping the decoding precision, the throughput rate is obviously improved, the real-time processing of multi-code-rate and multi-code-stream convolutional codes is supported, and a remarkable acceleration effect can be obtained compared with CPU (Central Processing Unit) implementation. The method is especially suitable for high-throughput ACM scenes, such as 5G communication and satellite navigation, requiring real-time processing of multiple code streams and long constraint length convolutional codes.

Methods, systems, and devices for wireless communication are described. Some energy harvesting (EH)-capable devices may implement channel coding for backscatter-based communications (e.g., backscatter communications may be encoded using error correction codes). The same mother code may be used with different coding rates, for example based on puncturing or shortening applications. The EH-capable device may use the same mother code and different coding rates for backscatter-based communications based on operating conditions at the EH-capable device. For example, the mother code may be an (N, K) block code, and the EH-capable device may adjust the coding rate by applying S-bit shortening. As another example, the mother code may be a convolutional code using a defined number K of input information bits and a defined number N of encoded output bits, and the EH-capable device may adjust the coding rate by applying P-bit puncturing.

This application relates to the field of battery state estimation technology, and provides a battery state estimation method, apparatus, terminal device, and storage medium. The method includes: acquiring battery operating data information for estimating the current state of the battery; inputting the battery operating data information into a pre-trained SOC estimation model to obtain the battery's SOC estimate and SOC estimation range. The SOC estimation model includes a convolutional coding module and a convolutional decoding module. The convolutional coding module includes a first CNN layer, a first positional coding layer, a coding layer, and a distillation layer connected in sequence. The convolutional decoding module includes a second CNN layer, a second positional coding layer, a decoding layer, and an output layer connected in sequence, with the output of the distillation layer connected to the input of the decoding layer. This application can reduce the impact of outliers on the estimation results and greatly improve the accuracy of SOC estimation.

Methods, systems, and devices for wireless communications are described. A first wireless communication devices may encode a set of data bits for transmission to a second wireless communication devices using a tail-biting convolutional code (TBCC) encoding scheme that does excludes cyclic redundancy check (CRC) bits as the tail bits and uses data bits as the tail bits. For example, a stream of data bits for encoding using the TBCC encoder may be separated into a first part and a second part, and the first part may be used as the tail bits. The first part and the second part may be separated by the CRC bits for encoding using the TBCC encoder. Accordingly CRC generation may be performed in parallel with at least a portion of the TBCC encoding, reducing latency and the amount of data to be buffered while waiting for the CRC generation.

This invention discloses a parallel interleaving system and method for multi-channel convolutional coding. The technical solution includes: a convolutional coding module sending generated multi-channel coded data and two punctured valid flag signals; an interleaving write address generation module sending two generated interleaving write addresses; a ping-pong read / write gating module sending generated ping-pong read / write gating signals and gating the coded data and interleaving write addresses; performing an interleaving write operation; an interleaving read address generation module sending multi-channel interleaving read addresses; gating the interleaving read addresses; performing an interleaving read operation and sending interleaved data; using dual-port RAM for synchronously switched interleaving read / write operations; and the system stopping operation. This invention reduces the complexity of convolutional coding and has the advantages of low complexity, low clock speed, high throughput, and high reliability.

Methods, systems, and devices for wireless communications are described. A first device may transmit, to a second device, a bit sequence encoded with a convolutional encoder associated with a constraint length of eight and associated with a subset of polynomials of a polynomial set, wherein the polynomial set is selected from a group of polynomial sets, expressed with octal values, consisting of polynomial sets described herein.

Certain aspects of the present disclosure provide a design for nested convolutional codes. The design has sufficiently low complexity that it may be implemented in an A-loT system where even the reader is a UE with limited power and processing resources. The design utilizes nested polynomial sets, where different subsets of polynomials may be used for different coding rates.

Methods, systems, and devices for wireless communication are described. In some systems, a wireless communication device, such as an ambient internet-of-things (A-IoT) device, may include a convolutional encoder with a nested convolutional codes design that supports variable coding rates. The device may communicate an indication of a first coding rate to use for communication. The device may encode a set of information bits using the convolutional encoder with a fixed constraint length, such as a constraint length of six. The encoder may output multiple parity streams for the set of information bits, the quantity of parity streams corresponding to a lowest coding rate supported by the encoder. The device may puncture one or more of the parity streams according to the first coding rate and may transmit a signal indicating the bits of the remaining, unpunctured parity streams to achieve the indicated first coding rate.

Optimization scheme for Ordered Reliability Bit-Guessing Random Additive Noise Decoding (ORB-GRAND) suitable for high-rate Polarization-Adjusted Convolutional (PAC) codes uses an error pattern list, a

Communication systems that utilize receivers for decoding short block length messages are disclosed. In many embodiments, the receiver includes an antenna for receiving encoded data, via RF signals, a demodulator for obtaining symbols from the RF signal, a demapper for generating symbol metrics, and a parallel list decoder. In several embodiments, the parallel list decoder processes multiple trellis stages simultaneously, enabling efficient decoding of the symbol metrics to obtain received, bits. In certain embodiments, the parallel list decoder divides the decoding trellis into segments, processes these segments independently, and combines them pairwise to form new segments. This parallel processing approach can allow for reduced decoding latency and improved efficiency in handling short block length messages. making it particularly suitable for applications requiring rapid data exchange and low-latency communication.

The invention discloses an unmanned aerial vehicle detection and classification method based on deep learning. A received unmanned aerial vehicle radio frequency signal is processed to generate sparse enhanced MVDR spectrum features; based on an improved self-attention learning feature extraction and coding module and a convolutional coding module, a SunnyitUAVCNN neural network is constructed; sequentially carrying out sequence segmentation, linear embedding and spectrum physical position coding on the sparse enhanced MVDR spectrum features, carrying out feature hierarchical extraction and enhancement through the constructed neural network, and constructing a residual structure to enhance feature representation; and finally, introducing a classification confidence weighting mechanism, performing dimension compression and probability mapping on the feature matrix processed by the neural network, calculating classification confidence, and comparing the classification confidence with a preset threshold to complete unmanned aerial vehicle detection classification. According to the invention, the problem that unmanned aerial vehicles with unknown models or signal disguise cannot be effectively identified in the prior art is solved.