455 results about "Channel encoding" patented technology

The present invention relates to the technical field of cross-modal image signal reconstruction. Disclosed is a cross-modal joint source-channel coding and decoding method adaptable to changeable scenarios. The method comprises: first designing a Transformer encoder-based cross-modal channel coding and decoding optimization solution, so as to achieve the performance improvement and robustness of a channel encoder and a channel decoder; then designing a cross-modal source coding and decoding optimization solution for haptic-to-image generation based on a latent diffusion model, so that under an image signal loss scenario, haptic information is used to guide image generation; and finally, incorporating transfer learning technology, so as to reduce additional training costs caused by a system facing changeable cross-modal communication scenarios such as a changeable channel signal-to-noise ratio and different transmission tasks. Under cross-modal changeable communication scenarios, the joint source-channel coding and decoding method provided in the present invention can solve the problems of the inability of a receiving end to well complete image reconstruction, and additional model training costs caused by changeable channel environments and scenarios.

The invention overcomes the constraints imposed by conventional wireless communication standards by introducing a physical-layer optimized architecture that decouples transmission control from any single protocol. Rather than being confined by the predefined behaviors of LTE, 5G NR, Wi-Fi, or NB-IoT, the system implements a unified control system that dynamically manages radio parameters—such as modulation, coding, and power—based on real-time link quality and network context. This cross-standard, multimode capability effectively supersedes traditional standard-driven implementations, enabling adaptive, low-latency, and spectrum-efficient communication in complex heterogeneous environments.The system dynamically controls radio access network (RAN) and physical layer parameters, including carrier aggregation, dynamic spectrum allocation, modulation and coding scheme (MCS) adaptation, beamforming configuration, channel coding, transmit power control, and frequency selection. The system architecture includes multi-mode base stations, relay nodes, and edge access points that support inter-RAT handover, fast radio link recovery, and seamless mobility across diverse wireless technologies.

The deep joint source channel coding method comprises the following steps: a sending end obtains a first semantic feature of a first image, and performs constellation mapping modulation on the first semantic feature to obtain a first initial constellation point; the sending end extracts semantic information of the first initial constellation point, generates a rotation angle corresponding to the semantic information, and rotates the first initial constellation point according to the rotation angle to obtain a first rotation constellation point; the sending end generates a real part interleaving matrix and an imaginary part interleaving matrix based on the first rotating constellation point and the real part and the imaginary part of the channel state information, resorts the real part and the imaginary part of the symbol sequence respectively and then recombines the real part and the imaginary part into a complex signal to obtain a first interleaving signal; the sending end transmits the first interleaved signal to a receiving end through a fading channel, and the receiving end receives a second interleaved signal; the receiving end performs semantic reconstruction decoding on the second interleaved signal to obtain a second image; or, the receiving end performs semantic classification decoding on the second interlaced signal to obtain a second image category.

The invention discloses a medical image segmentation system based on a multi-architecture fusion and diffusion model. The medical image segmentation system comprises a dual-channel coding module which performs multi-scale feature extraction on an input medical image by using a dual-channel encoder; the dual-channel encoder comprises a plurality of scale levels, and each level comprises a first channel and a second channel which are parallel to each other; the cross-scale feature fusion module replaces the traditional jump connection, and enhances and fuses the multi-scale features output by the encoder; the decoding module receives the enhanced feature through a decoder and generates a preliminary segmentation mask; and the diffusion model post-processing module takes the preliminary segmentation mask as noise-containing input, and performs iterative denoising and optimization by using a pre-trained denoising diffusion probability model. According to the method, the limitation of a single network architecture in the aspects of long-range dependence modeling and local detail capture can be solved, a multi-scale feature fusion mechanism is optimized, and the fineness and robustness of a segmentation result can be improved.

The present disclosure provides a method and related products. The method includes: performing distribution matching on a first bit sequence to obtain a second bit sequence; obtaining at least two candidate bit sequences for the second bit sequence, where each of the at least two candidate bit sequences includes a first bit part for identifying the candidate bit sequence and a second bit part obtained based on interleaving of the second bit sequence; determining a third bit sequence in the at least two candidate bit sequences for channel coding. In this way, distribution matching needs to be performed simply once for the first bit sequence while obtaining at least two candidate bit sequences for the second bit sequence, which can reduce redundant processing and improve overall system efficiency.

Methods, systems, and devices for wireless communications are described. A wireless device may perform a probabilistic shaping procedure using a shaping rate that is selected in accordance with a rule associated with a target spectral efficiency value, a modulation order, or both. Similarly, the wireless device may perform a channel coding procedure whose coding rate is selected in accordance with the rule. The rule may correspond to a relationship between the coding rate and the shaping rate. In some cases, the wireless device may select the shaping rate and the coding rate to be predefined values based on a target spectral efficiency value. In some examples, the wireless device may select the shaping rate and the coding rate based on a threshold coding rate, a quantity of punctured nodes used in the channel coding procedure, a quantity of layers corresponding to a multi-layer transmission, or any combination thereof.

The invention discloses an SATA (Serial Advanced Technology Attachment) bus system based on an FPGA (Field Programmable Gate Array) and an implementation method thereof, and the SATA bus system comprises a hierarchical protocol processing unit which is used for realizing command analysis, data encapsulation, channel coding and signal conversion functions; the control module is used for receiving a read-write command and read-write parameters sent by the host, and then controlling the hierarchical protocol processing unit to read target data of the storage device according to the read-write command and the read-write parameters, or controlling the hierarchical protocol processing unit to write the target data into the storage device; the command and data processing module is used for caching read-write commands, read-write parameters and upper computer data in FIFO (First In First Out) in a layered manner; and the test data processing module is used for testing whether the storage equipment reads and writes the data normally to obtain a test result. According to the method, the interface design is simple and clear, the delay is low, the data reading and writing function of the storage medium can be tested without intervention of a host or a CPU, and the method can be widely applied to the technical field of serial advanced technology accessory interface control.

The invention relates to the technical field of communication, in particular to a satellite communication anti-interference transmission method based on a frequency hopping and spread spectrum fusion algorithm. According to the method, interference power is collected at multiple nodes, multiple sub-carrier frequencies and multiple moments to construct an interference observation tensor, interference features are extracted through low-rank tensor decomposition, and interference of each sub-carrier frequency in a future frequency hopping time slot is predicted; calculating a signal to interference plus noise ratio and capacity according to predicted interference in combination with transmitting power and noise, constructing a utility function containing a service weight and a balance coefficient, and distributing working sub-carrier frequency to each satellite communication node under concurrency constraint to generate a frequency hopping sequence; a transmitting end performs channel coding, modulation and spectrum spreading on service data and transmits the service data according to a frequency hopping sequence, and a receiving end completes synchronization, de-spreading and decoding and performs weighting processing by utilizing predicted interference. The method improves the spectrum utilization rate and the interference suppression capability, and enhances the satellite communication reliability.

The embodiment of the invention provides an unmanned aerial vehicle semantic communication method and device, and the method comprises the steps: enabling an unmanned aerial vehicle to reach a task point according to a planned track, and collecting image data at the task point; preprocessing the image data to obtain image information with consistent dimensions; performing semantic coding on the image information by using a semantic encoder to obtain a semantic feature vector; performing channel coding on the semantic feature vector by using a channel coder to obtain a semantic symbol; and sending the semantic symbols to a base station through a wireless channel. According to the method, only key semantic information needs to be transmitted, the amount of data needing to be transmitted is greatly reduced, occupied communication resources are reduced, the communication quality and reliability can be optimized to the maximum extent through trajectory planning and resource allocation, and the overall performance of a communication system is guaranteed.

The invention provides a semantic information transmission communication method and system based on VQGAN optimization. The method comprises the following steps: establishing a VQGAN model for an image; inputting an image to be transmitted into an encoder of the VQGAN model, and extracting image features corresponding to the image by the encoder; searching the index represented by the discrete potential space with the nearest distance according to the feature vector of the image feature; the index of the embedded vector is recorded, channel coding and modulation are carried out, and transmission is carried out through a channel; after channel transmission, the index is recovered through demodulation and channel decoding; and finding the spatial representation in the codebook according to the index, and performing image reconstruction by using a decoder of a receiving end to obtain a reconstructed image corresponding to the to-be-transmitted image. According to the method, a discrete codebook is established in a vector quantization mode, transmission content is reduced by only transmitting an index of the codebook, and high-resolution image reconstruction is performed based on a generative adversarial network and dynamic change of a confrontation channel and compatibility among different devices based on traditional channel coding.

Certain aspects of the present disclosure provide data compression and channel coding techniques for variable length payloads. A method performed at a wireless node may include obtaining a payload for transmission, compressing the payload using a variable length compression technique to obtain a compressed payload having compressed payload bits of a first length, adding padding bits to the compressed payload to obtain a padded compressed payload. The padded compressed payload comprises information bits including the compressed payload bits and the padding bits. The method further includes encoding the padded compressed payload and outputting the encoded padded compressed payload.

Various aspects of the present disclosure generally relate to wireless communication. Some aspects relate to artificial intelligence or machine learning (AI / ML) based channel coding, in which an AI / ML model is used to encode and / or modulate a message for transmission. Aspects described herein use an artificial neural network (ANN) which may include a number of self-attention layers. For example, the ANN may consist of self-attention layers. An ANN that includes only self-attention layers may be associated with a lower number of model parameters than other ANNs, such as ANNs that incorporate a set of transformer layers. Furthermore, the number of model parameters that define an ANN may be lower than a number of table parameters that define a codebook for a transformer-based ANN for channel coding. Thus, signaling overhead can be reduced.

A clustering and identification method for GIS partial discharge ultra-high frequency (UHF) signals based on time and frequency domains belongs to the field of power equipment condition monitoring technology. The method includes the following steps: Step S1, model training process; Step S2, x-branch encoding of the original electromagnetic wave signal; Step S3, filter mask generation and feature separation; Step S4, independent decoding and weighted fusion; and Step S5, online monitoring and identification process. This solution, capable of online monitoring, receives the original electromagnetic wave signal in real time and generates a single sensor feature map through dual-channel encoding, mask separation, and time-frequency decoding. This map is then input into the trained model and outputs the recognition result.

The invention provides a channel state information feedback enhancement method and system based on bidirectional channel correlation, and the method is executed at a base station end, and comprises the steps: receiving a downlink channel state information semantic vector which is coded, compressed and quantized by a user end through a deep joint source channel; carrying out inverse quantization on the semantic vector to obtain an intermediate semantic vector; based on the intermediate semantic vector, retrieving a related historical uplink semantic vector from an uplink channel semantic knowledge base; performing fusion enhancement on the intermediate semantic vector and the retrieval result through an attention mechanism to generate an enhanced semantic vector; inputting the enhanced semantic vector into a decoder, and outputting a reconstructed downlink channel state information matrix; wherein the encoder, the enhancement module and the decoder perform end-to-end joint training optimization by minimizing a reconstruction error. According to the method, the semantics is enhanced at the receiving end by utilizing the correlation of the uplink and downlink channels, the feedback precision and the system robustness are remarkably improved, and the method is suitable for a frequency division duplex system.

Systems, methods, apparatuses, and computer program products for semantic communication involving joint source and channel coding (JSCC) over current communication networks. One method may include receiving, by a first network entity, from a second network entity, a multi-level bit error rate (BER) interface configuration comprising at least one BER based upon the request for a communication session; generating, by the first network entity, an application source encoder and decoder configured to encode and decode, respectively, a plurality of levels corresponding to the at least one BER; and training, by the first network entity, the application source encoder and decoder according to the BER.

Methods, systems, and devices for wireless communications are described. In some cases, a first wireless device may communicate, with a second wireless device, a control signal indicating a systematic polar code configuration, the systematic polar code configuration indicating for the first wireless device to perform systematic polar encoding on a first set of bits associated with a non-uniform bit distribution. As such, the first wireless device may apply a systematic polar code to the first set of bits to generate a systematic polar codeword based on the systematic polar code configuration. In such cases, the systematic polar codeword may include a set of parity bits and a set of systematic bits. Thus, the first wireless device may transmit at least the set of parity bits of the systematic polar code.

The invention relates to a task-oriented semantic communication-oriented adaptive source channel coding system, which belongs to the field of wireless communication, and comprises a sending end for extracting a semantic feature map for evaluation from input data through a feature extractor initialized based on a pre-training large model, executing nested quantization and arithmetic coding based on a calculated importance score, and sending the semantic feature map to a task-oriented semantic communication-oriented adaptive source channel coding system; generating a scalable semantic bit stream with importance levels; the physical layer is used for carrying out reordering and grouping according to importance levels of bit streams, a channel encoder is combined with an interleaver to realize unequal error protection of semantic matching, and encoded bits are mapped to sign bits with different fault-tolerant capabilities in a constellation diagram through division modulation; and a receiving end: recovering the semantic feature map through arithmetic decoding and nested inverse quantization. According to the invention, on the premise of keeping compatibility with a digital communication protocol stack, through distortion-driven joint rate self-adaption, the transmission effectiveness for machine tasks and human vision is obviously improved under a limited bandwidth.

A method for acquiring channel quality includes: receiving a pilot signal sent by a network device through a downlink channel; obtaining a first channel matrix according to the pilot signal, wherein the first channel matrix is used to represent channel quality of the downlink channel; obtaining a compressed target channel matrix by compressing the first channel matrix according to a channel state information (CSI) compression model and a CSI compression parameter, wherein the CSI compression model comprises a channel encoder, and the channel encoder comprises a plurality of sub-encoders; and different sub-encoders correspond to different CSI compression parameters; and sending the target channel matrix to the network device, such that the channel quality of the downlink channel is determined by the network device according to the target channel matrix.

The invention discloses a federated learning semantic communication method for an unmanned aerial vehicle cluster, and the method comprises the steps: firstly, designing a multi-scale joint information source channel encoder through combining the characteristics of a traffic aerial image, and achieving the efficient extraction and compression of semantic features; then, locally training a convolutional neural network with a low-bit quantization weight at each unmanned aerial vehicle, and only uploading a quantization value of a variable quantity of a parameter, thereby reducing energy consumption and protecting privacy; the edge server carries out aggregation and global synchronization on the parameters uploaded by the unmanned aerial vehicles, and the system cooperation efficiency is improved; finally, through energy consumption modeling and experimental verification, it is proved that the method can effectively improve the reconstruction quality and greatly reduce the overall energy consumption, and has excellent robustness. According to the method, efficient semantic communication in a multi-unmanned aerial vehicle traffic scene can be realized with low energy consumption and high privacy protection, and technical support is provided for design and optimization of a future AI-assisted 6G intelligent traffic communication system.

The disclosed embodiments provide a communication method and apparatus, a computer-readable storage medium, and a computer program product. In the method, when a first communication apparatus determines that a first resource set used by a grant-based first terminal device for uplink transmission overlaps a second resource set used by a grant-free second terminal device for uplink transmission, the first communication apparatus determines a first transmission scheme in which the first terminal device performs the uplink transmission in an overlapping area, where the first transmission scheme includes at least one of a first channel coding scheme and a first multiple access scheme, and the overlapping area is determined by performing area division on a time-frequency resource of the first terminal device based on the overlapping. The first communication apparatus outputs the first transmission scheme.

Methods, systems, and devices for wireless communications are described. A user equipment (UE) may receive, from a base station, a configuration indicating a set of encoding parameters corresponding to a constellation shaping encoding process. The UE may calculate a number of bits of a first subset of a source bit stream, and the first subset of the source bit stream may include or encompass an input to a distribution matcher. The UE may apply, to the first subset, a distribution matcher parameter based on the set of encoding parameters. The UE may calculate a number of bits of a second subset of the source bit stream, and the second subset of the source bit stream may be concatenated with an output bit stream of the distribution matcher as an input to a channel encoder. The UE may signal the source bit stream to the base station.

A HARQ method implemented in relation to channel coding may be suboptimal in that the HARQ method does not leverage features of the source coding. For example, it makes no difference to the HARQ method whether source coding is even performed, let alone whether some portions of the compressed bits output from the source encoder have higher levels of priority, e.g. higher levels of importance to the success of the source decoding. In some embodiments, a HARQ method for source coding is provided. The HARQ method for source coding may be performed with or without channel coding. A first set of source encoded bits may be sent in a first transmission (e.g. an initial transmission), and a second set of source encoded bits may be sent in a second transmission (e.g. a retransmission) based on feedback. The feedback may be an indication of source decoding outcome.

The invention discloses a QC-LDPC check matrix construction method and device for NAND, equipment and a medium, and relates to the technical field of channel coding, and the method comprises the steps: firstly generating an initial check matrix without a four-ring structure; based on the row weight distribution characteristics of the initial matrix, adjusting non-zero item arrangement to generate a middle check matrix with uniform row weight; and finally, traversing non-zero items of the intermediate matrix column by column and row by row, and minimizing the number of six rings by adjusting a shift value to obtain a target check matrix. According to the method, by optimizing the ring structure and row redistribution of the check matrix in stages, the influence of four rings and six rings on the decoding performance is remarkably reduced, so that the data error correction capability of the NAND flash memory is improved, and the decoding time delay is reduced.

The invention discloses a multi-mode joint information source channel coding system for satellite-ground semantic communication. The multi-mode joint information source channel coding system comprises a joint information source channel coder and a decoder, the encoder is used for sequentially performing feature extraction, feature fusion, data cutting and phase modulation operation on input multi-modal data to generate a transmitting signal, and transmitting the transmitting signal to a ground base station through a channel; and the decoder is used for sequentially performing real and virtual part separation, data expansion, feature extraction and modal data recovery operation on the received signal so as to reconstruct multi-modal data. According to the system, public semantic information among multi-modal data can be mined, the time-varying low-signal-to-noise-ratio channel characteristics of a satellite downlink are combined, the information bottleneck theory highly related to data reconstruction quality is used as guidance to optimize a coding space, complex field transmission signals with the high compression ratio are generated in a self-adaptive mode, and the multi-modal multi-domain transmission signals are obtained. The reconstruction quality of the multi-modal data can be ensured, and the bandwidth and the energy consumption overhead of satellite communication can be remarkably reduced.

The invention relates to a frequency-space hybrid joint source channel coding method and an image transmission method. The method comprises the following steps: inputting an image to be transmitted into a joint source channel coder, and mapping the image into a channel input vector; an image block embedding module and a frequency space mixing module are sequentially arranged in each encoder layer of the joint source channel encoder, the frequency space mixing module independently divides a high-frequency feature and a low-frequency feature into two branches for parallel processing, and outputs of the high-frequency and low-frequency branches are spliced along a channel dimension and then are subjected to spatial feature modeling. The output of the frequency space mixing module is input into a next encoder layer; a channel adaptive attention mechanism is introduced into an encoder layer, real-time channel SNR is embedded into attention calculation of each encoder layer, and attention focuses are dynamically adjusted according to the real-time channel SNR. Compared with the prior art, the self-adaption to different channel signal-to-noise ratios is realized, and the reconstruction quality of two types of information of high-frequency texture and global semantics is effectively considered under the same code length.

The invention provides a robust Deep JSCC semantic communication system based on mutual information maximization, and relates to the field of semantic communication and joint source channel coding, and the system carries out semantic coding on to-be-transmitted source data according to a preset compression ratio and power constraint at a transmitting end to generate a channel input sequence; at a receiving end, performing semantic decoding on a noisy receiving signal transmitted by the additive white Gaussian noise channel to obtain reconstructed data and execute a downstream semantic task, and calculating a mutual information lower bound between channel input and the receiving signal by using a mutual information estimation module; a composite loss function fusing task loss, reconstruction loss and mutual information loss is constructed, and parameters of a mutual information estimator, a semantic encoder, a semantic decoder and a task execution module are alternately optimized through a joint training mechanism, so that the semantic encoder learns robust semantic representation with a self-adaptive compression ratio. The system does not need to depend on a discrete codebook, and the anti-noise capability of semantic features is improved through explicit maximization of mutual information.

Methods, systems, and devices for a framework for probabilistic shaping and channel coding for wireless signals are described to support a probabilistic shaping framework for higher-order modulations in which shaping and channel coding may be independent. A transmitting device may shape a set of information bits using a set of masking bits. The transmitting device may encode, shape, modulate, and transmit information bits to a receiving device, and the receiving device may demodulate, deshape, and decode the received information bits. In addition to transmitting the information bits to the receiving device, the transmitting device may also transmit a set of shaping bits, which may be indicative of the set of masking bits used to shape the information bits. The receiving device may use the set of shaping bits to generate the set of masking bits, and may use the set of masking bits to deshape the received information bits.

The application relates to the technical field of decoding, and provides a source channel joint decoding method and device, electronic equipment and a storage medium, the method comprising the following steps: acquiring initialization information of a channel encoder and prior probability information of a variable node of a source decoder; determining check node information of the source decoder based on the initialization information and the prior probability information; and performing the following iterative steps, which comprise the following steps: updating soft information of the variable node of the source decoder based on the check node information and the initialization information; and performing decoding decision based on the updated soft information to determine a decoding result. The method determines the check node information of the source decoder based on the initialization information and the prior probability information, iteratively updates the soft information of the variable node of the source decoder based on the check node information and the initialization information, that is, uses the information of the source as the soft information available in the decoding process, improves the coding gain, and thus improves the accuracy of the source channel joint decoding.