633 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 invention relates to a satellite-to-ground network adaptive image semantic communication method based on an NOMA technology, and the method comprises the following steps: S1, building a satellite-to-ground semantic communication frame integrated with the NOMA technology: carrying out the power superposition and serial interference elimination of different user transmission contents through the NOMA technology, a coding and decoding process is optimized through deep joint source channel coding based on hierarchical vision using a shift window; s2, establishing an adaptive semantic communication model: dynamically adjusting coding parameters based on a target bandwidth ratio and a signal-to-noise ratio of a satellite-ground channel; s3, proposing a dynamic weight adjustment algorithm: optimizing model convergence speed and transmission performance tradeoff under different channel conditions; and S4, designing a feature selection module: performing priority ranking on the image features, and selectively transmitting important features according to bandwidth resources. According to the method, the adaptive semantic communication model (ASeC-NOMA) which can be dynamically adjusted according to the target bandwidth ratio and the signal-to-noise ratio is constructed, and a large number of model storage parameters are saved while the transmission performance is ensured.

Provided in the embodiments of the present disclosure are a mapping method for probabilistic shaping and a reception processing method for probabilistic de-shaping. The mapping method comprises: on the basis of a target amplitude probability distribution and a bit to be shaped, acquiring a shaping amplitude bit by means of a first decoder, which is dedicated to a channel code; and mapping the shaping amplitude bit to form a modulation constellation point. In the embodiments of the present disclosure, decoding can be performed according to a target amplitude probability distribution and by means of a first decoder, which is dedicated to a channel code, such that a shaping amplitude bit is acquired, and the shaping amplitude bit is enabled to be close to the target amplitude probability distribution, thereby realizing a relatively small rate loss and a relatively low shaping complexity.

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 complex scene-oriented target identification method, system and device and a medium, and relates to the technical field of computer vision. The method comprises the following steps: inputting a to-be-detected image into a target recognition model for processing to obtain a target recognition result; the target identification model is constructed based on a dual-channel coding network and a weighted optimization loss function; the dual-channel coding network comprises a MobileNet channel and a wavelet channel; wherein the MobileNet channel is used for extracting multi-scale spatial features and is composed of a layered encoder and a multi-feature prediction decoder which are connected in sequence; the wavelet path is used for extracting frequency domain features and is composed of a global semantic wavelet coding module and a local wavelet fusion decoding module which are connected in sequence; and the multi-feature prediction decoder is also respectively connected with the global semantic wavelet coding module and the local wavelet fusion decoding module. According to the invention, the target identification precision and accuracy for complex scenes can be improved.

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 relates to a dynamic environment adaptive semantic communication system and method, which are used for realizing the whole task-oriented semantic communication, the system comprises a transmitting terminal network, a codebook space, a wireless channel and a receiving terminal network, the transmitting terminal network comprises a feature extractor and a joint source channel encoder, namely a JSC encoder; the feature extractor is used for identifying and extracting features related to a specific task from the original input data; the JSC encoder is used for: mapping the continuous feature vector output by the feature extractor to a discrete symbol representation suitable for wireless transmission; the codebook space is used for mapping a continuous feature vector output by the feature extractor into a discrete codeword index through a vector quantization mechanism; the wireless channel is used for converting the discrete code word index into an electromagnetic signal capable of being physically transmitted and completing a transmission process of the electromagnetic signal in a noise and fading environment; according to the method, the comprehensive performance optimization of task-oriented semantic communication is realized.

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 invention belongs to the technical field of wireless communication, and relates to a system for reducing communication congestion of a wireless communication network. The physical layer adopts an updated frequency hopping sequence to resist interference and is linked with an upper-layer transmission strategy and a topological structure to realize global optimization; link layer resource allocation adopts a dynamic adjustment channel coding mode to adapt to a channel state, so that packet loss caused by blocking of a service is avoided; network layer topology optimization provides real-time spectrum information support, and path planning avoids an interference area. Cross-layer cooperative anti-blocking is performed through dynamic linkage of a physical layer, a link layer and a network layer, limitation of a traditional layered architecture is broken, a'detection-decision-execution 'closed loop is formed, double avoidance of spectrum resources and topological paths is realized, and network anti-blocking capability and transmission efficiency are improved.

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 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.

The invention provides a target-oriented video semantic communication system based on a visual model, and the system comprises a semantic extractor which is based on an SAM2 model and is used for processing an original video, generating a segmentation mask and extracting semantic information; the ViMama encoder is used for carrying out channel encoding on the output of the semantic extractor; the channel adaptation module is used for optimizing a coding sequence ViMama decoder based on the signal-to-noise ratio information of a physical channel, and is used for carrying out channel decoding to obtain a feature sequence; and the semantic reconstruction device is used for performing semantic reconstruction based on the feature sequence, recovering data and outputting a target video. According to the method, the problems of large redundant semantic information interference, insufficient deep semantic coding capability and poor communication robustness in a complex channel environment in a video are solved, efficient compression and robust transmission of video data are realized on the premise of ensuring semantic integrity, and the overall performance and adaptability of semantic communication are greatly improved.

The invention discloses a low-complexity MSK coded modulation system phase synchronization receiving system and method, and relates to the technical field of continuous phase modulation. On one hand, an original message is coded and modulated by constructing a pre-coding mode, a receiving end realizes optimal sampling point extraction at the minimum intersymbol crosstalk moment after phase decoupling frequency conversion processing, MSK is converted into BPSK-like modulation, oversampling processing is not needed, modulation phase components of a receiving synchronization section can be offset, and the modulation efficiency of the receiving synchronization section is improved; therefore, accurate estimation of Doppler phase and frequency is realized, and the anti-Doppler capability is improved. On the other hand, coherent demodulation soft information is directly output after the real part of the signal subjected to Doppler frequency offset and phase offset compensation is obtained, the complexity of the demodulation algorithm is low, the performance of the demodulation algorithm is equivalent to that of BPSK, the demodulation algorithm is remarkably superior to that of an MSK optimal demodulation receiver in a low signal-to-noise ratio region, and the demodulation algorithm is particularly suitable for a bit interleaving coding modulation system combined with channel coding and has a wide application prospect. And reliable transmission under a low signal-to-noise ratio can be realized.

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.

A method for quantizing data representative of a radio signal received by a radio antenna of a mobile network. The method includes: demodulating the radio signal received by the antenna, providing a demodulated signal; scalar quantizing each value of the demodulated signal using a quantization table selected according to a channel coding level used to transmit the radio signal, providing a quantized demodulated signal; and transmitting the quantized demodulated signal to a channel decoding module.

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.

The invention discloses a multipath effect suppression method for 2.4 GHz radio frequency identification. The multipath effect suppression method comprises a transmitting end processing flow and a receiving end processing flow. A transmitting end carries out pulse code modulation on an analog signal to obtain a digital signal, blocks the digital signal after channel coding, and distributes the digital signal to subcarriers through quadrature amplitude modulation; and generating a time domain OFDM symbol through IFFT (Inverse Fast Fourier Transform), adding a cyclic prefix and a synchronization head, converting into an analog baseband signal, and performing up-conversion, filtering, amplification and radiation. The receiving end amplifies the signal, down-converts the signal to a baseband, filters the signal and converts the signal into a digital signal; the method comprises the following steps of: synchronizing header frame alignment, recovering a coding bit stream through FFT (Fast Fourier Transform) and QAM (Quadrature Amplitude Modulation) demodulation, carrying out CRC (Cyclic Redundancy Check) after decoding and merging, returning ACK (Acknowledgement Character) if According to the method, the multipath effect can be effectively inhibited, and the integrity of received data is improved.

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.

The present invention relates to a satellite-based method and system for processing ocean observation data. The method includes: obtaining ocean observation data of an ocean observation device within a set time; formatting the ocean observation data to obtain a plurality of data slices; arranging the plurality of data slices based on timestamps, and for each data slice, calculating the difference between this data slice and an adjacent data slice with a smaller timestamp, and defining the difference as the differential slice data corresponding to this data slice; for each differential slice data, performing: preprocessing the differential slice data to obtain preprocessed data, and determining whether the preprocessed data meets the similarity requirement. If so, defining this differential slice data as data to be processed, otherwise defining the preprocessed data as data to be processed; performing compression, encryption, and channel coding on the data to be processed to obtain data to be sent; and sending the data to be sent to a land observation station. The present invention can simplify ocean observation data and improve the security of transmitting ocean observation data.

The invention relates to a semantic-driven holographic communication combined information source channel coding method, which belongs to the technical field of wireless communication and comprises the following steps of: establishing an end-to-end point cloud semantic communication system model; the method comprises the following steps: designing a joint source channel coding model architecture, combining a 3D convolutional layer, a Voxception-Resnet module and a 3D attention feature 3D-AF module, and defining a basic unit to realize multi-scale feature extraction; establishing a voxel importance function based on a neuroscience inhibition effect, and deducing a closed-form solution of the voxel importance function; a three-dimensional attention feature module is designed, channel state information and a voxel importance function are fused, and dynamic semantic adjustment is achieved; and performing semantic communication by using the constructed end-to-end point cloud semantic communication system model. According to the invention, the stable performance of a single network in a continuous SNR range from-6dB to 8dB is realized, and compared with a fixed SNR training model, the performance is improved by 30% at most.

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 relates to the technical field of spectral imaging, in particular to a high-resolution snapshot hyperspectral imaging system and method based on deep learning. The system comprises a coding receiving module and an algorithm decoding reconstruction module. The coding receiving module comprises an imaging unit, a broadband multispectral filtering array and a detector; a target spectrum cube is imaged on the surface of the broadband multispectral filtering array through the imaging unit, the broadband multispectral filtering array performs spectral response coding on incident light and the incident light is received by the surface of the detector, and efficient coding compression from three-dimensional spectrum information to two-dimensional plane information is realized; the algorithm decoding reconstruction module comprises a spectrum reconstruction network; and combining the spectrum channel coding curve of the broadband multispectral filtering array with the data received by the detector, and inputting the combined data into a spectrum reconstruction network to obtain a high-quality spectrum cube. The method has the advantages that coding and decoding are jointly designed, and the spectral imaging resolution is improved through super-structure surface forward design and neural network fusion of spectral reconstruction.

The invention provides a communication method and a communication device applied to the field of communication. In the technical scheme provided by the invention, network equipment can perform sub-block interleaving processing on a first to-be-interleaved sequence comprising N sub-blocks based on a first sub-sequence, the first sub-sequence comprises N elements, the N elements are in one-to-one correspondence with the N sub-blocks, and each element in the N elements is used for indicating a sequence number of the corresponding sub-block in the first to-be-interleaved sequence, the first subsequence satisfies a preset relationship. The invention provides a channel coding scheme in a low power consumption scene.

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.

The invention discloses a low-complexity random access channel coding and decoding method based on a sparse regression code, which belongs to the technical field of random access channel coding and decoding, and comprises the following steps of: acquiring to-be-sent information of all active users through a sending end; wherein the information to be sent comprises identity identification information and message information; encoding and transmitting the to-be-sent information, and repeating a plurality of stages; receiving signals are obtained through a receiving end, and whether the whole transmission process is finished after the tth stage is completed or not is judged; wherein the obtained receiving signal transmitted in the first stage is the superposition of a plurality of identity identification sub-code words and noise; the received signals transmitted from the second stage to the t-th stage are all superposition of a plurality of message sub-code words and noise; if the transmission is finished, determining the number of active users according to the number of the transmission stages, and decoding the received signals of the first stage to obtain identity information of all the active users; and decoding the received signals transmitted from the second stage to the t-th stage to obtain message information of all active users.