759 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 discloses a semantic communication method for adaptive coding of a semantic source channel under a parallel channel. The method comprises the following steps: S1, constructing a communication model for adaptive coding of the semantic source channel under the parallel channel; s2, at a sending end, encoding semantic information source samples in (X, S), distributing bit streams after encoding each semantic information source sample to an independent channel for transmission, and adopting K channel encoders with different channel rates to protect respective bit streams so as to resist channel errors; s3, at a receiving end, decoding the received signals by using K channel decoders, combining the received signals into a single serial flow, and decoding the single serial flow by using a semantic source decoder based on a deep neural network; s4, determining a source rate and prior information under any given deep neural network model; and S5, constructing an optimization problem, and performing joint optimization of the deep neural network parameter phi and the resource allocation variable # imgabs0 #. According to the invention, resource allocation optimization in a parallel Gaussian channel scene is realized.

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.

The invention provides a channel environment adaptive sampling-semantic-channel coding joint optimization method and system, and relates to the technical field of semantic communication, a sending end performs semantic sampling on an image needing to be transmitted to obtain a semantic sampling result; the sending end inputs the semantic sampling result into an encoder to obtain an image feature vector needing to be transmitted; a receiving end receives the image feature vector influenced by the physical channel noise and preprocesses the image feature vector; the receiving end inputs the preprocessing result into a decoder to obtain an image feature vector needing semantic reconstruction; and the receiving end performs semantic reconstruction according to the image feature vector needing semantic reconstruction to obtain a reconstructed image. According to the method provided by the invention, the characteristics of an information source and a channel are combined, image transmission in a variable signal-to-noise ratio environment can be supported while semantic sampling and reconstruction are considered, and the reconstruction quality of the image is ensured.

The invention discloses a semantic transmission method for a visible light and infrared fusion image of a night vehicle road environment, and the method comprises the steps: collecting visible light and infrared images in a vehicle driving process, and improving the visibility of the images under a low-light condition through a visible light image enhancement network; secondly, fusing the enhanced visible light image and the infrared image; thirdly, performing semantic guidance processing on the fused image, identifying target semantic information, extracting semantic features, and evaluating the importance of feature vectors so as to generate a semantic feature group; and finally, the sending end encodes the fused image into a potential space representation, the fused image is encoded and compressed into a conditional signal through a channel, the conditional signal is transmitted to a receiving end through an additive white Gaussian noise channel, and the receiving end dynamically adjusts the weight of a denoising device based on a potential diffusion model by using a conditional perception neural network and controls a generation process. And finally, generating a restored image through a semantic decoder. The method is of great significance in improving the reliability and safety of the automatic driving system.

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 remote speech enhancement transmission method and system based on semantic communication in the technical field of speech signal transmission processing, and the system comprises a local transmitting end which is used for carrying out the short-time Fourier transform of a to-be-enhanced noisy speech signal, and then carrying out the semantic feature extraction of the frequency spectrum of the noisy speech signal through a semantic encoder; carrying out dimension adjustment on the voice semantic features by using a channel encoder; and finally, transmitting to a remote receiving end through a channel. The remote receiving end is used for receiving the voice semantic feature signal transmitted through the channel; after dimension recovery is carried out on a received voice semantic feature signal by utilizing a channel decoder, semantic decoding is carried out by utilizing a semantic decoder to obtain a real part and an imaginary part of a predicted pure voice signal, and finally inverse short-time Fourier transform is carried out to obtain a reconstructed voice signal. According to the invention, under the condition of saving communication resources, the quality of pure voice recovered by a remote receiving end under a low signal-to-noise ratio channel transmission condition can be obviously 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.

A method includes performing channel encoding on a plurality of information bits to obtain a codeword that includes a plurality of code bits; segmenting the codeword into a plurality of segments of code bits; performing the following for each of the plurality of segments of code bits of the codeword: selecting, based on the segment of code bits, a set of channel resources, wherein each set of channel resources is selected among a plurality of sets of channel resources, wherein each of the sets of channel resources includes a unique combination of channel resources including one or more of a selected base sequence, a cyclic shift and a selected set of frequency domain resource elements; mapping the selected base sequence onto the selected set of frequency domain resource elements; and transmitting the selected and frequency mapped base sequence via an OFDM symbol.

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.

The embodiment of the invention provides an air-sea cross-domain communication method and device. The method comprises the following steps: fusing a multi-system communication protocol into a cross-domain communication network protocol through a water surface wireless communication multi-band access technology, and carrying out adaptive networking; the method comprises the following steps: performing dictionary table mapping on original information sent by underwater subsurface buoy sensor equipment to obtain a translated character sequence, constructing a Huffman tree according to the occurrence frequency of each character in the translated character sequence, and generating a Huffman code corresponding to each character according to the Huffman tree; the method comprises the following steps: monitoring channel noise and a channel error rate of an underwater acoustic channel in real time, determining a real-time channel state, determining a channel coding parameter adjustment strategy matched with the real-time channel state through an adaptive algorithm, and dynamically adjusting a coding mode and coding parameters of the channel according to the channel coding parameter adjustment strategy. Uploading the Huffman code to a superior command center through a preset dual channel according to the dynamically adjusted coding mode and coding parameters; according to the invention, the air-sea cross-domain communication efficiency can be effectively improved.

The invention relates to a 5G broadcast television image communication system fused with deep learning and a method thereof. The system comprises an image processing module, a channel processing module, a data transmission module, a channel decoding module, an image reconstruction and enhancement module and a system optimization and self-adaption module. Through an image compression technology based on Vision Transform, an image is divided into image blocks with a fixed size, and a multi-head attention mechanism is utilized to extract global context and local features, so that efficient compression is realized. Meanwhile, the channel coding and decoding unit based on Transform enhances the anti-noise capability of the system by generating redundant bits and correcting cross-layer error codes, an image reconstruction and enhancement module is combined with a generative adversarial network (GAN) and a super-resolution model, detail compensation and enhancement can be carried out on the decompressed image, and through a system optimization and self-adaptive adjustment module, the image reconstruction and enhancement module can carry out self-adaptive adjustment on the image. A transmission strategy is dynamically adjusted according to a channel state and transmission feedback, and efficient and stable radio and television image communication is realized in a complex 5G network environment.

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 belongs to the technical field of communication navigation, and particularly relates to a covert communication method based on TACAN navigation. Inserting an immediate pulse pair into an auxiliary reference pulse of the TACAN signal emission pulse sequence; and performing channel coding on the subsequent pulse pair for transmitting communication data. The uplink transmission communication data frame of the ground control tower sequentially comprises packet header data, first channel estimation data SINBAL1, first effective data DATA1, second channel estimation data SINBAL2, second effective data DATA2 and protection data from front to back; and the lengths of the two bytes are respectively 6 bytes, 2 bytes, 4 bytes, 2 bytes, 4 bytes and 2 bytes.

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 image transmission, and discloses an image transmission method, transmitting equipment, receiving equipment and an image transmission system.The method is applied to the transmitting equipment, the transmitting equipment is connected with the receiving equipment through a transmission channel, and the method comprises the steps that a to-be-transmitted image is obtained, semantic feature extraction is conducted on the to-be-transmitted image, and the to-be-transmitted image is obtained; obtaining semantic features to be transmitted; obtaining a channel feature of the transmission channel, determining a corresponding preset coding strategy based on the channel feature, and performing channel coding on the to-be-transmitted semantic feature through the preset coding strategy; and sending a channel coding result to the receiving equipment, so that the receiving equipment performs image reconstruction based on the channel coding result to obtain the to-be-transmitted image. The channel characteristics of the transmission channel can be obtained so as to determine the corresponding preset coding strategy to perform channel coding on the to-be-transmitted image, so that the integrity of the to-be-transmitted image during transmission through the complex transmission channel is ensured.

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 near-field wireless transmission data processing method and system, and relates to the technical field of wireless communication, and the method comprises the steps: obtaining the spectrum characteristics of a near-field communication region and the wireless environment characteristics of the near-field communication region; selecting at least one candidate channel according to the spectrum characteristics, and determining an optimal working channel according to the wireless environment characteristics; determining an initial channel coding strategy according to the state characteristics of the optimal working channel, and adjusting the initial channel coding strategy based on the wireless environment characteristics to obtain an optimal channel coding strategy; inputting the wireless environment characteristics and the state characteristics of the optimal working channel into a pre-constructed modulation prediction model, and outputting an optimal signal modulation mode; the optimal channel coding strategy, the optimal signal modulation mode and the optimal working channel are used for sequentially and correspondingly carrying out data coding, signal modulation and signal sending on the data to be sent, the environment information is fully utilized, dynamic optimization of the transmission strategy is achieved, and therefore the reliability and efficiency of data transmission are improved.

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.