120 results about "Soft information" patented technology

The invention belongs to the technical field of communication, and particularly relates to a multiplication active code decoding method based on an SO-ORBGRAND decoder. The SO-ORBGRAND decoder outputs soft information by calculating a correct posterior probability of a conjecture code word sequence, and high-performance decoding is realized through soft information exchange and optimization processing between the row decoder and the column decoder. In the iteration process, a method for judging the validity of the code word through the check matrix is designed by utilizing the polarization characteristic of the multiplication active code, so that the iteration is supported to jump out in advance to reduce the complexity. The invention provides a multiplication active code decoding algorithm based on an SO-ORBGRAND decoder, and compared with various non-system multiplication active code decoding algorithms and the performance of traditional long-code polarization codes, the method has remarkable advantages in error correction performance; a method for judging the validity of the code word through the check matrix by utilizing the polarization characteristic design of the multiplication positive code is provided, the complexity is reduced while the judgment success rate is improved, and the implementation overhead is reduced.

The invention discloses a rail transit-oriented soft information codeword reconstruction security key extraction method and system, and relates to the field of digital information transmission, in the method, a sending end and a legal receiving end alternately send pilot frequencies to each other through a preset channel, and calculate a channel feature sequence of the preset channel; the sending end generates a master key from a preset random source, and encodes the master key to obtain a code word sequence; the sending end generates an information interaction sequence according to the first feature sequence and the code word sequence, and sends the information interaction sequence to a legal receiving end; after the legal receiving end receives the information interaction sequence, the legal receiving end reconstructs the second feature sequence according to the information interaction sequence to obtain a code word structure sequence; and the legal receiving end decodes the code word structure sequence to obtain a final key. The method and the device are used for improving the consistency rate of the secret keys among the legal users, so that the secret key generation and extraction efficiency is improved, and the safety of a rail transit system is improved.

The application provides a polar code soft input soft output decoding method, a decoding device and a communication device; the decoding method comprises the following steps: (S1) performing fast serial cancellation list decoding under dynamic frozen bit constraint for all special nodes constituting a polar code; the types of the special nodes comprise rate zero, rate one, repetition and single parity check; (S2) calculating the approximation of the sum of the posterior probabilities of the legal code words not accessed under each special node after decoding; (S3) using the approximation of the code book probability obtained in the step (S2) to calculate the bit level soft information of the output polar code. The low-latency polar code soft input soft output decoding method provided by the application improves the parallelism by realizing fast soft output decoding based on the Rate0, Rate1, REP and SPC nodes, and significantly reduces the decoding latency without losing the soft output precision compared with the SO-SCL decoding algorithm.

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 belief propagation LDPC decoding method and device based on deep learning, a medium and a program product. The method comprises the following steps: acquiring an LDPC code training sample set corresponding to a check matrix H; according to the check matrix H, determining a weight matrix and an activation function of each layer of a deep learning decoding model; based on the weight matrix and the activation function, using a belief propagation algorithm to establish a deep learning decoding model; training the deep learning decoding model by using the training sample set, and storing the trained deep learning decoding model as a decoder; and sending the LDPC code soft information which is corresponding to the check matrix H and needs to be decoded into the decoder to complete LDPC decoding. According to the method, iterative operation is completed by using deep learning in the error correction decoding process, the number of decoding iterations is reduced, and the sequence sent by the sending end is restored from the sequence containing noise and interference, so that the problem of decoding error codes caused by noise and other interference factors is solved.

The invention relates to the technical field of wireless communication, in particular to a super-Nyquist signal iterative interference elimination method based on symbol grouping and FEC (Forward Error Correction), which comprises the following steps of: acquiring bit streams, grouping symbols according to odd-even positions and encoding, and respectively generating and superposing odd-even sub-signals to generate FTN (Feeder Transfer Network) signals; performing matched filtering and sequence detection, and extracting soft information of odd and even positions; performing soft decoding on the soft information at the odd positions to generate Nyquist odd group signals; subtracting the odd-numbered group signals from the total signal of the receiving end to obtain even-numbered group feedback signals; performing matched filtering and soft decoding to obtain an even number position judgment bit, and regenerating an even number signal; and extracting an odd feedback signal by subtracting the total signal of the receiving end from the even regeneration signal, generating an odd decision based on Nyquist matched filtering and soft decoding, and performing loop iteration until ISI is completely eliminated. According to the invention, efficient and robust suppression of ISI in the FTN system can be realized, and the method can adapt to the dynamic change of an optical fiber channel.

A method for generating soft information for a digital signal decoder. The method includes receiving a first plurality of signals, each corresponding to a time index, each time index being associated with two states including state 1 and state 0. The method also includes processing the first plurality of signals to calculate path metric values of state 0 and 1 for generating each of a second plurality of most-likely symbols by hard decisions and intermediate information for a most-likely path and a second-likely path at each time index. The method includes computing a difference between the most-likely path and a second-likely path for a given one of the two states at each time index. The method also includes determining a soft information corresponding to either one of the two states at the time index per one of the second plurality of most-likely symbols.

The invention provides a compression method and device for soft information in a signal demodulation process and electronic equipment. The method comprises the following steps: acquiring linear soft information output by demapping in a signal demodulation process, wherein the linear soft information has a preset dynamic range; the linear soft information is subjected to dynamic range compression processing through a nonlinear quantization algorithm, nonlinear soft information is obtained, and the number of quantization levels allocated to low-amplitude soft information by the nonlinear quantization algorithm is larger than the number of quantization levels allocated to high-amplitude soft information by the nonlinear quantization algorithm; and outputting the non-linear soft information to a decoder, so that the decoder restores an original hard bit stream transmitted by a signal transmitting end based on a confidence coefficient characteristic in the non-linear soft information, and the bit width of the non-linear soft information is adaptive to the bit width constraint of the decoder on the input information. According to the invention, information loss in a signal demodulation process can be reduced.

Soft information can be used to train an artificial intelligence (AI) model. For example, a computer system determines first training data that includes a first image, first text, a second image, second text, a first indication of a first correspondence between the first image and the first text, and a second indication of a second correspondence between the second image and the second text. The computer system determines a likelihood of the first image and the second text corresponding to each other. The computer system generates second training data that includes the first image, the first text, the second image, the second text, the likelihood instead of the first indication, and the second indication. The computer system trains an AI model based at least in part on the second training data.

The invention relates to a dual dynamic optimization multi-user detection method based on SCMA in an uplink NOMA system, and belongs to the technical field of wireless communication. According to the method, the technical problems of insufficient multi-user interference suppression caused by codebook cross correlation enhancement in a high overload scene, poor convergence stability of a traditional detection algorithm and error code propagation caused by a hard decision mechanism are solved. The scheme of the invention comprises the following steps of: generating a dynamic codebook: constructing a low-mutual-interference codebook through resource load balancing and complex field amplitude phase joint optimization; dual confidence interference elimination: fusing user-level weight and symbol-level weight to dynamically adjust elimination intensity; according to the cross-layer iteration mechanism, soft information closed-loop feedback is achieved in combination with interference suppression merging equalization and hierarchical decoding; and dynamic damping updating: adaptively adjusting the soft information feedback intensity based on the signal-to-noise ratio to suppress oscillation. The method has the beneficial effects that the multi-user interference suppression capability is improved in a breakthrough manner, the interference elimination precision is revolutionarily optimized, and the system keeps ultrahigh reliability in a severe environment with a low signal-to-noise ratio.

The invention discloses a data processing method, device and equipment for a QC-LDPC decoder. The method comprises the following steps: storing posterior probability information into a first memory; in the reading stage of the QC-LDPC decoder, soft information corresponding to a layer where a check matrix is located is read from a first memory or a second memory, a check node value corresponding to the layer where the check matrix is located is read from a third memory, and a variable node update value is stored in the second memory; and in a write-in stage of the QC-LDPC decoder, reading the variable node update value from the second memory, storing the check node update value to a third memory, storing the soft information update value to the first memory and the second memory, and storing the soft information update value to the second memory. And the decoding result is read from the second memory after iteration is completed. By optimizing caching and calling of information such as check nodes, variable nodes and soft information, use of memory resources is reduced.

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.

The application discloses a low-complexity deep learning MIMO detection method based on partial MAP, comprising the following steps: obtaining multiple groups of training and test samples, and performing hierarchical and data preprocessing on the training and test data samples through QR decomposition to obtain K training sublayers and calculate the input and output labels of each training sublayer; training a DNN for generating local LLR in each detection stage of the K training sublayers based on a partial MAP method; performing layer-by-layer inspection from the Kth layer to the first layer, for each detection stage, calculating the local LLR by using the trained DNN, updating the LLR result of the current layer in combination with the prior information transmitted by the previous layer, and transmitting the LLR result to the next layer as prior information until the final LLR result is obtained; inputting the final LLR result into an FEC decoder to perform error correction and obtain a final signal estimation result; and the partial MAP directly outputs log-likelihood ratio soft information, and the combination of the partial MAP and a forward error correction code can obtain better detection performance.

This application provides an LDPC multi-level coded transmission method, apparatus, and electronic device, introducing a multi-level coded modulation scheme to achieve inter-stream and inter-bit code rate allocation based on channel quality differences, and implementing joint iterative optimization of detection and decoding at the receiver. At the transmitter, multi-level coded modulation is performed according to a pre-constructed parameter table, which allocates code rates at the sub-stream level and between bits for single-stream or multi-stream data. High-reliability streams / bits use higher code rates, while low-reliability streams / bits use lower code rates, thus achieving fine-grained code rate allocation. At the receiver, MIMO detection, demodulation, and decoding are jointly iteratively processed according to the corresponding multi-level coded modulation structure based on the same parameter table. Joint optimization of detection and decoding performance is achieved through hard or soft information feedback mechanisms, providing a high-spectral-efficiency and high-reliability transmission scheme for future mobile communication systems.

Disclosed are an MIMO detection method, a computer program product, an electronic device and a medium, which relate to the technical field of communications, and are applied to a receiver to obtain channel information, noise information and a set constellation configuration set, constellation points in the constellation configuration set being fixed and only including constellation points for message update; determining a to-be-processed signal which fails to be decoded; initializing an output symbol and first soft information according to the to-be-processed signal; updating the second soft information based on the first soft information, the to-be-processed signal, the channel information, the noise information and the constellation configuration set; updating the output symbol based on the second soft information, and updating the first soft information based on the output symbol and the second soft information; detecting whether the maximum number of updating iterations is reached or not; if not, returning to execute the step of updating the second soft information based on the first soft information, the channel information, the noise information and the constellation configuration set; and if yes, decoding the to-be-processed signal based on the output symbol. According to the invention, the processing delay is reduced, and the throughput is improved.

The present application relates to the technical field of communications. Disclosed are a DTX detection method and apparatus, and an electronic device and a storage medium. In the present application, the method comprises: a receiving end acquiring at least one group of soft information sequences of first information sent by means of a sending end; on the basis of a decoded information sequence determined from the at least one group of soft information sequences, obtaining a polar code sequence; and then on the basis of a sequence similarity between the polar code sequence and the at least one group of soft information sequences, detecting whether the sending end is in a DTX state, and optionally, if the sequence similarity is less than a similarity threshold value, determining that the sending end is in the DTX state. In this way, since the polar code sequence is decoded information, the reliability thereof is high, and the DTX state detection (or discrimination) effect is more obvious due to the sequence similarity. Therefore, the accuracy of DTX detection can be improved.

The present invention discloses an iterative detection decoding method based on tree search, comprising: initializing a K-Best detector; obtaining a priori message L through a FastSOL decoder; A1 (s i ); perform the K-Best detector with the prior message L A1 (s i ) to obtain a symbol estimate sequence; the symbol estimate sequence is converted into a bit estimate sequence, which is output to the FastSOL decoder for FastSOL decoding to obtain a decoded result sequence; a determination is made as to whether the maximum number of iterations has been reached. If not, the decoded result sequence is output to the K-Best detector as a priori information; otherwise, detection and decoding are completed, and the corresponding FER performance data is output. This invention utilizes soft information exchange between the detection and decoding modules to achieve better reliability than separate detection and decoding (SDD). This solution is optimized to meet the requirements of error rate performance and complexity, achieving better error rate performance and lower complexity by adjusting the layer width and message exchange.

A system includes a first chiplet that includes at least one demodulator for demodulating at least one received signal from a receiver to generate hard bits and soft information from the received signal and a second chiplet coupled to exchange information with the first chiplet. The second chiplet includes at least one correlator to detect a symbol pattern indicating frame boundaries of frames having a known frame symbol period length in an acquisition state and transitioning the first and second chiplets to a connected state in response to a threshold number of successful frame boundary detections. The at least one correlator uses soft bit representations to correlate and deduce the frame boundaries in a windowed mode using the known frame length and previous frame boundary information while in the connected state and transitions the first and second chiplets out of the connected state and back to the acquisition state in response to at least one unsuccessful frame boundary detection.

Acceleration of S-polarized ECC throughput by a scheduler is disclosed. A method of simplified successive cancellation list (SSCL) error decoding of an S-polar code includes representing an S-polar code as a perfect binary tree; providing a node v with a soft information vector from a parent node of v to compute a soft information vector for a left child node of v; providing v with a hard decision vector from the left child node and using it with to create a soft information vector and pass it to a right child node of v; providing v with a hard decision vector from its right child node and using it with to create a hard decision vector β v and pass it to its parent node; when v is an i-th leaf node of the perfect tree, updating two path metrics and selecting a path obtained by extending a current path by the lowest path metric.

This invention discloses a method and system for a multi-mode fusion wireless communication chip. By constructing a four-dimensional joint observation vector set, the received signals of different communication systems are regarded as observations of the same channel under different projection spaces. Then, the local coherent structure is extracted and piecewise fitting is performed on the four-dimensional complex unit sphere to generate a piecewise constant joint channel state identifier sequence. This sequence does not depend on pilot symbols and is derived only from the consistency of the received signal itself, possessing low overhead, fast response, and strong cooperative characteristics. On this basis, resource allocation, parameter configuration, phase preset, interference cancellation, and soft information fusion are all carried out around the same joint channel state identifier, making the originally fragmented reception processes of each system form a closed-loop linkage. Therefore, it achieves a significant reduction in channel state representation overhead, close synchronization between state updates and actual channel changes, and deep cooperation between the physical layer and demodulation layer of multiple systems.

The present invention provides a method for generating LDPC soft information, comprising reading hard bit data corresponding to data stored in an NVM; performing LDPC hard decision decoding based on the hard bit data to obtain an LDPC hard decision decoding result and a hard decision decoding output; if the LDPC hard decision decoding result is a failure, reading soft bit data associated with the hard bit data; mapping the hard decision decoding output and the soft bit data into soft information; and performing LDPC soft decision decoding based on the soft information. The technical solution of the present invention can reduce the number of repeated flash reads, improve throughput, and increase decoding success rate.

The invention discloses a communication system of an improved parallel cascade LDPC code structure based on a single encoder, and belongs to the technical field of aviation platform laser communication. Aiming at the bottlenecks that the traditional PCGC depends on double encoders, the hardware overhead is large, the decoding delay is high and the complementarity requirement on component codes is harsh, the system adopts a single encoder architecture design: firstly, a basic verification sequence is generated through a single LDPC encoder, and differential verification constraints are constructed through interleaving and repeating operations; meanwhile, a zero syndrome and non-zero syndrome dual-check sequence design is introduced, so that the minimum distance of a code word is increased; a decoding end fuses a normalized minimum sum algorithm and a hierarchical message updating and dynamic early stop mechanism, combines channel sensing soft information construction and a self-adaptive interleaving and redundancy allocation strategy, and adapts to composite channel characteristics of an aviation platform.

The embodiment of the invention provides a data decoding error correction method and device, a storage medium and an electronic device. The method comprises the following steps: determining a plurality of test sequences based on soft information of to-be-decoded data; a first test sequence and a second test sequence are removed from the plurality of test sequences to obtain a target test sequence, and the first test sequence is a test sequence with hard decoding failure; the second test sequence is N-1 test sequences in N test sequences which are successfully subjected to hard decoding and have the same flip position after hard decoding; wherein N is a positive integer greater than 1; and performing decoding error correction on the to-be-decoded data based on the target test sequence. Through the embodiment of the invention, the problems of high decoding complexity and large delay of a BCH soft decoding mode in the related technology can be solved, and meanwhile, the effect of reducing the consumption of soft decoding resources can be achieved.

This invention discloses a joint blind channel estimation and modulation identification method based on adaptive hybrid regeneration, belonging to the field of blind signal processing in communication. This method addresses the problems of error propagation caused by hard-decision regeneration and excessive computational complexity of soft-information regeneration in iterative blind receivers by introducing an adaptive hybrid decision regeneration mechanism into the iterative loop of channel estimation and data detection. This mechanism dynamically sets a threshold based on the confidence level of the posterior log-likelihood ratio output by the decoder, using hard decision for high-confidence information and soft decision for low-confidence information, and adaptively adjusting the threshold based on the target soft decision rate to balance performance and computational overhead. This invention can effectively suppress error propagation under conditions of unknown modulation coding and channel state, achieving reliable joint blind estimation and identification with controllable computational complexity.

A method for generating soft information for a digital signal decoder. The method includes receiving a first plurality of signals, each corresponding to a time index, each time index being associated with two states including state 1 and state 0. The method also includes processing the first plurality of signals to calculate path metric values of state 0 and 1 for generating each of a second plurality of most-likely symbols by hard decisions and intermediate information for a most-likely path and a second-likely path at each time index. The method includes computing a difference between the most-likely path and a second-likely path for a given one of the two states at each time index. The method also includes determining a soft information corresponding to either one of the two states at the time index per one of the second plurality of most-likely symbols.

The present invention belongs to the technical field of space communication and satellite communication, and particularly relates to a maximum a posteriori probability decoding method and system for high code rate convolutional codes. The method includes: converting the soft information of the received high code rate convolutional codeword into log-likelihood ratio information; updating the forward information on the Trellis diagram; updating the backward information on the Trellis diagram; calculating the edge information of all Trellis branches according to the updated forward information and backward information; obtaining the log-likelihood a posteriori probability information of each input bit according to the edge information of each branch; and obtaining the final decoding output through the decision of the log-likelihood a posteriori probability information of each input bit. By adopting the method of the present invention, the bit error rate of the CCSDS high code rate convolutional code can be reduced.

The invention relates to the technical field of decoding, and provides a source-channel joint decoding method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining the initialization information of a channel encoder, and the prior probability information of a variable node of a source decoder; determining check node information of the information source decoder based on initialization information and the prior probability information; executing the following iteration steps: updating the soft information of the variable node of the information source decoder based on the check node information and the initialization information; and based on the updated soft information, performing decoding judgment to determine a decoding result. According to the method, check node information of a source decoder is determined based on initialization information and prior probability information, soft information of variable nodes of the source decoder is iteratively updated based on the check node information and the initialization information, that is, the information of a source is used as available soft information in the decoding process, the coding gain is improved, and the decoding efficiency is improved. Therefore, the accuracy of source-channel joint decoding is improved.

The present invention provides a data quantization method, device, and storage medium, relating to the field of wireless communication technology. The method includes: performing digital down-conversion processing on an input signal based on a first quantization bit width to obtain a baseband signal; the first quantization bit width is determined based on the peak-to-average ratio of the input signal; performing channel estimation and equalization processing on the baseband signal based on a second quantization bit width; the second quantization bit width is obtained based on real-time calculation of the power of pilot symbols in the baseband signal; demodulating the baseband signal after channel estimation and equalization processing, and dynamically truncating the demodulated soft information based on the second quantization bit width and modulation mode to obtain truncated soft information; performing saturation quantization truncation processing on the truncated soft information, and outputting the truncated soft information to a decoder. This optimizes signal quantization accuracy and resource efficiency.

The invention discloses an enterprise credit analysis and rating method based on multi-source soft information processing, and belongs to the technical field of data processing, and the method comprises the steps: obtaining multi-source information data containing soft information and hard information; preprocessing the multi-source information data to generate preprocessed data; extracting feature data used for representing credit conditions from the preprocessed data; comparing different source features in the feature data to generate a consistency evaluation result between the feature data; performing dynamic weighted fusion on the feature data based on a consistency evaluation result to generate fused feature data; and inputting the fused feature data into the credit rating model to generate a credit rating result, and adopting a technical means of generating a consistency evaluation result by comparing different source features in the feature data and performing dynamic weighted fusion on the feature data based on the result to effectively improve the accuracy and reliability of enterprise credit rating.

The invention relates to a joint coding OTFS iterative detection method, which belongs to the field of wireless communication, and is characterized in that based on an orthogonal time-frequency-space OTFS modulation system, a coding transmitting signal of a transmitting end reaches a multi-antenna receiving end through a time-varying multipath channel; preliminarily separating received signals from different angles of arrival at a receiving end by using a multi-antenna array and beam forming; then, the separated signals pass through an iteration Dual MRC detector to obtain symbol-level detection information; symbol-level information is converted into bit-level LLR information through LLR demodulation of QAM, the bit-level LLR information is sent to a decoder, and detection and decoding are completed through continuous iteration. According to the method, the error code performance of the OTFS system is improved by using multiple antennas, beam forming, soft information exchange between the iterative Dual MRC detector and the decoder and iterative decoding.