50 results about "Sum product algorithm" patented technology

A method for decoding Low Density Parity Check (LDPC) codes comprises executing a sum product algorithm to recover a set of information bits from an LDPC code represented as a bipartite graph of symbol nodes and check nodes, the sum product algorithm being responsive to input log likelihood ratios associated with the symbol nodes. The check nodes are updated by generating a set of forward difference metrics and a set of backward difference metrics in dependence on the ratios of logarithmic probabilities each associated with a corresponding symbol node of the LDPC code, updating each metric in the set of forward difference metrics in dependence on the absolute value of the log likelihood ratio associated with the symbol node and the absolute value of the previous metric in the set, updating each metric in the set of backward difference metrics in dependence on the absolute value of the log likelihood ratio associated with the symbol node and the absolute value of the previous metric in the set, and generating log likelihood ratios to be propagated back to each symbol node in dependence on the updated sets of forward and backward difference metrics.

The present invention relates to a decoding method and a decoder, a program, a recording-and-reproducing apparatus and a method, and a reproducing apparatus and a method that are suitable for decoding encoded data encoded by using a linear code on ring R. A low-density processing unit performs parity-check-matrix low-density processing, performs linear combination for rows of a parity check matrix included in an obtained reception word, and generates a parity check matrix according to the linear-combination result, thereby reducing the density of the parity check matrix used for decoding, at step S21. Then, at step S22, an LDPC decoding unit performs decoding by using a sum product algorithm (SPA) by using the parity check matrix whose density is reduced through the processing performed at step S21. Where the processing at step S22 is finished, the LDPC decoding unit finishes decoding for the reception word. The present invention can be used for an error-correction system.

The invention provides an AUV (Autonomous Underwater Vehicle) multi-source information fusion method andequipment based on a factor graph, which are used for realizing navigation and positioning of anAUV integrated navigation system. According to the method, an information fusion problem of the AUV integrated navigation system is converted into a maximum posteriori probability problem for solvingjoint probability distribution of multivariate random variables by utilizing a factor graph theory, and the maximum posteriori probability problem is expressed by using a factor graph model. Optimalestimation of the navigation state is achieved according to transmission and updating of a factor graph message transmission algorithm, namely a sum product algorithm, in a factor graph model of the AUV multi-source information integrated navigation system. The method effectively solves the problems of asynchronization and short-time failure of updating frequencies of different navigation information sources in an AUV integrated navigation system, and is suitable for underwater complex and changeable environments and task requirements.

The invention discloses a bit flipping based LDPC code local searching and decoding method and mainly aims at solving the problem that an existing bit flipping type algorithm is poor in error correction performance and sum-product algorithm hardware implementation is complicated. The technical scheme is that a linear programming decoding mode and odd-even check are combined to form a new decoding model to implement the method, and the method comprises the steps of 1 initializing decoding parameters; 2 sequentially flipping multiple variable nodes simultaneously, and receiving a nearest code words by decreasing a target function value searching distance; 3 judging whether decoding is completed or not according to syndrome vectors; 4 sequentially flipping a value of one variable node and searching effective code words by decreasing non-zero elements in the syndrome vectors; 5 constructing multiple initial solution vectors to execute bit flipping code search in a looping mode; 6 using solution vector outputs as translated code words if the syndrome vectors are zero vectors. The bit flipping based LDPC code local searching and decoding method is good in error correction performance, high in convergence rate and low in hardware implementation complication level, can remarkably improve the efficiency of a decoding module of a communication system with a binary symmetric channel and can be used in the technical field of communication.

The invention discloses a terminal positioning method and a base station, comprising: A, establishing a historical data base storing position coordinates of more than one clustering point and an AOA, a TOA and an SNR of each clustering point; B, for each terminal to be positioned, acquiring the AOA, the TOA and the SNR of the terminal, or the AOA, the TOA, the SNR and an AGPS position coordinate; if the AGPS position coordinate is obtained, taking the obtained AGPS position coordinate as an initial position estimation of the terminal, if not, then finding a clustering point which is closest to the terminal to be positioned based on the obtained AOA, the TOA and the SNR and the AOA, the TOA and the SNR of each clustering point, and taking the found position coordinate of the clustering point as an initial estimation position of the terminal to be positioned; and calculating the approximate distance between every two random terminals to be positioned; C, obtaining the final estimation position of each terminal to be positioned by adopting sum product algorithm and iterative calculation based on the obtained approximate distance and the initial estimation position. The method provided by the invention is not affected by scene, and is capable of carrying out better positioning.

Systems and methods for generating check node updates in the decoding of low-density parity-check (LDPC) codes use new approximations in order to reduce the complexity of implementing a LDPC decoder, while maintaining accuracy. The new approximations approximate the standard sum-product algorithm (SPA), and can reduce the approximation error of min-sum algorithm (MSA) and have almost the same performance as sum-product algorithm (SPA) under both floating precision operation and fixed-point operation.

Disclosed is a method and apparatus for dynamic channel assignment (DCA) in a wireless network, which describes the complex channel assignment problem with a decoding problem. The invention describes the decoding problem with a normal graph and specifies all the local rules enforced by all the nodes at access point sides and subscriber sides. Then, the invention carries out the sum-product algorithm to solve the DCA. It is not only a fully-distributed low-complexity DCA technology, but also significantly increases the network throughput. The invention further adopts the concept of subscriber exclusive region to guarantee the link quality between a subscriber and an access point.

A method of generating check matrixes for LDPC codes includes analyzing a “Sum-Product Algorithm” for Low-Density Parity-Check codes, on the assumption that a Log Likelihood Ratio between input / output data at a decoder can be approximated in a Gaussian distribution; fixing a coding rate; obtaining an optimal ensemble, which is an ensemble that minimizes the threshold of SNR, of row and column weights in one linear programming to maximize a Gaussian noise; and generating a check matrix for LDPC codes in accordance with the ensemble obtained.

Techniques are described for performing a check node update (CNU) as part of iterative decoding of a low density-parity check (LDPC) code. The CNU uses a min-sum decoding approach that monitors whether two values received in messages from two variable nodes connected to a check nodes are equal and are the minimum value among the values received by the check nodes from other variable nodes connected thereto. Upon detecting such an event, the minimum value is adjusted by reducing it by an adjustment value to generate an adjusted minimum value. This adjusted minimum value approximates the minimum value that a sum-product algorithm (SPA) decoding approach would have generated. The adjusted minimum value is included in a response message sent from the check node to a variable node. The bit corresponding to that variable node is decoded based on this adjusted minimum value.

The invention relates to a minimum sum decoding method of selective annealing of a low density parity check code, which is suitable for soft decision decoding of the low density parity check codes and replaces the traditional multiplicative revise minimum sum decoding method. Based on the minimum sum decoding method, the invention adopts a multiplicative factor smaller than 1 to revise output of check nodes with unsuccessful check. The method comprises the following implementation steps of: merging external information quantity input by the check nodes and information from a channel by a variable node as decision soft information of iteration; probing whether a decision sequence satisfies a check equation; taking down or updating a node sequence set U with unsuccessful check, if U is empty, finishing decoding, and if U is not empty, updating and outputting information to the variable node by the check nodes based on minimum sum regulations; carrying out annealing treatment on check node output information belonging to U plus a factor smaller than 1; and turning to next iterative decoding. In the method, the performance is obviously superior to other improved minimum sum decoding method, and the calculation complexity is far lower than a sum-product algorithm.

A low-density parity check (LDPC) code decoding method may be provided. The LDPC code decoding method may linearize or perform step-approximation on a natural logarithm hyperbolic cosine function included in a check node updating equation of a sum-product algorithm used for decoding an LDPC code, and may convert the linearized function to correspond to a check node updating equation of a min-sum algorithm.

The invention relates to the field of communication system technology, in particular a Hamming code iterated interpretation method based on sum of products algorism, which can be applied to bluetooth systems, computer memory systems, mobile memory systems and DVD system, wherein iterated code translation based on sum of products algorism is introduced into Hamming code to solve the problem of code interpreting complexity and performance.

The invention discloses a low-complexity maximum likelihood approximate q-ary LDPC (Low-Density Parity-Check) code decoding method. The problem that in the prior art, a trapping set of an iterative decoding method for q-ary LDPC codes is not converged and the problem that the complexity of the approximate maximum likelihood decoding method for the q-ary LDPC codes is relatively high are solved. The method provided by the invention comprises the steps of carrying out iterative decoding; converting a q-ary form into a binary form; selecting deletion bits; selecting additional deletion bits; carrying out bit deletion operation on a binary judgment sequence; carrying out binary list erasure decoder on a deletion sequence; establishing a candidate codon list; determining the current minimum Euclidean distance; and assigning the current minimum Euclidean distance to the current threshold Euclidean distance; and finishing decoding. According to the method, an FFT-QSPA (fast Fourier transform based q-ary sum-product algorithm) and a binary list erasure decoder LED method with relatively low complexity are cascaded, so the decoding performance is approximate to the maximum likelihood decoding performance, and the decoding complexity is relatively low.

The invention discloses a combined channel state detecting and decoding method based on a state transition model, which belongs to the technical field of satellite communication in motion. Interrupted channel structure information is utilized to construct an interrupted channel state transition model, a sum-product algorithm is adopted, a channel transition probability function is utilized to update channel state variable node messages by means of a factor graph structure, and iterative computation is carried out continuously to obtain channel state distribution and decoding results. According to the invention, the channel transition probability function is utilized to update channel state variable node messages, the dependence on the information symbol length is effectively lowered, and under a low signal to noise ratio, the channel state information is well detected. The method can achieves the error detection probability identical with that a channel state information detection algorithm based on signal energy with relatively high detection precision. The method has the following substantial advantages that the detection precision is high, and detection and decoding are carried out in a combined manner.

The invention discloses a cooperative positioning method based on a sequential consistent weighted sum-product algorithm. The sequential consistent weighted sum-product algorithm is employed to estimate the position of a target node by calculating the corrected posterior probability distribution of the position of the target node. The convergence speed is fast, and better convergence solution is provided. The method is applicable to real-time and accurate cooperative positioning of a wireless sensor network.

The invention relates to a low-density even-odd check decoding method, which includes that the maximum iteration times is set, and variable nodes are initialized through channel output; iterative operation is carried out, and a correctional minimum sum-product algorithm is adopted to calculate the likelihood ratio of current check node and the variable node; the likelihood ratio and posterior probability of the current variable node and the check node are calculated; the current bit value is judged according to posterior possibility to obtain the decoded result; the decoded result is verified and judged if the iteration times reaches the maximum iteration times; if so, codeword is output; if not, the iteration times pluses 1 to continue the iteration operation. The invention adopts a simplified algorithm, in particular to the calculation simplification of check node, so the operation speed is greatly improved; thereby, the low-density even-odd check decoding is possibly realized in software.

The invention discloses a joint channel state detection and decoding algorithm based on classification learning and belongs to the technical field of on-the-move satellite communication. An intermittent channel state transfer model is established by utilizing intermittent channel structure information; through a sum-product algorithm, by means of transmission among factor graph structure channel observation function nodes, channel state variable nodes, received symbol variable nodes, symbol mapping function nodes, mixed mapping nodes and coding constraint nodes, and through weighted average of neighbor channel state node information, current channel state node information is obtained; and through continuous iterative computation, a channel state distribution and decoding result is obtained. Compared with a channel state detection and decoding method based on the channel state transfer model, the algorithm has the obvious advantages of being low in complexity and self-adaptive to channel change and the like.

The invention provides an iterative massage passing (IMP) PN code capturing method based on a sum-product algorithm on the condition of a low signal to noise ratio. According to the method, an m sequence is modelized into a special linear block code; a sum-product decoding algorithm is executed on a Tanner graph to obtain maximum posteriori estimation of the m sequence; and an initial state is selected by introducing a posteriori log-likelihood ratio to generate a local m sequence; and at last, serial correlation verification is carried out with reception data and capturing is completed. The greatest advantage of the method provided in the invention is as follows: maximum posteriori estimation of an m sequence is directly decoded by utilization of a sum-product decoding algorithm and a posteriori log-likelihood ratio is introduced to select an initial state. Besides, the method has advantages of rapid capturing speed, low complexity and excellent performance under a low signal to noise ratio. According to the invention, a fundamental principle on IMP PN code capturing is mainly introduced and then an IMP PN code capturing method based on a sum-product algorithm is provided; and an analysis on a selection process of an initial state of an m sequence is emphasized and a detailed flow chart is provided; at last, a capturing performance and a complexity of the method are analyzed though examples.

Systems and methods for generating check node updates in the decoding of low-density parity-check (LDPC) codes use new approximations in order to reduce the complexity of implementing a LDPC decoder, while maintaining accuracy. The new approximations approximate the standard float-point sum-product algorithm (SPA), and can reduce the approximation error of min-sum algorithm (MSA) and have almost the same performance under 5 bits fix-point realization as the float-point sum-product algorithm (SPA).

The invention provides an iterative massage passing (IMP) PN code capturing method based on a sum-product algorithm on the condition of a low signal to noise ratio. According to the method, an m sequence is modelized into a special linear block code; a sum-product decoding algorithm is executed on a Tanner graph to obtain maximum posteriori estimation of the m sequence; and an initial state is selected by introducing a posteriori log-likelihood ratio to generate a local m sequence; and at last, serial correlation verification is carried out with reception data and capturing is completed. The greatest advantage of the method provided in the invention is as follows: maximum posteriori estimation of an m sequence is directly decoded by utilization of a sum-product decoding algorithm and a posteriori log-likelihood ratio is introduced to select an initial state. Besides, the method has advantages of rapid capturing speed, low complexity and excellent performance under a low signal to noise ratio. According to the invention, a fundamental principle on IMP PN code capturing is mainly introduced and then an IMP PN code capturing method based on a sum-product algorithm is provided; and an analysis on a selection process of an initial state of an m sequence is emphasized and a detailed flow chart is provided; at last, a capturing performance and a complexity of the method are analyzed though examples.

The invention discloses a multi-AUV collaborative navigation method adopting a factor graph and sum product algorithm. The method comprises the following steps that firstly, a state equation and a measurement equation are established for describing an AUV navigation system; secondly, a corresponding multi-AUV collaborative navigation system factor graph model is established according to the state equation and the measurement equation of the AUV, and the factor graph model contains a ring structure, wherein the loop-containing factor graph is equivalently converted into a loop-free factor graph model containing an aggregation node in order to obtain an accurate solution of the system; and finally, one-step prediction updating is peformed on the position and the azimuth angle of the AUV according to a system state equation, and then the position and the azimuth angle of the AUV are estimiated according to the observed quantity between the AUVs obtained by the system in combination with a measurement equation. The estimation method based on the graph theory is adopted, and the method is novel. Besides, the actual engineering positioning precision can be met, meanwhile, the calculated amount is smaller, and the method shows higher system expandability and is higher in applicability in actual engineering application.

This invention provides a decode method for low density packet checking codes, which tests the likelihood ratio output by information nodes in the period of an iterative decoding of sum product algorithm to adaptively output the hard judgment value of reliable information node directly and stops refreshment to reliable information nodes in the successive iterative period to reduce the operation volume.

The invention provides an AUV multi-source information fusion method and device based on a factor graph to realize navigation and positioning of an inertial-based autonomous underwater vehicle (Autonomous Underwater Vehicle, AUV) integrated navigation system. In this method, the information fusion problem of AUV integrated navigation system is transformed into the maximum a posteriori probability problem of solving the joint probability distribution of multivariate random variables by using the factor graph theory, which is represented by a factor graph model. According to the factor graph message passing algorithm, that is, the sum-product algorithm, the transfer and update in the factor graph model of the AUV multi-source information integrated navigation system can realize the optimal estimation of the navigation state. The invention effectively solves the problems of asynchronous update frequency and short-term failure of different navigation information sources in the AUV integrated navigation system, and is suitable for complex and changeable underwater environments and task requirements.

The invention discloses a method and a device for acquiring the capacity of asymmetric game players, a facility and a medium. The method comprises the following steps: acquiring game objects of an asymmetric game; constructing a probabilistic graphical model according to the game objects, in the probabilistic graphical model, setting one team capacity regulating factor for each team participatingin game playing of the asymmetric game, wherein the team capacity regulating factor acts to each member in the team, and in the probabilistic graphical model, setting an exerting regulating factor foreach member participating in game playing of the asymmetric game, wherein the exerting regulating factor acts to each member in game playing; according to the probabilistic graphical model, acquiringa factor graph; acquiring game playing data; and based on the factor graph and according to the game playing data, determining the capacity of the players by using a sum product algorithm. With the technical scheme, the capacity of each game player participating in the asymmetric game can be acquired.