CN101345602B - Early termination method of low density check code iteration decoding - Google Patents

Early termination method of low density check code iteration decoding Download PDF

Info

Publication number
CN101345602B
CN101345602B CN 200810041921 CN200810041921A CN101345602B CN 101345602 B CN101345602 B CN 101345602B CN 200810041921 CN200810041921 CN 200810041921 CN 200810041921 A CN200810041921 A CN 200810041921A CN 101345602 B CN101345602 B CN 101345602B
Authority
CN
China
Prior art keywords
nodes
information
value
parity check
hard decision
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN 200810041921
Other languages
Chinese (zh)
Other versions
CN101345602A (en
Inventor
华颖
俞晖
陈徐薇
潘晓
徐友云
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shanghai National Engineering Research Center of Digital Television Co Ltd
Original Assignee
Shanghai Jiaotong University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shanghai Jiaotong University filed Critical Shanghai Jiaotong University
Priority to CN 200810041921 priority Critical patent/CN101345602B/en
Publication of CN101345602A publication Critical patent/CN101345602A/en
Application granted granted Critical
Publication of CN101345602B publication Critical patent/CN101345602B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Abstract

An early termination method for low density check code iteration coding belongs to channel coding technology field. In the invention, after each iteration process for belief propagation method finishes, if present hard decision result does not satisfy check equation, then computing check node reliability value, if relative error of the reliability value and iteration process reliability value of last time is smaller than a threshold, then interrupting counter and add 1 to the value, or interrupting counter and value being 0; if value of interrupting counter is bigger than a threshold, then interrupting iteration process, outputting present hard decision result as coding result of coder, or entering next iteration process. In the invention, check node reliability value is judged for present convergence type, computation complexity is low; compared with iteration coding early termination method, performance is equal or better; channel related parameter is not used thereby possessing a certain channel robust property.

Description

The in advance termination method of loe-density parity-check code iterative decoding
Technical field
The present invention relates to a kind of processing method of communication technical field, be specifically related to a kind of in advance termination method of loe-density parity-check code iterative decoding.
Background technology
LDPC code (loe-density parity-check code) is a kind of coding techniques of Gallager proposition in 1963, and it can be used as the error correction/detection technology of plurality of communication systems or information storage system.The performance of LDPC code is approached shannon limit, and decoding complexity is lower, and interpretation method has concurrency, at present many wireless communication standards all with the LDPC code as channel coding schemes.The LDPC code adopts the belief propagation method to decipher usually, and iteration is carried out on bipartite graph corresponding to code word.In each iteration, the soft value of information that represent probability exchanges between information nodes and parity check nodes and is upgraded, and the while, code word hard decision result was upgraded.If the hard decision result of certain iteration satisfies check equations, then decoding converges to a legal-code, and this moment, decode procedure was ended in advance.Otherwise decode procedure is proceeded, until reach the maximum iteration time that rule of thumb sets in advance.Said method can finish the decode procedure of decodable code word in advance.But for not decodable code word, then must carry out unnecessary many times iterative process, be unfavorable for reducing system power dissipation.
At present in the prior art, in the loe-density parity-check code iterative decoding process, end in advance the method for not decodable code word iterative process, mainly comprise two large classes: based on the method for hard value with based on the method for soft value, implement complexity based on the method for hard value lower, but it is not good enough to end effect, and can affect to a certain extent decoding performance; Method based on soft value can reduce mean iterative number of time better, guarantee that simultaneously decoding performance can not worsen, but computational complexity is higher.
Find by prior art documents, F.Kienle and N.Wehn are in " IEEE 61stVehicular Technology Conference (the 61st vehicle technology meeting of Institute of Electrical and Electronics Engineers) ", 2005.Pages:606-609 " the Low complexity stopping criterionfor LDPC code decoders (the low complex degree abort criterion of low-density check code encoder) " of upper proposition provided a kind of in advance termination method of the LDPC code iterative decoding based on soft value, this termination method is utilized the reliability value VNR of the posterior probability likelihood ratio computing information node of information nodes in the decode procedure, and judges the current iteration type according to the situation of change of this reliability value.When thinking that decode procedure is in the situation that can not restrain, end in advance iterative process.Its result of study shows, the decode procedure of ending in advance to restrain code word can reduce mean iterative number of time greatly when low signal-to-noise ratio, thereby saves the power consumption of decoder.But should the termination method need to utilize the posterior probability likelihood ratio of information nodes, computation complexity is higher; And need in the method to use a threshold value relevant with the characteristic of channel, need to adjust according to the various characteristics of channel, increased the enforcement difficulty of system.
Summary of the invention
The present invention is directed to above-mentioned the deficiencies in the prior art, a kind of in advance termination method of loe-density parity-check code iterative decoding has been proposed, use the external information calculation check node reliability value in the decode procedure, and judge the decoding type according to this reliability value, end in advance in some cases iterative process.Method of the present invention reduces mean iterative number of time and power consumption better, and implementation complexity is lower, and has certain cha nnel robustness.
The present invention is achieved by the following technical solutions, the present invention includes following steps:
Step 1 arranges the maximum iteration time of decode procedure and the threshold value that the reliability value changes relatively, the threshold value of ending Counter Value;
Step 2 in each iterative process, is used the belief propagation method to upgrade parity check nodes and is passed to the soft value of information of information nodes, the posterior probability likelihood ratio of information nodes, the soft value of information and the hard decision result that information nodes passes to parity check nodes;
Step 3, after the each iterative process of belief propagation method finishes, judge whether current hard decision result satisfies check equations, if do not satisfy, then pass to the reliability value of the soft value of information calculation check node of information nodes according to all parity check nodes in this iterative process; If satisfy, the hard decision result of this moment is exported in then decode procedure success and in advance termination;
Step 4 if the relative error of the reliability value that step 3 obtains and last iteration process reliability value is then ended Counter Value and added 1 less than the threshold value of the relative variation of reliability value of step 1 setting, makes zero otherwise end Counter Value;
Step 5, if end Counter Value greater than the threshold value of the termination Counter Value of step 1 setting, then end iterative process, current hard decision result is exported as the decoder for decoding result, otherwise enter the next iteration process, the iterations counter adds 1, and gets back to step 2, if the maximum iteration time that the iterations Counter Value is set greater than step 1 then enters step 6;
Step 6, if the iterations Counter Value greater than maximum iteration time, decode procedure finishes, with the hard decision result output of last iteration.
Describedly judge that whether current hard decision result satisfies check equations, is specially: calculate syndrome S=HHD T, wherein: H is the check matrix of LDPC code, and HD is the hard decision result, and the vector if syndrome S equals zero illustrates that then the hard decision result satisfies all check equations, and the decode procedure success is also ended in advance, and output hard decision at this moment is HD as a result; Otherwise show that the hard decision result does not satisfy all check equations.
Described renewal parity check nodes passes to the soft value of information of information nodes, and is specific as follows: to each parity check nodes
Figure GSB00000489013100031
M is the number of the parity check nodes of LDPC code:
At first, according to
Figure GSB00000489013100032
Figure GSB00000489013100033
Obtain the total information value Q at parity check nodes place j
Then, for any one and parity check nodes c jAdjacent information nodes v i, upgrade the soft value of information Q that parity check nodes passes to information nodes Ji,
Figure GSB00000489013100034
Sgn (Q Ji)=sgn (Q j) sgn (P Ij),
Wherein, P IjPass to the soft value of information of parity check nodes for information nodes, the set of all information nodes compositions that N (j) expression is adjacent with j parity check nodes,
Figure GSB00000489013100035
The probability likelihood ratio of described lastest imformation node and information nodes pass to the soft value of information of parity check nodes, are specially:
To each information nodes N is the code length of LDPC code.
At first, calculate posterior probability likelihood ratio
Figure GSB00000489013100038
Then, for any one and information nodes v iAdjacent parity check nodes c j, upgrade the soft value of information P that passes to parity check nodes Ij, right
Figure GSB00000489013100039
For hard decision HD as a result, it is updated to: HD i=sgn (Λ i);
Wherein, λ iBe the channel input message of i information nodes, Q JiPass to the soft value of information of information nodes for parity check nodes, the set of all parity check nodes compositions that N (i) expression is adjacent with i information nodes.
The reliability value of described calculation check node is specially: the reliability value
Figure GSB000004890131000310
Wherein, Q jBe the total information value of j parity check nodes, M represents the sum of parity check nodes.
Whether the relative error of described judge reliability value and last iteration process reliability value is specially less than the threshold value of setting: judge | CNR-CNR Last|＜λ CNR LastWhether set up, wherein, λ, CNR represents reliability value, CNR if being the threshold value that the reliability value changes relatively LastRepresent the reliability value in the last iteration.
Compared with prior art, the present invention has following beneficial effect: the present invention adopts parity check nodes reliability value to judge current convergence type, and computation complexity is lower; Compare performance quite with in advance termination method of existing iterative decoding or better, do not have to use the parameter relevant with the characteristic of channel, thereby have certain cha nnel robustness.
Description of drawings
Fig. 1 is the structure chart of a LDPC code bipartite graph.
Fig. 2 is the schematic diagram of parity check nodes and information nodes information updating in the belief propagation method;
Wherein: be to upgrade the schematic diagram that parity check nodes passes to the soft value of information of information nodes (a); (b) for the posterior probability likelihood ratio of lastest imformation node and pass to the schematic diagram of the soft value of information of parity check nodes.
Fig. 3 is the workflow diagram of the inventive method.
Fig. 4 be the inventive method under additive white Gaussian noise (AWGN) channel with the performance comparison diagram of additive method.
Fig. 5 be the inventive method under Rayleigh (Rayleigh) channel with the performance comparison diagram of additive method.
Embodiment
Below in conjunction with accompanying drawing embodiments of the invention are elaborated: the present embodiment is implemented under take technical solution of the present invention as prerequisite, provided detailed execution mode and concrete operating process, but protection scope of the present invention is not limited to following embodiment.
As shown in Figure 1, the structure chart that adopts a LDPC code bipartite graph of the present embodiment method, i.e. the connection diagram of parity check nodes and information nodes, information nodes is labeled as v, parity check nodes is labeled as c, the number of information nodes equals code length N, and the number of parity check nodes is M.
The present embodiment comprises following concrete steps:
Step 1 is according to received bit log-likelihood ratio value initialization J ∈ [1, M]: P Ij=λ i, wherein N and M are respectively the code length of LDPC code and the number of parity check nodes, λ iBe the channel input message of i information nodes, the maximum iteration time iter of decode procedure is set Max, initialization iterations Iteration=1; The threshold value λ that the parameter reliability value of the method for ending in advance changes relatively and the threshold value P that ends Counter Value are set, and counter Counter=0 is ended in initialization, this and last iteration parity check nodes reliability value CNR and CNR LastBe set to 0;
Step 2 is upgraded the total information value Q of parity check nodes successively according to the belief propagation method j, parity check nodes passes to the soft value of information Q of information nodes Ji, the posterior probability likelihood ratio Λ of information nodes i, information nodes passes to the soft value of information P of parity check nodes Ij, and the hard decision of information nodes HD=[HD as a result 1, HD 2..., HD N];
Shown in Fig. 2 (a), described renewal parity check nodes passes to the soft value of information Q of information nodes Ji, specific as follows: to each parity check nodes
Figure GSB00000489013100051
Basis at first The total information value at calculation check node place;
Then for any one and parity check nodes c jAdjacent information nodes v i, upgrade the soft value of information Q that passes to information nodes Ji,
Figure GSB00000489013100054
Sgn (Q Ji)=sgn (Q j) sgn (P Ij),
Wherein, the set of all information nodes compositions that N (j) expression is adjacent with j parity check nodes, f ( x ) = ln e x + 1 e x - 1 , sgn ( x ) = 1 , x &GreaterEqual; 0 - 1 , x < 0 .
Shown in Fig. 2 (b), the posterior probability likelihood ratio Λ of described lastest imformation node iAnd pass to the soft value of information P of parity check nodes Ij, information nodes the hard decision result, be specially:
To each information nodes
Figure GSB00000489013100057
At first, calculate posterior probability likelihood ratio
Figure GSB00000489013100058
Then, for any one and information nodes v iAdjacent parity check nodes c j, upgrade the soft value of information P that passes to parity check nodes Ij, right
Figure GSB00000489013100059
Hard decision as a result HD is updated to: HD i=sgn (Λ i);
The wherein set of N (i) expression all parity check nodes compositions adjacent with i information nodes.
Step 3 is calculated syndrome S=HHD T, wherein H is the check matrix of LDPC code.The vector if syndrome S equals zero, then illustrate hard decision as a result HD satisfy all check equations, decode procedure success is also ended in advance, the hard decision of output this moment is HD as a result; Otherwise enter step 4.
Step 4, calculation check node reliability value CNR:
Figure GSB00000489013100061
Wherein, Q jIt is the total information value of j parity check nodes;
Step 5, if | CNR-CNR Last|＜λ CNR Last, then end counter Counter and add 1; Otherwise ending counter Counter makes zero; If end counter Counter greater than P, then iterative process failure and execution are ended in advance, with the as a result HD output of hard decision of this iterative process; Otherwise forward step 6 to.
Step 6, CNR Last=CNR, iterations Iteration adds 1.Repeating step two is to step 5, until iterative process ends to withdraw from advance, perhaps iterations Iteration reaches iter Max
As shown in Figure 3, be the flow chart of an iterative process of the present embodiment method loe-density parity-check code, corresponding with the step 2 to six of foregoing description.
Shown in Fig. 4,5, be the LDPC code of code length 1944, code check 1/2 take the 802.11n standard definition as example, adopt the implementation effect of the present embodiment method.
As shown in Figure 4, under additive white Gaussian noise (AWGN) channel of two-phase offset keying (BPSK) modulation, 802.11n the code length 1944 of standard definition, the LDPC code of code check 1/2, the Performance Ratio when not adopting the iteration termination method, adopt based on the termination method (VNR) of information nodes reliability value and adopting the present embodiment method (CNR).Information updating is all based on the belief propagation method, and maximum iteration time all is made as 50 times.Threshold value VNR in the VNR termination method OffBe made as 4.0*1944=7776.λ in the CNR termination method is taken as 0.01, P and is made as 3.Solid dot solid line among the figure represents bit error rate (BER), and the solid dot dotted line represents frame error rate (FER), and the hollow dots dotted line represents mean iterative number of time.The CNR that the present embodiment proposes ends method in advance on almost not impact of decoding performance (BER and FER).Simultaneously, compare when not adopting the iteration termination method, mean iterative number of time (1.0dB is interval to 0.0dB) when low signal-to-noise ratio can reduce more than 80%, can reduce when signal to noise ratio is 0.6dB about 45%, and is basically identical when high s/n ratio.The mean iterative number of time of CNR method and existing iteration termination VNR method approach.
As shown in Figure 5, be under Rayleigh (Rayleigh) channel of BPSK modulation, the Performance Ratio of above-mentioned same LDPC code when not adopting the iteration termination method, adopt based on the termination method (VNR) of information nodes reliability value and adopting the present embodiment method (CNR).Information updating is equally all based on the belief propagation method, and maximum iteration time all is made as 50 times, and the parameter of ending in advance method is identical with upper figure.The CNR that the present embodiment proposes ends method in advance on almost not impact of decoding performance (BER and FER).Simultaneously, compare when not adopting the iteration termination method, mean iterative number of time (1.0dB is interval to 2.0dB) when low signal-to-noise ratio can reduce more than 70%, can reduce when signal to noise ratio is 2.6dB about 25%, and is basically identical when high s/n ratio.And existing more than CNR termination method based on the required mean iterative number of time of the VNR termination method of information nodes reliability value, the former mean iterative number of time was 1.6 times of the latter when signal to noise ratio was 2.4dB.This shows, CNR termination method has certain robustness to channel condition.
From the computation complexity angle, the in advance termination method of CNR of the present embodiment needs M+2 real arithmetic, and existing VNR termination method then needs N-1 real arithmetic.Because the number M of the parity check nodes of LDPC code is necessarily less than the number N of information nodes, the required computation complexity of CNR termination method is lower than VNR method, particularly in the situation that high code rate LDPC code.For example to act on the required operand of LDPC code of 7/8 code check approximately be 1/8 of VNR termination method to CNR termination method.

Claims (6)

1. the in advance termination method of a loe-density parity-check code iterative decoding is characterized in that, comprises the steps:
Step 1 arranges the maximum iteration time of decode procedure and the threshold value that the reliability value changes relatively, the threshold value of ending Counter Value;
Step 2 in each iterative process, is used the belief propagation method to upgrade parity check nodes and is passed to the soft value of information of information nodes, the posterior probability likelihood ratio of information nodes, the soft value of information and the hard decision result that information nodes passes to parity check nodes;
Step 3, after the each iterative process of belief propagation method finishes, judge whether current hard decision result satisfies check equations, if do not satisfy, then pass to the reliability value of the soft value of information calculation check node of information nodes according to all parity check nodes in this iterative process; If satisfy, the hard decision result of this moment is exported in then decode procedure success and in advance termination;
Step 4 if the relative error of the reliability value that step 3 obtains and last iteration process reliability value is then ended Counter Value and added 1 less than the threshold value of the relative variation of reliability value of step 1 setting, makes zero otherwise end Counter Value;
Step 5, if end Counter Value greater than the threshold value of the termination Counter Value of step 1 setting, then end iterative process, current hard decision result is exported as the decoder for decoding result, otherwise enter the next iteration process, the iterations counter adds 1, and gets back to step 2, if the maximum iteration time that the iterations Counter Value is set greater than step 1 then enters step 6;
Step 6, if the iterations Counter Value greater than maximum iteration time, decode procedure finishes, with the hard decision result output of last iteration.
2. the in advance termination method of loe-density parity-check code iterative decoding according to claim 1 is characterized in that, describedly judges that whether current hard decision result satisfies check equations, is specially: calculate syndrome S=HHD T, wherein: H is the check matrix of LDPC code, and HD is the hard decision result, and S is syndrome, and the vector if syndrome S equals zero illustrates that then the hard decision result satisfies all check equations, and the decode procedure success is also ended in advance, and output hard decision at this moment is HD as a result; Otherwise show that the hard decision result does not satisfy all check equations.
3. the in advance termination method of loe-density parity-check code iterative decoding according to claim 1 is characterized in that, described renewal parity check nodes passes to the soft value of information of information nodes, and is specific as follows: to each parity check nodes
Figure FDA00001788337000021
Wherein, M is the number of the parity check nodes of LDPC code:
At first, according to | Q j | = &Sigma; i &Element; N ( j ) f ( | P ij | ) , sgn ( Q j ) = &Pi; i &Element; N ( j ) sgn ( P ij ) Obtain the total information value Q at parity check nodes place j
Then, for any one and parity check nodes c jAdjacent information nodes v i, upgrade the soft value of information Q that parity check nodes passes to information nodes Ji, &ForAll; i &Element; N ( j ) : | Q ji | = f ( | Q j | - f ( | P ij | ) ) , sgn(Q ji)=sgn(Q j)·sgn(P ij)，
Wherein, P IjPass to the soft value of information of parity check nodes for information nodes, the set of all information nodes compositions that N (j) expression is adjacent with j parity check nodes,
Figure FDA00001788337000025
sgn ( x ) = 1 , x &GreaterEqual; 0 - 1 , x < 0 .
4. the in advance termination method of loe-density parity-check code iterative decoding according to claim 1 is characterized in that, the posterior probability likelihood ratio of described lastest imformation node and information nodes pass to the soft value of information of parity check nodes, are specially:
To each information nodes
Figure FDA00001788337000027
Wherein, N is the code length of LDPC code,
At first, calculate posterior probability likelihood ratio &Lambda; i = &lambda; i + &Sigma; j &Element; N ( i ) Q ji ;
Then, for any one and information nodes v iAdjacent parity check nodes c j, upgrade the soft value of information P that passes to parity check nodes Ij, right &ForAll; j &Element; N ( i ) : P ij = &Lambda; i - Q ji ;
For hard decision HD as a result, it is updated to: HD i=sgn (Λ i);
Wherein, λ iBe the channel input message of i information nodes, Q JiPass to the soft value of information of information nodes for parity check nodes, the set of all parity check nodes compositions that N (i) expression is adjacent with i information nodes.
5. the in advance termination method of loe-density parity-check code iterative decoding according to claim 1 is characterized in that, the reliability value of described calculation check node is specially: the reliability value
Figure FDA000017883370000210
Wherein, Q jBe the total information value of j parity check nodes, M represents the sum of parity check nodes.
6. the in advance termination method of loe-density parity-check code iterative decoding according to claim 1 is characterized in that, whether the relative error of described judge reliability value and last iteration process reliability value is specially less than the threshold value of setting: judge | CNR-CNR Last|＜λ CNR LastWhether set up, wherein, λ, CNR represents reliability value, CNR if being the threshold value that the reliability value changes relatively LastRepresent the reliability value in the last iteration.
CN 200810041921 2008-08-21 2008-08-21 Early termination method of low density check code iteration decoding Active CN101345602B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN 200810041921 CN101345602B (en) 2008-08-21 2008-08-21 Early termination method of low density check code iteration decoding

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN 200810041921 CN101345602B (en) 2008-08-21 2008-08-21 Early termination method of low density check code iteration decoding

Publications (2)

Publication Number Publication Date
CN101345602A CN101345602A (en) 2009-01-14
CN101345602B true CN101345602B (en) 2013-01-16

Family

ID=40247502

Family Applications (1)

Application Number Title Priority Date Filing Date
CN 200810041921 Active CN101345602B (en) 2008-08-21 2008-08-21 Early termination method of low density check code iteration decoding

Country Status (1)

Country Link
CN (1) CN101345602B (en)

Families Citing this family (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102005250A (en) * 2010-10-27 2011-04-06 记忆科技(深圳)有限公司 Quasi-cyclic low-density parity check code decoder and decoding method
CN105306074A (en) * 2015-11-04 2016-02-03 杭州国芯科技股份有限公司 Method for lowering power consumption of LDPC (Low Density Parity Check) decoder
CN108429605B (en) * 2018-03-09 2020-04-07 西安电子科技大学 Belief propagation decoding method based on reliability grading
CN113067582B (en) * 2019-12-13 2024-04-12 华为技术有限公司 Parallel decoding method and device
CN111917420B (en) * 2020-08-25 2023-07-04 广东省新一代通信与网络创新研究院 LDPC self-adaptive decoding method and LDPC self-adaptive decoder
CN112865812B (en) * 2021-01-18 2022-09-30 武汉梦芯科技有限公司 Multi-element LDPC decoding method, computer storage medium and computer
CN112994704B (en) * 2021-02-03 2023-06-16 Oppo广东移动通信有限公司 Decoding early termination method, storage medium and electronic equipment
CN113612485B (en) * 2021-08-03 2024-04-16 深圳宏芯宇电子股份有限公司 Decoding method, decoding device, equipment and storage device

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1968069A (en) * 2006-10-19 2007-05-23 上海交通大学 Low-complexity soft input/output detection method in multi-antenna orthogonal frequency-division multiplexing system
CN101106381A (en) * 2007-08-09 2008-01-16 上海交通大学 Hierarchical low density check code decoder and decoding processing method

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1968069A (en) * 2006-10-19 2007-05-23 上海交通大学 Low-complexity soft input/output detection method in multi-antenna orthogonal frequency-division multiplexing system
CN101106381A (en) * 2007-08-09 2008-01-16 上海交通大学 Hierarchical low density check code decoder and decoding processing method

Also Published As

Publication number Publication date
CN101345602A (en) 2009-01-14

Similar Documents

Publication Publication Date Title
CN101345602B (en) Early termination method of low density check code iteration decoding
US7539920B2 (en) LDPC decoding apparatus and method with low computational complexity algorithm
Zhang et al. Lowering LDPC error floors by postprocessing
US7454684B2 (en) Apparatus and method for turbo decoder termination
US20050229087A1 (en) Decoding apparatus for low-density parity-check codes using sequential decoding, and method thereof
CN109257148B (en) Polarization code BP decoding method based on Gaussian approximate threshold judgment
CN102138282B (en) Reduced complexity LDPC decoder
CN103208995B (en) A kind of premature termination method of low density parity check code decoding
US8291298B2 (en) Analog iterative decoder with early-termination
CN108964669B (en) LDPC code quadratic programming decoding method based on degree decomposition and alternative multiplier method
CN105959015A (en) LDPC code linear programming decoding method based on minimum polyhedral model
CN106888026A (en) Segmentation polarization code coding/decoding method and system based on LSC CRC decodings
CN101345532A (en) Decoding method for LDPC channel code
CN107612560A (en) Polarization code earlier iterations method of shutting down based on partial information bit log likelihood ratio
CN105530014A (en) LDPC code alternating direction multiplier decoding method based on simplified projection operator
Deng et al. Reduced-complexity deep neural network-aided channel code decoder: A case study for BCH decoder
CN101577607A (en) Normalization minimum sum decoding method capable of terminating iteration early
US11184025B2 (en) LDPC decoding method and LDPC decoding apparatus
CN103607208A (en) LDPC minimum sum decoding method based on normalization correction factor sequences
CN101635574B (en) Method for increasing convergence rate of decoder for hierarchical irregular low-density check code
Wang et al. Low-power vlsi design of ldpc decoder using dvfs for awgn channels
CN116614142A (en) Combined decoding method based on BPL decoding and OSD decoding
CN102611462A (en) LDPC-CC (Low-Density Parity-Check Convolution Codes) decoding algorithm and decoder
CN103338044B (en) Protograph code for deep space optical communication system
CN104753542B (en) For the bit reversal of LDPC code and linear programming combination interpretation method

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
C14 Grant of patent or utility model
GR01 Patent grant
C41 Transfer of patent application or patent right or utility model
TR01 Transfer of patent right

Effective date of registration: 20160331

Address after: 200120 Shanghai, Pudong New Area, east of the three lane road, No. 1018, 1-2 floor, 3

Patentee after: Shanghai NERC-DTV National Engineering Research Center Co., Ltd.

Address before: 200240 Dongchuan Road, Shanghai, No. 800, No.

Patentee before: Shanghai Jiao Tong University