CN105680880A - LDPC code dynamic asynchronous update method based on V2C dynamic selection strategy - Google Patents
LDPC code dynamic asynchronous update method based on V2C dynamic selection strategy Download PDFInfo
- Publication number
- CN105680880A CN105680880A CN201610009679.XA CN201610009679A CN105680880A CN 105680880 A CN105680880 A CN 105680880A CN 201610009679 A CN201610009679 A CN 201610009679A CN 105680880 A CN105680880 A CN 105680880A
- Authority
- CN
- China
- Prior art keywords
- variable node
- node
- residual error
- check
- variable
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 34
- 230000008901 benefit Effects 0.000 description 4
- 238000004891 communication Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 238000005457 optimization Methods 0.000 description 2
- 238000012216 screening Methods 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 230000001788 irregular Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
- H03M13/00—Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes
- H03M13/03—Error detection or forward error correction by redundancy in data representation, i.e. code words containing more digits than the source words
- H03M13/05—Error detection or forward error correction by redundancy in data representation, i.e. code words containing more digits than the source words using block codes, i.e. a predetermined number of check bits joined to a predetermined number of information bits
- H03M13/11—Error detection or forward error correction by redundancy in data representation, i.e. code words containing more digits than the source words using block codes, i.e. a predetermined number of check bits joined to a predetermined number of information bits using multiple parity bits
- H03M13/1102—Codes on graphs and decoding on graphs, e.g. low-density parity check [LDPC] codes
- H03M13/1105—Decoding
Landscapes
- Physics & Mathematics (AREA)
- Probability & Statistics with Applications (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Error Detection And Correction (AREA)
- Detection And Prevention Of Errors In Transmission (AREA)
Abstract
The invention discloses an LDPC code dynamic asynchronous update method based on a V2C dynamic selection strategy. In a point residual of variable nodes and in a side residual from the variable nodes to check nodes, the most instable variable node and the most unreliable side information can be dynamically selected by triple determination to be updated. According to the LDPC code dynamic asynchronous update method disclosed by the invention, the residual is not used as the sole measure, but stability judgment is set, the dynamic change characteristics of messages in a decoding process are fully used to quickly and accurately position the most unreliable message, and a more reasonable message update sequence can be provided for the dynamic asynchronous update method based on the message residuals of the variable nodes and the variable nodes to the check nodes, so that the proposed method can be used for reasonably allocating computing resources to accelerate the convergence speed and improve the decoding performance.
Description
Technical field
The invention belongs to communication technical field, particularly relate to a kind of LDPC code dynamic asynchronous update method based on the dynamic selection strategy of C2V.
Background technology
The sixties in 19th century, Gallager proposes LDPC code namely binary low density parity check code first. After LDPC code was rediscovered in 1996, LDPC code just obtains the extensive concern of academia and industrial quarters. In the research process of these more than ten years, the excellent properties of LDPC code progressively shows. LDPC code is the linear block codes that a class has intertexture characteristic, and need not introduce interleaver just has good antiburst error performance, can avoid time delay. Code word itself openness makes the decoding complexity of LDPC code relatively low, has relatively low error code flat. Being configured to decoding algorithm optimization and last performance evaluation from code word, LDPC code has the Optimization Design of set of system. LDPC code has application prospect highly, current LDPC code is classified as standard code mode by WiMAX, UWB, satellite digital video, 10GBase-T etc., in following LDPC code also will be widely used in satellite communication, marine exploration, optical transport, quantum secret communication, Hologram Storage etc.
In the interpretation method of LDPC code, from the scheduling of information updating, it is broadly divided into information updating strategy three kinds different: synchronization message more New Policy, permanent order asynchronous-update strategy and dynamic asynchronous information updating strategy. Dynamic asynchronous information updating strategy is that in three kinds of strategies, convergence rate is the fastest, and error-correcting performance is best, is highly suitable to be applied for needing the occasion of fast decoding. 2007, Casado et al. proposes a kind of belief propagation algorithm based on residual error and RBP algorithm, using the size of residual values as measuring in dynamic asynchronous update algorithm, the message to update is selected dynamically according to residual extent, there is no fixing update sequence, it is possible to centralized calculation resource priority updates the node messages that those are least stable. RBP algorithm is the algorithm that a greediness is higher, and preferential renewal has the side information of maximum residul difference every time. In order to reduce the greediness of RBP algorithm, Casado proposes the NWRBP algorithm that greediness is relatively low on the basis of RBP algorithm.Kim et al. proposed a kind of VCRBP decoding algorithm based on variable node to check-node later, and the method uses variable node to the residual error of check-node as selection strategy, to reduce the impact of greediness. Then, Liu et al. successively proposes a kind of EDS-LBP decoding algorithm based on message relative residual degree and based on the variable node Intelligent Dynamic IVCRBP decoding algorithm to check-node message residual error, and both algorithms are obtained for lifting in error-correcting performance and convergence rate. Lee et al. has carried out corresponding improvement for the unjustness of the information updating of dynamic asynchronous update algorithm and the greediness of algorithm, though excellent performance, dynamic asynchronous update algorithm still suffers from some shortcomings part. At present, dynamic asynchronous update algorithm is still carried out deep research by the researcher of LDPC code, in the hope of bigger breakthrough performance.
Dynamic asynchronous update algorithm dynamically adjusts information updating order, and dynamic allocation of resources can cause the unjustness of information updating. In a decoding iteration, some message can be updated many times and the update times of some message is less even without being updated, and too much or very few renewal all can affect error-correcting performance and the convergence rate of algorithm. Dynamic selection strategy decides the renewal order of message in decoding process, is a vital part in dynamic asynchronous update algorithm, but the research of this respect is little. Current most of dynamic asynchronous update algorithm is all as measuring that message dynamically updates according to extent residual before and after information updating, it is believed that its reliability of information that residual error is more big is more little, it should preferentially update. At the some residual sum check-node based on variable node in the limit residual error of variable node (C2V), its dynamic selection strategy is all select residual error for measuring, but rely on merely the dynamic selection strategy of residual error to lose accuracy to a certain extent, unreliable information can be caused erroneous judgement.
Summary of the invention
For the deficiency that prior art exists, the invention provides a kind of LDPC code dynamic asynchronous update method based on the dynamic selection strategy of C2V, it takes full advantage of the dynamic variation characteristic of message in decoding process, it is quickly and accurately positioned message least reliably, more reasonably information updating order can be provided for dynamic asynchronous update method, so that method reasonable distribution calculates resource, accelerate convergence rate, improve decoding performance.
The technical solution used in the present invention is as follows:
A kind of LDPC code dynamic asynchronous update method (namely V-CVRBP algorithm) based on the dynamic selection strategy of C2V, at the some residual sum check-node of variable node in the limit residual error of variable node, have employed the dynamic selection strategy of triple judgement select least stable variable node and least reliably C2V side information be updated, the dynamic selection strategy of described triple judgements comprises the following steps that
S11. according to stability criteria, all variable nodes are judged, if there is unstable variable node, therefrom finding out the unstable variable node that residual error is maximum, from all variable nodes, otherwise just finding out the variable node with maximum residul difference; Wherein, stability criteria is in the iterative decoding algorithm of LDPC code, if the LLR value symbol of a variable node remains unchanged after continuous three iteration, then it is stable for claiming this variable node;
S12. from the variable node of maximum residul difference, the C2V side information that residual error is maximum is found;
S13. the point maximum unstable variable node of residual error and the maximum limit of limit residual error preferentially will be updated in dynamic asynchronous update algorithm;
Wherein, the computing formula of limit residual sum point residual error is r (mk)=| | f (mk)-mk| |, as r (mk) when being limit residual error, mkWith f (mk) represent the side information before and after updating respectively; As r (mk) when being a some residual error, mkWith f (mk) represent the LLR value of variable node before and after updating respectively.
Based on the dynamic selection strategy of triple judgements in the present invention, begin at unreliable information of searching on a large scale, hunting zone is reduced after stability criteria condition, by reducing hunting zone after the condition filter of variable node maximum point residual error further, final only need to calculating is compared the limit residual error that the unstable variable node maximum with residual error be associated and is determined least stable side information. Additionally, residual sum point residual error in limit make use of twice, front and back decoding information, stability criteria make use of the discriminative information after continuous three decodings. New dynamic selection strategy takes full advantage of the dynamic characteristic of information in decoding process, by screening the renewal order providing message more quickly and accurately for dynamic asynchronous update method layer by layer, further speeds up convergence rate, improves decoding performance.
Specifically, the dynamic selection strategy of triple judgements is particularly applicable in the some residual sum check-node of variable node in the limit residual error of variable node by the present invention, and concrete steps include as follows:
S21. by stability criteria, all variable nodes are judged; If there is the variable node being unsatisfactory for stability criteria, then from unstable variable node set N1In find out the variable node of maximum residul difference; If all variable nodes all meet stability criteria, then from stable variable node set N2In find out the variable node with maximum residul difference, then perform S21;
S22. find out with S21 in there is the variable node v of maximum residul differenceiThe check-node set S being connectedj, i.e. Sj={ cj|cj∈N(vi), and find out and gather SjIn all check-nodes be connected variable node set Vk, wherein VkComprise variable node vi;
S23. set of computations SjTo set VkLimit residual error, and therefrom find out the limit c with maximum limit residual errorj2vk; Limit c hereinj2vkNamely the C2V limit that the residual error to find of S12 is maximum;
S24. the variable node v of the maximum residul difference searched out in S21 to S23iLimit c with maximum limit residual errorj2vkAs final least stable variable node and least reliable limit, in order to be preferentially updated in interpretation method. Wherein: N (vi) represent and variable node viThe set of all check-nodes being connected.
In an iteration, the renewal step of an information updating process includes as follows:
S31. least stable variable node v is selected according to the dynamic selection strategy of triple judgementsiLimit c least reliablyj2vk, update check-node cjTo all with check-node cjVariable node N (the c being connectedj) message, namely to all vb∈N(cj) more new information
S32. variable node v is updatedb, and by residual errorWithIt is set to 0;
S33. to all with variable node vkThe check-node being connected, updates variable node vkTo the message of these check-nodes, namely to all ca∈N(vk) more new information
S34. to all vd∈N(ca)\vi, it is contemplated that calculate residual errorPrepare for decoding iteration next time.
Wherein:Represent variable node viSome residual error;Represent check-node cjTo variable node vkLimit residual error; N (cj) represent all with check-node cjThe set of the variable node being connected; N (ca)\viRepresent except variable node viAll with check-node c outwardaThe set of the variable node being connected;Represent check-node cjPass to variable node vbInformation;Represent variable node vkPass to check-node caInformation.
Compared with prior art, the invention have the benefit that the present invention does not rely on merely residual error for measuring, but it is provided with stability criteria, take full advantage of the dynamic variation characteristic of message in decoding process, it is quickly and accurately positioned out message least reliably, can for providing more reasonably information updating order based on the dynamic asynchronous update method of variable node and check-node to variable node message residual error, so that method reasonable distribution calculates resource, accelerate convergence rate, improve decoding performance.
Accompanying drawing explanation
Fig. 1: the dynamic selection strategy flow chart of the triple judgement of the present invention;
Fig. 2: the present invention is based on the dynamic selection strategy flow chart of C2V;
Fig. 3: the present invention is based on the selection schematic diagram that least can keep to the side in the dynamic selection strategy of C2V;
Fig. 4: V-CVRBP decoding algorithm schematic diagram of the present invention;
The error-correcting performance contrast of Fig. 5: 1/2-(576,288) LDPC code;
The error-correcting performance contrast of Fig. 6: 1/2-(1152,576) LDPC code;
Fig. 7: 1/2-(576,288) LDPC code is constringency performance contrast when signal to noise ratio is 2.5dB.
Detailed description of the invention
Below in conjunction with accompanying drawing, the present invention is described in further detail.
Such as Fig. 1, for the dynamic selection strategy flow chart of triple judgements that the present invention proposes based on the LDPC code dynamic asynchronous update method of the dynamic selection strategy of C2V.
S11. according to stability criteria, all variable nodes are judged, if there is unstable variable node, therefrom finding out the unstable variable node that residual error is maximum, from all variable nodes, otherwise just finding out the variable node with maximum residul difference; Wherein, stability criteria is in the iterative decoding algorithm of LDPC code, if the LLR value symbol of a variable node remains unchanged after continuous three iteration, then it is stable for claiming this variable node;
S12. from the variable node with maximum point residual error, the C2V side information with maximum limit residual error is found;
S13. the point maximum unstable variable node of residual error and the maximum limit of limit residual error preferentially will be updated in dynamic asynchronous update algorithm;
Wherein, the computing formula of limit residual sum point residual error is r (mk)=| | f (mk)-mk| |, as r (mk) when being limit residual error, mkWith f (mk) represent the side information before and after updating respectively; As r (mk) when being a some residual error, mkWith f (mk) represent the LLR value of variable node before and after updating respectively.
Such as Fig. 2, the process that some residual sum check-node according to stability criteria, variable node is searched for layer by layer to the limit residual error these three condition of variable node, final least stable variable node and the least reliable side information of obtaining, and in interpretation method priority treatment. Specifically comprise the following steps that
S21. by stability criteria, all variable nodes are judged; If there is the variable node being unsatisfactory for stability criteria, then from unstable variable node set N1In find out the variable node of maximum residul difference; If all variable nodes all meet stability criteria, then from stable variable node set N2In find out the variable node with maximum residul difference, then perform S21;
S22. find out with S21 in there is the variable node v of maximum residul differenceiThe check-node set S being connectedj, i.e. Sj={ cj|cj∈N(vi), and find out and gather SjIn all check-nodes be connected variable node set Vk, wherein VkComprise variable node vi;
S23. set of computations SjTo set VkLimit residual error, and therefrom find out the limit c with maximum limit residual errorj2vk;S24. the variable node v of the maximum point residual error searched out in S21 to S23iLimit c with maximum limit residual errorj2vkAs final least stable variable node and least reliable limit, in order to be preferentially updated. Wherein: N (vi) represent and variable node viThe set of all check-nodes being connected.
In the present invention, all of variable node has been divided into two parts by stability criteria, only need to select the variable node with maximum point residual error in the part variable node set be unsatisfactory for stability criteria when searching for least stable variable node. Only all of variable node all meets stability criteria, namely in Fig. 2Time, just can choose the maximum variable node of residual error from all stable variable node set as the preferential variable node updated.
Screening through stability criteria and maximum variable node message point residual error so that check-node reduces much to the calculating of variable node (C2V) limit residual error with comparison range.
The present invention is when check-node is to variable node (C2V) side information least reliably in search, and hunting zone is somewhat expanded to and least stablized in the connected minor structure of variable node, as shown in Figure 3. The search of maximum limit residual error is no longer only and unstable variable node vi3 limits being connected, but expand to from check-node cjThe all limits set out. Although hunting zone somewhat expands a bit, but so can improve the greediness of algorithm to a certain extent.
In an iteration, the renewal step of an information updating process includes as follows:
S31. least stable variable node v is selected according to the dynamic selection strategy of triple judgementsiLimit c least reliablyj2vk, update check-node cjTo all with check-node cjVariable node N (the c being connectedj) message, namely to all vb∈N(cj) more new informationAs shown in Fig. 4 (a);
S32. variable node v is updatedb, and by residual errorWithIt is set to 0;
S33. to all with variable node vkThe check-node being connected, updates variable node vkTo the message of these check-nodes, namely to all ca∈N(vk) more new informationAs shown in Fig. 4 (b);
S34. to all vd∈N(ca)\vi, it is contemplated that calculate residual errorAs shown in Fig. 4 (c), prepare for decoding iteration next time.
Wherein:Represent variable node viSome residual error;Represent check-node cjTo variable node vkLimit residual error; N (cj) represent all with check-node cjThe set of the variable node being connected; N (ca)\viRepresent except variable node viAll with check-node c outwardaThe set of the variable node being connected;Represent check-node cjPass to variable node vbInformation;Represent variable node vkPass to check-node caInformation.
Implement according to the method described above, just can realize the present invention well. Coding codeword is transmitted by channel after being modulated, and at decoding end, adopts proposed decoding algorithm to decode, can obtain information sequence by iterative decoding.
In order to compare the performance of the dynamic asynchronous update algorithm that the present invention proposes, it is necessary to be calculated machine emulation. Specifically, employing randomly generates LDPC code and transmits on awgn channel, and utilizes the multiple different decoding algorithm comprising this algorithm to decode, maximum iteration time is 5, maximum mistake frame number is set to 100 frames, and modulation system is that BPSK, BER performance comparison figure is such as shown in Fig. 5 to Fig. 6. Eb/N0Representing Normalized Signal/Noise Ratio, unit is decibel (dB). It is 576 and 1152 that Fig. 5 and Fig. 6 has been respectively compared code length, and code check is the irregular codes error-correcting performance contrast that uses seven kinds different decoding algorithm obtained of 1/2. For 576 code words, when relatively high s/n ratio, slightly good than IVCRBP algorithm of the error-correcting performance of V-CVRBP algorithm, compared with up-to-date OV-RBP algorithm then slightly almost.In BER=1.0 × 10-5Time, V-CVRBP algorithm can obtain the gain of about 0.2dB compared with IVCRBP algorithm. Compared with OV-RBP algorithm, in BER=2.0 × 10-6Place, V-CVRBP algorithm has the performance boost of about 0.1dB. When code word increases, becoming apparent from of the superiority performance of the V-CVRBP algorithm error-correcting performance in the present invention. As can be seen from Figure, the present invention proposes dynamic asynchronous update algorithm and has better error-correcting performance compared to other algorithm and less error code is flat. Investigating the decoding performance of a kind of decoding algorithm, except error-correcting performance and error code are flat, convergence of algorithm speed is also an important index. For analyzing the convergence situation of decoding algorithm proposed by the invention further, (576,288) code word adopts various different decoding algorithm constringency performance comparison diagram as shown in Figure 7 under fixing signal to noise ratio. It can be seen that the dynamic asynchronous update algorithm proposed in the present invention shows convergence property quickly, such that it is able to reduce the complexity of decoding algorithm by reducing iterations.
Claims (3)
1. the LDPC code dynamic asynchronous update method based on the dynamic selection strategy of C2V, it is characterized in that, at the some residual sum check-node of variable node in the limit residual error of variable node, have employed the dynamic selection strategy of triple judgement select least stable variable node and least reliably C2V side information be updated, the dynamic selection strategy of described triple judgements comprises the following steps that
S11. according to stability criteria, all variable nodes are judged, if there is unstable variable node, therefrom finding out the unstable variable node that residual error is maximum, from all variable nodes, otherwise just finding out the variable node with maximum residul difference; Wherein, stability criteria is in the iterative decoding algorithm of LDPC code, if the LLR value symbol of a variable node remains unchanged after continuous three iteration, then it is stable for claiming this variable node;
S12. from the variable node of maximum residul difference, the C2V side information that residual error is maximum is found;
S13. the point maximum unstable variable node of residual error and the maximum limit of limit residual error preferentially will be updated in dynamic asynchronous update algorithm;
Wherein, the computing formula of limit residual sum point residual error is r (mk)=| | f (mk)-mk| |, as r (mk) when being limit residual error, mkWith f (mk) represent the side information before and after updating respectively; As r (mk) when being a some residual error, mkWith f (mk) represent the LLR value of variable node before and after updating respectively.
2. the LDPC code dynamic asynchronous update method based on the dynamic selection strategy of C2V according to claim 1, it is characterized in that, the dynamic selection strategy of triple judgements being particularly applicable in the some residual sum check-node of variable node in the limit residual error of variable node, concrete steps include as follows:
S21. by stability criteria, all variable nodes are judged; If there is the variable node being unsatisfactory for stability criteria, then from unstable variable node set N1In find out the variable node of maximum residul difference; If all variable nodes all meet stability criteria, then from stable variable node set N2In find out the variable node with maximum residul difference, then perform S21;
S22. find out with S21 in there is the variable node v of maximum residul differenceiThe check-node set S being connectedj, i.e. Sj={ cj|cj∈N(vi), and find out and gather SjIn all check-nodes be connected variable node set Vk, wherein VkComprise variable node vi;
S23. set of computations SjTo set VkLimit residual error, and therefrom find out the limit c with maximum limit residual errorj2vk;
S24. the variable node v of the maximum residul difference searched out in S21 to S23iLimit c with maximum limit residual errorj2vkAs final least stable variable node and least reliable limit, in order to be preferentially updated in interpretation method;
Wherein: N (vi) represent and variable node viThe set of all check-nodes being connected.
3. the LDPC code dynamic asynchronous update method based on the dynamic selection strategy of C2V according to claim 2, it is characterised in that the renewal step of an information updating process includes as follows in an iteration:
S31. least stable variable node v is selected according to the dynamic selection strategy of triple judgementsiLimit c least reliablyj2vk, update check-node cjTo all with check-node cjVariable node N (the c being connectedj) message, namely to all vb∈N(cj) more new information
S32. variable node v is updatedb, and by residual errorWithIt is set to 0;
S33. to all with variable node vkThe check-node being connected, updates variable node vkTo the message of these check-nodes, namely to all ca∈N(vk) more new information
S34. to all vd∈N(ca)\vi, it is contemplated that calculate residual errorPrepare for decoding iteration next time;
Wherein:Represent variable node viSome residual error;Represent check-node cjTo variable node vkLimit residual error; N (cj) represent all with check-node cjThe set of the variable node being connected; N (ca)\viRepresent except variable node viAll with check-node c outwardaThe set of the variable node being connected;Represent check-node cjPass to variable node vbInformation;Represent variable node vkPass to check-node caInformation.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610009679.XA CN105680880B (en) | 2016-01-04 | 2016-01-04 | LDPC code dynamic asynchronous update method based on C2V dynamic select strategy |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610009679.XA CN105680880B (en) | 2016-01-04 | 2016-01-04 | LDPC code dynamic asynchronous update method based on C2V dynamic select strategy |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105680880A true CN105680880A (en) | 2016-06-15 |
| CN105680880B CN105680880B (en) | 2019-06-07 |
Family
ID=56299404
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610009679.XA Active CN105680880B (en) | 2016-01-04 | 2016-01-04 | LDPC code dynamic asynchronous update method based on C2V dynamic select strategy |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105680880B (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106330201A (en) * | 2016-08-18 | 2017-01-11 | 中山大学 | Variable node reliability dynamic selection strategy-based multi-system LDPC updating method |
| CN106330202A (en) * | 2016-08-18 | 2017-01-11 | 中山大学 | Binary system LDPC code updating method based on variable node reliability dynamic selection strategy |
| CN106899309A (en) * | 2017-01-06 | 2017-06-27 | 中山大学 | Low complex degree LDPC dynamic dispatchings decoding update method based on variable node reliability |
| CN107104680A (en) * | 2017-03-20 | 2017-08-29 | 中山大学 | LDPC code decoding update method based on variable node reliability dynamic select strategy |
| CN110086568A (en) * | 2019-04-02 | 2019-08-02 | 中山大学 | The LDPC code interpretation method of dynamic select strategy based on information updating variable range |
| CN110086476A (en) * | 2019-04-02 | 2019-08-02 | 中山大学 | LDPC code interpretation method based on the fixed dynamic select strategy of information updating range |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102195655A (en) * | 2011-02-25 | 2011-09-21 | 山东大学 | Quasi-cyclic LDPC (Low Density Parity Check) decoder and decoding method thereof |
| CN102594365A (en) * | 2012-02-29 | 2012-07-18 | 中山大学 | Dynamic asynchronous BP decoding method |
| CN104639178A (en) * | 2015-03-06 | 2015-05-20 | 中山大学 | Dynamic column updating and decoding method based on LDPC (low-density parity-check) code |
| EP2892157A1 (en) * | 2014-01-02 | 2015-07-08 | Alcatel Lucent | Offset Min-Sum decoding of LDPC codes |
-
2016
- 2016-01-04 CN CN201610009679.XA patent/CN105680880B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102195655A (en) * | 2011-02-25 | 2011-09-21 | 山东大学 | Quasi-cyclic LDPC (Low Density Parity Check) decoder and decoding method thereof |
| CN102594365A (en) * | 2012-02-29 | 2012-07-18 | 中山大学 | Dynamic asynchronous BP decoding method |
| EP2892157A1 (en) * | 2014-01-02 | 2015-07-08 | Alcatel Lucent | Offset Min-Sum decoding of LDPC codes |
| CN104639178A (en) * | 2015-03-06 | 2015-05-20 | 中山大学 | Dynamic column updating and decoding method based on LDPC (low-density parity-check) code |
Non-Patent Citations (2)
| Title |
|---|
| XINGCHENG LIU等: ""Variable-Node-Based Dynamic Scheduling Strategy for Belief-Propagation Decoding of LDPC Codes"", 《IEEE COMMUNICATIONS LETTERS》 * |
| YI GONG等: ""Effective Informed Dynamic Scheduling for Belief Propagation Decoding of LDPC Codes"", 《IEEE TRANSACTIONS ON COMMUNICATIONS》 * |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106330201A (en) * | 2016-08-18 | 2017-01-11 | 中山大学 | Variable node reliability dynamic selection strategy-based multi-system LDPC updating method |
| CN106330202A (en) * | 2016-08-18 | 2017-01-11 | 中山大学 | Binary system LDPC code updating method based on variable node reliability dynamic selection strategy |
| CN106330201B (en) * | 2016-08-18 | 2019-10-25 | 中山大学 | Non-Binary LDPC Coded update method based on variable node reliability dynamic select strategy |
| CN106330202B (en) * | 2016-08-18 | 2019-10-25 | 中山大学 | Binary system LDPC code update method based on variable node reliability dynamic select strategy |
| CN106899309A (en) * | 2017-01-06 | 2017-06-27 | 中山大学 | Low complex degree LDPC dynamic dispatchings decoding update method based on variable node reliability |
| CN106899309B (en) * | 2017-01-06 | 2020-04-03 | 中山大学 | Low-complexity LDPC dynamic scheduling decoding updating method based on variable node reliability |
| CN107104680A (en) * | 2017-03-20 | 2017-08-29 | 中山大学 | LDPC code decoding update method based on variable node reliability dynamic select strategy |
| CN107104680B (en) * | 2017-03-20 | 2020-06-16 | 中山大学 | LDPC code decoding updating method based on variable node reliability dynamic selection strategy |
| CN110086568A (en) * | 2019-04-02 | 2019-08-02 | 中山大学 | The LDPC code interpretation method of dynamic select strategy based on information updating variable range |
| CN110086476A (en) * | 2019-04-02 | 2019-08-02 | 中山大学 | LDPC code interpretation method based on the fixed dynamic select strategy of information updating range |
| CN110086568B (en) * | 2019-04-02 | 2020-09-22 | 中山大学 | LDPC code decoding method based on dynamic selection strategy with variable message updating range |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105680880B (en) | 2019-06-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105680880A (en) | LDPC code dynamic asynchronous update method based on V2C dynamic selection strategy | |
| CN105680876A (en) | LDPC code dynamic asynchronous update method based on V2C dynamic selection strategy | |
| CN104467874B (en) | A kind of LDPC code dynamic dispatching interpretation method based on oscillatory variation node | |
| CN107248866B (en) | Method for reducing decoding time delay of polarization code | |
| CN105553892A (en) | Channel estimation method based on polar code | |
| JP5301575B2 (en) | Channel coding apparatus and method in digital broadcast communication system using low density parity check code | |
| CN113098530B (en) | LDPC code decoding method based on average cluster residual dynamic scheduling selection strategy | |
| CN104639178A (en) | Dynamic column updating and decoding method based on LDPC (low-density parity-check) code | |
| CN106330201B (en) | Non-Binary LDPC Coded update method based on variable node reliability dynamic select strategy | |
| CN106899309B (en) | Low-complexity LDPC dynamic scheduling decoding updating method based on variable node reliability | |
| CN106992026A (en) | The interpretation method that a kind of LDPC code snap information for NAND flash storage mediums recovers | |
| CN102594365B (en) | Dynamic asynchronous BP decoding method of LDPC code | |
| Hu et al. | A comparative study of polar code decoding algorithms | |
| US20090006924A1 (en) | Fast decoding method for low density parity check (ldpc) code | |
| KR101459534B1 (en) | Method and apparatus for designing a degree distribution of LDPC code | |
| CN106330202B (en) | Binary system LDPC code update method based on variable node reliability dynamic select strategy | |
| CN104753542B (en) | For the bit reversal of LDPC code and linear programming combination interpretation method | |
| CN110212924B (en) | LT code encoding and decoding method and system | |
| CN113131950A (en) | Self-adaptive continuous elimination priority decoding method for polarization code | |
| CN107241104B (en) | Local different-sign dynamic BP decoding method for LDPC code | |
| CN107241103B (en) | Local dynamic BP decoding method for LDPC code | |
| CN118054797B (en) | Coding and decoding method, device and equipment | |
| Romano et al. | Sub-optimal importance sampling for fast simulation of linear block codes over BSC channels | |
| CN107104680B (en) | LDPC code decoding updating method based on variable node reliability dynamic selection strategy | |
| Zhengke et al. | A simplified code-aided carrier synchronization algorithm |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |