Temperature-aware log-likelihood ratio information computing method and computing apparatus for LDPC decoding, and solid-state disk

Abstract

Provided in the present invention are a temperature-aware log-likelihood ratio information computing method and computing apparatus for LDPC decoding, and a solid-state disk. The temperature-aware log-likelihood ratio information computing method for LDPC decoding comprises: acquiring a set of log-likelihood ratio information corresponding to different read temperatures; according to the set, analyzing the intrinsic relationship between the read temperatures and the log-likelihood ratio information, and establishing a relationship model for the read temperatures and the log-likelihood ratio information; and, during execution of an LDPC decoding operation, using the relationship model to compute log-likelihood ratio information corresponding to the current temperature, and executing the LDPC decoding operation. The present invention establishes the relationship model for the read temperatures and the log-likelihood ratio information and then uses the relationship model to compute the log-likelihood ratio information corresponding to the current temperature, so as to improve the precision of the log-likelihood ratio information and enhance the error correction capability of LDPC decoding, thereby reducing the number of decoding iterations and time consumed for decoding.

Description

Temperature-aware LDPC decoding log-likelihood ratio information calculation method, calculation device and solid state disk TECHNICAL FIELD

[0001] The present application relates to the technical field of computers, in particular to a temperature-aware LDPC decoding log-likelihood ratio information calculation method, calculation device and solid state disk. BACKGROUND

[0002] Low-Density Parity-Check (LDPC) uses log-likelihood ratio information as an initial value to perform iterative decoding algorithm with strong error correction capability and is widely used in three-dimensional flash memory to ensure data reliability.

[0003] The precision of log-likelihood ratio information affects the error correction capability and performance of LDPC code, and high-precision log-likelihood ratio information can improve the error correction capability of LDPC decoding to reduce the number of decoding iterations and decoding time consumption.

[0004] Therefore, how to improve the precision of log-likelihood ratio information and thus improve the error correction capability and performance of LDPC decoding is the focus of attention of those skilled in the art.

[0005] SUMMARY

[0006] The purpose of the present application is to provide a temperature-aware LDPC decoding log-likelihood ratio information calculation method, calculation device and solid state disk, which can improve the precision of log-likelihood ratio information, improve the error correction capability of LDPC decoding, and thus reduce the number of decoding iterations and decoding time consumption.

[0007] In order to achieve the above purpose, the present application provides a temperature-aware LDPC decoding log-likelihood ratio information calculation method, comprising:

[0008] Obtain a set of log-likelihood ratio information corresponding to different read temperatures;

[0009] According to the set, analyze the internal relationship between the read temperature and the log-likelihood ratio information, and establish a relationship model between the read temperature and the log-likelihood ratio information;

[0010] When performing LDPC decoding operation, the relationship model is used to calculate the log-likelihood ratio information corresponding to the current temperature, and the LDPC decoding operation is performed.

[0011] In an optional solution, the method for obtaining a set of log-likelihood ratio information corresponding to different read temperatures comprises:

[0012] Step 1: Give a temperature set composed of different read temperatures;

[0013] Step 2: write random data into the three-dimensional flash memory chip at a set temperature;

[0014] Step 3: select a temperature from the temperature set, at which the written data is read out and an LDPC decoding operation is performed;

[0015] Step 4: obtain the log-likelihood ratio information corresponding to the case that the decoding result is correct at the current reading temperature;

[0016] Step 5: repeat steps 2 to 4 until all temperatures in the temperature set are traversed;

[0017] Step 6: obtain a set of log-likelihood ratio information corresponding to different reading temperatures.

[0018] In an optional solution, the relationship model is established by using a machine learning method or a statistical fitting method.

[0019] In an optional solution, after the LDPC decoding operation is performed, the method further comprises: counting the number of decoding iterations and the change of the error rate after decoding.

[0020] The application further provides a temperature-aware LDPC decoding log-likelihood ratio information calculation device, comprising:

[0021] An obtaining module is configured to obtain a set of log-likelihood ratio information corresponding to different reading temperatures.

[0022] A relationship model module is configured to analyze the internal relationship between the reading temperature and the log-likelihood ratio information according to the set, and establish a relationship model between the reading temperature and the log-likelihood ratio information.

[0023] An execution module is configured to calculate the log-likelihood ratio information corresponding to the current temperature by using the relationship model when performing an LDPC decoding operation, and perform the LDPC decoding operation.

[0024] The application further provides a solid state disk, comprising: a controller, wherein the controller is pre-integrated with the above relationship model.

[0025] When performing an LDPC decoding operation, the controller obtains the log-likelihood ratio information corresponding to the current reading temperature according to the relationship model, and then performs the LDPC decoding operation.

[0026] The application further provides a solid state disk, wherein the solid state disk performs an LDPC decoding operation by using the above temperature-aware LDPC decoding log-likelihood ratio information calculation method to obtain the log-likelihood ratio information corresponding to the current reading temperature, and then performs the LDPC decoding operation.

[0027] The application has the following beneficial effects:

[0028] The present application can improve the precision of the log-likelihood ratio information, improve the LDPC decoding error correction capability, and thus reduce the decoding iteration number and decoding time consumption by establishing a relationship model between the reading temperature and the log-likelihood ratio information, and calculating the log-likelihood ratio information corresponding to the current temperature by using the relationship model. BRIEF DESCRIPTION OF DRAWINGS

[0029] The above and other objects, features and advantages of the present application will become more apparent from the following detailed description when taken in conjunction with the accompanying drawings in which like reference characters refer to like parts throughout the figures, and wherein:

[0030] FIG. 1 is a flowchart of a temperature-aware LDPC decoding log-likelihood ratio information calculation method according to an embodiment of the present application. DETAILED DESCRIPTION

[0031] The present application will be further described by examples in conjunction with the accompanying drawings and specific embodiments. The advantages and features of the present application will become more apparent from the following description in conjunction with the drawings, however, it should be noted that the technical solutions of the present application can be implemented in various forms and are not limited to the specific embodiments described herein. The drawings are very simplified and use non-precise proportions, and are only used to facilitate and clarify the purpose of illustrating the embodiments of the present application.

[0032] It should be understood that when an element or layer is referred to as being "on", "adjacent", "connected to", or "coupled to" another element or layer, it can be directly on, adjacent, connected or coupled to the other element or layer, or intervening elements or layers can be present. In contrast, when an element is referred to as being "directly on", "directly adjacent", "directly connected to", or "directly coupled to" another element or layer, then there are no intervening elements or layers present. It will be understood that, although the terms first, second, third, etc. can be used herein to describe various elements, components, regions, layers and / or sections, these elements, components, regions, layers and / or sections should not be limited by these terms. These terms are only used to distinguish one element, component, region, layer or section from another element, component, region, layer or section. Therefore, a first element, component, region, layer or section discussed below could be termed a second element, component, region, layer or section without departing from the teachings of the present application.

[0033] Spatially relative terms, such as "beneath", "below", "lower", "under", "above", "upper" and the like, can be used herein for ease of description to describe one element or feature's relationship to another element(s) or feature(s) as illustrated in the figures. It will be understood that the spatially relative terms are intended to encompass different orientations of the device in use and / or operation in addition to the orientations depicted in the figures. For example, if a device in the figures is inverted, then a dependent element or feature described as "below" or "beneath" another element or feature would then be oriented "above" and / or "over" the other element or feature. Thus, the exemplary term "below" can encompass both an orientation of above and below. The device can be otherwise oriented (rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted accordingly.

[0034] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising", when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0035] The temperature has an important influence on the log-likelihood ratio information, and the traditional method does not consider the influence of the temperature on the log-likelihood ratio information, so that the accuracy of the log-likelihood ratio information is not enough, and the number of decoding iterations and the time consumed by decoding are increased.

[0036] The present application establishes a relationship model between the reading temperature and the log-likelihood ratio information, and can improve the accuracy of the log-likelihood ratio information.

[0037] Embodiment 1

[0038] Referring to FIG. 1, the present embodiment provides a temperature-aware LDPC decoding log-likelihood ratio information calculation method, which comprises:

[0039] Obtain a set of log-likelihood ratio information corresponding to different reading temperatures;

[0040] According to the set, analyze the internal relationship between the reading temperature and the log-likelihood ratio information, and establish a relationship model between the reading temperature and the log-likelihood ratio information;

[0041] When performing the LDPC decoding operation, the relationship model is used to calculate the log-likelihood ratio information corresponding to the current temperature, and the LDPC decoding operation is performed.

[0042] Specifically, the method comprises the following steps:

[0043] Step 1: A temperature set composed of different reading temperatures is given.

[0044] Step 2: Random data is written into a three-dimensional flash memory chip at a set temperature.

[0045] Step 3: A temperature is selected from the temperature set, at which the written data is read out and an LDPC decoding operation is performed.

[0046] Step 4: Log-likelihood ratio information corresponding to the case where the decoding result is correct at the current reading temperature is obtained.

[0047] Step 5: Steps 2 to 4 are repeatedly performed until all temperatures in the temperature set are traversed.

[0048] Step 6: A set of log-likelihood ratio information corresponding to different reading temperatures is obtained.

[0049] Step 7: According to the set, the internal relationship between the reading temperature and the log-likelihood ratio information is analyzed, and a relationship model between the reading temperature and the log-likelihood ratio information is established.

[0050] Step 8: When performing the LDPC decoding operation, the relationship model is used to calculate the log-likelihood ratio information corresponding to the current temperature, and the LDPC decoding operation is performed.

[0051] In step 1, the temperature set includes multiple temperatures of high and low temperatures.

[0052] In step 2, in the embodiment, the set temperature is the same temperature, that is, the experiment is performed at the same writing temperature and different reading temperatures. In other embodiments, it can also be divided into multiple groups, and the writing temperatures of different groups are also different, and the influence of the writing temperature on the log-likelihood ratio information is analyzed.

[0053] In steps 3 and 4, when performing the LDPC decoding operation, the decoding iteration may be performed multiple times, and the decoding error may occur, and the decoding error also has corresponding log-likelihood ratio information. The influence of the log-likelihood ratio information at the current temperature on the number of decoding iterations is analyzed. Step 4 only obtains the log-likelihood ratio information corresponding to the case where the decoding result is correct.

[0054] In step 7, the relationship model is established by using a machine learning method or a statistical fitting method.

[0055] The embodiment of step 8 further comprises step 9: The number of decoding iterations and the change of the error rate after decoding are counted. The effectiveness of the temperature-aware log-likelihood ratio information calculation method is evaluated.

[0056] The embodiment can improve the precision of the log-likelihood ratio information, improve the LDPC decoding error correction capability, and thus reduce the decoding iteration number and decoding time consumption by establishing a relationship model between the reading temperature and the log-likelihood ratio information, and calculating the log-likelihood ratio information corresponding to the current temperature by using the relationship model.

[0057] Embodiment 2

[0058] The embodiment provides a temperature-aware LDPC decoding log-likelihood ratio information calculation device, which comprises:

[0059] An acquisition module is configured to acquire a set of log-likelihood ratio information corresponding to different reading temperatures.

[0060] A relationship model module is configured to analyze the internal relationship between the reading temperature and the log-likelihood ratio information according to the set, and establish a relationship model between the reading temperature and the log-likelihood ratio information.

[0061] An execution module is configured to calculate the log-likelihood ratio information corresponding to the current temperature by using the relationship model when performing an LDPC decoding operation, and perform the LDPC decoding operation.

[0062] Embodiment 3

[0063] The embodiment provides a solid state disk, which comprises a controller, wherein the controller is pre-integrated with the relationship model of the embodiment 1; when performing LDPC decoding, the controller acquires the log-likelihood ratio information corresponding to the current reading temperature according to the relationship model, and then performs LDPC decoding.

[0064] The relationship model of the embodiment is pre-established and verified, and then the relationship model is integrated into the controller of the solid state disk.

[0065] In other embodiments, the relationship model can also not be pre-established, and the relationship model is established online and optimized during the use of the solid state disk, and when performing LDPC decoding, the log-likelihood ratio information corresponding to the current reading temperature is acquired by using the optimized model, and then the LDPC decoding operation is performed.

[0066] The above description is only a description of the preferred embodiments of the present application, and does not limit the scope of the present application in any way, and any modification or modification of the above-mentioned disclosure by a person skilled in the art belongs to the protection scope of the claims.

Claims

1. A temperature-aware LDPC decoding log-likelihood ratio information calculation method, characterized in that: include: Obtain a set of log-likelihood ratio information corresponding to different reading temperatures; Analyzing the intrinsic relationship between the read temperature and the log-likelihood ratio information based on the set, and establishing a relationship model between the read temperature and the log-likelihood ratio information; When performing the LDPC decoding operation, the relationship model is used to calculate the log-likelihood ratio information corresponding to the current temperature, and the LDPC decoding operation is performed.

2. The temperature-aware LDPC decoding log-likelihood ratio information calculation method according to claim 1, wherein: The method for obtaining a set of log-likelihood ratio information corresponding to different reading temperatures includes: Step 1: Provide a temperature set consisting of different reading temperatures; Step 2: Writing random data into the 3D flash memory chip at a set temperature; Step 3: Select a temperature from the temperature set, read the written data and perform an LDPC decoding operation at the temperature; Step 4: Obtain the corresponding log-likelihood ratio information when the decoding result is correct at the current reading temperature; Step 5: Repeat steps 2 to 4 until all temperatures in the temperature set are traversed; Step 6: Obtain a set of log-likelihood ratio information corresponding to different reading temperatures.

3. The temperature-aware LDPC decoding log-likelihood ratio information calculation method according to claim 1, wherein: The relationship model is established by using a machine learning method or a statistical fitting method.

4. The temperature-aware LDPC decoding log-likelihood ratio information calculation method according to claim 1, wherein: After performing the LDPC decoding operation, the method further includes: counting the number of decoding iterations and changes in the bit error rate after decoding.

5. A temperature-aware LDPC decoding log-likelihood ratio information calculation device, characterized in that: include: An acquisition module, used to obtain a set of log-likelihood ratio information corresponding to different reading temperatures; a relationship model module, configured to analyze the intrinsic relationship between the read temperature and the log-likelihood ratio information based on the set, and establish a relationship model between the read temperature and the log-likelihood ratio information; The execution module is used to calculate the log-likelihood ratio information corresponding to the current temperature using the relationship model when performing the LDPC decoding operation, and perform the LDPC decoding operation.

6. A solid state drive, characterized in that: include: A controller, wherein the controller is pre-integrated with the relationship model according to any one of claims 1 to 4; When performing LDPC decoding, the controller obtains the log-likelihood ratio information corresponding to the current reading temperature according to the relationship model, and then performs LDPC decoding.

7. A solid state drive, characterized in that: When performing LDPC decoding, the solid-state hard disk uses the temperature-aware LDPC decoding log-likelihood ratio information calculation method described in any one of claims 1 to 4 to obtain the log-likelihood ratio information corresponding to the current reading temperature, and then performs the LDPC decoding operation.

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