Data may be stored in a variety of ways, including in flash cells in a flash-based storage system. A flash-based storage system allows multiple levels (i.e., voltages) to be written to each flash cell or transistor. If M voltage levels can be reliably written and read back from each flash cell, then the system can store log2M bits/cell. As the capacity increases, the probability of a readback error increases, thus dictating the use of stronger error correction codes. One such class of codes includes low density parity check (LDPC) codes. LDPC codes enable soft information (i.e., bit reliabilities) to be used to improve decoding performance. A statistical characterization of the read channel is needed to form the bit reliabilities. A problem with the use of LDPC codes arises when the readback sequence of data includes voltages which do not conform to the long-term read channel statistics. One case of this is a stuck cell in NAND flash, in which the readback voltage is independent of the written data. Stuck cells occur as a result of manufacturing defects/flaws, or aging/deterioration of cells. In some cases, for example, when a cell is stuck, the readback voltage is always 0 for that cell and is independent of any read channel statistics. The presence of stuck cells can severely degrade system performance.
Various embodiments of the invention are disclosed in the following detailed description and the accompanying drawings.
The invention can be implemented in numerous ways, including as a process; an apparatus; a system; a composition of matter; a computer program product embodied on a computer readable storage medium; and/or a processor, such as a processor configured to execute instructions stored on and/or provided by a memory coupled to the processor. In this specification, these implementations, or any other form that the invention may take, may be referred to as techniques. In general, the order of the steps of disclosed processes may be altered within the scope of the invention. Unless stated otherwise, a component such as a processor or a memory described as being configured to perform a task may be implemented as a general component that is temporarily configured to perform the task at a given time or a specific component that is manufactured to perform the task. As used herein, the term ‘processor’ refers to one or more devices, circuits, and/or processing cores configured to process data, such as computer program instructions.
A detailed description of one or more embodiments of the invention is provided below along with accompanying figures that illustrate the principles of the invention. The invention is described in connection with such embodiments, but the invention is not limited to any embodiment. The scope of the invention is limited only by the claims and the invention encompasses numerous alternatives, modifications and equivalents. Numerous specific details are set forth in the following description in order to provide a thorough understanding of the invention. These details are provided for the purpose of example and the invention may be practiced according to the claims without some or all of these specific details. For the purpose of clarity, technical material that is known in the technical fields related to the invention has not been described in detail so that the invention is not unnecessarily obscured.
In a soft decision coded system that employs soft information such as system 100, a large error can cause a bit to be labeled as being reliable even when it is in error (e.g., a large LLR of the wrong sign). Errors of this type can cause an LDPC code to fail, hence if they occur often enough, the system performance will be degraded.
As an example, to store the bits [1, 0, 0, 1] in this cell, level 14 or 0.93V would be written. When this cell is read back, a voltage in the region of 0.93V is read in most cases. However, if this cell is a stuck cell, then a voltage with a significant deviation from the write voltage, for example 0.03V, may be observed. In a hard decision coded system, this readback error would cause [0, 0, 0, 0] to be selected because [0, 0, 0, 0] is the closest to 0.03V in the table, so there would be two bit errors (the MSB and the LSB). However, with sufficient redundancy in the hard decision code, the two bit errors can be corrected.
In a soft decision coded system, such as system 100, the bit reliabilities produced by demapper 108 are shown in
where Pr is the probability. In this case, what was written was [1, 0, 0, 1] or 0.93V and what was read back was 0.03V. In other words, 0.03V was input to demapper 108, which outputted the bit reliabilities 1.00, 1.00, 0.99, and 0.56, for bits 3, 2, 1, and 0, respectively, as shown in table 202. As shown, the most significant bit (MSB), or bit 3, is being presented to the decoder as a certain 0 (reliability 1.00), since levels that have a 1 in that bit position are at a significant distance from [0, 0, 0, 0] and hence very unlikely. In reality, bit 3 is in fact a 1 and should have a low reliability value. Bit 2 is 0 with a reliability of 1.00. Bit 1 is 0 with a reliability of 0.99. Bit 0, the least significant bit (LSB), is 0 with a reliability of 0.56.
Because bits 3 and 2 have such a low LLR, an LDPC decoder may not be able to correct these bits. In this particular example, bit 2 does not require correction (since it is actually a 0) but bit 3 requires correction since it is actually a 0. Bits 1 and 0 have a higher LLR, so they still may be correctable by an LDPC decoder. In some cases, an LDPC decoder is not able to correct bits with an LLR<−10. As such, if the hard decision is [0, 0, 0, 0], the output of the LDPC decoder may be [0, 0, 0, 1] even though it should be [1, 0, 0, 1]. Thus, in this example, there would be one bit error.
In some embodiments, saturation of the LLRs is performed so that the error can be corrected by the LDPC, but at the expense of decoder performance. Saturation means that the value of each LLR is limited to above and/or below certain value(s) or saturation point(s). For example, if the saturation point is −5, then if the LLR is less than −5, the LLR is set equal to −5. A saturation point can be selected that helps flip stuck bits associated with stuck cells, but performance is reduced when using saturation.
To write data in this example, user data is provided as input to serial to parallel block 306, which outputs a first set of data to be input to LDPC encoder 308 and a second set of data to be input to RS encoder 310. In this example, the first set of data comprises the two LSBs in a group of 4 adjacent bits and the second set of data comprises the two MSBs in the same group of 4 bits. LDPC encoder 308 outputs encoded data to serial to parallel block 312, which outputs two parallel, encoded LSBs to mapper 316. RS encoder 310 outputs encoded data to serial to parallel block 314, which outputs two parallel, encoded MSBs, to mapper 316. Mapper 316 outputs a voltage based on a mapping scheme, as more fully described below. The voltage is applied to the cell.
To read data from the cell; a readback voltage is read back from the cell and provided as input to LSB demapper 320 and MSB demapper 324. LSB demapper 320 outputs two log likelihood ratios (LLRs) or bit reliabilities corresponding to the two LSB, which are input to LDPC decoder 322. In some embodiments, LSB demapper 320 is implemented using a lookup table. LDPC decoder 322 outputs two decoded LSBs, which are input to MSB demapper 324 and output from read system 304. MSB demapper 324 outputs two encoded MSBs based on the two decoded LSBs and the readback voltage. In some embodiments, MSB demapper 324 outputs as the encoded MSBs the RS bits that: (1) correspond to the voltage level that is closest to the readback voltage and (2) have as the LSBs the two decoded LSBs. The encoded MSBs are input to RS decoder 326, which outputs the decoded MSBs.
In read system 304, decoding is performed in multiple stages. In other words, LDPC decoder 322 first decodes a first set of bits (i.e., the LSBs) and then RS decoder 326 decodes a second set of bits (i.e., the MSBs). This is because the input to RS decoder 326 is affected based on the decoded LSBs.
Although the examples described herein include two bits/cell or four bits/cell, the techniques described herein may be applied to any number of bits/cell. For example, some systems may use eight or 16 bits/cell. Similarly, how bits are divided or grouped varies from embodiment to embodiment. In the case of an eight bit cell, in some embodiments two of the eight bits are MSBs (i.e., encoded using one encoder) and the other six are LSBs (i.e., encoded using another encoder). In some other embodiments, four of the eight bits are MSBs and the other four bits are LSBs.
Although system 300 includes LDPC and RS encoders and decoders, in various embodiments other types of codes may be used. For example, instead of the RS code, a BCH code or other hard decision code may be used. For example, instead of the LDPC code, any code that is described by a parity check matrix, a soft decision Reed Solomon code, or other soft decision code may be used.
In this example, the two LSBs of each cell are encoded using an LDPC code (see second column from left in table) and the two MSBs of each cell are encoded using an RS or BCH code (see leftmost column in table). For example, LDPC encoder 308 is used to encode the two LSBs and RS encoder 310 is used to encode the two MSBs. In some embodiments, on the encoding side, both the RS and LDPC codeword lengths are chosen to be the same length. In some embodiments, the rates of the RS and LDPC codes are chosen so that the probability of failure of the RS code (including stuck cells) given that the LDPC codeword has been successfully decoded, is approximately the same as the probability of failure of the LDPC code (i.e., neither code is the weak link). In most cases, this design criterion will yield a low rate LDPC code (around rate R≈0.8).
In some embodiments, an overall or average system rate is given, and the rate or redundancy of the RS code is first selected, and then any remaining redundancy is given to the LDPC. As an example, suppose that the desired average system rate is R=0.9 and the same number of bits is used in the LDPC and the RS codes. Based on the statistics of stuck bits, a redundancy or rate (R2) is determined for the RS code such that the RS bits can be corrected. R1, the rate of the LDPC code can then be determined as follows:
0.5(R1+R2)=0.9
R1=1.8−R2
The above is one example of determining rates for the soft decision and hard decision codes. In various embodiments, different rates may be used.
On the decoding side, the LDPC bits (i.e., the LSBs in this example) are first decoded without knowledge of the RS code. In
As an example, to store the bits [1, 0, 0, 1] in this cell, a level 14 or 0.93V would be written. When this cell is read back, a voltage in the region of 0.93V is read in most cases. However, if this cell is a stuck cell, then a voltage with a significant deviation from the write voltage, for example 0.03V, may be observed. In the hybrid system of
Although the examples described herein concern component codes applied to either MSBs or LSBs, in various embodiments, other implementations may be used, such as one based on component codes applied to groups of bits that include both MSBs and LSBs. In other words, any appropriate grouping of bits may be used in various embodiments. For example, in a four bits/cell system, the first and third bits may be LDPC bits and the second and fourth bits may be RS/BCH bits. In another example, the MSBs may be LDPC bits and the LSBs may be RS/BCH bits.
In some applications, the mapping of
In some embodiments, MSB demapper 324 is a slicer with four sets of thresholds that are selected by the two LSBs. For example, if the LDPC decoder outputs [0, 1], then the set of thresholds selected would be those halfway between the voltages corresponding to [0, 0, 0, 1], [0, 1, 0, 1], [1, 0, 0, 1], and [1, 1, 0, 1], creating four bins whose boundaries are the thresholds. The MSBs output by demapper 324 would be determined based on the bin that the readback voltage falls in.
If BCH coding is used, Gray code mapping the RS/BCH bits may help performance since if there is a partially stuck cell, the BCH code can help correct it. In some cases the RS/BCH bits are not Gray code mapped. For example, if RS coding is used, performance is not necessarily affected by whether or not the RS/BCH bits are Gray code mapped.
Although the examples described herein include Gray code mapping, various mappings may be used in various embodiments. For example, the LSB mapping may be Gray code mapped, while the MSBs may be mapped using another mapping scheme. Furthermore, a particular group of bits and their associated mapping may span multiple NAND flash cells.
During manufacturing, stuck cells can be mapped out such that data is not stored in blocks of cells that have too many stuck cells in them. However, this is an expensive process and extra blocks of cells need to be added in order to make up for the loss of storage. Using the techniques disclosed herein, more stuck cells can be tolerated, and therefore fewer blocks need to be mapped out, providing better yield and improving overall efficiency.
Although the foregoing embodiments have been described in some detail for purposes of clarity of understanding, the invention is not limited to the details provided. There are many alternative ways of implementing the invention. The disclosed embodiments are illustrative and not restrictive.
This application claims priority to U.S. Provisional Patent Application No. 61/126,937 entitled A CODING ARCHITECTURE FOR MULTI-LEVEL NAND FLASH MEMORY WITH STUCK CELLS filed May 7, 2008 which is incorporated herein by reference for all purposes.
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