The present invention relates to a memory system, a circuit comprising a memory cell, a flash memory device and a memory device.
In the following, some embodiments of the invention will be detailed using the accompanying figures, in which:
a shows an embodiment of a memory system;
b illustrates an error correction by an embodiment;
c shows an embodiment of a circuit;
d shows an embodiment of a flash memory device;
e shows an embodiment of a memory device;
f shows an embodiment of a flash memory device in a housing;
g shows another embodiment of a flash memory device in a housing;
a illustrates a value range of an output of a single level memory cell;
b illustrates a value range of an output of a multi level memory cell;
a illustrates a detection of an outcome of a multi level memory cell with an embodiment;
b shows a sensing example of an embodiment;
a shows a memory system; and
b shows a code illustration.
The plurality of memory cells 110 can comprise non-volatile memory cells. In particular, the plurality of memory cells 110 may comprise NAND- or NOR-Flash memory cells. Embodiments are not limited to non volatile memories and other memory architectures may also be utilized. The read-out circuit 120 may comprise a plurality of sense amplifiers configured to sense the memory cells wherein the read-out circuit 120 can be configured to read-out a status of a memory cell by comparison of an output of a sense amplifier to a threshold.
In some embodiments, the read-out circuit 120 can be configured to sequentially change a word line voltage according to a predetermined manner. In such a case, the read-out circuit 120 may read-out a status of a memory cell by determining an output of a sense amplifier with varying word line voltage and deriving the status from the value of the word line voltage at a time when a comparison between the output of the sense amplifier and the threshold fulfills a predefined relationship. Furthermore, the read-out circuit 120 can be configured to adapt the predetermined manner to an age of the memory cell. Aging effects of memory cells may be partly or completely compensated by embodiments. A detailed embodiment in this regard is described below.
For example, the read-out circuit 120 may comprise a counter for counting incremental word line voltage changes and the read-out circuit 120 can be configured to determine the reliability information based on a count. An output of a sense amplifier may correspond to a bit line voltage and the read-out circuit 120 may be configured to determine the reliability information from the current value of the count at the time when the bit line voltage reaches the threshold, with the threshold representing the above-mentioned predetermined manner. An even more detailed description is presented with regard to
Further, the plurality of memory cells 110 may comprise multi level memory cells. In particular, the plurality of memory cells 110 may comprise 2n-level memory cells and the read-out circuit 120 may be configured to read-out an m-bit value, with m being equal to n+1 or greater, per memory cell. The read-out circuit 120 may be configured to provide the read-out status of the plurality of memory cells 110 along with a plurality of reliability information associated with the read-out status as a plurality of binary values.
In embodiments, the data processor 130 can be configured to derive the payload data by performing an error detection and/or an error correction by combining the read-out status and the associated reliability information. The data processor 130 can be further configured to derive the payload data by performing error detection and/or error correction by combining a plurality of read-out states, an associated plurality of reliability information and a plurality of redundancy data.
In embodiments, the memory system 100 may further comprise an encoder to receive the payload data and to derive the redundancy data associated with the payload data based on the payload data and an encoding rule. The data processor 130 can be configured to use a maximum likelihood estimation rule, a linear block correction code and/or a Trellis decoding scheme to determine the payload data.
b illustrates an error correction by an embodiment.
In an embodiment of a memory system 100 said valid codewords can be stored in the plurality of memory cells 110, comprising the payload data and the redundancy data. The read-out circuit 120 is configured to read-out a status of the plurality of memory cells, the read-out status comprising the payload data, the redundancy data and associated reliability information. The read-out status can be mapped to a valid codeword. In accordance with some embodiments, this mapping is performed by use of the reliability information. The thus derived codeword unambiguously indicates the payload data of interest. However, according to a comparison embodiment also discussed below, the reliability information is not used. Rather the mapping from the read-out status to the codeword is performed merely by quantization, such as by evaluating a bit line voltage versus a threshold yielding a binary codeword, with in case of a resulting invalid codeword, deriving a valid codeword from the invalid codeword merely by use of knowledge exploiting the redundancy within the codeword introduced by the redundancy data 136.
Multiple effects, as, for example, noise, electrical disturbances, aging of the memories or memory cells etc., may cause a date of such a memory system being corrupted or erroneous as already noted above.
Assume for example that a valid binary codeword 138 was written to the plurality of memory cells 110. A read-out of the same results, by use of quantization or thresholding, to a detected codeword 144. Due to the above-mentioned corruption, same may be invalid, i.e., it does not lie in the set 134 of valid codewords. Error correction exploiting the redundancy 136 may be carried out by choosing a valid codeword 146, which lies closest to the codeword 144 within the set 140 of read-out statuses. In the example depicted in
In embodiments the data processor 130 is configured to derive the payload data from the read-out status using the reliability information. In
The data processor 130 may be able to determine, that the first digit 0.9 of codeword 148 has a high probability of being a “1”, where the second and third digits, 0.4 and 0.6, have rather high probabilities of being incorrect “0” and “1”, since they are rather close to the decision threshold 0.5. Consequently, the data processor 130 may flip the second and third digits rather than the first digit, correctly deciding on the codeword 138, which was actually stored. Thus, the probability of deriving the correct codeword and thus, the correct payload data, is increased relative to the case of correcting the invalid codeword merely by use of redundancy data.
c shows an embodiment of a circuit 150 comprising a memory cell 155 for storing a data bit and a read-out circuit 160 for deriving a sense result from the memory cell 155, the sense result indicating a read-out result along with a reliability information for said read-out result. Furthermore, the circuit 150 comprises a means 165 for performing an error detection and/or error correction based on the reliability information and the read-out results to obtain the data bit.
In embodiments the memory cell 155 may comprise a non volatile memory cell. The means 165 for performing can be configured to use a Trellis decoding scheme to obtain the data bit. The means 165 for performing may be configured to use a linear block correction code.
Embodiments may carry out a method for reading a data bit from a memory cell, comprising the steps of storing the data bit, deriving a read-out result from the memory cell, and determining a reliability information along with said read-out result. Embodiments may further carry out a step of performing an error detection and/or error correction based on the read-out result and the reliability information to obtain the data bit.
d illustrates an embodiment of a flash memory device 170. The flash memory device 170 comprises a word line 172, a bit line 174 and a flash memory cell 176 coupled to the word line 172 and to the bit line 174. Furthermore, the flash memory device 170 comprises a word line voltage provider 178 being operative to sequentially vary a word line voltage on the word line 172. Moreover, the flash memory device 170 comprises a read-out circuit 180 being connectable to the bit line 174 and being configured to provide a sense result indicating a read-out result for the flash memory cell 176 along with a corresponding reliability information based on the word line voltage and a bit line voltage on the bit line 174. In
In embodiments the word line voltage provider 178 may further comprise an incrementor for incrementing a word line voltage and the read-out circuit 180 may be configured to determine the sense result dependent on the word line voltage.
In embodiments the flash memory cell 176 and the read-out circuit 180 may be commonly integrated on a die, and the read-out circuit 180 may be configured to provide the sense result such that the sense result is receivable at an external contact of the die.
e shows an embodiment of a memory device 182 comprising a 2n-level memory cell 184 and a read-out circuit 186 configured to provide a sense result from the 2n-level memory cell 184, the sense result having a resolution greater than or equal to 2n+1.
In embodiments the 2n-level memory cell and the read-out circuit 186 may be commonly integrated on a die, and a read-out circuit 186 may be configured to provide a sense result such that the sense result is receivable at an external contact of the die.
f illustrates an embodiment of a memory device 182, wherein the 2n-level memory cell 184 and the read-out circuit 186 are integrated in a housing 188. In the embodiment shown in
Another embodiment of a memory device 182 is depicted in
a illustrates an example of a probability density function (PDF=Probability Density Function) of a read-out or sense result of a single level memory cell (SLC=Single Level memory Cell).
b illustrates a similar scenario for a multi level memory cell (MLC=Multi Level memory Cell).
Trends and development may be regarded likely to move towards storing more than one or two bits per cell, for example, three or four or even more. Increasing the number of bits per cell may also increase the likelihood of appearing errors, for example, during a read process, and therefore a momentum for much more powerful error correction methodologies may be created. A similar tendency can be observed with respect of structure sizes. The smaller structure sizes of the flash process technology, the higher a failure probability may be. Storing more than one bit per cell may, for example, by means of multilevel representation, reduce margins between different level distributions.
a shows another viewgraph having bit line voltage Vt on the abscissa and sensing probability or the PDF on the ordinate.
For example, for writing to such a multi level cell, a multitude of target levels for storage may be distinguished in the analog domain. As indicated in
Within the scope of a read sensor there is a statistical variation of the read levels, as it was described above, for example, assuming a Gaussian distributed error, which can be superimposed to the bit line voltage. During the write process, an expectation may only be a compact level distribution around the desired target levels. During aging of a memory cell, a widening and movement of the distributions can reduce the separation windows. During the read process, the likelihood of false classification due to occasional distribution overlap raises. Embodiments may therefore make use of soft values rather than digital respectively binary classification of output signals of sense amplifiers, which may be used as an input for ECC.
By means of wear leveling, cells of a memory cell array may homogeneously have the same count of erases. Decision levels may be globally adapted by means of hard coded algorithms, to compensate for aging effects. This compensation can be based on experience and prognosis. Embodiments may globally adapt the decision levels after read failure by means of systematic variations of this decision level and storage of the resulting level. However, cell degradation may be inhomogeneous due to read disturbance. Embodiments may carry out local adaption as well.
b illustrates a sensing example of an embodiment.
Embodiments may carry out sensing of the bit line level with a granularity, which is finer than a write level granularity. This can be seen from
Embodiments can therefore generate and use information on a physical condition of a memory, which is also known as soft information from the field of coding. Soft information can, for example, be created during a read operation and/or be dependent on the read bit, read bytes or read bigger units, may be used in addition to a normal correction ability of the used codes to increase the error correction capability or performance. In embodiments the error correction performance may be increased from a range of, for example, up to approximately 16 bits per 512 bytes to a range of correctable bits of 100 per 512 bytes or more. Embodiments may combine the obtained soft information with, for example, low-density parity-check codes (LDPC=Low-Density Parity-Check) or with Trellis Coding Modulation (TCM=Trellis Coding Modulation). Embodiments may further improve error detection and/or error correction ability of memory systems by combining multiple coding strategies as, for example, inner coding and outer coding of the above mentioned codes. Embodiments are not limited to the above mentioned codes, other codes or combinations with other codes may be used as well.
Embodiments may be implemented as flash memory systems in which the ECC unit uses soft information. This soft information may be generated within the flash memory mechanism.
Another embodiment is depicted in
After a number of cycles of the clock signal 605, i.e. after a number of increments of the incrementor 610 and the word line voltage on the word line 620 the transistor Ti1 opens. Therewith, the voltage on the bit line 625 changes, and the sense amplifier or sense transistor Tsense detects the data. The output of the data will be A/D converted by the A/D converter 640 and provided to the counter 615, which is also coupled to the clock signal input 605. The counter 615 can therewith determine a number of steps carried out until the output of the A/D converter 640 indicates the data. The number of steps can be taken as indication of how secure the read data are. The output of the counter can be used as soft information. In one simple embodiment only a single bit may be used as soft information as will be described in the following.
In
The region 725 can also be considered the region with a lower likelihood for the data being correct, because the threshold 715 may no longer be ideal. Thus, the closer a value of a read-out or a sense result is to the center, i.e., the ideal threshold 715, the more likely it is that the date may be wrong. Therefore, the closeness to the ideal threshold may be used as soft information.
In an embodiment, if the bit line voltage Vt is in the “secure area” 720 the soft information data will be set to “0”. If the bit line voltage Vt is in the “insecure area” 725, then the soft information will be set to “1”, respectively vise versa. This may be one primitive approach which would require more read cycles to detect the bit line voltage. Embodiments can provide a benefit that a later forward error correction can significantly improve the level of correctness of the data. The above described embodiment may be a primitive approach by using only one bit of soft information for all data obtained from reading the same word line. Of course in other embodiments a finer level can be used, for example, two bits of soft information, i.e., four levels of security.
The embodiment which was described above, i.e., using a multiple read procedure, uses this concept for generation of soft information in order to improve the error correction. The number of read pulses in order to get stable data may serve as soft information. Embodiments may use many different methodologies for generation of such soft information. In the embodiment described above, the number of needed read pulses serves as a quality indication of the reliability of a read-out result, for example, a flash cell, in other words, the number of needed read pulses serves as indication, on how secure the read-out result of a memory cell can be considered. The number of read pulses can be used as information for further processing the error correction part.
In embodiments, once the soft information is generated, it can be preprocessed for the ECC decoder, e.g. by converting a count number into reliability information. Then soft information or reliability information together with a codeword, which may comprise payload data and redundancy data, can be sent to the ECC decoder. Optionally, embodiments may utilize a linear block ECC correction, for example, BCH, after an iterative ECC correction, as, for example, TCM.
Following step 810 data may be transferred from the flash memory system or chip to a micro-controller in step 820. This may also be done within an extra data line, for example, in parallel to an 8-bit wide bus. In other embodiments the transfer of soft information may be carried out by using a special interface, for example, a high speed serial interface.
Once the data was transferred, e.g., from the flash memory to the micro-controller in step 820 error decoding and correction can be carried out in a step 830. The error decoding/correction operations of step 830 may be carried out as part of a functional block of the micro-controller with or without the use of the soft information. Optionally, additional benefits may be achieved if several codes are combined, as, for example, a BCH and a LDPC code.
A combination of codes for flash usage with an embodiment, e.g., using LDPC codes or Trellis code modulation, is illustrated in
Embodiments may use codes like BCH, Reed-Solomon, Hamming etc., which in comparison guarantee the correction up to a predetermined maximum number of correctable errors as long as a number of errors does not exceed a known error correction ability of the chosen code. In other words, embodiments may use codes, in which the code correction ability is predictable, for as long as an actual number of errors stays below a maximum.
Embodiments may provide higher reliability, also when combining codes. According to
In a similar way, the pattern according to the non-binary vector 1203, in which the first two components are 0, yields that the LSB is always set to 1. The more interesting case in this embodiment is the case 1202 where the first and the last component of the non-binary vector are 0. If M1 is greater than M2 than the LSB is set to 0 while the MSB is set to M1. In the other case the LSB is set to 1 and the MSB is set to M2. Therefore, the ECC decoder can use the non-binary value in order to correct errors.
Some embodiments may make effective use of memory space for storage of user data and not for storage of parity data, which would decrease the storage amount of user data. Some systems may dimension the size for the parity to the minimum size really needed, yielding a high error ratio, whereas an embodiment can may enable a lower error ratio.
Embodiments may be implemented in the following memory systems or memory modules, which can be used in almost every application utilizing digital data. Memory systems are used to store or buffer digital data, where multiple different memory technologies, as, for example, flash memories are known.
Error detection and error correction functionality can be integrated in a memory system 1300 as part of a component, i.e., either on the memory 1320 or the controller respectively micro-controller 1330 or even on both components. The purpose of an error detection or correction functionality is to eliminate errors, for example due to the above mentioned effects, and keep the functionality of the memory system, respectively to disable not sufficient memory completely.
Embodiments may also use bad block marking methodologies, which can be used in addition and treat permanent appearing errors, for example, by detecting them directly after production. Some embodiments may focus on temporary errors and errors which may appear after production, for example, because of the above mentioned effects, as, e.g. aging effects of the memory cells, which may lead to an increasing number of appearing errors over time.
Additional data bits may be added for administration tasks or for storing created parity data of a used code in the memory.
Embodiments may increase a performance of error detection or correction means by utilizing soft information in terms of reliability information for read-out results of memory cells. Embodiments may enable enhanced error correction schemes through provision of said reliability information.
Depending on certain implementation requirements of the inventive methods, the inventive methods may be implemented in hardware or in software. The implementation can be performed using a digital storage medium, in particular a flash memory, a disc, a DVD (DVD=Digital Versatile Disk) or a CD (CD=Compact Disk) having electronically readable control signals stored thereon, which cooperate with a programmable computer system such that the inventive methods are performed. Generally, the present invention is, therefore, a computer program product with a program code stored on a machine readable carrier, the program code being operative for performing the inventive methods when the computer program product runs on a computer. In other words, the inventive methods are, therefore, a computer program having a program code for performing a least one of the inventive methods when the computer program runs on a computer.
Number | Name | Date | Kind |
---|---|---|---|
6279133 | Vafai et al. | Aug 2001 | B1 |
7158418 | Chae et al. | Jan 2007 | B2 |
7844879 | Ramamoorthy et al. | Nov 2010 | B2 |
20040008567 | Furuyama | Jan 2004 | A1 |
20050157555 | Ono et al. | Jul 2005 | A1 |
20050268208 | Shimizume et al. | Dec 2005 | A1 |
20070002611 | Ye et al. | Jan 2007 | A1 |
20070033490 | Moosrainer et al. | Feb 2007 | A1 |
20070220400 | Toda et al. | Sep 2007 | A1 |
20070226590 | Nagai | Sep 2007 | A1 |
20080082897 | Brandman et al. | Apr 2008 | A1 |
20080137413 | Kong et al. | Jun 2008 | A1 |
20080151617 | Alrod et al. | Jun 2008 | A1 |
20080201625 | Mulligan | Aug 2008 | A1 |
20090013231 | Lam | Jan 2009 | A1 |
20110103145 | Sarin et al. | May 2011 | A1 |
20110185261 | Toda | Jul 2011 | A1 |
Number | Date | Country | |
---|---|---|---|
20090244973 A1 | Oct 2009 | US |