Selective re-programming of analog memory cells

Information

  • Patent Grant
  • 8238157
  • Patent Number
    8,238,157
  • Date Filed
    Sunday, April 11, 2010
    14 years ago
  • Date Issued
    Tuesday, August 7, 2012
    11 years ago
Abstract
A method for data storage includes defining, in a memory that includes multiple analog memory cells, an erased state, a set of non-erased programming states and a partial subset of the non-erased programming states. Data is initially stored in a first group of the analog memory cells by programming each of at least some of the memory cells in the first group from the erased state to a respective non-erased programming state selected from the set of non-erased programming states. After initially storing the data, a second group of the analog memory cells, which potentially cause interference to the first group, is programmed. After programming the second group, the first group is selectively re-programmed with the data by repeating programming of only the memory cells in the first group whose respective programming states belong to the partial subset.
Description
FIELD OF THE INVENTION

The present invention relates generally to memory devices, and particularly to methods and systems for re-programming analog memory cells.


BACKGROUND OF THE INVENTION

Several types of memory devices, such as Flash memories, use arrays of analog memory cells for storing data. Each analog memory cell stores a quantity of an analog value, also referred to as a storage value, such as an electrical charge or voltage. This analog value represents the information stored in the cell. In Flash memories, for example, each analog memory cell holds a certain amount of electrical charge. The range of possible analog values is typically divided into intervals, each interval corresponding to one or more data bit values. Data is written to an analog memory cell by writing a nominal analog value that corresponds to the desired bit or bits.


Some memory devices, commonly referred to as Single-Level Cell (SLC) devices, store a single bit of information in each memory cell, i.e., each memory cell can be programmed to assume two possible programming levels. Higher-density devices, often referred to as Multi-Level Cell (MLC) devices, store two or more bits per memory cell, i.e., can be programmed to assume more than two possible programming levels.


Flash memory devices are described, for example, by Bez et al., in “Introduction to Flash Memory,” Proceedings of the IEEE, volume 91, number 4, April, 2003, pages 489-502, which is incorporated herein by reference. Multi-level Flash cells and devices are described, for example, by Eitan et al., in “Multilevel Flash Cells and their Trade-Offs,” Proceedings of the 1996 IEEE International Electron Devices Meeting (IEDM), New York, N.Y., pages 169-172, which is incorporated herein by reference. The paper compares several kinds of multilevel Flash cells, such as common ground, DINOR, AND, NOR and NAND cells.


Eitan et al., describe another type of analog memory cell called Nitride Read Only Memory (NROM) in “Can NROM, a 2-bit, Trapping Storage NVM Cell, Give a Real Challenge to Floating Gate Cells?” Proceedings of the 1999 International Conference on Solid State Devices and Materials (SSDM), Tokyo, Japan, Sep. 21-24, 1999, pages 522-524, which is incorporated herein by reference. NROM cells are also described by Maayan et al., in “A 512 Mb NROM Flash Data Storage Memory with 8 MB/s Data Rate”, Proceedings of the 2002 IEEE International Solid-State Circuits Conference (ISSCC 2002), San Francisco, Calif., Feb. 3-7, 2002, pages 100-101, which is incorporated herein by reference. Other exemplary types of analog memory cells are Floating Gate (FG) cells, Ferroelectric RAM (FRAM) cells, magnetic RAM (MRAM) cells, Charge Trap Flash (CTF) and phase change RAM (PRAM, also referred to as Phase Change Memory—PCM) cells. FRAM, MRAM and PRAM cells are described, for example, by Kim and Koh in “Future Memory Technology including Emerging New Memories,” Proceedings of the 24th International Conference on Microelectronics (MIEL), Nis, Serbia and Montenegro, May 16-19, 2004, volume 1, pages 377-384, which is incorporated herein by reference.


SUMMARY OF THE INVENTION

An embodiment of the present invention provides a method for data storage, including:


in a memory that includes multiple analog memory cells, defining an erased state, a set of non-erased programming states and a partial subset of the non-erased programming states;


initially storing data in a first group of the analog memory cells by programming each of at least some of the memory cells in the first group from the erased state to a respective non-erased programming state selected from the set of non-erased programming states;


after initially storing the data, programming a second group of the analog memory cells, which potentially cause interference to the first group; and


after programming the second group, selectively re-programming the first group with the data by repeating programming of only the memory cells in the first group whose respective programming states belong to the partial subset.


In some embodiments, initially storing the data includes writing respective storage values into the memory cells in the first group and verifying the written storage values using first verification thresholds, and selectively re-programming the first group includes re-writing the storage values that are associated with the partial subset, and verifying the re-written storage values using second verification thresholds, higher than the corresponding first verification thresholds. In an embodiment, programming the memory cells includes writing respective storage values into the memory cells, and defining the partial subset includes including in the partial subset at least a non-erased programming state corresponding to a lowest range of the analog values among the non-erased memory states. In a disclosed embodiment, programming the memory cells includes writing respective storage values into the memory cells, and defining the partial subset includes including in the partial subset at least a non-erased programming state corresponding to a highest range of the analog values among the non-erased memory states.


In some embodiments, the method includes programming the second group with dummy data responsively to detecting that programming of the second group is postponed, so as to cause re-programming of the first group. In an embodiment, detecting that the programming of the second group is postponed includes detecting that a time that elapsed since the programming of the second group exceeds a predefined maximum value. In another embodiment, detecting that the programming of the second group is postponed includes determining that shut-off of electrical power is imminent.


In a disclosed embodiment, upon preparing to read the data from the first group, the method includes applying a corrective action to the first group responsively to detecting that that the first group was not re-programmed. Applying the corrective action may include programming the second group with dummy data, so as to cause re-programming of the first group. Additionally or alternatively, applying the corrective action may include sensing at least one analog value that was written into a respective analog memory cell in the first group and has become negative. Further additionally or alternatively, applying the corrective action may include applying one or more programming pulses to at least one of the memory cells in the first group.


There is additionally provided, in accordance with an embodiment of the present invention, apparatus for data storage, including:


a memory, which includes multiple analog memory cells; and


circuitry, which is configured to define an erased state, a set of non-erased programming states and a partial subset of the non-erased programming states, to initially store data in a first group of the analog memory cells by programming each of at least some of the memory cells in the first group from the erased state to a respective non-erased programming state selected from the set of non-erased programming states, to program a second group of the analog memory cells, which potentially cause interference to the first group, after initially storing the data, and, after programming the second group, to selectively re-program the first group with the data by repeating programming of only the memory cells in the first group whose respective programming states belong to the partial subset.


The present invention will be more fully understood from the following detailed description of the embodiments thereof, taken together with the drawings in which:





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 is a block diagram that schematically illustrates a memory system, in accordance with an embodiment of the present invention;



FIGS. 2A-2C are graphs showing programming states and threshold voltage distributions in a group of analog memory cells, in accordance with embodiments of the present invention;



FIG. 3 is a flow chart that schematically illustrates a method for selective re-programming of analog memory cells, in accordance with an embodiment of the present invention;



FIG. 4 is a diagram that schematically illustrates a partially-programmed memory block, in accordance with an embodiment of the present invention; and



FIG. 5 is a flow chart that schematically illustrates a method for data readout from a partially-programmed memory block, in accordance with an embodiment of the present invention.





DETAILED DESCRIPTION OF EMBODIMENTS
Overview

Data storage in analog memory cells is typically performed by writing a respective analog value (also referred to as storage value) to each memory cell. The storage operation programs at least some of the memory cells from an erased state to respective non-erased programming states, selected from a predefined set of programming states. (The erased state is also regarded herein as a programming state. Programming states other than the erased state are referred to as non-erased programming states.) Data readout typically involves reading the analog values from the memory cells and determining, based on the read analog values, the programming state of each memory cell. In practical memory devices, however, a given memory cell may suffer from interference from other memory cells, and this interference may cause read errors. Typically, the interference is caused by cross-coupling from neighboring memory cells.


Embodiments of the present invention that are described hereinbelow provide improved methods and systems for programming analog memory cells. The disclosed techniques reduce interference effects by programming a group of memory cells in two phases. The first phase is performed before programming of potentially-interfering memory cells. The second phase, which is referred to as re-programming, is performed after the potentially-interfering memory cells are programmed. The second programming phase comprises an iterative process, which applies programming pulses to the memory cells until the analog values of the memory cells reach certain verification thresholds. Since the second programming phase is performed after the potential interference is already present, the iterative programming and verification process inherently compensates for the interference.


In some cases, however, two-phase programming may cause performance degradation. For example, the verification thresholds used during the second programming phase are typically higher than the respective verification thresholds used in the first programming phase. The need to assign different verification thresholds to the two phases increases the overall range of analog values. As a result, memory cells are more likely to suffer from over-programming, because the analog values may reach higher maximum values. The likelihood of analog values drifting below zero and becoming unreadable may also increase, for example when one of the programming states is assigned analog voltages that are closer to 0V. In other cases, the separation between adjacent memory states may be reduced, thus increasing the likelihood of read errors.


In some embodiments, performance degradation is reduced by defining a partial subset of the non-erased programming states, and applying the second programming phase selectively, only to the memory cells whose programming states belong to the partial subset. Programming states that are outside the predefined subset are programmed only in the first programming phase. Re-programming may be omitted, for example, for the lowest and highest non-erased programming states (i.e., the non-erased programming states corresponding to the lowest and highest analog values). By applying re-programming only to a predefined subset of the non-erased programming states, only the programming states in the subset typically have different verification thresholds for the first and second phases. As a result, the overall range of analog voltages can be reduced, and the separation between adjacent programming states can be increased.


System Description


FIG. 1 is a block diagram that schematically illustrates a memory system 20, in accordance with an embodiment of the present invention. System 20 can be used in various host systems and devices, such as in computing devices, cellular phones or other communication terminals, removable memory modules (“disk-on-key” devices), Solid State Disks (SSD), digital cameras, music and other media players and/or any other system or device in which data is stored and retrieved.


System 20 comprises a memory device 24, which stores data in a memory cell array 28. The memory array comprises multiple analog memory cells 32. In the context of the present patent application and in the claims, the term “analog memory cell” is used to describe any memory cell that holds a continuous, analog value of a physical parameter, such as an electrical voltage or charge. Array 28 may comprise analog memory cells of any kind, such as, for example, NAND, NOR and Charge Trap Flash (CTF) Flash cells, phase change RAM (PRAM, also referred to as Phase Change Memory—PCM), Nitride Read Only Memory (NROM), Ferroelectric RAM (FRAM), magnetic RAM (MRAM) and/or Dynamic RAM (DRAM) cells.


The charge levels stored in the cells and/or the analog voltages or currents written into and read out of the cells are referred to herein collectively as analog values or storage values. Although the embodiments described herein mainly address threshold voltages, the methods and systems described herein may be used with any other suitable kind of storage values.


System 20 stores data in the analog memory cells by programming the cells to assume respective memory states, which are also referred to as programming levels. The programming states are selected from a finite set of possible states, and each programming state corresponds to a certain nominal storage value. For example, a 2 bit/cell MLC can be programmed to assume one of four possible programming states by writing one of four possible nominal storage values into the cell.


Memory device 24 comprises a reading/writing (R/W) unit 36, which converts data for storage in the memory device to analog storage values and writes them into memory cells 32. In alternative embodiments, the R/W unit does not perform the conversion, but is provided with voltage samples, i.e., with the storage values for storage in the cells. When reading data out of array 28, R/W unit 36 converts the storage values of memory cells 32 into digital samples having a resolution of one or more bits. Data is typically written to and read from the memory cells in groups that are referred to as pages. In some embodiments, the R/W unit can erase a group of cells 32 by applying one or more negative erasure pulses to the cells.


The storage and retrieval of data in and out of memory device 24 is performed by a Memory Signal Processor (MSP) 40. MSP 40 comprises an interface 44 for communicating with memory device 24, and a signal processing unit 48, which processes the data that is written into and read from device 24. In some embodiments, unit 48 encodes the data for storage using a suitable Error Correction Code (ECC) and decodes the ECC of data retrieved from the memory. In some embodiments, unit 48 produces the storage values for storing in the memory cells and provides these values to R/W unit 36. Alternatively, unit 48 provides the data for storage, and the conversion to storage values is carried out by the R/W unit internally to the memory device. Alternatively to using an MSP, the methods described herein can be carried out by any suitable type of memory controller.


MSP 40 communicates with a host 52, for accepting data for storage in the memory device and for outputting data retrieved from the memory device. MSP 40, and in particular unit 48, may be implemented in hardware. Alternatively, MSP 40 may comprise a microprocessor that runs suitable software, or a combination of hardware and software elements.


The configuration of FIG. 1 is an exemplary system configuration, which is shown purely for the sake of conceptual clarity. Any other suitable memory system configuration can also be used. Elements that are not necessary for understanding the principles of the present invention, such as various interfaces, addressing circuits, timing and sequencing circuits and debugging circuits, have been omitted from the figure for clarity.


In the exemplary system configuration shown in FIG. 1, memory device 24 and MSP 40 are implemented as two separate Integrated Circuits (ICs). In alternative embodiments, however, the memory device and the MSP may be integrated on separate semiconductor dies in a single Multi-Chip Package (MCP) or System on Chip (SoC), and may be interconnected by an internal bus. Further alternatively, some or all of the MSP circuitry may reside on the same die on which the memory array is disposed. Further alternatively, some or all of the functionality of MSP 40 can be implemented in software and carried out by a processor or other element of the host system. In some embodiments, host 44 and MSP 40 may be fabricated on the same die, or on separate dies in the same device package.


In some embodiments, MSP 40 (or other memory controller that carries out the methods described herein) comprises a general-purpose processor, which is programmed in software to carry out the functions described herein. The software may be downloaded to the processor in electronic form, over a network, for example, or it may, alternatively or additionally, be provided and/or stored on non-transitory tangible media, such as magnetic, optical, or electronic memory.


In an example configuration of array 28, memory cells 32 are arranged in multiple rows and columns, and each memory cell comprises a floating-gate transistor. The gates of the transistors in each row are connected by word lines, and the sources of the transistors in each column are connected by bit lines. The memory array is typically divided into multiple pages, i.e., groups of memory cells that are programmed and read simultaneously. Pages are sometimes sub-divided into sectors. In some embodiments, each page comprises an entire row of the array. In alternative embodiments, each row (word line) can be divided into two or more pages. For example, in some devices each row is divided into two pages, one comprising the odd-order cells and the other comprising the even-order cells. In a typical implementation, a two-bit-per-cell memory device may have four pages per row, a three-bit-per-cell memory device may have six pages per row, and a four-bit-per-cell memory device may have eight pages per row.


Erasing of cells is usually carried out in blocks that contain multiple pages. Such blocks are referred to herein as erasure blocks or memory blocks. Typical memory devices may comprise several thousand erasure blocks. In a typical two-bit-per-cell MLC device, each erasure block is on the order of 32 word lines, each comprising several tens of thousands of cells. Each word line of such a device is often partitioned into four pages (odd/even order cells, least/most significant bit of the cells). Three-bit-per cell devices having 32 word lines per erasure block would have 192 pages per erasure block, and four-bit-per-cell devices would have 256 pages per block. Alternatively, other block sizes and configurations can also be used. Some memory devices comprise two or more separate memory cell arrays, often referred to as planes. Since each plane has a certain “busy” period between successive write operations, data can be written alternately to the different planes in order to increase programming speed.


In some embodiments, R/W unit 36 programs memory cells 32 using an iterative Program and Verify (P&V) process. In a typical P&V process, an entire group of memory cells (e.g., a word line) is programmed by applying a sequence of programming pulses to the memory cells in the group. The storage values programmed in the cells are read after each pulse and compared (“verified”) with one or more verification thresholds. The programming iterations continue selectively only for memory cells that have not yet reached the desired levels.


Re-Programming of Selected Memory States


FIGS. 2A-2C are graphs showing programming states and threshold voltage distributions for several example re-programming schemes, in accordance with embodiments of the present invention. These examples refer to a group (e.g., a word line) of four-level memory cells, each memory cell storing two bits of data. Each memory cell in the group can be programmed to one of four programming states 60A . . . 60D, representing two-bit combinations “11”, “10”, “00” and “01”, respectively. Programming state 60A, also represents erased memory cells, and is referred to herein as an erased state. States 60B-60D in this example are referred to as non-erased states. Typically although not necessarily, the memory cells that are associated with the erased state have negative threshold voltages, and the memory cells that are associated with the non-erased states have positive threshold voltages.



FIG. 2A shows an example in which re-programming is applied to all three non-erased programming states. This example is depicted herein as a reference, in order to demonstrate the advantages of the disclosed techniques. In the example of FIG. 2A, the memory cells in the group are initially erased, i.e., associated with state 60A. At this stage, the threshold voltages of the memory cells are distributed in accordance with a distribution 64.


In a first programming phase, each memory cell is programmed with two data bits, i.e., to one of the four states 60A . . . 60D. Programming typically comprises an iterative P&V process. (Memory cells that are programmed with “11” do not receive programming pulses and thus remain at state 60A.) The first programming phase is designed so that the threshold voltages of the memory cells associated with non-erased states 60B . . . 60D are distributed in accordance with distributions 68A . . . 68C, respectively. The memory cells associated with state 60A remain distributed according to distribution 64.


The first programming phase is carried out before programming of at least some of the memory cells that potentially cause interference to the cell group in question. After the first programming phase, the potentially-interfering memory cells (e.g., a neighboring word line) are programmed. A second programming phase is performed after the potentially-interfering memory cells are programmed.


In the second programming phase (“a re-programming phase”), the threshold voltages of the memory cells that are associated with non-erased states 60B . . . 60D are increased. After the second programming phase, the threshold voltages of the memory cells associated with non-erased states 60B . . . 60D are distributed in accordance with distributions 72A . . . 72C, respectively. The second programming phase is typically performed using an iterative P&V process.


Since the second programming phase is performed while the interference from neighboring memory cells is already present, the second programming phase inherently compensates for this interference. Typically, the average increase in threshold voltage (the displacement of distributions 72A . . . 72C relative to distributions 68A . . . 68C, respectively) depends on the amount of expected interference that is to be compensated for.


As can be seen in FIG. 2A, each non-erased state that is programmed in two phases is associated with a relatively large interval on the threshold voltage axis. These large intervals are important, for example, when the memory cells are subjected to a long retention period after performing only the first programming phase. In particular, state 60B may occupy a range of relatively small positive threshold voltages. In this scenario, the likelihood of threshold voltages in state 60B drifting below 0V and becoming unreadable may increase. Additionally or alternatively, the overall range of threshold voltages (sometimes referred to as “voltage window”) is increased. A large voltage window may increase the likelihood of over-programming memory cells.


The effect on the voltage window caused by re-programming can be seen in the example of FIG. 2A. In this example, the final desired positions of programming states 60B . . . 60D are at distributions 72A . . . 72C, respectively. In the first programming phase, the memory cells are programmed to distributions 68A . . . 68C. In the second programming phase, the memory cells are re-programmed to the final distributions 72A . . . 72C. The average displacement of distributions 72A . . . 72C relative to distributions 68A . . . 68C, respectively, is denoted d. If only the first programming phase is executed, and then the memory cells are subject to a retention period, the data still needs to be retained reliably. Therefore, the lowest edge of distribution 68A should have sufficient margin above 0V. Typically, the lowest edge of distribution 68A is positioned at a similar value to the case in which re-programming is not applied to programming state 60B. Distributions 72A . . . 72C (the final positions of states 60B . . . 60D) are shifted by d relative to this position. Thus, the re-programming operation causes an increase of d in the voltage window.



FIGS. 2B and 2C show examples of selective re-programming schemes, in accordance with embodiments of the present invention. In these schemes, system 20 programs only a partial subset of the non-erased programming states using two programming phases. The system programs one or more of the non-erased programming states using a single programming phase, i.e., without re-programming.


In the example of FIG. 2B, non-erased programming states 60C and 60D are programmed using two programming phases, as described above. Non-erased programming state 60B, on the other hand, is programmed using a single programming phase. As can be seen in the figures, the range of threshold voltages occupied by state 60B in FIG. 2B is narrower than the range of threshold voltages occupied by this state in FIG. 2A. As a result, state 60B in FIG. 2B is positioned further away from 0V in comparison with state 60B in FIG. 2A. Therefore, the scheme of FIG. 2B has a lower likelihood that threshold voltages of memory cells in state 60B will drift below 0V and become unreadable.


In the alternative example of FIG. 2C, only state 60C is programmed using two programming phases. States 60B and 60D are programmed using a single programming phase. As a result, the threshold voltage ranges occupied by states 60B and 60D in FIG. 2B are narrower than the corresponding ranges occupied by these states in FIG. 2A. Refraining from re-programming the highest programming state (state 60D) is sometimes advantageous for a number of reasons. For example, the programming sequence is typically faster, since the programming pulses do not need to reach the high end of the voltage window. Additionally, interference that affects this state typically does not cause read errors, since there is no adjacent programming state above it.


As can be seen in FIGS. 2B and 2C, in the first programming phase, programming states 60B and 60C occupy threshold voltage ranges that are relatively close to one another (see the relatively small separation between distributions 72A and 68B). Nevertheless, this separation does not cause performance degradation because at this stage (after the first programming phase) the memory cells are subject to little or no interference. In this situation, small separation between the programming states is typically sufficient. When interference appears (as a result of programming the neighboring memory cells), it is immediately compensated for by the second programming phase. Thus, there is no situation in which programming states 60B and 60C are read when their threshold voltage distributions are too close apart.


System 20 can use the narrower threshold voltage ranges in the schemes of FIGS. 2B and 2C to (1) further increase the distance of state 60B from 0V, (2) increase the separation between adjacent programming states, and/or (3) reduce the maximum threshold voltage reached by state 60D.


As noted above, the first and second programming phases may be implemented using iterative Programming and Verification (P&V) processes. In some embodiments, system 20 programs the memory cells to different threshold voltage distributions in the first and second programming phases by using a different set of verification thresholds in each programming phase.


Consider, for example, programming state 60C in FIG. 2B. In the first programming phase, system 20 programs the memory cells associated with state 60C to reach distribution 68B by verifying the cell threshold voltages using a verification threshold denoted V2A. In the second programming phase, system 20 programs the memory cells associated with this state to reach distribution 72B by using a higher verification threshold V2B. The memory cells of state 60D (FIG. 2B) undergo a similar process: In the first programming phase, system 20 programs these memory cells using a verification threshold V3A, so as to produce distribution 68C. In the second programming phase, system 20 programs the memory cells of state 60D using a higher verification threshold V3B, so as to produce distribution 72C.


For programming states that are programmed in a single programming phase, i.e., without re-programming, system 20 uses a single verification threshold. See, for example, state 60B in FIG. 2B, which is programmed using a single verification threshold V1A. State 60D in FIG. 2C, too, is programmed using only verification threshold V3A.


Re-programming of a given programming state is performed using a higher verification threshold in order to compensate for interference, and particularly since the cell threshold voltages can only be increased and not decreased. Consider, for example, interference that occurs after the first programming phase and causes an increase in the cell threshold voltage. If the verification threshold of the second programming phase is higher than this increased threshold voltage, then the re-programming operation will be able to compensate for the interference. Otherwise, i.e., if the difference between the verification thresholds in the first and second programming phases is too small, some or even all of the interference may not be compensated for.


In some embodiments, system 20 can implement the selective re-programming scheme described herein by applying both the first and the second programming phases to all the memory cells in the group. In these embodiments, the verification thresholds are increased between the first and the second programming phases only for the programming states in which re-programming is employed. For the programming states in which re-programming is omitted, the verification thresholds are not increased between the first and the second programming phases.


The examples of FIGS. 2B and 2C refer to four-level memory cells. This choice, however, is made purely by way of example. In alternative embodiments, the selective re-programming schemes described herein can be used with memory cells having any desired number of programming states, such as eight-level or sixteen-level memory cells. In alternative embodiments, any other suitable subset of the non-erased programming states can be chosen for re-programming.


Note that the second programming phase in the disclosed techniques does not write additional data into the memory cells beyond the data that was programmed by the first programming phase (i.e., it does not modify the programming states of the memory cells). Rather, the second programming phase shifts the cell threshold voltages within the same programming states in order to compensate for interference. The disclosed two-phase schemes should be distinguished from programming schemes that program additional data into the memory cells (and thus modify the programming states of the memory cells) in subsequent programming stages.


The selective re-programming schemes described herein can be applied by MSP 40, by R/W unit 36 in memory device 24, or jointly by the R/W unit and MSP. The element or elements performing these functions, in hardware and/or in software, are sometimes referred to herein as circuitry that carries out the methods described herein.



FIG. 3 is a flow chart that schematically illustrates a method for selective re-programming of analog memory cells, in accordance with an embodiment of the present invention. The method begins with system 20 initially programming a group of memory cells 32, in the present example a word line that is referred to as a target word line, at a first phase programming step 80. In the first programming phase, system 20 applies an iterative P&V process that uses certain verification thresholds, so as to reach the desired threshold voltage distributions.


After the first programming phase, system 20 programs a group of memory cells that potentially cause interference to the target word line, at an interfering cell programming step 84. In the present example, system 20 programs an adjacent word line, whose memory cells potentially cause interference to the target word line.


After programming the adjacent word line, system 20 selectively re-programs the memory cells of the target word line, at a second phase programming step 88. In the second programming phase, system 20 re-programs only the memory cells that are associated with a predefined partial subset of the non-erased programming states. In the schemes of FIGS. 2B and 2C above, the non-erased programming states comprise states 60B . . . 60D. In the example of FIG. 2B, the partial subset comprises only states 60C and 60D. In the example of FIG. 2C, the partial subset comprises only state 60C. When re-programming the memory cells in a given non-erased programming state, system 20 uses a higher verification threshold than the verification threshold that was used to program these memory cells in the first programming phase.


In the example embodiments described herein, the interference is caused by memory cells in an adjacent word line. This sort of interference is sometimes referred to as vertical interference. The disclosed techniques, however, can be used to compensate for interference that is caused by any other group of memory cells, not necessarily in an adjacent word line. In some embodiments, interference may be caused by memory cells in the same word line as the interference group of memory cells. This sort of interference is sometimes referred to as horizontal interference. For example, in some memory devices a given page is stored in the even-order memory cells of a given word line, and another page is stored in the odd-order memory cells of the same word line. Interference may be caused from the odd-order cells to the even-order cells, or vice versa.


Readout from Partially-Programmed Memory Blocks

In some embodiments, array 28 is partitioned into multiple memory blocks, also referred to as erasure blocks or simply blocks. Each block comprises multiple word lines. When storing data in a given block, system 20 typically programs the word lines of the block in sequential order.


When using the selective re-programming schemes described above, system 20 typically programs the block in the following order:

    • Apply the first programming phase to word line N.
    • Apply the first programming phase to word line N+1.
    • Go back and apply the second programming phase to word line N.
    • Apply the second programming phase to word line N+1.
    • Apply the first programming phase to word line N+2.
    • Continue programming in the same manner, until filling the block.


Other programming orders can also be used. Certain aspects of using different word line programming orders are addressed in PCT International Publication WO 2009/037691, whose disclosure is incorporated herein by reference.


In practice, however, programming of a given block may terminate before all the word lines of the block are programmed. For example, the stored data may not occupy an entire block or an integer number of blocks. As another example, electrical power may be removed from system 20 before all the word lines of the block are programmed. Alternatively, system 20 may not complete the programming of all word lines in the block for any other reason.


In particular, if word line N+1 is not programmed, then the above-described programming sequence may not continue, and word line N may not be re-programmed. In some embodiments, re-programming of word line N is performed immediately after first-phase programming of word line N+1, often in the same programming command from the user's perspective. If programming stops after first-phase programming of word line N, this word line will not be re-programmed.


In other words, when the programming of a certain block stops before all its word lines are programmed, the last-programmed word line in the block may remain programmed using only the first programming phase. Referring to FIG. 2B, for example, the threshold voltages in the last-programmed word line may be distributed according to distributions 64, 72A, 68B and 68C, instead of 64, 72A, 72B and 72C. In particular, threshold voltages of memory cells belonging to the lowest non-erased state (state 60B in the example of FIGS. 2A-2C) may drift below 0V after retention.


Even if word line N+1 were re-programmed at this stage, the re-programming operation would occur when the interference from the next word line is not present, and therefore cannot compensate for the interference. Attempting to read such a word line may cause read errors. In some embodiments, system 20 (typically MSP 40) takes measures to correct the programming of the last-programmed word line in a partially-programmed block.


(In some MLC devices, each word line stores multiple pages, which are not necessarily programmed at the same time. In some embodiments, a word line is considered the last-programmed word line in the block if the next word line is not programmed at all. In other embodiments, a word line is considered the last-programmed word line in the block if the next word line is not fully-programmed with all the possible pages. Further alternatively, the last-programmed word line in the block may be defined as the word line that holds the most-recently-programmed page in the block.)


For example, system 20 may program the word line that follows the last-programmed word line artificially with dummy data. In some embodiments, artificial programming of word line N+1 by MSP 40 causes memory device 24 to re-program word line N. The MSP may program word line N+1 with constant data, with a fixed data pattern, with random data, or with any other suitable data. In an example embodiment, the MSP programs word line N+1 with a pattern that generates peak interference. Such patterns typically perform better in increasing the threshold voltages of word line N above zero. The artificial programming wastes word line N+1, but on the other hand enables re-programming of word line N.



FIG. 4 is a diagram that schematically illustrates a partially-programmed memory block, in accordance with an example embodiment of the present invention. FIG. 4 shows a memory block 90, which comprises multiple word lines denoted WL1, WL2, . . . . A certain range 94, comprising word lines WL1 . . . WLN, is programmed with data. A subsequent range 98, comprising the remaining word lines of the block, is not programmed. In order to cause memory device 24 to re-program the last-programmed word line WLN, MSP artificially programs a word line 102 (WLN+1) with dummy data.


System 20 may decide to program word line N+1 with dummy data in response to various conditions or events. For example, the MSP may measure the time that elapsed since programming of the last page in the block. If the elapsed time exceeds a certain value, the MSP may deduce that the block is likely to remain partially-programmed, and therefore decide to program word line N+1 with dummy data. As another example, the MSP may sense (or receive a notification) that the electrical power supply to system 20 is about to be shut-off. In order to prepare for power removal, the MSP may decide to program word line N+1 with dummy data and cause re-programming of word line N. Further alternatively, the MSP may decide to program word line N+1 with dummy data in response to any other suitable condition or event.


The description above refers to programming word line N+1 with dummy data when word line N is the last word line that is programmed in a partially-programmed block. Alternatively, however, system 20 may decide to program word line N+1 with dummy data upon detecting that the programming of word line N+1 is postponed for any other reason.


In alternative embodiments, the MSP performs certain corrective actions in order to read the last-programmed word line in a partially-programmed block, assuming that this word line did not undergo re-programming. These corrective actions are taken in preparation for reading the word line, sometimes long after programming. For example, the MSP may program the next word line (word line N+1) with dummy data. As explained above, this programming causes the memory device to go back and re-program word line N. In the present example, however, programming of word line N+1 is performed at readout time (possibly following a long retention period) and not at programming time.


As another example of a corrective action, the MSP may apply a readout process that senses the threshold voltages of the memory cells in word line N even if they are negative, i.e., have drifted below 0V. The MSP may use any suitable technique for sensing negative threshold voltages. Example methods are described in U.S. Patent Application Publication 2008/0181001, whose disclosure is incorporated herein by reference. This technique is particularly suitable for scenarios in which some of the cell threshold voltages have drifted below 0V over the retention period that elapsed since programming.


As yet another example of a corrective action, R/W unit may apply one or more programming pulses to word line N, in order to increase the threshold voltages of the memory cells and enable successful readout. Further alternatively, system 20 may apply any other suitable corrective action in order to enable successful readout of the last-programmed word line in a partially-programmed memory block.


The MSP may decide to apply the readout-time corrective actions for various reasons. For example, the MSP may maintain a list of blocks that are currently partially-programmed. If a block appears on this list, the MSP may conclude that corrective action is needed for reading the last-programmed word line of this block. In alternative embodiments, the memory device may provide one or more status flags for each word line, which indicate the programming status of the word line. The MSP may read these flags and determine whether the block has un-programmed word lines. As another example, when preparing to read a given word line, the MSP may attempt to read the next word line in the block and sense whether it is programmed or erased.



FIG. 5 is a flow chart that schematically illustrates a method for data readout from a partially-programmed memory block, in accordance with an embodiment of the present invention. The method begins with MSP 40 storing data in memory device 24, at a storage step 110. After a certain retention period, the MSP prepares to read data from a certain word line WL, at a read preparation step 114. In particular, the MSP checks whether this word line is the last-programmed word line in a partially-programmed block, at a checking step 118. If the word line is not the last-programmed word line in a partially-programmed block, the MSP assumes that the word line has been re-programmed properly. Therefore, the MSP proceeds to read the data from the word line, at a readout step 122. The MSP outputs the read data, at an output step 126.


If, on the other hand, the MSP determines that the word line is the last-programmed word line in a partially-programmed block, it may assume that this word line has not been re-programmed properly. Therefore, the MSP applies a corrective action, at a readout-time correction step 130. The MSP may apply any of the corrective actions described above, for example. After applying the corrective action, the MSP reads the word line, at readout step 122. The MSP then outputs the read data, at output step 126.


It will be appreciated that the embodiments described above are cited by way of example, and that the present invention is not limited to what has been particularly shown and described hereinabove. Rather, the scope of the present invention includes both combinations and sub-combinations of the various features described hereinabove, as well as variations and modifications thereof which would occur to persons skilled in the art upon reading the foregoing description and which are not disclosed in the prior art.

Claims
  • 1. A method for data storage, comprising: in a memory that includes multiple analog memory cells, defining an erased state, a set of non-erased programming states and a partial subset of the non-erased programming states;initially storing data in a first group of the analog memory cells by programming each of at least some of the memory cells in the first group from the erased state to a respective non-erased programming state selected from the set of non-erased programming states;after initially storing the data, programming a second group of the analog memory cells, which potentially cause interference to the first group; andafter programming the second group, selectively re-programming the first group with the data by repeating programming of only the memory cells in the first group whose respective programming states belong to the partial subset,wherein initially storing the data comprises writing respective storage values into the memory cells in the first group and verifying the written storage values using first verification thresholds, and wherein selectively re-programming the first group comprises re-writing the storage values that are associated with the partial subset, and verifying the re-written storage values using second verification thresholds, higher than the corresponding first verification thresholds.
  • 2. The method according to claim 1, wherein programming the memory cells comprises writing respective storage values into the memory cells, and wherein defining the partial subset comprises including in the partial subset at least a non-erased programming state corresponding to a lowest range of the analog values among the non-erased memory states.
  • 3. The method according to claim 1, wherein programming the memory cells comprises writing respective storage values into the memory cells, and wherein defining the partial subset comprises including in the partial subset at least a non-erased programming state corresponding to a highest range of the analog values among the non-erased memory states.
  • 4. A method for data storage, comprising: in a memory that includes multiple analog memory cells, defining an erased state, a set of non-erased programming states and a partial subset of the non-erased programming states;initially storing data in a first group of the analog memory cells by programming each of at least some of the memory cells in the first group from the erased state to a respective non-erased programming state selected from the set of non-erased programming states;after initially storing the data, programming a second group of the analog memory cells, which potentially cause interference to the first group;after programming the second group, selectively re-programming the first group with the data by repeating programming of only the memory cells in the first group whose respective programming states belong to the partial subset; andprogramming the second group with dummy data responsively to detecting that programming of the second group is postponed, so as to cause re-programming of the first group.
  • 5. The method according to claim 4, wherein detecting that the programming of the second group is postponed comprises detecting that a time that elapsed since the programming of the second group exceeds a predefined maximum value.
  • 6. The method according to claim 4, wherein detecting that the programming of the second group is postponed comprises determining that shut-off of electrical power is imminent.
  • 7. A method for data storage, comprising: in a memory that includes multiple analog memory cells, defining an erased state, a set of non-erased programming states and a partial subset of the non-erased programming states;initially storing data in a first group of the analog memory cells by programming each of at least some of the memory cells in the first group from the erased state to a respective non-erased programming state selected from the set of non-erased programming states;after initially storing the data, programming a second group of the analog memory cells, which potentially cause interference to the first group;after programming the second group, selectively re-programming the first group with the data by repeating programming of only the memory cells in the first group whose respective programming states belong to the partial subset; andupon preparing to read the data from the first group, applying a corrective action to the first group responsively to detecting that that the first group was not re-programmed.
  • 8. The method according to claim 7, wherein applying the corrective action comprises programming the second group with dummy data, so as to cause re-programming of the first group.
  • 9. The method according to claim 7, wherein applying the corrective action comprises sensing at least one analog value that was written into a respective analog memory cell in the first group and has become negative.
  • 10. The method according to claim 7, wherein applying the corrective action comprises applying one or more programming pulses to at least one of the memory cells in the first group.
  • 11. Apparatus for data storage, comprising: a memory, which comprises multiple analog memory cells; andcircuitry, which is configured to define an erased state, a set of non-erased programming states and a partial subset of the non-erased programming states, to initially store data in a first group of the analog memory cells by programming each of at least some of the memory cells in the first group from the erased state to a respective non-erased programming state selected from the set of non-erased programming states, to program a second group of the analog memory cells, which potentially cause interference to the first group, after initially storing the data, and, after programming the second group, to selectively re-program the first group with the data by repeating programming of only the memory cells in the first group whose respective programming states belong to the partial subset,wherein the circuitry is configured to initially store the data by writing respective storage values into the memory cells in the first group and verifying the written storage values using first verification thresholds, and to selectively re-program the first group by re-writing the storage values that are associated with the partial subset and verifying the re-written storage values using second verification thresholds, higher than the corresponding first verification thresholds.
  • 12. The apparatus according to claim 11, wherein the circuitry is configured to program the memory cells by writing respective storage values into the memory cells, and wherein the partial subset comprises at least a non-erased programming state corresponding to a lowest range of the analog values among the non-erased memory states.
  • 13. The apparatus according to claim 11, wherein the circuitry is configured to program the memory cells by writing respective storage values into the memory cells, and wherein the partial subset comprises at least a non-erased programming state corresponding to a highest range of the analog values among the non-erased memory states.
  • 14. Apparatus for data storage, comprising: a memory, which comprises multiple analog memory cells; andcircuitry, which is configured to define an erased state, a set of non-erased programming states and a partial subset of the non-erased programming states, to initially store data in a first group of the analog memory cells by programming each of at least some of the memory cells in the first group from the erased state to a respective non-erased programming state selected from the set of non-erased programming states, to program a second group of the analog memory cells, which potentially cause interference to the first group, after initially storing the data, and, after programming the second group, to selectively re-program the first group with the data by repeating programming of only the memory cells in the first group whose respective programming states belong to the partial subset,wherein the circuitry is configured to program the second group with dummy data responsively to detecting that programming of the second group is postponed, so as to cause re-programming of the first group.
  • 15. The apparatus according to claim 14, wherein the circuitry is configured to detect that the programming of the second group is postponed by detecting that a time that elapsed since the programming of the second group exceeds a predefined maximum value.
  • 16. The apparatus according to claim 14, wherein the circuitry is configured to detect that the programming of the second group is postponed by determining that shut-off of electrical power is imminent.
  • 17. Apparatus for data storage, comprising: a memory, which comprises multiple analog memory cells; andcircuitry, which is configured to define an erased state, a set of non-erased programming states and a partial subset of the non-erased programming states, to initially store data in a first group of the analog memory cells by programming each of at least some of the memory cells in the first group from the erased state to a respective non-erased programming state selected from the set of non-erased programming states, to program a second group of the analog memory cells, which potentially cause interference to the first group, after initially storing the data, and, after programming the second group, to selectively re-program the first group with the data by repeating programming of only the memory cells in the first group whose respective programming states belong to the partial subset,wherein, upon preparing to read the data from the first group, the circuitry is configured to apply a corrective action to the first group responsively to detecting that that the first group was not re-programmed.
  • 18. The apparatus according to claim 17, wherein the corrective action comprises programming the second group with dummy data, so as to cause re-programming of the first group.
  • 19. The apparatus according to claim 17, wherein the corrective action comprises sensing at least one analog value that was written into a respective analog memory cell in the first group and has become negative.
  • 20. The apparatus according to claim 17, wherein the corrective action comprises applying one or more programming pulses to at least one of the memory cells in the first group.
CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Patent Application 61/168,604, filed Apr. 12, 2009, whose disclosure is incorporated herein by reference. This application also claims the benefit of U.S. Provisional Patent Application 61/218,080, filed Jun. 18, 2009.

US Referenced Citations (567)
Number Name Date Kind
3668631 Griffith et al. Jun 1972 A
3668632 Oldham Jun 1972 A
4058851 Scheuneman Nov 1977 A
4112502 Scheuneman Sep 1978 A
4394763 Nagano et al. Jul 1983 A
4413339 Riggle et al. Nov 1983 A
4556961 Iwahashi et al. Dec 1985 A
4558431 Satoh Dec 1985 A
4608687 Dutton Aug 1986 A
4654847 Dutton Mar 1987 A
4661929 Aoki et al. Apr 1987 A
4768171 Tada Aug 1988 A
4811285 Walker et al. Mar 1989 A
4899342 Potter et al. Feb 1990 A
4910706 Hyatt Mar 1990 A
4993029 Galbraith et al. Feb 1991 A
5056089 Furuta et al. Oct 1991 A
5077722 Geist et al. Dec 1991 A
5126808 Montalvo et al. Jun 1992 A
5163021 Mehrotra et al. Nov 1992 A
5172338 Mehrotta et al. Dec 1992 A
5182558 Mayo Jan 1993 A
5182752 DeRoo et al. Jan 1993 A
5191584 Anderson Mar 1993 A
5200959 Gross et al. Apr 1993 A
5237535 Mielke et al. Aug 1993 A
5272669 Samachisa et al. Dec 1993 A
5276649 Hoshita et al. Jan 1994 A
5287469 Tsuboi Feb 1994 A
5365484 Cleveland et al. Nov 1994 A
5388064 Khan Feb 1995 A
5416646 Wells et al. May 1995 A
5416782 Wells et al. May 1995 A
5446854 Khalidi et al. Aug 1995 A
5450424 Okugaki et al. Sep 1995 A
5469444 Endoh et al. Nov 1995 A
5473753 Wells et al. Dec 1995 A
5479170 Cauwenberghs et al. Dec 1995 A
5508958 Fazio et al. Apr 1996 A
5519831 Holzhammer May 1996 A
5532962 Auclair et al. Jul 1996 A
5533190 Binford et al. Jul 1996 A
5541886 Hasbun Jul 1996 A
5600677 Citta et al. Feb 1997 A
5638320 Wong et al. Jun 1997 A
5657332 Auclair et al. Aug 1997 A
5675540 Roohparvar Oct 1997 A
5682352 Wong et al. Oct 1997 A
5687114 Khan Nov 1997 A
5696717 Koh Dec 1997 A
5726649 Tamaru et al. Mar 1998 A
5726934 Tran et al. Mar 1998 A
5742752 De Koening Apr 1998 A
5748533 Dunlap et al. May 1998 A
5748534 Dunlap et al. May 1998 A
5751637 Chen et al. May 1998 A
5761402 Kaneda et al. Jun 1998 A
5798966 Keeney Aug 1998 A
5799200 Brant et al. Aug 1998 A
5801985 Roohparvar et al. Sep 1998 A
5838832 Barnsley Nov 1998 A
5860106 Domen et al. Jan 1999 A
5867114 Barbir Feb 1999 A
5867428 Ishii et al. Feb 1999 A
5867429 Chen et al. Feb 1999 A
5877986 Harari et al. Mar 1999 A
5889937 Tamagawa Mar 1999 A
5901089 Korsh et al. May 1999 A
5909449 So et al. Jun 1999 A
5912906 Wu et al. Jun 1999 A
5930167 Lee et al. Jul 1999 A
5937424 Leak et al. Aug 1999 A
5942004 Cappelletti Aug 1999 A
5946716 Karp et al. Aug 1999 A
5969986 Wong et al. Oct 1999 A
5982668 Ishii et al. Nov 1999 A
5991517 Harari et al. Nov 1999 A
5995417 Chen et al. Nov 1999 A
6009014 Hollmer et al. Dec 1999 A
6009016 Ishii et al. Dec 1999 A
6023425 Ishii et al. Feb 2000 A
6034891 Norman Mar 2000 A
6040993 Chen et al. Mar 2000 A
6041430 Yamauchi Mar 2000 A
6073204 Lakhani et al. Jun 2000 A
6101614 Gonzales et al. Aug 2000 A
6128237 Shirley et al. Oct 2000 A
6134140 Tanaka et al. Oct 2000 A
6134143 Norman Oct 2000 A
6134631 Jennings Oct 2000 A
6141261 Patti Oct 2000 A
6151246 So et al. Nov 2000 A
6157573 Ishii et al. Dec 2000 A
6166962 Chen et al. Dec 2000 A
6169691 Pasotti et al. Jan 2001 B1
6178466 Gilbertson et al. Jan 2001 B1
6185134 Tanaka et al. Feb 2001 B1
6209113 Roohparvar Mar 2001 B1
6212654 Lou et al. Apr 2001 B1
6219276 Parker Apr 2001 B1
6219447 Lee et al. Apr 2001 B1
6222762 Guterman et al. Apr 2001 B1
6230233 Lofgren et al. May 2001 B1
6240458 Gilbertson May 2001 B1
6259627 Wong Jul 2001 B1
6275419 Guterman et al. Aug 2001 B1
6278632 Chevallier Aug 2001 B1
6279069 Robinson et al. Aug 2001 B1
6288944 Kawamura Sep 2001 B1
6292394 Cohen et al. Sep 2001 B1
6301151 Engh et al. Oct 2001 B1
6304486 Yano Oct 2001 B1
6307776 So et al. Oct 2001 B1
6314044 Sasaki et al. Nov 2001 B1
6317363 Guterman et al. Nov 2001 B1
6317364 Guterman et al. Nov 2001 B1
6345004 Omura et al. Feb 2002 B1
6360346 Miyauchi et al. Mar 2002 B1
6363008 Wong Mar 2002 B1
6363454 Lakhani et al. Mar 2002 B1
6366496 Torelli et al. Apr 2002 B1
6385092 Ishii et al. May 2002 B1
6392932 Ishii et al. May 2002 B1
6396742 Korsh et al. May 2002 B1
6397364 Barkan May 2002 B1
6405323 Lin et al. Jun 2002 B1
6405342 Lee Jun 2002 B1
6418060 Yang et al. Jul 2002 B1
6442585 Dean et al. Aug 2002 B1
6445602 Kokudo et al. Sep 2002 B1
6452838 Ishii et al. Sep 2002 B1
6456528 Chen Sep 2002 B1
6466476 Wong et al. Oct 2002 B1
6467062 Barkan Oct 2002 B1
6469931 Ban et al. Oct 2002 B1
6480948 Virajpet et al. Nov 2002 B1
6490236 Fukuda et al. Dec 2002 B1
6522580 Chen et al. Feb 2003 B2
6525952 Araki et al. Feb 2003 B2
6532556 Wong et al. Mar 2003 B1
6538922 Khalid et al. Mar 2003 B1
6549464 Tanaka et al. Apr 2003 B2
6553510 Pekny et al. Apr 2003 B1
6558967 Wong May 2003 B1
6560152 Cernea May 2003 B1
6567311 Ishii et al. May 2003 B2
6577539 Iwahashi Jun 2003 B2
6584012 Banks Jun 2003 B2
6615307 Roohparvar Sep 2003 B1
6621739 Gonzales et al. Sep 2003 B2
6640326 Buckingham et al. Oct 2003 B1
6643169 Rudelic et al. Nov 2003 B2
6646913 Micheloni et al. Nov 2003 B2
6678192 Gongwer et al. Jan 2004 B2
6683811 Ishii et al. Jan 2004 B2
6687155 Nagasue Feb 2004 B2
6707748 Lin et al. Mar 2004 B2
6708257 Bao Mar 2004 B2
6714449 Khalid Mar 2004 B2
6717847 Chen Apr 2004 B2
6731557 Beretta May 2004 B2
6732250 Durrant May 2004 B2
6738293 Iwahashi May 2004 B1
6751766 Guterman et al. Jun 2004 B2
6757193 Chen et al. Jun 2004 B2
6774808 Hibbs et al. Aug 2004 B1
6781877 Cernea et al. Aug 2004 B2
6804805 Rub Oct 2004 B2
6807095 Chen et al. Oct 2004 B2
6807101 Ooishi et al. Oct 2004 B2
6809964 Moschopoulos et al. Oct 2004 B2
6819592 Noguchi et al. Nov 2004 B2
6829167 Tu et al. Dec 2004 B2
6845052 Ho et al. Jan 2005 B1
6851018 Wyatt et al. Feb 2005 B2
6851081 Yamamoto Feb 2005 B2
6856546 Guterman et al. Feb 2005 B2
6862218 Guterman et al. Mar 2005 B2
6870767 Rudelic et al. Mar 2005 B2
6870773 Noguchi et al. Mar 2005 B2
6873552 Ishii et al. Mar 2005 B2
6879520 Hosono et al. Apr 2005 B2
6882567 Wong Apr 2005 B1
6894926 Guterman et al. May 2005 B2
6907497 Hosono et al. Jun 2005 B2
6925009 Noguchi et al. Aug 2005 B2
6930925 Guo et al. Aug 2005 B2
6934188 Roohparvar Aug 2005 B2
6937511 Hsu et al. Aug 2005 B2
6958938 Noguchi et al. Oct 2005 B2
6963505 Cohen Nov 2005 B2
6972993 Conley et al. Dec 2005 B2
6988175 Lasser Jan 2006 B2
6992932 Cohen Jan 2006 B2
6999344 Hosono et al. Feb 2006 B2
7002843 Guterman et al. Feb 2006 B2
7006379 Noguchi et al. Feb 2006 B2
7012835 Gonzales et al. Mar 2006 B2
7020017 Chen et al. Mar 2006 B2
7023735 Ban et al. Apr 2006 B2
7031210 Park et al. Apr 2006 B2
7031214 Tran Apr 2006 B2
7031216 You Apr 2006 B2
7039846 Hewitt et al. May 2006 B2
7042766 Wang et al. May 2006 B1
7054193 Wong May 2006 B1
7054199 Lee et al. May 2006 B2
7057958 So et al. Jun 2006 B2
7065147 Ophir et al. Jun 2006 B2
7068539 Guterman et al. Jun 2006 B2
7071849 Zhang Jul 2006 B2
7072222 Ishii et al. Jul 2006 B2
7079555 Baydar et al. Jul 2006 B2
7088615 Guterman et al. Aug 2006 B2
7099194 Tu et al. Aug 2006 B2
7102924 Chen et al. Sep 2006 B2
7113432 Mokhlesi Sep 2006 B2
7130210 Bathul et al. Oct 2006 B2
7139192 Wong Nov 2006 B1
7139198 Guterman et al. Nov 2006 B2
7145805 Ishii et al. Dec 2006 B2
7151692 Wu Dec 2006 B2
7158058 Yu Jan 2007 B1
7170781 So et al. Jan 2007 B2
7170802 Cernea et al. Jan 2007 B2
7173859 Hemink Feb 2007 B2
7177184 Chen Feb 2007 B2
7177195 Gonzales et al. Feb 2007 B2
7177199 Chen et al. Feb 2007 B2
7177200 Ronen et al. Feb 2007 B2
7184338 Nagakawa et al. Feb 2007 B2
7187195 Kim Mar 2007 B2
7187592 Guterman et al. Mar 2007 B2
7190614 Wu Mar 2007 B2
7193898 Cernea Mar 2007 B2
7193921 Choi et al. Mar 2007 B2
7196644 Anderson et al. Mar 2007 B1
7196928 Chen Mar 2007 B2
7196933 Shibata Mar 2007 B2
7197594 Raz et al. Mar 2007 B2
7200062 Kinsely et al. Apr 2007 B2
7210077 Brandenberger et al. Apr 2007 B2
7221592 Nazarian May 2007 B2
7224613 Chen et al. May 2007 B2
7231474 Helms et al. Jun 2007 B1
7231562 Ohlhoff et al. Jun 2007 B2
7243275 Gongwer et al. Jul 2007 B2
7254690 Rao Aug 2007 B2
7254763 Aadsen et al. Aug 2007 B2
7257027 Park Aug 2007 B2
7259987 Chen et al. Aug 2007 B2
7266026 Gongwer et al. Sep 2007 B2
7266069 Chu Sep 2007 B2
7269066 Nguyen et al. Sep 2007 B2
7272757 Stocken Sep 2007 B2
7274611 Roohparvar Sep 2007 B2
7277355 Tanzana Oct 2007 B2
7280398 Lee et al. Oct 2007 B1
7280409 Misumi et al. Oct 2007 B2
7280415 Hwang et al. Oct 2007 B2
7283399 Ishii et al. Oct 2007 B2
7289344 Chen Oct 2007 B2
7301807 Khalid et al. Nov 2007 B2
7301817 Li et al. Nov 2007 B2
7308525 Lasser et al. Dec 2007 B2
7310255 Chan Dec 2007 B2
7310269 Shibata Dec 2007 B2
7310271 Lee Dec 2007 B2
7310272 Mokhesi et al. Dec 2007 B1
7310347 Lasser Dec 2007 B2
7312727 Feng et al. Dec 2007 B1
7321509 Chen et al. Jan 2008 B2
7328384 Kulkarni et al. Feb 2008 B1
7342831 Mokhlesi et al. Mar 2008 B2
7343330 Boesjes et al. Mar 2008 B1
7345924 Nguyen et al. Mar 2008 B2
7345928 Li Mar 2008 B2
7349263 Kim et al. Mar 2008 B2
7356755 Fackenthal Apr 2008 B2
7363420 Lin et al. Apr 2008 B2
7365671 Anderson Apr 2008 B1
7388781 Litsyn et al. Jun 2008 B2
7397697 So et al. Jul 2008 B2
7405974 Yaoi et al. Jul 2008 B2
7405979 Ishii et al. Jul 2008 B2
7408804 Hemink et al. Aug 2008 B2
7408810 Aritome et al. Aug 2008 B2
7409473 Conley et al. Aug 2008 B2
7409623 Baker et al. Aug 2008 B2
7420847 Li Sep 2008 B2
7433231 Aritome Oct 2008 B2
7433697 Karaoguz et al. Oct 2008 B2
7434111 Sugiura et al. Oct 2008 B2
7437498 Ronen Oct 2008 B2
7440324 Mokhlesi Oct 2008 B2
7440331 Hemink Oct 2008 B2
7441067 Gorobetz et al. Oct 2008 B2
7447970 Wu et al. Nov 2008 B2
7450421 Mokhlesi et al. Nov 2008 B2
7453737 Ha Nov 2008 B2
7457163 Hemink Nov 2008 B2
7457897 Lee et al. Nov 2008 B1
7460410 Nagai et al. Dec 2008 B2
7460412 Lee et al. Dec 2008 B2
7466592 Mitani et al. Dec 2008 B2
7468907 Kang et al. Dec 2008 B2
7468911 Lutze et al. Dec 2008 B2
7469049 Feng Dec 2008 B1
7471581 Tran et al. Dec 2008 B2
7483319 Brown Jan 2009 B2
7487329 Hepkin et al. Feb 2009 B2
7487394 Forhan et al. Feb 2009 B2
7492641 Hosono et al. Feb 2009 B2
7508710 Mokhlesi Mar 2009 B2
7526711 Orio Apr 2009 B2
7539061 Lee May 2009 B2
7539062 Doyle May 2009 B2
7551492 Kim Jun 2009 B2
7558109 Brandman et al. Jul 2009 B2
7558839 McGovern Jul 2009 B1
7568135 Cornwell et al. Jul 2009 B2
7570520 Kamei et al. Aug 2009 B2
7574555 Porat et al. Aug 2009 B2
7590002 Mokhlesi et al. Sep 2009 B2
7593259 Kim Sep 2009 B2
7594093 Kancherla Sep 2009 B1
7596707 Vemula Sep 2009 B1
7609787 Jahan et al. Oct 2009 B2
7613043 Cornwell et al. Nov 2009 B2
7616498 Mokhlesi et al. Nov 2009 B2
7619918 Aritome Nov 2009 B2
7631245 Lasser Dec 2009 B2
7633798 Sarin et al. Dec 2009 B2
7633802 Mokhlesi Dec 2009 B2
7639532 Roohparvar et al. Dec 2009 B2
7644347 Alexander et al. Jan 2010 B2
7656734 Thorp et al. Feb 2010 B2
7660158 Aritome Feb 2010 B2
7660183 Ware et al. Feb 2010 B2
7661000 Ueda et al. Feb 2010 B2
7661054 Huffman et al. Feb 2010 B2
7665007 Yang et al. Feb 2010 B2
7680987 Clark et al. Mar 2010 B1
7733712 Walston et al. Jun 2010 B1
7742351 Inoue et al. Jun 2010 B2
7761624 Karamcheti et al. Jul 2010 B2
7797609 Neuman Sep 2010 B2
7810017 Radke Oct 2010 B2
7848149 Gonzales et al. Dec 2010 B2
7869273 Lee et al. Jan 2011 B2
7885119 Li Feb 2011 B2
7904783 Brandman et al. Mar 2011 B2
7924587 Perlmutter et al. Apr 2011 B2
7928497 Yaegashi Apr 2011 B2
7929549 Talbot Apr 2011 B1
7930515 Gupta et al. Apr 2011 B2
7945825 Cohen et al. May 2011 B2
7978516 Olbrich et al. Jul 2011 B2
7995388 Winter et al. Aug 2011 B1
8000135 Perlmutter et al. Aug 2011 B1
8014094 Jin Sep 2011 B1
8037380 Cagno et al. Oct 2011 B2
8040744 Gorobets et al. Oct 2011 B2
8065583 Radke Nov 2011 B2
8085586 Golov et al. Dec 2011 B2
20010002172 Tanaka et al. May 2001 A1
20010006479 Ikehashi et al. Jul 2001 A1
20020038440 Barkan Mar 2002 A1
20020056064 Kidorf et al. May 2002 A1
20020118574 Gongwer et al. Aug 2002 A1
20020133684 Anderson Sep 2002 A1
20020166091 Kidorf et al. Nov 2002 A1
20020174295 Ulrich et al. Nov 2002 A1
20020196510 Hietala et al. Dec 2002 A1
20030002348 Chen et al. Jan 2003 A1
20030103400 Van Tran Jun 2003 A1
20030161183 Tran Aug 2003 A1
20030189856 Cho et al. Oct 2003 A1
20040057265 Mirabel et al. Mar 2004 A1
20040057285 Cernea et al. Mar 2004 A1
20040083333 Chang et al. Apr 2004 A1
20040083334 Chang et al. Apr 2004 A1
20040105311 Cernea et al. Jun 2004 A1
20040114437 Li Jun 2004 A1
20040160842 Fukiage Aug 2004 A1
20040223371 Roohparvar Nov 2004 A1
20050007802 Gerpheide Jan 2005 A1
20050013165 Ban Jan 2005 A1
20050024941 Lasser et al. Feb 2005 A1
20050024978 Ronen Feb 2005 A1
20050030788 Parkinson et al. Feb 2005 A1
20050086574 Fackenthal Apr 2005 A1
20050121436 Kamitani et al. Jun 2005 A1
20050144361 Gonzalez et al. Jun 2005 A1
20050157555 Ono et al. Jul 2005 A1
20050162913 Chen Jul 2005 A1
20050169051 Khalid et al. Aug 2005 A1
20050189649 Maruyama et al. Sep 2005 A1
20050213393 Lasser Sep 2005 A1
20050224853 Ohkawa Oct 2005 A1
20050240745 Iyer et al. Oct 2005 A1
20050243626 Ronen Nov 2005 A1
20060004952 Lasser Jan 2006 A1
20060028875 Avraham et al. Feb 2006 A1
20060028877 Meir Feb 2006 A1
20060101193 Murin May 2006 A1
20060106972 Gorobets et al. May 2006 A1
20060107136 Gongwer et al. May 2006 A1
20060129750 Lee et al. Jun 2006 A1
20060133141 Gorobets Jun 2006 A1
20060156189 Tomlin Jul 2006 A1
20060179334 Brittain et al. Aug 2006 A1
20060190699 Lee Aug 2006 A1
20060203546 Lasser Sep 2006 A1
20060218359 Sanders et al. Sep 2006 A1
20060221692 Chen Oct 2006 A1
20060221705 Hemink et al. Oct 2006 A1
20060221714 Li et al. Oct 2006 A1
20060239077 Park et al. Oct 2006 A1
20060239081 Roohparvar Oct 2006 A1
20060256620 Nguyen et al. Nov 2006 A1
20060256626 Werner et al. Nov 2006 A1
20060256891 Yuan et al. Nov 2006 A1
20060271748 Jain et al. Nov 2006 A1
20060285392 Incarnati et al. Dec 2006 A1
20060285396 Ha Dec 2006 A1
20070006013 Moshayedi et al. Jan 2007 A1
20070019481 Park Jan 2007 A1
20070033581 Tomlin et al. Feb 2007 A1
20070047314 Goda et al. Mar 2007 A1
20070047326 Nguyen et al. Mar 2007 A1
20070050536 Kolokowsky Mar 2007 A1
20070058446 Hwang et al. Mar 2007 A1
20070061502 Lasser et al. Mar 2007 A1
20070067667 Ikeuchi et al. Mar 2007 A1
20070074093 Lasser Mar 2007 A1
20070086239 Litsyn et al. Apr 2007 A1
20070086260 Sinclair Apr 2007 A1
20070089034 Litsyn et al. Apr 2007 A1
20070091677 Lasser et al. Apr 2007 A1
20070091694 Lee et al. Apr 2007 A1
20070103978 Conley et al. May 2007 A1
20070103986 Chen May 2007 A1
20070104211 Opsasnick May 2007 A1
20070109845 Chen May 2007 A1
20070109849 Chen May 2007 A1
20070115726 Cohen et al. May 2007 A1
20070118713 Guterman et al. May 2007 A1
20070143378 Gorobetz Jun 2007 A1
20070143531 Atri Jun 2007 A1
20070159889 Kang et al. Jul 2007 A1
20070159892 Kang et al. Jul 2007 A1
20070159907 Kwak Jul 2007 A1
20070168837 Murin Jul 2007 A1
20070171714 Wu et al. Jul 2007 A1
20070183210 Choi et al. Aug 2007 A1
20070189073 Aritome Aug 2007 A1
20070195602 Fong et al. Aug 2007 A1
20070206426 Mokhlesi Sep 2007 A1
20070208904 Hsieh et al. Sep 2007 A1
20070226599 Motwani Sep 2007 A1
20070236990 Aritome Oct 2007 A1
20070253249 Kang et al. Nov 2007 A1
20070256620 Viggiano et al. Nov 2007 A1
20070263455 Cornwell et al. Nov 2007 A1
20070266232 Rodgers et al. Nov 2007 A1
20070271424 Lee et al. Nov 2007 A1
20070280000 Fujiu et al. Dec 2007 A1
20070291571 Balasundaram Dec 2007 A1
20070297234 Cernea et al. Dec 2007 A1
20080010395 Mylly et al. Jan 2008 A1
20080025121 Tanzawa Jan 2008 A1
20080043535 Roohparvar Feb 2008 A1
20080049504 Kasahara et al. Feb 2008 A1
20080049506 Guterman Feb 2008 A1
20080052446 Lasser et al. Feb 2008 A1
20080055993 Lee Mar 2008 A1
20080080243 Edahiro et al. Apr 2008 A1
20080082730 Kim et al. Apr 2008 A1
20080089123 Chae et al. Apr 2008 A1
20080104309 Cheon et al. May 2008 A1
20080104312 Lasser May 2008 A1
20080109590 Jung et al. May 2008 A1
20080115017 Jacobson May 2008 A1
20080123420 Brandman et al. May 2008 A1
20080123426 Lutze et al. May 2008 A1
20080126686 Sokolov et al. May 2008 A1
20080130341 Shalvi et al. Jun 2008 A1
20080148115 Sokolov et al. Jun 2008 A1
20080151618 Sharon et al. Jun 2008 A1
20080151667 Miu et al. Jun 2008 A1
20080158958 Sokolov et al. Jul 2008 A1
20080181001 Shalvi Jul 2008 A1
20080198650 Shalvi et al. Aug 2008 A1
20080198654 Toda Aug 2008 A1
20080209116 Caulkins Aug 2008 A1
20080209304 Winarski et al. Aug 2008 A1
20080215798 Sharon et al. Sep 2008 A1
20080217598 Sharon et al. Sep 2008 A1
20080219050 Shalvi et al. Sep 2008 A1
20080239093 Easwar et al. Oct 2008 A1
20080239812 Abiko et al. Oct 2008 A1
20080253188 Aritome Oct 2008 A1
20080263262 Sokolov et al. Oct 2008 A1
20080263676 Mo et al. Oct 2008 A1
20080270730 Lasser et al. Oct 2008 A1
20080282106 Shalvi et al. Nov 2008 A1
20080288714 Salomon et al. Nov 2008 A1
20090013233 Radke Jan 2009 A1
20090024905 Shalvi et al. Jan 2009 A1
20090034337 Aritome Feb 2009 A1
20090043831 Antonopoulos et al. Feb 2009 A1
20090043951 Shalvi et al. Feb 2009 A1
20090049234 Oh et al. Feb 2009 A1
20090073762 Lee et al. Mar 2009 A1
20090086542 Lee et al. Apr 2009 A1
20090089484 Chu Apr 2009 A1
20090091979 Shalvi Apr 2009 A1
20090094930 Schwoerer Apr 2009 A1
20090106485 Anholt Apr 2009 A1
20090112949 Ergan et al. Apr 2009 A1
20090132755 Radke May 2009 A1
20090144600 Perlmutter et al. Jun 2009 A1
20090150894 Huang et al. Jun 2009 A1
20090157950 Selinger Jun 2009 A1
20090157964 Kasorla et al. Jun 2009 A1
20090158126 Perlmutter et al. Jun 2009 A1
20090168524 Golov et al. Jul 2009 A1
20090172257 Prins et al. Jul 2009 A1
20090172261 Prins et al. Jul 2009 A1
20090193184 Yu et al. Jul 2009 A1
20090199074 Sommer et al. Aug 2009 A1
20090204824 Lin et al. Aug 2009 A1
20090204872 Yu et al. Aug 2009 A1
20090213653 Perlmutter et al. Aug 2009 A1
20090213654 Perlmutter et al. Aug 2009 A1
20090225595 Kim Sep 2009 A1
20090228761 Perlmutter et al. Sep 2009 A1
20090240872 Perlmutter et al. Sep 2009 A1
20090265509 Klein Oct 2009 A1
20090300227 Nochimowski et al. Dec 2009 A1
20090323412 Mokhlesi et al. Dec 2009 A1
20090327608 Eschmann Dec 2009 A1
20100017650 Chin et al. Jan 2010 A1
20100034022 Dutta et al. Feb 2010 A1
20100057976 Lasser Mar 2010 A1
20100061151 Miwa et al. Mar 2010 A1
20100082883 Chen et al. Apr 2010 A1
20100083247 Kanevsky et al. Apr 2010 A1
20100110580 Takashima May 2010 A1
20100131697 Alrod et al. May 2010 A1
20100142268 Aritome Jun 2010 A1
20100142277 Yang et al. Jun 2010 A1
20100169547 Ou Jul 2010 A1
20100169743 Vogan et al. Jul 2010 A1
20100174847 Paley et al. Jul 2010 A1
20100199150 Shalvi et al. Aug 2010 A1
20100211803 Lablans Aug 2010 A1
20100287217 Borchers et al. Nov 2010 A1
20110010489 Yeh Jan 2011 A1
20110060969 Ramamoorthy et al. Mar 2011 A1
20110066793 Burd Mar 2011 A1
20110075482 Shepard et al. Mar 2011 A1
20110107049 Kwon et al. May 2011 A1
20110149657 Haratsch et al. Jun 2011 A1
20110199823 Bar-Or et al. Aug 2011 A1
20110302354 Miller Dec 2011 A1
Foreign Referenced Citations (43)
Number Date Country
0783754 Jul 1997 EP
1434236 Jun 2004 EP
1605509 Dec 2005 EP
9610256 Apr 1996 WO
9828745 Jul 1998 WO
02100112 Dec 2002 WO
03100791 Dec 2003 WO
2007046084 Apr 2007 WO
2007132452 Nov 2007 WO
2007132453 Nov 2007 WO
2007132456 Nov 2007 WO
2007132457 Nov 2007 WO
2007132458 Nov 2007 WO
2007146010 Dec 2007 WO
2008026203 Mar 2008 WO
2008053472 May 2008 WO
2008053473 May 2008 WO
2008068747 Jun 2008 WO
2008077284 Jul 2008 WO
2008083131 Jul 2008 WO
2008099958 Aug 2008 WO
2008111058 Sep 2008 WO
2008124760 Oct 2008 WO
2008139441 Nov 2008 WO
2009037691 Mar 2009 WO
2009037697 Mar 2009 WO
2009038961 Mar 2009 WO
2009050703 Apr 2009 WO
2009053961 Apr 2009 WO
2009053962 Apr 2009 WO
2009053963 Apr 2009 WO
2009063450 May 2009 WO
2009072100 Jun 2009 WO
2009072101 Jun 2009 WO
2009072102 Jun 2009 WO
2009072103 Jun 2009 WO
2009072104 Jun 2009 WO
2009072105 Jun 2009 WO
2009074978 Jun 2009 WO
2009074979 Jun 2009 WO
2009078006 Jun 2009 WO
2009095902 Aug 2009 WO
2011024015 Mar 2011 WO
Provisional Applications (2)
Number Date Country
61218080 Jun 2009 US
61168604 Apr 2009 US