Randomizer Using Dual PRNGs and XOR Logic for NAND Flash Data Scrambling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In nonvolatile memory systems like NAND flash memory, insufficient randomness of data sequences during writing increases error rates and degrades memory cell reliability, particularly due to regularity in pseudorandom sequences used for data scrambling.
Innovation Solution
A randomizer is implemented with two pseudorandom number generators and XOR circuits to generate a new pseudorandom sequence by calculating the exclusive logical sum of their outputs, breaking shift additivity and reducing regularity and bias in the generated sequence, thus enhancing randomness and reducing inter-cell interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single pseudorandom number generator is used for data scrambling, then the device complexity is low, but the randomness of the generated sequence is insufficient leading to increased error rates
Solution Approach 1:
The patent combines multiple pseudorandom number generators (first PRNG and second PRNG) to generate a composite pseudorandom sequence. The first PRNG generates a first pseudorandom sequence, the second PRNG generates a second pseudorandom sequence, and these are merged through XOR operations to create a final pseudorandom sequence with enhanced randomness properties, thereby improving data reliability without excessive complexity increase.
Solution Approach 2:
The patent uses composite pseudorandom sequences formed by combining outputs from different PRNG algorithms (e.g., M-sequence PRNG and Gold-code PRNG). This composite approach leverages the strengths of different generation methods to produce a sequence with superior randomness characteristics compared to any single PRNG alone.
2Reliability
If multiple pseudorandom number generators are used to improve randomness, then the reliability of data reading is improved, but the device complexity increases
Solution Approach 1:
The patent divides the pseudorandom sequence generation function into separate modular components: a first PRNG module, a second PRNG module, and XOR combination modules. This segmentation allows each PRNG to be independently designed and optimized, making the overall complex system more manageable and maintainable while achieving the reliability benefits of multiple generators.
Solution Approach 2:
The patent designs the multiple PRNGs and XOR combination circuits to serve multiple functions: generating pseudorandom sequences for data scrambling, providing interference patterns for memory cell protection, and enabling flexible configuration for different memory architectures. This multi-functionality justifies the increased device complexity by delivering multiple benefits from the same structural additions.
3Device complexity
If pseudorandom sequences with regularity are used for scrambling, then the device complexity is low, but inter-cell interference increases and memory cell reliability degrades
Solution Approach 1:
The patent converts the inherent regularity patterns of individual PRNG outputs into beneficial randomness by combining multiple PRNG sequences through XOR operations. The regularities of individual sequences interact to cancel out patterns and enhance overall randomness, thereby reducing inter-cell interference while maintaining manageable device complexity.
Data Source
AI summary
A randomizer includes a first pseudorandom number generator, a second pseudorandom number generator, and a first logic circuit configured to output a pseudorandom sequence by carrying out an operation on a pseudorandom sequence generated by the first pseudorandom number generator and a pseudorandom sequence generated by the second pseudorandom number generator, and a second logic circuit configured to randomize a data string input to the randomizer based on the pseudorandom sequence output by the first logic circuit.