Adaptive Memory Descrambling Using Entropy-Based Seed Selection
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Solution Overview
Problem
Existing memory devices face errors during data retrieval due to incorrect scrambling seeds obtained from decoded data, leading to incorrect descrambling and decoding, especially when the scrambling seeds have errors.
Innovation Solution
An adaptive decoding controller is used to extract and evaluate candidate scrambling seeds from encoded data without decoding it, selecting the seed based on entropy metrics to ensure accurate descrambling and decoding, thereby reducing error rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the scrambling seed is obtained from decoded data, then the descrambling process can be performed, but errors in the scrambling seed lead to incorrect data retrieval
Solution Approach 1:
The patent applies preliminary action by extracting candidate scrambling seeds from the encoded data before decoding occurs. This allows the system to prepare multiple potential scrambling seeds in advance, evaluate them using entropy metrics, and select the correct one before the actual descrambling process, thereby preventing error propagation from incorrect seed selection.
Solution Approach 2:
The patent implements feedback by using entropy analysis to evaluate the quality of candidate scrambling seeds. The system calculates entropy metrics for each candidate seed, uses this feedback to identify the correct scrambling seed, and then proceeds with descrambling only after verification, creating a closed-loop validation mechanism that ensures accuracy.
2Measurement precision
If multiple candidate scrambling seeds are evaluated using entropy metrics, then the correct scrambling seed can be selected accurately, but the decoding process becomes more complex
Solution Approach 1:
The patent applies partial action by evaluating only a limited set of candidate scrambling seeds extracted from specific portions of the encoded data, rather than exhaustively searching all possible seeds. The entropy metric evaluation is applied selectively to these candidates, providing sufficient accuracy without requiring complete enumeration of all possibilities.
3Reliability
If the scrambling seed is obtained before decoding, then errors in decoding do not affect seed accuracy, but the process requires additional steps
Solution Approach 1:
The patent merges the scrambling seed extraction process with the encoded data itself, obtaining candidate seeds directly from the encoded bitstream without requiring separate seed storage or transmission. This integration allows the system to extract multiple candidates from different positions in the encoded data, combining information from the data structure itself to enable accurate seed selection.
Data Source
AI summary
Disclosed herein is a memory device and a method of descrambling and decoding encoded data. In one aspect, encoded data is received. A scrambling seed is obtained from the encoded data prior to decoding the encoded data. The encoded data is descrambled according to the scrambling seed, and the descrambled data is decoded. The descrambled data may be decoded according to statistics of the descrambled data.