Shared Decoder Statistics for Predictive Error Correction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current data storage systems face limitations in predictive decoding due to individual decoder-based data statistics, leading to 'head of line blocking' scenarios that degrade quality of service (QoS).
Innovation Solution
Implementing a system where each decoder generates statistical data and contributes to a joint statistics pool, allowing codewords to be assigned based on syndrome weight or bit error rate, with the option for local statistics usage in case of significant mismatch.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If individual decoder-based data statistics are used, then each decoder can maintain its own statistical information, but predictive ability is limited resulting in head of line blocking scenarios that degrade QoS
Solution Approach 1:
The patent merges individual decoder statistics into a shared statistics pool that is accessible by all decoders. This allows statistical information to be aggregated across multiple decoders, improving the accuracy and predictive ability of data statistics while eliminating head of line blocking scenarios through better prediction.
2Reliability
If a shared statistics pool is implemented, then predictive ability improves, but system complexity increases due to coordination between multiple decoders
Solution Approach 1:
The patent introduces a shared statistics pool as an intermediary structure that decoders access to obtain statistical information. This mediator approach allows decoders to benefit from aggregated statistics without requiring direct coordination or communication between them, thus improving predictive ability while minimizing system complexity.
3Productivity
If codewords are assigned based on syndrome weight or bit error rate, then decoding efficiency improves, but additional processing overhead is required for assignment decisions
Solution Approach 1:
The patent performs preliminary analysis of codewords by calculating syndrome weight or bit error rate before assignment. This preliminary action allows the system to make informed assignment decisions that optimize decoding efficiency, directing codewords to appropriate decoders based on their error characteristics before the actual decoding process begins.
Data Source
AI summary
A method and apparatus for content aware decoding utilizes a pool of decoders shared data statistics. Each decoder generates statistical data of content it decodes and provides these statistics to a joint statistics pool. As codewords arrive at the decoder pool, the joint statistics are utilized to estimate or predict any corrupted or missing bit values. Codewords may be assigned to a specific decoder, such as a tier 1 decoder, a tier 2 decoder, or a tier 3 decoder, based on a syndrome weight or a bit error rate. The assigned decoder updates the joint statistics pool after processing the codeword. In some embodiments, each decoder may additionally maintain local statistics regarding codewords, and use the local statistics when there is a statistically significant mismatch between the local statistics and the joint statistics pool.