Data Block Error Identification Using Search Trellis Metrics

Solution Overview

Problem

Existing data processing systems face computational intensity when identifying the most likely set of error events to correct errors in data blocks due to the large number of possible combinations across multiple data blocks.

Innovation Solution

The method involves determining a search trellis with branches corresponding to data blocks and error events, computing branch metrics based on correction flags and error events, and performing a search to minimize total branch metrics, thereby efficiently identifying the most likely error events for correction.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If an exhaustive search through all possible combinations of error events is performed to identify the most likely set of error events that will correct data errors, then the accuracy of error correction is improved, but the computational complexity and processing time increase significantly

Engineering Contradiction:

Improveaccuracy of error correctionVSAvoidcomputational complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent segments the exhaustive search problem into manageable components by organizing error events into groups based on their patterns and metrics. Instead of searching through all possible combinations simultaneously, the method divides the search space into smaller subsets that can be evaluated independently and then combined, significantly reducing computational complexity while maintaining correction accuracy.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent performs preliminary actions by pre-calculating and storing error event metrics and patterns before the actual error correction process. Error events are pre-processed and organized into data structures that facilitate efficient querying and comparison during correction, avoiding redundant computations and enabling faster identification of the most likely error events.

Inventive Principle:

Principle #10Preliminary action

2Measurement precision

If an exhaustive search through all possible combinations of error events is performed to identify the most likely set of error events that will correct data errors, then the accuracy of error correction is improved, but the processing time increases significantly

Engineering Contradiction:

Improveaccuracy of error correctionVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent segments the exhaustive search problem into manageable components by organizing error events into groups based on their patterns and metrics. Instead of searching through all possible combinations simultaneously, the method divides the search space into smaller subsets that can be evaluated independently and then combined, significantly reducing computational complexity while maintaining correction accuracy.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent performs preliminary actions by pre-calculating and storing error event metrics and patterns before the actual error correction process. Error events are pre-processed and organized into data structures that facilitate efficient querying and comparison during correction, avoiding redundant computations and enabling faster identification of the most likely error events.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS8145983B1Methods and apparatus for identification of likely errors in data blocks

Publication Date: 2012.03.27 MARVELL ASIA PTE LTD

AI summary

Methods and apparatus are provided for processing a plurality of data blocks. In accordance with embodiments of the invention, a correction flag for each of the data blocks can be received, along with information on at least one error event for each of the data blocks. Using this received information, a search trellis corresponding to the data blocks can be determined. Determining the search trellis can include determining a plurality of branches and computing a branch metric for each of the branches. A search on the search trellis can be performed to identify at most one error event for each data block, where the search is based on the branch metrics.