Variable Length CLDPC Encoder for Autonomous Vehicle Black Box
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Solution Overview
Problem
Existing storage devices face challenges in efficiently managing different types of data with varying error rates and priorities, as using a common error correction code (ECC) technique increases design and fabrication costs and may not optimize storage efficiency.
Innovation Solution
Implementing a convolutional low-density parity-check (CLDPC) code with a variable parity size, where the parity size is dynamically selected based on the data source and priority, allowing for more efficient allocation of parity bits to higher priority or higher error rate data, and using a pipelined encoding process to generate independently accessible and decodable chunks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a common ECC technique is used for all data, then design cost and fabrication cost are reduced, but storage efficiency and error correction capability are compromised
Solution Approach 1:
The patent implements a dynamic ECC system where the encoder selects different code rates (e.g., 50%, 66%, 75%) based on data priority and error rate characteristics. This allows the system to adaptively adjust error correction capability for different data types, improving both reliability for critical data and storage efficiency for less critical data, while maintaining a single unified encoder design.
Solution Approach 2:
The patent applies different ECC parameters to different portions of data based on their specific requirements. High-priority data receives stronger error correction (lower code rate), while low-priority data uses weaker correction (higher code rate). This localized optimization resolves the contradiction by tailoring error correction strength to local data needs rather than applying a uniform approach.
2Reliability
If different ECC techniques are used for different data types, then error correction capability is optimized, but design cost and fabrication cost increase
Solution Approach 1:
The patent designs a single unified encoder that can operate with multiple code rates (50%, 66%, 75%) by selecting different subsets of parity bits. This multi-functional encoder replaces what would traditionally require multiple separate encoders, achieving optimized error correction for different data types while maintaining a single fabrication design and reducing overall design cost.
Solution Approach 2:
The patent changes the operational parameters of a single encoder by dynamically selecting different code rates and parity bit allocations based on data characteristics. Instead of creating multiple encoders with different structures, the system modifies the operational parameters (code rate, parity size) of one encoder to achieve optimized error correction for various data types, thereby reducing design and fabrication costs.
3Reliability
If more parity bits are allocated to all data, then error correction capability is improved, but storage efficiency decreases
Solution Approach 1:
The patent applies stronger error correction (more parity bits) only to specific high-priority or high-error-rate data portions, while using weaker correction (fewer parity bits) for other data. This localized application of parity bits improves error correction capability where needed while maintaining storage efficiency for the overall data set, resolving the contradiction between reliability and productivity.
Solution Approach 2:
The patent uses partial action by allocating parity bits selectively rather than uniformly to all data. Only the necessary portions of data receive full error correction protection, while other portions receive reduced protection. This partial application of error correction maintains adequate reliability for critical data while improving overall storage efficiency by reducing the total number of parity bits required.
4Productivity
If less parity bits are allocated to all data, then storage efficiency is improved, but error correction capability deteriorates
Solution Approach 1:
The patent dynamically changes the code rate parameter based on data characteristics, selecting from options like 50%, 66%, or 75% code rates. This allows the system to use higher code rates (more efficient storage) for low-priority data while switching to lower code rates (better error correction) for high-priority data, thereby maintaining adequate error correction capability across all data while improving overall storage efficiency.
Data Source
AI summary
A black box recorder for an autonomous vehicle includes an interface configured to receive data from an engine control unit (ECU) device. The data includes first data and second data. The black box recorder further includes an error correction code (ECC) engine configured to determine a first parity size associated with the first data based on a characteristic of the first data and a second parity size associated with the second data based on a characteristic of the second data. The first parity size is different than the second parity size. The ECC engine is further configured to generate a convolutional low-density parity-check (CLDPC) codeword that includes the first data, the second data, first redundancy data associated with the first data, and second redundancy data associated with the second data. The first redundancy data has the first parity size, and the second redundancy data has the second parity size.