Media Access Control Processor Power Reduction via Conditional Decoding
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Solution Overview
Problem
Current network processing systems, particularly those using LDPC-FEC, face significant power consumption challenges due to the high processing workload and power requirements for decoding data, especially in optical network units (ONUs).
Innovation Solution
The implementation of a conditional decoding window (CDW) mechanism in ONUs, which allows only relevant FEC codewords destined for the ONU to be decoded, while pausing or ignoring irrelevant codewords, thereby reducing overall power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all FEC codewords are decoded in optical network units, then data error detection and correction capability is maintained, but power consumption increases significantly
Solution Approach 1:
The patent segments the FEC decoding process by introducing conditional decoding windows that selectively decode only specific codewords based on relevance criteria. Instead of uniformly decoding all codewords, the system divides them into relevant and irrelevant groups, applying decoding operations only to the relevant subset, thereby reducing overall power consumption while maintaining error detection capability for important data.
Solution Approach 2:
The patent implements partial action by decoding only a portion of the total codewords rather than all codewords. The conditional decoding window mechanism allows the system to perform decoding operations on selected codewords that meet specific criteria, leaving other codewords undecoded. This partial approach reduces processing workload and power consumption while still providing sufficient error detection and correction for the most critical data segments.
2Use of energy by moving object
If conditional decoding window mechanism is implemented to reduce power consumption, then energy efficiency improves, but processing complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-defining and signaling the boundaries and parameters of conditional decoding windows before the actual decoding process. The system prepares the decoding strategy in advance by establishing which codewords will be decoded based on predetermined criteria, allowing the main processing unit to efficiently execute the decoding without real-time decision-making complexity. This preliminary setup reduces the computational burden during active decoding operations.
Data Source
AI summary
Systems and techniques for forward error correction decode processing power reduction are described herein. A capacity of a network slice is determined for a user network interface (UNI) based on a subset of forward error correction (FEC) codewords to be decoded by the media access control processor. A number of decoder cores is calculated to decode the capacity of the network slice. A utilization value is determined for a decoder core. A decoder utilization value is calculated for the decoder cores using the utilization value a number of decoding iterations. A non-decoding media access control processor utilization value is obtained for the network slice. A geometry is calculated for the media access control processor using the number of decoder cores, the decoder utilization value, and the non-decoding media access control processor utilization value. A media access control processor manufacturing specification data is generated based on the calculated geometry.