Packet-Header Conditional Codeword Decoding to Reduce Network Power
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Solution Overview
Problem
Existing network devices consume excessive power due to the decoding of all forward error correction (FEC) codewords, even when only a subset is necessary, leading to inefficient power usage and high energy consumption.
Innovation Solution
Implementing a conditional decoding mechanism that allows network units to selectively decode only the FEC codewords relevant to their traffic, using a conditional decoding window and report system to identify and ignore irrelevant codewords, thereby reducing unnecessary decoding and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all FEC codewords are decoded, then error correction reliability is improved, but power consumption increases
Solution Approach 1:
The patent extracts and processes only the essential information from FEC codewords by reading packet headers to identify relevant codewords before full decoding. This selective extraction approach allows the system to decode only necessary codewords, removing unnecessary decoding operations that consume power while maintaining error correction reliability for relevant data.
Solution Approach 2:
The patent performs preliminary action by reading packet headers and identifying relevant codewords before executing the power-intensive decoding operation. This preliminary filtering step enables the system to prepare a decoding map that guides subsequent selective decoding, ensuring that only necessary codewords are processed while maintaining reliability.
2Use of energy by moving object
If selective decoding is implemented, then power consumption is reduced, but device complexity increases
Solution Approach 1:
The patent segments the decoding process into distinct phases: header reading, relevance identification, decoding map generation, and selective decoding execution. This segmentation allows the complex selective decoding mechanism to be broken down into manageable modular components, making the system easier to implement and maintain while achieving power reduction through selective processing.
Solution Approach 2:
The patent introduces a decoding map as an intermediary data structure that bridges the gap between header analysis and selective decoding. This intermediary component simplifies the overall complexity by providing a clear interface between the identification phase and the decoding phase, making the selective decoding mechanism more manageable and easier to implement.
3Measurement precision
If header-based identification is used, then decoding accuracy is improved, but processing time increases
Solution Approach 1:
The patent extracts only the essential identification information from packet headers without performing complete packet processing. By extracting just the necessary header fields for codeword relevance identification, the system achieves accurate codeword identification while minimizing the time spent on header processing, thus balancing accuracy with processing speed.
Data Source
AI summary
Systems and techniques for conditional codeword decoding using packet headers are described herein. A data payload is received. Parity data is removed from the data payload to generate a codeword dataset. Frames are identified in the codeword dataset. Headers of the frames are evaluated to identify port identifiers for the frames. A conditional decoding map is generated based on the port identifiers. The decoding map is transmitted to a conditional decoder to decode codewords included in the conditional decoding map.