Adaptive FEC Selection Using Channel Error Modeling
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Solution Overview
Problem
Current communication systems face challenges in effectively selecting and applying optimal forward error correction (FEC) settings for data communications over varying channel conditions, leading to suboptimal bit error rates and communication efficiency.
Innovation Solution
An apparatus and method that obtain channel characteristic information, such as transfer function, noise, and error modeling data, to select and adjust FEC settings, including puncturing and shortening, based on target bit error rates and receiver capabilities, using models like the N-state Fritchman's Markov-chain model for error modeling and LDPC code evaluation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fixed FEC settings are used for all channel conditions, then device complexity is reduced and ease of operation is improved, but bit error rate performance deteriorates and communication efficiency is reduced
Solution Approach 1:
The patent implements dynamic FEC setting selection by introducing a channel characteristic information obtaining module, a FEC setting selection module, and an indication providing module. The system dynamically adapts FEC parameters (such as code rate, block length, and puncturing patterns) based on real-time channel conditions including signal-to-noise ratio, error patterns, and channel state information. This dynamic adaptation resolves the contradiction by allowing the system to optimize bit error rate performance through condition-specific FEC configurations while maintaining manageable complexity through automated selection algorithms and standardized implementation procedures.
Solution Approach 2:
The patent applies parameter changes by modifying FEC code parameters (code rate, block length, puncturing fraction, shortening length) based on measured channel characteristics. The system evaluates multiple FEC parameter combinations and selects the optimal set that matches current channel conditions. This approach improves reliability by tailoring error correction strength to actual channel quality while the systematic parameter evaluation framework keeps device complexity within acceptable bounds through algorithmic optimization rather than exhaustive configuration.
2Productivity
If dynamic FEC setting adjustment is implemented, then bit error rate performance and communication efficiency are improved, but device complexity increases
Solution Approach 1:
The patent implements feedback mechanisms where the receiver measures channel characteristic information (error patterns, signal quality metrics) and feeds this information back to the transmitter or to a central controller. Based on this feedback, the system automatically adjusts FEC settings for subsequent transmissions. This feedback loop enables continuous optimization of communication efficiency by adapting to changing channel conditions while the automated nature of the feedback processing keeps implementation complexity manageable through standardized protocols and algorithms.
Solution Approach 2:
The patent enables self-service by allowing the communication system to automatically select and configure optimal FEC parameters without requiring manual intervention or complex external control. The system autonomously evaluates channel conditions, compares performance metrics across different FEC configurations, and selects the most appropriate settings. This self-service capability improves communication efficiency through continuous optimization while reducing the operational complexity burden on users and operators.
3Measurement precision
If channel characteristic information is obtained through measurements, then FEC setting accuracy is improved, but measurement time and processing overhead increase
Solution Approach 1:
The patent applies preliminary action by performing channel characteristic measurements and FEC setting evaluations in advance before actual data transmission begins. The system conducts channel sounding, error pattern analysis, and FEC performance prediction during initialization or idle periods. This preliminary characterization allows the system to have accurate channel models ready when transmission starts, improving measurement precision while minimizing time loss during actual communication by having preparations already completed.
Solution Approach 2:
The patent implements partial action by selectively measuring only the most critical channel characteristics relevant to FEC selection rather than进行全面 channel analysis. The system identifies key parameters (such as signal-to-noise ratio, bit error rate, error cluster patterns) that have the greatest impact on FEC performance and focuses measurement resources on these parameters. This selective measurement approach maintains sufficient accuracy for effective FEC setting selection while reducing overall measurement and processing time by excluding less critical parameters.
Data Source
AI summary
Various example embodiments for supporting forward error correction (FEC) in a communication system are presented. Various example embodiments for supporting FEC in a communication system may include selection of a FEC setting (e.g., an amount of puncturing and/or shortening of a FEC code, a FEC code, or the like) for a communication channel from a transmitter to a receiver based on channel characteristic information of the communication channel from the transmitter to the receiver (e.g., transfer function information, channel loss information, noise characteristic information, error information (e.g., bit error rate, error modeling, or the like), or the like). Various example embodiments for supporting FEC in a communication system, based on selection of a FEC setting for a communication channel based on channel characteristic information of the communication channel, may be applied within various types of communication systems, including various types of wired and/or wireless communication systems.