Erasure Decoding of Data Blocks Under Shadowing Conditions
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Solution Overview
Problem
Existing error correction techniques in 60 GHz wireless transmission systems are inefficient during unexpected modifications in transmission conditions, such as shadowing, and rely more on reducing error rates rather than correcting errors, which affects the reliability and efficiency of data transmission in synchronous wireless home communications networks.
Innovation Solution
A method that employs a dual-level error correction approach using a Reed Solomon code, where data blocks are prioritized and decoded based on the number of erasures, allowing for efficient decoding even under conditions of shadowing by utilizing multiple transmissions and redundancy information to correct errors effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If MIMO error correction techniques are used, then data transmission reliability is improved under normal conditions, but the system becomes inefficient when unexpected modifications occur in transmission conditions
Solution Approach 1:
The invention segments the error correction process into two distinct phases: a first decoding attempt using conventional MIMO techniques, and a second decoding attempt using a different error correction method. This segmentation allows the system to try the most efficient method first, and only invoke the more resource-intensive method when necessary, thus resolving the contradiction between reliability and adaptability.
Solution Approach 2:
The system dynamically switches between different error correction strategies based on the outcome of the first decoding attempt. If the first attempt succeeds, the system remains in the efficient MIMO mode. If it fails, the system transitions to the alternative error correction method, adapting to the changed transmission conditions while managing resource consumption.
2Reliability
If error correction techniques are implemented to increase reliability, then data transmission reliability is improved, but resource and energy consumption increases
Solution Approach 1:
The invention applies partial error correction action by first attempting decoding with a lightweight MIMO technique. Only when this partial action proves insufficient does the system engage the full error correction capability with the alternative method. This staged approach ensures reliability while minimizing unnecessary energy consumption from full error correction when not needed.
Solution Approach 2:
The system performs self-service by automatically selecting the appropriate error correction method based on decoding success. The first decoding attempt serves itself by potentially resolving errors without requiring the more resource-intensive second method, thus reducing overall energy consumption while maintaining reliability.
3Reliability
If multiple transmissions are performed to ensure efficient reception, then data reception reliability is improved, but transmission time and resource usage increase
Solution Approach 1:
The system performs preliminary error correction using the fast MIMO technique before attempting full decoding. This preliminary action quickly resolves many errors without requiring multiple retransmissions, thus reducing transmission time while maintaining reliability. The alternative error correction method is reserved as a backup rather than being applied routinely.
Data Source
AI summary
When decoding a set of symbols to be decoded, several data blocks representative of the set of symbols to be decoded are received by a decoding node of a communications network. The data blocks are encoded using an error correction code enabling a decoding by erasure. The decoding node performs the following steps: first selecting at least one of the data blocks, first determining first erasures, and checking whether the number of the first erasures is below a given threshold. In a case the check is positive, the decoding node performs first decoding by erasure of the set of symbols to be decoded. In a case the check is negative, the decoding node performs second selecting of at least one of the data blocks, second determining second erasures, and second decoding by erasure of the set of symbols to be decoded from the second erasures.