TBCC List Decoding with State Propagation for Faster Trellis Search
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Solution Overview
Problem
Decoding performance in wireless communication systems is limited by the need to evaluate numerous candidate paths in tail-biting convolutional code (TBCC) decoders, leading to inefficiencies and increased decoding time, especially as data rates increase.
Innovation Solution
Propagating state information through trellis stages of the decoder allows for the early disqualification of candidate paths that do not end at the same state, reducing the number of paths that need to be evaluated and thereby improving decoding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all candidate paths are evaluated in TBCC decoder, then decoding accuracy is improved, but decoding complexity and time increase
Solution Approach 1:
The patent applies preliminary action by propagating state information from earlier trellis stages to later stages before complete path evaluation. This allows the decoder to pre-identify and eliminate candidate paths that cannot possibly satisfy the tail-biting constraint (where start and end states must match), thereby reducing the number of paths requiring full evaluation while maintaining decoding accuracy
Solution Approach 2:
The patent implements partial action by evaluating only a subset of candidate paths rather than all possible paths. By using state propagation to identify and discard invalid paths early, the decoder performs partial evaluation sufficient to achieve accurate decoding without the excessive computational burden of exhaustive path evaluation
2Measurement precision
If all candidate paths are evaluated in TBCC decoder, then decoding accuracy is improved, but decoding time increases
Solution Approach 1:
The patent applies preliminary action by propagating state information from earlier trellis stages to later stages before complete path evaluation. This allows the decoder to pre-identify and eliminate candidate paths that cannot possibly satisfy the tail-biting constraint (where start and end states must match), thereby reducing the number of paths requiring full evaluation while maintaining decoding accuracy
Solution Approach 2:
The patent implements skipping by rapidly discarding invalid candidate paths through state propagation checks rather than performing complete evaluation on each path. This allows the decoder to rush through the elimination of impossible paths and focus computational resources only on viable candidates, significantly reducing overall decoding time
3Productivity
If state propagation is implemented, then decoding efficiency is improved, but device complexity increases
Solution Approach 1:
The patent applies universality by designing the state propagation mechanism to serve multiple functions simultaneously: it propagates state information for path evaluation, enables early elimination of invalid paths, and provides constraints for candidate selection. This multi-functionality achieves decoding efficiency improvements without proportionally increasing device complexity
Solution Approach 2:
The patent implements feedback by using propagated state information to continuously guide and refine candidate path selection throughout the decoding process. The state information flows backward from later trellis stages to inform earlier stage decisions, creating a feedback loop that improves decoding efficiency while maintaining manageable complexity through intelligent path pruning
Data Source
AI summary
Certain aspects of the present disclosure relate to techniques and apparatus for enhanced decoding, for example, by providing a multi-phase tail biting convolutional code (TBCC) decoding algorithm. An exemplary method generally includes obtaining, via a wireless medium, a codeword encoded with a TBCC encoding scheme, generating metrics for candidate paths through trellis stages of a decoder, propagating information from at least one of the trellis stages to a later trellis stage, while generating the metrics, selecting a set of the candidate paths based on the propagated information, and decoding the encoded codeword by evaluating the selected set of candidate paths based, at least in part, on the generated metrics. Other aspects, embodiments, and features are claimed and described.