An SCL decoding approach recognizes polar code information sets by expanding paths under frozen and information bit assumptions and selecting the pattern with the best average path metric reliability.
Efficient design and decoding of polar codes
3 Pith papers cite this work. Polarity classification is still indexing.
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A bitwise over-parameterized neural decoder for polar codes is introduced with explicit theoretical bounds on bit and block error rates derived via convergence analysis, local generalization, and Gaussian approximation under AWGN.
The SO-FSCL algorithm extends fast SCL decoding to provide soft outputs for polar codes with major reductions in latency and complexity and near-identical performance to conventional SO-SCL.
citing papers explorer
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Blind Recognition of Polar Codes Using Successive Cancellation List Decoding
An SCL decoding approach recognizes polar code information sets by expanding paths under frozen and information bit assumptions and selecting the pattern with the best average path metric reliability.
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Bitwise Over-Parameterized Neural Polar Decoding: A Theoretical Performance Analysis
A bitwise over-parameterized neural decoder for polar codes is introduced with explicit theoretical bounds on bit and block error rates derived via convergence analysis, local generalization, and Gaussian approximation under AWGN.
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Node-Based Soft-Output Fast Successive Cancellation List Decoding of Polar Codes
The SO-FSCL algorithm extends fast SCL decoding to provide soft outputs for polar codes with major reductions in latency and complexity and near-identical performance to conventional SO-SCL.