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.
List decoding of polar codes
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
citation-role summary
method 1
citation-polarity summary
years
2026 5roles
method 1polarities
use method 1representative citing papers
Feedback enables genie-aided SC decoding and flexible thresholds that significantly improve finite-length performance of polar codes, with a new characterization of the error event distribution.
Polar and convolutional coset codes with two-step class identification and decoding provide spectrally efficient unequal message protection for short blocks without custom code design.
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
-
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.
-
On Polar Coding with Feedback
Feedback enables genie-aided SC decoding and flexible thresholds that significantly improve finite-length performance of polar codes, with a new characterization of the error event distribution.
-
Polar and Convolutional Codes for the Unequal Message Protection Problem
Polar and convolutional coset codes with two-step class identification and decoding provide spectrally efficient unequal message protection for short blocks without custom code design.
-
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.
-
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.