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Found 4 papers, 0 papers with code
Scalable Polar Code Construction for Successive Cancellation List Decoding: A Graph Neural Network-Based Approach
In addition, when an IMP model trained on a length-128 polar code directly applies to the construction of polar codes with different code rates and blocklengths, simulations show that these polar code constructions deliver comparable performance to the 5G polar codes.
Parallelism versus Latency in Simplified Successive-Cancellation Decoding of Polar Codes
In particular, when the number of processing elements $P$ that can perform SSC decoding operations in parallel is limited, as is the case in practice, the latency of SSC decoding is $O\left(N^{1-1/\mu}+\frac{N}{P}\log_2\log_2\frac{N}{P}\right)$, where $N$ is the block length of the code and $\mu$ is the scaling exponent of the channel.
Information Theory Information Theory
Construction of Polar Codes with Reinforcement Learning
This paper formulates the polar-code construction problem for the successive-cancellation list (SCL) decoder as a maze-traversing game, which can be solved by reinforcement learning techniques.
Decoding Polar Codes with Reinforcement Learning
In this paper we address the problem of selecting factor-graph permutations of polar codes under belief propagation (BP) decoding to significantly improve the error-correction performance of the code.
