2 research outputs found
Performance and Complexity of the Sequential Successive Cancellation Decoding Algorithm
Simulation results illustrating the performance and complexity of the
sequential successive cancellation decoding algorithm are presented for the
case of polar subcodes with Arikan and large kernels, as well as for extended
BCH\ codes. Performance comparison with Arikan PAC and LDPC codes is provided.
Furthermore, complete description of the decoding algorithm is presented
Window Processing of Binary Polarization Kernels
A decoding algorithm for polar (sub)codes with binary
polarization kernels is presented. It is based on the window processing (WP)
method, which exploits the linear relationship of the polarization kernels and
the Arikan matrix. This relationship enables one to compute the kernel input
symbols probabilities by computing the probabilities of several paths in Arikan
successive cancellation (SC) decoder.
In this paper we propose an improved version of WP, which has significantly
lower arithmetic complexity and operates in log-likelihood ratios (LLRs)
domain. The algorithm identifies and reuses common subexpressions arising in
computation of Arikan SC path scores.
The proposed algorithm is applied to kernels of size 16 and 32 with improved
polarization properties. It enables polar (sub)codes with the considered
kernels to simultaneously provide better performance and lower decoding
complexity compared with polar (sub)codes with Arikan kernel.Comment: Final version to appear in IEEE Transactions on Communications. The
source code is available at https://github.com/gtrofimiuk/SCLKernelDecode