Symbol-Based Successive Cancellation List Decoder for Polar Codes

Polar codes is promising because they can provably achieve the channel capacity while having an explicit construction method. Lots of work have been done for the bit-based decoding algorithm for polar codes. In this paper, generalized symbol-based successive cancellation (SC) and SC list decoding algorithms are discussed. A symbol-based recursive channel combination relationship is proposed to calculate the symbol-based channel transition probability. This proposed method needs less additions than the maximum-likelihood decoder used by the existing symbol-based polar decoding algorithm. In addition, a two-stage list pruning network is proposed to simplify the list pruning network for the symbol-based SC list decoding algorithm.Comment: Accepted by 2014 IEEE Workshop on Signal Processing Systems (SiPS

A Multi-Kernel Multi-Code Polar Decoder Architecture

Polar codes have received increasing attention in the past decade, and have been selected for the next generation of wireless communication standard. Most research on polar codes has focused on codes constructed from a $2\times2$ polarization matrix, called binary kernel: codes constructed from binary kernels have code lengths that are bound to powers of $2$. A few recent works have proposed construction methods based on multiple kernels of different dimensions, not only binary ones, allowing code lengths different from powers of $2$. In this work, we design and implement the first multi-kernel successive cancellation polar code decoder in literature. It can decode any code constructed with binary and ternary kernels: the architecture, sized for a maximum code length $N_{max}$, is fully flexible in terms of code length, code rate and kernel sequence. The decoder can achieve frequency of more than $1$ GHz in $65$ nm CMOS technology, and a throughput of $615$ Mb/s. The area occupation ranges between $0.11$ mm$^2$ for $N_{max}=256$ and $2.01$ mm$^2$ for $N_{max}=4096$. Implementation results show an unprecedented degree of flexibility: with $N_{max}=4096$, up to $55$ code lengths can be decoded with the same hardware, along with any kernel sequence and code rate

Improved Successive Cancellation Flip Decoding of Polar Codes Based on Error Distribution

Polar codes are a class of linear block codes that provably achieves channel capacity, and have been selected as a coding scheme for $5^{\rm th}$ generation wireless communication standards. Successive-cancellation (SC) decoding of polar codes has mediocre error-correction performance on short to moderate codeword lengths: the SC-Flip decoding algorithm is one of the solutions that have been proposed to overcome this issue. On the other hand, SC-Flip has a higher implementation complexity compared to SC due to the required log-likelihood ratio (LLR) selection and sorting process. Moreover, it requires a high number of iterations to reach good error-correction performance. In this work, we propose two techniques to improve the SC-Flip decoding algorithm for low-rate codes, based on the observation of channel-induced error distributions. The first one is a fixed index selection (FIS) scheme to avoid the substantial implementation cost of LLR selection and sorting with no cost on error-correction performance. The second is an enhanced index selection (EIS) criterion to improve the error-correction performance of SC-Flip decoding. A reduction of $24.6\%$ in the implementation cost of logic elements is estimated with the FIS approach, while simulation results show that EIS leads to an improvement on error-correction performance improvement up to $0.42$ dB at a target FER of $10^{-4}$.Comment: This version of the manuscript corrects an error in the previous ArXiv version, as well as the published version in IEEE Xplore under the same title, which has the DOI:10.1109/WCNCW.2018.8368991. The corrections include all the simulations of SC-Flip-based and SC-Oracle decoders, along with associated comments in-tex