Abstract
This paper presents a new latency reduction method for successive-cancellation (SC) decoding of polar codes that performs a frozen-bit checking on the rate-other (R-other) nodes of the Fast Simplified SC (Fast-SSC) pruning tree. The proposed method integrates the Fast-SSC algorithm and the Improved SSC method (frozen-bit checking of the R-other nodes). We apply a recognition-based method to search for as many constituent codes as possible in the decoding tree offline. During decoding, the current node can be decoded directly, if it is a special constituent code; otherwise, the frozen-bit check is executed. If the frozen-bit check condition is satisfied, the operation of the R-other node is the same as that of the rate-one node. In this paper, we prove that the frame error rate (FER) performance of the proposed algorithm is consistent with that of the original SC algorithm. Simulation results show that the proportion of R-other nodes that satisfy the frozen-bit check condition increases with the signal-to-noise-ratio (SNR). Importantly, our proposed method yields a significant reduction in latency compared to those given by existing latency reduction methods. The proposed method solves the problem of high latency for the Improved-SSC method at a high code rate and low SNR, simultaneously.
Highlights
Polar codes [1] have been proven to achieve the symmetric capacity of memoryless channels with a successive-cancellation (SC) decoder
We demonstrate the performance of the proposed method with binary phase shift keying (BPSK) over the additive white Gaussian noise (AWGN) channel
To calculate the ratio of the latency reduction, it was necessary to count the number of codes for each of the constituent code types
Summary
Polar codes [1] have been proven to achieve the symmetric capacity of memoryless channels with a successive-cancellation (SC) decoder. They have low implementation complexity and a very low error-floor [2]. In [4], a simplified SC (SSC) decoder is reported, for which the latency is reduced by classifying three types of constituent code nodes in the decoding tree. These are rate-zero (R-0), rate-one (R-1), and rate-other (R-other) nodes, the leaves of which are all frozen bits, all information bits, and partially frozen and information bits, respectively. The R-0 and R-1 nodes are shown as white and black circles, respectively, and the R-other nodes are represented by squares
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