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A reduced-complexity successive-cancellation decoding algorithm for polar codes

机译:极坐标的复杂度降低的连续取消解码算法

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Polar codes are codes which provably achieve the capacity of arbitrary symmetric binary-input channels with the complexity of encoders and decoders O(N log N), where N is the code block-length. In the paper, we will focus on a lower complexity implementation of decoding algorithm in the log-likelihood ratio domain. We use the update rule proposed by Gallager in the decoding algorithm of low density parity check (LDPC) codes to replace the node update rules used in successive cancellation (SC) algorithm for polar codes. To simplify the logarithmic and the exponential operations in the Gallager's approach node updates rule for polar codes, we further utilize a piece-wise linear algorithm to approximate the involution transform function, where the piece-wise linear algorithm only uses multiplication and addition operation. It has resulted in a reduced complexity SC decoding algorithm for polar codes. The numerical simulations show that our proposed SC algorithm (Piece-wise approx.) has a lower implementation complexity for polar code decoding, but at the cost about 0.7dB degradation in the bit-error-rate (BER) performance in comparison with the SC algorithm proposed by Arikan when the BER is 10−5. The proposed SC algorithm (Piece-wise approx.) is a tradeoff between the error performance and the decoding complexity.
机译:极码是证明可实现任意对称二进制输入通道容量的编码器,其编码器和解码器的复杂度为O(N log N),其中N为代码块长度。在本文中,我们将重点介绍对数似然比域中较低复杂度的解码算法的实现。我们在低密度奇偶校验(LDPC)码的解码算法中使用Gallager提出的更新规则,以替换在极坐标码的连续消除(SC)算法中使用的节点更新规则。为了简化Gallager逼近极点代码的更新节点更新规则中的对数和指数运算,我们进一步利用分段线性算法来近似对合变换函数,其中分段线性算法仅使用乘法和加法运算。这导致极性码的SC解码算法复杂度降低。数值模拟表明,我们提出的SC算法(逐片近似)对于极性码解码具有较低的实现复杂度,但与SC相比,误码率(BER)性能下降了约0.7dB。 BER为10 −5 时由Arikan提出的算法。所提出的SC算法(逐片近似)是在错误性能和解码复杂度之间的权衡。

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