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Improved decoding for Raptor codes with short block-lengths over BIAWGN channel

机译:改进了BIAWGN信道上具有短块长度的Raptor码的解码

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Decoding of Raptor codes consists of decoding of both the LT part and the precode part of the codes. When LT decoding is performed, a scenario may arise where the message passing-based decoding process is unable to provide non-zero log-likelihood ratio (LLR) updates to a fraction of input symbols even if it is mathematically possible to do so. The problem is even more critical for codes with short block-lengths and for smaller overheads. We show that this problem degrades the overall decoding performance of Raptor codes over binary input additive white Gaussian noise (BIAWGN) channel. To combat this problem, the Gauss-Jordan elimination (GJE) is used to assist decoding so that the decoder can continuously provide non-zero LLR updates to all the input symbols connected in the decoding graph. Through simulation results we show that the GJE-assisted method provides significantly better bit error rate (BER) performance of Raptor codes than the traditional method across a wide range of signal to noise ratio (SNR) and transmission overheads.
机译:猛禽代码的解码包括对代码的LT部分和预编码部分的解码。当执行LT解码时,可能会出现以下情况:即使在数学上是可行的,基于消息传递的解码过程也无法提供对输入符号的一部分的非零对数似然比(LLR)更新。对于具有短块长度的代码和较小的开销,该问题甚至更为严重。我们表明,此问题在二进制输入加性高斯白噪声(BIAWGN)通道上会降低Raptor码的整体解码性能。为了解决这个问题,使用高斯-乔丹消除(GJE)辅助解码,以便解码器可以连续地向解码图中连接的所有输入符号提供非零的LLR更新。通过仿真结果,我们证明,在宽范围的信噪比(SNR)和传输开销方面,GJE辅助方法提供的Raptor码误码率(BER)性能明显优于传统方法。

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