We consider the concatenation of a convolutional code (CC) with an optimized cyclic redundancy check (CRC) code as a promising paradigm for good short blocklength codes. The resulting CRC-aided convolutional code naturally permits the use of serial list Viterbi decoding (SLVD) to achieve maximum-likelihood decoding. The convolutional encoder of interest is of rate-$1/\omega$ and the convolutional code is either zero-terminated (ZT) or tail-biting (TB). The resulting CRC-aided convolutional code is called a CRC-ZTCC or a CRC-TBCC. To design a good CRC-aided convolutional code, we propose the distance-spectrum optimal (DSO) CRC polynomial. A DSO CRC search algorithm for the TBCC is provided. Our analysis reveals that the complexity of SLVD is governed by the expected list rank which converges to $1$ at high SNR. This allows a good performance to be achieved with a small increase in complexity. In this paper, we focus on transmitting $64$ information bits with a rate-$1/2$ convolutional encoder. For a target error probability $10^{-4}$, simulations show that the best CRC-ZTCC approaches the random-coding union (RCU) bound within $0.4$ dB. Several CRC-TBCCs outperform the RCU bound at moderate SNR values.
翻译:我们认为,以最佳周期冗余检查(CRC)为最佳循环代码(CC)的混凝法是良好的短长代码的一个有希望的范例。因此,由CRC协助的革命代码自然允许使用序列列表Viterbi解码(SLVD)实现最大相似解码。利息的混合编码为1美元/美元/美元/美元。利息的混合编码为零中值(ZT)或尾比值(TB),因此,由CRC协助的共振代码被称为CRC-ZTCC或CRC-TBCC。为设计一个良好的CRC协助的革命代码,我们建议使用远光谱优化(DSO)的序列列表,以实现最大相似的解码。我们的分析表明,SLVD的复杂程度受预期列表等级的制约,该等级在高SNRR(Z-B)之间接近1美元/美元,这样可以以小的复杂程度实现良好的业绩。在本文中,我们着重显示以RC内部汇率显示一个16/2的比例。