CRC-Aided High-Rate Convolutional Codes With Short Blocklengths for List Decoding
Wenhui Sui, Brendan Towell, Ava Asmani, Hengjie Yang, Holden Grissett, Richard D. Wesel · IEEE Transactions on Communications · 2023
Recently, rate-$1/n$zero-terminated (ZT) and tail-biting (TB) convolutional codes (CCs) with cyclic redundancy check (CRC)-aided list decoding have been shown to closely approach the random-coding union (RCU) bound for short blocklengths. This paper designs CRC polynomials for rate-$(n-1)/n$ZT and TB CCs with short blocklengths. This paper considers both standard rate-$(n-1)/n$CC polynomials and rate-$(n-1)/n$designs resulting from puncturing a rate-$1/2$code. The CRC polynomials are chosen to maximize the minimum distance$d_{\min }$and minimize the number of nearest neighbors$A_{d_{\min }}$. For the standard rate-$(n-1)/n$codes, utilization of the dual trellis proposed by Yamada et al. lowers the complexity of CRC-aided serial list Viterbi decoding (SLVD). CRC-aided SLVD of the TBCCs closely approaches the RCU bound at a blocklength of 128. This paper compares the FER performance (gap to the RCU bound) and complexity of the CRC-aided standard and punctured ZTCCs and TBCCs. This paper also explores the complexity-performance trade-off for three TBCC decoders: a single-trellis approach, a multi-trellis approach, and a modified single-trellis approach with pre-processing using the wrap around Viterbi algorithm.