English

Variable-length Convolutional Coding for Short Blocklengths with Decision Feedback

Information Theory 2016-11-17 v2 math.IT

Abstract

This paper presents a variable-length decision-feedback scheme that uses tail-biting convolutional codes and the tail-biting Reliability-Output Viterbi Algoritm (ROVA). Comparing with recent results in finite-blocklength information theory, simulation results for both the BSC and the AWGN channel show that the decision-feedback scheme using ROVA can surpass the random-coding lower bound on throughput for feedback codes at average blocklengths less than 100 symbols. This paper explores ROVA-based decision feedback both with decoding after every symbol and with decoding limited to a small number of increments. The performance of the reliability-based stopping rule with the ROVA is compared to retransmission decisions based on CRCs. For short blocklengths where the latency overhead of the CRC bits is severe, the ROVA-based approach delivers superior rates.

Cite

@article{arxiv.1410.8023,
  title  = {Variable-length Convolutional Coding for Short Blocklengths with Decision Feedback},
  author = {Adam R. Williamson and Tsung-Yi Chen and Richard D. Wesel},
  journal= {arXiv preprint arXiv:1410.8023},
  year   = {2016}
}

Comments

Accepted for publication to IEEE Transactions on Communications. 15 single-spaced, double-column pages; 8 figures; 3 tables

R2 v1 2026-06-22T06:40:22.435Z