This paper presents a variable-length decision-feedback scheme that usestail-biting convolutional codes and the tail-biting Reliability-Output ViterbiAlgoritm (ROVA). Comparing with recent results in finite-blocklengthinformation theory, simulation results for both the BSC and the AWGN channelshow that the decision-feedback scheme using ROVA can surpass the random-codinglower bound on throughput for feedback codes at average blocklengths less than100 symbols. This paper explores ROVA-based decision feedback both withdecoding after every symbol and with decoding limited to a small number ofincrements. The performance of the reliability-based stopping rule with theROVA is compared to retransmission decisions based on CRCs. For shortblocklengths where the latency overhead of the CRC bits is severe, theROVA-based approach delivers superior rates.
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