Adaptive Hybrid ARQ Systems With BCJR Decoding.

We propose and evaluate a novel method of constructing Hybrid Automatic Repeat reQuest (HARQ) systems using the specific properties of the Bahl, Cocke, Jelinek, and Raviv (BCJR) error-correcting algorithm. Because the convergence to the actual codeword is not always guaranteed with the BCJR approach, we propose a system in which two different types of Negative AcKnowledgement messages (NAKs) are employed. The first type is the conventional 1-bit NAK, and the second type specifies retransmission pattern in such a way that the additional parity bits are concentrated on the parts of the code trellis that did not converge to a valid sequence. This is different from the traditional construction of rate-compatible punctured codes (RCPCs), which attempts to obtain the optimal weight distance properties of the codes without taking the convergence properties of the BCJR decoder into account. We demonstrate the performance of the algorithm using RCPCs, and we show that our system outperforms the best known conventional HARQ scheme in terms of the throughput and the average length of retransmitted blocks on practical Gaussian, Rayleigh, and thresholded Rayleigh channels. Moreover, as opposed to other adaptive HARQ algorithms, our solution requires no precomputed lookup tables, and it is robust to changes in the channel characteristics and only introduces moderate increase in feedback link throughput requirements. [ABSTRACT FROM AUTHOR]