Throughput improvement on bidirectional Fano algorithm

Recently, we introduced a bidirectional Fano algorithm (BFA) [10] which can achieve much higher decoding throughput compared to the regular unidirectional Fano algorithm (UFA), especially at low signal-to-noise-ratio (SNR). However, the decoding throughput improvement of the conventional BFA with respect to the UFA reduces as the SNR increases and converges to 100% at high SNR. In this paper, two parameters in the BFA, which are known as the number of merged states (NMS) and the threshold increment value Δ, are exploited to improve the decoding throughout of the conventional BFA. The improved BFA can achieve much higher decoding throughput compared to the UFA and the conventional BFA, especially at high SNR. For example at Eb/N0=5dB, the throughput improvement achieved by the improved BFA is about 280% compared to the UFA and about 80% compared to the conventional BFA, and its computational complexity is only 4% of the Viterbi algorithm.

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