  The bidirectional Fano algorithm (BFA) can achieve at least two times
decoding throughput compared to the conventional unidirectional Fano algorithm
(UFA). In this paper, bidirectional Fano decoding is examined from the queuing
theory perspective. A Discrete Time Markov Chain (DTMC) is employed to model
the BFA decoder with a finite input buffer. The relationship between the input
data rate, the input buffer size and the clock speed of the BFA decoder is
established. The DTMC based modelling can be used in designing a high
throughput parallel BFA decoding system. It is shown that there is a tradeoff
between the number of BFA decoders and the input buffer size, and an optimal
input buffer size can be chosen to minimize the hardware complexity for a
target decoding throughput in designing a high throughput parallel BFA decoding
system.
