高吞吐量双向Fano解码器的离散时间Markov链模型
A Discrete Time Markov Chain Model for High Throughput Bidirectional Fano Decoders
摘要：
双向Fano算法（BFA）可以实现至少两倍于传统的单向Fano算法（UFA）的解码吞吐量。本文从排队论的角度研究了双向Fano译码。采用离散时间马尔可夫链（DTMC）对具有有限输入缓冲区的BFA解码器进行建模。建立了BFA解码器的输入数据速率、输入缓冲区大小和时钟速度之间的关系。基于DTMC的建模方法可用于设计高吞吐量的并行BFA解码系统。结果表明，在设计高吞吐量的并行BFA解码系统时，BFA解码器的数目和输入缓冲区的大小之间存在一个折衷关系，可以选择最佳的输入缓冲区大小，以使硬件复杂度最小化.
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
