Memory sub-banking scheme for high throughput turbo decoder

Mayank Tiwari, Yuming Zhu, Chaitali Chakrabarti

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


Turbo codes have revolutionized the world of coding theory with their superior performance. However, the implementation of these codes is both computationally and memory-intensive. Recently, the sliding window (SW) approach has been proposed as an effective means of reducing the decoding delay as well as the memory requirements of Turbo implementations. In this paper we present a sub-banked implementation of the SW-based approach that achieves high throughput, low decoding latency and reduced memory energy consumption. Our contributions include derivation of the optimal memory sub-banked structure for different SW configurations, study of the relationship between memory size, energy consumption and decoding latency for different SW configurations and study of the effect of number of sub-banks on the throughput and decoding latency of a given SW configuration. The theoretical study has been validated by SimpleScalar for a rate 1/3 MAP decoder.

Original languageEnglish (US)
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
StatePublished - 2004
EventProceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing - Montreal, Que, Canada
Duration: May 17 2004May 21 2004


OtherProceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing
CityMontreal, Que

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Signal Processing
  • Acoustics and Ultrasonics


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