Implementing the Viterbi algorithm on general-purpose parallel computers

Michael D. Alston; Paul M. Chau; Kar-Ming Cheung

doi:10.1117/12.130924

30 November 1992 Implementing the Viterbi algorithm on general-purpose parallel computers

Michael D. Alston, Paul M. Chau, Kar-Ming Cheung

Proceedings Volume 1770, Advanced Signal Processing Algorithms, Architectures, and Implementations III; (1992) https://doi.org/10.1117/12.130924
Event: San Diego '92, 1992, San Diego, CA, United States

Abstract

The Viterbi algorithm (VA) for decoding convolutionally encoded data has historically been implemented on special-purpose digital electronic hardware. For short/moderate (K equals 3 to 9) constraint length codes, a primary design goal is to maximize the decoded bit rate while minimizing circuit area. In recent years, a number of special-purpose architectures based upon shuffle-exchange networks, cube-connected cycles, ring-based networks, systolic arrays, or programmable processors have been designed for efficient implementation of the VA at these and longer constraint lengths. However, at the same time, the performance:cost ratio of high- end general-purpose computing machines has been improving dramatically. Recognizing the substantial investment in time and resources required to design and build an ASIC-based decoder for long (K equals 10 to 15) constraint length codes, the feasibility of implementation of the VA as a background process on a readily available general-purpose parallel processing machine deserves exploration. We consider the limitations and benefits of a Viterbi decoder for long constraint length codes implemented in software on a general-purpose parallel processing machine.

Citation Download Citation

Michael D. Alston, Paul M. Chau, and Kar-Ming Cheung "Implementing the Viterbi algorithm on general-purpose parallel computers", Proc. SPIE 1770, Advanced Signal Processing Algorithms, Architectures, and Implementations III, (30 November 1992); https://doi.org/10.1117/12.130924

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available