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A dynamically reconfigurable adaptive viterbi decoder
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Source International Symposium on Field Programmable Gate Arrays archive
Proceedings of the 2002 ACM/SIGDA tenth international symposium on Field-programmable gate arrays table of contents
Monterey, California, USA
Session: Innovative Applications table of contents
Pages: 227 - 236  
Year of Publication: 2002
ISBN:1-58113-452-5
Authors
Sriram Swaminathan  University of Massachusetts, Amherst, MA
Russell Tessier  University of Massachusetts, Amherst, MA
Dennis Goeckel  University of Massachusetts, Amherst, MA
Wayne Burleson  University of Massachusetts, Amherst, MA
Sponsor
SIGDA: ACM Special Interest Group on Design Automation
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 9,   Downloads (12 Months): 57,   Citation Count: 10
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ABSTRACT

The use of error-correcting codes has proven to be an effective way to overcome data corruption in digital communication channels. Although widely-used, the most popular communications decoding algorithm, the Viterbi algorithm, requires an exponential increase in hardware complexity to achieve greater decode accuracy. In this paper, we describe the analysis and implementation of a reduced-complexity decode approach, the adaptive Viterbi algorithm (AVA). Our AVA design is implemented in reconfigurable hardware to take full advantage of algorithm parallelism and specialization. Run-time dynamic reconfiguration is used in response to changing channel noise conditions to achieve improved decoder performance. Implementation parameters for the decoder have been determined through simulation and the decoder has been implemented on a Xilinx XC4036-based PCI board. An overall decode performance improvement of 7.5X for AVA has been achieved versus algorithm implementation on a Celeron-processor based system. The use of dynamic reconfiguration leads to a 20% performance improvement over a static implementation with no loss of decode accuracy.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  10

Collaborative Colleagues:
Sriram Swaminathan: colleagues
Russell Tessier: colleagues
Dennis Goeckel: colleagues
Wayne Burleson: colleagues