An efficient viterbi decoder
K. S. Arunlal,S. A. Hariprasad +1 more
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TL;DR: A new efficient fangled Viterbi algorithm is proposed in this paper with less complexity and processing time along with 2 bit error correction capabilities.
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Abstract: Convolutional encoding with Viterbi decoding is a good forward error correction technique suitable for channels affected by noise degradation. Fangled Viterbi decoders are variants of Viterbi decoder (VD) which decodes quicker and takes less memory with no error detection capability. Modified fangled takes it a step further by gaining one bit error correction and detection capability at the cost of doubling the computational complexity and processing time. A new efficient fangled Viterbi algorithm is proposed in this paper with less complexity and processing time along with 2 bit error correction capabilities. For 1 bit error correction for 14 bit input data, when compared with Modified fangled Viterbi decoder, computational complexity has come down by 36-43% and processing delay was halved. For a 2 bit error correction, when compared with Modified fangled decoder computational complexity decreased by 2236%.
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References
Error bounds for convolutional codes and an asymptotically optimum decoding algorithm
TL;DR: The upper bound is obtained for a specific probabilistic nonsequential decoding algorithm which is shown to be asymptotically optimum for rates above R_{0} and whose performance bears certain similarities to that of sequential decoding algorithms.
7.6K
A dynamically reconfigurable adaptive viterbi decoder
Sriram Swaminathan,Russell Tessier,Dennis Goeckel,Wayne Burleson +3 more
- 24 Feb 2002
TL;DR: The analysis and implementation of a reduced-complexity decode approach, the adaptive Viterbi algorithm (AVA), is described and the use of dynamic reconfiguration leads to a 20% performance improvement over a static implementation with no loss of decode accuracy.
A reconfigurable Viterbi decoder architecture
K. Chadha,Joseph R. Cavallaro +1 more
- 20 Nov 2001
TL;DR: A novel reconfigurable Viterbi decoder which provides dynamic adaptation to different constraint length and code rate convolutional codes is presented, suitable for use in receiver architectures of the 802.11a wireless local area network and 3G cellular code division multiple access environments.
45
•Proceedings Article
FPGA implementation of Viterbi decoder
S. Hema,V. Suresh Babu,P. Ramesh +2 more
- 16 Feb 2007
TL;DR: It is shown that the larger the constraint length used in a convolutional encoding process, the more powerful the code produced.
41