The "art of trellis decoding" is computationally hard-for large fields

2002 ◽  
Author(s):  
K. Jain ◽  
I. Mandoiu ◽  
V.V. Vazirani
Keyword(s):  
Trellis Decoding

Hyper-trellis decoding of pixel-domain Wyner-Ziv video coding

2008 ◽  
Vol 18 (5) ◽  
pp. 557-568 ◽  
Author(s):  
Arun Avudainayagam ◽  
John M. Shea ◽  
Dapeng Wu
Keyword(s):  
Video Coding ◽  
Trellis Decoding

Trellis decoding technique for binary-adder channel with M users and its application in LANs

1997 ◽  
Vol 144 (2) ◽  
pp. 65 ◽  
Author(s):  
G. Markarian ◽  
B. Honary ◽  
P. Benachour
Keyword(s):  
Trellis Decoding

Viterbi Decoder in Hardware

2018 ◽  
pp. 6307-6318
Author(s):  
Mário Pereira Véstias
Keyword(s):  
Maximum Likelihood ◽  
Viterbi Algorithm ◽  
Viterbi Decoder ◽  
Maximum Likelihood Decoding ◽  
High Data ◽  
Design Requirements ◽  
Trellis Decoding ◽  
And Performance ◽  
Viterbi Decoders ◽  
Very High

Trellis decoding is used to recover encoded information that was corrupted during transmission over a noisy channel. The Viterbi algorithm is the most well known trellis-based maximum likelihood decoding algorithm. The Viterbi algorithm is executed by a Viterbi decoder. Different hardware solutions may be considered to implement a Viterbi decoder with different design requirements in terms of area, performance, power consumption, among others. The most appropriate solution depends on the metric requirements of the application as well as on the target technology. Properties of the Viterbi algorithm are used to simplify and improve the architecture of the Viterbi decoder. In particular, statistical properties of the Viterbi algorithm are used to design parallel Viterbi decoders with very high data decoding rates. The article focuses on the implementation of a Viterbi decoder in hardware, including optimizations to improve the area and performance.

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