What is a Viterbi trellis?

A maximum-likelihood detector searches over all possible input sequences using an efficient recursive algorithm known as the Viterbi algorithm. A trellis is used to represent all possible input sequences (see Fig. 14). Each path through the trellis represents a different binary input sequence.

What is the Viterbi algorithm used for?

The Viterbi algorithm is an efficient way to make an inference, or prediction, to the hidden states given the model parameters are optimized, and given the observed data. It is best visualized by a trellis to find out how the path is select from a time step to the next.

What is trellis encoding?

Trellis coded modulation (TCM) combines modulation and encoding processes to achieve better efficiency without increasing the bandwidth. Bandwidth-constrained channels operate in the region R / W > 1, where R = data rate and W = bandwidth available.

What is Viterbi decoding algorithm?

The Viterbi algorithm is the most resource-consuming, but it does the maximum likelihood decoding. It is most often used for decoding convolutional codes with constraint lengths k≤3, but values up to k=15 are used in practice. Viterbi decoding was developed by Andrew J.

What are the advantages of trellis codes?

Trellis coding offers a means of increasing data rate without increasing transmitted bandwidth. This is ideally suited to experimental verification. The gain is achieved with multi-level, multi-phase signalling.

Is Viterbi algorithm optimal?

We show that the Viterbi algorithm runtime is optimal up to subpolynomial factors even when the number of distinct observations is small.

How do you decode convolutional codes?

Viterbi algorithm is utilized to decode the convolutional codes. Again the decoding can be done in two approaches. One approach is called hard decision decoding which uses Hamming distance as a metric to perform the decoding operation, whereas, the soft decision decoding uses Euclidean distance as a metric.