SPRUI30H November 2015 – May 2024 DRA745 , DRA746 , DRA750 , DRA756
Figure 30-4 shows the example block diagram of the Convolutional Encoder in VCP module.
From the parameters, it can derive a trellis diagram that provides a useful representation of the code but whose complexity grows exponentially with the constraint length K. Figure 30-5 shows the trellis diagram of the code from Figure 30-4. The fact that there is a limited number of possible transitions from one state to another makes the code powerful and will be used in the decoding process.
As a maximum-likelihood sequence estimation (MLSE) decoder, the Viterbi decoder identifies the code sequence with the highest probability of matching the transmitted sequence based on the received sequence.
The Viterbi algorithm is composed of a metric update and a traceback routine. The metric update performs a forward recursion in the trellis over a finite number of symbol periods where probabilities are accumulated (the VCP accumulates on 13 bits) for each individual state, based on the current input symbol (branch metric information). The accumulated metric is known as path metrics or state metrics. Once a path through the trellis is identified, the traceback routine performs a backward recursion in the trellis and outputs hard decisions or soft decisions.