Convolutional Codes & Viterbi Decoder

This lecture covers Convolutional Codes, which transform information sequences into coded symbols with memory, and the Viterbi Algorithm for low-complexity decoding. It explains the state diagram and trellis diagram representations, the branch metric computation, and the state metric updates. The Viterbi Algorithm is detailed, including branch and state metric computations, and the traceback process. The lecture also discusses the high-level architecture of the Viterbi Algorithm, state metric computation using Add Compare Select (ACS), and examples of forward and backward iterations. It concludes with insights on limiting the survivor path length in large code blocks.