Abstract
Maximum likelihood (ML) decoding of short constraint length convolutional codes became feasible with the invention of the Viterbi decoder. Several authors have since upper bounded the performance of ML decoders. A method to calculate the event error probability of an ML decoder for convolutional codes is described.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
