Abstract

We address the problem of joint source-channel maximum a posteriori (MAP) decoding of a Markov sequence which is first encoded by a source code, then encoded by a convolutional code, and sent through a noisy memoryless channel. The existing joint source-channel decoding algorithm for the case of general convolutional encoder has O(M K2 N) time complexity, where M is the length in bits of the information sequence, K is the size of the Markov source alphabet and N is the number of states of the convolutional encoder. We show that for Markov sources satisfying the so-called Monge property the decoding complexity can be decreased to O(M K N) by applying a fast matrix search technique.

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 call

Disclaimer: 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.