Probabilistic Coding

4 credits

Convolutional codes, maximum-likelihood (ML) decoding, maximum a-posteriori (MAP) decoding, parallel and serial concatenation architectures, turbo codes, repeat-accumulate (RA) codes, the turbo principle, turbo decoding, graph-based codes, message-passing decoding, low-density parity check codes, threshold analysis, applications. Recommended preparation: ECE 155, Digital Communications Theory, and ECE 159, Data Processing and Information Theory. Prerequisites: ECE 259A with a grade of B– or above; graduate standing.