Computer Science – Information Theory
Scientific paper
2009-02-26
Computer Science
Information Theory
Scientific paper
We consider transmission of stationary and ergodic sources over non-ergodic composite channels with channel state information at the receiver (CSIR). Previously we introduced alternate capacity definitions to Shannon capacity, including the capacity versus outage and the expected capacity. These generalized definitions relax the constraint of Shannon capacity that all transmitted information must be decoded at the receiver. In this work alternate end-to-end distortion metrics such as the distortion versus outage and the expected distortion are introduced to relax the constraint that a single distortion level has to be maintained for all channel states. For transmission of stationary and ergodic sources over stationary and ergodic channels, the classical Shannon separation theorem enables separate design of source and channel codes and guarantees optimal performance. For generalized communication systems, we show that different end-to-end distortion metrics lead to different conclusions about separation optimality even for the same source and channel models.
Effros Michelle
Goldsmith Andrea
Liang Yifan
No associations
LandOfFree
Source-Channel Coding and Separation for Generalized Communication Systems does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Source-Channel Coding and Separation for Generalized Communication Systems, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Source-Channel Coding and Separation for Generalized Communication Systems will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-254787