Can `finite be more than `infinite in distributed information coding?
S. Sandeep PradhanProfessor
University of Michigan, Department of Electrial Engineering and Computer Science
Thursday, May 22, 2014|
4:00pm - 5:00pm
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About the Event
With the deployment of communication network infrastructures such as packet-switched wireline networks, mobile cellular wireless networks, and distributed sensor networks, it has become important to have a deeper understanding of how information needs to be stored, processed and transmitted efficiently to harness the full potential of these networks. In this talk we look at distributed information processing and coding and report a new coding phenomenon. In particular, we show that for distributed source coding (data compression) involving two or more information sources, as the block-length of the code is increased, the performance improves initially, but plateaues, and then decreases. The best performance is achieved for some finite block-length that depends on the source distribution. To achieve the same performance, the standard Berger-Tung approach requires multi-letterization. This explains why for distributed source coding, Berger-Tung coding scheme is not optimal which was recently established using an alternate argument based on continuity. The new approach leads to new computable characterization of performance limits as well as a new coding strategy. We explore application of this approach in other network communication problems.
Contact: Ann Pace
Sponsor: University of Michigan, Department of Electrical Engineering & Computer Science
Open to: Public