AG Kommunikationstheorie

Thema:

Introduction to compressed sensing and its application to network coding

Abstract:

Compressed sensing is a new paradigm for signal sampling which enables to recover a sparse signal from much fewer measurements than the size of the signal. It allows in numerous applications to trade-off costly sensors for cheap computation time. It can be used for example in medical imaging (x-ray) or in mobile communication (spectrum sensing).

In this talk we will first present the fundamentals of compressed sensing, show how it can be used practically and explain its performance bounds. In a second part we will apply compressed sensing to network coding and prove that it enables to increase the capacity of the network when the transmitted signal is sparse.



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