Multiplexed Compressed Sensing for general frequency sparse signals

Abstract

Compressed Sensing algorithms have provided feasible and reasonably accurate solutions to the problem of reconstructing signals of which only sub-Nyquist number of samples have been acquired. A framework called MOSAICS for acquiring multiple analog channels using limited number of A/D converters by exploiting CS based undersampling has been proposed in our previous work. In this paper we introduce an improvised reconstruction algorithm into the MOSAICS scheme, which overcomes a limitation in MOSAICS, thereby being able to handle a wider class of signals.