A novel methods for increasing performance metrics and feasability of compressive sensing based modulated wideband converter

In this thesis, Compressive Sensing based Multi-channel Modulated Wideband Converter (MWC) sampling system which can sample frequency-sparse signals at Sub-Nyquist rate is introduced. CS basics and theorems which constitutes a frequency compression methodology of MWC, incoherence sensing-sparse sampling modeling are detailed. After that, sub-systems of MWC such as random demodulation, analog filtering, signal reconstruction etc… are introduced in order to show the system chain of MWC. The proposed method for increasing dynamic range of MWC is explained and it is showed that the proposed method extraordinarily makes MWC feasible for caption of high and low power signals together. For robustness of MWC, in the thesis, the online calibration method which gives oppurtunities to small, cheap and effective calibration equipments of MWC for field applications. Likewise, MWC full system simulation and results are detailly explained and the simulation results are compared with traditional sampling methods. Finally, the proposed hardware architecture of MWC is introduced and proposed solution methods in the thesis can overcome for hardware non-ideality expected problems, which stem from hardware non-ideality and non-linearity of MWC. As a result, CS based MWC, which has high performance metrics and hardware-applicable is supposed to be substituted to traditional sampling methodology in order to obtain more signal bandwidth by preserving sampling performance metrics.