Spectrum sensing is the process of identifying the frequencies of a spectrum in which
Signals Of Interest (SOI) are present. In case of continuous time signals present in a
wideband spectrum, the information rate is seen to be much less than that suggested
by its bandwidth and are therefore known as sparse signals. A review of the literature
in [1] and [2] indicates that two of the many techniques used in wideband spectrum
sensing of sparse signals are the Wideband Compressive Radio Receiver (WCRR) for
multitoned signals and the mixed analog digital system for multiband signals. In both
of these techniques even though the signals are sampled at sub-Nyquist rates using
Compressive Sampling (CS), the recovery algorithms used by them are different from
that of CS. In WCRR, a simple correlation function is used for the detection of carrier
frequencies and in a mixed analog digital system, a simple digital algorithm is used for
the identification of frequency support. Through a literature survey, we could identify
that a VHSIC hardware descriptive ModelSim simulation model for wideband spectrum
sensing of multitoned and multiband signals using sub Nyquist sampling does
not exist. If a ModelSim simulation model can be developed using VHDL codes, it can
be easily adapted for FPGA implementation leading to the development of a realistic
hardware prototype for use in Cognitive Radio (CR) communication systems.
The research work reported through this dissertation deals with the implementation of
simulation models of WCRR and mixed analog digital system in ModelSim by making
use of VHDL coding. Algorithms corresponding to different blocks contained in the
conceptual design of these models have been formulated prior to the coding phase.
After the coding phase, analyses of the models are performed using test parameter
choices to ensure that they meet the design requirements. Different parametric choices
are then assigned for the parametric study and a sufficient number of iterations of these
simulations were carried out to verify and validate these models. / MIng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2014
| Identifer | oai:union.ndltd.org:NWUBOLOKA1/oai:dspace.nwu.ac.za:10394/10820 |
| Date | January 2014 |
| Creators | Aziz, Shanu |
| Source Sets | North-West University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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