Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 2010.Thesis (Ph. D.) -- Bilkent University, 2010.Includes bibliographical references leaves 144-158.In this thesis, novel array signal processing techniques are proposed for identifi-
cation of multipath communication channels based on cross ambiguity function
(CAF) calculation, swarm intelligence and compressed sensing (CS) theory. First
technique detects the presence of multipath components by integrating CAFs of
each antenna output in the array and iteratively estimates direction-of-arrivals
(DOAs), time delays and Doppler shifts of a known waveform. Second technique
called particle swarm optimization-cross ambiguity function (PSO-CAF) makes
use of the CAF calculation to transform the received antenna array outputs to
delay-Doppler domain for efficient exploitation of the delay-Doppler diversity of
the multipath components. Clusters of multipath components are identified by
using a simple amplitude thresholding in the delay-Doppler domain. PSO is
used to estimate parameters of the multipath components in each cluster. Third
proposed technique combines CS theory, swarm intelligence and CAF computation.
Performance of standard CS formulations based on discretization of the
multipath channel parameter space degrade significantly when the actual channel
parameters deviate from the assumed discrete set of values. To alleviate this
“off-grid”problem, a novel technique by making use of the PSO, that can also be
used in applications other than the multipath channel identification is proposed.
Performances of the proposed techniques are verified both on sythetic and real
data.Güldoğan, Mehmet BurakPh.D
