الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
Massive multiple-input multiple-output (MIMO) is a breakthrough
technology advancing huge network capacities in multiuser (MU)
scenarios in which a base station, with a large number of antennas,
simultaneously serves multiple users in the same time-frequency resources.
The presented study gives an overall view of the massive MIMO channel
behavior for different situations through the channel matrix singular value
spread (SVS) and users’ channels correlation. As the inter-user spacing or
the number of base station antennas increase, the SVS and inter-user
correlation enhance and the users’ channels can be easily separated. In
addition, and based on dirty-paper coding (DPC), the behavior of these
situations is discussed by computing the sum-rate capacity versus the
number of antennas at the base station in the massive MIMO downlink
channel. Moreover, the proposed model applies the reciprocity theorem to
account for the transmission channel by using the antennas transfer
functions to compute the magnitude and phase of the voltage induced at the
receiving antennas terminals for a given input excitation. Through channel
matrix normalization and singular value decomposition (SVD), the
obtained results are close to those obtained experimentally where as the
number of base station antennas increases, the SVS decreases and the
monotonic sum-rate capacity improves. The ray tracing recipe for an ultrawideband
(UWB)
channel is analytically validated with the experimental
results in the literature and the magnitude and phase of the received voltage
are estimated as a function of frequency in a given environment through
the antenna transfer function and reciprocity theorem. The model is then
extended to a massive MIMO channel to validate its performance metrics,
i.e., the SVS and sum-rate…etc., with the experimental results in the
literature and demonstrate the favorable features of massive MIMO
systems. The setting is a suitable case study for a 100 m ×100 m indoor
environment typically found in a harsh RF industrial environment. The
results also show that using more antennas at the base station improves the
capability of focusing power to a certain user. Besides, via the water-filling
ix
algorithm to demonstrate the optimal transmit power distribution among
users’ channels to achieve maximum mutual information, the results show
that as the number of antennas at the base station side grows up, the
disparity of the power values among users’ channels significantly reduces.
Concerning the duplexing transmission schemes, in time division
duplexing (TDD) mode, the entire bandwidth for both uplink and downlink
is utilized and the propagation channel reciprocity can be used where the
amount of resources needed for pilots only depends on the number of
simultaneously served terminals. However, in frequency division
duplexing (FDD) systems, which are widely deployed because of their
existing spectrum assignments, the uplink and downlink channels are at
different frequencies and thus are not reciprocal where a considerable
amount of feedback overhead is required. One of the main objectives of
the thesis is to exploit the directional spatial correlation for the uplink and
downlink channels, based on the structure of their multipath clusters, to
estimate the downlink channel for an FDD system. The proposed method
uses the spatial correlation between the uplink and downlink where the
clusters are deduced from the uplink channel. Then, the phase of the signal
arriving at the base station is modified to construct the signal departing
from the base station and hence the downlink channel can be estimated.