الفهرس 
Thesis OrganizationOnly 14 pages are availabe for public view
 |  | from | 174 |  |  |
| | | from | 174 | | |
Abstract
The Underwater Acoustic (UAW) communication has attracted a huge attention during
the last two decades because of the extension of its applications in different domains. It is
getting increased attention in a wide range of applications such as speech transmission between
divers, military, environmental research, coastal surveillance systems, and Autonomous Underwater Vehicle (AUV) operation. However, there are several challenging issues surrounding
such communication systems due to severe channel conditions such as attenuation, ambient
noise, water salinity, temperature, frequency selectivity, multi-path effect with significant tap
delays and Doppler shifts. Because of these challenging issues, UAW communication systems
support low data rates and have poor performance.
The use of Orthogonal Frequency Division Multiplexing (OFDM) as a modulation technique for transmission of acoustic signals in maritime environments is demonstrated in this
study. Unfortunately, the receiver side of OFDM has a Carrier Frequency Offset (CFO) issue.
The challenges connected with the CFO are addressed in this thesis, as well as several equalization algorithms for UAW channels with the purpose of reducing some of these channel fundamental flaws. In addition, in this work, we investigate and enhance the performance of data
transmission using a hybrid underwater and terrestrial system with low-complexity linear
equalization.
The first section provides a description of the underwater channel environment, followed by a presentation of UAW channel modelling, which predicts the underwater channel
impulse response. In the second section, a full overview of an OFDM system in UAW communication is provided. After that, the thesis presents a look at the CFO problem in UAWOFDM systems, as well as a look at various estimation and compensation algorithms. The
thesis describes a proposed CFO estimate algorithm based on Zadoff-Chu (ZC) sequences.
The proposed Zadoff-Chu estimation algorithm has a wide estimation range with lower computational complexity more than that of the other estimation algorithms. The third section
presents a hybrid underwater and terrestrial Single-Input Single-Output (SISO) system with
joint low-complexity equalization and CFO compensation based on banded-matrix approximation using four transformation techniques: Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Sine Transform (DST), and Discrete Wavelet Transform
(DWT).
The proposed JLCRLZF equalizer based on DCT provides a reduction in the simulation
time of about 33% compared to the corresponding conventional one based on DCT. Also, atAcknowledgement
III
BER=10-2, and τ=10 it requires only an extra SNR about 1dB to achieve the same BER compared to the corresponding conventional one based on DCT. The proposed JLCRLZF equalizer based on DST provides a reduction in the simulation time of about 33.2% compared to
the corresponding conventional one based on DCT. Also, at BER=10-2, and τ=10 it requires
only an extra SNR about 0.5 dB to achieve the same BER compared to the corresponding
conventional one based on DST. The proposed JLCRLZF equalizer based on DWT provides
a reduction in the simulation time of about 21 % compared to the corresponding conventional
one based on DCT. Also, at BER=10-2, and τ=10 it requires only an extra SNR about 0.1dB
to achieve the same BER compared to the corresponding conventional one based on DWT.
The fourth section presents a hybrid underwater and terrestrial Multiple-Input MultipleOutput (MIMO) system with a joint low-complexity equalization and CFO compensation algorithm based on banded-matrix approximation to increase the data rate and solve the bandwidth limitation issue. However, at the same time, it increases the complexity of the receivers.
Hence, the utilization of the proposed equalizer will eliminate such problem. Finally, the proposed system performance was tested according to different underwater channel challenges
such as change in the depth, salinity, PH degree and temperature.