simulation of mobile hydroacoustic communications in underwater acoustic sensor networks

105 Pages·2015·5.28 MB·English

SIMULATION OF MOBILE HYDROACOUSTIC
COMMUNICATIONS IN UNDERWATER ACOUSTIC SENSOR
NETWORKS
by
Bita Hasannezhad
A thesis submitted to
the Faculty of Graduate Studies and Research
in partial fulfillment of
the requirements for the degree of
MASTER OF COMPUTER SCIENCE
School of Computer Science
at
CARLETON UNIVERSITY
Ottawa, Ontario
September, 2015
(cid:2)c Copyright by Bita Hasannezhad, 2015
Table of Contents
List of Figures v
List of Acronyms vii
Abstract ix
Acknowledgements x
Chapter 1 Introduction 1
1.1 Underwater Communications . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Underwater Acoustic Sensor Networks . . . . . . . . . . . . . . . . . 3
1.2.1 Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 Mobility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.4 Statement of the Problem . . . . . . . . . . . . . . . . . . . . . . . . 5
1.5 Overview of Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.6 Organization of Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Chapter 2 Background 7
2.1 Underwater Acoustic Waves . . . . . . . . . . . . . . . . . . . . . . . 7
2.2 Underwater Communications . . . . . . . . . . . . . . . . . . . . . . . 10
2.2.1 Noise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.2.2 Nyquist’s Formula . . . . . . . . . . . . . . . . . . . . . . . . 12
2.2.3 Shanon’s Formula . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.2.4 Signal Energy per Bit over Noise Power Spectral Density (E /N ) 13
b 0
2.2.5 Attenuation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.2.6 Signal-To-Noise-Ratio . . . . . . . . . . . . . . . . . . . . . . 15
Chapter 3 Related Work 16
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
ii
3.2 Underwater Communications . . . . . . . . . . . . . . . . . . . . . . . 16
3.3 Underwater Sensor Networks . . . . . . . . . . . . . . . . . . . . . . . 19
3.4 Underwater Mobility Models . . . . . . . . . . . . . . . . . . . . . . . 20
3.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
Chapter 4 Underwater Mobility Simulation 25
4.1 Simulation Model Architecture . . . . . . . . . . . . . . . . . . . . . . 25
4.2 Simulation Steps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
4.3 The Integration Process of OMNeT++ and MATLAB . . . . . . . . 27
Chapter 5 Evaluation 28
5.1 Simulation Environment . . . . . . . . . . . . . . . . . . . . . . . . . 28
5.2 Simulation Application . . . . . . . . . . . . . . . . . . . . . . . . . . 29
5.3 Network Configuration . . . . . . . . . . . . . . . . . . . . . . . . . . 30
5.4 Metrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
5.4.1 Collecting Distances . . . . . . . . . . . . . . . . . . . . . . . 30
5.4.2 Bit Error Rate . . . . . . . . . . . . . . . . . . . . . . . . . . 32
5.4.3 Signal Energy per Bit over Noise Power Spectral Density (E /N ) 32
b 0
5.5 Curve Fitting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
5.6 BER as a Function of Distance . . . . . . . . . . . . . . . . . . . . . 33
5.7 BER as a Function of Signal Energy per Bit over Noise Power Spectral
Density . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
Chapter 6 Conclusion 37
6.1 Future Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
Appendix A Simulation Tools and Software Requirements 40
A.1 OMNeT++ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
A.1.1 INET . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
A.1.2 MiXiM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
A.1.3 MiXiM-INET-Bundle . . . . . . . . . . . . . . . . . . . . . . . 41
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A.1.4 Existing Mobility Models in INET and MiXiM . . . . . . . . . 41
A.2 MATLAB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
A.2.1 Using MATLAB Shared Libraries . . . . . . . . . . . . . . . . 43
Appendix B Simulation Implementation 46
B.1 OMNeT++ IDE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
B.1.1 The Project Files . . . . . . . . . . . . . . . . . . . . . . . . . 50
B.2 Implementation Aspects . . . . . . . . . . . . . . . . . . . . . . . . . 52
B.2.1 Core Components . . . . . . . . . . . . . . . . . . . . . . . . . 52
B.2.2 Defining Messages . . . . . . . . . . . . . . . . . . . . . . . . . 59
B.2.3 Parameters and Configurations . . . . . . . . . . . . . . . . . 63
B.2.4 Mobility Modeling . . . . . . . . . . . . . . . . . . . . . . . . 71
B.2.5 The Integration Process of OMNeT++ and MATLAB . . . . 76
B.3 Collecting Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
B.4 Building and Running the Simulation . . . . . . . . . . . . . . . . . . 87
B.4.1 Building the Project . . . . . . . . . . . . . . . . . . . . . . . 87
B.4.2 Running the Simulation . . . . . . . . . . . . . . . . . . . . . 89
Appendix C Decibel and Linear Form 91
Bibliography 92
iv
List of Figures
1.1 Basic hydroacoustic communication model. . . . . . . . . . . . 2
2.1 Longitudinal wave versus transverse (lateral) wave. . . . . . . 8
2.2 Spherical, cylindrical, and planar waves. . . . . . . . . . . . . 9
4.1 Integration of three protocol layers. . . . . . . . . . . . . . . . 25
4.2 Simulation model architecture. . . . . . . . . . . . . . . . . . . 26
5.1 The position of sensors at different time steps: T , T , T , T
1 2 3 4
and T . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
5
5.2 BER as a function of Distance. . . . . . . . . . . . . . . . . . 34
5.3 BER as a function of the E /N ratio. . . . . . . . . . . . . . 36
b 0
A.1 Mobility Models chart in INET. . . . . . . . . . . . . . . . . . 44
A.2 The inheritance diagram of MobilityBase. . . . . . . . . . . . . 45
B.1 OMNeT++ IDE. . . . . . . . . . . . . . . . . . . . . . . . . . 47
B.2 OMNeT++corecomponents: simplemodules,compoundmod-
ule, gates, and channels. . . . . . . . . . . . . . . . . . . . . . 48
B.3 The INI file form-based editor. . . . . . . . . . . . . . . . . . . 50
B.4 The INI file source editor. . . . . . . . . . . . . . . . . . . . . 51
B.5 The inheritance diagram of cSimpleModule. . . . . . . . . . . . 53
B.6 The inheritance diagram of MobilityBase. . . . . . . . . . . . . 75
B.7 The inheritance diagram of MovingMobilityBase and IineSeg-
mentsMobilityBase. . . . . . . . . . . . . . . . . . . . . . . . . 75
B.8 The Edit Configuration Window. . . . . . . . . . . . . . . . . 88
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Dedicated to my beloved spouse, my devoted parents, and my great supervisor
List of Acronyms
AMOUR Autonomous Modular Optical Underwater Robot
AUV Autonomous Underwater Vehicle
AWGN Additive White Gaussian Noise
BEM Basis Expansion Model
CFD Computational Fluid Dynamics
DART Deep-ocean Assessment and Reporting of Tsunamis
DOP Dilution of Precision
DSSS Direct-Sequence Spread Spectrum
FPGA Field-Programmable Gate Array
FSK Frequency-Shift Keyed
GNED Graphical NEtwork Description
GPS Global Positioning System
GSL GNU Scientific Library
IDE Integrated Development Environment
MAC Medium Access Control
MATLAB MATrix LABoratory
MCM Meandering Current Mobility
MCR MATLAB Compiler Runtime
MoBAN Mobility Model for Body Area Networks
NED NEtwork Description
NIC Network Interface Controller
OFDM Orthogonal Frequency Division Multiplexing
OSTBC Orthogonal Space-Time Block Coding
PPP Point-to-Point Protocol
PSK Phase-Shift Keyed
ROV Remotely Operated Vehicle
SBR-DLP Sector-based Routing with Destination Location Prediction
SLMP Scalable Localization Scheme with Mobility Prediction
TCP Transmission Control Protocol
TDMA Time Division Multiple Access
TWS Tsunami Warning System
UDP User Datagram Protocol
UPS Underwater Positioning Systems
UUV Unmanned Underwater Vehicles
UWASN UnderWater Acoustic Sensor Network
UWSN UnderWater Sensor Network
viii
Abstract
Underwater networks are gaining more attention not only because more than 71% of
the Earth’s surface is covered with water, but also due to the growing needs of under-
water communications. Research on underwater communication techniques plays a
mostimportantroleforexploringoceansandotheraquaticenvironments. Underwater
acoustic sensor network is an area of such research. An UnderWater Acoustic Sensor
Network (UWASN) consists of a variable number of self-organized sensors and au-
tonomous vehicles, deployed to monitor and explore the aquatic environment. These
autonomous sensors communicate acoustically. We study the software simulation of
underwater acoustic communications with mobility in UWASNs. Sensors in the stud-
ied networks are mobile due to the marine environments, such as ocean currents. As
a consequence, displacements of sensors affect the UWASNs from different aspects,
such as data transmission and network lifetime. We study and simulate the mobility
of sensors and their communications, moving according to the Meandering Current
Mobility (MCM) model. OMNeT++ and MATLAB are used to model and integrate
three protocol layers of UWASNs: network, link, and physical. The network layer,
simulated using OMNeT++, comprises transmission and reception of packets. The
link layer, also simulated using OMNeT++, includes coding and decoding of frames.
The physical layer is simulated using MATLAB. It contains models of a modulator,
a channel, and a demodulator of underwater acoustic digital data signals. Moreover,
the effects of noise and attenuation on the underwater communications are considered
in the physical layer model. Two major metrics are calculated in this work: Bit Error
Rate (BER) as a function of distance and BER as a function of signal energy per
bit over noise power spectral density (E /N ). Finally, the performance of commu-
b 0
nicating sensors moving according to the MCM model is evaluated. The simulation
results illustrate that the BER for digital data signals is an increasing function of the
distance. An increase in a transmitter-receiver separation distance, affects the data
transmission by increasing the BER. In addition, the BER for digital data signals is
a decreasing function of the E /N ratio. Also, the simulated BERs are higher than
b 0
the theoretical BERs, that only take into account white noise.
ix
Acknowledgements
I would like to express my sincere gratitude to my supervisor Dr. Michel Barbeau for
his guidance and endless support during the completion of this work. I am very grate-
ful for his patience, motivation, and immense knowledge. He is the best professor and
teacher who truly made a difference in my life. However, words are not enough to ex-
pressmygratitudeto him. Besides mysupervisor, I would like tothanktherest ofmy
thesis committee: Professor Evangelos Kranakis, Professor St´ephane Som´e, Professor
Jean-PierreCorriveau,fortheirinsightfulcomments. IexpressmythankstoSt´ephane
Blouin, Joaquin Garcia-Alfaro, and Gimer Cervera. Special thanks to Public Works
and Government Services Canada (PWGSC contract #W7707−145688/001/HAL),
Natural Sciences and Engineering Research Council of Canada (NSERC) for finan-
cial support. Last not least, to my spouce, parents, siblings and friends for all their
patience and support.
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