The majority of the work on underwater communication has mainly been based on acoustic communication. Acoustic communication faces many known problems, such as high propagation delays, very low data rates, and highly environment-dependent channel behavior.
In this presentation, to address these shortcomings, magnetic induction is introduced as a possible communication paradigm for underwater applications. Accordingly, all research challenges in this regard are explained. Fundamentally different from the conventional underwater communication paradigm, which relies on EM, acoustic, or optical waves, the underwater MI communications rely on the time varying magnetic field to covey information between the transmitting and receiving parties. MI-based underwater communications exhibit several unique and promising features such as
negligible signal propagation delay, predictable and constant channel behavior, sufficiently long communication range with high bandwidth, as well as silent and stealth underwater operations.
A detailed note on the Fourier Transform of the Unit Step Signal. This text explains the various approaches used in the evaluation of the Fourier transform of the unit step signal.
This presentation discusses the hardware details of 8051 microcontroller, viz. the pin description, reset circuit, port architectures, oscillator circuit and machine cycle etc in 8051
A second important technique in error-control coding is that of convolutional coding . In this type of coding the encoder output is not in block form, but is in the form of an encoded
sequence generated from an input information sequence.
convolutional encoding is designed so that its decoding can be performed in some structured and simplified way. One of the design assumptions that simplifies decoding
is linearity of the code. For this reason, linear convolutional codes are preferred. The source alphabet is taken from a finite field or Galois field GF(q).
Convolution coding is a popular error-correcting coding method used in digital communications.
The convolution operation encodes some redundant information into the transmitted signal, thereby improving the data capacity of the channel.
Convolution Encoding with Viterbi decoding is a powerful FEC technique that is particularly suited to a channel in which the transmitted signal is corrupted mainly by AWGN.
It is simple and has good performance with low implementation cost.
CONTROL SYSTEMS PPT ON A LEAD COMPENSATOR CHARACTERISTICS USING BODE DIAGRAM ...sanjay kumar pediredla
A LEAD COMPENSATOR CHARACTERISTICS USING BODE DIAGRAM FOR MAXIMUM OF 50 DEG PHASE ANGLE
THIS PPT IS SO USEFUL FOR THE ENGINEERING STUDENTS FOR CONTROL SYSTEMS STUDENTS AND THIS PPT ALSO CONTAINS A MATLAB CODING FOR THE LEAD COMPENSATOR AND THE RESULTS ARE ALSO PLOTTED IN THAT PPT AND THE PROBLEM CAN ALSO BE SOLVED BY USING THE DATA IN PPT AND IT IS SO USEFUL PPT
A detailed note on the Fourier Transform of the Unit Step Signal. This text explains the various approaches used in the evaluation of the Fourier transform of the unit step signal.
This presentation discusses the hardware details of 8051 microcontroller, viz. the pin description, reset circuit, port architectures, oscillator circuit and machine cycle etc in 8051
A second important technique in error-control coding is that of convolutional coding . In this type of coding the encoder output is not in block form, but is in the form of an encoded
sequence generated from an input information sequence.
convolutional encoding is designed so that its decoding can be performed in some structured and simplified way. One of the design assumptions that simplifies decoding
is linearity of the code. For this reason, linear convolutional codes are preferred. The source alphabet is taken from a finite field or Galois field GF(q).
Convolution coding is a popular error-correcting coding method used in digital communications.
The convolution operation encodes some redundant information into the transmitted signal, thereby improving the data capacity of the channel.
Convolution Encoding with Viterbi decoding is a powerful FEC technique that is particularly suited to a channel in which the transmitted signal is corrupted mainly by AWGN.
It is simple and has good performance with low implementation cost.
CONTROL SYSTEMS PPT ON A LEAD COMPENSATOR CHARACTERISTICS USING BODE DIAGRAM ...sanjay kumar pediredla
A LEAD COMPENSATOR CHARACTERISTICS USING BODE DIAGRAM FOR MAXIMUM OF 50 DEG PHASE ANGLE
THIS PPT IS SO USEFUL FOR THE ENGINEERING STUDENTS FOR CONTROL SYSTEMS STUDENTS AND THIS PPT ALSO CONTAINS A MATLAB CODING FOR THE LEAD COMPENSATOR AND THE RESULTS ARE ALSO PLOTTED IN THAT PPT AND THE PROBLEM CAN ALSO BE SOLVED BY USING THE DATA IN PPT AND IT IS SO USEFUL PPT
The presentation gives basic insight into Information Theory, Entropies, various binary channels, and error conditions. It explains principles, derivations and problems in very easy and detailed manner with examples.
It gives how states are representing in various canonical forms and how it it is different from transfer function approach. and finally test the system controllability and observability by kalman's test
The internet technology is divided into many stages and one of them is 1G. The topics cover up in this : history, explanation, flaws and future version.
Deployment Analysis of TDM/WDM Single Fiber PON with Colourless ONU operating...Josep Fabrega
A single-fiber full-duplex hybrid TDM/WDM-PON is demonstrated to operate at 2.5/1.25 Gbps rates, with RSOA ONU. It achieves high power budget (GPON compliant) at a distances higher than 20km, and serves up to 1280 users.
The presentation gives basic insight into Information Theory, Entropies, various binary channels, and error conditions. It explains principles, derivations and problems in very easy and detailed manner with examples.
It gives how states are representing in various canonical forms and how it it is different from transfer function approach. and finally test the system controllability and observability by kalman's test
The internet technology is divided into many stages and one of them is 1G. The topics cover up in this : history, explanation, flaws and future version.
Deployment Analysis of TDM/WDM Single Fiber PON with Colourless ONU operating...Josep Fabrega
A single-fiber full-duplex hybrid TDM/WDM-PON is demonstrated to operate at 2.5/1.25 Gbps rates, with RSOA ONU. It achieves high power budget (GPON compliant) at a distances higher than 20km, and serves up to 1280 users.
The attached narrated power point presentation attempts to explain the various digital communication techniques as applied to optical communications. The material will be useful for KTU final year B tech students who prepare for the subject EC 405, Optical Communications.
Polymer Waveguide Based Optical Interconnects for High-Speed On-Board Communi...Jian Chen
Multimode polymer waveguides constitute an attractive technology for use in board-level optical interconnects:
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- Bandwidth performance of multimode WGs can be enhanced using refractive index engineering, launch conditions, waveguide layout, etc.;
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Automated Traffic Density Detection and Speed MonitoringBharat Biyani
Designed and proposed an RF system to detect speed and traffic density with a RADAR unit in remote areas and to provide real-time monitoring of the traffic density data with a satellite link. Based on calculated parameters, required RF components from real vendors were identified. The system model is then simulated with the obtained parameters in AWR Virtual System Simulator and analyzed nominal and worst case cascaded gain, noise figure, P1dB and OIP3. The general deviation expected in these parameters was determined by performing yield analysis.
Institute: NIMO Project Management Institute
This training course includes 35 hours of instruction (Professional Development Units - PDU’s) related to
project management, program management, project risk, project scheduling or agile project management.
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6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
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Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
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2. Structure of Presentation
2
Introduction
• Working principle
of MI
communications
• Comparison of
different UWC
technologies
Basic MI
communications
using Single-Hop
mode
• System modelling
• Path loss
Basic MI
communications
using Multi-Hop-
Relay mode
• System modelling
Numerical analysis
of different UWC
technologies
• Path loss
• Bit Error Rate
(BER)
*UWC=Under Water Communications
*MI= Magnetic Induction
3. Working Principle of MI Based Communications
3
Coil Distance, r
Transmitter coil
Receiver coil
Coil radius, a
I
Induced emf
Magnetic FieldTransmitter coil
4. Working Principle of MI Based Communications
4
Antenna Antenna Antenna Antenna
Receiver ReceiverTransmitter Transmitter
Processor Processor
r
Near Field
Propagation
Communication Transceiver Communication Transceiver
5. Under Water Communications Challenges
5
Example of long path
Ocean Floor
Ambient noise
Biological noise
Transmitter
Receiver
Direct path
Bottom reflection
Surface reflection
Ocean surface
6. Comparison of Different UWC Technologies
6
Communications
paradigm
Propagation
speed
Data rates Communications
ranges
Stealth
operation
Channel dependency
Magnetic Induction
Electromagnetic
Acoustic
Optical
~Mb/s
1500 m/s
3.33 ×107 m/s
3.33 ×107 m/s
3.33 ×107 m/s ~Mb/s
~Mb/s
~kb/s
10-100 m
≤ 10 m
10-500 m
~ km
Conductivity
Conductivity, multipath
Light scattering, line of
sight communications,
ambient light noise
Multipath, doppler effect,
temperature, pressure,
salinity, environmental
sound noise
Visible
Audible
7. Promising features of Under Water MI Communications
77
Negligible signal propagation delay
Frequency offsets due to the Doppler effects are
negligible
Predictable and constant channel response
Reduced path loss due to Multi-Hop-Relay mode
Sufficiently large communications range with high
data rates
Cost effective, easily-deployable and flexible antenna
structures
8. Applications of Under Water MI Communications
8
Collaborative sensing and tracking with under water swarming
robots
Stealth and real time under water surveillance and patrol
Disaster assessment, search, and rescue in a cluttered under
water environment
Telemetry and remote control from under water or surface
equipment
Diver to diver, diver to shore or diver to vessel communications
10. Structure of Presentation
10
Introduction
• Working principle
of MI
communications
• Comparison of
different UWC
technologies
Basic MI
communications
using Single-Hop
mode
• System modelling
• Path loss
Basic MI
communications
using Multi-Hop-
Relay mode
• System modelling
Numerical analysis
of different UWC
technologies
• Path loss
• Bit Error Rate
(BER)
11. Basic MI Communications Using Single-Hop Mode
11
Received signal
Inductive link
Transmitted signal Receiver coilTransmitter coil
12. System Modelling-MI Single-Hop Mode
12
M =
μ ∙ NTX ∙ aTX
2
∙ NRX ∙ aRX
2
∙ π
2 (aTX
2
+ r2)3
L =
μ ∙ N2
∙ A
l
R =
N ∙ 2π ∙ a ∙ ρ
A
μ= Magnetic permeability in Hm-1 = μr. μ0
NTX, NRX= Number of turns of the
transmitter and receiver coils
ρ = Electrical resistivity in Ω⋅m
A= Cross sectional area of the copper
wire = π ∙ (d/2) 2
d= Diameter of the copper wire in m
aTX aRX
r
14. Path Loss-MI Single-Hop Mode
To maximize PRX
Assuming ZTX = 0
Zin
2
= Complex conjugate of the input impedance at port 2
Zin
(2)
=
V2
I2
= Z22 −
Z12
2
ZTX +Z11
Angular frequency,
ω = 2 ∙ π ∙ f
Path loss of magnetic induction
in fresh water
ZL = Zin
2
ZL = RRX +
ω2∙M2∙RTX
RTX
2 +ω2∙LTX
2 + j(
ω3∙M2∙LTX
RTX
2 +ω2∙LTX
2 − ωLRX)
PLMI = −10 log
RL ∙ ω2
∙ M2
RTX RL + RRX
2 + RTX XL + ω ∙ LRX
2
Attenuation (inverse of skin depth)
α =
1
δ
= π ∙ f ∙ μ ∙ σ
σ = Electrical conductivity of sea
Attenuation in sea water
Total path loss in sea water
PLα = 20 log eα∙r
= 8.69α ∙ r
PLSW = PLMI + PLα14
15. Structure of Presentation
15
Introduction
• Working principle
of MI
communications
• Comparison of
different UWC
technologies
Basic MI
communications
using Single-Hop
mode
• System modelling
• Path loss
Basic MI
communications
using Multi-Hop-
Relay mode
• System modelling
Numerical analysis
of different UWC
technologies
• Path loss
• Bit Error Rate
(BER)
16. System Modelling-Multi-Hop Relay Mode
16
r r r
Transmitter Coil Receiver CoilRelay Coil Relay Coil Relay Coil
Antenna Antenna Antenna Antenna Antenna
Transmitter ReceiverRelay node Relay node Relay node
r rr
V1 V2
ZTX
ZL
I1 I2
17. Structure of Presentation
17
Introduction
• Working principle
of MI
communications
• Comparison of
different UWC
technologies
Basic MI
communications
using Single-Hop
mode
• System modelling
• Path loss
Basic MI
communications
using Multi-Hop-
Relay mode
• System modelling
Numerical analysis
of different UWC
technologies
• Path loss
• Bit Error Rate
(BER)
18. Numerical Analysis-Different UWC Technologies
18
MI system
EM wave system
Acoustic system
500 Hz
1.5 m
1.5 m
6 m
90 m
4000 m
8 kHz
1000
1000
0.01724 ohm∙mm2/m
1.45 mm (AWG 15)
1.65 mm2
400 MHz
4 S/m
0.01 S/m
716∙85×10-12 F/m
Operating frequency: f (both fresh and sea water)
Operating frequency: f
Operating frequency: f
Radius of transmitter coil: aTX
Cross-sectional area for a copper wire of 1.45 mm: A
Length(solenoid): l
Number of turns (receiver Coil): NRX
Radius of receiver coil: aRX
Number of turns (transmitter Coil): NTX
Electrical resistivity of copper: ρ
Sea water conductivity, Ϭ
Diameter of the copper wire: d
Fresh water conductivity, Ϭ
Dielectric permittivity, ε
Deep water depth
Shallow water depth
20. Link Budget and Bit Error Rate
Signal-to-Noise Ratio (SNR)
at the receiver: (general)
Signal-to-Noise Ratio (SNR)
at the Receiver: (Acoustic)
SNR=SL−PL−NL+DI≥DT
SNR=PT – PL −PN
PT = Transmission power (dBm)
PL = Path loss for different
transmission media
PN = Noise power (dBm)
SL= Source level (dB)
= 10 log (
𝐼𝑡
0.67∙10−8)
NL= Noise level (dB)
DI = Directive index
DT= Detection threshold
pb
16QAM
=
3
8
erfc (
4
10
∙
Eb
N0
)
The BER for the modulation
scheme 16-QAM
Eb
N0
= SNR ∙
BN
R
BN= Noise bandwidth
R= Data rate
20
0
23. Bit Error Rate-MI Multi-Hop Relay Mode
23
BitErrorRate
Distance in m
24. Conclusion on MI Communications System
24
Lower path loss and BER for short transmission
ranges (up to 10 m)
Path loss is higher in sea water due to electrical
conductivity
Multi-Hop-Relay mode reduces path loss and
extends communications ranges
Superior BER performance and potential for
enormous applications
26. Path Loss-Multi-Hop Relay Mode
26
PTX(r0) = Re(Z11a) |I1|2
Transmitted Power for a Small Distance, r0 Received Power
PRX=Re(ZL) ∙ g=a k=b
g=n−1 k=n
|λgk|2
∙
|Z21n|2
|ZL+Z22n|2
∙ | I1|2
λgk =
Z21G
γgkPath Loss= −10 log
PRX(r)
PTX(r)
27. Numerical Analysis-Different UWC Technologies
27
MI system-Single-Hop mode
EM wave system
Acoustic system
1.6 m
1.6 m
6 m
90 m
4000 m
8 kHz
950
950
0.01724 ohm∙mm2/m
1.45 mm (AWG 15)
1.65 mm2
400 MHz
4 S/m
0.01 S/m
716∙85×10-12 F/m
Operating frequency: f (both fresh and sea water)
Operating frequency: f
Operating frequency: f
Radius of transmitter coil: aTX
Cross-sectional area for a copper wire of 1.45 mm: A
Length(solenoid): l
Number of turns (receiver Coil): NRX
Radius of receiver coil: aRX
Number of turns (transmitter Coil): NTX
Electrical resistivity of copper: ρ
Sea water conductivity, Ϭ
Diameter of the copper wire: d
Fresh water conductivity, Ϭ
Dielectric permittivity, ε
Deep water depth
Shallow water depth
2.3 kHz (fresh water), 500 Hz (sea water)
28. Bit Error Rate-Single-Hop Mode
28
BitErrorRate
Distance in m
PT= -60.01 dBm, PN=-74.81 dBm and R=7 kbps (assumption)
29. Under Water Communications Challenges
29
Harsh Under water environment
Limited Bandwidth
Extended Multipath
Rapid time variation
Severe Fading
Noise
Ambient
Physical
Processes
Human Activities
Biological
Aquatic Animal
Activities
In magneto inductive communications system, the distance of coils is usually larger, and transferred power drops off sharply to a very small fraction, so the coils should be asymmetric, which the transmitter coil being heavy and large, and the receiver coils being light and small. We are working in conductive media such as water, where the electrical conductivity sigma leads to energy dissipation of the material because of the eddy current which generates strong secondary field. Electrical conductivity gives a measure of a material’s ability to conduct an electric current.
1. The principle of magnetic induction is the current in the primary coil (transmitter) generates magnetic field then the magnetic field induces current in to secondary coil (receiver). Magnetic flux is a general term associated with a field that is bound by a certain area. So, magnetic flux is any area that has a magnetic field passing through it. Electron has a magnetic dipole moment. It's close to an electric dipole moment because it generates a magnetic field that behaves similarly to an electric dipole field (falls off like 1 /r3). The lowest order moment possible in magnetism that obeys Maxwell's equations is the dipole moment.
Magnetic induction (MI) is a promising physical layer technique for UWCNs that is not affected by multipath propagation and fading.
1. Important applications for shallow water such as diver-to-diver voice and text communications can be developed using this technique.
Real-time data transfer between AUVs, or AUVs and underwater sensors, Stealth and real-time underwater surveillance and patrol
Telemetry and remote control from underwater or surface equipment is also possible, since the water to air boundary is crossed by the magnetic component of an electromagnetic signal with relatively low attenuation.
Communication between AUVs and docking stations, or control of AUVs from surface vessels and shore is helpful in environmental and military applications suchas mine countermeasures during coastal reconnaissance missions.
Diver to shore or vessel communication are other interesting applications.
Collaborative sensing and tracking with underwater swarming robots.
(A) Collaborative sensing and tracking with underwater swarming robots: Fish behavior shows an astonishing ability to efficiently find food sources and favorable habitat regions through schooling behavior, that is, rapid orienting and synchronized moving of a group of fish with respect to environmental gradients, such as local variations in chemical stimuli such as odorant plumes or other environmental properties such as phytoplankton density.
Underwater MI communications can enable a swarm of underwater robots (e.g., agile robotic fish) to mimic this collective and synchronized intelligence of fish by exchanging control and environmental gradient information with guaranteed delay bounds.
In such a way, swarming robots can collaboratively track sources of pollution, toxicity, and biohazard with high convergence speed and accuracy.
(B) Stealth and real-time underwater surveillance and patrol: The high bandwidth along with the constant and reliable channel conditions achieved by underwater MI communications can enable real-time underwater surveillance, which demands high-speed delivery of a large volume of multimedia contents (e.g., audio, video, and scalar data).
In addition, the stealth and silent features of underwater MI communications allow underwater surveillance to be carried out in stealth mode.
Shortcomings of Acoustic communication:
-High propagation delay as because the sound speed equals 1500 m/s
-Very low data rates, low bandwidth
-highly environment dependent channel behavior (salinity, pressure, temperature gradient)
-prevalent Doppler effect
-refraction in deep water
-reflection in shallow water (water depth<100m)
-High Bit Error Rate
-In extreme cases, the sound speed variations with depth cause refraction of signals and result in a spatially-variant channel. As a result, shadow zones are formed, which cause significant bit error rates and loss of connectivity .
Shortcomings of Optical communication:
In underwater optical channels, the source and destination nodes should form a directional link in a close proximity with high precision in pointing the narrow laser beams . Furthermore, the multiple scattering of light results in dispersion and creates the inter symbol interference(ISI)
-Multiple scattering ,limiting the application of optical signals to short-range distances.-the transmission of optical signals requires a direct line of sight, which is another challenge for mobile underwater vehicles and robots.
For fibre optic systems, bit errors mainly result from imperfections in the components used to make the link. These include the optical driver, receiver, connectors and the fibre itself. Bit errors may also be introduced as a result of optical dispersion and attenuation that may be present. Also noise may be introduced in the optical receiver itself. Typically these may be photodiodes and amplifiers which need to respond to very small changes and as a result there may be high noise levels present.
Shortcomings of Electromagnetic Signal: In underwater RF communication, electromagnetic waves propagate over very short distances due to high levels of attenuation increasing with conductivity and frequency. Large antenna size, low operation frequencies and high transmission power are necessary.
-suffer from high path loss, which limits their communication range.
-To increase the EM range, a large antenna is used for low frequencies, but this is unsuitable for small underwater vehicles.
Due to the high velocity of MI propagation, frequency offsets due to the Doppler effect are negligible.
-This extremely high propagation speed of MI waves can significantly improve the delay performance of underwater communications, while providing facilities to design and implement underwater networking protocols, such as medium access control (MAC) and routing, and the underwater networking services (e.g., localization). Moreover, physical layer synchronization among wireless devices becomes simple and reliable due to the negligible delay and stable channel.
Comparison between MI and Acoustic : Another very promising low-cost, robust and efficient method is the magneto-inductive (MI) wireless communication Unlike acoustic channel, MI channel does not have high latency and it mitigates the challenges of dynamical conditions and high power consumptions by using simple, low cost and low power coils. The channel conditions depend on the permeability of the communication medium and a uniform channel is created in air, seawater and most types of soil and rock due to almost the same permeability. Furthermore, the feasible communication distance dramatically increases with waveguides .
Negligible signal propagation delay: Different from acoustic waves that propagate at a speed of 1500 m/s under water, MI waves propagate at aspeed of 3.33 × 107 m/s under water. This extremely high propagation speed of MI waves can significantly improve the delay performance of underwater communications, while facilitating the design and implementation of the underwater networking protocols, such as medium access control (MAC) and routing, and the underwater networking services (e.g., localization). Moreover, physical layer synchronization among wireless devices becomes simple and reliable due to the negligible delay and stable channel.
Predictable and constant channel response: Since the radiation resistance of a coil is much smaller than that of an electric dipole, only a very small portion of energy is radiated to the far field by the coil. Hence, compared to acoustic communication, multi-path fading is not an issue for MI-based underwater communication. Moreover, because of the high propagation speed of MI waves, the frequency offsets caused by Doppler effect can be greatly mitigated. Without suffering from multi-path fading and Doppler effect, the MI channel conditions (e.g., data rate and packet loss rate over a given transmission range) are highly constant and predictable. Moreover, without suffering from light scattering as in optical communications, the transmission range and channel quality of MI communications are independent of water quality factors such as water turbidity. In addition, both acoustic and optical communications have to deal with a high level of acoustic and ambient light noises. The EM noise experienced by MI channels is limited under water because the high-frequency noise is absorbed by the water medium. Sufficiently large communication range with high data rate: In MI-based communications, the transmission and reception are accomplishedthrough the use of a pair of small-size wire coils, that is, coil antennas. Different from the dipole antenna used in most EM wave-based communications, there is no minimum frequency below which the antenna cannot work. On the one hand, the time varying magnetic field can be generated no matter how small the coil is at the MI transmitter. On the other hand, as long as there is magnetic flux going through the coil, the MI receiver can capture the signal even if the frequency is as low as the Megahertz band. This property means that each small coil antenna can be utilized to emit low-frequency MI signals, which allow small underwater robots and vehicles to communicate over sufficiently long distances. Moreover, the operating frequency of MI coils can reach Megahertz bands while maintaining predictable and constant channel quality, which leads to much higher data rates than in the acoustic communications.
Multi hop relay mode: The experiments carried out in [7] demonstrate the validity of using magnetic fields for communication in shallow water. Anunderwater communication system that uses the magnetic field as a carrier at a frequency of 12 kHz and has a range of 30 m wassuccessfully designed for surface air to diver voice transmission [8]. In addition, data rates of 100 to 300 bps have been achievedin several MI communication tests carried out in coastal areas over mixed-media (air-water) ranges of 250–400 m [7]. However, the authors [7] point out that the high path loss limits the transmission distance. The s a trade off between QOS (quality of service) and distance.
For this reason, they suggest using a system of MI transceivers operating in multi-hop relay-mode. We propose to reduce costs and energy using relay points (just a simple coil without any energy source or processing device). Those relay coils form a MI waveguide that guides the magneto-inductive waves.
Magnetic induction (MI) is a promising physical layer technique for UWCNs that is not affected by multipath propagation and fading.
1. Important applications for shallow water such as diver-to-diver voice and text communications can be developed using this technique.
Real-time data transfer between AUVs, or AUVs and underwater sensors, Stealth and real-time underwater surveillance and patrol
Telemetry and remote control from underwater or surface equipment is also possible, since the water to air boundary is crossed by the magnetic component of an electromagnetic signal with relatively low attenuation.
Communication between AUVs and docking stations, or control of AUVs from surface vessels and shore is helpful in environmental and military applications suchas mine countermeasures during coastal reconnaissance missions.
Diver to shore or vessel communication are other interesting applications.
Collaborative sensing and tracking with underwater swarming robots.
(A) Collaborative sensing and tracking with underwater swarming robots: Fish behavior shows an astonishing ability to efficiently find food sources and favorable habitat regions through schooling behavior, that is, rapid orienting and synchronized moving of a group of fish with respect to environmental gradients, such as local variations in chemical stimuli such as odorant plumes or other environmental properties such as phytoplankton density.
Underwater MI communications can enable a swarm of underwater robots (e.g., agile robotic fish) to mimic this collective and synchronized intelligence of fish by exchanging control and environmental gradient information with guaranteed delay bounds.
In such a way, swarming robots can collaboratively track sources of pollution, toxicity, and biohazard with high convergence speed and accuracy.
(B) Stealth and real-time underwater surveillance and patrol: The high bandwidth along with the constant and reliable channel conditions achieved by underwater MI communications can enable real-time underwater surveillance, which demands high-speed delivery of a large volume of multimedia contents (e.g., audio, video, and scalar data).
In addition, the stealth and silent features of underwater MI communications allow underwater surveillance to be carried out in stealth mode.
In magneto inductive communications system, the distance of coils is usually larger, and transferred power drops off sharply to a very small fraction, so the coils should be asymmetric, which the transmitter coil being heavy and large, and the receiver coils being light and small. We are working in conductive media such as water, where the electrical conductivity sigma leads to energy dissipation of the material because of the eddy current which generates strong secondary field. Electrical conductivity gives a measure of a material’s ability to conduct an electric current.
1. The principle of magnetic induction is the current in the primary coil (transmitter) generates magnetic field then the magnetic field induces current in to secondary coil (receiver). Magnetic flux is a general term associated with a field that is bound by a certain area. So, magnetic flux is any area that has a magnetic field passing through it. Electron has a magnetic dipole moment. It's close to an electric dipole moment because it generates a magnetic field that behaves similarly to an electric dipole field (falls off like 1 /r3). The lowest order moment possible in magnetism that obeys Maxwell's equations is the dipole moment.
When data is transmitted over a data link, there is a possibility of errors being introduced into the system. If errors are introduced into the data, then the integrity of the system may be compromised. As a result, it is necessary to assess the performance of the system, and bit error rate, BER, provides an ideal way in which this can be achieved.If the medium between the transmitter and receiver is good and the signal to noise ratio is high, then the bit error rate will be very small - possibly insignificant and having no noticeable effect on the overall system However if noise can be detected, then there is chance that the bit error rate will need to be considered.
The main reasons for the degradation of a data channel and the corresponding bit error rate, BER is noise and changes to the propagation path (where radio signal paths are used). Both effects have a random element to them, the noise following a Gaussian probability function while the propagation model follows a Rayleigh model. This means that analysis of the channel characteristics are normally undertaken using statistical analysis techniques.
Convergence Zone:
In the ocean, zones where the surface waters of the ocean come together. They develop owing to unevenness in the wind field above the ocean and in the distribution of water density. They usually form at the junction of warm and cold waters and consequently are characterized by sharp horizontal gradients of temperature, salinity, density, and chemical and biological indicators (in certain cases the horizontal temperature gradient may be as much as 6°-7°C for several dozen meters). Owing to the uneven distribution of density, anticyclonic and cyclonic circulations of surface waters develop in convergence zones. In anticyclonic circulation there is intensive mixing and submergence of waters; in cyclonic circulation ascending streams of water develop and bring nutritional salts from the depths to the surface of the ocean.
This creates conditions for high biological productivity in these zones.
For Short Transmission Ranges (up to 9 m), the Path Loss and BER are Lower with the MI System for Fresh Water Compared to the Electromagnetic and Acoustic Communication Systems.
The Performance of the MI System in Sea Water is Good, although the Path Loss Values are Higher than in Fresh Water Due to the Electrical Conductivity of Sea Water.
The Multi-Hop Relay Technique Reduces Path Loss and Extends Communication Ranges. For Fresh Water. It Achieves Better Results than the Ordinary MI and the EM Wave Systems, and Outperforms the Acoustic System under All Propagation Phenomena.
Because of it’s Superior BER Performance, the Transmission Ranges Have Been Improved Moderately in Sea Water and Have Been Extended Considerably to Hundreds of Meters in Fresh Water. This Opens the Potential for a Number of Applications to Emerge.
harsh underwater environments. These environments include areas with a high concentration of conductive elements, through highly reflective barriers such as the surface of water and communicating through the earth.
(A) Ambient Noise : Mainly 2 types: Physical activities and Human activities.
Physical activities: Rainfall,, Seismic activities, Surface motion, caused by wind-driven waves is the major factor resulting in the noise in the frequency region 100 Hz – 100 kHz (which is the operating region used mostly by the acoustic systems)
Human activities: Distant Shipping (Noise caused by distant shipping is more in the frequency region 10 Hz -100 Hz), Oil exploration, Construction work, Turbulence(low frequency region, (f < 10 Hz)thermal noise becomes dominant for high frequencies i.e., f>100 kHz.
(B) Biological Noise: Aquatic animal made noise for communication, Prey manipulation, echolocation.
2. limited bandwidth (Limited throughput-Limited Data rates)-Bandwidth is the range of allowed or possible frequencies in which information passes. High data rates require high frequency contents ..hence high bandwidth channel to transmit them.
3. Extended multipath : Underwater channel is a time varying multipath channel causing ISI, ICI (Inter Channel Interference) and fading. Due to the effect of time and frequency spreading, achieving high data rates in underwater wireless communication is challenging.
4. Rapid time variation and severe fading: (Doppler Effect)The Doppler Effect is much more severe, because of thefollowing reasons:
the speed of sound is low,
the system is inherently a wideband system, the Doppler frequencies can be relatively large compared to the carrier frequency, and theDoppler shifts are dependent on the sub-carriers.
The frequency of the transmitted signal is significantly distorted by the Doppler Effect and multipath propagation. The motion induced distortion has far-reaching implications on the design of the synchronization unit and the channel estimation algorithm.
Generally, Doppler effect is caused by,
(i)Doppler shift caused by tx / rx motion.
(ii)Doppler shift caused by the moving sea surface.
SIR(Signal to Interference Ratio) not only depends on Doppler shift but also depends on bandwidth and the transmit power and all these factors are related as follows:
As Doppler frequency increases then ICI (Inter Channel Interference) power (or) transmit power increases
(ii) As bandwidth increases ICI power decreases but the ambient noise power increases. –fD ∞ PICI ∞ 1/BW ∞Ptx
BW ∞ Pambient noise ∞1/ PICI
Magnetic induction (MI) is a promising physical layer technique for UWCNs that is not affected by multipath propagation and fading.
1. Important applications for shallow water such as diver-to-diver voice and text communications can be developed using this technique.
Real-time data transfer between AUVs, or AUVs and underwater sensors, Stealth and real-time underwater surveillance and patrol
Telemetry and remote control from underwater or surface equipment is also possible, since the water to air boundary is crossed by the magnetic component of an electromagnetic signal with relatively low attenuation.
Communication between AUVs and docking stations, or control of AUVs from surface vessels and shore is helpful in environmental and military applications suchas mine countermeasures during coastal reconnaissance missions.
Diver to shore or vessel communication are other interesting applications.
Collaborative sensing and tracking with underwater swarming robots.
(A) Collaborative sensing and tracking with underwater swarming robots: Fish behavior shows an astonishing ability to efficiently find food sources and favorable habitat regions through schooling behavior, that is, rapid orienting and synchronized moving of a group of fish with respect to environmental gradients, such as local variations in chemical stimuli such as odorant plumes or other environmental properties such as phytoplankton density.
Underwater MI communications can enable a swarm of underwater robots (e.g., agile robotic fish) to mimic this collective and synchronized intelligence of fish by exchanging control and environmental gradient information with guaranteed delay bounds.
In such a way, swarming robots can collaboratively track sources of pollution, toxicity, and biohazard with high convergence speed and accuracy.
(B) Stealth and real-time underwater surveillance and patrol: The high bandwidth along with the constant and reliable channel conditions achieved by underwater MI communications can enable real-time underwater surveillance, which demands high-speed delivery of a large volume of multimedia contents (e.g., audio, video, and scalar data).
In addition, the stealth and silent features of underwater MI communications allow underwater surveillance to be carried out in stealth mode.
Magnetic induction (MI) is a promising physical layer technique for UWCNs that is not affected by multipath propagation and fading.
1. Important applications for shallow water such as diver-to-diver voice and text communications can be developed using this technique.
Real-time data transfer between AUVs, or AUVs and underwater sensors, Stealth and real-time underwater surveillance and patrol
Telemetry and remote control from underwater or surface equipment is also possible, since the water to air boundary is crossed by the magnetic component of an electromagnetic signal with relatively low attenuation.
Communication between AUVs and docking stations, or control of AUVs from surface vessels and shore is helpful in environmental and military applications suchas mine countermeasures during coastal reconnaissance missions.
Diver to shore or vessel communication are other interesting applications.
Collaborative sensing and tracking with underwater swarming robots.
(A) Collaborative sensing and tracking with underwater swarming robots: Fish behavior shows an astonishing ability to efficiently find food sources and favorable habitat regions through schooling behavior, that is, rapid orienting and synchronized moving of a group of fish with respect to environmental gradients, such as local variations in chemical stimuli such as odorant plumes or other environmental properties such as phytoplankton density.
Underwater MI communications can enable a swarm of underwater robots (e.g., agile robotic fish) to mimic this collective and synchronized intelligence of fish by exchanging control and environmental gradient information with guaranteed delay bounds.
In such a way, swarming robots can collaboratively track sources of pollution, toxicity, and biohazard with high convergence speed and accuracy.
(B) Stealth and real-time underwater surveillance and patrol: The high bandwidth along with the constant and reliable channel conditions achieved by underwater MI communications can enable real-time underwater surveillance, which demands high-speed delivery of a large volume of multimedia contents (e.g., audio, video, and scalar data).
In addition, the stealth and silent features of underwater MI communications allow underwater surveillance to be carried out in stealth mode.