This document provides a comprehensive study of acoustic channel models for underwater wireless communication networks. It describes the characteristics of acoustic propagation in shallow and deep water channels. For shallow water, it considers time-varying multipath and Doppler effects. For deep water, it examines multipath propagation. It presents transmission loss models for both channels based on factors like spreading, absorption, reflections. Numerical simulations are used to analyze issues like signal-to-noise ratio. The models aim to help develop effective communication protocols for underwater wireless networks.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
STATE-OF-THE-ART OF THE PHYSICAL LAYER IN UNDERWATER WIRELESS SENSOR NETWORKSijwmn
With the current technology revolution, underwater wireless sensor networks (UWSNs) find several applications such as disaster prevention, water quality monitoring, military surveillance and fish farming. Nevertheless, this kind of networks faces a number of challenges induced by the nature of the underwater environment and its influence on the network physical media. Therefore, the ultimate objective of this paper is to lay down the key aspects of the physical layer of the underwater sensor networks (UWSNs). It discusses issues related to the characteristics and challenges of the underwater communication channel, differences between terrestrial wireless sensor networks and UWSNs, and acoustic propagation models in underwater. The paper also surveys some of the underwater acoustic modems. This study is essential to better understand the challenges of designing UWSNs and alleviate their effects.
Realization of ofdm based underwater acoustic communicationeSAT Journals
Abstract Nowadays underwater communication plays a vital role in applications from commercial extends to military purposes. Present underwater communication systems involve the transmission of information in the form of sound, electromagnetic (EM), or optical waves. All these techniques has their own benefits and limitations. Acoustic communication is the most versatile and widely used technique in underwater environments because of its low attenuation compared with others. Acoustic waves are more applicable for thermally stable, deep water settings. But acoustic waves in shallow water can be adversely affected by temperature gradients, surface ambient noise, and multipath propagation due to reflection and refraction. The much slower speed of acoustic propagation in water, about 1500 m/s (meters per second), compared with that of electromagnetic and optical waves, and is another limiting factor for efficient communication and networking. Nevertheless, the currently favorable technology for underwater communication is upon acoustics. In this paper, we are planning to design a simple underwater acoustic system. We first discuss about the problems of underwater communication. Then we are designing a data transmission system in underwater and its analysis is done in the next step. Keywords: Underwater acoustic communication, Orthogonal frequency division multiplexing, Differential phase shift keying
This document provides a comparative study of three different types of underwater wireless optical
communication links: line-of-sight, modulating retroreflector, and reflective. It begins with background
on the importance of underwater wireless communication and limitations of existing acoustic
technology. Next, it discusses the advantages of underwater optical communication using the blue-
green window and defines key concepts like extinction coefficient. The document then describes
three models for underwater optical communication links - line-of-sight, modulating retroreflector,
and reflective - and provides equations for signal propagation through water.
Diurnal Variability of Underwater Acoustic Noise Characteristics in Shallow W...TELKOMNIKA JOURNAL
The biggest challenge in the underwater communication and target locating is to reduce the effect
of underwater acoustic noise (UWAN). An experimental model is presented in this paper for the diurnal
variability of UWAN of the acoustic underwater channel in tropical shallow water. Different segments of
data are measured diurnally at various depths located in the Tanjung Balau, Johor, Malaysia. Most
applications assume that the noise is white and Gaussian. However, the UWAN is not just thermal noise
but a combination of turbulence, shipping and wind noises. Thus, it is appropriate to assume UWAN as
colored rather than white noise. Site-specific noise, especially in shallow water often contains significant
non-Gaussian components. The real-time noise segments are analyzed to determine the statistical
properties such as power spectral density (PSD), autocorrelation function and probability density function
(pdf). The results show the UWAN has a non-Gaussian pdf and is colored. Moreover, the difference in
UWAN characteristics between day and night is studied and the noise power at night is found to be more
than at the day time by around (3-8dB).
This document discusses underwater acoustic communication and some of the challenges. It describes how about 2/3 of the Earth is covered in oceans, leaving a huge amount of natural resources to potentially discover through underwater exploration and monitoring. However, underwater acoustic communication is difficult due to factors like multipath propagation, time variations of the channel, small available bandwidth, and strong signal attenuation over long ranges. It also provides examples of potential underwater applications that could benefit from improving underwater acoustic communication technologies.
Short Range Underwater Communication Using Visible Ledguestcd295
This document proposes using visible light LEDs for short-range underwater wireless communication as an alternative to conventional acoustic systems. It analyzes the performance of such an optical system by modeling the underwater wireless optical channel based on underwater optics. The analysis shows that a single-color LED performs poorly in the wavelength-dependent underwater environment. To address this, the paper proposes a multi-wavelength adaptive scheme combined with rate adaptive transmission that can adapt to channel changes by controlling data rate and power for each wavelength band. An experiment was conducted to confirm the analysis by measuring received power and bit error rate in a turbid water tank.
This document discusses spectral analysis and filtering of ambient noise in shallow water. It aims to analyze the time series of nonstationary ambient noise signals using spectral analysis methods. Understanding ambient noise is important for applications like SONAR systems, as the noise sets the limit for signal detection. The document explores estimating the power spectrum of ambient noise using nonparametric methods and investigating how noise levels vary with factors like wind speed, tide height, and temperature. It also discusses using adaptive filters to reject unwanted noise like ship noise from desired signals.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
STATE-OF-THE-ART OF THE PHYSICAL LAYER IN UNDERWATER WIRELESS SENSOR NETWORKSijwmn
With the current technology revolution, underwater wireless sensor networks (UWSNs) find several applications such as disaster prevention, water quality monitoring, military surveillance and fish farming. Nevertheless, this kind of networks faces a number of challenges induced by the nature of the underwater environment and its influence on the network physical media. Therefore, the ultimate objective of this paper is to lay down the key aspects of the physical layer of the underwater sensor networks (UWSNs). It discusses issues related to the characteristics and challenges of the underwater communication channel, differences between terrestrial wireless sensor networks and UWSNs, and acoustic propagation models in underwater. The paper also surveys some of the underwater acoustic modems. This study is essential to better understand the challenges of designing UWSNs and alleviate their effects.
Realization of ofdm based underwater acoustic communicationeSAT Journals
Abstract Nowadays underwater communication plays a vital role in applications from commercial extends to military purposes. Present underwater communication systems involve the transmission of information in the form of sound, electromagnetic (EM), or optical waves. All these techniques has their own benefits and limitations. Acoustic communication is the most versatile and widely used technique in underwater environments because of its low attenuation compared with others. Acoustic waves are more applicable for thermally stable, deep water settings. But acoustic waves in shallow water can be adversely affected by temperature gradients, surface ambient noise, and multipath propagation due to reflection and refraction. The much slower speed of acoustic propagation in water, about 1500 m/s (meters per second), compared with that of electromagnetic and optical waves, and is another limiting factor for efficient communication and networking. Nevertheless, the currently favorable technology for underwater communication is upon acoustics. In this paper, we are planning to design a simple underwater acoustic system. We first discuss about the problems of underwater communication. Then we are designing a data transmission system in underwater and its analysis is done in the next step. Keywords: Underwater acoustic communication, Orthogonal frequency division multiplexing, Differential phase shift keying
This document provides a comparative study of three different types of underwater wireless optical
communication links: line-of-sight, modulating retroreflector, and reflective. It begins with background
on the importance of underwater wireless communication and limitations of existing acoustic
technology. Next, it discusses the advantages of underwater optical communication using the blue-
green window and defines key concepts like extinction coefficient. The document then describes
three models for underwater optical communication links - line-of-sight, modulating retroreflector,
and reflective - and provides equations for signal propagation through water.
Diurnal Variability of Underwater Acoustic Noise Characteristics in Shallow W...TELKOMNIKA JOURNAL
The biggest challenge in the underwater communication and target locating is to reduce the effect
of underwater acoustic noise (UWAN). An experimental model is presented in this paper for the diurnal
variability of UWAN of the acoustic underwater channel in tropical shallow water. Different segments of
data are measured diurnally at various depths located in the Tanjung Balau, Johor, Malaysia. Most
applications assume that the noise is white and Gaussian. However, the UWAN is not just thermal noise
but a combination of turbulence, shipping and wind noises. Thus, it is appropriate to assume UWAN as
colored rather than white noise. Site-specific noise, especially in shallow water often contains significant
non-Gaussian components. The real-time noise segments are analyzed to determine the statistical
properties such as power spectral density (PSD), autocorrelation function and probability density function
(pdf). The results show the UWAN has a non-Gaussian pdf and is colored. Moreover, the difference in
UWAN characteristics between day and night is studied and the noise power at night is found to be more
than at the day time by around (3-8dB).
This document discusses underwater acoustic communication and some of the challenges. It describes how about 2/3 of the Earth is covered in oceans, leaving a huge amount of natural resources to potentially discover through underwater exploration and monitoring. However, underwater acoustic communication is difficult due to factors like multipath propagation, time variations of the channel, small available bandwidth, and strong signal attenuation over long ranges. It also provides examples of potential underwater applications that could benefit from improving underwater acoustic communication technologies.
Short Range Underwater Communication Using Visible Ledguestcd295
This document proposes using visible light LEDs for short-range underwater wireless communication as an alternative to conventional acoustic systems. It analyzes the performance of such an optical system by modeling the underwater wireless optical channel based on underwater optics. The analysis shows that a single-color LED performs poorly in the wavelength-dependent underwater environment. To address this, the paper proposes a multi-wavelength adaptive scheme combined with rate adaptive transmission that can adapt to channel changes by controlling data rate and power for each wavelength band. An experiment was conducted to confirm the analysis by measuring received power and bit error rate in a turbid water tank.
This document discusses spectral analysis and filtering of ambient noise in shallow water. It aims to analyze the time series of nonstationary ambient noise signals using spectral analysis methods. Understanding ambient noise is important for applications like SONAR systems, as the noise sets the limit for signal detection. The document explores estimating the power spectrum of ambient noise using nonparametric methods and investigating how noise levels vary with factors like wind speed, tide height, and temperature. It also discusses using adaptive filters to reject unwanted noise like ship noise from desired signals.
Underwater Object Detection and Tracking Using Electromagnetic WavesMusbiha Binte Wali
The document presents five different 3D underwater wireless sensor network (UWSN) architectures proposed for detecting and localizing underwater intruders using electromagnetic waves. The architectures consist of sensor nodes, cluster heads, a surface sink, and an onshore base station. Localization accuracy is evaluated using metrics like normalized mean square error in distance estimation. The impact of network parameters such as node topology, network length, and detection threshold on system performance is analyzed through simulations. This work investigates electromagnetic communication for underwater localization, as existing approaches rely primarily on acoustic networks.
This document provides an overview of underwater wireless communication technologies. It discusses the unique challenges of underwater acoustic channels, including high propagation loss, multipath interference, and low sound speed. It then describes acoustic modems, modulation techniques, and equalization methods used to achieve wireless data transmission in underwater environments. Finally, it outlines applications and research areas for underwater networks, including environmental monitoring, archaeology, and search and rescue. The goal is to lay the groundwork for more advanced underwater communication and networking to enhance ocean exploration.
1) Underwater communication faces challenges due to the medium but has progressed with acoustic and optical modulation/demodulation.
2) Channel modeling is important to evaluate techniques before implementation and reduces hardware costs. Common models include the additive noise channel and radiative transfer equation models.
3) Acoustic communication uses sound waves and has advantages of long range but limited bandwidth. Optical uses light with higher bandwidth but more attenuation. Hybrid systems may improve performance.
Underwater optical communication is a promising alternative to acoustic methods for underwater wireless communication. Radio waves do not propagate well underwater, so optical methods using lasers and LEDs can provide line-of-sight transmission of data, video and signals for vehicle control. Several factors influence the performance of underwater optical links, including absorption and scattering by water constituents like phytoplankton and dissolved organic matter, as well as scattering from suspended particles.
This document discusses underwater acoustic communication. It notes deficiencies in current communication methods and the necessity of acoustic communication. It provides an overview of acoustic communication models and modems. Applications are described including controlling autonomous underwater vehicles and sensors. Limitations are outlined such as limited bandwidth and battery power. The conclusion states the goal is to overcome limitations and implement advanced acoustic technology for oceanographic research.
In this i tried to explain about under water communication.
Introduction of underwater communication.
Problem due to Multipath Propagation
Techniques used for underwater communication
1. Single Carrier Systems
2. MCM Techniques
3. Space-Time Modulation Techniques
Applications
Limitations
Conclusion
Channel Characterization of EM Waves Propagation at MHz Frequency through Sea...MuhammadTahir513
Dr.Muhammad Tahir completed his PhD on 26 June 2019 in Information & Communication Engineering from School of Electronics and Information Engineering, Changchun University of Science and Technology, Changchun, Jilin, PR China. His major research interests includes RF/MW Propagation,Underwater Communication and Energy Optimization in WSNs.
This document presents information on underwater wireless communication. It discusses how acoustic waves can be used for underwater wireless transmission instead of radio waves due to water's inhibiting effects on radio waves. The document outlines the working, applications, advantages and disadvantages of underwater wireless communication using acoustic waves and acoustic modems. It provides figures showing different acoustic modems and the network architecture. The conclusion states that underwater wireless using acoustic waves can achieve high data rates with lower path loss compared to other methods.
This document provides an outline and introduction for a case study analyzing the influence of transportation infrastructure on watershed boundaries and stream networks in the Rouge River watershed in Michigan. The study used LiDAR data to delineate watershed boundaries and extract stream networks. It then analyzed the conformity between these features and road/rail networks using buffering techniques. The results showed a high percentage of the watershed boundary was within road/rail buffers, and the stream network demonstrated substantial conformity to road networks. This conformity is likely to increase stream degradation issues in urban areas. More research is needed to relate conformity impacts to "urban stream syndrome."
This document presents information about underwater acoustic communication channels. It discusses how sound can be used as a wireless communication medium underwater, as radio waves do not propagate well in water. It describes some of the key challenges with underwater acoustic channels, including limited bandwidth, multipath propagation, Doppler effects from water movements, noise from biological and man-made sources, and scattering. It also provides examples of potential underwater applications that could benefit from acoustic communication technologies, such as pollution monitoring, seismic monitoring, and autonomous underwater vehicle control.
wireless Communication Underwater(Ocean)tanveer alam
Underwater wireless communication uses acoustic signals to transmit digital information through water. Wired connections are not always feasible for underwater experiments due to problems like cable breaks or high costs. Acoustic communication is affected by factors like path loss, noise, multipath propagation, and Doppler spread. Advanced acoustic modems employ techniques like error correction coding to achieve low bit error rates. Underwater acoustic sensor networks use groups of sensors and autonomous underwater vehicles linked by acoustic connections to collaboratively monitor things like pollution, currents, and equipment. Despite progress, limitations remain regarding battery life, bandwidth, and environmental impacts on performance.
This document discusses underwater optical wireless communication networks. It presents models for three types of optical wireless communication links: (1) a line-of-sight link, (2) a modulating retroreflector link, and (3) a reflective link. It analyzes the performance of these links based on models that account for properties of the underwater optical channel, including absorption and scattering of light. The analysis shows that communication performance decreases dramatically with increasing water absorption, though scattered light can mitigate this to some extent. A high-data-rate underwater optical wireless network is concluded to be feasible for applications like sensor networks and UUV communication, with extended range possible using a multi-hop approach.
Satellite Communication and Energy Conservation Theoriesijtsrd
Satellite communication becomes inevitable in daily life. It is development of science, common media for most communications. Most inventions are properly engineered nowadays. Mobile, Internet, Radio, Television, climate condition reports, and many such advantages. There are many advantages and some disadvantages in using satellite communication, and some side effects. Proper usage of satellite communication makes a healthy environment, wastage of energy in terms of unnecessary disturbance should be avoided for a healthy environment. This journal briefly discusses how to use the satellite communication effectively in terms of energy conservation. Palaniraj Kannapillai "Satellite Communication and Energy Conservation Theories" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1 , December 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29666.pdf Paper URL: https://www.ijtsrd.com/engineering/telecommunications/29666/satellite-communication-and-energy-conservation-theories/palaniraj-kannapillai
Comparative Limnological Studies of Nnamdi Azikiwe University (Unizik) and A...Scientific Review SR
The limnological studies of Unizik and Amansea streams, Awka South Local Governments Area,
Anambra State, Nigeria, were carried out using standard methods. The mean water temperature, dissolved oxygen
content, transparency and pH were 26.330C, 2.75 mg/l, 49.10cm and 7.80 respectively, in Unizik Stream. For
Amansea Stream, the values were 26.580C, 2.40mg/l, 35.87cm and 7.70, respectively. The mean BOD,
Alkalinity, water depth and water current values recorded in Unizik stream were 16.00mg/l 119.70mg/l,58.25cm
and 0.45m/s respectively, while in Amansea Stream the values were 11.50mg/l, 111.35mg/l, 59.43cm and 0.39/s
respectively. The physicochemical parameters of the two streams vary spatially. Unizik and Amansea streams
exhibited features that are typical of streams in tropical environment. The low dissolved oxygen content, high
biochemical oxygen demand and low alkalinity values indicate that the water bodies are unsuitable to support
aquatic life.
Propagation Effects and Their Impact on Satellite-Earth Links: Introduction,
Quantifying attenuation and depolarization,
Propagation effects that are not associated with hydrometeors, Prediction of rain attenuation,
Prediction of XPD,
Propagation impairments countermeasures.
Underwater Wireless Communication is the wireless communication in which acoustic signals (waves) carry digital information through an underwater channel.
Underwater Object Detection and Tracking Using Electromagnetic WavesMusbiha Binte Wali
The document presents five different 3D underwater wireless sensor network (UWSN) architectures proposed for detecting and localizing underwater intruders using electromagnetic waves. The architectures consist of sensor nodes, cluster heads, a surface sink, and an onshore base station. Localization accuracy is evaluated using metrics like normalized mean square error in distance estimation. The impact of network parameters such as node topology, network length, and detection threshold on system performance is analyzed through simulations. This work investigates electromagnetic communication for underwater localization, as existing approaches rely primarily on acoustic networks.
This document provides an overview of underwater wireless communication technologies. It discusses the unique challenges of underwater acoustic channels, including high propagation loss, multipath interference, and low sound speed. It then describes acoustic modems, modulation techniques, and equalization methods used to achieve wireless data transmission in underwater environments. Finally, it outlines applications and research areas for underwater networks, including environmental monitoring, archaeology, and search and rescue. The goal is to lay the groundwork for more advanced underwater communication and networking to enhance ocean exploration.
1) Underwater communication faces challenges due to the medium but has progressed with acoustic and optical modulation/demodulation.
2) Channel modeling is important to evaluate techniques before implementation and reduces hardware costs. Common models include the additive noise channel and radiative transfer equation models.
3) Acoustic communication uses sound waves and has advantages of long range but limited bandwidth. Optical uses light with higher bandwidth but more attenuation. Hybrid systems may improve performance.
Underwater optical communication is a promising alternative to acoustic methods for underwater wireless communication. Radio waves do not propagate well underwater, so optical methods using lasers and LEDs can provide line-of-sight transmission of data, video and signals for vehicle control. Several factors influence the performance of underwater optical links, including absorption and scattering by water constituents like phytoplankton and dissolved organic matter, as well as scattering from suspended particles.
This document discusses underwater acoustic communication. It notes deficiencies in current communication methods and the necessity of acoustic communication. It provides an overview of acoustic communication models and modems. Applications are described including controlling autonomous underwater vehicles and sensors. Limitations are outlined such as limited bandwidth and battery power. The conclusion states the goal is to overcome limitations and implement advanced acoustic technology for oceanographic research.
In this i tried to explain about under water communication.
Introduction of underwater communication.
Problem due to Multipath Propagation
Techniques used for underwater communication
1. Single Carrier Systems
2. MCM Techniques
3. Space-Time Modulation Techniques
Applications
Limitations
Conclusion
Channel Characterization of EM Waves Propagation at MHz Frequency through Sea...MuhammadTahir513
Dr.Muhammad Tahir completed his PhD on 26 June 2019 in Information & Communication Engineering from School of Electronics and Information Engineering, Changchun University of Science and Technology, Changchun, Jilin, PR China. His major research interests includes RF/MW Propagation,Underwater Communication and Energy Optimization in WSNs.
This document presents information on underwater wireless communication. It discusses how acoustic waves can be used for underwater wireless transmission instead of radio waves due to water's inhibiting effects on radio waves. The document outlines the working, applications, advantages and disadvantages of underwater wireless communication using acoustic waves and acoustic modems. It provides figures showing different acoustic modems and the network architecture. The conclusion states that underwater wireless using acoustic waves can achieve high data rates with lower path loss compared to other methods.
This document provides an outline and introduction for a case study analyzing the influence of transportation infrastructure on watershed boundaries and stream networks in the Rouge River watershed in Michigan. The study used LiDAR data to delineate watershed boundaries and extract stream networks. It then analyzed the conformity between these features and road/rail networks using buffering techniques. The results showed a high percentage of the watershed boundary was within road/rail buffers, and the stream network demonstrated substantial conformity to road networks. This conformity is likely to increase stream degradation issues in urban areas. More research is needed to relate conformity impacts to "urban stream syndrome."
This document presents information about underwater acoustic communication channels. It discusses how sound can be used as a wireless communication medium underwater, as radio waves do not propagate well in water. It describes some of the key challenges with underwater acoustic channels, including limited bandwidth, multipath propagation, Doppler effects from water movements, noise from biological and man-made sources, and scattering. It also provides examples of potential underwater applications that could benefit from acoustic communication technologies, such as pollution monitoring, seismic monitoring, and autonomous underwater vehicle control.
wireless Communication Underwater(Ocean)tanveer alam
Underwater wireless communication uses acoustic signals to transmit digital information through water. Wired connections are not always feasible for underwater experiments due to problems like cable breaks or high costs. Acoustic communication is affected by factors like path loss, noise, multipath propagation, and Doppler spread. Advanced acoustic modems employ techniques like error correction coding to achieve low bit error rates. Underwater acoustic sensor networks use groups of sensors and autonomous underwater vehicles linked by acoustic connections to collaboratively monitor things like pollution, currents, and equipment. Despite progress, limitations remain regarding battery life, bandwidth, and environmental impacts on performance.
This document discusses underwater optical wireless communication networks. It presents models for three types of optical wireless communication links: (1) a line-of-sight link, (2) a modulating retroreflector link, and (3) a reflective link. It analyzes the performance of these links based on models that account for properties of the underwater optical channel, including absorption and scattering of light. The analysis shows that communication performance decreases dramatically with increasing water absorption, though scattered light can mitigate this to some extent. A high-data-rate underwater optical wireless network is concluded to be feasible for applications like sensor networks and UUV communication, with extended range possible using a multi-hop approach.
Satellite Communication and Energy Conservation Theoriesijtsrd
Satellite communication becomes inevitable in daily life. It is development of science, common media for most communications. Most inventions are properly engineered nowadays. Mobile, Internet, Radio, Television, climate condition reports, and many such advantages. There are many advantages and some disadvantages in using satellite communication, and some side effects. Proper usage of satellite communication makes a healthy environment, wastage of energy in terms of unnecessary disturbance should be avoided for a healthy environment. This journal briefly discusses how to use the satellite communication effectively in terms of energy conservation. Palaniraj Kannapillai "Satellite Communication and Energy Conservation Theories" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1 , December 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29666.pdf Paper URL: https://www.ijtsrd.com/engineering/telecommunications/29666/satellite-communication-and-energy-conservation-theories/palaniraj-kannapillai
Comparative Limnological Studies of Nnamdi Azikiwe University (Unizik) and A...Scientific Review SR
The limnological studies of Unizik and Amansea streams, Awka South Local Governments Area,
Anambra State, Nigeria, were carried out using standard methods. The mean water temperature, dissolved oxygen
content, transparency and pH were 26.330C, 2.75 mg/l, 49.10cm and 7.80 respectively, in Unizik Stream. For
Amansea Stream, the values were 26.580C, 2.40mg/l, 35.87cm and 7.70, respectively. The mean BOD,
Alkalinity, water depth and water current values recorded in Unizik stream were 16.00mg/l 119.70mg/l,58.25cm
and 0.45m/s respectively, while in Amansea Stream the values were 11.50mg/l, 111.35mg/l, 59.43cm and 0.39/s
respectively. The physicochemical parameters of the two streams vary spatially. Unizik and Amansea streams
exhibited features that are typical of streams in tropical environment. The low dissolved oxygen content, high
biochemical oxygen demand and low alkalinity values indicate that the water bodies are unsuitable to support
aquatic life.
Propagation Effects and Their Impact on Satellite-Earth Links: Introduction,
Quantifying attenuation and depolarization,
Propagation effects that are not associated with hydrometeors, Prediction of rain attenuation,
Prediction of XPD,
Propagation impairments countermeasures.
Underwater Wireless Communication is the wireless communication in which acoustic signals (waves) carry digital information through an underwater channel.
A União Europeia está preocupada com o impacto da inteligência artificial no mercado de trabalho. Muitos empregos podem ser automatizados, mas a IA também pode criar novas oportunidades. A UE está trabalhando para garantir que a IA seja desenvolvida e aplicada de forma ética e segura para beneficiar a sociedade e economia.
Công ty cổ phần dịch vụ PG Á Đông là một công ty chuyên nghiệp, uy tín hàng đầu tại thành phố Hồ Chí Minh, Hà Nội trong lĩnh vực cung cấp PG, PB, cung cấp lễ tân, cung cấp MC nam nữ chuyên nghiệp, cung cấp người mẫu ảnh, cung cấp các nhóm nhảy, nhóm múa tại thành phố Hồ Chí Minh, Hà Nội và trên toàn quốc.
Louise Browne is recommended by Lee Minskoff of The Dream Street Foundation. Minskoff said that Louise is the most competent, intelligent and tireless person he can think of. When they worked together writing grants, Minskoff had trouble distinguishing Louise's input from his own because she is so remarkable.
Drama ini mengisahkan perjalanan hidup Abu, seorang anak muda dari pedalaman yang awalnya buta IT. Melalui kursus yang diadakan FELCRA, Abu belajar tentang IT dan berhasil menjadi pelajar terbaik. Lima tahun kemudian, Abu kini berjaya sebagai pengusaha IT terkemuka dan dihormati warga kampungnya. Dia mendirikan pusat komputer untuk membantu anak-anak pedalaman lain.
The document discusses franchise development training that occurred. An individual was trained for one month at the corporate headquarters and a second store location in Kentucky, USA. The individual was recognized with a Service Excellence Award.
El documento es la letra de la canción "Un Millón de Amigos" de Roberto Carlos. La canción expresa el deseo del cantante de tener un millón de amigos para poder cantar más fuerte y llevar su canto a quien lo necesite. También menciona querer mirar los campos, navegar con rumbo norte y creer en la paz del futuro.
This is a short overview of the projectacademie. A company specialised in learning companies how to work in a team.
for more information please check our website : www.deprojectacademie.nl
1) Underwater communication faces challenges due to the medium but has progressed with acoustic and optical modulation/demodulation.
2) Channel modeling is important to evaluate techniques before development and reduces hardware costs. Common models include additive noise, acoustic, and optical channels.
3) Acoustic waves best communicate underwater but have limited bandwidth while optical has more bandwidth but higher attenuation. Hybrid systems may improve performance.
1) Underwater communication faces challenges due to the medium but has progressed with acoustic and optical modulation/demodulation.
2) Channel modeling is important to evaluate techniques before implementation and reduces hardware costs. Common models include the additive noise channel and radiative transfer equation models.
3) Acoustic communication uses sound waves and has advantages of long range but limited bandwidth. Optical uses light with higher bandwidth but more attenuation. Hybrid systems may improve performance.
Under water acoustic (uw a) communication architecture and the key notions of...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Under water acoustic (uw a) communication architecture and the key notions of...eSAT Journals
Abstract The study of the communication architecture for the underwater is very important due the wide applications based on these sensing devices. The more observed examples of applications are climate change monitoring, study of marine life, pollution control, and military purposes. It is observed the radio frequency (RF) electromagnetic waves [1], Optical electromagnetic waves, underwater Optical communication [2] waves all have been used for the underwater sensor networking. But these have shown with its slight disadvantages for the underwater related works. So this can be overcome by the usage of the acoustic communication as a means of transmission technology for the underwater networked system. It is also observed that the underwater acoustic signals are suffering from the some transmission loss, high propagation delay, limited bandwidth. So to eliminate these observed factors with respect to the underwater sensor networks the communication architecture has been developed to provide the point to point, having low data rate and high bandwidth signal and delay tolerant applications. Therefore this article has been written to give the details of how the communication architecture can be designed and for the underwater network and the key factors which relates to the propagation of underwater acoustic signals. Keywords: UW-A, Doppler Spread, Attenuation, Variance
Study of Absorption Loss Effects on Acoustic Wave Propagation in Shallow Wate...IJAAS Team
This document summarizes a study on modeling acoustic wave absorption in shallow water using different empirical models. It compares Thorp's formula, Schulkin-Marsh model, and Fisher-Simmons formula for calculating absorption coefficients in different frequency ranges. Simulation results using MATLAB are evaluated against measured data from Desaru Beach in Malaysia. The models show that absorption loss increases with frequency and range, acting as a low-pass filter. Higher frequencies allow for higher data rates but experience greater attenuation over long distances. The document concludes by finding the most suitable frequency ranges and depths to minimize absorption loss for underwater acoustic propagation links.
Development of an FHMA-based Underwater Acoustic Communications System for Mu...Waqas Tariq
This paper describes the design of an underwater acoustic communications system for multiple underwater vehicles, based on frequency-hopping multiple-access (FHMA) and tamed spread-spectrum communications. The system makes used of the tamed spread-spectrum method, frequency hopping, 4FSK, and a rake receiver. In order to make the system more practical, the underwater channel and the effect of the number of users on the bit error ratio (BER) are also taken into account. Since the necessary proving experiments are not easily conducted in the ocean, a platform is developed that uses the sound card of a computer, combined with a sound box and microphone, to transduce energy for acoustic communications. Simulated and experimental results indicate that this system could provide reliable underwater communications between multiple underwater vehicles.
This document provides an overview of underwater wireless communication technologies. It discusses the unique challenges of underwater acoustic channels, including high propagation loss, multipath interference, and low sound speed. It then describes acoustic modems, modulation techniques, and equalization methods used to achieve wireless data transmission in underwater environments. The document outlines centralized and decentralized network topologies and protocols being developed for underwater sensor networks. Applications include environmental monitoring, marine research, and defense. Overall limitations include limited bandwidth and high error rates due to channel characteristics.
The document summarizes underwater wireless communication technology. It discusses how acoustic waves are used instead of radio waves to transmit information underwater over long distances. It describes some of the challenges of underwater acoustic channels including high propagation loss, severe multipath interference, and low sound speed. The document also provides an overview of acoustic modem technology, discussing modulation schemes like FSK and PSK, and the use of equalizers to address multipath interference. The goal of underwater wireless communication is to enable applications like environmental monitoring without the need for heavy cables.
While wireless communication technology today has become part of our daily life, the
idea of wireless undersea communications may still seem far-fetched. However, research has
been active for over a decade on designing the methods for wireless information transmission
underwater. Human knowledge and understanding of the world’s oceans, which constitute
the major part of our planet, rests on our ability to collect information from remote undersea
locations.
The major discoveries of the past decades, such as the remains of Titanic, or the hydrothermal
vents at bottom of deep ocean, were made using cabled submersibles. Although such
systems remain indispensable if high-speed communication link is to exists between the
remote end and the surface, it is natural to wonder what one could accomplish without the
burden (and cost) of heavy cables.
Hence the motivation, and interest in wireless underwater communications. Together with
sensor technology and vehicular technology, wireless communications will enable new
applications ranging from environmental monitoring to gathering of oceanographic data,
marine archaeology, and search and rescue missions.
Error Rate Performance of Interleaved Coded OFDM For Undersea Acoustic LinksCSCJournals
Studies on undersea acoustic communication links, set up through highly complex and inhomogeneous underwater channel using various orders of QAM and PSK based OFDM techniques, have been reported in open literature. However, their bit error rate performances still need to be improved. Coding, when combined with OFDM, helps to detect and correct errors without having the overhead of too many retransmissions, as the bandwidth is a scarce resource in undersea scenario. The technique of interleaving, which is frequently employed in digital communication and storage systems to enhance the performance of the coding schemes, can be used to improve the error rate performance of the coded OFDM. The error rate performances of interleaved convolutional and BCH coded OFDMs for undersea acoustic links for binary phase shift keying and its differential variant have been studied in this paper. It is found that at high SNR, the process of interleaving and coding offers significant improvement in the error rate performance. It is also worth mentioning the fact that interleaving improves the performance of both convolutional and BCH coded OFDM systems.
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Seawater salinity modelling based on electromagnetic wave characterizationIJECEIAES
Wireless communications have experienced tremendous growth, and improving their performance based on specific parameters requires an accurate model. Salt seawater, being an abundant resource, could play a crucial role in various applications such as enhancing electrical conductivity, monitoring security, improving battery power efficiency, and creating liquid antennas. Salinity is an essential factor to consider when developing these applications. This paper focused on investigating the electromagnetic properties of seawater salinity in the context of marine wireless communications. The results of the study showed that salinity has a significant impact on the Fresnel reflection coefficient in terms of magnitude, phase shift, and polarization, and can either constructively or destructively affect it. The new model paved the way for the development of an integrated salt seawater model that addressed the complex salinity issues involved in these applications.
1) The document describes a wavelet-based technique for denoising underwater signals affected by wind-driven ambient noise. It uses discrete wavelet transform to decompose the noisy signal into coefficients. 2) A threshold is calculated using the universal threshold method and applied to the coefficients to remove noise. Hard and soft thresholding are evaluated. 3) The denoised signal is then reconstructed from the modified coefficients using inverse discrete wavelet transform. The technique is shown to effectively reduce wind noise and improve the signal-to-noise ratio.
1) The document describes a wavelet-based technique for denoising underwater signals affected by wind-driven ambient noise. It uses discrete wavelet transform to decompose the noisy signal into coefficients. 2) Thresholding is then applied to the coefficients, where threshold values are calculated separately for each level of decomposition using universal thresholding. 3) The signal is then reconstructed from the modified coefficients after thresholding to reduce noise. The technique aims to improve the signal-to-noise ratio of underwater signals corrupted by wind noise.
This document provides an overview of underwater communication protocols and challenges in underwater wireless sensor networks (UWSNs). It discusses that UWSNs face different challenges than terrestrial networks due to limited bandwidth, high propagation delays, and dynamic underwater channels. Several MAC protocols have been proposed to provide energy efficient and reliable data transmission from sensor nodes to a sink node in UWSNs. The document reviews research on localization techniques, existing MAC protocols, and advances and future trends in the physical, MAC and routing layers of UWSN communication stacks. It aims to give a comprehensive overview of the current state of research in key areas of UWSNs.
UNDER WATER EIRELESS COMMUNICATION.pptxssuser0af13c
Underwater wireless communication faces many challenges due to factors like multipath propagation, time-varying channels, small bandwidth, and high signal attenuation over long distances. While electromagnetic waves don't propagate well underwater, acoustic waves provide the best solution for underwater communication. Underwater wireless networks use acoustic signals and can be centralized, with nodes communicating through a base station, or decentralized, with peer-to-peer communication between nodes. Factors like path loss, noise, multipath, high propagation delays influence acoustic communication. Applications include marine archaeology, search and rescue missions, and pollution monitoring.
Design of Underwater wireless optical/acoustic link for reduction of back-sca...theijes
Underwater communication plays a significant role in the study of climate change through ocean monitoring and associated sensor networks. It is severely limited when compared to free space communication because water is essentially opaque to electromagnetic radiation except in the visible band. Even in the visible band, light penetrates only a few hundred meters in the clearest waters and much less in turbid waters due to the presence of suspended sediment or high concentrations of marine life. Consequently, acoustic techniques are been used for underwater communication systems which is relatively mature and robust. Acoustic systems are capable of long range communication. But traditional underwater acoustic communications cannot provide high enough data rates to enable monitoring technology. Optical wireless communications, centred around blue-green wavelengths, are being used as an alternative. Here a hybrid design is being introduced using an optical/acoustic link to reduce back scattering of transmitted light.
Error Performance Analysis in Underwater Acoustic Noise with Non-Gaussian Dis...TELKOMNIKA JOURNAL
1) The document analyzes error performance in underwater acoustic noise channels with non-Gaussian distributions. Field data was collected off the coast of Malaysia and found to follow a Student's t distribution rather than Gaussian.
2) A probability density function for the noise amplitude is proposed based on the Student's t distribution. An expression for binary error probability is derived considering the non-Gaussian noise characteristics.
3) Simulations show the underwater acoustic noise channel has slightly better error performance than Gaussian noise channels at low SNR, but significantly worse performance at high SNR, due to the shape of the Student's t distribution. The non-Gaussian noise degrades performance more for higher order modulations.
Scattering Regimes for Underwater Optical Wireless Communications using Monte...IJECEIAES
Optical wireless communications has shown tremendous potential for underwater applications as it can provide higher bandwidth and better security compared to acoustic technologies. In this paper, an investigation on scattering regimes for underwater links using Monte Carlo simulation has been presented.While the focus of this paper is on diffuse links, the simulation results of collimated links is also provided for comparison purpose. Three types of water namely clear, coastal and turbid water are being used in the simulation. It is shown that the effect of scattering on the path loss cannot be accurately modeled by the existing channel model; ie. Beers-Lambert (BL) law. It has been shown that the distance at which the unscattered light drops to zero can be used to estimate the transition point for the scattering regimes in case of diffuse links. The transition point for diffuse links in coastal water and turbid water can be estimated to be around 22 m and 4 m respectively. Further analysis on the scattering order probability at different scattering regimes illustrates how scattering is affected by beam size, water turbidity and distance. From the frequency response plot, it is estimated that the bandwidth of several order of GHz can be achieved when the links are operating in the minimal scattering region and will reduce to several hundreds of MHz when the link is operating in multiple scattering region.
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C OMPREHENSIVE S TUDY OF A COUSTIC C HANNEL M ODELS FOR U NDERWATER W IRELESS C OMMUNICATION N ETWORKS
1. International Journal on Cybernetics & Informatics (IJCI) Vol. 4, No. 2, April 2015
DOI: 10.5121/ijci.2015.4222 227
COMPREHENSIVE STUDY OF ACOUSTIC CHANNEL
MODELS FOR UNDERWATER WIRELESS
COMMUNICATION NETWORKS
S Anandalatchoumy1
and G Sivaradje2
Department of Electronics and Communication Engineering, Pondicherry Engineering
College, Pondicherry, India.
ABSTRACT
In underwater acoustic communication, shallow water and deep water are two different mediums which
exhibit many challenges to deal with due to the time varying multipath and Doppler Effect in the former
case and multipath propagation in the latter case. In this paper, the characteristics of the acoustic
propagation are described in detail and channel models based on the various propagation phenomena in
shallow water channel and deep water channel as well are presented and the transmission losses incurred
in each model are thoroughly investigated. Signal to noise ratio (SNR) at the receiver is thoroughly
analyzed. Numerical results obtained through analytical simulations carried out in MATLAB bring to light
the important issues to be considered so as to develop suitable communication protocols for Underwater
Wireless Communication Networks (UWCNs) to provide effective and reliable communication.
KEYWORDS
Underwater Acoustic Communication, Transmission Loss, Shallow Water, Deep Water.
1. INTRODUCTION
About 70% of the earth is surrounded by water in the form of oceans. Wireless signal
transmission underwater will enable many different applications to be performed in highly
dynamic and harsh environment of underwater medium which would benefit the mankind to
enhance their life [1]. So, tremendous success of the application of wireless sensor technology in
the development of terrestrial wireless sensor networks has motivated the scientists and
researchers to apply the same technology to explore the less unexplored ocean to benefit mankind
from the ocean natural resources and to rescue them from natural disasters like Tsunamis,
earthquakes and so on. This has paved the way for them to develop Underwater Wireless
Communication Networks (UWCNs).
Basically, UWCNs are formed by group of sensors and/or autonomous underwater vehicles
deployed underwater and networked through wireless links by acoustic signals to perform
collaborative monitoring tasks over a given area [1]. These networks are also referred to as
Underwater Wireless Sensor Networks. Underwater acoustic communication channel exhibits
challenges in many aspects which are quite different from the terrestrial radio communication
channel due to the acoustic propagation characteristics such as transmission loss, multipath
propagation and multipath fading, Doppler spreading, ambient noise, time-dependent channel
variations and variable delay. This makes underwater wireless communication more challenging.
Moreover, higher frequencies experience more absorption loss resulting in the limit of usable
bandwidth. This necessitates studying the propagation characteristics of the acoustic channel in
2. International Journal on Cybernetics & Informatics (IJCI) Vol. 4, No. 2, April 2015
228
order to facilitate the efficient deployment of sensor nodes and development of higher layer
communication protocols for UWCNs to ensure effective and reliable communication.
In this paper, a comprehensive study of the acoustic propagation characteristics and acoustic
channel models are provided with detailed discussions on the design issues and research
challenges for effective communication in underwater environment. This paper is organized into
6 sections as follows: Section 2 outlines some of the existing literature related to the acoustic
channel models, Section 3 discusses the fundamental aspects of ocean acoustics and introduces
the main aspects of the propagation characteristics of the underwater acoustic channel, Section 4
discusses the transmission losses incurred in shallow and deep water channel and ambient noise
in the ocean, Section 5 analyzes the signal to noise ratio at the receiver and Section 6 concludes
this paper highlighting the important considerations for the design of UWCNs for effective
communication.
2. RELATED WORK
The model proposed in [2] is a very simple underwater acoustic channel model to generate a
reliable prediction of the transmission loss that increases in proportion to the acoustic
frequency.Underwater channel models proposed in the literature are simple. The transmission loss
is computed by considering only the effects of spreading effect and absorption effect [3]. The
propagation loss formula combined with a stochastic fading component calculated from two
Gaussian variables is used to compute transmission loss [4]. However, these models do not do not
consider several effects such as multipath, fading, shadow zones, which exist in underwater
environments.
Authors in [5] proposed a Rayleigh fading channel model for shallow water but there is still no
single model available as accepted by the entire research community which is applicable for
shallow waters [6]. In [7], a simple stochastic channel model is proposed and no experimental
results are presented. Moreover, the model does not include acoustic propagation physics, e.g.,
spreading and absorption.. An underwater acoustic channel based on Rice fading model is
introduced in [8] where there can be several propagation paths named Eigen paths and the
Poisson distribution is used to represent the number of Eigen paths reaching a receiver.
Themodelsproposed in [9] are simple deep water acoustic models. These models include acoustic
propagation physics such as spreading and absorption and captures transmission losses due to sea
surface and sea bottom. They do not however consider the real time effect of different
propagation phenomena in the deep underwater such as surface duct, convergence zones, deep
sound channel and reliable acoustic paths.
This paper presents a comprehensive study of underwater acoustic channel modelsbased on the
characteristics of sound propagation due to various modes for shallow and deep water. Shallow
water challenges such as time-varying multipath due to multiple reflections from the sea surface
and the sea bottom are focused and the effects of all existing different propagation phenomena
such as surface reflection, surface duct, bottom bounce, convergence zone, deep sound channel,
reliable acoustic paths in the deep water are analyzed. The research challenges for deployment,
localization and routing schemes for UWCNs are also pointed out based on numerical results.
3. International Journal on Cybernetics & Informatics (IJCI) Vol. 4, No. 2, April 2015
229
3. FUNDAMENTALS OF OCEAN ACOUSTICS
The ocean is an extremely complicated and dynamic acoustic medium with the characteristic
feature of inhomogeneous nature. Regular and Random are two kinds of heterogeneities observed
in the ocean which cause fluctuations in the sound field. Hence, the speed of sound varies with
depth, temperature, salinity, location, time of the day and season. Basically, ocean acoustic
channel is divided into two channels: Shallow water channel and Deep water channel. Shallow
water refers to water column with depth 100m and below whereas deep water refers to water
column with depth above 100m.
3.1. Sound Propagation in the Ocean
The study of sound propagation in the ocean is vital to the understanding of wireless signal
transmission underwater through acoustic channel. Sound propagation in the ocean is influenced
by the physical and chemical properties of the seawater and by the geometry of the channel itself
[10]. Sound propagates in the ocean with variable sound velocity. Sound velocity varies with
variations in temperature, salinity and depth. Variations of the sound velocity are relatively small.
However, even small changes cansignificantly affect the propagation of sound in the ocean.
An empirical formulafor estimating sound velocity as a function of temperature, salinity and
depth is given by Mackenzie and found to be more appropriate [11]:
2 2 4 3 2 7 2
1449 4.591 5.304 10 2.374 10 1.34( 35) 1.63 10 1.675 10− − − −
= + − × + × + − + × + ×c T T T S D D
2 3 3
1.025 10 ( 35) 7.139 10− −
+ × − − ×T S TD (1)
where, ‘c’ is the sound speed expressed in m/s, ‘T’is temperature expressed in ° C, salinity ‘S’is
salinity expressed in parts per thousand (ppt) and ‘D’is depth expressed in meters. Eqn. (1) is
valid for 0° <T ≤30°C; 30 ppt≤ S ≤ 40 ppt; 0≤ D <= 8000m. Figure 1illustrates the Sound
velocity profile. The impact of temperature, salinity and depth upon the sound velocity in the
ocean can be observed in three layers of regions with different depth ranges. First layer region is
from the surface to a depth of 200m from the surface which contains surface layer (0 to 100m)
delimited by red line in the figure and seasonal thermocline layer (100m to 200 m) delimited by
green line. Second layer region is from 200m depth to 1000m depth which contains main
thermocline layer delimited by magenta line. In this layer, sound velocity decreases primarily due
to rapidly decreasing temperature. Third layer is from 1000m depth to ocean bottom which
contains deep isothermal layer. In this layer, temperature becomes almost constant of about
2o
celsius and sound speed increases linearly only due to increase in depth. Sound velocity is
highly variable depending upon the depth, temperature, salinity, season and time of the day. Its
value usually ranges from 1450m/s to 1560m/s [10].
3.2. Propagation Loss of Sound
An underwater acoustic signal experiences attenuation due to spreading, scattering and absorption
[3].
3.2.1. Spreading Loss
4. International Journal on Cybernetics & Informatics (IJCI) Vol. 4, No. 2, April 2015
230
Spreading loss is a measure of signal weakening due to the effect of geometrical spreading when
a sound wave propagates away from the source. . Spherical spreading and Cylindrical spreading
are two kinds of spreading in underwater acoustics: The spreading loss is calculated using the
formula given below [2]:
( )10spreadingPL k log r= (2)
where, PLspreading is the path loss expressed in dB, r is the transmission range in meters and k is the
spreading factor (k = 1 for cylindrical spreading and k = 2 for spherical spreading).
3.2.2. Absorption Loss
The absorption loss represents the energy loss of sound due to the transformation of energy in the
form of heat due to the chemical properties of viscous friction and ionic relaxation in the ocean
and this loss is range-dependent and computed as follows:
3
10α
−
= ×PL rabsorption (3)
where, PLabsorptionis the path loss expressed in dB, r is transmission range in meters and α is the
absorption coefficient in dB/km.
AbsorptionCoefficient
An empirical formula for absorption coefficient has been proposed which varies with frequency,
pressure (depth) and temperature and is valid for frequency range of 100 Hz to 1 MHz [12, 13]. It
is expressed in dB/Km and given as follows:
22 A P f fA P f f 2 2 21 1 1 2A P f [dB/ km]3 32 22 2
21 (3)
(2)(1)
α = + +
++
14243
1424314243
f ff f
(4)
The first term in Eqn. (4) corresponds to the contribution of boric acid, BOH3, the second term
corresponds to the contribution of magnesium sulphate, MgSO4 and the third term corresponds to
the contribution of pure water, H2O to the absorption loss of the acoustic signal in sea water. The
effects of temperature, the ocean depth (pressure) and the relaxation frequencies of boric acid and
magnesium sulphatemoleculesare represented by ‘A’ coefficients , ‘P’ coefficients, and f1, f2
respectively.
5. International Journal on Cybernetics & Informatics (IJCI) Vol. 4, No. 2, April 2015
231
Figure 1.Sound velocity profile Figure 2. Absorption Coefficient
Figure 2 represents the influence of various components and parameters of attenuation. It can be
clearly noted that boric acid is dominant factor in contributing to attenuation coefficient for
frequencies in the range below 1 kHz, for frequency range 1 kHz to 100 kHz magnesium sulphate
and for frequency above 100 kHz pure water contributes more to attenuation coefficient. It can
also be observed that attenuation increases very rapidly with frequency and that the orders of
magnitude are highly variable. For frequencies of 1 kHz and below, attenuation is below a few
hundredths of dB/km and is therefore not a limiting factor. At 10 kHz, attenuation is about 1
dB/km precluding ranges of more than tens of kilometers. At 100 kHz, attenuation reaches
several tens of dB/km and the practical range cannot exceed 1km.
4. TRANSMISSION LOSS
Transmission loss (TL) is defined as the accumulated decrease in acoustic intensity when an
acoustic pressure wave propagates outwards from a source. The magnitude is estimated by the
sum of the magnitudes of geometrical spreading loss and absorptionloss. The TL value can be
useful in determining the arriving signal strength of a data stream and even the minimum required
signal strength necessary to successfully complete a transmission within an underwater wireless
acoustic network.
4.1. Transmission Loss in Shallow Water (Direct Path Model)
Acoustic signals in shallow water propagate within a cylinder bounded by the surface and the sea
floor resulting in cylindrical spreading. The transmission loss caused by cylindrical spreading and
absorption can be expressed as follows [2]:
3
10 10TL log r rα
−
= + × (5)
where, TL is the transmission loss expressed in dB, α is the absorption coefficient expressed in
dB/km and r is the transmission range in meters.
10
2
10
3
10
4
10
5
10
6
10
7
10
-6
10
-4
10
-2
10
0
10
2
10
4
10
6
Frequency(Hz)
Absorptioncoeffient(dB/Km)
Purewater
Mgso4
boricacid
Absorption coefficient(sum of above components)
1480 1500 1520 1540 1560 1580 1600 1620 1640 1660 1680
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
sound speed (m/s)
depth(m)
6. International Journal on Cybernetics & Informatics (IJCI) Vol. 4, No. 2, April 2015
232
(a)
(b)
Figure 3.TL as a function of distance and frequency
(a) Direct path modelfor shallow water (b) Direct path model for deep water
Figure 3 (a) represents the total transmission loss in shallow water as a function of distance for
different frequencies. It can be easily observed from the figure that inferred that transmission to
larger distances requires low frequencies and at low frequencies, cylindrical spreading is the most
important factor affecting TL because it is not frequency dependent.
4.2. Transmission Loss in Deep Water (Direct Path Model)
Deep water is considered to be a homogeneous unbounded medium and the transmission loss is
caused due to spherical spreading and absorption. The transmission loss caused by spherical
spreading and absorption can be expressed as follows [2]:
3
0 102TL log r rα
−
= + × (6)
where TL is the transmission loss expressed in dB, α is the absorption coefficient expressed in
dB/Km and r is the transmission range in meters.
Figure 3 (b) represents the total transmission loss in deep water as a function of distance for
different frequencies. It can be well understood from the figure that transmission to larger
distances requires low frequencies and at low frequencies, spherical spreading is the most
important factor affecting TL because it is not frequency-dependent. The TL values in deep water
are larger than in shallow water for low frequencies or low transmission distances because the
spreading term dominates. TL in deep water is lower than TL in shallow water for large distances
and higher frequencies since the absorption losses are the major cause of TL and they diminish
with depth. Hence, it is clearly inferred that effective communication is possible when
transceivers are located in deep water.
4.3 Transmission Loss in Shallow Water (Multipath Model)
Sound propagates to a distance in shallow water by repeated reflections from the surface and
bottom resulting in multipath propagation [14]. Transmission loss calculations were completed
using frequency dependent acoustic algorithms based on the semi-empirical step model of H.W.
Marsh and M. Schulkin. The following equation is used when r, the horizontal separation distance
0 200 400 600 800 1000 1200
0
100
200
300
400
500
600
700
800
900
1000
Distance(m)
Frequency(kHz)
50
100
150
200
250
300
350
400
0 200 400 600 800 1000 1200
0
100
200
300
400
500
600
700
800
900
1000
Distance(m)
Frequency(KHz)
50
100
150
200
250
7. International Journal on Cybernetics & Informatics (IJCI) Vol. 4, No. 2, April 2015
233
between sound source and receiver is up to 1 times H, which for the purposes of this analysis was
conservatively defined as the average water depth of the acoustic study area [15]:
20 60 –TL logr r k
L
α= + + (7)
where,
r = horizontal separation distance between sound source and receiver (kilometers)
H = skip distance(in km), defined as the maximum transition range at which rays make contact
with either the surface or bottom and calculated as:
( )1/3H d z= + (8)
where,
d = mixed layer depth (m), z - water depth (m), α = shallow water absorption coefficient
(dB/kilometer) and kL= near-field anomaly. The intermediate (or transition zone) is defined
for H ≤ r ≤ 8H where modified cylindrical spreading occurs accompanied by mode stripping
effects. The transmission loss equation representing this intermediate range is given as follows
[15]:
( )15 / –1 5 60TL logr r r H logH k
T L
α α= + + + + − (9)
where, αT = shallow water attenuation coefficient.
Figure 4. Transmission loss for various frequencies(Multipath model for shallow water)
Long range TL occurs where r > 8 H. Due to the boundaries of the sea surface and sea floor,
sound energy is not able to propagate uniformly in all directions from a source indefinitely;
therefore, long range TL is represented as cylindrical spreading, limited by the channel
boundaries. Cylindrical spreading propagation is applied using the equation given below [15]:
( )10 / –1 10 60α α= + + + + −TL logr r r H logH k
T L
(10)
where, αT= shallow water attenuation coefficient (dB).
The near-field anomaly (kL) and shallow water attenuation coefficient (αT) are functions of
frequency, sea state, and bottom composition and their values are found in [2]. The anomaly term
is related to the reverberant sound field developed near the source by surface and bottom reflected
sound energy resulting in an apparent increase in source levels. The shallow water attenuation
0 1 2 3 4 5 6 7
40
60
80
100
120
140
160
180
200
220
Distance(Km )
Transmissionloss(dB)
f=0.1
f=0.2
f=1
f=2
f=4
f=10
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234
coefficient is an empirically determined factor related to sound scattering and other losses at
water column boundaries.
Transmission loss in shallow water (multipath) with a bottom composition of sand and a sea state
1 is shown in Figure 4. It is clearly noted that TL increases with increasing frequency and
distance. When compared with single path model, multipath model results in higher transmission
loss due to reflections.
4.4. Transmission Loss in Deep Water (Multipath Model)
Sound propagates in deep water to a distance due to six propagation phenomena as detailed below
resulting in multipath propagation. TL calculations for each category are derived at each different
propagation path.
4.4.1. Surface Reflection
The loss on surface reflection as a function of the angle of incidence to the horizontal can be
calculated using the Beckmann-Spizzichino model as follows [16]:
( )
( )
( )( )( )
21 / 1
10 – 1 90 /60 /30
21 2
2
/
θ
+
−
= +
+
f f
TL log wSR
f f
(11)
where, 2
1 2 210 , 378f f f w−
= = , w-wind
speed(m/s).
The total transmission loss as a result of surface reflection for near-surface source and receiver
can be computed as [16]:
3
20 10α −
= + × + SRTL log r r TL , (12)
where, r - transmission range (m) and α – attenuation coefficient of sea water (dB/km).
Figure 5(a) represents TL due to surface reflection as a function of frequency by the curve of
blue color.
4.4.2. Surface Duct
Sound emanating from a source in isothermal layer is prevented from spreading in all directions
and is confined between the boundaries of the mixed sound channel. This propagation
phenomenon is called surface duct. Transmission loss due to surface duct can be computed as
follows [3]:
( ) 3
20 10α α −
= + + ×LTL log r r ,
( )2
350r H short ranges< (13)
( ) 3
10 10 10 ,α α −
= + + + ×o LTL log r log r r ( )2
350>r H long ranges (14)
10 ݈ ݎ ݃ = 20.9 + 5݈ܪ ݃, (15)
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235
( )
( )
1/2
26.6 1.4
1452 3.5
S
L
H
f
T
α =
+
(16)
where, S = sea state number and T = temperature (degree Celsius) H = mixed layer depth (m)
.
Figure 5(a) represents TL due to surface duct as a function of frequency by the curve of green
color. It can very well be inferred that transmission to medium distances is possible with
moderate transmission loss.
4.4.3. Bottom Bounce
This is the propagation phenomenon due to sound reflection from the sea floor at grazing angles
to a plain boundary between two fluids of different densities ( ρ1 – density of sea water and ρ2 –
density of sea water with sediment ) and sound velocities (c1 – sound velocity in pure water and c2
– sound velocity in sea bottom with sediment). The bottom bounce loss can be computed as
follows [3]:
2 2 1/2
1 1
2 2 1/2
1
2
1
( ( )–
1
( (
0
– )
θ θ
θ θ
=
−
−
BB
msin n cos
TL log
msin n cos
(17)
where, m = 2
1
ρ
ρ
and n = 1
2
c
c
and 1θ = Grazing angle.
The values of m and n for different sediment types in sea bottom are found in [12]
The total transmission loss as a result of bottom bounce for a near-bottom source and receiver can
be computed as [3]:
3
20 10α −
= + × + BBTL log r r TL (18)
Figure 5(b) represents TL due to bottom bounce as a function of frequency by the curve of red
color. It can very well be seen that TL due to bottom bounce is much higher indicating that this is
to be avoided. Hence, it is always advisable to avoid deploying the transceivers near sea floor in
underwater communication networks.
4.4.4. Convergence Zone
Convergence zone is formed as a result of the propagation of sound from a source located near
the surface. In deep water, the sound rays are bent downward as a result of the negative speed
gradient forming regions of convergence zone when the upper ray of the sound beam becomes
horizontal. The depth at this point is called the critical depth. The water column depth must be
greater than the critical depth for the existence of convergence zones. The total transmission
loss for the signal within a convergence zone is computed as follows [17]:
3
20 10 – _α −
= + ×TL log r r CZ gain , (19)
where, CZ_gain refers to the convergence zone gain that can be obtained numerically [17]. The
values of CZ_gain are usually found to be in the range 5dB-20 dBFigure 5(a) represents TL due
10. International Journal on Cybernetics & Informatics (IJCI) Vol. 4, No. 2, April 2015
236
to convergence zone as a function of frequency by the curve of magenta color.It can be inferred
that transmission loss is lower within convergence zone indicating that underwater
communication gets improved.
4.4.5. Deep Sound Channel
The deep sound channel or SOFAR (Sound Fixing and Ranging) is formed along the axis where
the sound speed is minimum. The propagation to long ranges is possible if the source and receiver
are located below or above near the deep sound channel axis. The total transmission loss for the
deep sound channel model is computed as follows [3]:
3
10 10 10α −
= + + ×oTL log r log r r , (20)
where, ro is the transition from cylindrical to spherical spreading and is calculated by:
1/2
8
s z
o
s
r D
r
Z
=
, (21)
where, rs is the skip distance, Ds is the axis depth and zs is the source depth.
Figure 5(a) represents TL due to deep sound channel as a function of frequency by the curve of
cyan color. It can be clearly noted from the figure that transmission to long ranges are possible
with low transmission loss.
4.4.6. Reliable Acoustic Path
When the sound propagates from a deep source to shallow receiver, transmission to moderate
distances takes place through the reliable acoustic path. The path is reliable since it does not get
affected by the reflection from the surface or from the ocean bottom. The transmission loss
for this model can be computed as follows [18]:
3
20 10α −
= + ×TL log r r
(22)
Figure 5(a) represents TL due to reliable acoustic path as a function of frequency by the curve of
black color. It can be well understood that the graph is similar to that of direct path model due to
the fact that the surface and the bottom reflections do not affect the transmission signal.
(a) (b)
Figure 5. TL for deep water multipath models
(a) TL due to SR, SD, CZ, DSC, RAP (b) TL due to bottom bounce
10 20 30 40 50 60 70 80 90 100
40
60
80
100
120
140
160
180
200
Frequency(kHz)
Transmissionloss(dB)
SR
SD
CZ
DSC
RAP
10 20 30 40 50 60 70 80 90 100
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
5.5
x 10
4
Frequency(kHz)
Transmissionloss(dB)
BB
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237
4.5. Ambient Noise
Ambient noise is an important underwater acoustic characteristic of the ocean. Ambient noise
contains the amount of information concerned with atmosphere of the ocean, sea state of the
ocean, wind speed and marine biological effects. Four basic sources model the different
dominating levels of ambient noise in the ocean. They are: turbulence, waves, shipping and
thermal noise. The overall power spectral density of the ambient noise is expressed in dB and is
given by [19]:
NL NLNL NL NL
tb sh wv th
= + + + (23)
where,
27 – 30 ,NL log f f in KHz
tb
=
,
0.5
50 7.5 20 40 0.(f 4)= + + − +NL w log f log
wv
( ) ( )40 20 –0.5 26 60 0.03= + + − +NL s logf log f
sh
25 20NL log f
th
= − +
w – windspeed (m/s) and s – shipping activity factor
Figure 6 represents the total noise level and the noise levels contributed by different sources of
turbulence, shipping, waves and thermal noise. It can be inferred that the turbulence noise is the
dominant factor for frequencies below 20 Hz, distant shipping is the dominant factor for
frequencies in the range from 20 Hz to 200 Hz, surface motion caused by wind-driven waves is
the dominant factor for frequencies in the range from 200 Hz – 200 kHz and thermal noise is the
dominant factor for frequencies above 200 kHz.
Figure 6. Ambient Noise vs Frequency
10
-3
10
-2
10
-1
10
0
10
1
10
2
-80
-60
-40
-20
0
20
40
60
80
100
120
Frequency(kHz)
NoiseP.S.D.(dB)
Turbulent noise
Shipping noise
Waves driven noise
Thermal noise
Total noise level
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238
5. SIGNAL TO NOISE RATIO (SNR)
(a)
(b)
Figure 7. Signal-to-Noise Ratio as a function of frequency
(a) for shallow water model (b) for deep water model
(b)
The SNR of an underwater acoustic signal at a receiver can be computed in dB by the passive
sonar equation [6] as follows:
SNR SL TL NL DI= − − − (24)
where,
NL is the ambient noise level in ocean (dB), TL is the transmission loss (dB),
DI is the directivity index and is set to zero and SL is the source level of transmitter (dB) given
by,
1( )8
10
0.67 10
It
SL log
x −
=
(dB), where tI is the transmission power intensity (25)
In shallow water, the intensity, tI is given in Watts/m2
as follows:
2 1
t
t
P
I
m zπ
=
× × ×
(26)
In deep water, tI ,is given in Watts/m2
as follows:
4 1
t
t
P
I
m zπ
=
× × ×
, where, tP is the transmitter power (Watt) and z is the depth (m). (27)
The relationship between SNR and frequency for shallow water are shown in Figure 7(a). SNR
increases with increasing transmission power. The optimal frequency for which the maximum
SNR can be achieved in shallow water is 20 kHz. The relationship between SNR and frequency
for deep water are shown in Figure 7(b). SNR increases with increasing transmission power. The
optimal frequency for which the maximum SNR can be achieved in deep water is 20 kHz.
10 20 30 40 50 60 70 80 90 100
19.8
19.9
20
20.1
20.2
20.3
20.4
20.5
20.6
20.7
Frequency(KHz)
Signal-to-Noise-Ratio(dB)
Pt=2w
Pt=3w
Pt=4w
10 20 30 40 50 60 70 80 90 100
17.2
17.4
17.6
17.8
18
18.2
18.4
Frequency(KHz)
Signal-to-Noise-Ratio(dB)
Pt=30w
Pt=40w
Pt=50w
13. International Journal on Cybernetics & Informatics (IJCI) Vol. 4, No. 2, April 2015
239
6. CONCLUSION
Based on the study of acoustic propagation characteristics, underwater acoustic channel models
for each mode of propagation in deep water and shallow water have been presented.Our study on
channel models shows that attenuation increases with frequency, long range systems have low
bandwidth and short range systems have high bandwidth. The distance between transceivers and
the requirements of specific applicationsdetermine the desired communication range. The ambient
noise is dependent on selected frequency. Of all the six basic propagation phenomena of sound in
deep water, TL is very much lower within the convergence zone providing the suggestions for the
optimal deployment of source and receiver nodes in underwater communication networks. Also,
SNR for both the cases are thoroughly analyzed. The optimal frequency for which maximum
SNR value can be achieved is found to be 20 kHz in shallow water and deep water as well. The
numerical results obtained through analytical simulations carried out in this paper facilitate the
researchers and scientists to develop higher layer communication protocols for UWCNs to
guarantee for effective and reliable communication.
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AUTHORS
S. Anandalatchoumy receivedB.Tech. degree in 2006 and M.Tech in 2010 in Electronics
and Communication Engineering from Pondicherry University, India. She has 5 years in
teaching experience. She is currently working as Senior Assistant Professor in the
Department of Electronics and Communication Engineering, Christ college of Engineering
and Technology, Pondicherry, India. She is currently pursuing her Ph.D. degree in
Pondicherry Engineering College. Her areas of interest are Wireless communication and
Sensor Networks.
G. Sivaradje received B.E degree from University of Madras in 1991 and M.Tech. in 1996
in Electronics and Communication Engineering and Ph. D degree from Pondicherry
University, India in 2006. He has 16 years in teaching and 4 years of industrial experience.
He is currently working as Professor in the Department of Electronics and Communication
Engineering, Pondicherry Engineering College, Pondicherry, India. He has 16 Publications
in reputed International and National Journals and published research papers more than 50 in
International and National Conferences. His areas of interest are Wireless Networking and
Image Processing.