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ES4C4 Optical Communication Systems
Prepared by Dr Mark Leeson (Module Leader)
E-mail: [email protected]
Alternative Assessment to Summer Examination 2020
The coronavirus crisis has created a period of extraordinary teaching and learning conditions that
means to complete your year of studies we are to have this alternative assessment to replace part or
all of the ES4C4 summer examination, which is for 4.5 credits (30% of module 15 credits).

In addition, you will be required to take a 1-hour Perception Test; details will be shared on Moodle

Alternative online support for this module is available:
For technical queries, please email the relevant staff member (Mark Leeson or Tianhua Xu) depending
on the section of the module and we will respond within two working days. For general queries about
the operation of the module please contact the Module Leader.

The Learning Outcomes for this written assessment are:

1. Exhibit insight into emerging technologies in optical wireless systems.
2. Demonstrate advanced understanding of optical receiver signals and bit errors.

Alternative Assessment - Underwater Optical Wireless Communications

1. Introduction
A significant portion of the earth’s surface is covered with water and the ocean represents one of the
ultimate frontiers for exploration, science, and technology. There has been a growing interest in
ocean exploration system research in recent years due to the increasing global climate change and
resource depletion. Although radio frequency (RF) waves through air/water interfaces is relatively
seamless and RF is tolerant to turbidity and water turbulence, it has significant drawbacks. RF can
only propagate a few metres in seawater at extremely low frequencies due to the conductive nature
of the transmission medium. This short range, coupled with high costs, significant energy-
consumption and a need for extremely large transmission antennas makes RF and unattractive
option for underwater communications. Acoustic waves are the most established technology that is
currently responsible for most underwater wireless communication (UWC) systems because of their
ability to cover long distances. However, the transmission data rate is relatively low since its typical
frequencies are between tens of Hz and hundreds of kHz. Acoustic links also suffer from severe
communication delays due to the slow propagation of sound waves in water; moreover, acoustic
transceivers are generally costly, bulky and consume much energy. The technology can also
negatively impact marine life that uses sound waves to perform navigation and communication.
Thus, underwater optical wireless communications (UOWC) has become a possible and attractive
alternative or complementary solution to achieve higher data rates, higher communication security,
energy efficiency and lower implementation costs.
This assignment offers an introduction to the modelling of UOWC links using a simplified approach in

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2. Theoretical Background
Light in the blue-green portion of the spectrum propagates best underwater, this is a wavelength
range of approximately 450 nm to 550 nm. Understanding light propagation in water is challenging
due to the difference in the fundamental components of the various water bodies and demands
fundamental understanding of the physio-chemical underwater environment. The optical properties
of water are divided into two groups [1]: inherent optical properties (IOPs) and apparent optical
properties (AOPs). The former depend only on the composition of the medium and the particulate
substances within it, whereas the latter depend on both the medium and the geometric illumination
structure. The major IOPs are scattering coefficient, absorption coefficient, attenuation coefficient
and volume scattering function; the main AOPs are irradiance, radiance, and reflectance. In UOWC,
the IOPs have greater effect on the communication link performance and are the focus of the
coverage here.

2.1. Optically Important Ocean Constituents
Substances contained in the aquatic medium are classified as either dissolved (with particle
diameters < 0.4 µm) or particulate matter. The main optical components are [1]:

• Sea Water: comprises pure water and inorganic dissolved materials, which are not surprisingly
mostly salts.
• Particulate Organic Material: includes many organisms, of which phytoplankton are the most
optically important.
• Dissolved Organic Material: consists of decaying marine matter and broken-down plant tissue.
• Inorganic Particles: clays, sands, rocks that have been blown or washed from land into the
ocean, as well as metal oxides and minerals.

The properties of different water bodies vary with the concentration of dissolved substances and
geographical location. There are four different water types considered in UOWC:
• Pure seawater: Absorption is the main restriction; it is the sum of that in pure water without
suspended particles and that by salts in pure saltwater.
• Clear ocean: This has a higher concentration of dissolved particles; there is classification into
Jerlov water types [2], depending on geography and suspended particle concentration.
• Coastal water: The effect of scattering and absorption increases as there is a higher
concentration of dissolved particles and hence increased turbidity.
• Turbid harbour water: Optical propagation is limited by high absorption and scattering from
the high concentration of suspended and dissolved particles.

The physical properties of the ocean also vary with depth but that is not considered here – refer to
Apel [2] for details.

2.2. Attenuation
The two major factors that determine underwater light attenuation are absorption and scattering.
Their impact can cause three undesirable effects to UOWC system design. Firstly, the total light
propagation energy will diminish continuously due to absorption which will reduce the UOWC link
distance. Secondly, scattering will result in a reduction of the number of photons collected by the
detector, which degrades the system signal to noise ratio given the finite size of the receiver optical

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aperture. Thirdly, scattering may cause photons to arrive at the detector plane in different time slots,
leading to dispersion. The overall absorption and scattering coefficients of sea water, respectively
() and (), are found from the sum of the various optical components multiplied by each of their
concentrations [2]. These are then combined to form the overall beam attenuation coefficient, (),
(with units of m-1) thus:

() = () + () (1)

2.3. Power Loss
As discussed above, both absorption and scattering prevent a photon from reaching a receiver after
passing through an underwater channel. These two processes are basically responsible for the decay
of the transmitted power as the photon beam propagates through water. The most basic modelling
scheme of IOPs encapsulates this power loss and it is combined with the Beer-Lambert (BL) law to
give an expression for the received power in terms of the power at the source (0) after a specified
distance () [3]:

= 0 exp[−()] (2)

This does neglect any scattered photons that eventually reach the receiver and is only valid for line-
of-sight links [Error! Reference source not found.].

3. Assignment Tasks
You are to investigate a UOWC line-of-sight link using MATLAB (and Excel if you wish for some
plots, although it can all be done in MATLAB). This will be a simplified version of a full analysis
and you will also need to think about the implications of including other factors in your design.

(a) You are provided with the function “fwaterT(lambda,WaterType).m” that takes as its
arguments the wavelength in nm (lambda) and the type of water (WaterType). This
returns the value of () from (1), which can then be used in (2) to work out
approximately how much power arrives at the receiver. Thermal noise dominates the
performance because background light does not propagate very far in the water. Obtain
the OOK BER curve of pure water (set “WaterType” to 0) as a function of distance over a
suitable length range (try around 400 m to 1500 m initially) at a bit rate of 100 kbps using
an input power of 40 dBm and a wavelength of 532 nm. Assume that the receiver has a
noise equivalent bandwidth of half the bit rate, contains an ideal amplifier with an ideal
photodiode, presents an effective resistance of 1 kΩ and operates at a temperature of
280K. Then, estimate the distance over which a BER of 10-6 can be achieved.

(b) Change the wavelength of operation to one determined by running the function
“fstudentwl(ID).m” that is provided and replacing “ID” with your student number. Then
repeat part (a), plotting the two BER curves on the same graph and again estimating the
distance over which a BER of 10-6 can be achieved. Note that you can adjust the distance
of transmission to obtain satisfactory plots in this and subsequent parts.

(c) Increase the bit rate to 1 Mbps and estimate the distance over which a BER of 10-6 can
now be achieved for both the wavelengths above.

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(d) Choose another water type (you can see what they are by typing “help fwaterT” once you
have the function in your MATLAB path). Plot suitable BER curves over appropriate
distances at 100 kbps and 1 Mbps then estimate the distances over which a BER of 10-6
can be achieved for both the wavelengths previously used.

(e) Provide a short (approximately half-page) discussion and summary of your conclusions to
include aspects that could affect the model and are neglected.

(f) Produce a brief review of underwater optical wireless communications; this can focus on
one or more aspects and be around 1-page long.

4. References
1. C. D. Mobley, Light and Water: Radiative Transfer in Natural Waters, San Diego: Academic Press,
2. J. R. Apel, Principles of Ocean Physics, London: Academic Press, 1987.
3. N. G. Jerlov, Marine Optics, Amsterdam: Elsevier, 1976.
4. B. M. Cochenour, L. J. Mullen and A. E. Laux, "Spatial and temporal dispersion in high bandwidth
underwater laser communication links," MILCOM 2008 - 2008 IEEE Military Communications
Conference, San Diego, CA, 2008, pp. 1-7.

Submission Guidance
Maximum length: 3 pages, with up to 1 page for figures and tables.
Format: 12-point Calibri font and with 1.5 line spacings.
References should be included as needed and your MATLAB code should be added as an appendix.

Submit this assignment on Tabula in pdf format by 12:00 noon on 16 June 2020 (Week 38).
When submitting your pdf assign to the document the filename identifier of ES4C4-student id–2020,
where ‘student id’ is for your university student number.
There cannot be a hard copy submission.
A late submission (without a legitimate mitigating reason) will be subject to the normal School of
Engineering late submission penalties.

Your assignment will be checked for plagiarism using the Turnitin software and should there be
evidence of direct copying from another source you will be liable to a reduction in your mark which
could result in a mark of zero.

Assessment Criteria

This assignment is to be marked out of 100.

Marks will be allocated:

Basic Model Operation 40%
Discussion and Conclusions 20%
Review Section 30%
Presentation 10%

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Final Note

This written assignment replaces all or part of a 2020 summer examination; therefore, it will follow
standard assessment processes regarding how it is marked for cheating and plagiarism.

Individual feedback will not be provided and neither will a solution be made available. Standard
examination feedback will be provided after the summer.

This assignment will be moderated following normal examination procedures and scrutinised by
External Examiners.

Gill Cooke 03 April 2020




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