coherent passive optical networks for 5g transport · building low-latency and high-capacity...
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Coherent Passive Optical Networks for 5G
Transport
من لتراسل الجيل الخامس رابطةالمتالشبكات الضوئية الكامنة االتصاالت الخلوية
By
Waseem W. Shbair
Supervised by
Prof. Fady El Nahal
Professor of Electrical Engineering
A thesis submitted in partial fulfilment
of the requirements for the degree of
Master of Electrical Engineering
January/2019
زةــــغب ةــالميــــــة اإلســـــــــامعـالج
البحث العلمي والدراسات العليا عمادة
الهندســـةة ـــــــــــــــــــــــــــــــليـــــك
الهندسة الكهربائيةتير ــــــــــــــماجس
The Islamic University of Gaza
Deanship of Research and Graduate Studies
Faculty of Engineering
Master of Electrical Engineer
I
إقــــــــــــــرار
أنا الموقع أدناه مقدم الرسالة التي تحمل العنوان:
Coherent Passive Optical Networks for 5G
Transport
الشبكات الضوئية الكامنة المترابطة لتراسل الجيل الخامس من االتصاالت الخلوية
الخاص، باستثناء ما تمت اإلشارة إليه حيثما ورد، وأن أقر بأن ما اشتملت عليه هذه الرسالة إنما هو نتاج جهدي
لنيل درجة أو لقب علمي أو بحثي لدى أي مؤسسة االخرين هذه الرسالة ككل أو أي جزء منها لم يقدم من قبل
تعليمية أو بحثية أخرى.
Declaration
I understand the nature of plagiarism, and I am aware of the University’s policy on
this.
The work provided in this thesis, unless otherwise referenced, is the researcher's own
work, and has not been submitted by others elsewhere for any other degree or
qualification.
:Student's name وسيم وليد شبيرم. اسم الطالب:
التوقيع:Signature:
:22nd of Dec, 2018 Date التاريخ:
III
Abstract
Building low-latency and high-capacity optical networks is very important issue,
especially when new high-speed cellular technologies is about to come.
There are different ways to build such networks. One of the most reliable networks
that can be rely on for such an application, is the coherent wavelength division
multiplexing (WDM) passive optical networks (PON). In this research a modified
scheme simulated using dual-polarization quadric phase-shift keying (DP-QPSK)
transceiver.
The aim of new scheme is to build an 800 Gbps network with excellent readings in bit
error rate in downlink and uplink respectively. This network will be used in the
construction of the transport architecture of fifth generation (5G) of cellular networks
either in mobile front haul (MFH) or mobile back haul (MBH).
The results verify that the modified topology of coherent WDM DP-QPSK PON using
100 km span of single mode fiber (SMF) is very adequate for 5G MFH and MBH
requirements. BER of the analyzed scheme was very close to the back-to-back model.
Also, resulted constellation diagrams indicates an error-free transmission can be
achieved.
IV
ملخص الدراسة
يعد بناء الشبكات األلياف الضوئية ذات السرعة العالية والقدرات االستيعابية العالية مسألة مهمة للغاية ، خاصة
.عندما تكون التقنيات الخلوية الجديدة عالية السرعة على وشك المجيء
األكثر موثوقية والتي يمكن االعتماد عليها لمثل هناك طرق مختلفة لبناء مثل هذه الشبكات. واحدة من الشبكات
هذا التطبيق ، وهي شبكات األلياف الضوئية المترابطة والتي تعمل بتقنية األطوال الموجية المقسمة. في هذا
البحث ، تم تطوير مخطط معدل باستخدام تقنية تحويل الطور الرباعي ثنائي االستقطاب ومحفز في الوصلة
.لخاصة بالتنزيلا
جيجابت في الثانية مع قراءات ممتازة في معدل أخطاء 800يهدف المخطط الجديد إلى إنشاء شبكة بسرعة
. سيتم استخدام هذه خاصة بالتحميلوتحقيق قياسات هامة في الوصلة ال خاصة بالتنزيلالبتات في الوصلة ال
في أو الشبكة األمامية لتراسل المحطات من الشبكات الخلوية سواء في امس الشبكة في بناء بنية النقل للجيل الخ
.الشبكة الخلفية لتراسل المقاسم
لشبكة األلياف الضوئية المترابطة والتي تعمل بتقنية األطوال الموجية المقسمة أن الهيكل المعدل ائجالنتؤكد ت
كيلومتر من 100 وتقنية تحويل الطور الرباعي ثنائي االستقطاب ومحفز في الوصلة الخاصة بالتنزيل لمسافة
النقل في الجيل الخامس من الشبكات الخلوية سواء في الشبكة يكون كافيا جدا لمتطلبات األلياف أحادية النمط
في المخطط الذي تم تحليله قريبا جدا من (BER) وكان معدل الخطأ في البتات األمامية أو في الشبكة الخلفية.
كذلك ، فإن مخططات الكوكبة الناتجة تشير إلى إمكانية تحقيق إرسال خالي النموذج المترابط )بدون الفايبر(.
.من األخطاء
V
Epigraph page
لم عليم ن نشاء وفوق كل ذي ع نرفع درجات م
(76اآلية –)سورة يوسف
VI
Dedication
To my mother, who encourages me to do my best.
To my father, who inspires me by his passion for knowledge.
To my wife and kids, who support me and give hope.
VII
Acknowledgment
First and the foremost, I would like to thank Almighty Allah for bestowing His
blessings upon me and giving the strength to carry out and complete this work.
I am extremely grateful to my supervisor Dr. Fady El Nahal for his valuable
advice, guidance, beneficial discussions and encouragement throughout my research.
Apart from his valuable academic advice and guidelines, he has been extremely kind,
friendly, and helpful. I am also very grateful to my thesis committee members, Dr.
Talal Skaik and Dr. Mohammed El Astal for their care, cooperation and constructive
advices.
I would like to give my special thanks to my parents, wife, and kids for their
support, patience and love. Without their encouragement, motivation and
understanding, it would have been impossible for me to complete this work. Finally,
my sincere thanks are due to all people who supported me to complete this work.
VIII
Table of Contents
Declaration .................................................................................................................. I
Judgement .................................................................................................................. II
Abstract ..................................................................................................................... III
Epigraph page ............................................................................................................ V
Dedication ................................................................................................................. VI
Acknowledgment ..................................................................................................... VII
Table of Contents .................................................................................................. VIII
List of Tables ........................................................................................................... XII
List of Figures ........................................................................................................ XIII
List of Abbreviations .............................................................................................. XV
Chapter 1 Introduction ......................................................................................... 2
1.1 Background and Context ................................................................................... 2
1.2 Scope and Objectives ........................................................................................ 3
1.3 Significance ....................................................................................................... 4
1.4 Limitations ........................................................................................................ 4
1.5 Overview of Thesis ........................................................................................... 4
Chapter 2 Background ......................................................................................... 7
2.1 Introduction ....................................................................................................... 7
2.2 Optical communication system ......................................................................... 8
2.2.1 Introduction ................................................................................................ 8
2.2.2 Optical Transmitter .................................................................................... 8
2.2.3 Fiber link .................................................................................................... 9
2.2.4 Optical Receiver ...................................................................................... 10
IX
2.3 Overview of PON technologies ...................................................................... 11
2.3.1 Introduction .............................................................................................. 11
2.3.2 High-speed PONs .................................................................................... 13
2.3.3 Low-latency TDM PONs ......................................................................... 14
2.3.4 WDM PONs ............................................................................................. 14
2.4 Overview of 5G transport ............................................................................... 16
2.4.1 Introduction .............................................................................................. 16
2.4.2 5G Prospects ............................................................................................ 17
2.4.3 5G Challenges .......................................................................................... 17
2.4.4 Concept of 5G transport architecture ....................................................... 18
2.4.5 Bandwidth and latency requirements ....................................................... 20
2.4.6 Deployment scenarios .............................................................................. 21
2.5 Summary ......................................................................................................... 22
Chapter 3 Methodology ...................................................................................... 25
3.1 Introduction ..................................................................................................... 25
3.2 Coherent Detection ......................................................................................... 26
3.2.1 Introduction .............................................................................................. 26
3.2.2 Fundamental concept ............................................................................... 27
3.2.3 Homodyne detection ................................................................................ 29
3.2.4 Heterodyne detection ............................................................................... 29
3.3 Modulation Technique .................................................................................... 30
3.3.1 Homodyne schemes ................................................................................. 31
3.3.1.1 OOK Homodyne system ..................................................................... 31
3.3.1.2 PSK Homodyne system ....................................................................... 32
X
3.3.2 Heterodyne schemes ................................................................................ 33
3.3.2.1 OOK Heterodyne system .................................................................... 34
3.3.2.2 PSK Heterodyne system ...................................................................... 34
3.3.2.3 FSK Heterodyne system ...................................................................... 35
3.4 Summary ......................................................................................................... 36
Chapter 4 Topology, Results and Discussion.................................................... 39
4.1 Introduction ..................................................................................................... 39
4.2 Scheme topology ............................................................................................. 40
4.2.1 TRx structure ........................................................................................... 42
4.2.2 Wavelength spectrum .............................................................................. 43
4.3 Results and discussion .................................................................................... 43
4.3.1 Introduction .............................................................................................. 43
4.3.2 The 100 km span of SMF model results .................................................. 46
4.3.2.1 Wavelengths spectrum of the SMF model .......................................... 46
4.3.2.2 Constellation diagram of the SMF model ........................................... 47
4.3.2.3 BER of SMF model ............................................................................. 51
4.3.2.4 Power budget of SMF model .............................................................. 52
4.3.3 Back-to-Back model results ..................................................................... 52
4.3.3.1 Constellation diagram of B-to-B model .............................................. 53
4.3.3.2 BER of B-to-B model .......................................................................... 53
4.3.4 Comparison of B-to-B and 100 km SMF results ..................................... 54
4.3.5 Comparison of 100 km SMF downlink vs uplink BER results ............... 55
4.3.6 Comparison of 100 km vs 80 km SMF downlink BER results ............... 56
1.2 Summary ......................................................................................................... 57
XI
Chapter 5 Conclusions and Future Work......................................................... 59
5.1 Conclusions ..................................................................................................... 59
5.2 Future Work .................................................................................................... 60
The Reference List .................................................................................................... 61
Appendix 1 OptiSystem tool ................................................................................. 63
Appendix 2 Technical Background of OptiSystem elements ........................... 67
XII
List of Tables
Table (2.1): 5G Transport bandwidth and latency requirements (Wey & Zhang, 2018)
................................................................................................................................... 21
Table (3.1): Summary of photon numbers required for a 10-9 BER by an ideal
receiver having a photodetector with unity quantum efficiency ................................ 35
Table (4.1): InGaAs wavelength spectrum used for up/down streams ...................... 43
Table (4.2): Parameter values for devices used in Optisystem layout ....................... 44
Table (4.3): Simulated results for up/down stream BER (dB) in the 100 km SMF
span ............................................................................................................................ 51
Table (4.4): Summary of Simulated loss budget ....................................................... 52
Table (4.5): Simulated results for downstream BER in B-to-B case ......................... 54
XIII
List of Figures
Figure (1.1): Bandwidth demand (in red) for 5G MFH/MBH based PON technology 3
Figure (2.1): Optical Communication System ............................................................. 8
Figure (2.2): Schematic of a conventional silica fiber structure .................................. 9
Figure (2.3): PON architecture .................................................................................. 11
Figure (2.4): Main 5G challenges (Light, 2015) ........................................................ 18
Figure (2.5): Network elements for 4G/LTE and 5G-NR (Top) and signal processing
function chain (bottom) ............................................................................................. 19
Figure (2.6): 5G Deployment scenarios ..................................................................... 21
Figure (3.1): Fundamental concept of a coherent light-wave system (Keiser, 2011) 27
Figure (3.2): Fundamental setup of a homodyne receiver (Keiser, 2011) ................. 31
Figure (3.3): Homodyne receiver techniques comparison with unity quantum
effeciency ................................................................................................................... 32
Figure (3.4): General heterodyne receiver configurations. (a) Synchronous detection
uses a carrier-recovery circuit. (b) Asynchronous detection uses a one-bit delay line
(Keiser, 2011) ............................................................................................................ 33
Figure (3.5): Heterodyne detection comparison of various modulation techniques. (a)
synchronous (b) asynchronous ................................................................................... 36
Figure (4.1): Architecture of 800 Gbps coherent WDM PON system ...................... 41
Figure (4.2): TRx components used to generate transmitted signal and decode
received one. (a) optical part. (b) Electrical part. ...................................................... 42
Figure (4.3): General diagrams (a) QPSK constellation diagram (b) Wavelengths
spectrum received at ONU side (Downlink) .............................................................. 44
Figure (4.4): Wavelengths spectrum view (a) Upstream [λ1 to λ8] (b) Downstream
[λ9 to λ16]. ................................................................................................................. 47
Figure (4.5): Constellation diagrams in x (left) and y (right) polarization signals for
all 8 uplink wavelengths ............................................................................................ 49
Figure (4.6): Constellation diagrams in x (left) and y (right) polarization signals for
all 8 downlink wavelengths ....................................................................................... 51
XIV
Figure (4.7): B-to-B model for 100 Gb/s DP-QPSK fiber transmission system ....... 53
Figure (4.8): Constellation diagram for B-to-B model with λ9 as input and OSNR 17
dB. (a) x-polarization (b) y-polarization .................................................................... 53
Figure (4.9): BER versus OSNR for B-to-B and 100 km span of SMF .................... 55
Figure (4.10): BER versus OSNR for uplink and downlink in the 100 km of SMF . 55
Figure (4.11): Comparison of 100 km vs 80 km SMF span ...................................... 56
Figure (A2.1): DP-QPSK optical transmitter layout ................................................. 67
Figure (A2.2): DP-QPSK optical receiver layout ...................................................... 68
Figure (A2.3): Universal DSP High Level Algorithm Design .................................. 69
Figure (A2.4): Examples decision boundaries for QPSK and 16-QAM ................... 71
XV
List of Abbreviations
3GPP 3rd Generation Partnership Project
4G 4th Generation Wireless
5G 5th Generation Wireless
5G-NR 5th Generation Wireless New Radio
AMCC Auxiliary Management and Control Channel
APD Avalanch PhotoDiode
ASK Amplitude Shift-Keying
B5G Beyond 5th Generation wireless
BBU Base Band Unit
BER Bit Error Rate
CA Carrier Aggregation
CAPEX Capital Expenditure
CD Chromatic Dispersion
CO Central Office
CoMP Cooperative MultiPoint
CPRI Common Public Radio Interface
C-RAN Centralized Radio Access Network
CU Centralized Unit
CW Continuous Wave
DBA Dynamically Bandwidth Allocation
DMT Discrete MultiTon
D-MUX Demultiplexer
DP-QPSK Dual-Polarization Quadric Phase-Shift Keying
DPSK Differential Phase Shift-Keying
D-RAN Distributed Radio Access Network
DSP Digital Signal Processor
DU Distribution Unit
EDFA Erbium Doped Fiber Amplifiers
EPC Evolved Packet Core
E-PON Ethernet Passive Optical Network
FSAN Full Service Access Network
FSK Frequency Shift-Keying
GPT Grant Processing Time
IF Intermediate Frequency
IM/DD Intensive modulation of direct detection
IoT Intenet of Things
IQ In-Phase/Quadrature
ITU-T International Telecomunications Union – Taskforce
LED Light Emitting Diodes
LO Local Oscillator
XVI
LTE Long-Term Evolution
MAC Media Access Control
MBH Mobile Back-Haul
MFH Mobile Front-Haul
M-MIMO Massive Multiple-Input Multiple-Output
MUX Multiplexer
NGC Next Generation Core
NGPON2 New Generation Passive Optical Network 2
NRZ Non-Return to Zero
OBSAI Open Base Station Architecture Initiative
ODN Optical Distribution Network
OLT Optical Line Terminal
ONU Optical Network Unit
OOK On-Off Keying
OPEX Operational Expenditure
OSNR Optical Signal-to-Noise Ration
OTN Optical Transport Network
P2MP Point-to-Multipoint
PAM Pulse Amplitude Modulation
PHY Physical Layer
PIN Positive intrinsic-negative
PLL Phase-Locked Loop
PMD Polarization Mode Dispersion
PON Passive Optical Network
PRBS Pseudorandom Binary Sequence
PSK Phase Shift-Keying
RAC Radio Access Control
RAN Radio Access Network
REAM Reflective Electro-Absorption Modulator
RF Radio Frequency
RRH Remote Radio Head
RTT Round Trip Time
RU Radio Unit
SDO Standards Development Organizations
SMF Single Mode Fiber
SOA Semiconductor Optical Amplifier
TDMA Time Division Multiple Access
TRx Transceiver
WDM Wave Division Multiplexing
Chapter 1
Introduction
2
Chapter 1
Introduction
1.1 Background and Context
The transport (or transmission) network plays an essential role in reliable 5th
generation wireless (5G) new radio (NR) and beyond 5th generation wireless (B5G)
deployments. Several technologies are competing to be proposed for 5G transport
system. For example, point-to-point fiber access, passive optical network (PON),
Flexible Ethernet, and optical transport network (OTN) were discussed in standards
organizations. Which one of mentioned technologies will satisfy 5G requirements? In
fact, there is no clear answer to this question because 5G operators have different
business models and various deployment plans built on their own budgets and markets.
Technology maturity and market timing will play a big role in choosing appropriate
transport technology by an operator.
As a start, and before discussing the transport technology choices, we need to
understand the key 5G requirements and how they would affect the transport network
design. Among the competing technologies, PON stands out as a strong candidate
because of the following (Wey & Zhang, 2018):
• PON point-to-multipoint topology (P2MP).
• Efficient use of fiber resources resulted from its topology.
• Wide deployment around the world for fixed access services.
According to the growing bandwidth demand initiated by latest applications such
as mobile front-haul (MFH) networks for the 5G, the IEEE 802.3ca Task Force had
announced, in 2017, commenced discussion of the first 100 Gb/s-based PON standard
in the form of 100 G Ethernet PON (100G-EPON) (Suzuki & others, 2017).
In this research project, we review the current 5G transport requirements, followed by
an overview of optical access technologies and standards development activities
specifically for 5G transport. And finally, we aim to analyze a scheme to highlight
state of the coherent PON technology used to overcome 5G transport system. A
3
significant software tool called OptiSystem will be used to simulate the scheme.
Simulated scheme and results will be presented in a separate chapter.
1.2 Scope and Objectives
The bandwidth demands for 5G mobile front-haul (MFH) and mobile back haul
(MBH) based on PON technology that are needed for the connection between small
cells and base band unit (BBU) is illustrated in Figure (1.1). The peak data rate is
assumed to be 20 Gb/s for each sector (Suzuki & others, 2018), with the integrated
remote radio head (RRH) covering three sectors in a small cell. For a Macro cell, the
total peak wireless data rate for a single sector is assumed to reach 60 Gb/s. Thus, the
data rate between the optical line terminal (OLT) and the optical network unit (ONU)
in 5G MFH/MBH can increase to 100 Gb/s for a small cell and up to 800 Gb/s for
macro cell contains 8 small cells.
Figure (1.1): Bandwidth demand (in red) for 5G MFH/MBH based PON technology
In this research, the researcher will review the 5G transport standards, discuss
optical access technologies and standard development activities, highlight several state
of the art PON technologies, and finally, researcher will introduce a solution for the
future 5G cells. That is, a 100-km fiber link for macro cell with 800 Gb/s capacity
4
which support up to 8 wavelengths; each wavelength serves a small cell with 100 Gb/s
transport data rate.
1.3 Significance
Too many researches have studied the 100 Gbps PON and below. In this research
a significant data rate will be achieved (800 Gbps). This achievement will be
introduced using the wavelength division multiplexing (WDM) coherent PON with
dual polarization (DP) technique and quadric phase shift keying (QPSK) modulation.
With DP-QPSK, one symbol will carry 4 times the on-off keying (OOK) bits. This
will highly utilize the fiber optic link resources to the maximum.
1.4 Limitations
This project will be implemented using a simulation program software
Optisystem and not using real hardware. Which in fact, will be more informative about
real obstacles and bit error rates (BER) that may be affected by several types of
dispersion "e.g. chromatic dispersion (CD) and polarization mode dispersion (PMD)"
1.5 Overview of Thesis
This thesis is organized as follows:
In Chapter 1, an introduction to the new scheme is presented and the scope with
the signification while the limitation is cleared.
In Chapter 2, a background review that summarizes most of current knowledge
of 5G standards and transport architecture will be presented. In addition, a summary
of what recently achieved by local and global researchers in PONs will be introduced.
In Chapter 3, a detailed introduction will be viewed for the modulation technique
DP-QPSK that will be used in our simulation project.
In Chapter 4, simulation scheme will be discussed and it will contain all fiber
link components with brief description of its function. Also, the simulation results will
5
be shown for both transmission direction uplink and downlink including power budget
and BER with corresponding to the added optical signal to noise ratio (OSNR).
Finally, the conclusion and future work will be presented in Chapter 5.
6
Chapter 2
Background
7
Chapter 2
Background
2.1 Introduction
To support increase in density and achieve required capacity in 5G wireless
technology, various air interface technologies are needed. From these air interfaces,
cooperative multipoint (CoMP), carrier aggregation (CA), and massive multiple-input
multiple-output (M-MIMO) are being nominated. Such technologies require high
speed information processing from multiple base stations to a common centralized
station. Also, there will be a tight synchronization of different radio sites that must be
considered. Hence, 5G MFH/MBH have to meet more stringent requirements not only
in terms of data rate but also in terms of latency, jitter, and BER (De La Oliva & others,
2015).
To address these challenges, several studies propose PON as 5G MFH/MBH
architecture solution. Because it is enabling a flexible and software-defined
reconfiguration of all networking elements in a multi-tenant and service-oriented
unified management environment.
Since PON was introduced in 1990s, its market grows up rapidly till now to serve more
than 100 million broadband subscribers worldwide (Wey & Zhang, 2018). 'PON
market revenue is being expected to reach $7.6 billion by 2022-2023' (Kunstler, 2018).
According to this info and for operational costs saving, PON has its advantageous for
5G wireless transport to share the fiber infrastructure with fixed access.
In this chapter, main part of optical communication system structure will be clarified.
Then, a highlight of several types of PON technologies depending on data multiplexing
scheme will be reviewed. Next, we will review 5G MFH/MBH architecture emerged
by the 3rd generation partnership project (3GPP) announced in the publication
TR38.801 in March, 2017 with reference to some studies in the field.
8
2.2 Optical communication system
2.2.1 Introduction
Optical fiber is widely used as a transmission channel for communication systems and
supports high-bit-rate over long distance because data is transmitted through glass
wires as light waves. Optical communication light wave is usually described in one of
three ways:
1. The classical physics (ray theory) that the propagation of a ray of light in optical fiber
follows Snell Law.
2. Think of light as an electromagnetic wave (electromagnetic theory).
3. The light consists of tiny particles-photons (quantum theory).
Fiber optics communication systems consist of three elements as shown in Figure (2.1)
Figure (2.1): Optical Communication System
2.2.2 Optical Transmitter
Optical transmitter converts the information carrying electrical signals to optical
signals and launches the optical signals into an optical fiber. The most common light
sources are Light Emitting Diodes (LEDs) and Laser Diodes (LDs).
LEDs emit light through spontaneous emission and are used extensively in fiber optic
communication systems due to their small size, long lifetime and low cost. They are
used in short distance and low bandwidth networks.
LDs emit light through amplification of radiation by simulated emission. Laser has a
higher output power than LED and so they are capable of transmitting information
over longer distances and provide high bandwidth communication (Keiser, 2011).
9
2.2.3 Fiber link
Optical fiber is a dielectric waveguide that operates at optical frequencies and transmits
information in the light form. It provides a data connection between the transmitter
and receiver. As shown in Figure (2.2) optical fiber has a central core in which the
light is guided, embedded in an outer cladding of slightly lower refractive index. Core
and cladding are protected by buffer and outer coat (Keiser, 2011).
Figure (2.2): Schematic of a conventional silica fiber structure
Optical fiber is classified into two categories based on number of modes (single mode,
multi-mode) or on the refractive index (step, graded). A mode in an optical fiber
corresponds to one of the possible multiple ways in which a wave may propagates
through the fiber. More formally, a mode corresponds to a solution of the wave
equation that is derived from Maxwell's equations and subject to boundary conditions
imposed by the optical fiber waveguide (Keiser, 2011).
Single mode fiber (SMF) with a relatively narrow diameter, through which only one
mode will propagate typically 1310 or 1550 nm, carries higher bandwidth than
multimode fiber. However, it requires a light source with a narrow spectral width.
Also, SMF has a narrow core (eight microns) and the index of refraction between the
core and the cladding changes less than it does for multimode fibers.
A fiber is called multimode if more than one mode propagates through it. In general,
a larger core diameter or high operating frequency allows a greater number of modes
to propagate (Keiser, 2011).
10
Attenuation is the loss of optical power of a signal as it travels down a fiber.
Attenuation depends on the wavelength of the light propagating within it and is
measured in decibels per length (dB/m, dB/km). Attenuation characteristics can be
classified into intrinsic and extrinsic. Intrinsic attenuation occurs due to substances
inherently present in the fiber, whereas extrinsic attenuation occurs due to external
influences such as bending or connection loss (Keiser, 2011).
2.2.4 Optical Receiver
An optical detector which converts the optical signals back to electrical signals so that
the information is recovered and delivered to the destination found here. An ideal
optical receiver will have high sensitivity, large bandwidth and low temperature
sensitivity, low power consumption and polarization independence.
The most common optical receivers found in fiber optic communication systems are:
1. Positive intrinsic-negative (PIN) photodiodes
2. Avalanche photodiode (APD) receivers.
Both are highly sensitive semiconductor devices that convert light pulses into electrical
signals (Keiser, 2011).
PIN photodiode consists of a thick intrinsic depletion region sandwiched between
positive and negative doped regions. PINs are the most commonly employed receivers
in fiber optic communication systems due to their ease in fabrication, high reliability,
low noise, low voltage and relatively high bandwidth.
APD is a photodiode that internally amplifies the photocurrent by an avalanche
process. It has a greater sensitivity by internally amplifying the photocurrent without
introducing the noise associated with external electronic circuitry. It has higher gain
and bandwidth than PIN but it requires a much greater voltage to be applied across the
active region. This requirement for higher power reduces the capability of
miniaturization of a receiver unit and limits the possibilities of integration in
communication systems (Keiser, 2011).
11
2.3 Overview of PON technologies
2.3.1 Introduction
PON is a point to multipoint network (P2MP) as shown in Figure (2.3).
Figure (2.3): PON architecture
PON uses a passive optical splitter where there is no need for power at all. In the
downstream direction, the splitter divides the light sending from the CO and then
broadcasts it to all Optical Network Units (ONUs). In the upstream direction, the
splitter couples the light coming from ONUs, and transmits it over the fiber connected
to the OLT. These essential components of PON will be explained later in this
subsection.
Since there are no optical repeaters or other active devices in the network, the network
is referred to as passive optical network (Ansari, 2013).
PON was created by the Full-Service Access Network (FSAN) working group which
is an affiliation of network operators and telecom vendors. PON converts and
encapsulates multiple services such as Plain Old Telephone Service (POTS), Voice
over Internet Protocol (VoIP), data and video in a single packet type for transmission
over the PON fiber. From figure (2.3) PON consists of three main parts (Ansari, 2013):
• Optical Line Terminal (OLT):
OLT is located at the service provider’s central office (CO). It provides the interface
between PON and the backbone network and it is responsible for the enforcement of
Or
12
any media access control (MAC) protocol for upstream bandwidth arbitration (Ansari,
2013).
• Optical Network Unit (ONU):
The ONU is located near end users. It provides the service interface to end users. It
also cooperates with the OLT in order to control and monitor all PON transmission
and to enforce the MAC protocol for upstream bandwidth arbitration (Ansari, 2013).
• Optical Distribution Network (ODN):
The ODN in PON connects the OLT at the CO and ONUs near user. It consists of the
distribution fibers and all the passive optical distribution elements, mainly optical
splitters and/or wavelength division multiplexing selective elements (WDM filters),
that are located in sockets or cabinets (Ansari, 2013). The splitting ratio in most cases
is between 1:8 and 1:128 and can be performed in lumped or cascaded elements.
Capital expenditure (CAPEX) and operational expenditure (OPEX) are playing an
important role for any mobile operator when upgrading to a new technology such as
5G. So, the sharing advantage property that fiber can provide, will make it better
candidate for 5G transport as well as supporting existing RAN technologies. Before
5G, PONs with 10 Gb/s seems to be very sufficient for current market. But in 5G era,
higher speed PONs will have strong attendance in the scene especially when fiber
infrastructure exists.
In general, PON technologies worldwide could be classified into the following types
according to data multiplexing (Ansari, 2013):
1. Time division multiplexing (TDM) PON,
2. Wavelength division multiplexing (WDM) PON,
3. Orthogonal frequency division multiplexing (OFDM) PON
Two significant factors must be considered in future high-speed PONs that well
support 5G, which are latency and bandwidth (Liu & Effenberger, 2016). In this
section, we will highlight three PON technologies capable of addressing these two
13
factors. Taking in mind, that any 5G support PON will have different topology from
typical residential one rather than providing accommodation for higher cost
technologies (Wey & Zhang, 2018).
2.3.2 High-speed PONs
Enabled by wavelength tunability and channel bonding, new generation of passive
optical networks-2 (NGPON2) will be able to deliver 80 Gb/s bandwidth by
aggregating eight 10 Gb/s wavelengths via TWDM, plus potentially 160 Gb/s more
with sixteen 10 Gb/s point-to-point (PtP)-WDM overlay wavelengths as reported in
the international telecommunication union-telecommunication (ITU-T) (G.989.2)
publication in April, 2016. So, NG-PON2 is a candidate for 5G transport using the
wavelength resources. However, complexity of transceiver design caused by
wavelength tunability, channel bonding, and strict crosstalk requirements will increase
the overall cost of the network (Wey & Zhang, 2018).
Another path, which has attracted more and more industry attention, is to increase the
data rate of a single wavelength TDM-PON. The initial data rate is targeting 25 Gb/s
in order to meet the minimum Fx interface requirement in 5G for functional split 7a.
The IEEE 802.3ca specifies a 25Gb/s per wavelength PON system using non-return to
zero (NRZ) modulation with the support of advanced forward error correction to
achieve the 29-dB power budget class (called PR30) as reported in the IEEE 802.3ca
draft standard that released in March, 2018. In the same standard, 50 Gb/s Ethernet
PON (50G-EPON) will be realized by bonding two 25 Gb/s wavelength channels.
Because of the additional insertion loss of wavelength multiplexer and demultiplexer
in a wavelength bonding system, semiconductor optical amplifiers (SOAs) have been
introduced to realize 50G EPON (Umeda & Liu, 2018).
Compared with bonding two 25 Gb/s wavelengths, single wavelength 50 Gb/s is of
great value since it is not only involving fewer optical components and the associated
system cost, but also saves half of the wavelength resources. To achieve single
wavelength operation at such high data rate, 50 Gb/s NRZ modulation would be
required (Zhang, Wey, & Huang, 2017). Other techniques using advanced modulation
formats are also possible, for example, duobinary (Houtsma & van Veen, 2018), 4-
14
level pulse-amplitude modulation (PAM4) (Zhang & others, 2018), and discrete multi-
tone (DMT) (Tao & others, 2017) together with advanced digital signal processing
(DSP) equalization. Recently, the feasibility of a single-wavelength 50 Gb/s TDM-
PON has been demonstrated by using NRZ/duobinary or PAM-4 with over 29 dB
power budget using SOA and DSP (Zhang & others, 2018).
In other hand, when 100 Gb/s PON is required the coherent detection using DP-QPSK
will be a promising technique that we will introduce in the next chapter.
2.3.3 Low-latency TDM PONs
Conventional bandwidth allocation schemes for TDM-PON significantly increase the
overall latency beyond the minimum value allowed in 5G specifications. Much effort
has been made to reduce the overall latency of future TDM-PON. Some of these efforts
are summarized in this subsection.
In conventional TDM-PON, OLT implements dynamically bandwidth allocation
(DBA) to avoid upstream data collisions and grants the time slots for upstream signals
from specific ONUs. This process and the corresponding grant processing time (GPT)
cause high overall latency. Therefore, simplifying the handshake process or GPT are
potential directions to reduce the latency. Fixed-length DBA (Hatta, Tanaka, &
Sakamoto, 2016) and traffic-load dependent DBA (Hatta, Tanaka, & Sakamoto, 2017)
are proposed recently to mitigate the latency issue in TDM-PON.
Regarding the quiet window issue; in the current TDM-PON ONU registration or
activation process, upstream traffic is interrupted for over 200 μs when new ONUs is
invited to join. These interruptions add to the latency, which can exceed the acceptable
values in 5G. Alternative solutions for ONU registration in TDM-PON are required,
e.g., using a second wavelength for ONU discovery and ranging, or modifying the
existing activation process to minimize the interruptions (Li, Sun, Yang, & Hu, 2014).
2.3.4 WDM PONs
WDM-PON has several unique advantages for 5G fronthaul applications, including
high capacity, low latency (as it does not need DBA), fiber savings, and operational
15
simplicity. Each user is assigned one dedicated wavelength. Each wavelength will
require 25 Gb/s or higher for 5G deployments (Yang, 2017).
Two key enabling technologies are expected for WDM-PON. Firstly, colorless ONUs
using tunable transceiver technology provide operational flexibility. A recent report of
a 25 Gb/s colorless ONU incorporates reflective electro-absorption modulator with
semiconductor optical amplifier (REAM-SOA) to support 5G fronthaul (Zhou &
Deng, 2015). At present, tunable transceiver technologies for 25 Gb/s and beyond still
have a long way to go to be cost effective for the mass market. As 5G/business services
can bear higher cost, it is conceivable that tunable transceivers may find more early
adopters in 5G than in the residential market. Challenges such as wavelength tuning
range, wavelength stability, and photonics integration for cost reduction, require more
study.
Secondly, an auxiliary management and control channel (AMCC) provides the means
to transmit wavelength allocation and assignment information and OAM (operation,
administration, management) data. For 5G transport, how AMCC would be applied to
transparent transmission of OAM data, is still an open question. An example of
wavelength adjustment method for the upstream signal using the AMCC in a WDM-
PON for 5G is demonstrated in (Honda & others, 2018).
In summary, the next wave of PON innovations is targeting single-wavelength data
rate at 25 and 50 Gb/s regardless of PON flavor. On the transmit side, new modulation
schemes such as PAM-4, duobinary, and discrete multiton (DMT), are being proposed
alongside the conventional NRZ method. It remains to be seen which of these
modulation schemes will be most effective. On the receive side, for a PON dedicated
for wireless services, the ODN loss budget is much more relaxed than the conventional
fixed access PON, which translates to additional cost saving. The latency issue in
TDM-PON has stimulated several promising proposals to mitigate the extra delays due
to DBA and quiet window during ONU activation.
For WDM-PON, the tunable transceiver is both a critical enabling technology and a
major challenge especially for data rate at 25 Gb/s and above. Innovations for cost-
effective tunable transceiver technologies remain under investigation.
16
For now, a demonstration of 100 Gb/s/λ × 8 wavelengths (800 Gb/s) based real-time
wavelength division multiplexing (WDM)-PON system using coherent detection and
simplified digital signal processor (DSP) suitable for PON use will be presented next
chapter. Addressing the technical issues associated with burst mode coherent
reception, the results will facilitate the real life coherent PON systems.
2.4 Overview of 5G transport
2.4.1 Introduction
Clouding, virtualized network concept, and supporting massive machine type
communication in addition to the faster speed and higher bandwidth distinguish 5th
generation of mobile communication from other generations. In this section, we will
highlight the changes of 5G transport architecture, bandwidth and latency
requirements, and suggested deployment scenarios depending on different operators'
requirements.
In the 4th generation (4G) / long-term evolution (LTE) radio access network (RAN),
transport architecture consists of two parts (Wey & Zhang, 2018):
1. Backhaul part connects the evolved packet core (EPC) and BBU.
2. Fronthaul part connects the BBU and RRH.
This 4G fronthaul is used to transfer the in-phase/quadrature (IQ) data in a continuous
bit rate regardless the availability of user traffic by the function of common public
radio interface (CPRI) or open base station architecture initiative (OBSAI) protocols.
This is not an efficient way to use such transport system in 5G. Because if considering
the same protocols, data rates will over 100 Gb/s can be expected. Latency also, plays
an important factor in this architecture. In 4G, 250 µs is the maximum BBU-RRH
round trip time (RTT) which is not a problem when connecting them by fiber in the
same cell (Wey & Zhang, 2018). In the following subsections, an overview of 5G
transport architecture and how it overcomes these obstacles will be presented.
17
2.4.2 5G Prospects
The development of wireless technologies has greatly improved people’s ability to
communicate and live in both business operations and social functions.
What will the 5G network, which is expected to be standardized around 2020, look
like? Compared to 4G networks, 5G networks should achieve (Wang & Others, 2014):
• 1000 times the system capacity
• 10 times the spectral efficiency
• Energy efficiency and data rate (i.e., peak data rate of 10 Gb/s for low
mobility and peak data rate of 1 Gb/s for high mobility)
• 25 times the average cell throughput
• The aim is to connect the entire world, and achieve seamless and
ubiquitous communications between anybody, anything, anywhere,
anytime, and anyhow
One of 4G challenges is the high-speed mobility (Wang & Others, 2014). High-speed
trains can easily reach 350 up to 500 km/h, while 4G networks can only support
communication scenarios up to 250 km/h. 5G must overcome this issue with
supporting high-speed mobility such as mentioned trains.
2.4.3 5G Challenges
There are some challenges for 5G technology, including (Wang & Others, 2014):
• The physical scarcity of radio frequency (RF) spectra allocated for
cellular communications. These frequency spectra have been used
heavily, making it difficult for operators to acquire more.
• The deployment of advanced wireless technologies comes at the cost
of high energy consumption. Increase of CO2 emission indirectly.
• Other challenges are, for example, average spectral efficiency, high
data rate and high mobility, seamless coverage, diverse quality of
service (QoS) requirements, and fragmented user experience
18
(incompatibility of different wireless devices/interfaces and
heterogeneous networks), to mention only a few.
Figure (2.4) shows main 5G challenges and as appear in the figure, upgrading backhaul
is forming 33% of these challenges.
Figure (2.4): Main 5G challenges (Light, 2015)
2.4.4 Concept of 5G transport architecture
When forwarding to 5G, a massive scale of connected devices will be served through
a centralized/cloud transport network environment. This means all BBUs will be
moved to a common location to perform the centralization processing leaving only
RRHs in the cell location with minimum power consumption. So, here a problem in
the media that will format the fronthaul of BBU-RRH which must support high
bandwidth and very low latency requirements will appear. To clarify this problem, if
we consider a 32-antenna port cell working for a bandwidth of 100 MHz radio channel,
the required CPRI bandwidth will be 157 Gb/s (3GPP, 2017). In other hand, the latency
should include propagation time through transport media (e.g. for fiber RTT, 10
µs/km) which will affect the processing delay. To solve this problem, a new design
has been created for 5G technology contains next generation core (NGC), centralized
unit (CU), distributed unit (DU), and radio unit (RU). The main function of this new
design is to redistribute the radio processing functions that is already processed in EPC,
BBU and RRH in 4G/LTE. These functions include radio resource control (RRC),
19
packet data convergence protocol (PDCP), radio frequency (RF), high/low layers of
radio link control (RLC), media access control (MAC), and physical layer (PHY).
Figure (2.5) illustrates the difference between 4G/LTE architecture and 5G new radio
design (Wey & Zhang, 2018).
Figure (2.5): Network elements for 4G/LTE and 5G-NR (Top) and signal processing
function chain (bottom)
As shown in Figure (2.5), there are 8 splits indicating the bandwidth specified by
3GPP. Split 8 is the conventional 4G/LTE CPRI fronthaul interface. In 5G-NR, since
RF and Low-PHY functions are located in one common place called RU, bandwidth
limitations in split 8 is not a problem. splits 1-7 offers a key differentiator in that the
amount of data transported can scale with user traffic. This allows the transport
network to dynamically adapt to traffic conditions and efficiently aggregate traffic
from multiple cells, when shared media such as PON is used. In general, the industry
defined two splits (Wey & Zhang, 2018):
1. High layer split called Fronthaul-II/Midhaul/F1; which specified by 3GPP as
split 2.
2. Low layer split called Fronthaul-I/Fx; which still open for vendors and could
be 7a, 7b, or 7c; see table 2.1.
20
2.4.5 Bandwidth and latency requirements
As in Table (2.1), the peak values of bandwidth for eight mentioned splits under
optimal conditions can be shown clearly (Wey & Zhang, 2018). Bandwidths in the
table had been calculated for the case of 100 MHz radio frequency bandwidth, 256-
QAM modulation, 8x8 MIMO layers, and 32 antenna ports for radio frequency range
less than 6 GHz. By comparison, in 4G LTE, typical values of the respective
parameters are 20 MHz radio frequency bandwidth, 64 QAM, 2x2 MIMO layers, and
up to 22 antenna ports. As the discussion on latency is still ongoing in various
standards development organizations (SDOs), we show only the potential range of
latency values in Table (2.1).
A general guidance from operators for throughput bandwidth (capacity of a PON) in
both backhaul and F1 is less than 10 Gb/s during 5G Phase 1 rollout (radio bandwidth
up to 3.5 GHz), increasing to 25/50 Gb/s in Phase 2 (radio bandwidth > 6 GHz)
(Chanclou, 2018), and up to 86 Gb/s in a later Phase (Ujikawa & Nakamura, 2018).
21
Table (2.1): 5G Transport bandwidth and latency requirements (Wey & Zhang,
2018)
Split Uplink
Bandwidth
Downlink
Bandwidth One-Way latency
1 4 Gb/s 3 Gb/s
1-10 ms 2 (F1) 4016 Mb/s 3024 Mb/s
3 Lower than option 2
4 4000 Mb/s 3000 Mb/s
100 to a few 100 µs
5 4000 Mb/s 3000 Mb/s
6 4133 Mb/s 5640 Mb/s
7a 10.1-22.2 Gb/s 16.6-21.6 Gb/s
7b 37.8-86.1 Gb/s 53.8-86.1 Gb/s
7c 10.1-22.2 Gb/s 53.8-86.1 Gb/s
8 (CPRI) 157.3 Gb/s 157.3 Gb/s
2.4.6 Deployment scenarios
There are four deployment scenarios for 5G-NR as illustrated in Figure (2.6) (Wey &
Zhang, 2018).
Figure (2.6): 5G Deployment scenarios
1. Scenario 1: this scenario is most likely 4G/LTE deployment where the DU and
CU are located in one access point forming centralized radio access network
22
(C-RAN). Here, backhaul and one fronthaul (Fx) will be deployed for
transport.
2. Scenario 2: where the CU is located in the aggregation node as part of the
mobile edge cloud. In this scenario, C-RAN is formed too with backhaul and
two front hauls (F1 and Fx). Here, a utilization reduction will be scored in Fx
fronthaul that will allow other applications to use the fiber link.
3. Scenario 3: DU and RU are located with cell site to form the distributed radio
access network (D-RAN).
4. Scenario 4: small cell will be formed by connecting CU, DU, and RU in cell
site. Here, a tradition backhaul is used to save costs.
2.5 Summary
In this chapter, the concept of conventional 5G transport architecture was discussed,
which is similar to 4G/LTE one. Then the proposed design by 3GPP of 5G-NR was
introduced and compared to conventional one. Also, the minimum bandwidth and
latency requirements of 5G-NR splits was discussed. Various deployment scenarios,
depending on operators, was introduced for 5G-NR.
The structure of optical communication system has been viewed with explanations for
its elements. Then an overview of the highly nominated technology for 5G-NR
transport architecture PON was discussed in details. The two major factors that plays
essential role in building up the 5G-NR transport architecture are latency and
bandwidth. We reviewed the latest researches in these two topics in detail in last
section.
As a conclusion, the research in the 100 Gbps and above high-speed PONs is very
promising for the expected need of 5G-NR transport architecture and its promising
applications such as internet of things (IoT), smart homes, smart farming, and health
industry.
23
24
Chapter 3
Methodology
25
Chapter 3
Methodology
3.1 Introduction
As per given in chapter 2, of the advantages and leakages of several PON
technologies, WDM PON appears to be a best choice for reliable 5G and beyond 5G
transport system. Because of its high capacity, low latency, fiber savings, and
operational simplicity, it precedes other PON technologies. The WDM PON is very
attractive for future broadband access network due to its capability of providing
practically unlimited bandwidth to each end node. However, for the massive
commercial deployment, its competitiveness is yet to be improved. In particular, we
need to increase its operating speed (initiation time) and maximum reach (distance),
and, at the same time, enhance its cost-effectiveness (Chung, 2013).
The scarcity of spectrum, the required flexibility and constant evolution of PON
requirements point to an excellent fitting of use of coherent techniques in optical
access. Its filter-less receiver operation, the inherent gain and its flexibility as what
regards signal manipulation (higher order formats, pulse shaping, compensation
mechanisms, etc.) allow taking advantage of the full potential of the fiber transmission
in a flexible way (Teixeira & others, 2017).
For all mentioned objectives, a suggestion was introduced in this research to analyze
high speed WDM PON operating at more than 100 Gbps/wavelength(λ) using optical
amplifiers and the digital coherent detection technique to support about 100 km of
single mode fiber (SMF) distance. In this suggested study, to make the solution cost-
effective, we assumed to use a DP-QPSK transmitter in which the optical signal will
be generated to be transmitted either in downlink or uplink. Also, a DP-QPSK receiver
will be used in which the optical signal will be received either in OLT or ONU. In
addition to that a restrain of the use of expensive external modulators and optical
amplifiers will be considered.
26
3.2 Coherent Detection
3.2.1 Introduction
Intensive modulation of direct detection (IM/DD) is a method where a simple
and cost-effective light-wave transmission scheme in which the light intensity of the
optical source is modulated linearly with respect to the input electrical signal voltage.
This scheme pays no attention to the frequency or phase of optical carrier, since a
photodetector at the receiving end only responds to the changes in the power level
(intensity) that falls directly in it. The photodetector then transforms the optical power
level variations back to the original electrical signal format. Although methods adopt
IM/DD offer simplicity and relatively low cost, their sensitivities are limited by noise
generated in the photodetector and receiver preamplifier. These noises degrade the
receiver sensitivities of square-law IM/DD transmission systems by 10 to 20 dB from
the fundamental quantum noise limit (Keiser, 2011).
Coherent detection solves this problem that network providers are facing. It takes the
typical ones and zeroes in a digital signal (the blinking on and off of the light in the
fiber) and uses sophisticated technology to modulate the amplitude and phase of that
light and send the signal across each of two polarizations. This, in turn, imparts
considerably more information onto the light speeding through a fiber optic cable.
Spectral purity and frequency stability of semiconductor lasers had been improved by
several researches since 1978 where alternative techniques using homodyne and
heterodyne detection of the optical signal appeared to be feasible. The term "Coherent"
comes from the implementation that depends on phase coherence of the optical carrier.
In this type of detection, light is treated as a carrier medium that can be amplitude,
frequency, or phase modulated similar to the methods used in microwave radio
systems (Keiser, 2011).
As the needs in 5G transport architecture are increasing to at least 10 Gbps and beyond
(refer to chapter 2 functional splits), the coherent detection technique seems to be more
attractive method to be considered in design than direct detection. It enables a higher
spectral efficiency and greater tolerance to chromatic and polarization mode
dispersions.
27
3.2.2 Fundamental concept
Figure (3.1): Fundamental concept of a coherent light-wave system (Keiser, 2011)
Figure (3.1) illustrates the fundamental concept of coherent light-wave systems. The
main idea in the coherent detection technique is to amplify the incoming signal by
coupling it to a local generated continuous wave (CW) optical field. In communication
systems, coupling means that if we have two signals with frequencies 𝜔1 and 𝜔2, the
output will be other waves with frequencies equal to 2𝜔1, 2𝜔2, and 𝜔1 ± 𝜔2. All
these frequencies are filtered at the receiver except 𝜔1 − 𝜔2 in coherent lightwave
systems. CW signal is created by a device called local oscillator (LO). Result of this
coupling process is a dominant receiver noise. Then the LO noise that can be
subtracted to get the original signal i.e. limited sensitivity at receiver (Keiser, 2011).
To simplify this concept and to find out how receiver sensitivity performance will be
improved, let us consider the electric field of transmitted signal having the form:
𝐸𝑠 = 𝐴𝑠cos[𝜔𝑠𝑡 + 𝜑𝑠(𝑡)] (3.1)
where, 𝐴𝑠 is the amplitude of the optical signal field, 𝜔𝑠 is the optical signal carrier
frequency, and 𝜑𝑠(𝑡) is the phase of the optical signal. So, amplitude, frequency or
phase of the optical signal can be modulated to send information. Following are the
modulation techniques that can be used (Keiser, 2011):
1. Amplitude shift keying (ASK) or on-off keying (OOK). In this case, 𝜑𝑠(𝑡) will
be constant and the signal amplitude 𝐴𝑠 will carry 0 or 1 bit during each bit
period depending on which is transmitted.
28
2. Frequency shift keying (FSK). Here, 𝐴𝑠 will be constant and hence 𝜔𝑠𝑡 will
have the value 𝜔1𝑡 or 𝜔2𝑡 where, 𝜔1 and 𝜔1 represent binary signal values.
3. Phase shift keying (PSK). In this method, data is transmitted by varying the
phase with sine wave 𝜑𝑠(𝑡) = 𝛽 sin𝜔𝑚𝑡, where 𝛽 is the modulation index and
𝜔𝑚 is the modulation frequency.
At receiver in coherent systems, a locally generated optical wave will be added to the
incoming signal and then the coupled signal will be detected. There are four
demodulation formats. Depending on the coupling process with local oscillator wave,
we have heterodyned or homodyned detection. Depending on how electrical signal is
detected, we have synchronous or asynchronous detection. As mentioned in (Keiser,
2011), the homodyne receivers are more sensitive than heterodyne receivers, and the
synchronous detection is more sensitive than asynchronous detection. If LO has the
form,
𝐸𝐿𝑂 = 𝐴𝐿𝑂cos[𝜔𝐿𝑂𝑡 + 𝜑𝐿𝑂(𝑡)] (3.2)
where, 𝐴𝐿𝑂 is the amplitude of the LO signal field, 𝜔𝐿𝑂 is the optical LO carrier
frequency, and 𝜑𝐿𝑂(𝑡) is the phase of the optical LO. Then the detected current 𝐼𝑐𝑜ℎ(𝑡)
will be proportional to the square of the total electric field of the signal falling on the
photodetector. Here, we have to mention that LO wave will be coupled with received
signal before (on the surface) the photodetector (Keiser, 2011). This info gives,
𝐼𝑐𝑜ℎ(𝑡) = (𝐸𝑠 + 𝐸𝐿𝑂)2
=1
2𝐴𝑠
2 +1
2𝐴𝐿𝑂
2 + 𝐴𝑠𝐴𝐿𝑂cos[(𝜔𝑠 − 𝜔𝐿𝑂)𝑡 + 𝜑𝑠(𝑡) − 𝜑𝐿𝑂(𝑡)]𝑐𝑜𝑠𝜃(𝑡) (3.3)
where,
𝑐𝑜𝑠𝜃(𝑡) =𝐸𝑠.𝐸𝐿𝑂
|𝐸𝑠||𝐸𝐿𝑂| (3.4)
Represents the polarization misalignment between the signal wave and LO wave.
Since the optical power is proportional to the intensity at the photo detector, we then
have (Keiser, 2011),
29
𝑃(𝑡) = 𝑃𝑠 + 𝑃𝐿𝑂 + 2√𝑃𝑠𝑃𝐿𝑂𝑠𝑐𝑜𝑠[(𝜔𝑠 −𝜔𝐿𝑂)𝑡 + 𝜑𝑠(𝑡) − 𝜑𝐿𝑂(𝑡)]𝑐𝑜𝑠𝜃(𝑡) (3.5)
where, 𝑃𝑠 and 𝑃𝐿𝑂 are the signal and LO optical powers, respectively, with 𝑃𝐿𝑂 ≫ 𝑃𝑠.
Thus, we see the angular frequency difference 𝜔𝐼𝐹 = 𝜔𝑠 − 𝜔𝐿𝑂 is an intermediate
frequency, and the phase angle 𝜑(𝑡) = 𝜑𝑠(𝑡) − 𝜑𝐿𝑂(𝑡) is the time-varying phase
difference between the signal and LO levels. Normally, 𝜔𝐼𝐹 is in radio frequency range
of tens or hundreds of megahertz (Keiser, 2011).
3.2.3 Homodyne detection
When 𝜔𝐼𝐹 = 0, that is we have the same frequency of received signal and LO wave,
the homodyne detection will be the case (Keiser, 2011). Equation (3.5) becomes:
𝑃(𝑡) = 𝑃𝑠 + 𝑃𝐿𝑂 + 2√𝑃𝑠𝑃𝐿𝑂𝑠𝑐𝑜𝑠𝜑(𝑡)𝑐𝑜𝑠𝜃(𝑡) (3.6)
Hence, two modulation schemes can be achieved in homodyne detection. Either
varying 𝑃𝑠 while keeping 𝜑(𝑡)constant, i.e. OOK, or varying 𝜑(𝑡) while keeping 𝑃𝑠
constant, i.e. PSK. When considering 𝑃𝐿𝑂 ≫ 𝑃𝑠, the last term of equation will contain
the information and hence the LO will work as signal amplifier, thereby giving greater
receiver sensitivity than direct detection (Keiser, 2011). Homodyne receivers are most
sensitive coherent systems. However, they are also the most difficult to build, since
the LO must be controlled by an optical phase-locked loop (PLL). In addition,
designing the same frequency for signal and LO laser will stringent requirements on
these two sources. The homodyne detection, requires extremely narrow spectral width
(linewidth) and high degree of wavelength tunability (Keiser, 2011).
For above reasons, homodyne detection systems are very suitable detection technique
to be considered in building 5G transport architecture.
3.2.4 Heterodyne detection
When 𝜔𝐼𝐹 ≠ 0, that is we have different frequencies of received signal and LO wave
where no optical PLL is needed, the heterodyne detection will be the case. Heterodyne
receivers are much easier to implement than homodyne receivers. However, a 3-dB
degradation in sensitivity will be the cost for this simplification (Keiser, 2011).
30
OOK, FSK, or PSK modulation can be used in heterodyne detection. Since 𝑃𝐿𝑂 ≫ 𝑃𝑠,
we can ignore 𝑃𝑠 in equation (3.5). The receiver output current then contains a dc term
given by
𝑖𝑑𝑐 =𝜂𝑞
ℎ𝑣𝑃𝐿𝑂 (3.7)
where, 𝜂 is the quantum effecincy, 𝑞 is the electron charge = 1.60218 ×10-19 C, ℎ is
Planck's constant = 6.6256 ×10-34, and 𝑣 is the frequency. In other hand, time varying
IF term given by
𝑖𝐼𝐹 =2𝜂𝑞
ℎ𝑣√𝑃𝑠𝑃𝐿𝑂 𝑐𝑜𝑠[𝜔𝐼𝐹𝑡 + 𝜑(𝑡)]𝑐𝑜𝑠𝜃(𝑡) (3.8)
Normally, the dc current will be filtered in the receiver and IF current will be amplified.
Information then can be recovered from the IF current using conventional RF
demodulation techniques (Keiser, 2011).
As per mentioned heterodyne detection concept, it is clear that implementation of 5G
transport architecture using heterodyne detection elements is more cost effective than
using homodyne devices. However, there will be a 3-dB sensitivity degradation in
heterodyne receiver.
3.3 Modulation Technique
From previous section we figured that coherent technique with homodyne detection
supports OOK and PSK modulation techniques. Also, heterodyne detection supports
three types of modulation techniques, which are OOK, FSK, and PSK. In this section
a lookup of the modulation schemes and a comparison of the BER in each scheme will
be presented. To achieve informative BER comparison, we assume 10-9 BER target
for all schemes. The best receiver sensitivity technique, is that which needs less
photons on the photodetector surface to decode information.
31
3.3.1 Homodyne schemes
Figure (3.2): Fundamental setup of a homodyne receiver (Keiser, 2011)
As can be seen from figure (3.2), the received optical signal will be coupled (mixed)
with the phase-locked-local-oscillator laser wave. The two coupled signals are
identical in phase; i.e. 𝜔𝐼𝐹 = 0, but has different amplitude. The coupled signals will
go through photodetector surface into the low pass filter to recover the original signal
that contains desired information.
3.3.1.1 OOK Homodyne system
For OOK homodyne detection, the BER is given by (Keiser, 2011):
𝐵𝐸𝑅 =1
2𝑒𝑟𝑓𝑐√𝜂𝑁𝑃
(3.9)
where, 𝑒𝑟𝑓𝑐 is the error function, and 𝑁𝑃 is the average number of electron-hole pairs.
𝑒𝑟𝑓𝑐√𝑥 =𝑒−𝑥
√𝜋𝑥 (3.10)
Therefore, to achieve 10-9 BER, 18 photons per bit are required at the receiver to
detect the information for a unity quantum efficiency (𝜂 = 1).
32
3.3.1.2 PSK Homodyne system
PSK homodyne detection gives the best theoretical receiver sensitivity but it is also,
the most difficult method to implement (Keiser, 2011). Figure (3.2) illustrates the
fundamental setup of a homodyne receiver. BER is given by (Keiser, 2011):
𝐵𝐸𝑅 =1
2𝑒𝑟𝑓𝑐√2𝜂𝑁𝑃
(3.11)
Therefore, to achieve 10-9 BER, only 9 photons per bit are required at the receiver to
detect the information for a unity quantum efficiency (𝜂 = 1).
It is clear can be concluded that receiver sensitivity in PSK homodyne detection system
is about twice of that in OOK homodyne detection system.
Following figure (3.3) shows a comparison of both homodyne OOK and homodyne
PSK bet error rates with respect to corresponding required number of photons in each
technique.
Figure 3.3): Homodyne receiver techniques comparison with unity quantum
effeciency
1E-111.01E-092.01E-093.01E-094.01E-095.01E-096.01E-097.01E-098.01E-099.01E-09
68101214161820
BER
Average number of Photons
Homodyne receiver system (Unity Quantum Effeciency)
OOK
PSK
33
3.3.2 Heterodyne schemes
An attractive feature of heterodyne receivers is that they can be implemented for
synchronous or asynchronous detection. Figure (3.4) shows the general receiver
configuration (Keiser, 2011). As can be seen from Figure (3.4) (a), in case of
synchronous detection, the received optical signal will be coupled (mixed) with the
frequency-locked-local-oscillator laser wave. The coupled two signals have different
phases and amplitudes. The coupled signals will go through photodetector surface into
a bandpass filter then it will be multiplied by carrier recovery signal which is usually
a microwave phase-locked loop (PLL), to generate a local phase reference. The
resulted signal will have a mixed of intermediate frequency and PLL. One then uses
low pass filter to recover the original signal that contains desired information. In figure
(3.4) (b), asynchronous PSK detection can be generated by replacing PLL by a 1-bit
delay. Also, this technique called differential phase shift keying (DPSK). Since with a
PSK method information is encoded by means of changes in the optical phase, the
mixer will produce a positive or negative output depending on whether the phase of
the received signal has changed from the previous bit. Then the transmitted signal can
be recovered from the output (Keiser, 2011).
Figure (3.4): General heterodyne receiver configurations. (a) Synchronous detection uses a
carrier-recovery circuit. (b) Asynchronous detection uses a one-bit delay line (Keiser, 2011)
34
As mentioned in previous section, heterodyne detection can support OOK, PSK and
FSK modulation techniques. BER comparison of the three modulation techniques will
be presented next.
3.3.2.1 OOK Heterodyne system
In OOK synchronous heterodyne detection system, the BER is given by (Keiser,
2011):
𝐵𝐸𝑅 =1
2𝑒𝑟𝑓𝑐√
1
2𝜂𝑁𝑃 (3.12)
And for the OOK asynchronous heterodyne detection system, the BER is given by
(Keiser, 2011):
𝐵𝐸𝑅 =1
2exp(−
1
2𝜂𝑁𝑃 ) (3.13)
Therefore, to achieve 10-9 BER, 36 and 40 photons per bit are required in OOK
synchronous and asynchronous heterodyne respectively at the receiver to detect the
information for a unity quantum efficiency (𝜂 = 1).
3.3.2.2 PSK Heterodyne system
In PSK synchronous heterodyne detection system, the BER is given by (Keiser, 2011):
𝐵𝐸𝑅 =1
2𝑒𝑟𝑓𝑐√𝜂𝑁𝑃
(3.14)
And for the PSK asynchronous heterodyne detection system, the BER is given by
(Keiser, 2011):
𝐵𝐸𝑅 =1
2exp(−𝜂𝑁𝑃
) (3.15)
Therefore, to achieve 10-9 BER, 18 and 20 photons per bit are required in PSK
synchronous and asynchronous heterodyne respectively at the receiver to detect the
information for a unity quantum efficiency (𝜂 = 1).
35
3.3.2.3 FSK Heterodyne system
In FSK synchronous heterodyne detection system, the BER is given by (Keiser, 2011):
𝐵𝐸𝑅 =1
2𝑒𝑟𝑓𝑐√
1
2𝜂𝑁𝑃 (3.16)
And for the FSK asynchronous heterodyne detection system, the BER is given by
(Keiser, 2011):
𝐵𝐸𝑅 =1
2exp(−
1
2𝜂𝑁𝑃 ) (3.17)
Therefore, to achieve 10-9 BER, 36 and 40 photons per bit are required in FSK
synchronous and asynchronous heterodyne respectively at the receiver to detect the
information for a unity quantum efficiency (𝜂 = 1).
Following table (3.1) summarizes the number of photons required for a target of 10-9
BER and a unity quantum efficiency.
Table (3.1): Summary of photon numbers required for a 10-9 BER by an ideal
receiver having a photodetector with unity quantum efficiency
Modulation
Number of photons
Homodyne Heterodyne
Synchronous Asynchronous
On-off keying (OOK) 18 36 40
Phase-shift keying (PSK) 9 18 20
Frequency-shift keying (FSK) __ 36 40
Following figure (3.5) shows a comparison of heterodyne OOK, PSK and FSK bet
error rates with respect to corresponding required number of photons in each
technique. Figure (3.5) (a) shows the comparison in synchronous heterodyne detection
while figure (3.5) (b) shows the comparison in asynchronous heterodyne detection.
36
(a)
(b)
Figure (3.5): Heterodyne detection comparison of various modulation techniques.
(a) synchronous (b) asynchronous
3.4 Summary
In this chapter the coherent detection technique is discussed in details. The advantages
of coherent detection over direct detection was introduced. Two main types of coherent
detection are compared which are homodyne and heterodyne detection techniques.
Each type has different sensitivity for different modulation technique. A comparison
of BER using OOK, PSK, and FSK in heterodyne and OOK, and PSK in homodyne
was presented by equations and numerical examples.
1E-11
1.01E-09
2.01E-09
3.01E-09
4.01E-09
5.01E-09
6.01E-09
7.01E-09
8.01E-09
9.01E-09
17192123252729313335373941
BER
Average number of Photons
PSK
OOK & FSK
1E-11
1.01E-09
2.01E-09
3.01E-09
4.01E-09
5.01E-09
6.01E-09
7.01E-09
8.01E-09
9.01E-09
17192123252729313335373941
BER
Average number of Photons
PSK
OOK & FSK
37
As a result, the homodyne detection using PSK is the most attractive technique to be
used in 5G transport architecture due to its highest sensitivity and responsiveness. This
technique will be simulated in the next chapter starting from topology and ending by
results discussion.
38
Chapter 4
Topology, Results and
Discussion
39
Chapter 4
Topology, Results and Discussion
4.1 Introduction
In this chapter, we will introduce the coherent wavelength division
multiplexing dual polarization quadric phase-shift keying passive optical network
(WDM DP-QPSK PON) topology that we study as a solution for 5G and B5G transport
architecture. Firstly, a block diagram of the topology will be presented as an
introduction to the deployment network. Second, a simulation for the 8×8 wavelengths
network will be discussed in details. Finally, results of back-to-back (B-to-B) and fiber
connected networks will be compared.
Before starting this chapter, it is obvious to state the reasons that we choose WDM
DP-QPSK upon other types of PON technologies. As per 5G and B5G transport
architecture topologies mentioned in chapter2, there are two major factors play
essential role that we may be reminded here; that are, latency and bandwidth. In
addition to these two factors, distance between central office (CO) and different 5G-
NR components have to be considered also. Following are main reasons for choosing
such scheme:
1. WDM PONs have several unique advantages for 5G fronthaul applications,
including high capacity, low latency (as it does not need DBA), fiber savings,
and operational simplicity.
2. Coherent (homodyne) PSK modulation technique has the highest sensitivity
upon other modulation techniques which increases the availability for longer
distance transmission.
3. QPSK multiplies the capacity of OOK or BPSK (1 b/symbol) as 2 bits will be
transmitted within one symbol.
4. Dual polarization definitely will double the double, i.e. 4 bits will be
transmitted within one symbol in case of DP-QPSK; hence, the capacity will
be increased.
40
Our scheme is supporting 100 km distance with optical booster for the downlink (DL)
and optical amplifier for the uplink (UL). These two instruments are located within
optical line terminal (OLT) to eliminate further power requirements in optical
distribution network (ODN) and to achieve minimum power consumptions at optical
network units (ONUs) for keeping the network passive. To support shorter distances,
booster and amplifier can be adapted easily within OLT to reduce power consumption.
This simulated scheme supports 800 Gb/s as total capacity, which is a pioneer
achievement for such 100 km of distance.
Unfortunately, and because of resource limitations, we could not implement the
hardware that can reflect simulation introduced in this thesis. To carry out project
simulations, OptiSystem tool version 15.2 was used (Optiwave, 2018).
4.2 Scheme topology
Figure (4.1) shows the experimental setup for our 100 Gbps/λ based coherent WDM-
PON prototype. The architecture of the analyzed 100 Gbps/λ coherent WDM-PON
system features a symmetric WDM-PON system with 8×100 Gbps wavelengths in
both the downstream (DN) and upstream (UP). The optical line terminal (OLT) is
connected to each ONU on a dedicated wavelength via an optical coupler located in
the 100 km single mode fiber (SMF) access span. In this test, the 8 upstream
wavelengths were allocated from 1537.79 nm (λ1) to 1540.56 nm (λ8), and the
downstream ones were allocated from 1558.17 nm (λ9) to 1561.01 nm (λ16), in both
cases with 50 GHz channel spacing; see Table (4.1).
At the OLT, we used a 100 Gb/s non-return-to-zero (NRZ) DP-QPSK real-time optical
coherent transceiver (TRx), an optical MUX/DEMUX with a 50 GHz grid, a WDM
gaussian optical filter, a booster amplifier for the downlink (DL), and a pre-amplifier
for the uplink (UL). The booster and pre-amplifier are using erbium doped fiber
amplifiers (EDFA).
At ONU side, we used the same 100 Gb/s non-return-to zero (NRZ) DP-QPSK real-
time optical coherent transceiver (TRx), and optical 1×8 coupler which defined in
simulator as 1×8 power splitter and 8×1 power coupler.
41
Figure (4.1): Architecture of 800 Gbps coherent WDM PON system
42
4.2.1 TRx structure
The TRx structure that is used in both OLT and ONUs is shown in Figure (4.2).
Figure 4.2): TRx components used to generate transmitted signal and decode
received one. (a) optical part. (b) Electrical part.
Figure (4.2) describes the internal hierarchy of used optical coherent TRx which is
consisting of following two parts:
1. Optical part (see Figure 4.2 (a)): contains optical DP-QPSK transmitter to
modulate the pseudorandom binary sequence (PRBS); i.e. info to be transmitted
on downstream signal, optical circulator to isolate upstream from downstream,
optical filter with gaussian frequency transfer function, and optical coherent DP-
PSK receiver to receive the uplink signal. (See Appendix 1 for details on optical DP-
QPSK transmitter and optical coherent DP-PSK receiver models).
43
2. Electrical part (see Figure 4.2 (b)): includes digital signal processor (DSP) for
QPSK component that performs several important functions to aid in recovering
the incoming transmission channel after coherent detection, decision component
that processes the I and Q electrical signal channels received from the DSP stage
then normalizes the electrical amplitudes of each I and Q channel to the respective
m-PSK grid and performs a decision on each received symbol based on normalized
threshold settings, two PSK sequence decoders to decode the sequence generated
by decision component, and finally a parallel to serial converter to couple the
two input sequences at bit rate R into one output sequence at 2R bit rate.
4.2.2 Wavelength spectrum
In our project, we used the 50 GHz grid-wavelengths as illustrated in Table (4.1)
Table (4.1): InGaAs wavelength spectrum used for up/down streams
Uplink Downlink
No. Wavelength
(nm)
Frequency
(THz)
No. Wavelength
(nm)
Frequency
(THz)
λ1 1537.79 194.95 λ9 1558.17 192.40
λ2 1538.19 194.90 λ10 1558.58 192.35
λ3 1538.58 194.85 λ11 1558.98 192.30
λ4 1538.98 194.80 λ12 1559.39 192.25
λ5 1539.37 194.75 λ13 1559.79 192.20
λ6 1539.77 194.70 λ14 1560.20 192.15
λ7 1540.16 194.65 λ15 1560.61 192.10
λ8 1540.56 194.60 λ16 1561.01 192.05
This laser wavelength spectrum exists in the ‘near infrared’ spectrum and can be
detected by indium gallium arsenide (InGaAs) photodetectors.
4.3 Results and discussion
4.3.1 Introduction
In this section, we will show the design network created in OptiSystem for the 100 km
span of single mode fiber (SMF) and back-to-back (B-to-B) model. Then a comparison
44
between the connected fiber link results and B-to-B model results will be presented at
the end of this chapter. Three main results will be discussed here, BER vs OSNR,
constellation diagram (see figure 4.3(a)), wavelength spectrum (see figure 4.3(b)), and
power budget of the model.
Figure (4.3): General diagrams (a) QPSK constellation diagram (b) Wavelengths
spectrum received at ONU side (Downlink)
Following table (4.2) is illustrating all paramters used in the Optisystem simulation
layout. As can be seen in the table, 20 dB gain was used in the preamplifier and booster
to compensate the fiber loss (0.2 dB/km × 100 km). Also, 1550 nm wavelength was
used as reference wavelength for all bidirectional devices such as fiber link,
multiplexer/demultiplexer and power splitter/combiner.
Table 4.2): Parameter values for devices used in Optisystem layout
Device (quantity) Parameter Value Unit
Layout (1) Bit rate 100×109 b/s
Symbol rate 25×109 Symbols/s
Samples per bit 4 -
Guard bits 100 -
Reference wavelength 1550 nm
Number of Iterations 5 -
Booster (1 in DL) Gain 20 dB
Pre-amplifier (1 in UL) Gain 20 dB
Bidirectional Optical Fiber (1) Distance 100 km
Reference wavelength 1550 nm
λ9 λ12 λ16
(a) (b)
45
Device (quantity) Parameter Value Unit
Attenuation 0.2 dB/km
Other parameters Default -
WDM Mux (1) Bandwidth 100 GHz
Insertion loss 0 dB
Filter Type Gaussian -
Channels 192.40, 192.35, 192.30,
192.25, 192.20, 192.15,
192.10, 192.05
THz
Other Parameters Default -
WDM De-Mux (1) Bandwidth 100 GHz
Insertion loss 0 dB
Filter Type Gaussian -
Channels 194.95, 194.90, 194.85,
194.80, 194.75, 194.70,
194.65, 194.60
THz
Other Parameters Default -
DP-QPSK Tx (16) Frequency Eight different values in
each UL/DL direction
THz
DP-PSK Rx (16) Frequency Eight different values in
each UL/DL direction
THz
Gaussian optical Filter (16) Frequency Eight different values in
each UL/DL direction
THz
Insetion Loss 0 dB
Bandwidth 100 GHz
DSP for QPSK (16) Propagation length 100 Km
Frequency Eight different values in
each UL/DL direction
THz
Insertion Loss 0 dB
Decision (16) Polarization type Dual -
Modulation Formate QPSK -
PSK Sequence Decoder (32) Bits per symbol 2 b/symbol
Phase offset 45 Degrees
BER Test Set (16) Polarization type Dual -
Number of guard bits 100 -
Sequence Length 65536 Bits
Sequence Length for
BER
65336 -
46
4.3.2 The 100 km span of SMF model results
In this subsection, we will present our simulation results using OptiSystem 15.2
(Optiwave, 2018) for the 100 km span of single mode fiber (SMF) model. Block
diagram in figure (4.1) illustrates the network elements model for the 8×8 coherent
WDM PON in which we measured the results.
4.3.2.1 Wavelengths spectrum of the SMF model
Figure (4.4) shows the wavelength spectrum in uplink and downlink. As can be
figured, all mentioned wavelengths in table (4.1) are allocated in the SMF span and
captured at the end of multiplexer in downlink and at end of power coupler in uplink.
Both spectrums were measured at the end of WDM Mux (in downlink) and at end of
power coupler (in uplink). As can be figured from spectrum, downlink spectrum power
is less than uplink due to the loss in WDM multiplexer.
(a)
47
(b)
Figure (4.4): Wavelengths spectrum view (a) Upstream [λ1 to λ8] (b) Downstream
[λ9 to λ16].
4.3.2.2 Constellation diagram of the SMF model
To show the constellation diagram of uplink and downlink signals, we showed all
results in two separated figures (4.5) and (4.6). In Figure (4.5), x and y polarization
constellation diagrams are shown for λ1, λ2, λ3, λ4, λ5, λ6, λ7, and λ8 which are the
upstream wavelengths. Figure (4.6), x and y polarization constellation diagrams are
shown for λ9, λ10, λ11, λ12, λ13, λ14, λ15, and λ16 which represent downstream
wavelengths. Following is a discussion of constellation diagrams in uplink and
downlink:
1. Uplink stream:
As can be concluded from constellation diagrams of uplink in figure (4.5), they show
clear constellation diagrams, which indicates that error free transmission can be
achieved.
48
Wavelength Constellation x-Polarization Constellation y-Polarization
λ1:
λ2:
λ3:
λ4:
λ5:
49
λ6:
λ7:
λ8:
Figure (4.5): Constellation diagrams in x (left) and y (right) polarization signals for
all 8 uplink wavelengths
2. Downlink stream:
Also, in the downlink constellation diagrams in figure (4.6), they show clear
constellation diagrams, which indicates that error free transmission can be achieved.
Wavelength Constellation x-Polarization Constellation y-Polarization
λ9:
50
λ10:
λ11:
λ12:
λ13:
λ14:
λ15:
51
λ16:
Figure (4.6): Constellation diagrams in x (left) and y (right) polarization signals for
all 8 downlink wavelengths
4.3.2.3 BER of SMF model
Following Table (4.3) shows the average log (BER) versus OSNR values added as
defined noise floor level to the downstream (received) signal for both streams and for
selected wavelengths. We used OSNR to examine the changes of noise floor level on
BER. From the table, we can figure that good BER can be achieved with relatively low
noise floor levels added by OSNR in both transmission links. Other downlink
wavelengths have similar results to λ9 and λ12. In uplink, λ1 and λ4 were chosen to
represent the BER values vs OSNR.
Better BER can be achieved by adjusting the OSNR levels to higher values. In real
world, no OSNR needed in implementation. We usually use OSNR just in the
simulation to check receiver sensitivity and thus BER.
Table (4.3): Simulated results for up/down stream BER (dB) in the 100 km SMF span
OSNR (dB)
BER (dB)
λ9 λ12 λ1 λ4
12 -1.844 -1.882 -1.766 -1.781
13 -2.208 -2.123 -2.016 -2.011
14 -2.433 -2.501 -2.315 -2.371
15 -2.736 -2.896 -2.67 -2.66
16 -3.258 -3.247 -3.06 -3.003
17 -3.7 -3.97 -3.49 -3.417
18 -4.9 -5.1 -4.72 -4.51
52
4.3.2.4 Power budget of SMF model
Table (4.4) summarizes the loss budgets obtained. The upstream achieved a loss
budget of 31.7 dB with an ONU output power of 15.7 dBm, and the downstream had
a 29.9 dB loss budget with an OLT output power of +14.4 dBm/ch. Based on the
standard specified maximum optical fiber attenuation of 0.2 dB/km at 1550 nm
wavelength and the maximum 10.9 dB insertion loss of 8 splits (ITU-T, 2012), we
found that these loss budgets support at least 8 ONU splits (10.9 dB) over 100 km of
SMF (0.2 dB/km x 100 km= 20.0 dB), where the total loss required to be
accommodated is 10.9 dB + 20.0 dB = 30.9 dB. Consequently, it was successfully
demonstrated that our simulated 100 Gb/s/λ-based coherent WDM-PON system has a
feasible loss budget which can support an 800 Gb/s symmetric bi-directional MFH
suitable for 5G.
Table (4.4): Summary of Simulated loss budget
Parameter Unit Upstream Downstream
Bit rate per λ Gb/s 100 100
OLT in/out power dBm/ch -16 +14.4
ONU in/out power dBm/ch +15.7 -15.5
Distance (Max loss) Km (dB) 100 (20 dB) 100 (20 dB)
ONU splits (Max loss) (dB) 8 (10.9 dB) 8 (10.9 dB)
Loss Budget dB 31.7 29.9
4.3.3 Back-to-Back model results
On the B-to-B model, one DP-QPSK transmitter is connected directly to the receiver
without the existence of fiber link. This model will show BER and constellation
diagrams without the effect of different types of dispersion in fiber (i.e. polarization
mode dispersion (PMD) and chromatic dispersion (CD)) and other nonlinear effects.
Figure (4.7) shows the B-to-B network simulated in OptiSystem (component symbols
and definitions can be found in Appendix 1).
53
Figure (4.7): B-to-B model for 100 Gb/s DP-QPSK fiber transmission system
4.3.3.1 Constellation diagram of B-to-B model
Figure (4.8) shows the x and y polarization constellation diagram for the B-to-B model
which indicating almost noise-free results. In the B-to-B model there is no dispersion
or nonlinear fiber effects since the transmitter is connected directly to the gaussian
optical filter then to receiver.
(a)
(b)
Figure (4.8): Constellation diagram for B-to-B model with λ9 as input and OSNR 17
dB. (a) x-polarization (b) y-polarization
4.3.3.2 BER of B-to-B model
Following Table (4.5) shows the average log (BER) versus OSNR values added as
defined noise floor level to the downstream (received) signal. We can adapt OSNR to
the desired level of BER.
DP-QPSK
Transmitter PRBS Gaussian
optical filter DP-PSK
Receiver
DSP Decision
Component
PSK sequence
Decoder
PSK sequence
Decoder
P/S
converter
BER
Tester
Direct
connection
54
Table (4.5): Simulated results for downstream BER in B-to-B case
OSNR (dB) BER (dB)
12 -1.88
13 -2.247
14 -2.633
15 -3.123
16 -3.611
17 -4.235
18 -5.213
As can be concluded from above table, good BER can be achieved with relatively
small noise power added by OSNR.
4.3.4 Comparison of B-to-B and 100 km SMF results
Figure (4.9) shows a comparison of the BER vs OSNR in both models, B-to-B and 100
km span of SMF. It is clear from the graph that the power penalty is negligible as the
BER results are very close to those of the back to back case. It shows that as the OSNR
level changes the BER (dB) reduces for better value. This indicates a good network
that can be relied on.
Simulation comparison result indicates that several types of dispersion and nonlinear
effects of fiber have some penalty factor on BER results. As can be seen in tables (4.2)
and (4.4), BER degraded a little for OSNR values 14 to 17 dB. But it seems improved
for OSNR 18 dB.
So, our solution of coherent WDM DP-QPSK PON is reliable for 5G transport. This
achievement of 100 km span of fiber transmission shows a close BER to the B-to-B
model without fiber. It means that using such network in 5G and B5G transmission
will move the transmission networks to a new era.
55
Figure (4.9): BER versus OSNR for B-to-B and 100 km span of SMF
4.3.5 Comparison of 100 km SMF downlink vs uplink BER results
Figure (4.10) shows a comparison of the BER in both transmission directions uplink
and downlink for a given values of OSNR.
For better view of the graph in figure (4.10), we selected λ9 and λ12 to represent
downlink and λ1 and λ4 to represent uplink. Numerical values of the graph are
illustrated in table (4.3).
Figure (4.10): BER versus OSNR for uplink and downlink in the 100 km of SMF
-6
-5
-4
-3
-2
-1
0
12 13 14 15 16 17 18
Ave
rage
log(
BER
)
OSNR (dB)
BER measurments for uplink and downlink
λ9
λ12
λ1
λ4
56
First impression that we can figure from UL/DL BERs, is that as long as the OSNR
increases; i.e. sensitivity of the receiver, as long as BER decreases in both directions.
Secondly, it can be shown clearly that BER in downstream is slightly better than BER
in upstream. This is because of the usage of booster in downlink signal before entering
the fiber. In uplink, the pre-amplifiers have a positive and negative impacts. The
positive one is amplifying the signal that carries the information. Negative impact that
noise signal generated by dispersion and nonlinear effects of fiber span is amplified
too. So, the booster location of the downlink is amplifying the pure information signal
that implies a good improvement in BER as can be seen.
4.3.6 Comparison of 100 km vs 80 km SMF downlink BER results
Figure (4.11) shows a comparison of the BER in downlink transmission direction for
different SMF span distances and a given value of OSNR.
Figure (4.11): Comparison of 100 km vs 80 km SMF span
As can be figured from this comparison, BER of first DL-wavelength (λ9) in 80 km
SMF span seems to be slightly better than the first DL-wavelength in the 100 km SMF
span. This is a normal result for shortest fiber spans; i.e. the shorter fiber length, the
better BER.
-6
-5
-4
-3
-2
-1
0
12 13 14 15 16 17 18
Ave
rage
log
(BER
)
OSNR input noise power
BER Mesurments of 100 km vs 80 km SMF
100 km λ9
80 km λ9
57
1.2 Summary
In this chapter, model of the 800 Gb/s coherent WDM PON was described in details.
A simulation of the model was done using OptiSystem version 15.0. Results of the
simulation including constellation diagrams, BER, power budget, and wavelength
spectrum was discussed. Constellation diagrams of all 16 wavelength (8 uplink and 8
downlink) indicate that error free transmission can be achieved. Wavelength spectrum
for the uplink and downlink was presented with brief discussion. As a result, great
achievement has been introduced in building such network since the comparison
results with B-to-B model is very fascinating. Finally, a comparison of the B-to-B
model with SMF one was introduced in last section. It is clear from results listed in
this chapter that our simulated 100 Gb/s/λ-based coherent WDM-PON system has a
feasible result which can support an 800 Gb/s symmetric bi-directional MFH suitable
for 5G.
58
Chapter 5
Conclusions and Future
Work
59
Chapter 5
Conclusions and Future Work
5.1 Conclusions
Cellular mobile operators use fiber optics to connect their networks with central
offices in most of modern cities. While new technology is about to be announced such
as 5G, the need for fast reliable networks with high capacity is increasing.
The 5G NR architecture calls for new design and new challenges for the
underlying transport network infrastructure. Different functional split options in the
radio signal processing chain are applicable for different deployment scenarios. Given
the assumption of optical access, this thesis focused on the bandwidth and latency
requirements and discussed their effects on optical access networks to support 5G
transport. Standards development activities of 5G NR transport and optical access
networks were reviewed. As an important next step, the experts in both wireless and
wireline standards bodies must work together to coordinate the interface specifications
between radio network layer and transport network layer.
In this thesis, a new achievement of 800 Gb/s for 100 km span of single mode
fiber is presented. Design block diagrams and different results were discussed. DP-
QPSK transmitters were used to achieve highest capacity. Homodyne DP-PSK
receivers were used to achieve our desired fiber length with lowest BER. The 8×8
WDM model illustrated can be a reliable network to deploy 5G transport architecture.
The results verify that the modified topology of coherent WDM DP-QPSK PON
using 100 km span of single mode fiber (SMF) is very adequate for 5G MFH and MBH
requirements, as it appears in the constellation diagrams of all 16 wavelengths and
BER results for uplink and downlink. The BER results of UL and DL are very close
to BER of the back-to-back system. This conclude that dispersion and other nonlinear
effects of the fiber span can be neglected with the fundamentals of using mentioned
design.
60
5.2 Future Work
Implementing the designed network of the coherent WDM DP-QPSK PON on
hardware will give good support for the results.
On the other hand, a development of the suggested network will continue to reach
more than 1 Tbps in capacity for longer distances. Also, an improvement on the
network may be apply with replacing homodyne receiver with heterodyne one for
reducing cost effect when interfacing to radio equipment.
61
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Chanclou P. (2018). Which fiber access technology for 5G. presented in the 2020 Network
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Chung Y. C. (2013). High-Speed Coherent WDM PON for Next-Generation Access Network.
IEEE, ICTON.
De La Oliva A., Costa Pèrez X., Azcorra A., Di Giglio A., Cavaliere F., Tiegelbekkers D.,
Lessmann J., Haustein T., Mourad A., & Iovanna P. (2015). Xhaul: Toward an Integrated
Fronthaul/Backhaul Architecture in 5G Networks. Paper submitted in IEEE Wireless
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El-Nahal F. (2018). Coherent Quadrature Phase Shift Keying (QPSK) Optical Communication
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Hatta S., Tanaka N., and Sakamoto T. (2017). Feasibility Demonstration of Low Latency DBA
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Hatta S., Tanaka N., Sakamoto T. (2016). Implementation of Ultra-Low Latency Dynamic
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Honda K., Nakamura H., Hara K., Sone K., Nakagawa G., Hirose Y., Hoshida T., Terada J.,
and Otaka A. (2018). Wavelength Adjustment of Upstream Signal using AMCC with
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Houtsma V. and van Veen D. (2018). Bi-Directional 25G/50G TDM-PON With Extended
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ITU-T. (2012). Characteristics of Multi-Degree Reconfigurable Optical Add/Drop
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Keiser G. (2011). Optical Fiber Communications (4th Ed): McGraw-Hill New York.
Kunstler J. (2018). NG-PON2 market and ecosystem update. Broadband Forum NG-PON2
council workshop, San Diego.
Li J., Sun W., Yang H., and Hu W. (2014). Adaptive Registration in TWDMPON With ONU
Migrations. Journal of Optical Communication Networks, 6, 943-951.
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Light R. P. (2015). Backhaul Presents 5G's Biggest Challenge. https://www.lightreading.com
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Wireless. Journal of Optical Communication Networks, 8, B70-B79.
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Inc, Ottawa, ON, Canada. [Online] Available: https://optiwave.com/
Suzuki N. and others. (2018). 100 Gb/s to 1 Tb/s Based Coherent Passive Optical Network
Technology. Journal of Lightwave Technology, 36(8).
Suzuki N., Yoshima S., Miura H., and Motoshima K. (2017). Demonstration of 100-Gb/s/λ-
Based coherent WDM-PON system using new AGC EDFA based upstream preamplifier
and optically superimposed AMCC function. IEEE, Journal of Lightwave Technology,
35(8), 1415–1421.
Tao M., Zhou L., Zeng H., Li S., and Liu X. (2017). 50-Gb/s/λ TDM-PON Based on 10G
DML and 10G APD Supporting PR10 Link Loss Budget after 20- km Downstream
Transmission in the O-band. Optical Fiber Communications Conference.
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A Review. Journal of lightwave technology, 35(4).
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meeting.
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Standards. IEEE, Journal of Lightwave Technology, DOI: 10.1109/JLT.2018.2856828.
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Optical Amplifier Supporting PR-30 Link Loss Budget. Optical Fiber Communications
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63
Appendix 1
OptiSystem tool
Optical communication systems are increasing in
complexity on an almost daily basis. Computer
simulations have become a useful part of mathematical
modelling of many natural systems; they play a role in
the process of engineering new technology to gain insight into the operation of those
systems.
OptiSystem is an innovative optical communication systems simulation package that
designs, tests and optimizes virtually any type of optical link in the physical layer of a
broad spectrum of optical networks.
OptiSystem is a stand-alone product that does not rely on other simulation frameworks.
It is a physical layer simulator based on the realistic modelling of fiber-optic
communication systems also possesses a powerful new simulation environment and a
hierarchical definition of components and systems.
The extensive library of active and passive components includes realistic, wavelength-
dependent parameters. Parameter sweeps allow investigating the effect of particular
device specifications on system performance (Optiwave, 2018).
Following items list used in thesis network design:
1. Optical DP-QPSK Transmitter:
This component simulates a single channel optical
coherent transmitter with an optical dual-polarization
QPSK signal. Technical background can be found in
Appendix 2.
64
2. Optical Coherent DP PSK/QAM Receiver:
The component simulates an optical dual-polarization
coherent receiver for m-PSK or m-QAM signals based on
a homodyne design. Technical background can be found
in Appendix 2.
3. Universal DSP:
The Universal digital signal processor (DSP)
component performs digital domain impairment
compensation to aid in recovering the incoming
transmission signal after coherent detection. It
provides support for the following higher order
modulation formats:
• BPSK, QPSK, 8PSK, 16PSK
• 8QAM, 16QAM, 32QAM, 64QAM, 128QAM, 256QAM
In addition, for QAM modulation formats; square, star, and circular constellation
formats are supported. Technical background can be found in Appendix II.
4. Gaussian Optical Filter:
Optical filter with a Gaussian frequency transfer
function. Technical background can be found in
Appendix 2.
5. Decision:
The Decision component processes the I and Q electrical
signal channels received from the DSP stage, normalizes
the electrical amplitudes of each I and Q channel to the
respective m-PSK or m-QAM grid and performs a decision on each received symbol
based on normalized threshold settings. It supports the following modulation formats:
65
• BPSK, QPSK, 8PSK, 16PSK
• 8QAM, 16QAM, 32QAM, 64QAM, 128QAM, 256QAM
In addition, for QAM modulation formats; square, star, and circular constellation
formats are supported. The Decision component supports single or dual polarization
(SP/DP) multiplexing schemes. Technical background can be found in Appendix 2.
6. PSK sequence decoder
Phase-shift keying sequence decoder.
7. Parallel to serial converter (P/S)
Combine 2 input sequences at bit rate R into one output
sequence at 2R bit rate.
8. Bit Error Rate (BER) Test set
This component generates a large bit sequence, transmit s
the bit sequence to DUT, and then compares the bit
sequence it received from DUT to the transmitted bit
sequence. Technical background can be found in
Appendix 2.
9. Ideal Circulator
Ideal optical isolator. User can control the insertion loss
only— there is no return loss or isolation.
10. N×1 Mux Bidirectional
This component is bi-directional multiplexer or
demultiplexer. It has a trapezoidal filter shape and arbitrary
number of channels.
66
11. 1×N Splitter Bidirectional
This component is a power splitter and combiner with
arbitrary number of input ports. It is bidirectional, with
wavelength dependent insertion loss and return loss.
12. Bidirectional Optical Fiber
The component simulates the bidirectional propagation of
arbitrary configuration of optical signals in a single-mode
fiber. Dispersive and nonlinear - self-phase modulation (SPM), cross-phase
modulation (XPM), stimulated Raman (SRS) and Brillouin (SBS) scattering effects -
are taken into account.
Raman interaction for an arbitrary configuration of sampled and parameterized signals
is also considered. The component provides most of the functionality of the total field
approach fiber model (except for the simulation of the Raman effect in birefringent
fibers). The four-wave mixing effect between multiple sampled signals is not
considered.
13. Optical Amplifier
Enables the design of amplifiers, including EDFAs, that
consider pre -defined operational conditions. This means that
expected gain, noise figure, and amplifier output power can be
previously specified. The amplifier presents the same facilities
as a black box model, which enables you to select the operation mode with gain
control, power control, or to perform simulations under saturated conditions, as well
as define the expected amplifier performance. It is especially suited to perform prompt
performance analysis of one or cascaded amplifiers in a long-haul system.
67
Appendix 2
Technical Background of OptiSystem elements
In this appendix, we will show technical background of main OptiSystem components
used to build network illustrated in Chapter 4. Components that will be technically
viewed here are DP-QPSK transmitter, DP-PSK receiver, universal DSP, gaussian
optical filter, decision, and BER test set.
1. DP-QPSK transmitter:
The layout representing the optical coherent dual-polarization QPSK transmitter
component is shown in figure (A2.1) below. In this case, polarization multiplexing is
used, the laser output is split into two orthogonal polarization components, which are
modulated separately by QPSK modulators (similar to the one shown in the QPSK
transmitter layout) and then combined using a polarization beam splitter (PBS).
Figure (A2.1): DP-QPSK optical transmitter layout
68
2. DP-PSK receiver:
The optical coherent dual-polarization PSK receiver consists of a homodyne receiver
design. The component has a LO laser polarized at 45o relative to the polarization beam
splitter, and the received signal is separately demodulated by each LO component
using two single polarization PSK receivers. Figure (A2.2) shows the layout
representing the receiver.
Figure (A2.2): DP-QPSK optical receiver layout
3. Universal DSP
The Universal DSP component performs several important functions to aid in
recovering the incoming transmission channel(s) after coherent detection. It can be
used with coherent system designs that utilize m-QAM or m-PSK modulation with
single polarization (X channel) or dual polarization (X and Y channel) multiplexing.
Block diagram of the universal DSP is illustrated in Figure (A2.3).
The Universal DSP component includes 12 functions and algorithms starting with a
preprocessing stage (3 functions) followed by the signal recovery stage (8 functions
and algorithms):
69
Preprocessing stage
• Add Noise to Signal (Samples/Symbol = (4 or 8) x Samples per bit)
• DC Blocking (Samples/Symbol = (4 or 8) x Samples per bit)
• Normalization (Samples/Symbol = (4 or 8) x Samples per bit)
Main algorithms stage
• Bessel Filter (Samples/Symbol = (4 or 8) x Samples per bit)
• Resampling (Samples/Symbol = 2)
• Quadrature Imbalance (QI) Compensation (Samples/Symbol = 2)
• Chromatic Dispersion (CD) Compensation (Samples/Symbol = 2)
• Nonlinear (NL) Compensation (Samples/Symbol = 2)
• Timing Recovery (Samples/Symbol = 2)
• Adaptive Equalizer - AE (Samples/Symbol = 2)
• Down-sampling (Samples/Symbol = 1)
• Frequency Offset Estimation - FOE (Samples/Symbol = 1)
• Carrier Phase Estimation - CPE (Samples/Symbol = 1)
Figure (A2.3): Universal DSP High Level Algorithm Design
70
4. Gaussian Optical Filter
The filter transfer function is:
where H(f) is the filter transfer function, α is the parameter Insertion loss, fc is the filter
center frequency defined by the parameter Frequency, B is the parameter Bandwidth,
N is the parameter Order, and f is the frequency.
5. Decision
The Decision component processes the I and Q electrical signal channels received
from the DSP stage, normalizes the electrical amplitudes of each I and Q channel to
the respective m-PSK or m-QAM grid and performs a decision on each received
symbol based on normalized threshold settings. It supports the following modulation
formats:
• BPSK, QPSK, 8PSK, 16PSK
• 8QAM, 16QAM, 32QAM, 64QAM, 128QAM, 256QAM
In addition, for QAM modulation formats; square, star, and circular constellation
formats are supported. The Decision component supports single or dual polarization
(SP/DP) multiplexing schemes Prior to processing the input data, the electrical signals
are first re-sampled to 2 Samples per symbol (1st and N/2+1 sampled signal are used
for the re-sampling (where N = Samples per symbol). The second data point (N/2+1)
is then selected - to bring the sampling rate to 1 Sample/symbol. The Decision
component performs the following functions (in order):
• DC blocking
• Normalization
• Error Vector Magnitude (EVM) calculation
• Decision
71
• Calculate Symbol Error Rate (SER)
The decision algorithm performs a soft decision on all the received symbols based on
the threshold boundaries. For example, for QPSK the boundaries (x = 0; y = 0) are
used. Similarly, for 16-QAM the boundaries (x = -1, 0, 2; y = -2, 0, +2) are used. See
Figure (A2.4).
Figure (A2.4): Examples decision boundaries for QPSK and 16-QAM
When “Optimize decision” is selected, three additional procedures are performed to
correct any residual mis-alignment or rotations in the constellation prior to applying
the soft decisions.
6. Bit Error Rate (BER) Test set
Introduction
The BER Test Set (BERT) performs the direct error counting for one or more sweep
iterations of a defined sequence length of bits. From this data it is possible to determine
the bit error rate (BER) for each iteration and the running average of BERs. BER data
is also provided for X, Y and X+Y polarization channels.
Overview of main parameters
Prior to performing the BER analysis of a system, it’s important to determine if guard
bits and leading/trailing zeros will be needed. For example, when performing the
72
analysis of coherent systems, the DSP algorithm requires a certain number of bits to
train the compensation system. Guard bits are thus useful as we do not want to count
“training” errors as part of our overall BER system performance. Guard bits are set in
Layout parameters. This value specifies to the BERT to ignore the same number of
bits at the beginning and end of each bit sequence.
For the case of a single polarization system the BER is:
𝐵𝐸𝑅 =𝐸𝑟𝑟𝑜𝑟𝑠
𝑆𝑒𝑞𝑢𝑒𝑛𝑐𝑒𝐿𝑒𝑛𝑔𝑡ℎ − 2 × 𝐺𝑢𝑎𝑟𝑑𝐵𝑖𝑡𝑠
For the case of a dual polarization system the BER is:
𝐵𝐸𝑅 =𝑋𝐸𝑟𝑟𝑜𝑟𝑠 + 𝑌𝐸𝑟𝑟𝑜𝑟𝑠
𝑆𝑒𝑞𝑢𝑒𝑛𝑐𝑒𝐿𝑒𝑛𝑔𝑡ℎ − 2 × 𝐺𝑢𝑎𝑟𝑑𝐵𝑖𝑡𝑠
where the Errors are counted only for the portion of the sequence that are outside of
the guard bits (GB) (see following example).
Example: How BER is calculated when using guard bits?
Let’s take for example the following 16-bit sequence which has four-bit errors at the
end of a transmission link (the errors are shown in bold red)
Transmit 0 1 1 0 1 0 1 1 1 1 0 0 0 1 0 0
Receive
(GB = 0)
1 1 1 0 0 0 1 1 0 1 0 0 0 1 1 0
If Guard bits = 0, then the BER = 4/16 = 0.25. If Guard bits = 3, then we remove the
first and last 3 bits from the received bit sequence as follows and hence, the resulting
BER is now 2/ (16-6) = 0.2:
Receive
(GB = 0)
0 0 0 1 1 0 1 0 0 0