Coherent Passive Optical Networks for 5G Transport · Building low-latency and high-capacity...

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


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

http://www.cs.stir.ac.uk/~kjt/research/conformed.html

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



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



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


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


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)

https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&ved=2ahUKEwjC5LDUr6ffAhWGb1AKHRSRBEMQjRx6BAgBEAU&url=https://sites.google.com/site/fiveguyscubesats/communication-systems/cubesat-transmitter-system&psig=AOvVaw3YpBQ1HJan8CQiUYJqWk9I&ust=1545153290161104

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


THz

Gaussian optical Filter (16) Frequency Eight different values in


THz

Insetion Loss 0 dB

Bandwidth 100 GHz

DSP for QPSK (16) Propagation length 100 Km

Frequency Eight different values in


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:


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:


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

The Reference List

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Ansari J. Z. N. (2013). Media Access Control and Resource Allocation for Next Generation

Passive Optical Networks. Springer New York Heideelberg Dordrecht London Library of

Congress.

Chanclou P. (2018). Which fiber access technology for 5G. presented in the 2020 Network

Vision 5G and Optical Networking Panel at the Optical Fiber Communications

Conference.

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

Communications, 15, 1536-1284.

El-Nahal F. (2018). Coherent Quadrature Phase Shift Keying (QPSK) Optical Communication

Systems. Optoelectronics letters, 14(5), pp: 372-375.

Hatta S., Tanaka N., and Sakamoto T. (2017). Feasibility Demonstration of Low Latency DBA

Method with High Bandwidth-efficiency for TDM-PON. Optical Fiber Communications

Conference, M3I.2.

Hatta S., Tanaka N., Sakamoto T. (2016). Implementation of Ultra-Low Latency Dynamic

Bandwidth Allocation Method for TDM-PON. IEICE Communications Express, DOI:

10.1587/comex.2016XBL0143.

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

Power Monitoring for WDM-PON in 5G Mobile Era. Optical Fiber Communications

Conference.

Houtsma V. and van Veen D. (2018). Bi-Directional 25G/50G TDM-PON With Extended

Power Budget Using 25G APD and Coherent Detection. Journal of Lightwave Technol,

36, 122-127.

ITU-T. (2012). Characteristics of Multi-Degree Reconfigurable Optical Add/Drop

Multiplexers, ITU-T Standard Series G.672. https://www.itu.int/rec/T-REC-G.672

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.

62

Light R. P. (2015). Backhaul Presents 5G's Biggest Challenge. https://www.lightreading.com

Liu X. and Effenberger F. (2016). Emerging Optical Access Network Technologies for 5G

Wireless. Journal of Optical Communication Networks, 8, B70-B79.

Optiwave. (2018). OptiSystem software tool to simulate optical networks. Optiwave Systems

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.

Teixeira A., Shahpari A., Ferreira R., Guiomar F. P., and Reis J. D. (2017). Coherent Access:

A Review. Journal of lightwave technology, 35(4).

Ujikawa H. and Nakamura H. (2018). NTT_PON upgradability for mobile. FSAN Osaka

meeting.

Umeda D. and Liu D. (2018). Gain Control of SOA Preamplifier. umeda_3ca_1b_0318, IEEE

802.3ca meeting.

Wang C. X., Haider F., Yang Y., Yuan D., Aggoune H. M., Haas H., Fletcher S., Hepsaydir

E. (2014). Cellular Archeticture and Key Technologies for 5G Wireless Communication

Networks. IEEE, Cimmunications Magazine, 0163-6804/14.

Wey J. S. and Zhang J. (2018). Passive Optical Networks for 5G Transport: Technology and

Standards. IEEE, Journal of Lightwave Technology, DOI: 10.1109/JLT.2018.2856828.

Yang B. (2017). Key WDM-PON Technologies for 5G Fronthaul. ZTE Technology Magazine,

19(5), paper No. 30.

Zhang J., Wey J. S., and Huang X. (2017). Experimental Results of Single Wavelength 50G

PON. IEEE 802.3ca meeting.

Zhang J., Wey J. S., Yu J., Tu Z., Yang B., Yang W., Guo Y., Huang X., Ma and Z. (2018).

Symmetrical 50-Gb/s/λ PAM-4 TDM-PON in O-band with DSP and Semiconductor

Optical Amplifier Supporting PR-30 Link Loss Budget. Optical Fiber Communications

Conference, M1B.4.

Zhou X. and Deng N. (2015). A 25-Gb/s 20-km wavelength reused WDM system for mobile

fronthaul applications. European Conference on Optical Communication, DOI:

10.1109/ECOC.2015.7341998.

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.

https://optiwave.com/optisystem-overview/

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




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:




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

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