Contents
• Introduction
• Optical code-division multiplexing (OCDM) techniques
• Dispersion in optical fiber
• Motivation
• Theoretical Model and Analysis
• Spectral amplitude encoding (SAE) OCDM System
• Linear Dispersive Channel
• Theoretical BER over Linear Dispersive Channel
• Simulation Model
• Results & Discussions
• Conclusions

Overview
• SAE/OCDM has been considered as a promising technique for
the next-generation optical access and local networks
• Impact of dispersion is one of critical factors to performance of
SAE/OCDM system
• This has been analyzed theoretically and experimentally [3][5]
• In this work, we implement a simulation model using
OptiSystem® software suite for analyzing the performance of
SAE/OCDM systems
• We especially focus on modeling and analyzing the impact of dispersion

• Time Domain Encoding:
• Spectral Amplitude Encoding (Freq. domain):
OCDM (Optical Code Division Multiplexing)
1 0
t t
Tb
Tc = Tb / NTc
01010101
t
f
01010101
0
1
0
1
0
1
0
1
Broadband
source
t
f
Tc=Tb
Dispersion
phenomena
1
2
3
4

Impact of Dispersion
1
0
1
0
0
0
1
• Chromatic dispersion (group velocity dispersion, aka. GVD)
• Peak reduction
• Pulse Broadening
• Time Skewing

Motivation (1)
• Experimental study on the impact of dispersion has been reported
• H. Tamai et al., “Experimental study on time-spread/wavelength-hop
optical code division multiplexing with group delay compensating
en/decoder,” IEEE Photon. Technol. Lett., 2004.
• It is the experimental study with real implementation
• Limitation: expensive, not flexible, delayed, difficult to analyze when
scalability is required
• Theoretical study using the Linear dispersive channel model for
analyzing the performance of SAE/OCDM systems
• Ngoc T. Dang et al., “Performance Analysis of Spectral Amplitude
Encoding OCDM Systems over a Linear Dispersive Optical Channel”,
IEEE/OSA J. Optical Comm. & Netw., 2009.
• Could easily analyze with different configuration, settings
• Validation required, some assumption is still far from practical conditions
SAE/OCDM SystemsSaturday, June 21, 2014

Motivation (2)
• Understanding the impact of dispersion is critical and needed to be
carefully considered in the system design
• Our proposal
• A trade-off solution
• Analyze the performance of SAE/OCDM system over dispersive channel
using optical simulation system
• Advantages
• Closer to the real implementation
• However, it is
• Cheaper
• Flexible: Easy to modify system’s parameters,
• More quickly  faster R&D process
• Scalable: easily analyze with a large number of users

THEORETICAL
ANALYSIS
Saturday, June 21, 2014

SAE/OCDM System: Principle
Transmitter -
User #1
Code C1
Transmitter -
User #2
Code C2
…
Transmitter -
User #K
Code CK
Receiver -
User #1
Code C1
Receiver -
User #2
Code C2
Receiver -
User #K
Code CK
…
Combiner
K • 1
Splitter
1 • K
Dispersive
optical channel
APD2
C1
C1
APD1

Linear Dispersive Channel Model
• The optical pulse propagation model with modified factors
was used for analytical modeling:
*Average received power of chip
number i transmitting over L km
of fiber
Gaussian pulse
peak power
attenuation
*Ps: Transmitted power per bit
K: Number of users
N: Code length
T0: half width of Gaussian Pulse

System’s BER over Linear Dispersive Channels (APD
Receiver)
• Received desired signal power (after decoding):
• Received MAI signal power (after decoding):
• BER:
SAE/OCDM Systems
*Additive branch
*Subtractive branch
*Additive branch

CONSTRUCTION OF
SIMULATION MODEL
AND ANALYSIS

Simulation Model for Transmitter
Hadamard code –
N=12 ω=6 λ=3
Optical Power
Combiner
Ps
Other
Users
PE = Pc (N -w)+ Pcw
gw
N
-g0
æ
è
ç
ö
ø
÷
γw
γ0
Ps
Pc =
Ps
N
101010101010
Fiber Bragg Gratings

Simulation Model
with APD Receiver
Cm
Cm
Optical Splitter
Optical Power
Splitter
Other User:
10101010
10100101
bit 1
bit 1
bit 0
bit 0

Results (Theoretical vs. Simulation)
• The performances of system with two cases: considering
dispersive channel and non-dispersive (only attenuation)
channel.
SAE/OCDM Systems
* 3 x 500 Mb/s active users in total 8 users, 10 km
optical fiber with attenuation 0.2dB/km, D = 16.75
ps/nm/km
BER vs.
APD gain,
Ps=-17dBm
BER vs. Ps,
APD gain = 7
0.5 dB

Conclusions & Summary
• We have built the computer simulation model for
SAE/OCDM system using APD receiver with 3 activating
users in 8 users total
• The well-matched simulation and theoretical results has
validated the simulation model. The simulation model
therefore could be used for OCDM system R&D
• Next step: we will build the simulations for more complete
models, with more practical parameters and more
practical devices such as EDFA, dispersion shifted fiber.

Question time
Thank you!

Some of recent experimental model for
SAE/OCDM systems
• Julien Penon et al., “Spectral-Amplitude-Coded OCDMA
Optimized for a Realistic FBG Frequency Response”,
Journal of Lightwave Technology, 2007.
• Mohammad Reza Salehi et al., “Code Performance
Comparison in SAC-OCDMA Systems under the Impact of
Group Velocity Dispersion”, J. Opt. Commun., 2012

Simulation of Linear
Dispersive Channel
SAE/OCDM Systems
Without
GVD
With GVD
1549 nm 1554 nm

Transmitter: Principle
Laser
Source
Spectral
Encoder
Data (0,1)
Cm
channel (OF)
Transmitter
λ1 … λ5 … λ8 λ2 λ4 λ6 λ8
Ps P =
Ps
N
´w = Pcw
Ps
Cm: 0 1 0 0 1 1 1 0
λ1λ2λ3λ4λ5λ6λ7λ8
Hadamard code –
N=8 ω=4 λ=2
Hadamard code:
• Code length: N – number of chips
• Code weight: ω – number of chip 1s
• In-phase cross correlation: λ – number
of similar chip 1s of two codes.
•
•
RCm,Cn
= cm,icn,i =
w if m = n
l if m ¹ n
ì
í
ï
îïi=1
N
å
w = N / 2,l = N / 4,RCm,Cn
=w - RCm,Cn
= N / 4
SAE/OCDM Systems

Motivation (2) (Obsoleted)
• Problem
• Theoretical model required to be validated
• The practical experiments: expensive, not scalable, not flexible and
delayed
• Some proposed models have assumption is far from practical
implementation. The dispersive characteristic of OF has not been
consider in experiment.
• Advantages
• Scalable: large and flexible number of users
• Easy to modify system’s parameters
• Get the result quickly  faster R&D process
• Cheaper than the real implementation

Multiplexing Techniques
Time t
λ
Wavelength
Time t
Wavelength
λ
t
λ
Code
• Codes used for
multiplexing
• Asynchronous access
ability
• Flexible number of
users
• Possibly cheaper
Time division
multiplexing(TDM)
Wavelength division
multiplexing(WDM)
Code division
multiplexing (CDM)
• Time synchronization
required
• Limited speed by
electronic processing
• Wavelength
management required
• Expensive

Simulation Systems
Other
Users
λ1=1549 λ2=1549.5 λ3=1550 λ4=1550.5
User 1 code: 11110000
λ5, λ6,
λ7, λ8,
Cm
Cm
Hadamard code –
N=8 ω=4 λ=2
Optical Splitter
Optical Power
Splitter
Optical Power
Combiner
Gratings
Ps

SAE/OCDM Receiver
Coupler
(3dB)
Decoder 1
Decoder 2
Threshold
Detection
Data (0,1)
PD1
PD2
Cm
Cm
I2
I = I2-I1
I1
channel (OF)
Pin1 =
Ps
N
RC1,C1
Pin2 =
Ps
N
RC1,C1
Receiver
delay
APD1
APD2
Balanced detection
λ2
λ7
λ5
λ6
λ2
λ7
λ6
λ5

• Received power at receiver #1 (designate for user #1):
• Complement code
branch - data:
• Direct code branch-data :
• Multiple Access Interfering:
• Balanced Detection:
PD1 =
Ps (gw - Ng0 )
2gwK
Theoretical Calculation
PD2 =
Ps (gw -wg0 )
2gwK
PI =
1
4K 1
K-1
å Ps -
Ps (w + l)g0
gw
æ
è
ç
ö
ø
÷
I1 = MÂ[(PD1 +PI )-(PD2 +PI )]

Spreading Sequence (Code)
• m-sequence (N, (N+1)/2, (N+1)/4), Hadamard (N, N/2, N/4),
MQC (N=p2+p, ω=p+1, λ=1) (p is odd prime number).
• There are several construction of these code sets.

OCDM Performance over Dispersive Channels

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Notes de l'éditeur