New Frontiers in Optical Networks

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New Frontiers in Optical Communication Systems & Networks (by Ioannis Tomkos & partners)“Networks and Optical Communications” research group – NOC
New Frontiers in
Optical Communication Systems & Networks
Presented by: Dr. Ioannis Tomkos (itom@ait.gr)
Co-authors: Behnam Shariati, Jose Manuel Rivas-Moscoso, Nikolaos-Panteleimon Diamantopoulos,
Dimitrios Klonidis, Dan M. Marom
International Conference on Transparent Optical Networking
(ICTON), Girona, July 2017

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New Frontiers in Optical Communication Systems & Networks (by Ioannis Tomkos & partners)
NOC’s research contributions in optical
communications systems and networks
Scope:
Research on architectures,
protocols, algorithms, transmission
systems, technologies and
technoeconomic studies for high-
speed telecommunication systems
applicable in backbone core/metro
networks, access networks and
datacenter interconnection (DCNs)
Scientific Results (2003-2016):
 Over 150 publications in archival
scientific journals and magazines
 Over 450 publications in major
international conferences and
workshops
 Participated in 25 EU research
projects, including 18 EU funded
projects: 5 projects within FP6, 14
projects within FP7 and 2 H2020
 Led 9 EU research projects as
Technical Manager of the entire
consortium: 2 FP6 and 6 FP7
 Many awards & distinctions

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AIT’s NOC EU projects in time per topic
Over 100MEuros Funding overall – Close to 10MEuros for AIT
…fortunate to work effectively with many partner organizations and experts!

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Main research focus (and focus of this talk):
Core/Metro Optical Networks with focus on FONs
I. Tomkos, S. Azodolmolky, J. Sole-Pareta, D. Careglio, E. Palkopoulou,
“A Tutorial on the Flexible Optical Networking Paradigm (FON): State of the Art, Trends, and Research Challenges”,
(Invited Tutorial), Proceedings of the IEEE, Volume 102, Issue 9, Pages 1317 – 1337, Sept. 2014
IEEE Xplore Highlight
“The cover page of this issue of PIEEE highlights the
tutorial paper on flexible optical networking which
provides a comprehensive look at the different pieces that
compose the flexible optical networking puzzle”
[Article related with FOX-C and INSPACE EU projects]

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Recent research focus (relevant trends to be discussed:
Datacenter interconnection networks
 Highly-cited articles:
• A Survey on Optical Interconnects for Data Centers, IEEE
Survey and Tutorials, 2012 (by C. Kachris and I. Tomkos)
• Optical interconnection networks in data centers: recent
trends and future challenges, IEEE Communications
Magazine, 2014 (by C. Kachris, K. Kanonakis and I. Tomkos)
 Highly-cited book
• “Optical Interconnects for
Future Data Center Networks“,
Springer, 2013
(by C. Kachris, K. Bergman and I. Tomkos)
 Initiator of the
subcommittee on
“Optics for Datacoms
and Computercoms”
(2011)
 Co-founder of the
“Optical Data Centre
Interconnect – ODCI”)
conference (2015)

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The “Roadmap of Optical Communications” pointing to
“New Frontiers” (It is a collective effort!)
 Lightwave communications is a necessity
for the information age
 Optical fiber is the only medium that
can meet the modern society's needs for
transporting massive amounts of data
over long distances.
 Supported in some applications by
Free Space Optics
 Optical communications is a diverse and
rapidly changing field, where experts in
photonics, communications, electronics,
and signal processing need to work side by
side to meet the ever-increasing demands for
higher capacity, lower cost, and lower energy
consumption.

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 Main Drivers for the Evolution of Optical Communications towards the next
generation and recent trends
 Two main research topics on core networks over the past 8 years for
backbone optical networks
• Spectrally flexible optical networks (aka “Elastic Optical Networks – EON”)
• Spatially flexible optical networking (aka “Space Division Multiplexed Optical
Networks” – SDM)
 In fact, these two topics are not orthogonal, as many people treat them, but
can be considered together as complementary approaches to enable the best
future optical networking solutions, based on the concept of
• Spatially-Spectrally flexible optical networks (aka “SS-FON)
 What are the envisioned limitations?
 Which are the most probable use cases?
 Summary & Conclusions
Talk Outline

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Global Traffic Growth
 Internet traffic (particularly from video, cloud
services and mobile users) is increasing at
significant CAGR
[Ref] Cisco Global Cloud Index, 2015-2020
Datacenter growth
#ofhyper-scaledatacenters
Global data center IP traffic growth
Zettabyteperyear
 This Internet traffic growth increasingly
impacts mostly intra-DC traffic
% share of DC servers
(installed base)
Future applications (e.g. Tactile Internet, 5th
generation mobile services, Internet of
Things, Big Data) will push further the
demands for better network infrastructures

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Strong optical equipment gear growth driven by
100G coherent technology in core/metro networks
 100G Coherent Technology is experiencing very strong growth!
 The same growth is expected in the next years for 200/400G

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Traffic evolution and consequences on Optical Systems
 Traffic increases at a rate of 20-40% per year, while capacity of
deployed SMF-based networks approaches fundamental limits…
• What can be done?
 As a result, we can estimate the requirements of optical systems
in terms of interface-speeds and WDM system -capacity:
Traffic growth 20% 40%
Interface rates
1 Tb/s 2023 2017
10 Tb/s 2035 2024
WDM system
capacity
50 Tb/s 2019 2015
500 Tb/s 2031 2022
P. Winzer, Bell Labs Technical Journal vol. 19, 2014

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A turning point in history…
 A paradigm shift is occurring as we speak during which from
Hyperscale DC operators are taking the lead in technology
developments from traditional Telecom Operators

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Expected sales per supported system interface rate
A big business opportunity awaits those who focus now on +100Gbps systems
and will be ready with a tested product by late 2018-early 2019

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Traffic is growing faster than technology capabilities
(defined by Moore’s Law) since several years now!
 The performance of electronics (in terms of speed/bandwidth and power consumption)
cannot follow the growth of the data => a new paradigm is required!
Photonics to the rescue!!!

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The main limitation in the scaling of electronic ICs:
Power Consumption…
 We observe that
transistors counts
(1971-2015) are
keep growing
exponentially,
following Moore’s
law
 However
performance
growth is limited in
recent years,
mainly by power
consumption issues.

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The slow down of Moore’s law is the main limiting
factor in the sustainability of our Society…
 Cloud Computing/Internet power consumption is
expected to reach over 1000 Billion KWh in 2020!
2007
(Billion KWh)
2020
(Billion KWh)
Data Centers 330 1012
Telecoms 293 951
Total Cloud 623 1963
[Source: How Clean is Your Data Center, Greenpeace, 2012]

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Power consumption is (and will be) the
performance parameter that we need to focus on
Table 1: CMOS power dissipation
 When we pass below the 15nm-based fabrication process, transistor features are
approaching the size of tens of atoms.
 As the technology will evolve towards even smaller feature sizes, the future CMOS
electronics technology will no longer be able to take advantage of Moore’s law in terms
of power performance, as it used to.

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What was (and still is…) the wrong approach
followed by photonics experts so far?
 Photonics always promise to reduce the power consumption and cost, BUT…
 For signal processing, we need to consider new approaches that are inspired
by the unique properties of light and are implemented via photonic devices
• Providing significant benefits, in terms of ultra-high speed, small footprint and
ultra-low power consumption, for signal processing and transmission systems.
 However, it has been quite unfortunate that for a couple of decades now, the
vast majority of Photonic scientists focused on photonic implementations that
basically try to replicate the configuration of electronic
processing/switching/computing systems and hence do not optimally utilize
the capabilities of photonics to their fullest extend
• In such low-innovation conventional approaches, the scientists seek to use non-
linear elements to implement decisions within optical logic circuits/gates.
 Keep in mind: The design of optical signal processing circuits does not
necessarily have to mimic the design of the electronic signal processing
circuits!  Think out of the box!

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State of the Art options for scaling the capacity
of optical communication systems
Parallel Fibers (PSM)
A form of
Space Division Multiplexing (SDM)
• Cost & Power, normalized per Gb/s
do not drop as the # of fibers goes up
• Need fiber plant upgrade in each gen using
multi-core or multi-mode fibers
Wavelength Division Multiplexing (WDM)
 Cost & Power, normalized per Gb/s
do not drop as the # of ls goes up

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Today’s solution for single carrier 100Gbps coherent
transceiver used in metro/core networks
 SLR/MLR coherent transceiver:
DSPchip
Datain/out
/2
Q I
/2
DP IQ Mod
Q I
DAC
DAC
DAC
DAC
ADC
ADC
ADC
ADC
ECL
LO
Drivers
RF LP filters
RF LP filters (optional)
PBS
PBS
Sx
Sy
LOy
LOx
Ix
Qx
Iy
Qy
Balanced
photodetector
DFB
Intensity
modulatorsplitter
50/50
211
-1PRBS
(3.5or7)
Gb/s
BPG
4:1
MUX
QPSK↔16QAM
to
Balanced
photodetector
DFB
Intensity
modulatorsplitter
50/50
211
-1PRBS
(3.5or7)
Gb/s
BPG
4:1
MUX
QPSK↔16QAM
to
Balanced
photodetector
DFB
Intensity
modulatorsplitter
50/50
211
-1PRBS
(3.5or7)
Gb/s
BPG
4:1
MUX
QPSK↔16QAM
to
Balanced
photodetector
DFB
Intensity
modulatorsplitter
50/50
211
-1PRBS
(3.5or7)
Gb/s
BPG
4:1
MUX
QPSK↔16QAM
to
90º Hybrid
TIA
DP coherent receiver

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Conventional WDM networks:
From SLR to MLR to ???
 Single-Line Rate (SLR) networks
• Conventional WDM networks that operate today using a fixed bit-rate and
modulation format for all fixed-grid channels
 They are becoming more dynamic, more physical layer aware, more intelligent
 But they are also low spectral efficiency systems…
 Mixed-Line Rate (MLR) networks
• Allow for multi-rate channels to run in the same system, while still capitalizing on
the legacy infrastructure
• Utilize the conventional fixed spectrum grid and are rate-specific
10G40G10G 10G100G 40G
Fixed Channel
Spacing
Bandwidth-
Fixed Optical
Node
Bandwidth-
Fixed Optical
Node
Mixed
Line-Rate/
Modulation Format
f

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• Assuming an annual traffic increase of 35% on the network under study (France
Telecom’s), it is not possible to serve all demands (in C-band) after 2020
• Cost calculated with today’s technologies & for FT national network
Network performance of today’s solutions (SLR)
Single Line Rate (SLR) WDM networks
(100G using DP-QPSK over 50GHz ITU-T grid)
2020 2020
Results obtained for France Telecom Network

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Flexible/elastic optical networks
The definition:
 Flexible (Elastic) Optical Network = A network able to adapt its resources (link capacity,
transmission bandwidth per node, switching capacity etc.) according to the connectivity (i.e.
traffic) demands in an automated fashion
• Flexible, elastic, tunable, gridless, or adaptive are a few examples of the terms used by
the research community to describe such solutions
 The target
• Offer optimization of the poorly-filled wavelengths of the fixed spectrum grid via a
flexible spectrum allocation that requires a new flexible wavelength-grid, enabling
adaptive sub-wavelength and super-wavelength services
400G40G10G 400G100G 40G
Flexible
Spectrum
Spectrum-
Flexible Optical
Node
Spectrum-
Flexible Optical
Node
Adaptive
Line-Rate/
Modulation Format
f
Bandwidth-Flexible
WSS
Bandwidth-Flexible
WSS
Bandwidth-Flexible
WSS
Bandwidth-Flexible
WSS

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How spectral super-channels can adapt to
changes of the traffic demands to support
elastic bandwidth?
 The bit-rate per “flex-channel” can be
tuned while the occupied spectrum of
the “super-channel” remains constant
 The bit-rate of the “super-channel”
can be tuned by changing the number of
“sub-channels” while the bit-rate per
each “sub-channel” remains constant
 Both the bit-rate of each “sub-
channel” and the number of “sub-
channels” per “super-channel” can vary
Super-channels
when combined
with flex-grid
offer spectrum
savings
Spectral super-channels can enable the path to higher
bit-rates while maintaining high spectral efficiency
Wasted bandwidth
(reduced spectral efficiency)

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• Through superior flexibility and scalability in spectrum allocation, MLR
network outperforms the SLR scenario in the whole range of study
• Cost calculated with today’s technologies & for FT national network
Network performance of today’s solutions (SLR & MLR)
Flexi-grid Multi Line Rate (MLR) networks
(enabled by changing the modulation format: DP-BPSK, DP-QPSK, DP-8QAM, DP-16QAM)
2022
ProjectionResults obtained for France Telecom Network

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Technology Roadmap for transceiver technology
SLR 10G
SLR 40G
SLR 100G
SLR 200G
MLR 10G/40G/100G
WDM Sp-Ch
Fine-grid Sp-Ch
400G
2000 2005 2010 2015 2020 2025
TechnologicalComplexity
Year
Fine-grid
Sp-Ch 1T
Source: Finisar

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Silicon Photonics: the new Opportunity to reduce costs and
power consumption (before Graphene  and after InP…)
Silicon Photonics: Repurpose the silicon
microelectronics ecosystem to build silicon chips that
can manipulate light as well as electrical signals
• Eco-system in place (generic CMOS foundaries) for SiPho
chip design and mass fabrication

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DIMENSION H2020 EU Project
Directly Modulated Lasers on Silicon

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Mid-term options to cope with capacity crunch
 Deployment of parallel systems over already
deployed fibers that belong to the same fiber cable
like already utilized fibers
 Extending operation/amplification bands to S and L
bands (multi band systems: C+L or S+C+L) or even
beyond (i.e. the fiber low-loss BW is 300nm!!!)
 We performed comparison of multi-band and multi-
fiber systems as mid-term migrations scenarios In
terms of:
 Networking-level performance (spectrum utilization)
 Infrastructure cost

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 Researchers have been trying to increase the spectrum utilization
beyond the C-band since the 90s using new doped amplifiers and
Raman-based amplification:
Extending the operating/amplification
wavelength band beyond 100nm
Raman+
amplifier
Raman amplifier
Raman and Hybrid
EDFA/Raman amplifier

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• The multi-band scenario spanning the S+C+L bands is capable to accommodate 8% and 14%
more traffic to the network (for 60% and 100% reach increase, respectively) compared to
the C-band EDFA-based parallel system with three fibers.
• The increase in the Capacity × Reach for Raman systems is not much compared to the C-band EDFA
systems due to the fact that Telefónica’s core network is a rather small network.
Simulation results
8%
14%
[ref] B. Shariati et al, “Investigation of mid-term network
migration scenarios comparing multi-band and multi-fiber
deployments, ” OFC 2016.

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What is the ultimate solution in capacity expansion
(beyond WDM and high-baud rates)?  SDM
 SDM: add parallel systems (hopefully cost-effectively)
• Of course by simply increasing the number of systems in parallel, the cost and power
consumption also increase linearly!
 SDM is anticipated to be the key solution to address the looming “capacity crunch” in long-
term, while promising to reduce further the cost-per-bit transmitted.
• The cost-per-bit reduction is expected to be realized only if we introduce some levels
of component sharing and integration; i.e. spatial integration of network elements
(transceivers, amplifiers, switches)
TRx TRx
Amp
TRx TRx
Amp
TRx TRx
Amp
TRx TRx
Amp
Integrated
TRx
Integrated
Amp
Integrated
TRx
Integrated fiber
[ref] J. M. Rivas-Moscoso, B. Shariati, A. Mastropaolo, D. Klonidis, I. Tomkos, “Cost benefit quantification of SDM
network implementations based on spatially integrated network elements,” ECOC 2016.

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1. “Uncoupled/Weakly-coupled” spatial modes
2. “Strongly-coupled” spatial modes
3. “Coupled spatial sub-groups” of modes
Bundles of Single-mode fibers (SMFs) Uncoupled multi-core fibers (MCFs)
Strongly-coupled MCF Few-mode fibers (FMFs)
Uncoupled groups of coupled-cores Few-mode multi-core fibers (FM_MCFs)
“Integrated fibers” for SDM-based optical networks

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Important questions under examination - I
 How SDM can possibly bring down the cost?
• Spatial integration of network elements (e.g.
development of new types of transceivers and most
importantly switching nodes/ROADMs)

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The INSPACE H2020 EU project consortium
 INSPACE tries to develop the transceiver and (primarily)
switching solutions for affordable SDM

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Integrated spatial super-channel transceivers
LINE OUT
LINE IN
LO
LaserSplitters
Case of bundles
of SMF
[ref] J. M. Rivas-Moscoso, B. Shariati, A. Mastropaolo, D. Klonidis, I. Tomkos,
“Cost benefit quantification of SDM network implementations based on
spatially integrated network elements,” ECOC 2016.

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LINE OUT
LINE IN
LO
Laser
MCF breakout
MCF breakout
Splitters
Case of MCF

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LINE OUT
LINE IN
LO
Laser
FMF photonic lantern
FMF photonic lantern
Separate DSP per sub-channel or can some
modules be shared?
FMF photonic
lantern ()
[Ref] M. D. Feuer et al, “Joint digital signal processing
receivers for spatial superchannels”, IEEE PTL, 24(21), 2012.For instance, frequency and phase estimation modules can be shared
resulting in reduced complexity, power consumption, and cost.
Case of FMF
The spatial super-channel TRx,
since all sub-channels are
transmitted at the same
frequency, do not require
frequency combs or AWGs, and
can bring the cost down by 5-
20% for integrated spatial Sp-
Ch TRx with 2-10 Sb-Chs vs.
spectral Sp-Ch TRx.

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SDM Switching Strategies
 Independent switching (Ind-Sw)
• All spectral slices and spatial modes/cores can be independently directed to
any output port
 Joint switching (J-Sw)
• All spatial modes/cores are treated as a single entity, while spectral slices
can be freely switched by the WSS
 Fractional-joint switching (FrJ-Sw)
• A kind of hybrid approach in which a number of subgroups of G spatial
modes/cores, as well as all spectral slices, can be independently switched to
all output ports
spatial group-switching
[Ref] D. Marom et al, IEEE. Commun. Mag., 53(2), Feb 2015.

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Example of ROADM architecture (degree=3): trade-
offs for different switching schemes
Ind-Sw FrJ-Sw (G=2)J-Sw
Assuming 4 spatial dimensions (only 1 degree is shown below)
Eight 1×3 WSSs Two 4×12 WSSs Four 2×6 WSSs
Requires large number of WSS
with small port counts
Highest level of flexibility 2 WSS/degree, but very
high port count
Intermediate flexibility
Sacrifices flexibility for
architecture simplicity
Intermediate number of WSS
Low port count
D2
D3
D2
D3
D2
D3
D2
D3
D2
D3
D2
D3

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SDM technology elements
 INSPACE SDM Wavelength Selective Switches for (Fr)J-Sw
• High port count WSS for joint switching of spatial modes
A conventional 120 WSS can turn into a 7-mode(12) spatial-spectral WSS
(First demonstration in OFC 2012)
New port definition: S(MN)
S = nº of spatial modes
In1
Out1
Out2 M = nº of input fibre subgroups
N = nº of output fibre subgroups

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CD(C) ROADM architectures for SDM networks
 SDM ROADMs cost can be reduced by exploiting joint switching scheme.
• A cost analysis was performed considering alternative designs for A/D units.
The focus in on the optimization of A/D modules.
[ref] J. M. Rivas-Moscoso, B. Shariati, D. M. Marom, D. Klonidis, I. Tomkos, “Comparison of CD(C) ROADM architectures for space division multiplexed networks,” OFC 2017.

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Total Relative Cost of various SDM ROADM realizations
The most cost-effective architecture is the one which:
i) maximizes the number of available A/D ports, and
ii) does not heavily increase the port count of pass-through WSSs.
J-Sw based ROADMs
are more cost effective than those exploiting Ind-Sw and FrJ-Sw
0
100
200
300
400
500
TotalRelativeCostwrt19WSSs
Number of Spatial Superchannel Transceivers with 6 Spatial Channels
(C1) Ind-Sw (C1) FrJ-Sw (G=3) (C1) J-Sw
C1 C2 C3 C4 C5 C6 C7 C1 C2 C3 C4 C5 C6 C7 C1 C2 C3 C4 C5 C6 C7
20 40 60
[ref] J. M. Rivas-Moscoso, B. Shariati, D. M. Marom, D. Klonidis, I. Tomkos, “Comparison of CD(C) ROADM architectures for space division multiplexed networks,” OFC 2017.
How does joint switching scheme perform compared
to the benchmark (i.e. independent switching)?

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Important questions under examination - II
 What are the consequences of crosstalk
among parallel cores/modes in SDM systems?
• Reach reduction  How much?
 A reach estimation tool is required for SDM
networks utilizing MCF/FMF fibers

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• Extra impairments introduced by SDM fibers need to be compensated, otherwise their
impact on the quality of transmission should be considered while planning the network.
• Linear impairments are expected to be perfectly compensated, however, nonlinear
impairments are unlikely to be compensated with the current DSP modules and, therefore,
result in performance degradation.
• Pch is the power of the launched optical signal
• NS is the number of spans
• Bref = 12.5 GHz is the reference bandwidth
• GASE is the power spectral density (PSD) of amplified spontaneous emissions (ASE) noise
Quality of transmission estimator for SDM networks
refd
d
BGG )(N
P
OSNR
NLI,ASEs
ch


SDM Approaches BuSMFs Weakly-coupled MCF FMF
Intra-modal impairments CD, SPM, XPM, FWM CD, SPM, XPM, FWM CD, SPM, XPM, FWM
Inter-modal
impairments
No Inter-fiber Crosstalk Minor Inter-core Crosstalk DGD, MDL, Mode Coupling,
Inter-Modal Nonlinearity
drefd
d
BGG XT,NLI,ASEs
ch
P)(N
P
OSNR


• GNLI,d is the PSD of the intra-core nonlinear
interference noise calculated
• PXT,d is the inter-core XT in core d
• GNLI,d is the PSD of the nonlinear interference
noise in mode d arising from both inter-modal
and intra-modal contributions.
MCFs
FMFs, BuSMFs

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• A set of simulations has been performed to obtain the maximum transparent
optical reach that can be achieved with: a) bundles of 6 SMFs, b) a 6-mode FMF,
and c) a 7-core MCF.
• In our analysis we considered four different modulation formats (PM-BPSK,
PM-QPSK, PM-8QAM, PM-16QAM).
• The symbol rate is fixed to 32 GBaud.
• A multi-span system with each span composed of 100 km of FMF, followed
by an EDFA with noise figure of 5 dB completely recovering the span loss.
• The reference BER is set to 10-3.
Optical reach in terms of launch power
[ref] B. Shariati, A. Mastropaolo, N. P. Diamantopoulos, J. M. Rivas-Moscoso, F. Pederzolli, D. Siracusa, D. Klonidis, I. Tomkos, “Spectrally-spatially flexible optical networking,” ACP 2016.

46
Important questions under examination - III
 Which are the bottlenecks for SDM
deployment?
• Increasing the MIMO-DSP complexity and the power
consumption (in order to handle the effects of crosstalk
 Making SDM less favorable for long-haul applications…

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MIMO DSP complexity and power consumption
 Spatial XT introduced by coupled SDM fibers (e.g. FMFs) is
expected to be mitigated by MIMO DSP, with a complexity for
real-time implementation determined by the number of spatial
channels and their corresponding delay spread
 Even though MIMO-DSP can ideally compensate all the linear
impairments in SDM systems, the power consumption of the
MIMO-DSP and of the overall SDM-TRx can be the limited factor
in the maximum capacity and achievable reach of SDM
networks
 An estimation for the power consumption of real-time MIMO-
DSP considering the current CMOS technology was calculated
based on the computation complexity of frequency-domain
equalizers (FDEs).

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MIMO DSP complexity and power consumption
is a huge burden for long-haul applications
 The power consumption of the MIMO-DSP is THE limited
factor in the maximum capacity and achievable reach of SDM
[ref] N-P. Diamantopoulos, B. Shariati, I. Tomkos, “On the power consumption of MIMO processing and its impact on the performance of SDM networks,” OFC 2017.

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Power consumption for SMFs, 3-mode, and 6-mode
FMFs
 The resulting power consumptions (per mode and per 600Gbps System) for 15
nm CMOS, based on the computational complexities illustrated previously
Power consumption per mode Total power consumption per 600 Gb/s
100 W 200 W
300 W
(50 W/mode)
600 W
(100 W/mode)
SMF 2104 km 2609 km 2780 km 2950 km
2-LP FMF 1699 km 2152 km 2306 km 2459 km
4-LP FMF 666 km 1050 km 1180 km 1309 km
Power-limited reach based on total consumption per 600 Gb/s module
[ref] D.C. Kilper et al., IEEE J. Sel. Topics Quantum Electron. 17(2), 275-284 (2011).
[ref] N-P. Diamantopoulos, B. Shariati, I. Tomkos, “On the
power consumption of MIMO processing and its impact on
the performance of SDM networks,” OFC 2017.

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Important questions under examination - IV
 What are the early use-cases for SDM?
• Datacenter interconnection
Any fiber can be used, as new deployments are not an issue for
new DCs.
MIMO complexity is not an issue. MIMO-less transceivers with
special fibers can be utilized (elliptical-core FMFs)
• Front-hauling of 5G network
Bundles of available SMFs can be used.
Due to short distances, weakly-coupled MCFs can be deployed as
new fiber installation is needed anyway

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Challenges of current data center networks
and where SDM can bring benefits
Current MMF/SMF based solutions (e.g. fat-tree or butterfly architectures) suffer from:
• oversubscription of higher layers interconnects in multitier topologies
• high power consumption and heat dissipation of many electronic switching ports for different tiers
• no direct rack-to-rack links, thus requiring intermediate switching ports which increases latency
and power consumption
• the lack of dynamic re-configurability
• link capacity scaling, as it mainly requires by installing new fibers
• cabling complexity is another major challenge when trying to scale DCs, as it creates issues, like:
 great difficulties in maintenance operation,
 complicated system upgrade during fiber failures, and
 major influence on throughput, scalability and energy efficiency management of DCs.
novel interconnect technologies, direct rack-to-rack connectivity
introducing optical bypass, exploiting solutions with lighter electronic processing
novel interconnect technologies (free space optics), novel interconnection networks
introducing optical bypass, novel interconnection networks
integrated SDM fibers, novel interconnect technologies, novel interconnection networks
integrated SDM fibers, free space optics, novel interconnection networks

52
Front-hauling of 5G networks utilizing SDM solutions
 C-RAN poses a heavy burden on the front-haul network
connecting BBUs and RRUs, while CPRI cannot meet this
capacity scaling requirement in a cost-effective way.
• SDM-based could radio access networks is a potential candidate to address
several issues in the front-hauling of 5G networks.
Dynamic
mapping of
downstream
sub-carrier
channels &
bands to
spatial
ouputs
Dynamic
mapping of
upstream
sub-carrier
channels &
bands to
spatial
ouputs
1,1
R F
f
1, 2
R F
f
11, S
R F
f
,1M
R F
f
, 2M
R F
f
,M S
M
R F
f
2 ,1
R F
f
2 , 2
R F
f
22 , S
R F
f
1,1
R F
f
1, 2
R F
f
11, S
R F
f
,1M
R F
f
, 2M
R F
f
,M S
M
R F
f
2 ,1
R F
f
2 , 2
R F
f
22 , S
R F
f
2N+1 MCF
(BS K, sector 3)
N cores downstream
N cores upstream
NxN MIMO
BS1
BS2
BS3
 ,3
1
,
K
D
s l
 ,3
2
,
K
D
s l
 ,3
,
K
N D
s l
 ,3
1
,
K
U
s l
 ,3
2
,
K
U
s l
 ,3
,
K
N U
s l
Small cell
environment
Individual Cell
configuration
with selective
DCA
1
1
1
2
2
23
3
3
Opticalmodulation&detection
Resource allocation table exam
BS SECTOR
OUTPUT
PORTS
fRF
1,1
fRF
1,2
fRF
1,S1 fRF
2,1
fRF
2,2
fRF
2,S2 fRF
M,1
f
1 1 s1
1,1
1 1 s2
1,1
1 1 sN
1,1
1 2 s1
1,2
1 2 s2
1,2
1 2 sN
1,2
1 3 s1
1,3
1 3 s2
1,3
1 3 sN
1,3
2 1 s1
2,1
2 1 s2
2,1
2 1 sN
2,1
2 2 s1
2,2
2 2 s2
2,2
2 2 sN
2,2
2 3 s1
2,3
2 3 s2
2,3
2 3 sN
2,3
3 1 s1
3,1
3 1 s2
3,1
3 1 sN
3,1
3 2 s1
3,2
3 2 s1
3,2
3 2 sN
3,2
3 3 s1
3,3
3 3 s2
3,3
3 3 sN
3,3
Capa
expansi
carr
aggreg
Capacity
expansion
by MIMO
J. M. Galve, I. Gasulla, S. Sales, J. Capmany, “Reconfigurable
radio access networks using multicore fibers,” J. of Quantum
Electronics, Jan 2016.

53
5G PPP Phase II Project BlueSpace
 Name: “Building on the use of Spatial Multiplexing 5G
Network Infrastructures and Showcasing Advanced
Technology and Networking Capabilities”
 Topic: ICT-07-2017 – 5G PPP
 Duration: June 2017 – May 2020
 Budget: 6.655.127€ (about 1.5ME in Greece)
 Effort: 755 PMs
 Partners:

54
Summary of this ICTON talk
 Why we need higher flexibility & capacity in future
networks
 Which new optical networking solutions must be
introduced in every tier/network segment to keep-up
with the pace of these new developments?
• The Elastic Optical Networking (EON) paradigm has been one of the first
proposed solutions to cope with the forecasted traffic increase and
variability by intelligently managing the resources.
• To cope with the looming capacity crunch, Space Division Multiplexed (SDM)
based optical networking has been proposed as the ultimate solution, relying
to a certain extent on the re-build of the infrastructure (i.e. new fibers,
transceivers, switches, and amplifiers).
Different flavors of SDM will be required for the different segments of
the Internet backbone, including the newly emerged Spectrally-Spatially
Flexible Optical Network (SS- FON).

55
Key references
 D. Klonidis, F. Cugini, O. Gerstel, M. Jinno, V. Lopez, E. Palkopoulou, M. Sekiya, D. Siracusa, G. Thouénon, and C. Betoule, “Spectrally and
spatially flexible optical network planning and operations,” IEEE Commun. Mag., Feb 2015.
 M. Song, E. Pincemin, A. Josten, B. Baeuerle, D. Hillerkuss, J. Leuthold, R. Rudnick, D. Marom, S. Ben-Ezra, J. Ferran, G. Thouenon, P.
Khodashenas, J. Rivas-Moscoso, C. Betoule, D. Klonidis, I. Tomkos, "Flexible optical cross-connects for high bit rate elastic photonic transport
networks," JOCN, Jul 2016.
 D. Marom, P. Colbourne, A. D’Errico, N. Fontaine, Y. Ikuma, R. Proietti, L. Zong, J. M. Rivas-Moscoso, I. Tomkos, “Survey of photonic
switching architectures and technologies in support of spatially and spectrally flexible optical networking,” (Invited) JOCN, Jan 2017.
 B. Shariati, A. Mastropaolo, N. P. Diamantopoulos, J. M. Rivas-Moscoso, F. Pederzolli, D. Siracusa, D. Klonidis, I. Tomkos, “Spectrally-spatially
flexible optical networking,” (Invited) ACP 2016.
 B. Shariati, D. Klonidis, D. Siracusa, F. Pederzolli, J. M. Rivas-Moscoso, L. Velasco, I. Tomkos, “Impact of traffic profile on the performance of
spatial superchannel switching in SDM networks,” ECOC 2016.
 B. Shariati, J. M. Rivas-Moscoso, D. M. Marom, S. Ben-Ezra, D. Klonidis, L. Velasco, I. Tomkos, “Impact of spatial and spectral granularity on
the performance of SDM networks based on spatial superchannel switching,” JLT, July 2017.
 P. S. Khodashenas, J. M. Rivas-Moscoso, D. Siracusa, F. Pederzolli, B. Shariati, D. Klonidis, E. Salvadori, and I. Tomkos, “Comparison of spectral
and spatial super-channel allocation schemes for SDM networks,” JLT, June 2016.
 B. Shariati, P. S. Khodashenas, J. M. Rivas-Moscoso, S. Ben-Ezra, D. Klonidis, F. Jimenez, L. Velasco, I. Tomkos, “Investigation of mid-term
network migration scenarios comparing multi-band and multi-fiber deployments,” OFC 2016.
 N. P. Diamantopoulos, B. Shariati, I. Tomkos, “On the power consumption of MIMO processing and its impact on the performance of SDM
networks,” OFC 2017.
 J. M. Rivas-Moscoso, B. Shariati, a. Mastropaolo, D. Klonidis, I. Tomkos, “Cost benefit quantification of SDM network implementations based
on spatially integrated network elements,” ECOC 2016.
 J. M. Rivas-Moscoso, B. Shariati, D. M. Marom, D. Klonidis, I. Tomkos, “Comparison of CD(C) ROADM architectures for space division
multiplexed networks,” OFC 2017.
 P. S. Khodashenas, J. M. Rivas-Moscoso, B. Shariati, D. Marom, D. Klonidis, I. Tomkos, “Investigation of spectrum granularity for performance
optimization of flexible Nyquist-WDM-based optical networks,” JLT, Dec 2015.
 B. Shariati, N. P. Diamantopoulos, D. Klonidis, J. Comellas, I. Tomkos, “On the benefits of FMF based data center interconnection utilizing
MIMO-less PAM-M transceivers,” (Invited) ICTON 2017.

56
Thank you for your
attention!
Dr. Ioannis Tomkos
email:
itom@ait.gr
Linkedin:
https://www.linkedin.com/in/dr-ioannis-tomkos-086b102/

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