6G: Towards a Fully Digital and Connected World - 6G Wireless Summit
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6G: Towards a Fully Digital and Connected World
Marco Giordani◦, Michele Polese◦, Marco Mezzavilla†, Sundeep Rangan†, Michele Zorzi◦
◦University of Padova, Department of Information Engineering, Italy
† NYU WIRELESS, Tandon School of Engineering, New York University, Brooklyn, NY, USA
6G Wireless Summit, Levi, Finland
March 26th, 2019
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Outline
Ø Introduction and Motivations
Ø 6G Key Performance Indices (KPIs)
Ø 6G Potential Applications
Ø 6G Enabling Technologies
• Disruptive Communication Technologies
• Novel 6G Communication Enabler
• Innovative Network Architectures
• Integrating Intelligence in the Network
Ø Conclusions and Research Directions
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Introduction and Motivations
• From 1G to 5G, passing through UMTS and LTE innovations, each generation of mobile
technology has tried to meet the needs of network operators and final consumers
• The rapid development of data-centric and automated processes may exceed even the
capabilities of emerging 5G systems, thereby calling for a new wireless generation
innovation
6G
1-10 Gbps
5G
100-1000 Mbps
2 Mbps
4G
64 Kbps
2.4 Kbps 3G
1G 2G
Internet of Massive broadband
Voice calling SMS Internet Applications Internet of Things Towards a Fully Digital and Connected World
1980 1990 2000 2010 2020 2025-2030 time
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Introduction and Motivations
5G is always associated with trade-offs: 6G will contribute to fill the gap between beyond-2020
societal and business demands and what 5G (and its predecessors) can support
• Consider potential applications for future connected systems and estimate the key
requirements in terms of throughput, latency, connectivity and other factors.
• Identify use cases beyond the performance of 5G systems under development today.
• Survey emerging technologies that are not available in networks today but have significant
promise for future 6G systems (including developments at all layers of the protocol stack)
New Spectrum Disaggregation/ virtualization
Disruptive Technologies Energy Efficiency
Cell-less Networks Artificial Intelligence
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6G Wireless Summit, 26th March 2019
6G: Towards a Fully Digital and Connected World
6G Applications and Use Cases
6G Wireless Summit, Levi, Finland
March 26th, 2019
6G: Towards a Fully Digital and Connected World 5
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6G Use Cases
Massive Scale
Communication Virtual Reality E-Health
High-Speed Mobility
Industry 4.0
Tactile Internet
Smart Cities
Holographic Telepresence Autonomous Driving
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6G Applications and Use Cases
INDOOR COVERAGE
• 80% of the mobile traffic is generated indoor
• 5G current cellular networks never really targeted indoor coverage
Ø High-frequencies cannot penetrate solid material
Ø 5G densification through femtocells (proposed as a solution) presents scalability
issues and high deployment and management costs for operators
6G
6G should target cost-aware indoor connectivity
solutions autonomously deployed by end-users
and managed by the network operators
(e.g., wireless relays coupled with
indoor communications)
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6G Applications and Use Cases
MASSIVE SCALE COMMUNICATIONS
• 5G networks are designed to support more than 1’000’000 connections per km2
• Mobile traffic will grow 3-fold from 2016 to 2021, pushing the number of connected devices to
the extreme (> 500 billion connected things worldwide by 2030)
• This will stress already congested networks, which will not guarantee the required QoS
6G
6G targets capacity expansion to offer high
throughput and continuous connectivity,
even when civil communication
infrastructures may be compromised
(public safety is main requirement)
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6G Applications and Use Cases
eHEALTH
• OBJECTIVE: revolutionize the health-care sector, e.g., eliminating time and space barriers
through remote surgery and guaranteeing health-care workflow optimizations.
• Current communication technologies cannot be applied in future health-care
Ø high cost and lack of real-time tactile feedback
Ø mmWaves can support low-latency, but do not guarantee connection continuity.
6G
6G enhancements will unleash the potential
of eHealth applications through innovations
like mobile edge computing, virtualization
and artificial intelligence
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6G Applications and Use Cases
INDUSTRY 4.0 and ROBOTICS
• OBJECTIVE: digital transformation of manufacturing through Cyber Physical Systems (CPS)
and Internet of Things (IoT) services.
• Enabling, among other things, Internet-based diagnostics, maintenance, operation, and direct
Machine to Machine (M2M) communications in a cost-effective, flexible and efficient way.
• CPS will break the boundaries between the physical factory and the cyber space computation.
6G
6G will foster the Industry 4.0 revolution
through new semiconductor and IC
innovations (e.g., terahertz scale
electronic packaging solutions)
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6G Applications and Use Cases
SMART CITY
• OBJECTIVE: life quality improvements, environmental monitoring, traffic control and city
management automation
• Current cellular systems have been mainly developed for broadband applications
• Smart city applications build upon data generated by low-cost and low-energy consuming
sensors, which efficiently interact with each other.
6G
6G will seamlessly include support for user-
centric M2M communication, promoting
ultra-long battery lifetime combined
with energy harvesting approaches
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6G Applications and Use Cases
HOLOGRAPHIC TELEPRESENCE
• OBJECTIVE: remotely connect with an increasing amount of digital accuracy
• ISSUE: raw hologram, without any optimization nor compression, with colors, full parallax,
and 30 fps, would require a daunting 4.32 Tbps data rate.
• ISSUE: latency requirement will hit the sub-millisecond, and thousands of synchronized view
angles will be necessary (2 tiles for 4K/8K HD, and 12 tiles for VR/AR)
6G
6G will develop architectures and network
designs able to digitalize and transfer all the
5 human senses, increasing the
overall target data rate
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6G Applications and Use Cases
UNMANNED MOBILITY (Autonomous Driving)
• OBJECTIVE: fully autonomous connected and intelligent transportation systems, offering safer
traveling, improved traffic management, and support for infotainment applications (>7000B$)
• Unprecedented levels of communication reliability and low end-to-end latency, even in
ultra-high mobility scenarios (up to an impressive 1000 km/h).
• Sensors (more than 200 per vehicle by 2020) will demand increasing data rates (in the order
of terabytes per driving hour), saturating the capacity of traditional technologies.
6G
6G will pave the way for the coming era of
connected vehicles through hardware and
software advancements and new
technologies to eliminate typical 5G
latency/reliability/throughput trade offs
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6G Wireless Summit, 26th March 20196G: Towards a Fully Digital and Connected World
6G Technologies and Innovations
6G Wireless Summit, Levi, Finland
March 26th, 2019
6G: Towards a Fully Digital and Connected World 14
6G Wireless Summit, 26th March 20194
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creasing energy and
Increasing energy and
bandwidth
6G Technologies and Innovations
bandwidth
ncreasing wavelength Disruptive Communication Technologies – Terahertz
Increasing wavelength
TeraHertz Visible Light
• Frequency bands between 100 GHz and 1 THz
TeraHertz à bring
Visible Light to the extreme the potentials and
430 THz 770 THz
challenges of high-frequency communications.
300 GHz 10 THz
430 THz 770 THz
GHz 300 GHz 10 THz
• Huge data rates (possible to allocate contiguous chunks of up to 200 GHz of spectrum)
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6G Technologies and Innovations
Disruptive Communication Technologies – Visible Light Communications
• Frequency bands between 430 GHz and 770 THz à complement RF communications by
Visible
piggybacking
Visibleon Lightwide adoption of LED luminaries
the
Light
430430
THzTHz 770 770
THzTHz
• VLC devices can switch between different light intensities to modulate a signal
• More mature research than THz (standard for VLC – IEEE 802.15.7 – has been defined)
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complemented by RF for the uplink
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6G: Towards a Fully Digital and Connected World
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6G Wireless Summit, 26th March 2019•
•
•
•
FOR SUBMISSION TO IEEE 30
[40] R. J. Weiler, M. Peter, T. Khne, M. Wisotzki, and W. Keusgen, “Simultaneous millimeter-wave multi-band channel sounding
FOR SUBMISSION access
in an urbanTO IEEEscenario,” in Proc. Eur. Conf. Antennas Propag. (EuCAP), May 2015, pp. 1–5. 30
[41] A. S. Poon and M. Ho, “Indoor multiple-antenna channel characterization from 2 to 8 GHz.” in Proc. IEEE Int. Conf.
Commun. (ICC), 2003, pp. 3519–3523.
[40] R. J. Weiler, M. Peter, T. Khne, M. Wisotzki, and W. Keusgen, “Simultaneous millimeter-wave multi-band channel sounding
[42] S. Jaeckel, M. Peter, K. Sakaguchi, W. Keusgen, and J. Medbo, “5G Channel Models in mm-Wave Frequency Bands,” in
in an urban access scenario,” in Proc. Eur. Conf. Antennas Propag. (EuCAP), May 2015, pp. 1–5.
Proc. Eur. Wireless Conf., May 2016, pp. 1–6.
[41] A. S. Poon and M. Ho, “Indoor multiple-antenna channel characterization from 2 to 8 GHz.” in Proc. IEEE Int. Conf.
[43] A. Ö. Kaya, D. Calin, and H. Viswanathan. (2016) 28 GHz and 3.5 GHz Wireless Channels: Fading, Delay and Angular
Commun. (ICC), 2003, pp. 3519–3523.
Dispersion.
[42] Jaeckel,
[44]S.R. C. QiuM.andPeter,
I.-T. K.
Lu,Sakaguchi,
“MultipathW. Keusgen,
resolving with
andfrequency “5G Channel
J. Medbo,dependence for Models in mm-Wave
wide-band Frequency
wireless channel modeling,” in
Bands,”IEEE
FOR SUBMISSION TO IEEE 30
Proc.
Trans. Wireless
Eur.Veh. Conf.,
Technol., vol.May 2016,
48, no. 1, pp.
pp. 1–6.
273–285, 1999.
6G Wireless Summit, 26th March 2019
[43] Kaya, D.
[45]A.K.Ö.Haneda, A.Calin,
Richter,
andand Viswanathan.
H.A. F. Molisch, (2016) 28 GHz
“Modeling and 3.5 GHz
the frequency dependence
WirelessofChannels:
ultra-wideband Delay and Angular
Fading,spatio-temporal indoor
FOR SUBMISSION TO IEEE 30
[40] Dispersion.
J. Weiler,
R.radio M. Peter,
channels,” IEEET. Khne,
Trans. M. Wisotzki,
Antennas Propag., Keusgen,
and W.vol. 60, no.“Simultaneous millimeter-wave
6, pp. 2940–2950, 2012. multi-band channel sounding
[44]
[46]in an
R.D. Qiu and
urban
C.Dupleich, I.-T.
access Lu, “Multipath
R. S.scenario,”
Thom, resolving
Proc.
G.inSteinb, Eur.
J. Luo, with
Conf. frequency
Antennas
E. Schulz, dependence
X. Propag.
Lu, G. Wang for
(EuCAP),wide-band
May
et al., wireless
2015, channel modeling,”
pp. 1–5.
“Simultaneous multi-band IEEE
channel sounding
[41] A.at
[40]Trans. Veh. Technol.,
R.S.mm-Wave
J.Poon
Weiler,and M. vol.
Ho,
frequencies,”
M. Peter, 48,inno.
T.“Indoor
Khne, M. pp. 273–285,
multiple-antenna
Proc. Eur. Conf.
1, Wisotzki, 1999.
channel
andAntennas
W. characterization
Propag.
Keusgen, (EuCAP),from
“Simultaneous 2 to
2016, pp.81–5.
millimeter-wave in Proc. IEEE
GHz.”multi-band channel Conf.
Int.sounding
6G: Towards a Fully Digital and Connected World
[45]
[47]Commun.
P.Haneda,
K.in Ky,
an urban Richter,
I.(ICC), 2003,
Carton,
A.access and
pp. 3519–3523.
Karstensen,
A.scenario,” W. Fan,
Proc. “Modeling
Eur.
A. F.inMolisch, G.Conf. the frequency
F. Pedersen
Antennas dependence
al., “Frequency
etPropag. of ultra-wideband
(EuCAP),dependency
May 2015, of spatio-temporal
pp.channel
1–5. parameters indoor
in urban
[42] S.LOS
[41]radio
A. channels,”
Jaeckel,
S. scenario
Poon
M.and IEEE
Peter,
for Trans.
mmwave
M.K.Ho, Antennas
Sakaguchi, W. Keusgen,
communications,”
“Indoor and
Propag., invol.
multiple-antenna 60, no. 6,
J. Medbo,
Proc. Eur.
channel pp.
“5G2940–2950,
Conf. Antennas
characterization 2012.
Models
Channel Propag.
from in
(EuCAP),
2 to 8mm-Wave
GHz.”2016, Bands,”
pp. 1–5.
Proc. IEEE
inFrequency in
Int. Conf.
[46]
[48]Proc.
D.Commun. (ICC),S. Thom,
Eur. Wireless
K.Dupleich,
Haneda, R.J.-i. Takada,
2003, G.
May
Conf.,pp. Steinb,
and T. Kobayashi,
2016,J. pp.
3519–3523. E. Schulz,
Luo,1–6. X. Lu, G.
“Experimental Investigation
Wang et al.,of“Simultaneous
Frequency Dependence channel
multi-band in sounding
Spatio-Temporal
[43] A.Propagation
[42]at S.mm-Wave
Ö.Jaeckel, frequencies,”
Kaya, D.Behaviour,”
M. Calin,
Peter, and in
in Proc.
H.Proc.
K. Sakaguchi,Eur.
Eur. Conf.
Viswanathan. Antennas
Antennas
(2016)
W.Conf.
Keusgen, 28 GHz
and Propag. (EuCAP),
(EuCAP),
and 3.5
J.Propag.
Medbo, “5GGHz 2016,
Wireless
Channel pp.
pp. 1–5.
1–6.
Channels:
2007,Models in mm-Wave
Fading, Frequency
Delay and Bands,”
Angular in
[47] P. Ky, I.
V. Nurmela
Proc.
[49]Dispersion. Carton, A.
Eur. Wireless Karstensen,
“METIS
et al., Conf., May W. Fan,
Channel G. F. Pedersen
Models,”
2016, pp. et al., “Frequency dependency
1–6. Mobile and wireless communications ofEnablers parameters
channel for in urban
the Twenty-twenty
[43]LOS
[44] A. scenario
Kaya,
R.Information
C.Ö.
Qiu for
D. mmwave
Calin,
and Society,
I.-T. Lu,Tech. Rep.,
“Multipath 2015.
andcommunications,”
H. Viswanathan. in
resolving with Proc.
(2016) Eur.
28 GHz
frequency Conf.
andAntennas
3.5 GHz
dependence Wireless
for Propag. (EuCAP),
wide-bandChannels: Fading,
wireless2016, pp. Delay
channel 1–5. and Angular
modeling,” IEEE
[48] K. Haneda, J.-i.
Sayeed,
Dispersion.
[50]Trans.
A. M.Veh. Takada, and T.
“Deconstructing
Technol., Kobayashi,
vol. 48, no. multiantenna“Experimental
fading
1, pp. 273–285, 1999. Investigation of Frequency Dependence in Spatio-Temporal
channels,” IEEE Trans. Signal Process., vol. 50, no. 10, pp. 2563–2579,
[44]Propagation
[45] K.2002.
R.Haneda, Behaviour,”
and
C. Qiu A. I.-T. Lu,
Richter, in
and Proc.
“Multipath
Eur.resolving
A. F. Molisch, Antennas
Conf.“Modeling Propag.
with frequency
the (EuCAP),
dependence
frequency 2007, pp.
for wide-band
dependence 1–6. wireless channel
of ultra-wideband modeling,”
spatio-temporal IEEE
indoor
[49] V. Nurmela
Trans.
[51]radio et
A. Alkhateeb, al.,
G. “METIS
Leus,
Veh. Technol.,
channels,” IEEE and
vol.
Trans. Channel
48,
R.no. Models,”
W.1,Heath
Antennas pp. 273–285,
Propag., Mobile
Jr., “Compressed
vol.1999. and wireless
60, no. sensing communications
based multi-user
6, pp. 2940–2950, for the
Enablers wave
2012. millimeter Twenty-twenty
systems: How many
[45]Information
[46] D.measurements
K.Dupleich, R. are
Haneda,Society,
A.S. needed?”
Richter,
Tech.and
Thom, in
G.Rep., 2015.
A. Proc.
F.
Steinb, Molisch,
J.IEEE
Luo, Int.
E. Conf. Acoust.,
“Modeling
Schulz, X.theLu, Speech
frequency
G. dependence
et al.,Process.
WangSignal (ICASSP),
of ultra-wideband
“Simultaneous multi-band 2015, pp. 2909–2913.
Aprilspatio-temporal
channel indoor
sounding
information on a higher frequency channel.
[50] M.
M.
A.radio
[52]at Sayeed,
L. “Deconstructing
Bencheikh,
channels,”
mm-Wave Y. Wang,
IEEE Trans.
frequencies,” multiantenna
and H.
Antennas
in Proc. fading
Propag.,
Eur.He,
Conf. channels,”
“Polynomial
vol.
Antennas 60,root IEEE
no.finding
Propag. pp.Trans. Signal
technique
2940–2950,
6, (EuCAP), Process.,
joint
2012.
2016,for
pp. vol. 50,
1–5.DOA DOD 10, pp. 2563–2579,
no. estimation in bistatic
the spatial correlation matrix derived at one
[46]2002.
[47] D.
P. MIMO radar,”R.Signal
Ky,Dupleich,
I. Carton, A. Process.,
S. Thom, G. Steinb,
Karstensen, W. 90,
J. Luo,
vol.Fan, G.
no. F.9, pp. 2723–2730,
Schulz,
E.Pedersen X.et Lu, 2010.
al., G. Wang et al.,
“Frequency “Simultaneous
dependency multi-band
of channel parameters
channelinsounding
urban
[51] M.
A.at
[53]LOS Bengtsson
Alkhateeb,
mm-Wave G. and B.
Leus, Ottersten,
and
frequencies,” R.
in W.“Low-complexity
Heath
Proc. Eur.Jr.,
Conf. estimators
“Compressed
Antennas for
sensing
Propag. distributed
based
(EuCAP), sources,”
multi-user
2016, IEEE Trans.
millimeter
pp. 1–5.
scenario for mmwave communications,” in Proc. Eur. Conf. Antennas Propag. (EuCAP), 2016, pp. 1–5. waveSignal Process.,
systems: vol. 48,
How many
[48] K.no. 8, pp.
[47]measurements
Ky,
P.Haneda, 2185–2194,
I. Carton,
J.-i.
areTakada, 2000.
needed?” in Proc.
A. Karstensen,
and IEEE
W.
T. Kobayashi, Conf.
Fan,Int.G.“Experimental Speech
Acoust., et
F. Pedersen Process.
al., “Frequency
Investigation
Signal of (ICASSP),
dependency
Frequency of April 2015,
channel
Dependence pp. 2909–2913.
inparameters in urban
Spatio-Temporal
[52] M.LOS
R.L.Keys, “Cubic
scenario
Bencheikh,
[54]Propagation for convolution
mmwave
Y. Wang, interpolation
communications,”
and H. He, for
“Polynomialdigital
in Proc. image
Eur.
root processing,”
Conf.
finding Antennas
technique
Behaviour,” in Proc. Eur. Conf. Antennas Propag. (EuCAP), 2007, pp. 1–6. IEEE
for Trans.
Propag.
joint Acoust.,
(EuCAP),
DOA DOD Speech,
2016, pp. Signal
1–5.
estimation in Process.,
bistatic
frequency to another at a much different frequency
[48]MIMO 29,
Haneda,
radar,” J.-i.
Signal 1153–1160,
pp.Takada, and
Process., T.1981.
vol. Kobayashi, “Experimental
no. 9, pp. 2723–2730, Investigation Dependence Spatio-Temporal
Need to define a “transformation function” to relate
[49] V.vol.
K.Nurmelano.et6,al., “METIS Channel 90,Models,” Mobile and wireless
2010. communications
of FrequencyEnablers for the
in Twenty-twenty
Disruptive Communication Technologies
[53] M.Propagation
Z.Bengtsson Dai, Z.
Behaviour,”
and Wang,in and
Ottersten, S.
Proc. Chen,
Eur. “Spatially
Conf.
“Low-complexity common
Antennas
estimators sparsity
Propag.
for based
(EuCAP),
distributed adaptive
2007, pp.
sources,” channel
1–6.
IEEE estimation
Trans. Signal and feedback
Process., vol. 48,for
increase multiplexing and system throughput without
[55]Information
Gao, L.Society, B. Tech. Rep., 2015.
IDEA: leverage channel state information acquiredapertures.
sources –
[49]no.
[50] massive
8,Nurmela
A.FDD
V.M. pp. etMIMO,”
al., “METIS
2185–2194,
Sayeed, 2000.
“Deconstructing Trans.
ChannelSignal
IEEE multiantenna Process.,
Models,”
fading Mobile
vol. and
channels,” no.
63,IEEE 23,
wirelesspp.
Trans. 6169–6183,
communications
Signal 2015.
Process., Enablers
vol. 50, no.
for10,the
pp.Twenty-twenty
2563–2579,
[54] M. Mishali
R.Information
Keys,
[56]2002. and
Society,
“Cubic Y. C.Tech.
convolution “Reduce
Eldar,Rep.,
interpolation boost:
2015.andfor Recovering
digital arbitrary sets
image processing,” of jointly
IEEE Trans. sparse
Acoust.,vectors,”
Speech,IEEE Trans.
Signal Signal
Process.,
[50]vol.
[51] M. Sayeed,
29, no. vol.
A.Process.,
A.Alkhateeb, 56,
pp.
6, G. no. 10,
“Deconstructing
1153–1160,
Leus, and pp. 4692–4702,
multiantenna
R. 1981.
W. fading channels,”
Heath Jr.,2008.
“Compressed IEEE
sensing Trans.
based Signal Process.,
multi-user millimeter 50, no.
vol.wave systems: 2563–2579,
10, pp.How many
[55] F. Gorodnitsky
Z.2002.
I.Gao,
[57]measurements and B. D.
Wang,
L. Dai,areZ.needed?” andRao,
S. “Sparse
Chen, signal
“Spatiallyreconstruction
common from
sparsity limited
based data using
adaptive FOCUSS:
channel A
estimationre-weighted
and minimum
feedback
in Proc. IEEE Int. Conf. Acoust., Speech Signal Process. (ICASSP), April 2015, pp. 2909–2913. for
areOBB
at a lower
Both sub-6
algorithm,” IEEE
Leus, Trans.
R. Signal
W. Heath Jr., 45,
“Compressed 3, pp.
sensing 600–616,
based 1997.
multi-user millimeter wave many
used at the
[51]FDD
[52] massive
M.norm MIMO,”
A.L.Alkhateeb,
Bencheikh,G.Y. IEEE
Wang, Trans.
andand H. Signal Process.,
He,Process., vol. vol.
“Polynomial root63, no.
no.finding pp. 6169–6183,
23,technique for joint2015.
DOA DOD estimation
systems:inHow
bistatic
M.measurements
[56] MIMOMishali and are
Y. needed?”
C. Eldar, in Proc.
“Reduce IEEE
and Int.
boost: Conf. Acoust.,
Recovering
radar,” Signal Process., vol. 90, no. 9, pp. 2723–2730, 2010. Speech
arbitrary Signal
sets Process.
of jointly (ICASSP),
sparse April
vectors,” 2015,
IEEE pp. 2909–2913.
Trans. Signal
MmWave System
Continuous downlink transmission with uplink acknowledgments
[53] L. Bencheikh,
[52]Process., vol. 56,
M.M.Bengtsson and no. 10,Wang,
B.Y.
Ottersten, and
pp. 4692–4702, “Polynomial
H. He,2008.
“Low-complexity estimators finding
rootfor technique
distributed for joint
sources,” IEEEDOA
Trans.DOD estimation
Signal Process., in
vol.bistatic
48,
[57]
Sub-6 GHz System
radar,” Signal Process., pp. 2723–2730, 2010.
I. MIMO
[57] no. F.8,Gorodnitsky
pp. 2185–2194, D. Rao, “Sparse
and B.2000. vol. 90,signal
no. 9,reconstruction from limited data using FOCUSS: A re-weighted minimum
SUBMISSION
assume that the sub-6 GHz and
[53] M. Bengtsson and B. Ottersten, “Low-complexity for sources,” IEEE Trans. Signal Process., vol. 48,
2012.
RFnorm
[54] R.Chain algorithm,”
Keys, IEEE
“Cubic convolution Signal Process.,
Trans. interpolation vol. estimators
for digital
45,image pp. distributed
no. 3,processing,” 1997.
600–616,IEEE Trans. Acoust., Speech, Signal Process.,
MIMO
no. 8, pp. 2185–2194, 2000.
channel
DAC vol. 29, no. 6, pp. 1153–1160, 1981.
MmWave System
FORfrequency
[54] R. Keys, “Cubic convolution interpolation for digital image processing,” IEEE Trans. Acoust., Speech, Signal Process.,
[55] Z. Gao, L. Dai, Z. Wang, and S. Chen, “Spatially common sparsity based adaptive channel estimation and feedback for
fading model (e.g., Rayleigh or Ricean).
GHz and mmWave
mmWave
Sub-6 vol.
GHz 29, no. 6, pp. 1153–1160, 1981.
System
FOR SUBMISSION TO IEEE
FDD massive MIMO,” IEEE Trans. Signal Process., vol. 63, no. 23, pp. 6169–6183, 2015.
TO IEEE as
[55] Z. Gao, L. Dai, Z. Wang, and S. Chen, “Spatially common sparsity based adaptive channel estimation and feedback for
Transmitter Receiver
[56] M. Mishali and Y. C. Eldar, “Reduce and boost: Recovering arbitrary sets of jointly sparse vectors,” IEEE Trans. Signal
RF Chain
Disruptive Communication Technologies – Full-Duplex
H
[58] M. Grant, S. Boyd, and Y. Ye,
radar,” Signal Process.,
FDD massive MIMO,” IEEE Trans. Signal Process., vol. 63, no. 23, pp. 6169–6183, 2015.
“IEEE standard for information
,
[56] I. F. Gorodnitsky and B. D. Rao,
[58]
the proposed strategies can be extended to other[51]
arrays
Process., vol. 56, no. 10, pp. 4692–4702, 2008.
no. 8, pp. 2185–2194, Aug. 2000.
6G Technologies and Innovations
systems
DAC
metropolitan area networks–Specific
[56] M. Mishali and Y. C. Eldar, “Reduce and boost: Recovering arbitrary sets of jointly sparse vectors,” IEEE Trans. Signal
H
layer (PHY) specifications amendment
“CVX:
[57] I. F. Gorodnitsky and B. D. Rao, “Sparse signal reconstruction from limited data using FOCUSS: A re-weighted minimum
array
Sub-6 GHznorm
2012.
vol.are
[56]“Sparse
Process., vol. 56, no. 10, pp. 4692–4702, 2008.
vol. 29, no. 6, pp. 1153–1160, Dec. 1981.
Fare clic per modificare stile
90, no.
Base station
norm algorithm,” IEEE Trans. Signal Process., vol. 45, no. 3, pp. 600–616, 1997.
M. Grant,
norm algorithm,” IEEE Trans. Signal Process.,
layer3:(PHY)
metropolitan
User equipment
[57] I. F. Gorodnitsky and B. D. Rao, “Sparse signal reconstruction from limited data using FOCUSS: A re-weighted minimum
a form
MmWave System
System
I. F. Gorodnitsky
using additional bandwidth.
algorithm,”
MmWave
Process., vol. 56, no. 10, pp. 4692–4702, Oct. 2008.
norm algorithm,”
SystemIEEE Trans. Signal Process., vol. 45, no. 3, pp. 600–616, 1997.
TX and the RX.estimation
requirements-Part
The transceiver in base stations and UEs will be capable of TX a signal while also TX
vol. 45,
MatlabS.software
operateof
FOR SUBMISSION TO IEEE
Enhancements
The sub-6 GHz channel is H and the mmWave channel is H.
IEEE
Boyd, and
Sub-6 GHz System
M. L. geometries
MmWave System
specifications
forY.
co-located,
signal reconstruction
Transmitter Receiver
Bencheikh, Y. Wang,
17
no.Trans.
III. S YSTEM AND CHANNEL MODEL
[57]technology–Telecommunications
for very
RF Chain
and B. D. from
9, pp. 2723–2730, Sep.
Sub-6 GHz System
no. 8, pp. 2185–2194, Aug. 2000.
http://www.stanford.edu/ boyd/cvx http://www.stanford.edu/ boyd/cvx
Gaussian or truncated Laplacian), and the complex coefficients ↵r
with
“IEEE standard for informationand
disciplined
area networks–Specific
side
or control messages à
3, pp.Signal
c,i
amendment
Ye, “CVX:
DAC
2010.
RF Chain
11: Wireless LAN
Rao, “Sparse
600–616,
vol. 29, no. 6, pp. 1153–1160, Dec. 1981.
aligned,
simultaneously.
convex
limited data
Matlab
DAC
Process.,
high throughput
signal
and H.suitable
using
Mar. 1997.
Process., vol. 56, no. 10, pp. 4692–4702, Oct. 2008.
He, “Polynomial
requirements-Part
3: Enhancements
[55] M. Mishali and Y. C. Eldar, “Reduce and boost: Recovering arbitrary sets of jointly sparse
FDD massive MIMO,” IEEE Trans. Signal Process., vol.
according
software f
information exchange
medium access1
[54] Z. Gao, L. Dai, Z. Wang, and S. Chen, “Spatially comm
Fig. 1: The multi-band MIMO system with co-located sub-6 GHz and mmWave a
[54] Z. Gao, L. Dai, Z. Wang, and S. Chen, “Spatially common sparsity based adaptive channel
technology–Telecommun
[55] M. Mishali and Y. C. Eldar, “Reduce and boost: Recover
FDD massive MIMO,” IEEE Trans. Signal Process., vol. 63, no. 23, pp. 6169–6183, Dec. 2
The ULAs are considered for ease of exposi
[52] M. Bengtsson and B. Ottersten, “Low-complexity estimators for distributed sources,” IEEE Tr
[52] M. Bengtsson and B. Ottersten, “Low-complexity estimato
MIMO radar,” Signal Process., vol. 90, no. 9, pp. 2723–2
reconstruc
[51] M. L. Bencheikh, Y. Wang, and H. He, “Polynomial root finding technique for joint DOA
programming
in the 60 f
FOCU
[53] R. Keys, “Cubic convolution interpolation for digital image processing,” IEEE Trans. Acou
mod roo
[53] R. Keys, “Cubic convolution interpolation for digital ima
and hav
vol. 45, no
We consider a multi-band MIMO system shown in Fig. 1, where ULAs of isFare clic per modificare stile
6G Technologies and Innovations
Disruptive Communication Technologies – Channel Sparsity
• Estimating the mmWave channel is equivalent to estimating the parameters of the channel
paths, i.e., the AoA, the AoD, and the gain of each path.
• IDEA: exploit the poor scattering nature of the mmWave channel to formulate the mmWave
channel estimation problem as a sparse compressed sensing problem: the channel power is
concentrated in a few entries of a virtual channel matrix
• It is sufficient to estimate the AoAs and AoDs
of the dominant paths to be resolved.
Example of 6 dominant paths (the location of each
square reflects the AoA and time delay of each path)
(a) Grayscale of angular-delay domain
B. Wang, et al., "Spatial- and Frequency-Wideband Effects in Millimeter-Wave Massive MIMO Systems," in IEEE Trans. Sig. Proc., vol. 66, no. 13, pp. 3393-3406, Jul. 2018.
Fig. 4. An illustration of a 6-path SFW channel, where M = 128, N = 12
6G: Towards a Fully Digital and Connected World
18
6G Wireless Summit, 26th March 2019
D. Sparse Channel Representation and Angular-Delay Or-Fare clic per modificare stile
6G Technologies and Innovations
Innovative Network Architectures – Disaggregation/virtualization
• IDEA: decouple network/control plane (CP) and forwarding/user plane (UP).
Ø SDN offers network programmability and centralization of the control
Ø SDN is agile and responsive (traffic flow meets fluctuating needs and demands).
Ø SDN is standards-based (e.g., OpenFlow) and vendor-neutral.
• IDEA: replace network services provided by dedicated hardware (e.g., network
switches) with virtualized software.
Ø NFV saves capital and operating expenses
NFV and SDN are complementary technologies
(SDN executes on an NFV infrastructure)
• C. J. Bernardos et al., "An architecture for software defined wireless networking," in IEEE Wireless Communications, vol. 21, no. 3, pp. 52-61, June 2014.
• R. Mijumbi, et al., "Network Function Virtualization: State-of-the-Art and Research Challenges," in IEEE COMST, vol. 18, no. 1, pp. 236-262, 2016
6G: Towards a Fully Digital and Connected World
19
6G Wireless Summit, 26th March 2019Fare clic per modificare stile
6G Technologies and Innovations
Innovative Network Architectures – Access/Backhaul integration
• Massive 6G data rates technologies à
IAB node stack
Backhaul Access
PDCP PDCP
adequate growth of the backhaul capacity RLC
MAC
RLC
MAC
PHY PHY
SCHED
Donor gNB
• THz and VLC deployments will call for a massive IAB node
increase in the density of access points, which should IAB node
be provided with backhaul connectivity to the core network à expensive
• IDEA: deploy a fraction of BSs with traditional fiber-like backhaul capabilities and the rest
of the BSs connecting to the fiber infrastructures wirelessly.
• 6G deployments will introduce new challenges and opportunities
• The networks will need higher autonomous configuration capabilities
• Out-of-band IAB can be realized to increase the overall network throughput.
• M. Polese, et al. , "End- to-End Simulation of Integrated Access and Backahul at mmWaves,” to appear on IEEE CAMAD, Sep. 2018.
• M. Polese, et al., "Distributed Path Selection Strategies for Integrated Access and Backhaul at mmWaves", to appear on IEEE GLOBECOM, Dec. 2018
6G: Towards a Fully Digital and Connected World
20
6G Wireless Summit, 26th March 2019Fare clic per modificare stile
6G Technologies and Innovations
Integrating Intelligence in the Network – Learning
• BACKGROUND: the signal received at multiple BSs renders a defining signature for the user
location and its interaction with the surrounding environment.
• BACKGROUND: UEs typically move through predefined paths, and some movements are
impossible due to the presence of obstacles, e.g., buildings, walls.
• IDEA: account for previous access statistics and use machine learning tools to predict the
network behaviors (e.g., by remembering/observing consequences of previous decisions).
SUPERVISED LEARNING
The amount of data generated
will be massive, thus labeling
the data may be infeasible. UNSUPERVISED LEARNING
Does not need labeling, used to
autonomously build complex
network representations
6G: Towards a Fully Digital and Connected World
21
6G Wireless Summit, 26th March 2019Fare clic per modificare stile
6G Technologies and Innovations
Mission Planning
Integrating Intelligence in the Network – Knowledge sharing and learning
Reference Planner
Fig. 4: Reference planners result: the desired path cut corners
• 5G: At at thebandwidth
high frequency, the massive turn to minimize path length
and spatial degreesand ofgenerate
freedombetter
are
Behavioral Planner
handling
unlikely to be fully used by any one cellular operator. Spectrum can be shared, in
time and in space, with several performance and energy benefits:
Controllers
§ Reducing deployment costs, if operators share bands and infrastructures
Candidate Strategy Generation
§ Inter-operators access and interference coordination
ACC Lane Merge
Controller Centering Assist Multiple candidate strategies
• 6G: operators and users may also be interested in sharing learned
representations
ed behavioral of specific network Prediction
planning framework deployments
Engine and/or use cases
§ Speed up the network configuration in new markets
Predicted surrounding
traffic scenarios
§ Better adapt to new unexpected scenarios which may emerge during network operations
RAL P LANNING F RAMEWORK Cost function-based Evaluation
ction II, there are shortcomings of Fuel
Progress Comfort Safety Consum
archical and parallel robot decision -ption
Due to real-time constraints, the mo-
nsider the effects of imperfect vehi-
peration between cars. In this paper, Best Strategy
behavioral planning framework that
6G: Towards a Fully Digital and Connected World Fig. 5: The block diagram of Prediction- and Cost-function
s of the hierarchical
6G Wireless and2019parallel ar-
Summit, 26th March
22Fare clic per modificare stile
6G Challenges
• Circuit design, high propagation loss
• Integrate energy characteristics in protocols
• Limited coverage, need for RF uplink
• Energy vs. high-deployment / MIMO 5
• Need for reliable frequency mapping
Efficient and low-power network operations
Energy will be at the core of 6G protocols design
Extreme multi-connectivity
s
g
e
stin
Exploit THz, VLC, mmWave and
nod
sub-6 GHz links
ve
wer
har
-po
rgy
Low
Ene
Disaggregated and virtualized RAN
The networking equipment will not require dedicated hardware
Cloud Edge Cell-less architecture
The UE connects to the RAN
and not to a single cell
Virtual Virtual
MAC PHY
Generic hardware
Fig. 4: Architectural innovations introduced in 6G networks.
• Slower network operations/security concerns • Scheduling, need for new network design
• CU/UP functions
ping arestudied
has been widely tightly coupled
[15], but such capabilities Scalability,
The• overcoming of the and interference
cell concept management
will also enable
have never been deeply integrated with the operations and a tight integration of the different 6G communication
protocols of cellular networks. 6G networks will exploit technologies. The users will be able to seamlessly tran-
a unified interface for localization and communications sition among sub-6 GHz, mmWave, terahertz or VLC
to (i)and
6G: Towards a Fully Digital improve control
Connected World operations, which can rely on links without manual interventions or configurations in
23
6G Wireless Summit,context
26th March 2019
information (without the need for exchanging the device, which will automatically select the best avail-6G: Towards a Fully Digital and Connected World
Marco Giordani◦, Michele Polese◦, Marco Mezzavilla†, Sundeep Rangan†, Michele Zorzi◦
◦University of Padova, Department of Information Engineering, Italy
† NYU WIRELESS, Tandon School of Engineering, New York University, Brooklyn, NY, USA
6G Wireless Summit, Levi, Finland
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