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Wireless 2.0: Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces(How it Works, State of Research, and the Road Ahead)
Marco Di Renzo Paris-Saclay University
Laboratory of Signals and Systems (L2S) CNRS and CentraleSupelec
Paris, Francemarco.di-renzo@universite-paris-saclay.fr
VDL IEEE COMSOCAtlanta Chapter, USANovember 19th, 2020
Smart Radio Environments & Reconf. Metasurfaces
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Current Wireless Networks
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Current Wireless Networks
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Current Wireless Networks
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Current Wireless Networks
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Current Wireless Networks
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Current Wireless Networks
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Current Wireless Networks: No Control of Radio Waves
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Current Wireless Networks: No Control of Radio Waves
“Dumb” Wireless
Current Wireless Networks: No Control of Radio Waves
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In conventional networks:
Current Wireless Networks: No Control of Radio Waves
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In conventional networks: We usually perceive the environment as an
“unintentional adversary” to communication
Current Wireless Networks: No Control of Radio Waves
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In conventional networks: We usually perceive the environment as an
“unintentional adversary” to communication
We usually optimize only the end-points of thecommunication network
Current Wireless Networks: No Control of Radio Waves
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In conventional networks: We usually perceive the environment as an
“unintentional adversary” to communication
We usually optimize only the end-points of thecommunication network
We have no control of the environment, which isviewed as a passive spectator
Current Wireless Networks: No Control of Radio Waves
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In conventional networks: We usually perceive the environment as an
“unintentional adversary” to communication
We usually optimize only the end-points of thecommunication network
We have no control of the environment, which isviewed as a passive spectator: we just adapt to it
Current Wireless Networks: No Control of Radio Waves
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In conventional networks: We usually perceive the environment as an
“unintentional adversary” to communication
We usually optimize only the end-points of thecommunication network
We have no control of the environment, which isviewed as a passive spectator: we just adapt to it
… WHAT IF …
Smart Radio Environments
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Smart Radio Environments
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Smart Wireless
Smart Radio Environments
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Smart Wireless
From Radio Environments…
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From Radio Environments…
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From Reflections …
… to Smart Radio Environments
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… to Smart Radio Environments
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… to Smart Reflections
Radio Environments
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Adaptation: End-Points Optimization
Radio Environments
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Adaptation: End-Points Optimization
Smart Radio Environments
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Control & Programmability: Joint Optimization
Smart Radio Environments
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Control & Programmability: Joint Optimization
Smart Radio Environments
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Smart Wireless
… from adaptation to …
Control & Programmability
Smart Radio Environments
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Smart Wireless
… from adaptation to …
Control & Programmability↓
Technology↓
RISs (metasurface)
↓Algorithms
↓AI
Smart Radio Environments
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Smart Wireless
… from adaptation to …
Control & Programmability↓
Technology↓
RIS (metasurface)
↓Algorithms
↓AI
Smart Radio Environments
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Smart Wireless
… from adaptation to …
Control & Programmability↓
Technology↓
RIS (metasurface)
↓Algorithms
↓AI
Smart Radio Environments
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Smart Wireless
… from adaptation to …
Control & Programmability↓
Technology↓
RIS (metasurface)
↓Algorithms
↓ML/AI
Smart Radio Environments
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Smart Wireless
… from adaptation to …
Control & Programmability↓
Technology↓
RIS (metasurface)
↓Algorithms
↓ML/AI
How Can We Realize Smart Radio Environments ?
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How Can We Realize Smart Radio Environments ?
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Reconfigurable Intelligent Surfaces (RISs)
What is an RIS ?
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What is an RIS ? …A New Antenna Technology for 6G
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July 14, 2020
What is an RIS ? …A New Antenna Technology for 6G
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July 14, 2020
Ei,HiEs,Hs
= f(Ei,Hi)
What Wave Transformations Can an RIS Apply ?
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What Wave Transformations Can an RIS Apply ?
40
RIS-Assisted Wireless: What Wave Transformations ?
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RIS-Assisted Wireless: What Wave Transformations ?
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RIS-Assisted Wireless: What Wave Transformations ?
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Reflection/Transmission“Surfaces”
RIS-Assisted Wireless: What Wave Transformations ?
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Transmit “Antennas”
How Does an RIS Look Like ?
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How Does an RIS Look Like (“surfaces”) ?
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Univ. CaliforniaSan Diego
MobiCom 2020
Aalto UniversityPhysics Appl. 2017
MITUSENIX 2020
Docomo 2020Transparent Metasurface
Southeast UniversityTWC 2020
Tsinghua UniversityAccess 2020
PRESS-LAIAACM HotNets 2017
How Does an RIS Look Like (“antennas”) ?
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How Does an RIS Look Like (“antennas”) ?
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What is an RIS Useful For ?
49
What is an RIS Useful For ? …RIS-Empowered Wireless
“Smart Radio Environments Empowered by RISs”, arXiv:2007.03435
What is an RIS Useful For ? …Smart Glasses
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What is an RIS Useful For ? …Large Smart Walls
52“SREs: An Idea Whose Time Has Come”, arXiv:1903.08925
Enhancing Coverage, Rate, Security Through RISs
53“RISs: Principles & Opportunities”, arXiv:2007.03435
Examples…
54“RISs vs. Relays”, arXiv:1908.08747
Reconfigurable Intelligent Surfaces
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Conceptual Structure
Reconfigurable Intelligent Surfaces
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Conceptual Structure
Reconfigurable Intelligent Surfaces
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Conceptual Structure and Operation
How To Construct an RIS ?
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How To Construct an RIS ?
Tiny Antenna Elements vs. (Homogenized) Metasurfaces
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How To Construct an RIS ?
Tiny Antenna Elements vs. (Homogenized) Metasurfaces
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How To Construct an RIS ?
61
Tiny Antenna Elements vs. (Homogenized) Metasurfaces
How To Construct an RIS ?
62
Tiny Antenna Elements vs. (Homogenized) Metasurfaces
How To Construct an RIS ?
Tiny Antenna Elements vs. (Homogenized) Metasurfaces
“Terahertz Massive MIMO with Holographic RIS”, arXiv:2009.10963
How To Construct an RIS ?
64
Tiny Antenna Elements vs. (Homogenized) Metasurfaces
How To Construct an RIS ?
65
RISs can be built in different ways, which include:
Tiny Antenna Elements vs. (Homogenized) Metasurfaces
How To Construct an RIS ?
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RISs can be built in different ways, which include:
Implementations based on large arrays of inexpensiveantennas that are usually spaced half of the wavelengthapart
Tiny Antenna Elements vs. (Homogenized) Metasurfaces
How To Construct an RIS ?
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RISs can be built in different ways, which include:
Implementations based on large arrays of inexpensiveantennas that are usually spaced half of the wavelengthapart
Metamaterial-based planar or conformal large surfaceswhose scattering elements have sizes and inter-distancesmuch smaller than the wavelength
Tiny Antenna Elements vs. (Homogenized) Metasurfaces
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What Does Make an RIS Different ?
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What Does Make an RIS (surfaces) Different ?
Nearly-Passive Design / Implementation
What Does Make an RIS (surfaces) Different ?
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Nearly-Passive Design / Implementation
Normal OperationPhase
Control & ConfigurationPhase
What Does Make an RIS (surfaces) Different ?
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Nearly-Passive Design / Implementation
An RIS is nearly-passive if the following three conditions arefulfilled simultaneously: No power amplification is used after configuration (during the
normal operation phase)
Minimal digital signal processing capabilities are needed only toconfigure the surface (during the control and programming phase)
Minimal power is used only to configure the surface (during thecontrol and programming phase)
Normal OperationPhase Passive
Control & ConfigurationPhase
Nearly-Passive RISs: Advantages and Limitations
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Example: RIS vs. (FD) Relay
Nearly-Passive RISs: Advantages and Limitations
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Example: RIS vs. (FD) Relay
Reduced hardware complexity
No additive noise
No power amplifiers
Interference-free full-duplex
…
Nearly-Passive RISs: Advantages and Limitations
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Example: RIS vs. (FD) Relay
RIS (1.5m = 140𝜆, reflector)vs. FD Relay (1-antenna)
arXiv:1908.08747
Reduced hardware complexity
No additive noise
No power amplifiers
Interference-free full-duplex
…
Nearly-Passive RISs: Advantages and Limitations (?)
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Example: RIS vs. (FD) Relay
3,720 inexpensive antennas on a 6 square-meter surface
MITUSENIX 2020
Reduced hardware complexity
No additive noise
No power amplifiers
Interference-free full-duplex
…
Nearly-Passive RISs: Long-Term Vision
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For these reasons, RISs may constitute an emerging andpromising software-defined architecture that can be realizedat reduced cost, size, weight, and power (C-SWaP design)
C-SWaP
Nearly-Passive RISs: Long-Term Vision
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Sustainable wireless design (e.g., low EMF exposure) without generating new waves and possibly made of physically &
aesthetically unobtrusive and recyclable material
C-SWaP
NTT Docomo, MetaWave, AGCTransparent Metasurface
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What Does Make an RIS Different ?
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What Does Make an RIS (antennas) Different ?
Low Complexity / Low Power / Single-RF Design
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What Does Make an RIS (antennas) Different ?
Low Complexity / Low Power / Single-RF Design
RIS-Based Antennas: Advantages and Limitations
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RIS
RIS-Based Antennas: Advantages and Limitations
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RIS
RIS-Based Antennas: Advantages and Limitations
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RIS
RIS-Based Antennas: Advantages and Limitations
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RIS
RIS-Based Antennas: Advantages and Limitations
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Example: Power Consumption
RIS-Based Antennas: Advantages and Limitations
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Example: Power Consumption
RIS
RIS-Based Antennas: Advantages and Limitations
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Example: Power Consumption
RIS
RIS-Based Antennas: Advantages and Limitations
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Example: Power Consumption
RIS
RIS-Based Antennas: Advantages and Limitations
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Example: Power Consumption
Compared with other transmission technologies, e.g.,phased arrays, multi-antenna transmitters, and relays, RISsrequire the largest number of scattering elements, but eachof them needs to be backed by the fewest and least costlycomponents. Also, no power amplifiers are usually needed.
RIS
RIS-Based Antennas: Advantages and Limitations
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Example: Power Consumption
… no free lunch rule …
Compared with other transmission technologies, e.g.,phased arrays, multi-antenna transmitters, and relays, RISsrequire the largest number of scattering elements, but eachof them needs to be backed by the fewest and least costlycomponents. Also, no power amplifiers are usually needed.
RIS
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Communication-Theoretic View
Communication-Theoretic View
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Conventional IT/COM Wireless
… encoder and decoder are optimized given the environment …
Communication-Theoretic View (“surfaces”)
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RIS-Empowered: “Optimizing the Environment”
… encoder and decoder are optimized jointly with the environment …
Communication-Theoretic View (“surfaces & antennas”)
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RIS-Empowered: “Modulating the Environment”
… encoder and decoder are optimized jointly with the environment …… and information data is modulated into environment-dependent states …
Example: Modulating the Environment (“antennas”)
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Example: Modulating the Environment (“antennas”)
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Spatial Modulation
modulation symbol: s1
RIS phases: R1, …, R12
Spatial ModulationIEEE Proc. 2014
Metasurface ModulationarXiv:2009.00789
Example: Modulating the Environment (“antennas”)
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Spatial Modulation
modulation symbol: s2
RIS phases: R1, …, R12
Spatial ModulationIEEE Proc. 2014
Metasurface ModulationarXiv:2009.00789
Example: Modulating the Environment (“surfaces”)
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Spatial Modulation
Example: Modulating the Environment (“surfaces”)
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Spatial Modulation
Example: Modulating the Environment (“surfaces”)
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Spatial Modulation
Joint Active & Passive Wireless Networks Design
“Holographic MIMO Surfaces for 6G”, arXiv:1911.12296
“RISs can fundamentallytransform today’s wirelessnetworks with active nodessolely into a new hybridnetwork comprising active andpassive components co-working in an intelligent way,in order to achieve asustainable capacity growthwith low and affordable costand power consumption”
Joint Active & Passive Wireless Networks Design
“Holographic MIMO Surfaces for 6G”, arXiv:1911.12296
What Do We Do @ CNRS & Paris-Saclay Univ. ?
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What Do We Do @ CNRS & Paris-Saclay Univ. ?
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… from theory to simulations and experiments…
Mainly, we do theory and simulations (physics-basedmodeling, analysis, and optimization in small-scale andlarge-scale wireless networks)
But, we validate our models in collaboration with partnerswhose research activity focuses on hardware development,experimental measurements, and ray tracing simulations
IEEE Trans. Wireless Commun.world’s first (arXiv:1911.05326)
Partner University (China)
Path-Loss: What is the Power Scattered by an RIS ?
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TxRx
?
Path-Loss Modeling (Theory)
106“On the Path-Loss of RISs”, arXiv2007.13158
Path-Loss Modeling (Experiments)
107IEEE Trans. Wireless Communications – arXiv:1911.05326
Path-Loss Modeling (Experiments)
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Some Recent Results
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Path-Loss Modeling – Physics-Based Foundation (submitted) M. Di Renzo et al., On the Path-Loss of Reconfigurable Intelligent Surfaces: An
Approach Based on Green’s Theorem Applied to Vector Fields (arXiv:2007.13158)
E2E Commun. Model – Mutual-Coupling/Unit-Cell Aware (submitted) M. Di Renzo et al., End-to-End Mutual-Coupling-Aware Communication Model for
Reconfigurable Intelligent Surfaces: An Electromagnetic-Compliant Approach Basedon Mutual Impedances (arXiv:2009.02694)
SNR Distribution – Improving Signal Reliability (WCL 2020) M. Di Renzo et al., Beamforming Through Reconfigurable Intelligent Surfaces in
Single-User MIMO Systems: SNR Distribution and Scaling Laws in the Presence ofChannel Fading and Phase Noise (arXiv:2005.07472)
Rate Optimization – RIS-Aided MIMO (submitted) M. Di Renzo et al., Achievable Rate Optimization for MIMO Systems with
Reconfigurable Intelligent Surfaces (arXiv:2008.09563)
Overhead-Aware Design – SE & EE (TWC 2020) M. Di Renzo et al., Overhead-Aware Design of Reconfigurable Intelligent Surfaces in
Smart Radio Environments (arXiv:2003.02538)
Joint Encoding – Capacity-Optimal Design (ISIT 2020) M. Di Renzo et al., Beyond max-SNR: Joint Encoding for Reconfigurable Intelligent
Surfaces (arXiv:1911.09443)
Single-RF MIMO – Metasurface-Based Modulation (submitted) Miaowen Wen, M. Di Renzo et al., Single-RF MIMO: From Spatial Modulation to
Metasurface-Based Modulation (arXiv:2009.00789)
Recurrent Questions (addressed in part)
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Recurrent Questions (addressed in part)
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Ei, Hi Es, Hs = f(Ei, Hi)
Recurrent Questions (addressed in part)
112
Ei, Hi Es, Hs = f(Ei, Hi)
2 2
1 1
S R exN pN N
n n n nn nn
nn
h g h jg
Recurrent Questions (addressed in part)
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Power scaling law vs. size of the RIS (~N2)
Power scaling law vs. transmission distancearXiv:1911.05326(measurements)
arXiv:2007.13158(theory)
Recurrent Questions (addressed in part)
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Sub-wavelength inter-distance
arXiv:2007.13158 arXiv:2009.10963
(left) d= 0.25 λ, (right) d = 0.5 λ
d = λ/2 d < λ/2 d 0 (<< λ/2)
Recurrent Questions (addressed in part)
115
Robustness to fading (Amount of Fading ~ 1/N)
arXiv:2005.07472
Recurrent Questions (addressed in part)
116
Channel estimation/feedback overhead
arXiv:2003.02538
Recurrent Questions (addressed in part)
117
Hardware limitations (e.g., quantization bits)
arXiv:2008.05317
Recurrent Questions (addressed in part)
118
Network deployment and optimization
arXiv:2008.09563
Recurrent Questions (addressed in part)
119
Network deployment and optimization
arXiv:2008.09563
Recurrent Questions (addressed in part)
120
Physics-aware communication model
(i) E2E Model(ii) EM-Compliant(iii) Mutual Coupling Aware(iv) Unit Cell Aware
arXiv:2009.02694
Physics-Aware Model – SNR vs. Impedance Modeling
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Physics-Aware Model – SNR vs. Impedance Modeling
122
ris
ris
2
ST SR1
2optimization
ST SR1
SNR : ,
,
N
Rn
N
n
P n n n n
n n n n
Γ h g
Γ h g
Physics-Aware Model – SNR vs. Impedance Modeling
123
ris
ris
22no coupling no coupling ST SR
VLOS1
I
RIS SS
2
ST SRoptimization
1 SS Sopt
R
... lots to optimize :)
Z : H, ,
, ,
N
Rn
N
n n n
n nP
n n n n
n nn n
Z
Z ZZ Z
Z ZZ
Physics-Aware Model – SNR vs. Impedance Modeling
124
ris
ris
2
ST SR1
2optimization
ST SR1
SNR : ,
,
N
Rn
N
n
P n n n n
n n n n
Γ h g
Γ h g
ris
ris
22no coupling no coupling ST SR
VLOS1
I
RIS SS
2
ST SRoptimization
1 SS Sopt
R
... lots to optimize :)
Z : H, ,
, ,
N
Rn
N
n n n
n nP
n n n n
n nn n
Z
Z ZZ Z
Z ZZ
Recurrent Questions (addressed in part)
125
Channel capacity limitJoint EncodingarXiv:1911.09443
Metasurface ModulationarXiv:2009.00789
Recurrent Questions (addressed in part)
126
What gains without instantaneous CSI (in writing) ?
RIS 4
RIS 3
RIS 2
RIS 1
127
Closing Remarks
Programming the Environment: Towards Wireless 2.0
128
Enhancing Coverage, EE, Rate Through Space Waves
129
Reconfigurable Intelligent Metasurfaces
130
Where Are We ?
Reconfigurable Intelligent Metasurfaces
131
Where Are We ?
Professor Stefano Maci, Huawei Antenna Summit 2019
Hundreds of Papers on arXiv… What’s Left ?
132
Hundreds of Papers on arXiv… What’s Left ?
133
EM-based circuital models
Path-loss and channel modeling
Fundamental performance limits
Robust optimization and resource allocation
Constrained system design and optimization
EM-based communications: “Layer-0” networking
Large-scale networks: Deployment, analysis, optimization
Ray tracing and system-level simulators
Beyond far-field communications
Beyond communications
Advantages and limitations… do RISs bring any (substantial) gains as compared with other
well-established technologies in wireless networks ?
On Electromagnetic Information Theory (EIT)
134
Opportunity – EIT: Reconciling COM, SP, IT, EM, …
135
G. Green, “An Essay on the Application of Mathematical Analysis to theTheories of Electricity and Magnetism”, 1828.
J. C. Maxwell, “A Dynamical Theory of the Electromagnetic Field”, 1865.
C. E. Shannon, “A (The) Mathematical Theory of Communication”, 1948.
Further Information: JSAC SI on “RIS-Assisted SREs”
136
RIS-Assisted SREs in IEEE-COMSOC
137
WTC & SPCC-TC
RIS-Assisted SREs in Europe (European Commission)
138
H2020-ICT ARIADNE (grant 871464, 6 million EUR) – Nov. 2019 - Oct. 2022
H2020-MSCA-EiD 5GSmartFact (grant 956670, 3.7 million EUR) – Mar. 2021 - Feb. 2025
H2020-MSCA-IF PathFinder (grant 891030, 185k EUR) – May 2021 – Apr. 2023
H2020-MSCA-ETN MetaWireless (grant 956256, 4.0 million EUR) – Dec. 2020 - Nov. 2024
H2020-ICT RISE-6G (grant 101017011, 6.5 million EUR) – Jan. 2021 – Dec. 2023
Thank You For Having Me… Appreciated… ICT-ARIADNE (H2020, 5G-PPP, grant 871464)
November 1st, 2019 – October 31st, 2022
A collaborative research project on RISs & AIFrom 2021: PathFinder (IF), 5GSmartFact (EiD), MetaWireless (ETN), RISE-6G (ICT-52)
Marco Di Renzo, Ph.D., H.D.R.Directeur de Recherche CNRS (CNRS Professor)Highly Cited Researcher, Web of Science (2019)IEEE Fellow, IEEE Communications Society (USA)IET Fellow, Institution of Engineering and Technology (UK)Editor-in-Chief, IEEE Communications LettersDistinguished Lecturer, IEEE Communications SocietyDistinguished Lecturer, IEEE Vehicular Technol. SocietyNokia Foundation Visiting Professor, Aalto Univ., Finland
Paris-Saclay UniversityLaboratory of Signals and Systems (L2S)CNRS and CentraleSupelec
E-Mail: marco.di-renzo@universite-paris-saclay.fr
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