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Reconfigurable Intelligent Surface: Energy Efficiency andIntelligent Configuration in Wireless Communication
Chongwen Huang1, Alessio Zappone3, George C. Alexandropoulos2,Merouane Debbah2,3, and Chau Yuen1
1Singapore University of Technology and Design, Singapore2Mathematical and Algorithmic Sciences Lab,
Huawei Technologies France SASU3CentraleSupelec, Universite Paris-Saclay, France
IEEE VTS and Comsoc Joint Workshop on 6G
SUTD, Apr. 24, 2019
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 1 / 34
. . . . . .
Outline
...1 Introduction & Background
Introduction
Background
Application Scenarios
...2 Recent Research Results
Reconfigurable Intelligent Surfaces (RIS) for Energy Efficiency inWireless Networks (TWC Under third reviewing)
Achievable Rate Maximization By Passive Intelligent Mirrors (ICASSP,Apr. 2018, Calgary, Alberta, Canada)
Low Resolution Reconfigurable Intelligent Surfaces (Goblecom Dec.2018, Abu Dhabi, UAE)
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 2 / 34
. . . . . .
Outline
...1 Introduction & Background
Introduction
Background
Application Scenarios
...2 Recent Research Results
Reconfigurable Intelligent Surfaces (RIS) for Energy Efficiency inWireless Networks (TWC Under third reviewing)
Achievable Rate Maximization By Passive Intelligent Mirrors (ICASSP,Apr. 2018, Calgary, Alberta, Canada)
Low Resolution Reconfigurable Intelligent Surfaces (Goblecom Dec.2018, Abu Dhabi, UAE)
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 3 / 34
. . . . . .
Introduction & Background
5G Use Cases
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 4 / 34
. . . . . .
Introduction & Background
A Vision of Beyond 5G Communication
Figure: Source: A Speculative Study on 6G, https://arxiv.org/abs/1902.06700.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 5 / 34
. . . . . .
Introduction & Background
Concerns for Beyond 5G (Post-5G and 6G) Communication
Tbps throughput per connection.
Centimeter level localization.
Latency in the order of nanoseconds.
Increased Energy Efficiency (EE).
Intelligent algorithms in all network layers: learn, predict, and adapt.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 6 / 34
. . . . . .
Introduction & Background
.What’s Reconfigurable Intelligent Surfaces (RIS)?..
......
RIS: Man-made surface composed of many small-unit reflectors equipped withsimple low-cost sensors and a cognitive enginea b.
Capability of soft controlling each of the units, which can effectively produce moreflexible manipulation of impinging electromagnetic field, such as polarization,scattering, focusing reflection control, absorbing, etc . c.
aHu et al., “The potential of using large antenna arrays on intelligent surfaces,”in 2017 IEEE 85th VTC
Spring, June 2017, pp. 1–6.bHum et al., “Reconfigurable reflect arrays and array lenses for dynamic antenna beam Control: A review,”
IEEE TAP, 2014.cH. Yang, et al., “A programmable metasurface with dynamic polarization, scattering and focusing control”.
Scientific reports, 6, 35692, 2016.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 7 / 34
. . . . . .
Introduction & Background
1
Figure: The programming and control of impinging electromagnetic field, such aspolarization, scattering control, focusing reflection control.
1H. Yang, et al., “A programmable metasurface with dynamic polarization, scattering and focusing control”.
Scientific reports, 6, 35692, 2016.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 8 / 34
. . . . . .
Background 2 (1/2)
Currently, Mostimplementation by 2Dmaterials (Meta-surface)
Example: 0.4m2 and 1.5mmthickness surface consisting of102 controllable cells andoperating at 2.47GHz.
Each unit cell is a rectangularpatch sitting on a ground planeand offering binary phasemodulation.
2Kaina et al., ‘Shaping complex microwave fields in reverberating media with binary tunable metasurfaces,”
Scientific Reports, 2014.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 9 / 34
. . . . . .
Background (2/2)
.Key RIS Features..
......
...1 Passive (nearly): No need any dedicated energy source
...2 Can be contiguous surface: Ideally, each point can reflect
...3 No receiver noise: due to no ADCs/DACs and Amplifier
...4 Soft programming: Ideally, each point of surface can be reconfigured
...5 Full-band response (Ideally): due to the reconfigurable; can work at anyoperating frequency wave
...6 Easily deployment: buildings facades,factory ceilings, human clothing, etc.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 10 / 34
. . . . . .
Application Scenarios-Outdoor
Figure: Outdoor wireless network operation (a) Current network (b) Smart network(O1, O2 and O3 coated with RIS).
Notes: The objects O1, O2, O3 are now coated with reconfigurablemeta-surfaces that modify the radio waves according to the generalizedlaws of reflection and refraction.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 11 / 34
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Application Scenarios-Indoor
Figure: (a) Without RIS Wall, (b) With RIS Wall
Notes: (a) the signal experiences path loss and multi-path fading andhardly reaches the target user. Whereas in (b), the signal propagation canbe reconfigured by RIS coated in the surfaces so that the signal is directedtowards the target user.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 12 / 34
. . . . . .
Outline
...1 Introduction & Background
Introduction
Background
Application Scenarios
...2 Recent Research Results
Reconfigurable Intelligent Surfaces for Energy Efficiency in WirelessNetworks (TWC Under third reviewing) 3
Achievable Rate Maximization By Passive Intelligent Mirrors (ICASSP,Apr. 2018, Calgary, Alberta, Canada)
Low Resolution Reconfigurable Intelligent Surfaces (Goblecom Dec.2018, Abu Dhabi, UAE)
3Chongwen Huang, Alessio Zappone, George C. Alexandropoulos, Merouane Debbah and Chau Yuen,
“Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Networks” Submitted to the IEEETransactions on Wireless Communications
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 13 / 34
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System Model
Large Intelligent Surface (LIS)
Base station
User
User
User
Reflecting Element
ͳ
ܭ
Figure: The considered RIS-basedmulti-user MISO system comprising ofa M-antenna base station serving in thedownlink K single-antenna users. RIS isassumed to be attached to asurrounding building’s facade.
The received signal at the k-thmobile user
yk = h2,kΦH1x+ nk ,
where:
h2,k ∈ C1×N represents thechannel between RIS and thek-th mobile user.H1 ∈ CN×M for the channelbetween BS and RIS.Φ , diag[ϕ1, ϕ2, . . . , ϕN ] is adiagonal matrix including theeffective phase shiftingvalues ϕn ∀n = 1, 2, . . . ,Nfor all RIS elements.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 14 / 34
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Problem Formulation.Objective..
......
Jointly optimal design of the RIS phase shifting matrix and the transmitpower allocation matrix by maximizing the EE under QoS constraints.
.Problem Formulation..
......
maxΦ,P
∑Kk=1 log2
(1 + pkσ
−2)
ξ∑K
k=1 pk + PBS + KPUE + NPn(b)(1a)
s.t. log2(1 + pkσ
−2)≥ Rmin,k ∀k = 1, 2, . . . ,K , (1b)
tr((H2ΦH1)+P(H2ΦH1)
+H) ≤ Pmax, (1c)
|ϕn| = 1 ∀n = 1, 2, . . . ,N, (1d)
Problem (4) is non-convex; and
Optimizing Φ is challenging due to the its discrete nature.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 15 / 34
. . . . . .
Proposed Solution (1/3)
Alternating optimization:
Optimization with respect to Φ
minΦ
tr((H2ΦH1)+P(H2ΦH1)
+H) (2a)
s.t. |ϕn| = 1 ∀n = 1, 2, . . . ,N (2b)
Using Sequential Fractional Programming, (4) will becomes
maxy
2Re(yH(λmaxIN2 − A)y(t)) (3a)
s.t. |yi | = 1 , ∀i = (j − 1)N + j , j = 1, 2, . . . ,N, (3b)
yi = 0 , ∀i = (j − 1)N + j , j = 1, 2, . . . ,N. (3c)
where y = vec(Φ−1) , A , (H+H2 ⊗H+
1 )H(H
+H2 ⊗H+
1 ) ∈ CN2×N2.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 16 / 34
. . . . . .
Proposed Solution (2/3)Alternating optimization:
Optimization with respect to Φ
minΦ
tr((H2ΦH1)+P(H2ΦH1)
+H) (4a)
s.t. |ϕn| = 1 ∀n = 1, 2, . . . ,N (4b)
Using Gradient Descent Approach, (4) will becomes
vec(Θ)(t+1) = vec(Θ)(t) + µd(t), (5)
y(t+1) = e jvec(Θ)(t+1) ◦ vec(IN) = y(t) ◦ e jµd(t) , (6)
d(t+1) = −q(t+1) +(q(t+1) − q(t))Tq(t+1)
∥q(t)∥2d(t), (7)
q(t) , ∇Θ
((y(t))HAy(t)
).
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 17 / 34
. . . . . .
Proposed Solution (3/3)
Alternating optimization:
Optimization with respect to P
maxP
∑Kk=1 log2
(1 + pkσ
−2)
ξ∑K
k=1 pk + PBS + KPUE + NPn(b)(8a)
s.t. pk ≥ σ2(2Rmin,k − 1), ∀k = 1, 2, . . . ,K , (8b)
tr((H2ΦH1)+P(H2ΦH1)
+H) ≤ Pmax. (8c)
For fixed Φ, the numerator of (13a) is concave in P, globally solvedwith limited complexity using Dinkelbach’s algorithm.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 18 / 34
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Simulation Results
Figure: The simulated RIS-based K -user MISO communication scenariocomprising of a M-antenna base station and a N-element intelligent surface.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 19 / 34
. . . . . .
Simulation Results
Figure: Average EE using either RIS orAF relay versus Pmax forRmin = 0bps/Hz.
Particularly, the EE of theRIS-based system is 300%larger than that of the onebased on the AF relay.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 20 / 34
. . . . . .
Simulation Results
-20 -10 0 10 20 30 400
50
100
150
Figure: Average EE using RIS versusPmax for M = 32, K = 16, and N = 16using: a) EE maximization forRmin = {0, 0.2R}; b) full powerallocation; and c)sum ratemaximization.
all designs perform similarly forPmax ≤ 15dBm, whichindicates that the EE and SEobjectives are nearly equivalentfor such transmit power levels.
using full BS transmit powerfor low Pmax is optimal.
for Pmax > 15dBm, the SEmaximization design naturallyincreases the SE, but leads todecreasing EE.
EE is maximized subject toQoS,the excess transmit poweris used in order to fulfill thethose constraints, but reducethe EE.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 21 / 34
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Simulation Results
Figure: Average sum rate using RISversus N for SNR = 20dB, M = 64,K = 64 and Rmin = 2bps/Hz with bothour presented algorithms as well asexhaustive global optimization.
both proposed algorithms yieldvery similar performance curvesthat are quite close to the onesobtained from the globaloptimization.
larger the N value is, the largeris the achievable SE.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 22 / 34
. . . . . .
Simulation Results
0 10 20 30 40 50100
110
120
130
140
150
160
170
Figure: Average EE using RIS versus Nfor SNR = −10dB andRmin = 0bps/Hz,
when N is quite small, alldesigns exhibit the same trend.
large N to observe EEdecreasing, this behavior seemsnot to happen forPn(b) = 0.01dBm due to smallPn(b).
an optimal trade-off existsbetween the rate benefit ofdeploying larger and larger RISstructure and its correspondingenergy consumption cost.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 23 / 34
. . . . . .
Outline
...1 Introduction & Background
Introduction
Background
Application Scenarios
...2 Recent Research Results
Reconfigurable Intelligent Surfaces for Energy Efficiency in WirelessNetworks (TWC Under third reviewing)
Achievable Rate Maximization By Passive Intelligent Mirrors (ICASSP,Apr. 2018, Calgary, Alberta, Canada)
Low Resolution Reconfigurable Intelligent Surfaces (Goblecom Dec.2018, Abu Dhabi, UAE) 4
4Chongwen Huang, George C.Alexandropoulos, Alessio Zappone, Merouane Debbah and Chau Yuen, “Energy
Efficient Multi-User MISO Communication using Low Resolution Reconfigurable Intelligent Surfaces” IEEEGLOBECOM, Abu Dhabi, UAE, 2018.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 24 / 34
. . . . . .
Simulation Results
Large Intelligent Surface (LIS)
Base station
User
User
Direct signal path
User
Low resolution
antenna element
ଵǡܐͳ
ܭ
Figure: RIS-assisted multi-user MISOcommunication comprising of a M-antennabase station simultaneously serving in thedownlink K single-antenna users
The received signal at the k-thmobile user
yk = (h2,kΦH1 + h1,k) x+ nk ,
where: h1,k ∈ C1×M the directchannel between BS and thek-th mobile user.
Phase shifting value (finiteresolution) for the n-thelement:
ϕn ∈ F ,{exp
(j2πm
2b
)}2b−1
m=0
.
(9)
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 25 / 34
. . . . . .
Proposed Joint Design Formulation
EE maximization problem is given:
maxΦ,P
∑Kk=1 log2
(1 + pk
σ2
)∑Kk=1 µkpk + KPc + NPn(b)
(10a)
s.t. log2
(1 +
pkσ2
)≥ Rmin,k ∀k = 1, 2, . . . ,K , (10b)
tr((H2ΦH1 +H)+P((H2ΦH1 +H)+)H) ≤ P , (10c)
ϕn ∈ F = {1, e j21−bπ, . . . , e j2π(2b−1)/2b}, b = 1, 2, . . .
∀n = 1, 2, . . . ,N. (10d)
Challenges:
(10) is non-convex; andOptimizing Φ is challenging due to the its discrete nature.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 26 / 34
. . . . . .
Proposed Joint Design (1/4).Solution Approach..
......
Employ alternating optimization to separately and iteratively solve formatrices P and Φ..RIS with 1-bit Phase Resolution..
......
First, optimization with respect to Φ:
minΦ
tr((H2ΦH1 +H)+P((H2ΦH1 +H)+)H) (11a)
s.t. θn = {0, π} ∀n = 1, 2, . . . ,N. (11b)
Still non-convex!
Proposed Solution: Relax the θn: constraint as
0 ≤ θn ≤ 2π.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 27 / 34
. . . . . .
Proposed Joint Design (2/4)
.RIS with 1-bit Phase Resolution..
......
Optimization with respect to Φ:
minΦ
tr((H2ΦH1 +H)+P((H2ΦH1 +H)+)H) (12a)
s.t. 0 ≤ θn ≤ 2π ∀n = 1, 2, . . . ,N. (12b)
Convex! Leveraging the function fmincon in MATLAB
Approximated solution
θn = 0: When 3π2 ≤ θn < 2π and 0 ≤ θn < π
2 .θn = π: When π
2 ≤ θn < 3π2 .
Low Complexity approach!
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 28 / 34
. . . . . .
Proposed Joint Design (3/4)
.RIS with 1-bit Phase Resolution..
......
Optimization with respect to P:
maxP
∑Kk=1 log2
(1 + pk
σ2
)∑Kk=1 µkpk + KPc + NPn(1)
(13a)
s.t. pk ≥ σ2(2Rmin,k − 1) ∀k = 1, 2, . . . ,K , (13b)
tr((H2ΦH1 +H)+P((H2ΦH1 +H)+)H) ≤ P . (13c)
Convex!Problem (13) can be globally solved with limited complexity usingDinkelbach’s methoda.
aDinkelbach, “On nonlinear fractional programming,” Manag. Science, 1967.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 29 / 34
. . . . . .
Proposed Joint Design (4/4).RIS with Finite Phase Resolution Elements..
......
2-bit resolution case:
minΦ
tr((H2ΦH1 +H)+P((H2ΦH1 +H)+)H) (14a)
s.t. θn = {0, π2, π,
3π
2} ∀n = 1, 2, . . . ,N. (14b)
Similar with One-bit!
Approximated solution
θn = 0: When 0 ≤ θn < π4 and 7π
4 ≤ θn < 2π.θn = π
2 : When π4 ≤ θn < 3π
4 .θn = π: When 3π
4 ≤ θn < 5π4 .
θn = 3π2 : Otherwise.
Similarly, it can be extended to other finite phase resolution.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 30 / 34
. . . . . .
Simulation Results
Figure: The simulated RIS-assisted K -user MISO communication scenariocomprising of a M-antenna base station and a N-element intelligent surface.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 31 / 34
. . . . . .
Simulation Results: Globecom Dec. 2018 (1)
-20 -15 -10 -5 0 5 10 15 20 25 3060
80
100
120
140
160
180
200
220
240
260
280
Infinite resolution exhaustive search
1-bit resolution exhaustive search
Proposed with 1-bit resolution
Proposed with 2-bit resolution
Amplify-and-forward relay
Figure: Achievable sum rate vs thetransmit SNR for K = 16, M = 12,N = 32, and Rmin,k = log2(1 +
SNR2K )
bps/Hz ∀k = 1, 2, . . . , 16.
2-bit phase resolution performsquite close to the infinite one.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 32 / 34
. . . . . .
Simulation Results: Globecom Dec. 2018 (2)
-10 -5 0 5 10 15 20 25 30 35 400
20
40
60
80
100
120
140
160
180
Infinite resolution exhaustive search
1-bit resolution exhaustive search
Proposed with 1-bit resolution
Proposed with 2-bit resolution
Amplify-and-forward relay
Figure: Energy efficiency maximizationvs the total BS transmit power P forK = 16, M = 12, N = 32, andRmin,k = 0 bps/Hz ∀k = 1, 2, . . . , 16.
The two low resolution casesresult in the highest EE.
Up to 45% Higher EE than therelay-assisted case.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 33 / 34
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Simulation Results: ICASSP Apr. 2018
-10 -5 0 5 10 15 20 25 300
20
40
60
80
100
120
140
160
180
200
Fig. R2.2. The average SE
comparison of the proposed
RIS system with no RIS
system. a) M = 32,K = 16,
N = 16; b) K = 8, M = 8,
N = 8.
The proposed methodapproaches the optimal.
With RIS, there are huge gainthan that of without RIS.
C. Huang, et al. () Communication via Intelligent Surfaces SUTD, Apr. 24, 2019 34 / 34