ArticlePDF Available

Article

# Reconfigurable Intelligent Surface-Based Wireless Communications: Antenna Design, Prototyping, and Experimental Results

## Abstract and Figures

One of the key enablers of future wireless communications is constituted by massive multiple-input multiple-output (MIMO) systems, which can improve the spectral efficiency by orders of magnitude. In existing massive MIMO systems, however, conventional phased arrays are used for beamforming. This method results in excessive power consumption and high hardware costs. Recently, reconfigurable intelligent surface (RIS) has been considered as one of the revolutionary technologies to enable energy-efficient and smart wireless communications, which is a two-dimensional structure with a large number of passive elements. In this paper, we develop a new type of high-gain yet low-cost RIS that bears 256 elements. The proposed RIS combines the functions of phase shift and radiation together on an electromagnetic surface, where positive intrinsic-negative (PIN) diodes are used to realize 2-bit phase shifting for beamforming. This radical design forms the basis for the world’s first wireless communication prototype using RIS having 256 two-bit elements. The prototype consists of modular hardware and flexible software that encompass the following: the hosts for parameter setting and data exchange, the universal software radio peripherals (USRPs) for baseband and radio frequency (RF) signal processing, as well as the RIS for signal transmission and reception. Our performance evaluation confirms the feasibility and efficiency of RISs in wireless communications. We show that, at 2.3 GHz, the proposed RIS can achieve a 21.7 dBi antenna gain. At the millimeter wave (mmWave) frequency, that is, 28.5 GHz, it attains a 19.1 dBi antenna gain. Furthermore, it has been shown that the RIS-based wireless communication prototype developed is capable of significantly reducing the power consumption.<br/
Content may be subject to copyright.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2977772, IEEE Access
Date of publication xxxx 00, 0000, date of current version xxxx 00, 0000.
Digital Object Identiﬁer xx.xxxx/ACCESS.2019.DOI
Reconﬁgurable Intelligent
Surface-Based Wireless
Communications: Antenna Design,
Prototyping, and Experimental Results
LINGLONG DAI1, BICHAI WANG1, MIN WANG1, XUE YANG1, JINGBO TAN1,
SHUANGKAISHENG BI1, SHENHENG XU1, FAN YANG1, ZHI CHEN2, MARCO DI RENZO3,
CHAN-BYOUNG CHAE4, AND LAJOS HANZO5
1Beijing National Research Center for Information Science and Technology (BNRist) as well as the Department of Electronic Engineering, Tsinghua University,
Beijing 100084, China (E-mail: daill@tsinghua.edu.cn, wbc15@mails.tsinghua.edu.cn, wangm@cqupt.edu.cn, yangxue020961@163.com,
tanjb17@mails.tsinghua.edu.cn, bsks18@mails.tsinghua.edu.cn, shxu@tsinghua.edu.cn, fan_yang@tsinghua.edu.cn)
2The National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu 611731,
China (E-mail: chenzhi@uestc.edu.cn)
3Université Paris-Saclay, CNRS, CentraleSupélec, Laboratoire des Signaux et Systèmes, Gif-sur-Yvette, France (E-mail: marco.direnzo@centralesupelec.fr)
4School of Integrated Technology, Yonsei University, 03722 ,Korea (E-mail: cbchae@yonsei.ac.kr)
5Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, U.K. (E-mail: lh@ecs.soton.ac.uk)
Corresponding author: Shenheng Xu (e-mail: shxu@tsinghua.edu.cn).
This work was supported in part by the National Natural Science Foundation of China for Outstanding Young Scholars under Grant
61722109, in part by the National Natural Science Foundation of China under Grant 61571270, in part by the Royal Academy of
Engineering under the U.K.-China Industry Academia Partnership Programme Scheme under Grant U.K.-CIAPP\49, in part by the
National Key R&D Program of China under Grant 2018YFB1801500, in part by the IITP by the Korea government (MSIP) (2019-0-00685
and 2016-11-1719), in part by the European Commission through the H2020 ARIADNE project under grant 871464, and in part by the
Engineering and Physical Sciences Research Council projects EP/Noo4558/1, EP/PO34284/1, COALESCE, of the Royal Society’s Global
Challenges Research Fund Grant as well as of the European Research Council’s Advanced Fellow Grant QuantCom.
ABSTRACT One of the key enablers of future wireless communications is constituted by massive
multiple-input multiple-output (MIMO) systems, which can improve the spectral efﬁciency by orders
of magnitude. In existing massive MIMO systems, however, conventional phased arrays are used for
beamforming. This method results in excessive power consumption and high hardware costs. Recently,
reconﬁgurable intelligent surface (RIS) has been considered as one of the revolutionary technologies to
enable energy-efﬁcient and smart wireless communications, which is a two-dimensional structure with a
large number of passive elements. In this paper, we develop a new type of high-gain yet low-cost RIS that
bears 256 elements. The proposed RIS combines the functions of phase shift and radiation together on
an electromagnetic surface, where positive intrinsic-negative (PIN) diodes are used to realize 2-bit phase
shifting for beamforming. This radical design forms the basis for the world’s ﬁrst wireless communication
prototype using RIS having 256 two-bit elements. The prototype consists of modular hardware and ﬂexible
software that encompass the following: the hosts for parameter setting and data exchange, the universal
software radio peripherals (USRPs) for baseband and radio frequency (RF) signal processing, as well as
the RIS for signal transmission and reception. Our performance evaluation conﬁrms the feasibility and
efﬁciency of RISs in wireless communications. We show that, at 2.3 GHz, the proposed RIS can achieve
a 21.7 dBi antenna gain. At the millimeter wave (mmWave) frequency, that is, 28.5 GHz, it attains a 19.1
dBi antenna gain. Furthermore, it has been shown that the RIS-based wireless communication prototype
developed is capable of signiﬁcantly reducing the power consumption.
INDEX TERMS Massive MIMO, prototype, reconﬁgurable intelligent surface (RIS), wireless communi-
cation.
VOLUME x, xxxx 1
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2977772, IEEE Access
L. Dai et al.: Reconﬁgurable Intelligent Surface-Based Wireless Communication
I. INTRODUCTION
MASSIVE multiple-input multiple-output (MIMO)
schemes constitute promising techniques for future
wireless communications. By relying on a large antenna
array, massive MIMO schemes provide a substantial power
gain and improve the spectral efﬁciency by orders of mag-
nitude [1] [2]. In existing massive MIMO systems, though,
conventional phased arrays are used for beamforming, and
this requires hundreds of high-resolution phase shifters and
complex feeding networks [3] [4]. The high power consump-
tion and hardware cost of these phase shifters and complex
feeding networks limit the antenna array scale in practical
massive MIMO systems. Hence, the potential advantages of
massive MIMO schemes cannot be fully realized.
There has recently emerged a promising alternative to the
traditional phased arrays– reconﬁgurable intelligent surfaces
(RISs) [5]–[13]. An RIS consists of a large number of nearly
passive elements with ultra-low power consumption. Each
element is capable of electronically controlling the phase
of the incident electromagnetic waves. It does so with un-
natural properties, such as, negative refraction, perfect ab-
sorption, and anomalous reﬂection [8], [12], [14]. Moreover,
the spatial feeding mechanism of RISs avoids the excessive
power loss caused by the bulky feeding networks of phased
arrays. Therefore, RISs signiﬁcantly reduce both the power
consumption and hardware cost. Albeit, to ensure the antenna
gain of the conventional phased arrays, it may be necessary
to install a larger number of antenna elements.
In [15], an analog design of RIS elements using varac-
tors has been proposed to provide continuous phase shift.
However, the response time of varactors is usually large,
and the phase accuracy is far from satisfaction due to the
analog control of varactors. To this end, RISs made of low-
resolution 1-bit elements have been widely investigated in
the literature [16]–[23]. Among them, the current reversal
mechanism has attracted extensive attention as a beneﬁt of
its phase response, which is near-constant across a wide
frequency band [21]–[23]. However, RISs with 1-bit ele-
ments can only provide two phase states, e.g., 0and π.
According to the theoretical analysis on the power loss of
using general b-bit elements in [24], 1-bit phase quantization
results in more than 3 dB antenna gain reduction due to the
signiﬁcant phase errors, and this result is also validated by
the experiment results in [25] and [26]. To mitigate the per-
formance degradation caused by the 1-bit phase quantization,
RISs with multi-bit elements can also be designed, though
at an increased system complexity and hardware cost. The
authors in [24] [25] showed that an RIS with 2-bit elements
strikes an attractive tradeoff between the performance and
complexity, as it has an acceptable antenna gain erosion of
about 1 dB caused by the 2-bit phase quantization [27].
However, only a couple of contributions may be found in the
literature on RISs with 2-bit elements [27]–[29]. Recently, a
novel dual linearly/circularly polarized RIS design with 2-bit
elements imposing a low magnitude loss has been proposed
in our previous 2-page conference report [30], where we have
designed an electronically controlled RIS with 2-bit elements
operating at 1.7 GHz. It is also worth mentioning that the RIS
elements in existing references can only response to single
linear polarization, while the proposed element design is
suitable for arbitrary polarization (dual linear, 45/135 linear,
or dual circular polarizations), provided a proper feeding and
transceiver system design. Hence, it can easily double the
channel capacity without using two separate large reﬂectar-
ray apertures.
It is in this context that we aim to achieve energy-efﬁcient
wireless communications by using RISs instead of conven-
tional phased arrays. We fabricate and measure an electron-
ically controlled RIS with 2-bit elements at 2.3 GHz and
28.5 GHz having, for the ﬁrst time, 16 ×16 elements. We
in fact design the world’s ﬁrst wireless communication pro-
totype using an RIS having 256 2-bit elements1. It should be
noted that the authors in [9] [10] developed a programmable
metasurface-based wireless transmission prototype. In their
prototype, the metasurface is used to modulate the signals
for transmission only. In the current work, though, the RIS
is used for beamforming both for transmission and reception.
As a result, the proposed RIS-based wireless communication
prototype is capable of servicing mobile users by real-time
beamforming. Speciﬁcally, the prototype designed consists
of modular hardware and ﬂexible software to realize the
wireless transceiver functions, including the hosts for param-
eter setting and data exchange, the universal software radio
peripherals (USRPs) for baseband and radio frequency (RF)
signal processing, as well as the RIS for signal transmission
and reception. The USRP at the transmitter ﬁrst performs
baseband signal processing, e.g., source coding, channel cod-
ing and orthogonal frequency division multiplexing (OFDM)
modulation. The RF signals output by the RF chains are
then transmitted via our RIS equipped with 256 2-bit ele-
antenna. To then recover the original signals, the USRP at
the receiver takes charge of both RF and baseband signal
processing. Additionally, except for the RIS-based wireless
communication prototype operating at 2.3 GHz, a prototype
operating at the millimeter wave (mmWave) frequency, i.e.,
28.5 GHz, is also developed3. Our performance evaluation
conﬁrms the feasibility and efﬁciency of RISs in wireless
communication systems for the ﬁrst time. More speciﬁcally,
it is shown that a 21.7 dBi antenna gain can be obtained by
the proposed RIS at 2.3 GHz, while at 28.5 GHz, a 19.1 dBi
antenna gain can be achieved. Furthermore, it has been shown
that the RIS-based wireless communication prototype de-
veloped signiﬁcantly reduces the power consumption, while
achieving similar or better performance in terms of effective
isotropic radiated power (EIRP), compared to conventional
1In this paper, the RIS is deployed at the transmitter [7] for performance
evaluation, which can also be used for intelligent reﬂection relay [6] [7].
2In this paper, a single RF chain is considered, which can be easily
extended to multiple RF chains.
3Two videos are provided to demonstrate the results in this paper:
http://oa.ee.tsinghua.edu.cn/dailinglong/research/research.html.
2VOLUME x, xxxx
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2977772, IEEE Access
L. Dai et al.: Reconﬁgurable Intelligent Surface-Based Wireless Communication
(a)
(b)
FIGURE 1. Structure of the proposed 2-bit RIS element: (a) exploded view;
(b) detailed view of the slot-loaded plane.
phased array-based wireless communications.
The rest of this paper is organized as follows. The basic
principles and implementation details of the RIS having 256
2-bit elements are introduced in Section II. The RIS-based
wireless communication prototype designed is described in
Section III. Section IV shows the experimental results. Final-
ly, we offer our conclusions in Section V.
II. THE RIS WITH 2-BIT ELEMENTS
For high-quality antenna array design, it is crucial to accu-
rately control the aperture ﬁeld, especially the phase distri-
bution for electronically forming a sharp pencil beam. The
conventional phased array utilizes a phase shifter connected
to each antenna element in the array to directly control the
element’s complex excitation with a speciﬁc phase state.
The massive number of required phase shifters gives rise to
the high power consumption and excessive hardware cost
of conventional phased arrays. By contrast, the proposed
RIS with 2-bit elements simply employs positive intrinsic-
negative (PIN) diodes integrated in each element, which
modulate the RF currents induced in the antenna elements
upon their illumination by turning ON or OFF the PIN
diodes. Therefore, the RIS element becomes capable of re-
radiating an electromagnetic ﬁeld having a speciﬁc phase
state. Hence, the desired electronic phase control capability
is realized without using conventional phase shifters.
TABLE 1. PIN diode states for different element conﬁgurations.
Conﬁguration PIN1/PIN2 PIN3 PIN4 PIN5
1 ON/OFF ON
2 OFF/ON
3 ON/OFF OFF
4 OFF/ON
Configuration 1 Configuration 2 Configuration 3 Configuration 4
FIGURE 2. Illustrations of the RF current paths for four different element
conﬁgurations.
The most essential breakthrough in the proposed RIS with
2-bit elements is its novel antenna element structure. Note
that earlier publications on RIS with 2-bit elements only
provide some conceptual element design, or the fabrication
and measurement of single element [29]. This work presents
the world’s ﬁrst fully functional RIS with individual element
phase control. The designed element structure is simple,
which has only 5 PIN diodes and requires only 2 control
signals for each element. Moreover, the biasing circuit is
carefully designed to choke the RF leakage through the
bias lines, thus reducing the magnitude insertion loss. As an
outcome, high-efﬁciency beamforming capability is accom-
plished by the RIS with 2-bit elements in this work.
Speciﬁcally, as depicted in Fig. 1(a), each antenna element
consists of a square-shaped upper patch, a slot-loaded plane
energy, while the ground plane suppresses the back radiation
slot-loaded plane is the key component controlling the RIS’s
phase state. Its detailed structure is shown in Fig. 1(b).
Positioned symmetrically are four sets of slots, into which
ﬁve PIN diodes are integrated.
Ideally, a 2-bit RIS element provides four quantized phase
states with a 90phase increment. The PIN diode states are
appropriately combined to beneﬁcially control the RF current
paths and the resonant lengths of the slots. This combination
results in tunable phase shifts for the proposed RIS element
design. Speciﬁcally, Slots 1, 2 and 3 are arranged in a T-
shaped conﬁguration, being complemented by a dummy Slot
4 invoked for maintaining a symmetric element structure.
The states of PIN 1 and PIN 2 are alternatively turned ON
or OFF, so that the currents induced may be reversed in the
x-direction, corresponding to a 180phase shift. The other
3 PIN diodes are turned ON or OFF simultaneously so as
to change the resonant lengths of the slots, permitting the
attainment of an additional 90phase shift may be realized.
Hence, a 2-bit phase resolution can be obtained, resulting in
four different phase states.
VOLUME x, xxxx 3
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2977772, IEEE Access
L. Dai et al.: Reconﬁgurable Intelligent Surface-Based Wireless Communication
FIGURE 3. Layout of the DC bias network of the 2-bit RIS element.
TABLE 2. Simulated element performance at 2.3 GHZ.
Conﬁguration Phase Shift Magnitude Response
1205.51.1dB
2383.21.2dB
3290.20.8dB
4110.30.8dB
The PIN diode states of the four element conﬁgurations
are tabulated in TABLE I, and a graphic illustration of the
RF current paths is presented in Fig. 2. It should be pointed
out that the incident and re-radiated ﬁelds of each element are
orthogonally polarized due to the change of current direction-
s. Thanks to the symmetric element structure, the proposed
RIS element is capable of providing the same performance
both under an x- and a y-polarized incident wave. Hence it is
suitable for both dual-linearly and dual-circularly polarized
systems.
The proposed 2-bit RIS element operates in the S band
with a center frequency of 2.3 GHz4. The element spacing
is 50 mm. The upper patch has a size of 37 mm ×37 mm
and it is etched on a 1-mm thick FR4 substrate. The slot-
loaded plane is etched on another FR4 substrate, which is
placed 6 mm below the upper patch. The ground is made
of an aluminum sheet, placed 12 mm below the slot-loaded
plane.
The type of the commercial PIN diode is SMP1340-040LF
from Skyworks. The ON state of the PIN diode is modeled
as a series of R= 0.8 Ω lumped resistors and L= 780
pH inductors. The OFF state can be modeled as a series of
C= 202 fF lumped capacitors, R= 10 Ω resistors and
L= 780 pH inductors. The DC bias network of the element
is depicted in Fig. 3. The ﬁve PIN diodes are divided into two
groups, which are then independently controlled by a pair of
bias lines. The forward and reverse DC voltages are +0.9V
and 0.9V, respectively.
Shown in Fig. 4 are the simulated phase and magnitude
performances of the proposed 2-bit RIS element for four
element conﬁgurations. TABLE II summarizes the exact
values at 2.3 GHz. It can be observed that the four element
phase states clearly exhibit a 2-bit phase resolution with an
4For simplicity, we only provide details about the RIS at 2.3 GHz, since
the design philosophy at 28.5 GHz is the same.
(a)
(b)
FIGURE 4. Simulated performances of the proposed 2-bit RIS element: (a)
phase performance; (b) magnitude performance.
approximate phase increment of 90. These states remain
very stable within the frequency band of interest ranging
from 2 GHz to 2.6 GHz. The insertion magnitude loss is less
than 1.2 dB, which slightly deteriorates at higher frequencies
above 2.5 GHz. Because of the current reversal mechanism,
the magnitude responses of the element conﬁgurations 1 and
2 (or 3 and 4) are similar, while their phase shift difference
is approximately 180. These simulated results successfully
demonstrate the electronic phase shifting capability of the
proposed 2-bit RIS element without using phase shifters.
Fig. 5 shows the design and fabrication of the RIS bearing
16 ×16 2-bit elements. The size of the surface is 800
mm ×800 mm, and the distance between the primary feed
and the surface is 720 mm. Upon being illuminated by the
primary feed, these 16 ×16 elements can be dynamically
reconﬁgured to convert the spherical wavefront impinging
from the feed into a planar wavefront in the desired direction.
Hence, the designed RIS can produce a focused high-gain
beam that is capable of promptly switching its direction
within a two-dimensional ±60angular range. Fig. 6, as an
example, shows the phase shift distribution of the elements
4VOLUME x, xxxx
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2977772, IEEE Access
L. Dai et al.: Reconﬁgurable Intelligent Surface-Based Wireless Communication
FIGURE 5. Photograph of the fabricated RIS having 16 ×16 2-bit elements.
Element Number (x axis)
Element Number (y axis)
FIGURE 6. Phase shift distribution of the RIS elements for the broadside
beam. Note that 16 elements (appearing as white) are removed for wiring the
bias lines.
for the broadside beam, where 16 elements (labeled with
white color) are removed for wiring the bias lines. For practi-
cal realization, the research team designed an FPGA-based
beamforming control board, which provides 256 DC bias
signals for individually setting the conﬁguration of all 16×16
elements. We can also form a large variety of shaped beams
provided that the appropriate conﬁgurations of the elements
are determined using a phase-only synthesis process and are
then pre-loaded into the beamforming control board.
III. RIS-BASED WIRELESS COMMUNICATION
PROTOTYPE
The RIS-based wireless communication prototype designed
consists of modular hardware and ﬂexible software, which
collectively realize our end-to-end wireless communication
system, including baseband signal processing, RF transmis-
sion, and so forth.
As shown in Fig. 7, the hardware structure of the RIS-
based wireless communication prototype designed consists
FIGURE 7. The RIS-based wireless communication prototype.
of the base station side, including the transmitter host, the
USRP at the transmitter and the RIS having 256 2-bit ele-
ments. It also comprises the user side, including the receiver
At the base station side, a graphical interface is real-
ized at the transmitter host. The interface is responsible for
controlling the parameters at the transmitter, including the
carrier frequency, transmit power, modulation and encoding
modes, and more. The signals, then, are delivered to the
USRP at the transmitter via the transmitter host. Once the
signals from the transmitter host have been received, the
USRP at the transmitter carries out the signal processing,
which aims to transform the signals into a form suitable for
transmission in wireless channels. (Later in this section, we
introduce the detailed signal processing ﬂow.) After that, the
processed signals are forwarded to the RIS having 256 2-bit
elements. As discussed in Section II, by adjusting the states
of the PIN diodes to control the phase for each element,
a sharp directional beam can be generated by the RIS for
transmission to the user side.
At the user side, the contaminated signals are received
from the wireless channel, which are then processed by
charge of the signal processing for recovering the original
signals, which is basically the inverse process of those in the
USRP at the transmitter. Finally, the recovered signals and
the corresponding parameters, such as the received signal
power, constellation, bit-error-rate (BER), data rates and so
on, are displayed by the graphical interface at the receiver
host.
To elaborate a little further, observe in Fig. 8 that the USRP
at the transmitter consists of four modules– the embedded
processor, the high-speed FPGA processor, the digital-to-
analog (DA) module and the RF module [31]. The embedded
processor and the high-speed FPGA processor jointly carry
out the baseband signal processing. The embedded processor
handles the media access control (MAC) layer process, such
as data framing. The high-speed FPGA module handles the
physical layer signal processing, such as channel coding and
VOLUME x, xxxx 5
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2977772, IEEE Access
L. Dai et al.: Reconﬁgurable Intelligent Surface-Based Wireless Communication
FIGURE 9. Signal processing ﬂow.
FIGURE 8. The hardware modules of USRP.
orthogonal frequency division multiplexing (OFDM) mod-
ulation. The DA module is used for the digital-to-analog
conversion (DAC) of the digital signals output by the FPGA
processor. The RF module takes care of the up-conversion
required for RF signal transmission. Similarly, the USRP at
the receiver also consists of four modules: the embedded
processor, the high-speed FPGA processor, the analog-to-
digital (AD) module and the RF module. The baseband signal
processing at the receiver is the inverse procedure of that at
the transmitter. The AD module is used for analog-to-digital
conversion (ADC) of the analog signals obtained by down-
conversion. Finally, the down-conversion of the received RF
signal is realized by the RF module.
In our prototype, the baseband signal processing procedure
follows the LTE standard relying on frequency division du-
plex (FDD) [32]–[34], and is implemented by a high-speed
FPGA processor as part of the USRP with the aid of graphical
programming.
Speciﬁcally, the signal processing ﬂow of the system is
shown in Fig. 9. The signals can be obtained from diverse
data sources, such as text, images, videos and so on. To
achieve efﬁcient and robust wireless communications, a se-
ries of signal precessing operations have to be carried out.
Firstly, the input signals are transferred to the encoder,
including source encoding and channel encoding. The former
is performed to reduce redundancy inherent in the multime-
dia input signals, facilitating more efﬁcient transmission. The
latter is performed to combat the channel-induced impair-
ments by correcting the transmission errors. After that, bit-
interleaving is applied to disperse the burst errors into ran-
dom errors, thus improving the channel coding performance,
especially for channels with memory. The interleaved bits are
then mapped to symbols according to the modulation modes,
such as phase shift keying (PSK) or quadrature amplitude
modulation (QAM). Here the different modulation modes
will result in different data rates, depending on the number
of bits/symbol.
As can be seen in Fig. 9, OFDM is adopted for wideband
transmission over dispersive channels. In this regard, after
adding the pilots and virtual subcarriers, the serial stream
of symbols is converted serial-to-parallel and mapped to
the frequency-domain OFDM subcarriers. The frequency-
domain OFDM symbols are transformed to the time-domain
by the inverse fast fourier transform (IFFT). After con-
catenating the cyclic preﬁx (CP), the OFDM symbols are
converted to the serially transmitted time-domain signals.
Following this, the serially transmitted signals are forwarded
to the DAC module and to the up-conversion module, and
ﬁnally are transmitted via the RIS.
The receiver basically carries out the inverse process of
the transmitter, where the synchronization signals and the
pilots are utilized for timing/frequency synchronization and
channel estimation. Finally, the estimated channel will be
used for signal detection.
6VOLUME x, xxxx
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2977772, IEEE Access
L. Dai et al.: Reconﬁgurable Intelligent Surface-Based Wireless Communication
FIGURE 10. The compact range anechoic chamber of size 20 m ×10 m ×
10 m.
The above signal processing ﬂow is controlled by the
software system. By changing the system parameters, such
as the transmit power, coding modes, modulation modes, and
so on, various transmission modes can be activated according
to speciﬁc scenarios and requirements.
IV. EXPERIMENTAL RESULTS
The constructed RIS with 2-bit elements is measured using
the compact anechoic chamber as shown in Fig. 10. The
chamber, measuring 20 m ×10 m ×10 m was build in
Tsinghua University. Fig. 11(a) shows the normalized mea-
frequency of 2.3 GHz. A high-gain pencil beam is formed
by controlling the phase shifts of the 2-bit RIS elements. The
half-power beamwidths are 9.1and 8.8in the two principal
planes, respectively, and the measured sidelobe levels are
16.7dB and 16.4dB. The measured antenna gains within
the frequency band of interest are plotted in Fig. 11(b). At 2.3
GHz, the measured gain is 21.7 dBi, which corresponds to
an aperture efﬁciency of 31.3%. The measured gain reaches
its maximum of 21.9 dBi at 2.4 GHz, and the 1-dB gain
bandwidth is 350 MHz, which is equivalent to 15.2% at the
design frequency of 2.3 GHz.
The beams scanned from 0to 60can be readily obtained
with the help of our beamforming control board. Plotted
in Fig. 12 are the measured radiation patterns, normalized
to the gain of the broadside beam. As the scanning angle
(a)
(b)
FIGURE 11. Measured performance of the broadside beam: (a) Normalized
radiation patterns at 2.3 GHz; (b) Antenna gains within the frequency band of
interest (from 2 GHz to 2.6 GHz).
FIGURE 12. Measured radiation patterns of the scanned beams. They are
normalized to the measured gain of the broadside beam.
increases, the measured gain decreases and the main beam
broadens. When the scanning angle is 60, the measured
gain is 18.0 dBi, and the scanning gain reduction is only 3.7
dB. These measured results successfully verify the ﬂexible
wide-angle beam-scanning capability of the proposed RIS
with 2-bit elements. Note that to achieve a 21.7 dBi antenna
VOLUME x, xxxx 7
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2977772, IEEE Access
L. Dai et al.: Reconﬁgurable Intelligent Surface-Based Wireless Communication
FIGURE 13. The constructed RIS-based prototype at 2.3 GHz: (a) transmitter;
gain, the conventional phased array requires 64 elements.
Considering the same total radiated power of 64 W, the
power consumption of the RIS is about 153 W, while that
of the conventional phased array is about 370 W. In this
case, the proposed RIS can reduce the power consumption
by 58.6%, while achieving similar performance in terms of
EIRP, compared to the conventional phased array.
Based on the proposed RIS with 2-bit elements, we con-
struct the transmitter and receiver of the RIS-based wireless
communication prototype shown in Fig. 13(a) and Fig. 13(b),
respectively. The over-the-air (OTA) test environment is in-
door, and the distance between the transmitter and receiver is
FIGURE 14. The constructed RIS-based prototype at 28.5 GHz: (a) the RIS
operating at 28.5 GHz; (b) transmitter; (c) receiver.
20 meters. High-deﬁnition virtual reality (VR) video streams
captured by a stereoscopic camera is used as the data source
in the RIS-based wireless communication prototype for real-
time demonstration.
The parameters of the test are listed as follows: 1) The res-
olution of the VR camera is 3920 ×1440, and the frame rate
is 30; 2) The carrier frequency of OFDM modulation is 2.3
GHz, and the number of subcarriers is 1200; 3) A variety of
modulation modes are available, including QPSK, 16QAM,
64QAM, etc, and Turbo encoding is used in conjunction with
diverse code rates. Fig. 13(c) shows the graphical interface
at the receiver side when we transmit the real-time VR
8VOLUME x, xxxx
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2977772, IEEE Access
L. Dai et al.: Reconﬁgurable Intelligent Surface-Based Wireless Communication
video using 64 QAM symbols. In the graphical interface, the
important parameters are displayed in real time, including
the received spectrum, constellation, signal power, data rate,
and so forth. We can see that the received 64 QAM symbols
can be clearly separated, and our prototype supports the real-
time transmission of high-deﬁnition VR video. Finally, we
veriﬁed that the EIRP of the RIS with 2-bit elements-based
wireless communication prototype developed is 51.7 dBm if
the transmitted power is 30 dBm. This is a 2 dB gain over
the RIS with 1-bit elements-based wireless communication
systems [26].
We also constructed, as shown in Fig. 14, an RIS-based
wireless communication prototype at 28.5 GHz. Fig. 14(a)
shows the designed RIS operating at 28.5 GHz, the measured
gain of which is 19.1 dBi, while the transmitter and receiver
are shown in Fig. 14(b) as well as Fig. 14(c).
V. CONCLUSION
In this paper, we have proposed, constructed and measured
a RIS having 256 2-bit elements. Our prototype signiﬁcant-
ly reduced the power consumption and hardware cost of
the conventional phased arrays. We have indeed designed
the world’s ﬁrst RIS-based wireless communication proto-
type for supporting energy-efﬁcient wireless communication-
s. The prototype consists of modular hardware and ﬂexi-
ble software, encompassing the hosts for parameter setting
and data exchange, the USRPs for baseband and RF signal
processing, as well as the RIS for signal transmission and
reception. Our experimental evaluation has demonstrated the
feasibility and efﬁciency of RIS in wireless communications
for the ﬁrst time. The test results showed that the proposed
RIS at 2.3 GHz could obtain a 21.7 dBi antenna gain and
at 28.5 GHz, a 19.1 dBi antenna. Furthermore, it has been
shown that the proposed RIS-based wireless communication
system signiﬁcantly reduced the power consumption without
degrading EIRP performance. Our prototype will ﬁnd a wide
range of applications in the near future, such as wireless com-
munications in complex terrains (e.g., mountains, snowﬁelds,
deserts and offshore areas), high-speed air-to-ground and air-
to-air data transmission, deep space communication, near-
earth satellite communication, mobile hotspot coverage, and
more. Our future work will consider nano-hole lens based
RIS for mmWave and sub-THz spectrums [35] [36].
REFERENCES
[1] S. Mumtaz, J. Rodriquez, and L. Dai, MmWave Massive MIMO: A
2016.
[2] F. Rusek, D. Persson, B. K. Lau, E. G. Larsson, T. L. Marzetta, O. Edfors,
and F. Tufvesson, “Scaling up MIMO: Opportunities and challenges with
very large arrays,” IEEE Signal Process. Mag., vol. 30, no. 1, pp. 40-60,
Jan. 2013.
[3] E. Bj¨ornson, E. G. Larsson, and T. L. Marzetta, “Massive MIMO: Ten
myths and one critical question,” IEEE Commun. Mag., vol. 54, no. 2, pp.
114-123, Feb. 2016.
[4] X. Gao, L. Dai, and A. M. Sayeed, “Low RF-complexity technologies to
enable millimeter-wave MIMO with large antenna array for 5G wireless
communications,” IEEE Commun. Mag., vol. 56, no. 4, pp. 211-217, Apr.
2018.
[5] M. Di Renzo, M. Debbah, D.-T. Phan-Huy, et al., “Smart radio environ-
time has come,” EURASIP J. Wirel. Commun. Netw., vol. 2019, no. 129,
pp. 1-20, Mar. 2019.
[6] E. Basar, M. D. Renzo, J. D. Rosny, M. Debbah, M.-S. Alouini, and
R. Zhang, “Wireless communications through reconﬁgurable intelligent
surfaces,” IEEE Access, vol. 7, pp. 116753-116773, Aug. 2019.
[7] K. Ntontin, M. D. Renzo, J. Song, F. Lazarakis, J. D. Rosny, D.-T.
Phan-Huy, O. Simeone, R. Zhang, M. Debbah, G. Lerosey, M. Fink,
S. Tretyakov, and S. Shamai, “Reconﬁgurable intelligent surfaces vs.
relaying: Differences, similarities, and performance comparison,” arXiv
preprint arXiv:1908.08747, Aug. 2019.
[8] Y.-C. Liang, R. Long, Q. Zhang, J. Chen, H. V. Cheng, and H. Guo, “Large
intelligent surface / antennas (LISA): Making reﬂective radios smart,
arXiv preprint arXiv:1906.06578, Jul. 2019.
[9] W. Tang, X. Li, J. Y. Dai, S. Jin, Y. Zeng, Q. Cheng, and T. J. Cui, “Wireless
communications with programmable metasurface: Transceiver design and
experimental results,” China Commun., vol. 16, no. 5, pp. 46-61, May
2019.
[10] W. Tang, M. Z. Chen, J. Y. Dai, Y. Zeng, X. Zhao, S. Jin, Q. Cheng, and T.
J. Cui, “Wireless communications with programmable metasurface: New
paradigms, opportunities, and challenges on transceiver design,” arXiv
preprint arXiv:1907.01956, Jul. 2019.
[11] P. Nayeri, F. Yang, and A. Elsherbeni, “Beam scanning reﬂectarray anten-
nas: A technical overview and state of the art,” IEEE Antennas Propag.
Mag., vol. 57, no. 4, pp. 32-47, Aug. 2015.
[12] J. Zhao, “Optimizations with intelligent reﬂecting surfaces (IRSs) in 6G
wireless networks: Power control, quality of service, max-min fair beam-
forming for unicast, broadcast, and multicast with multi-antenna mobile
users and multiple IRSs,” arXiv preprint arXiv:1908.03965, Aug. 2019.
[13] C. Hu and L. Dai, “Two-timescale channel estimation for reconﬁgurable
intelligent surface aided wireless communications,” arXiv preprint arX-
iv:1912.07990, Dec. 2019.
[14] H. Yang, F. Yang, S. Xu, Y. Mao, M. Li, X. Cao, and J. Gao, “A 1-bit
10 ×10 reconﬁgurable reﬂectarray antenna: Design, optimization, and
experiment,” IEEE Trans. Ant. and Propag., vol. 64, no. 6, pp 2246-2254,
Jun. 2016.
[15] X. Tan, Z. Sun, J. M. Jornet, and D. Pados, “Increasing indoor spectrum
sharing capacity using smart reﬂect-array,” in Proc. IEEE ICC, May 2016,
pp. 1-6.
[16] X. Tan, Z. Sun, D. Koutsonikolas, and J. M. Jornet, “Enabling indoor
mobile millimeter-wave networks based on smart reﬂect-arrays,” in Proc.
IEEE INFOCOM, Oct. 2018, pp. 1-9.
[17] H. Kamoda, T. Iwasaki, J. Tsumochi, T. Kuki, and O. Hashimoto, “60-
GHz electrically reconﬁgurable large reﬂectarray using single-bit phase
shifters,” IEEE Trans. Antennas Propag., vol. 59, no. 7, pp. 2524-2531,
Jul. 2011.
[18] O. Bayraktar, O. A. Civi, and T. Akin, “Beam switching reﬂectarray mono-
lithically integrated with RF MEMS switches,” IEEE Trans. Antennas
Propag., vol. 60, no. 2, pp. 854-862, Feb. 2012.
[19] E. Carrasco, M. Barba, and J. A. Encinar, “X-Band reﬂectarray antenna
with switching-beam using PIN diodes and gathered elements,” IEEE
Trans. Antennas Propag., vol. 60, no. 12, pp. 5700-5708, Dec. 2012.
[20] H. Yang, F. Yang, X. Cao, S. Xu, J. Gao, X. Chen, M. Li, and T. Li , “A
1600-element dual-frequency electronically reconﬁgurable reﬂectarray at
X/Ku-band,” IEEE Trans. Antennas Propag., vol. 65, no. 6, pp. 3024-3032,
June 2017.
[21] S. Montori, F. Cacciamani, R. V. Gatti, R. Sorrentino, G. Arista, C.
Tienda, J. A. Encinar, and G. Toso, “A transportable reﬂectarray antenna
for satellite Ku-band emergency communications,” IEEE Trans. Antennas
Propag., vol. 63, no. 4, pp. 1393-1407, Apr. 2015.
[22] S. Montori, L. Marcaccioli, R. V. Gatti, and R. Sorrentino, “Constant-
phase dual polarization MEMS-based elementary cell for electronic steer-
able reﬂectarrays,” in Proc. Eur. Microw. Conf., 2009, pp. 33-36.
[23] M. Zhang, S. Gao, Y. Jiao, J. Wan, B. Tian, C. Wu, and A. Farrall, “Design
of novel reconﬁgurable reﬂectarrays with single-bit phase resolution for
Ku-band satellite antenna applications,” IEEE Trans. Antennas Propag.,
vol. 64, no. 5, pp. 1634-1641, May 2016.
[24] Q. Wu and R. Zhang, “Beamforming optimization for wireless network
aided by intelligent reﬂecting surface with discrete phase shifts,” to appear
in IEEE Trans. Commun., Dec. 2019.
[25] B. Wu, A. Sutinjo, M. E. Potter, and M. Okoniewski, “On the selection of
the number of bits to control a dynamic digital MEMS reﬂectarray,” IEEE
Antennas Wireless Propag. Lett., vol. 7, pp. 183-186, Mar. 2008.
VOLUME x, xxxx 9
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2977772, IEEE Access
L. Dai et al.: Reconﬁgurable Intelligent Surface-Based Wireless Communication
[26] H. Yang, F. Yang, S. Xu, M. Li, X. Cao, J. Gao, and Y. Zheng, “A study of
phase quantization effects for reconﬁgurable reﬂectarray antennas,” IEEE
Antennas Wireless Propag. Lett., vol. 16, pp. 302-305, May 2016.
[27] R. Pereira, R. Gillard, R. Sauleau, P. Potier, T. Dousset, and X. Delestre,
“Four-state dual polarisation unit-cells for reﬂectarray applications,” Elec-
tron. Lett., vol. 46, pp. 742-743, May 2010.
[28] R. Pereira, R. Gillard, R. Sauleau, P. Potier, T. Dousset, and X. Delestre,
“Dual linearly-polarized unit-cells with nearly 2-bit resolution for reﬂec-
tarray applications in X-band,” IEEE Trans. Antennas Propag., vol. 60, no.
12, pp. 6042-6048, Dec. 2012.
[29] P. Nayeri, F. Yang, and A. Z. Elsherbeni, Reﬂectarray antennas: Theory,
designs, and applications. John Wiley & Sons, 2018.
[30] X. Yang, S. Xu, F. Yang, and M. Li, “A novel 2-bit reconﬁgurable
reﬂectarray element for both linear and circular polarizations,” in Proc.
Int. Symp. Antennas Propag. Soc., Oct. 2017, pp. 2083-2084.
[31] J. Jang, M. Chung, H. Hwang, Y.-G. Lim, H. Yoon, T. Oh, B. Min, Y.
Lee, K. Kim, C.-B. Chae, and D.-K. Kim, “Smart small cell with hybrid
beamforming for 5G: From theoretical feasibility to prototype results,”
IEEE Wireless Commun., vol. 23, no. 6, pp. 124-131, Dec. 2016.
[32] 3GPP, “TS36.211: Evolved Universal Terrestrial Radio Access (E-UTRA);
Physical Channels and Modulation (Release 10), V10.7.0,” Feb. 2013.
[33] 3GPP, “TS36.212: Evolved Universal Terrestrial Radio Access (E-UTRA);
Multiplexing and channel coding (Release 10), V10.8.0,” Jun. 2013.
[34] 3GPP, “TS36.213: Evolved Universal Terrestrial Radio Access (E-UTRA);
Physical layer procedures (Release 10), V10.12.0,” Mar. 2014.
[35] Y.-J. Cho, G.-Y. Suk, B. Kim, D.-K. Kim, and C.-B. Chae, “RF lens
embedded antenna array for mmWave MIMO: Design and performance,”
IEEE Commun. Mag., vol. 56, no. 6, pp. 42-48, Jul. 2018.
[36] T. Kwon, Y.-G. Lim, B. Min, and C.-B. Chae, “RF lens embedded massive
MIMO systems: Fabrication issues and codebook design,” IEEE Trans.
Microwave Theory and Techniques, vol. 64, no. 7, pp. 2256-2271, Jul.
2016.
B.S. degree from Zhejiang University, Hangzhou,
China, in 2003, the M.S. degree (with the highest
Hons.) from the China Academy of Telecommu-
nications Technology, Beijing, China, in 2006,
and the Ph.D. degree (with the highest Hons.)
from Tsinghua University, Beijing, China, in 2011.
From 2011 to 2013, he was a Postdoctoral Re-
search Fellow with the Department of Electronic
Engineering, Tsinghua University, where he was
an Assistant Professor from 2013 to 2016 and has been an Associate
Professor since 2016. His current research interests include massive MI-
MO, millimeter-wave communications, THz communications, NOMA, re-
conﬁgurable intelligent surface (RIS), and machine learning for wireless
communications. He has coauthored the book “MmWave Massive MIMO:
A Paradigm for 5G” (Academic Press, 2016). He has authored or coauthored
more than 60 IEEE journal papers and more than 40 IEEE conference papers.
He also holds 16 granted patents. He has received ﬁve IEEE Best Paper
Awards at the IEEE ICC 2013, the IEEE ICC 2014, the IEEE ICC 2017,
the IEEE VTC 2017-Fall, and the IEEE ICC 2018. He has also received
the Tsinghua University Outstanding Ph.D. Graduate Award in 2011, the
Beijing Excellent Doctoral Dissertation Award in 2012, the China National
Excellent Doctoral Dissertation Nomination Award in 2013, the URSI
Young Scientist Award in 2014, the IEEE Transactions on Broadcasting
Best Paper Award in 2015, the Electronics Letters Best Paper Award in
2016, the National Natural Science Foundation of China for Outstanding
Young Scholars in 2017, the IEEE ComSoc Asia-Paciﬁc Outstanding Young
Researcher Award in 2017, the IEEE ComSoc Asia-Paciﬁc Outstanding
Paper Award in 2018, and the China Communications Best Paper Award
in 2019. He is an Area Editor of IEEE Communications Letters, and an
Editor of IEEE Transactions on Communications and IEEE Transactions on
Vehicular Technology. Particularly, he is dedicated to reproducible research
and has made a large amount of simulation code publicly available.
BICHAI WANG (S’15) received her B.S. degree
in Electronic Engineering from Tsinghua Univer-
sity, Beijing, China, in 2015. She is currently
working towards the Ph.D. degree in the Depart-
ment of Electronic Engineering, Tsinghua Univer-
sity, Beijing, China. Her research interests are in
wireless communications, with the emphasis on
non-orthogonal multiple access, mmWave massive
MIMO, and deep learning-based wireless commu-
nications. She has received the Freshman Scholar-
ship of Tsinghua University in 2011, the Academic Merit Scholarships of
Tsinghua University in 2012, 2013, and 2014, respectively, the Excellent
Thesis Award of Tsinghua University in 2015, the National Scholarship in
2016, the IEEE VTC’17 Fall Best Student Paper Award in 2017, the IEEE
Transactions on Communications Exemplary Reviewer Award in 2017, the
7th IEEE ComSoc Asia-Paciﬁc Outstanding Paper Award in 2018, and the
Paul Baran Young Scholar Award in 2019.
MIN WANG received the Ph.D. degree from the
Department of Electronic Engineering, Tsinghua
University, Beijing, China, in 2018, Her current
research interests include reconﬁgurable reﬂectar-
ray antenna, amplifying reﬂectarray antenna, and
metasurface analysis.
XUE YANG (S’13) received the B.S. degree from
Xidian University, Xi’an, China, in 2013, the
Ph.D. degree from the Department of Electronic
Engineering, Tsinghua University, Beijing, China,
in 2017, Her current research interests include
reconﬁgurable reﬂectarray antenna, amplifying re-
ﬂectarray antenna, and metasurface analysis.
JINGBO TAN received the B.S. degree in the
Department of Electronic Engineering from Ts-
inghua University in 2017, and then he became a
Ph.D. student in the same department of Tsinghua
University since Sep. 2017. His current research
interests include channel feedback and codebook
design for massive MIMO and millimeter-wave
communications, and deep learning for wireless
communications.
10 VOLUME x, xxxx
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2977772, IEEE Access
L. Dai et al.: Reconﬁgurable Intelligent Surface-Based Wireless Communication
SHUANGKAISHENG BI received the B.S. de-
gree in the Department of Electronic Engineering
in 2018, and then he became a master student in
the same department of Tsinghua University since
Sep. 2018. Mr. Bi’s research interest is prototype
tions.
SHENHENG XU (M’09) received the B.S. and
M.S. degrees from Southeast University, Nanjing,
China, in 2001 and 2004, respectively, and the
Ph.D. degree from the University of California at
Los Angeles (UCLA), Los Angeles, CA, USA, in
2009, all in electrical engineering. From 2000 to
2004, he was a Research Assistant with the State
Key Laboratory of Millimeter Waves, Southeast
University. Since 2004, he has been a Graduate
Student Researcher and later a Post-Doctoral Re-
searcher with the Antenna Research, Analysis, and Measurement Laborato-
ry, UCLA. In 2012, he became an Associate Professor with the Department
of Electronic Engineering, Tsinghua University, Beijing, China. His research
interests include the novel designs of reﬂector and reﬂectarray antennas
for advanced applications, evolutionary algorithms, and electromagnetic and
antenna theories.
the B.S. and M.S. degrees from Tsinghua Univer-
sity, Beijing, China, in 1997 and 1999, respective-
ly, and the Ph.D. degree from the University of
California at Los Angeles (UCLA), in 2002.
From 1994 to 1999, he was a Research Assis-
tant at the State Key Laboratory of Microwave
and Digital Communications, Tsinghua Universi-
ty. From 1999 to 2002, he was a Graduate Student
Researcher at the Antenna Laboratory, UCLA.
From 2002 to 2004, he was a Post-Doctoral Research Engineer and Instruc-
tor at the Electrical Engineering Department, UCLA. In 2004, he joined
the Electrical Engineering Department, The University of Mississippi as an
Assistant Professor, and was promoted to an Associate Professor in 2009. In
2011, he joined the Electronic Engineering Department, Tsinghua University
as a Professor, and has served as the Director of the Microwave and Antenna
Institute since then.
Dr. Yang’s research interests include antennas, surface electromagnetics,
computational electromagnetics, and applied electromagnetic systems. He
has published over 400 journal articles and conference papers, seven book
chapters, and six books entitled Surface Electromagnetics (Cambridge Univ.
Press, 2019), Reﬂectarray Antennas: Theory, Designs, and Application-
s (IEEE-Wiley, 2018), Analysis and Design of Transmitarray Antennas
(Morgan & Claypool, 2017), Scattering Analysis of Periodic Structures
Using Finite-Difference Time-Domain Method (Morgan & Claypool, 2012),
Electromagnetic Band Gap Structures in Antenna Engineering (Cambridge
Univ. Press, 2009), and Electromagnetics and Antenna Optimization Using
Taguchi’s Method (Morgan & Claypool, 2007).
Dr. Yang served as an Associate Editor of the IEEE Transactions on
Antennas and Propagation (2010-2013) and an Associate Editor-in-Chief of
Applied Computational Electromagnetics Society (ACES) Journal (2008-
2014). He was the Technical Program Committee (TPC) Chair of 2014
IEEE International Symposium on Antennas and Propagation and USNC-
URSI Radio Science Meeting. Dr. Yang has been the recipient of several
prestigious awards and recognitions, including the Young Scientist Award of
the 2005 URSI General Assembly and of the 2007 International Symposium
on Electromagnetic Theory, the 2008 Junior Faculty Research Award of the
University of Mississippi, the 2009 inaugural IEEE Donald G. Dudley Jr.
Undergraduate Teaching Award, and the 2011 Recipient of Global Experts
Program of China. He is an ACES Fellow and IEEE Fellow, as well as an
IEEE APS Distinguished Lecturer for 2018-2020.
ZHI CHEN (SM’16) received B. Eng, M. Eng.,
and Ph.D. degree in Electrical Engineering from
University of Electronic Science and Technology
of China (UESTC), in 1997, 2000, 2006, respec-
tively. On April 2006, he joined the National Key
Lab of Science and Technology on Communica-
tions (NCL), UESTC, and worked as a professor
in this lab from August 2013. He was a visiting
scholar at University of California, Riverside dur-
ing 2010-2011. He is also the deputy director of
Key Laboratory of Terahertz Technology, Ministry of Education of China.
His current research interests include Terahertz communication, 5G mobile
communications and tactile internet.
VOLUME x, xxxx 11
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2977772, IEEE Access
L. Dai et al.: Reconﬁgurable Intelligent Surface-Based Wireless Communication
MARCO DI RENZO (F’20) was born in
L’Aquila, Italy, in 1978. He received the Laurea
(cum laude) and Ph.D. degrees in electrical engi-
neering from the University of L’Aquila, Italy, in
2003 and 2007, respectively, and the Habilitation a
Diriger des Recherches (Doctor of Science) degree
from University Paris-Sud, France, in 2013. Since
2010, he has been with the French National Center
for Scientiﬁc Research (CNRS), where he is a
CNRS Research Director (CNRS Professor) in
the Laboratory of Signals and Systems (L2S) of Paris-Saclay University
- CNRS and CentraleSupelec, Paris, France. He serves as the Editor-in-
Chief of IEEE Communications Letters. He served as an Editor of IEEE
Transactions on Communications, IEEE Transactions on Wireless Commu-
nications, IEEE Communications Letters, and as the Associate Editor-in-
Chief of IEEE Communications Letters. He is a Distinguished Lecturer of
the IEEE Vehicular Technology Society and IEEE Communications Society.
He is a recipient of several awards, including the 2013 IEEE-COMSOC
Best Young Researcher Award for Europe, Middle East and Africa, the
2013 NoE-NEWCOM# Best Paper Award, the 2014-2015 Royal Academy
of Engineering Distinguished Visiting Fellowship, the 2015 IEEE Jack
Neubauer Memorial Best System Paper Award, the 2015 CNRS Award for
Excellence in Research and Ph.D. Supervision, the 2016 MSCA Global
Fellowship (declined), the 2017 SEE-IEEE Alain Glavieux Award, the
2018 IEEE-COMSOC Young Professional in Academia Award, and 8 Best
Paper Awards at IEEE conferences (2012 and 2014 IEEE CAMAD, 2013
IEEE VTC-Fall, 2014 IEEE ATC, 2015 IEEE ComManTel, 2017 IEEE
SigTelCom, EAI 2018 INISCOM, IEEE ICC 2019). He is a Highly Cited
Researcher according to Clarivate Analytics and Web of Science, and a
Fellow of the IEEE.
CHAN-BYOUNG CHAE (S’06-M’09-SM’12) is
an Underwood Distinguished Professor in the
School of Integrated Technology, Yonsei Univer-
sity, Korea. Before joining Yonsei University, he
was with Bell Labs, Alcatel-Lucent, Murray Hill,
NJ, USA from 2009 to 2011, as a Member of Tech-
nical Staff, and Harvard University, Cambridge,
MA, USA from 2008 to 2009, as a Postdoctoral
Research Fellow. He received his Ph.D. degree
in Electrical & Computer Engineering from The
University of Texas at Austin in 2008. Prior to joining UT, he was a research
engineer at the Telecommunications R&D Center, Samsung Electronics,
Suwon, Korea, from 2001 to 2005.
He is now an Editor-in-Chief of the IEEE Trans. Molecular, Biological,
and Multi-scale Communications and a Senior Editor of the IEEE Wireless
Communications Letters. He has served/serves as an Editor for the IEEE
Communications Magazine (2016-present), the IEEE Trans. on Wireless
Communications (2012-2017), the IEEE Trans. on Molecular, Biological,
and Multi-scale Comm. (2015-2018), and the IEEE Wireless Communica-
tions Letters (2016-present). He is an IEEE ComSoc Distinguished Lecturer
for the term 2020-2021.
He was the recipient/co-recipient of the Young Engineer Award from the
National Academy of Engineering of Korea (NAEK) in 2019, the IEEE
DySPAN Best Demo Award in 2018, the IEEE/KICS Journal of Commu-
nications and Networks Best Paper Award in 2018, the Award of Excellence
in Leadership of 100 Leading Core Technologies for Korea 2025 from the
NAEK in 2017, the Yonam Research Award from LG Yonam Foundation
in 2016, the IEEE INFOCOM Best Demo Award in 2015, the IEIE/IEEE
Joint Award for Young IT Engineer of the Year in 2014, the KICS Haedong
Young Scholar Award in 2013, the IEEE Signal Processing Magazine Best
Paper Award in 2013, the IEEE ComSoc AP Outstanding Young Researcher
Award in 2012, the IEEE VTS Dan. E. Noble Fellowship Award in 2008.
LAJOS HANZO (M’91-SM’92-F’04) FREng,
FIEEE, FIET, Fellow of EURASIP, DSc received
his degree in electronics in 1976 and his doctorate
in 1983. In 2009 he was awarded an honorary
doctorate by the Technical University of Budapest
and in 2015 by the University of Edinburgh. In
my of Science. During his 40-year career in t-
elecommunications he has held various research
and academic posts in Hungary, Germany and the
UK. Since 1986 he has been with the School of Electronics and Computer
Science, University of Southampton, UK, where he holds the chair in
telecommunications. He has successfully supervised 111 PhD students, co-
authored 18 John Wiley/IEEE Press books on mobile radio communications
totalling in excess of 10 000 pages, published 1741 research contributions
at IEEE Xplore, acted both as TPC and General Chair of IEEE conferences,
presented keynote lectures and has been awarded a number of distinctions.
Currently he is directing a 60-strong academic research team, working on
a range of research projects in the ﬁeld of wireless multimedia communica-
tions sponsored by industry, the Engineering and Physical Sciences Research
Council (EPSRC) UK, the European Research Council’s Advanced Fellow
Grant and the Royal Society’s Wolfson Research Merit Award. He is an
enthusiastic supporter of industrial and academic liaison and he offers a
range of industrial courses. He is also a Governor of the IEEE ComSoc
and VTS. During 2008-2012 he was the Editor-in-Chief of the IEEE Press
and a Chaired Professor also at Tsinghua University, Beijing. For further
information on research in progress and associated publications please refer
to http://www-mobile.ecs.soton.ac.uk.
12 VOLUME x, xxxx
... Namely, these plasma elements present a bandwidth several times larger than many classical systems where it spans 0.1-0.2 GHz [34], [45]. ...
... For example, z pl = λ/2 may be sufficient to guarantee a 2-Bit phase resolution where the four states need to encompass a phase increment of 90 deg. The latter concept is particularly appealing for high gain IRS targeted at massive multipleinput multiple-output applications [45]. ...
Article
Full-text available
Gaseous Plasma Antennas are devices in which an ionized gas (i.e., plasma) is exploited to transmit and receive Electro-Magnetic waves. Their main advantage over metallic systems is the possibility to reconfigure the antenna performance (e.g., radiation pattern) by electronically varying the plasma parameters (e.g., density). Recently, Intelligent Reflecting Surfaces (IRSs) have been proposed to control the environment between transmitting and receiving antennas manipulating the signals reflected. In this work, the feasibility of a plasma-based IRS is investigated. A theoretical model has been developed to assess the use of plasma as a reflecting medium. Numerical simulations have been performed to preliminary design plasma-based IRSs. Two designs of IRSs, relying on plasma properties consistent with the technology at the state-of-the-art, are proposed. The former enables beam steering operations depending on the continuous control of the phase of the reflected wave. The latter exploits a 1-Bit coding strategy to produce specific diffraction patterns. The main advantage of a plasma-based IRS with respect to the metallic counterpart is the possibility to control the phase of the reflected wave, maintaining the magnitude of the reflection coefficient close to the unit. The main drawback of plasma-based systems is the necessity of using thick plasma elements (in the order of the wavelength in the air) to control the phase of the reflected wave over 360 deg. This constraint can be relaxed if digital plasma elements are adopted.
... lenges are still open such as building testbeds for experimental validation [74][75][76][77], the task of estimating the combined channel from the BS to the RIS and on to the UE [78,79], and the joint optimization of the multi-antenna BS and the RIS parameters [79][80][81][82][83][84][85]. Particularly relevant for this thesis is the latter category, concerning the joint optimization of active beamforming at the BS and passive beamforming at the RIS. ...
Thesis
The exponential increase of wireless user equipments (UEs) and network services associated with current 5G deployments poses several unprecedented design challenges that need to be addressed with the advent of future beyond-5G networks and novel signal processing and transmission schemes. In this regard, massive MIMO is a well-established access technology, which allows to serve many tens of UEs using the same time-frequency resources. However, massive MIMO exhibits scalability issues in massive access scenarios where the UE population is composed of a large number of heterogeneous devices. In this thesis, we propose novel scalable multiple antenna methods for performance enhancement in several scenarios of interest. Specifically, we describe the fundamental role played by statistical channel state information (CSI) that can be leveraged for reduction of both complexity and overhead for CSI acquisition, and for multiuser interference suppression. Moreover, we exploit device-to-device communications to overcome the fundamental bottleneck of conventional multicasting. Lastly, in the context of millimiter wave communications, we explore the benefits of the recently proposed reconfigurable intelligent surfaces (RISs). Thanks to their inherently passive structure, RISs allow to control the propagation environment and effectively counteract propagation losses and substantially increase the network performance.
... The RIS alleviates the negative effect of multipath-fading and can benefit from channel hardening [8] for robust wireless communication system operation. To date experimental setups have been demonstrated to show the benefits of RIS integration in active Tx-Rx links in multimode metallic enclosures [9],indoor [10], as well as in outdoor environments [11]. The Authors in [12] have shown experimental setups with signal generator, RIS and directional antennas. ...
Preprint
Full-text available
The fifth generating (5G) of wireless networks will be more adaptive and heterogeneous. Reconfigurable intelligent surface technology enables the 5G to work on multistrand waveforms. However, in such a dynamic network, the identification of specific modulation types is of paramount importance. We present a RIS-assisted digital classification method based on artificial intelligence. We train a convolutional neural network to classify digital modulations. The proposed method operates and learns features directly on the received signal without feature extraction. The features learned by the convolutional neural network are presented and analyzed. Furthermore, the robust features of the received signals at a specific SNR range are studied. The accuracy of the proposed classification method is found to be remarkable, particularly for low levels of SNR.
... IRS have been used to improve the throughput of millimeter wave and optical communications [10][11][12]. A practical implementation with measurements have confirmed the throughput enhancement when IRS are deployed with continuous or discrete phase shifts [13][14][15][16][17]. IRS using deep and machine learning techniques have been discussed in [18,19]. ...
Article
Full-text available
In this article, we study the performance of cognitive radio networks (CRN) with adaptive transmit power and energy harvesting. The secondary source SS\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$S_S$$\end{document} harvests power using the signal of node A. Then, it adapts its power to generate interference at primary destination PD\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P_D$$\end{document} lower than a predefined threshold T. The broadcasted signal by SS\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$S_S$$\end{document} is reflected by intelligent reflecting surfaces IRS so that reflections have a zero phase at the secondary destination SD\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$S_D$$\end{document}. The throughput at secondary destination is derived in the absence or presence of primary interference. IRS with N=8\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N=8$$\end{document}, 16, 32 reflectors offers 20, 26 and 32 dB gain versus CRN. The use of IRS as a transmitter improves the throughput by 1 dB versus IRS employed as a reflector.
Article
Full-text available
This paper proposes a new wireless enabling technology for future smart radio environments. The approach aims to enhance signal coverage within the shadow region(s) of wireless networks with the aid of so-called ’intelligent edges (IEs)’. IEs may be installed at the fringes of shadowing objects such as buildings, walls and other obstacles which obscure the optical signal path from a transmitter to receiver. We investigate two different approaches to illuminating the shadow region in wireless networks using IEs which exploit refraction or diffraction, operating in passive or active mode. The operation of IE-assisted communications are investigated, in particular the ways they can redirect electromagnetic energy towards regions with little or no wireless network coverage. Following from this, a number of variations of IEs are tested in real-world scenarios which consider illuminating the shadow region behind high-rise buildings, first in a city center, and then along a shoreline. Refractive IEs in particular, are shown to provide significant gains compared to the case when no IEs are involved, enhancing signal reception in the shadow region at street level behind a high rise building by as much as 12 dB. Critically, it is shown that intelligent edges offer a low complexity and cost-effective solution for improving connectivity in shadowing-limited environments.
Article
A tunable terahertz four-port multiple-input-multiple-output (MIMO) graphene-based microstrip patch antenna with self-multiplexing ability is designed and numerically studied. Insertion of cross-slot in the graphene patch improved the isolation level to the order of 50−70 dB in the four-port MIMO mode operation. Four separate biasing pads are used to obtain independent frequency tunability, which gives rise to MIMO and/or self-diplexing, self-triplexing, and self-quadruplexing operation, by using different combinations of dc bias voltages. The MIMO and self-multiplexing actions are attained while using common ground plane and continuous graphene patch. The MIMO performance parameters like envelope correlation coefficient (ECC), diversity gain, mean effective gain, port-to-port isolation, etc. are found to be within the acceptable limits. A four-port equivalent circuit model of the MIMO antenna is presented to provide insight into the radiation mechanism and to validate the simulation results. The designed four port antenna is found to provide ECC in the order of 0.0073 and isolation in the range of − dB while it is operated in the self-diplexing with two-port MIMO mode operation.
Article
Full-text available
The future of mobile communications looks exciting with the potential new use cases and challenging requirements of future 6th generation (6G) and beyond wireless networks. Since the beginning of the modern era of wireless communications, the propagation medium has been perceived as a randomly behaving entity between the transmitter and the receiver, which degrades the quality of the received signal due to the uncontrollable interactions of the transmitted radio waves with the surrounding objects. The recent advent of reconfigurable intelligent surfaces in wireless communications enables, on the other hand, network operators to control the scattering, reflection, and refraction characteristics of the radio waves, by overcoming the negative effects of natural wireless propagation. Recent results have revealed that reconfigurable intelligent surfaces can effectively control the wavefront, e.g., the phase, amplitude, frequency, and even polarization, of the impinging signals without the need of complex decoding, encoding, and radio frequency processing operations. Motivated by the potential of this emerging technology, the present article is aimed to provide the readers with a detailed overview and historical perspective on state-of-the-art solutions, and to elaborate on the fundamental differences with other technologies, the most important open research issues to tackle, and the reasons why the use of reconfigurable intelligent surfaces necessitates to rethink the communication-theoretic models currently employed in wireless networks. This article also explores theoretical performance limits of reconfigurable intelligent surface-assisted communication systems using mathematical techniques and elaborates on the potential use cases of intelligent surfaces in 6G and beyond wireless networks.
Article
Full-text available
A dual-frequency reconfigurable reflectarray (RRA) is proposed and verified experimentally. The RRA consists of 1600 electronically controllable elements. By integrating only a single PIN diode, the proposed element is capable to operate at two working frequencies with 1-bit phase resolution. The dual-frequency mechanism is explained through the mode analysis, and a parametric study is performed to provide guidelines for determining the two working frequencies. As an example, a 1600-element RRA prototype is realized by assembling 5 identical 8 $\times$ 40 sub-arrays. An FPGA control board is used to achieve real-time phase control of each element individually. The experimental results show that the broadside gains of the RRA are 29.3 dBi, 30.8 dBi at 11.1 GHz and 14.3 GHz, respectively. Excellent beam scanning performance is also obtained at both frequencies.