CORRESPONDING AUTHOR: Yuan Feng (e-mail: y.feng@nus.edu.sg). This work was
partly supported by the National Research Foundation, Singapore, and Infocomm
Media Development Authority under its Future Communications Research &
Development Programme, Grant No. FCP-NTU-RG-2022-011 and Grant No. FCP-NTU-
RG-2022-020, partly by Temasek Laboratories@NTU seed research project No.
TLSP23-13.

# Innovative RIS Prototyping Enhancing Wireless Communication with Real-Time
Spot Beam Tracking and OAM Wavefront Manipulation

Yufei Zhao1  Yuan Feng2  Afkar Mohamed Ismail1  Ziyue Wang1  Yong Liang
Guan1(Senior Member, IEEE)  Yongxin Guo2 (Fellow, IEEE)  and Chau Yuen1
(Fellow, IEEE)  School of Electrical and Electronic Engineering, Nanyang
Technological University, 639798, Singapore  Department of Electrical and
Computer Engineering, National University of Singapore, 117583, Singapore

###### Abstract

Reconfigurable metasurface, also known as Reconfigurable Intelligent Surfaces
(RIS), with its flexible beamforming, low-cost, and easy industrial deployment
characteristics, presents many interesting solutions in wireless application
scenarios. This paper presents a sophisticated reconfigurable metasurface
architecture that introduces an advanced concept of flexible full-array space-
time wavefront manipulation with enhanced dynamic capabilities. The practical
2-bit phase-shifting unit cell on the RIS is distinguished by its ability to
maintain four stable phase states, each with ${90^{\circ}}$ differences, and
features an insertion loss of less than 0.6 dB across a bandwidth of 200 MHz.
All reconfigurable units are equipped with meticulously designed control
circuits, governed by an intelligent core composed of multiple Micro-
Controller Units (MCUs), enabling rapid control response across the entire RIS
array. Owing to the capability of each unit cell on the metasurface to
independently switch states, the entire RIS is not limited to controlling
general beams with specific directional patterns, but also generates beams
with more complex structures, including multi-focus 3D spot beams and vortex
beams. This development substantially broadens its applicability across
various industrial wireless transmission scenarios. Moreover, by leveraging
the rapid-respond space-time coding and the full-array independent
programmability of the RIS prototyping operating at 10.7 GHz, we have
demonstrated that: 1) The implementation of 3D spot beams scanning facilitates
dynamic beam tracking and real-time communication under the indoor near-field
scenario; 2) The rapid wavefront rotation of vortex beams enables precise
modulation of signals within the Doppler domain, showcasing an innovative
approach to wireless signal manipulation; 3) The beam steering experiments for
blocking users under outdoor far-field scenarios, verifying the beamforming
capability of the RIS board.

Reconfigurable metasurfaces, Reconfigurable Intelligent Surface (RIS), Micro-
Controller Unit (MCU), 3D spot beam tracking, vortex beam, rotational Doppler

##  1 INTRODUCTION

In today’s urban landscapes, the dense layout of buildings presents
substantial obstacles to wireless services, especially affecting vehicles and
Unmanned Aerial Vehicles (UAVs) due to potential signal blockages that
deteriorate communication quality and may even cause disruptions [1, 2].
Traditional approaches to maintaining consistent connectivity struggle in
areas with tall structures, narrow passages, and various barriers. Recently,
reconfigurable metasurfaces, or Reconfigurable Intelligent Surfaces (RISs),
have emerged as a viable solution, providing unparalleled control over the
propagation of Electro-Magnetic (EM) waves [3, 4]. These surfaces are notable
for their adaptable beamforming abilities, affordability, and straightforward
integration into industrial settings, marking significant progress in meeting
the sophisticated needs of wireless services [5, 6, 7, 8].

While traditional metasurfaces show great promise, their practical use faces
several challenges due to complex design and control system limitations, such
as fixed states, low-order phase quantization, low response speed, and
cumbersome control logic. Previous work has initiated a wave of research into
intelligent metasurfaces, such as, [9] and [10] pioneered practical RIS
demonstration prototyping in 2020 with limited 1-bit phase modulation
capability per unit, which may result in 3 dB energy loss in beamforming
caused by the low bit quantization [11, 12]. A year later, [13] unveiled a
2-bit RIS system, which is limited to row-by-row unit control, restricting
beam scanning to just one dimension. The design suggested by [14], involving a
single Micro-controller Unit (MCU) and several shift registers, did offer a
way to independently control multiple states per unit cell. However, the
limited number of I/O ports on the MCU meant that updating all shift registers
took too much time, slowing down the RIS’s response speed, and limiting its
effectiveness in space-time-coding situations.

Drawing inspiration from these remarkable contributions above, we identified
the essential need for a RIS system capable of quickly and independently
controlling each unit without compromising dynamic responsiveness, especially
critical in situations requiring fast adaptability. Our research introduces an
innovative 2-bit phase-quantized RIS design that enables independent control
of each unit while effectively addressing challenges related to space-time
dynamic response. This system utilizes multiple MCUs to facilitate swift and
efficient state changes, essential for fast beam tracking and space-time
coding. Our 2-bit phase-quantized approach and hierarchical control of unit
cells significantly improve beamforming capabilities, allowing for the precise
and fast adjustment of cone beams and the creation of complex beam structures
like spot and vortex beams. This advancement enhances wireless services
flexibility and offers solutions tailored to the demanding conditions of
modern environments.

Additionally, addressing the complexities of wireless near-field scenarios, we
have evolved the traditional 2D beam direction scanning into 3D spatial spot
beam scanning, and introduced a spot beamforming phase compensation codebook
scheme for the phase-quantized RIS. Furthermore, a 3D spot beam tracking
algorithm specifically designed for rapidly moving users has been developed.
Through feedback between the user and the control system, stable spot beam
locking can be achieved, significantly bolstering the RIS prototyping’s
adaptability to complex EM environments. From theory to practice, innovations
at multiple levels in both software and hardware have endowed our RIS
prototyping with robust adaptability to various applications. In different
experimental scenarios, we demonstrate that (a) 3D spot beam scanning enables
dynamic tracking, guaranteeing stable and real-time data transmission with the
receiver; (b) vortex beams’ space-time wavefront manipulation facilitates
precise signal modulation in the Doppler domain, offering a novel signal
processing method; (c) beams steering for blocking users under outdoor far-
field scenarios, verifying the beamforming capability of the RIS board.

To clarify, the main contributions of this research can be summarized as
follows:

  1. 1.

Firstly, this paper proposes an innovative 2-bit RIS unit cell design through
a non-resonant method, that achieves four stable and reconfigurable phase
states, while maintaining consistent amplitude attenuation (below 0.6 dB)
within the effective bandwidth (over 200 MHz). Incorporating the full-array
independent control flexibility, this design furnishes an efficient solution
tailored to fulfill the intricate beam steering and space-time-coding
requirements.

  2. 2.

Next, in terms of programmable hardware support, we designed a RIS signal
control circuit board consisting of multiple MCUs, enabling parallel and pre-
configured phase states controlling for each independent Radio Frequency (RF)
unit cell. The RIS prototyping constructed based on this multi-MCU based
hierarchical control system not only achieves highly dynamic beam tracking in
horizontal, vertical, and depth (near and far) dimensions, but also enables
more complex structured EM waves, e.g., rotational vortex beams. This opens up
richer possibilities for future RIS-based wireless transmission solutions.

  3. 3.

Moreover, this study addresses the characteristics of the EM near-field in
multiple reflection scenarios and tailors a spot beamforming codebook scheme
for RIS-aided wireless communications, enhancing the precision of 3D spatial
beam tracking. A direct and efficient method for implementing spot beam
tracking has been proposed in this paper. It introduces a fast spot beam
scanning algorithm, facilitating rapid and robust tracking of moving users
through comprehensive scans of predetermined spatial regions, which enables
stable data transmission within complex reflection interference.

  4. 4.

Finally, from theory to practice, innovations at multiple levels in both
software and hardware have endowed our RIS prototyping with robust
adaptability to various applications. It effortlessly handles diverse and
complex beamforming requirements, as validated through full-wave EM simulation
analyses. In various experimental scenarios, we demonstrated the powerful
space-time wavefront manipulation capabilities of the RIS prototype, providing
an efficient testing platform for a wide range of future wireless
applications.

The rest of this paper is organized as follows: Section II delves into the
2-bit phase-quantized RIS implementation and its dynamic control system, with
a wide comparison of other related works. Section III explains the RIS
codebook design, and introduces an efficient 3D spot beam tracking approach,
which is verified by the real-time tracking communication experiment. Section
IV showcases the vortex wavefront high dynamic manipulation approach, offering
a novel signal processing method in the Doppler domain. In Section V, an
outdoor far-field test has been implemented to verify the beamforming
capability of our RF RIS board. In the end, Section VI concludes this paper
and discusses the implications of the findings, potential applications, and
avenues for future research.

Table 1: Comparisons of the reflective RIS prototyping from implementations to
applications

Ref. | Unit cell of the RIS board | Control Circuitry | Functions or
---|---|---|---
works | Components | Center Freq. | Polar.a | States | Ins. loss | Bandwidth | Controller | Control DoFb | Applications
[6] | 4 PINs | 3.5 GHz | LP, CP | 2 bit | 2 dB | 180 MHz | FPGA | By units | Polar. converter
[9] | 1 PIN | 11.5 GHz | LP | 1 bit | 1 dB | 1 GHz | MCU, FPGA | by units | Beam steerer
[13] | 2 PINs | 9.5 GHz | LP | 2 bit | 1 dB | 100 MHz | FPGA | By columns | Space-time-coding
[14] | 1 PIN | 60.25 GHz | LP | 1 bit | 5.3 dB | 450 MHz | FPGA | By units | Beam steerer
[16] | 2 PIN | 8.0 GHz | LP | 2 bit | 1 dB | 500 MHz | - | By columns | AM PM tunable
[20] | 4 PIN | 3.6 GHz | LP (daul) | 2 bit |  $<$1 dB | 400 MHz | FPGA | By rows | Beam steerer
[22] | 1 PIN | 26.0 GHz | LP | 1 bit |  $<$1 dB | 400 MHz | FPGA | - | Beam steerer
[23] | 5 PIN | 2.3 GHz | LP, CP | 2 bit, non- | 1 dB | 400 MHz | FPGA | By units | Beam steerer
[24] | RF Switch | 5.3 GHz | LP | 3 bit, non- | - | 118 MHz | MCU with | By units | Beam steerer
|  |  |  | resonant |  |  | serial bus |  |
[25] | 1 PIN | 28.5 GHz | LP (daul) | 1 bit | 2 dB | 2 GHz | FPGA | By units | Beam steerer
[26] | 1 PIN | 27.5 GHz | LP | 1 bit |  $<$3 dB | 5.25 GHz | - | By units | Beam steerer
[27] | 1 Varactor | 3.6 GHz | LP | 2 bit | 1.2 dB |  $<$400 MHz | FPGA | By columns | Time-digi.-coding
[28] | 4 Varactors | 3.7 GHz | LP | Multi-bit |  $<$3 dB | - | FPGA | By columns | Time-digi.-coding
This | 3 PINs | 10.7 GHz | LP | 2 bit, non- | 0.6 dB |  200 MHz | Hierarchical | By units | Spot beam steerer,
work |  |  |  | resonant |  |  | MCUs |  | rotational vortex

a LP: Linear polarization; CP: Circular polarization. b DoF: Degree of
freedom. It indicates the degree of flexibility with which the entire RIS
array can be controlled. It depends on the specific applications of each RIS
prototyping.

##  2 2-bit RIS Design with Its Powerful Control System

###  2.1 Phase-Quantized Unit Cell

In RIS-aided wireless solutions, the critical aspect for achieving
reconfigurability lies in how to design each independent RF discrete unit.
Conventional RIS utilizes RF units designed on resonant principles, enabling
control of EM wave phase and amplitude through adjustable electronic
components that manipulate the equivalent circuit’s impedance and reactance to
adjust the resonant frequency [15]. However, as the number of reconfigurable
states increases, the complexity of the unit cell design escalates [16, 17].
Moreover, nonlinear coupling between different states significantly impacts
the independence and stability of state transitions within the unit cell.
These problems pose significant challenges for both the design and practical
implementation of the whole RIS prototyping [18]. To address these
limitations, we introduce a novel non-resonance 2-bit phase-quantized
reconfigurable unit cell in this paper, which has been illustrated in Fig. 1.
To avoid inter-state coupling effects during state transitions of the unit
cell [16], we employ transmission line theory to devise a reconfigurable RF
non-resonance structure [19], capable of applying four distinct discrete phase
changes to incident EM waves while maintaining consistency in the amplitude.

Figure 1: Illustrates the innovative design of the RIS unit cell with respect
to (a) front-side, (b) back-side, and (c) laminated construction.
($a=13.8~{}\rm{mm}$, $b=8.3~{}\rm{mm}$, ${l_{0}}=3.46~{}\rm{mm}$,
${l_{1}}=3.84~{}\rm{mm}$, ${l_{2}}=5.64~{}\rm{mm}$, ${l_{3}}=7.64~{}\rm{mm}$,
width is $0.6~{}\rm{mm}$ for each line)

As shown in Fig. 1, each unit cell consists of three metallic and three
dielectric layers. The topmost metallic layer features a rectangular copper
patch with dimensions of 13.8 mm $\times$ 8.3 mm. This patch serves as the
initial point of engagement with the EM wave, capturing it for further
interaction with the other RIS components. Mounted on two 1 mm-thick Taconic
TLX-8 dielectric substrates (Substrates 1 and 2). Sandwiched between these
substrates is another adhesion layer composed of Rogers RO4450F. Along with
the copper ground layer beneath it, which has a thickness of 0.035 mm. A delay
line, referred to as ${l_{0}}$, is connected to the patch through a via.

The transmission line lengths in unit cell design are computed based on the
principle of achieving specific phase shifts for the reflected signals. The
goal is to control the phase of the reflected waves to achieve desired
beamforming patterns. The phase shift $\Delta\phi$ introduced by a
transmission line of length $L$ is given by $\Delta\phi{\rm{=}}\varepsilon L$,
where $\varepsilon$ is the phase constant of the transmission line, defined as
$\varepsilon={{2\pi}\mathord{\left/{\vphantom{{2\pi}{{\lambda_{\rm{c}}}}}}\right.\kern-1.2pt}{{\lambda_{\rm{c}}}}}$,
with ${{\lambda_{\rm{c}}}}$ being the wavelength of the operating frequency on
the high-frequency laminates. For a 2-bit RIS, we need to achieve four
distinct phase states ($0$, $\pi/2$, $\pi$, and $3\pi/2$). The required length
$L$ for each phase shift is computed using the following formula as,

$L={{\Delta\phi}\mathord{\left/{\vphantom{{\Delta\phi}\varepsilon}}\right.\kern-1.2pt}\varepsilon}={{\Delta\phi\cdot{\lambda_{\rm{c}}}}\mathord{\left/{\vphantom{{\Delta\phi\cdot{\lambda_{\rm{c}}}}{2\pi}}}\right.\kern-1.2pt}{2\pi}}.$
(1)

Specifically, for each phase shift:

$\left\\{{\begin{array}[]{*{20}{l}}{{L_{0}}=0+\delta,}&{{\rm{for~{}0~{}phase~{}shift,}}}\\\
{{L_{1}}={{{\lambda_{\rm{c}}}}\mathord{\left/{\vphantom{{{\lambda_{\rm{c}}}}4}}\right.\kern-1.2pt}4}+\delta,}&{{\rm{for~{}}}\pi{\rm{/2~{}phase~{}shift,}}}\\\
{{L_{2}}={{{\lambda_{\rm{c}}}}\mathord{\left/{\vphantom{{{\lambda_{\rm{c}}}}2}}\right.\kern-1.2pt}2}+\delta,}&{{\rm{for~{}}}\pi{\rm{~{}phase~{}shift,}}}\\\
{{L_{3}}=3{{{\lambda_{\rm{c}}}}\mathord{\left/{\vphantom{{{\lambda_{\rm{c}}}}4}}\right.\kern-1.2pt}4}+\delta,}&{{\rm{for~{}3}}\pi/2{\rm{~{}phase~{}shift,}}}\end{array}}\right.$
(2)

where $\delta$ is the constant initial length. After the initial design phase,
the transmission lines are verified using electromagnetic simulation tools
such as CST to ensure that the intended phase shifts are accurately achieved.
During the physical implementation progress, adjustments are made as necessary
to accommodate practical factors such as fabrication tolerances and the
properties of the substrate material.

As shown in 1, the bottom layer of each unit houses three additional delay
lines, ${l_{1}}$, ${l_{2}}$, and ${l_{3}}$, with lengths of 3.84 mm, 5.64 mm,
and 7.64 mm, respectively. Each of these delay lines is connected to delay
line ${l_{0}}$ through individual PIN diodes. These PIN diodes are
independently managed by separate signal control lines, each featuring an
inductor to isolate Alternating Current (AC) RF signals and mitigate potential
interference to the Direct Current (DC) circuit. Additionally, each control
line is equipped with an LED to visually indicate the current operational
state of the patch. A via grounds the center of the rectangular patch,
completing the whole electrical circuit. Engineered to function at a frequency
of 10.7 GHz with over 200 MHz bandwidth, the unit cell is capable of four
distinct operational states by changing the ON/OFF states of the PINs. The
ON/OFF states switching of the PIN diodes forces EM waves to traverse varying
lengths of propagation paths within the unit structure, thereby imposing
different phase delays on the reflected signal. We simulate the unit cell
together with PIN diodes SMP1320 under CST Studio Suite environment, and the
results have been shown in Fig. 2. Obviously, the amplitude attenuations of
the reflected signal of the four states of each unit remain below 0.6 dB
within a 200 MHz bandwidth ($10.6\sim 10.8$ GHz), while the phase differences
are stabilized at about $90^{\circ}$ among them. It is worth noting that for a
2-bit RIS design, achieving amplitude attenuation within 1 dB is already
considered outstanding performance [13, 20, 21].

Figure 2: Phase and amplitude simulations of the 2-bit unit cell.

As we know, in recent years, research on RIS has flourished. To better
showcase the works of various researchers on reflective RIS prototypes over
the past few years, a comparative Table 1 has been created that lists the key
features of our proposed design alongside those of existing works. As shown in
Table 1, current RIS prototype research varies significantly, primarily due to
specialized designs aimed at different application scenarios. There is no
standardized design scheme at present. To match actual application scenarios,
RIS prototypes focus not only on hardware metasurface design but also on
comprehensive system engineering, which includes selecting control chips,
circuit design, software algorithms, and communication protocols among various
components. For instance, the project in [22] demonstrates an RIS-enabled
ultra-massive MIMO system in a practical testbed, and addresses practical
challenges by integrating commercial NR base stations and off-the-shelf user
equipment. In [23], Dai et al. also successfully achieve 2-bit phase shifting
using non-resonant unit cells, which contributes to the industrialization of
RIS prototyping. Then, in [24], Rossanese et al. proposed another non-resonant
RIS unit cell design based on the RF switch. The researchers in [25] and [26]
explore azimuth and elevation beam control with independent control mechanisms
and 1-bit reconfigurable unit cells. Moreover, References [27] and [28]
initially introduced the time-domain digital-coding concept for metasurfaces,
which significantly enhanced the flexibility of RIS prototypes and opened up a
new research area for future RIS applications.

Inspired by previous research, in this work, we are dedicated to introducing a
novel design concept for the RIS prototype. Firstly, We propose a more
straightforward unit cell design through the non-resonant principle to achieve
2-bit phase shifting. In our design, different phase shifts correspond to
distinct delay line paths that are independent of each other. When a PIN diode
switches to select a different path, it does not affect the other paths,
thereby minimizing the interaction between different phase states. The
switching speed of the PIN diodes is typically in the nanosecond range, which
is sufficient to ensure rapid transitions between phase states. It is worth
noting that this approach avoids the repeated adjustments of the equivalent
circuit resonance states of unit cells required by many existing works,
significantly simplifying the RIS unit cell design process.

Secondly, as shown in Table 1, numerous studies have managed to achieve multi-
bit state reconfigurability for RIS. However, to transition RIS from a
laboratory setting to commercial use, the control of RIS should not be
overlooked. Developing a mechanism to achieve more flexible and rapid dynamic
responses, enabling the RIS prototype to adapt to more complex application
scenarios, remains a challenging issue. Hence, the following sections of this
paper introduce a hierarchical control mechanism based on parallel processing
and pre-configuration. The control architecture employs multiple MCUs, each
equipped with its own storage and computational capabilities. Each follower
MCU is responsible for controlling a small subset of RIS unit cells and
operates under the directives of a leader MCU. Unlike simple registers, each
MCU in our control board has independent storage and computational resources,
enabling it to pre-configure various codebook states for the unit cells under
its control. Upon receiving instructions from the leader MCU, each follower
MCU can rapidly switch states, which significantly accelerates the transition
process.

Furthermore, in our design, each unit of the RIS can independently change its
response state under the control system, allowing for functionalities such as
rapid beam steering, near-field spot beam tracking, and vortex wavefront
rotational modulation. All these features will be sequentially demonstrated in
the following sections. Additionally, thanks to its flexible space-time
digital coding ability, our system can quickly achieve continuous rotational
speed shifts of complex vortex beam wavefront. This capability enables the
receiver to observe the effects of carrier Doppler frequency shifts in the
frequency domain. These are the distinctive features that set the RIS
prototyping and the design methodology proposed in this paper apart from
previous works.

###  2.2 Rapidly-Respond Control Circuitry with Multi-MCU

Specifically, the current RIS prototyping contains 10 $\times$ 10 RF units
with an amount of 300 PIN diodes on it, which are connected to a user-defined
core signal control board employing multi-MCU chips on it [14]. The dynamic
reconfigurable functionality relies on a meticulously designed control board,
employing 11 MSP430F5529 MCUs, where one serves as a leader MCU and the
remaining 10 functions as follower MCUs. This configuration exemplifies
distributed processing, facilitating efficient control of the whole RIS
system. As demonstrated in Fig. 3, a total of 520 output pins are formed by
soldering the Metal-Oxide-Semiconductor Field Effect Transistor (MOSFET)
circuit circuit to each General Purpose Input/Output (GPIO) pin of the MCUs.
Specifically, the main MCU has 20 GPIOs left available for controlling the PIN
diodes, and each of the 10 follower MCUs has 50 GPIOs available for use. This
arrangement provides 520 output pins, creating a sophisticated control
mechanism that can handle a multitude of patterns. The MOSFET circuit,
consisting of 1 p-channel-MOS (pMOS) and 2 resistors, triggers on negative
voltage values, which inversion of input-output logic, wherein ’0’ represents
0V and ’1’ represents 3.3V, increases the robustness of the control circuit.
While the control board possesses 520 output pins, only 300 are used,
connecting to the current RIS board’s control lines. (Actually, we over-design
the control circuitry for other potential functions in the future. As the
level of industrial completion improves, the whole control system will also
become more compact and lightweight.)

Figure 3: Demonstrating the connection relationship and signal transmitting
progress of the whole RIS system with control circuitry.

Suppose that a codebook ${{\bf{U}}^{10\times
10}}\in\left\\{{0,1,2,3}\right\\}$ can be used to represent the state of each
unit cell on the RIS board. Four numbers represent four quantized phase
states. Each unit cell is controlled by three PIN diodes, with different
ON/OFF state combinations governing the 2-bit phase transition switch. Hence,
from this codebook, the binary state of each of the 300 pins can be
determined. Binary data is then converted to hexadecimal data, ready to be
transmitted to the MCUs. The leader MCU, upon power-up, establishes a
connection with a PC via USB, employing a Universal Asynchronous
Receiver/Transmitter (UART) for data transmission. The MCUs will receive
control instructions together with the codebooks of the RIS phase patterns
from the PC. The leader MCU validates the receiving data, extracts relevant
information, and prepares it for each follower MCU. The data transmission
protocol used is Serial Peripheral Interface (SPI), promoting high-speed data
exchange. Moreover, for the control system, the codebooks are pre-loaded into
the leader MCU, which is connected to the other follower MCUs via SPI. Each
follower MCU independently controls a small subset of PIN diodes’ ON/OFF
states. Upon receiving commands, all follower MCUs can operate in parallel
without interfering with each other. This parallel processing and pre-
configuration mechanism significantly enhances the operational efficiency of
the RIS control system, thus increasing the refresh rate of the entire RIS
array.

For instance, the current control system has 9 output ports connected to the
RIS PIN diodes, with each port’s data size being 8 bits (1 byte). Assuming
that command data is sent from the leader MCU to the other 10 followers within
one clock signal, and each follower receives 9 bytes of data, the total time
taken for SPI communication is calculated based on the number of bits sent and
the baud rate (in bits per second). Therefore, for 10 followers, 9 bytes per
follower, and a baud rate of 1 Mbps, the total action time for SPI
communication can be calculated as ${{10\times 9\times 8{\kern 1.0pt}{\kern
1.0pt}{\rm{bits}}}\mathord{\left/{\vphantom{{10\times 9\times 8{\kern
1.0pt}{\kern 1.0pt}{\rm{bits}}}{1{\kern 1.0pt}{\kern
1.0pt}{\rm{Mbps}}}}}\right.\kern-1.2pt}{1{\kern 1.0pt}{\kern
1.0pt}{\rm{Mbps}}}}=$ 0.72 ms. In other words, the control system needs at
least 0.72 ms to switch to a phase distribution corresponding to a new
codebook, i.e., ${D_{\rm{t}}}=0.72$ ms which will be described in Sec. 3.
Assuming we divide the half-space served by the RIS into $P=20$ regions of
different sizes, and ${t_{\rm{d}}}=1$ ms, then the time required for the RIS
to traverse all codebooks is approximately 15.4 ms for our current hardware
design. Indeed, the RIS prototype proposed in this paper is still in the
initial stages of development, and many signal processing algorithms are not
fully embedded in the MCUs but are instead executed using LabVIEW and MATLAB,
which leads to noticeable delays in the demos. As the level of industrial
completion improves, the speed of time-domain coding processing in this RIS
prototype, which has parallel processing and pre-configuration capabilities,
will undoubtedly accelerate.

###  2.3 Simulation, Fabrication and Measurement

After fabrication and assembly, the entirety of the RIS along with its control
system is depicted in Fig. 4. The RIS panel itself measures 228 mm by 208 mm
and comprises 100 unit cells arranged in a 10 $\times$ 10 grid, in addition to
20 plug headers that serve to connect the control lines of each unit cell to
the pMOS circuit on the control board. When there is a change in the phase
state of the RIS, LEDs positioned on the backside flash in accordance with the
ON/OFF status of the PIN diodes, offering a direct method to monitor the
operational state of the entire RIS prototyping visually.

Figure 4: Fabrication of the RIS prototyping.

As we know, mutual coupling arises from the EM interaction between closely
spaced unit cells, leading to induced currents that affect the current
distribution on each unit cell. The altered current distribution due to mutual
coupling can result in phase errors and amplitude variations across the array,
which negatively impact beamforming. Increasing the spacing between unit cells
can significantly reduce coupling effects, but excessively large spacing can
lead to higher side lobes in the radiation pattern due to spatial under-
sampling. In our design, we carefully chose the unit-cell size to be
approximately $3/5$ of a wavelength. This dimension is optimized through CST
under periodic boundary conditions. The slightly larger spacing helps to
mitigate mutual coupling without significantly affecting the beamforming
performance. For the inter-state coupling, our design utilizes microstrip
transmission lines of varying lengths to achieve phase shifts. The
reconfigurable phase state of each unit cell is directly correlated with the
physical length of each transmission line, which minimizes inter-state
coupling by ensuring that each phase state corresponds to a unique and
independent transmission path.

Furthermore, the simulations were designed to verify the beamforming
capabilities of the RIS prototyping. As illustrated in Fig. 5(a), the beam
emanating from the transmitter, once modulated by the RIS, creates two energy-
dense regions. These regions materialize concurrently in front of the RIS
normal with different locations, demonstrating the RIS’s ability to serve two
distinct users simultaneously without spatial interference. This scenario,
depicted as a representative example calculated via MATLAB, showcases the
potential for generating multiple spot beamformings through the RIS by
employing various codebooks, further exemplified in Fig. 5(b) and Fig. 5(c).
In Fig. 5(b), the two spot beams are positioned on either side of the RIS’s
normal, while in Fig. 5(c), the spot beams materialize at asymmetric locations
in space, predetermined by the system’s configuration. This versatility in
beam placement underscores the RIS’s advanced beamforming potential, enabling
precise and flexible targeting to meet diverse wireless applications, e.g.,
multi-focus wireless power transfer, wireless sensor networks, and device-to-
device communications.

Figure 5: Simulation results for the 3D spot beamforming. (a) 2 spot beams
along the normal direction of the RIS. (b) 2 spot beams located on either side
of the RIS normal direction. (c) 2 spot beams positioned at asymmetric
locations in the near field of the RIS.

Additionally, a measurement experiment is set up to replicate the spot
beamforming results observed in the above simulations. As shown in Fig. 6, we
positioned a rail in front of the RIS. On the rail, there is a slider that can
move step-by-step along the rail according to the programming. A waveguide
probe mounted on the slider is connected to a spectrum analyzer to measure and
record the spatial EM signal energy at each location. The experimental setup
is designed to validate the simulation results shown in Fig. 5(a) and Fig.
5(b), corresponding to two spot beamforming schemes, i.e., one perpendicular
to the RIS plane and the other parallel to the RIS plane. In the measurement,
the same RIS phase distribution pattern was programmed into the MCUs-based
control board. As illustrated in Fig. 6(a), the linear rail was aligned
perpendicular to the RIS plane, and the waveguide probe traversed from near to
far along the rail, with the spectrum analyzer capturing the spatial energy
distribution. The corresponding measurements, presented in Fig. 6(b),
consistently revealed two prominent energy peaks at distances of approximately
0.2m and 0.5m from the RIS plane, demonstrating focused beam energy at these
points, which is consistent with the simulation results in Fig. 5(a).
Similarly, to validate Fig. 5(b), the linear rail was set parallel to the RIS
plane at a distance of about 0.3m, and the waveguide probe was programmed to
traverse from right to left. The spectrum analyzer systematically recorded the
energy distribution along this path, as depicted in Fig. 6(c). The findings,
summarized in Fig. 6(d), displayed consistent dual energy peaks flanking the
normal to the center of the RIS, confirming the simulation results in Fig.
5(b).

Figure 6: Measurement for the 3D spot beamforming. (a) Measurement along the
$z$-axis perpendicular to the RIS plane. (b) Energy distribution along the
$z$-axis, results from (a). (c) Measurement along the $x$-axis parallel to the
RIS plane. (b) Energy distribution along the $x$-axis (0.3 m apart), results
from (c). (The red vertical lines indicate the measured positions of the peak
power)

Furthermore, it is worth noting that for some reconfigurable metasurface
schemes, although each unit cell has the capability of 2-bit phase states
control, only the entire row or column of unit states can be adjusted
simultaneously due to limitations in the control system [29]. Such RIS
typically only possesses the ability for cone beamforming and cannot form spot
beams, let alone structured EM waves such as vortex beams. Structured EM
waves, characterized by the intricate phase structure within the beam,
typically necessitate RIS to have at least simultaneous 2D control
capabilities for generation. In this paper, the proposed RIS prototyping
allows each unit cell to be independently controlled, with less coupling
between different reconfigurable phase states. Fig. 7(a)(b) display two types
of full-wave simulation results generating vortex beams in the CST
environment, further demonstrating the flexible beamforming capabilities of
the proposed RIS prototyping. These results not only highlight the advanced
functionality but also its potential to significantly impact the development
of many wireless solutions by facilitating more complex and efficient signal
distribution strategies, which will be demonstrated in our experiments.

Figure 7: Generation for vortex beams under CST Studio Suite. (a) Vortex
topology mode 1. (b) Vortex topology mode 2.

##  3 RIS-based Spot Beamforming and Tracking Scheme for Rapidly-Respond
Solutions

###  3.1 Codebook Design for RIS Spot Beamforming

In general, we consider
${{2{D^{2}}}\mathord{\left/{\vphantom{{2{D^{2}}}\lambda}}\right.\kern-1.2pt}\lambda}$
as the boundary distinguishing between the far-field and near-field of the RF
transmitter, where $D$ denotes the aperture size of the radiator, $\lambda$ is
the wavelength. However, in the RIS-assisted urban wireless communication
environment, with the increase in the 2D aperture size of the RIS board and
the higher carrier frequencies, the assumption of ideal far-field
communication conditions no longer holds in practical scenarios [30, 31]. This
influence is particularly evident in the beam-steering aspect of the antenna
array. As shown in Fig. 8(a), under the traditional far-field assumptions, the
beams controlled by the transmitter are cone-shaped beams, i.e., the receiving
users are at specific angular directions of the transmitter. In some specific
scenarios, such as serving far-field users with a 2D directional beamforming
requirement, the unit cells distributed in a particular column or row on the
RIS might exhibit an approximately identical phase distribution. This could
simplify the control circuit of the RIS. Nonetheless, for comprehensive beam
steering at both azimuth and elevation angles, the phase profile requires
individual configuration of each unit cell, which also demands a more complex
control mechanism [25, 26]. Generally, in real-world applications, especially
in congested urban environments, both the transmitter and receiver are in the
near-field region of the metasurface [32]. In 2023, Sadeghian et al. discusses
the impact of RIS in indoor environments and suggests that a significantly
large RIS might be necessary to make a noticeable difference compared to
ambient propagation [33]. In this scenario, what is incident on the RIS board
is no longer a planar wave but a spherical wavefront with a structured phase.
As demonstrated in Fig. 8(b), beamforming is affected not only by the angular
dimension but also by the distance. It has evolved from traditional 2D beam
scanning to 3D spatial beam focusing. In this context, distinct from
traditional cone beamforming, the new RIS-based codebook design can be
referred to as spot beamforming.

Figure 8: 2D directional beamforming vs. 3D spot beamforming.

In the Cartesian coordinate system, assume that the center of the RIS as the
coordinate origin, the coordinates of each unit cell on the RIS board can be
represented by
${{\bf{u}}_{m,n}}=\left({{x_{m,n}},{y_{m,n}},{z_{m,n}}}\right)$,
$m\in\left\\{{1,2,\ldots,M}\right\\}$, $n\in\left\\{{1,2,\ldots,N}\right\\}$,
$M\times N$ is the total number of the discrete unit cells on the RIS board,
and the transmitter’s coordinates relative to the RIS are denoted as
${{\bf{u}}_{\rm{T}}}=\left({{x_{\rm{T}}},{y_{\rm{T}}},{z_{\rm{T}}}}\right)$.
Then, the half-space served by the RIS can be partitioned into $P$ distinct
receiving regions based on varying angles and distances. We can assume the
coordinates of the center of each receiving region as
${{\bf{p}}_{i}}=\left({{x_{i}},{y_{i}},{z_{i}}}\right),{\kern 1.0pt}{\kern
1.0pt}i=1,\ldots,P$. Evidently, the number of codebooks recorded by the RIS is
directly associated with the granularity of spatial partitioning. Each
codebook essentially corresponds to a 2-bit quantized phase distribution state
on the RIS board.

Without loss of generality, assume that the RIS is placed at the $x$-$y$
plane. Generally, the positions of the transmitter and RIS are relatively
fixed. Based on pre-defined coordinate positions, it is straightforward to
calculate the geometric distance from the transmitter to each unit on the RIS
as,

${d_{m,n}}=\sqrt{{{\left({{x_{\rm{T}}}-{x_{m,n}}}\right)}^{2}}+{{\left({{y_{\rm{T}}}-{y_{m,n}}}\right)}^{2}}+{{\left({{z_{\rm{T}}}-{z_{m,n}}}\right)}^{2}}}.$
(3)

Then, the electric field reaching the $m$-th row and $n$-th column of the RIS
can be calculated as,

$\vec{E}\left({m,n}\right)=\frac{{G\lambda}}{{4\pi{d_{m,n}}}}\exp\left({-jk{d_{m,n}}}\right),$
(4)

where $G$ is the propagation constant associated with physical factors such as
antenna gain and radiation pattern,
${{k=2\pi}\mathord{\left/{\vphantom{{k=2\pi}\lambda}}\right.\kern-1.2pt}\lambda}$
is the wave vector, $j$ is the imaginary unit. According to the principle of
wave interference, after reflection from all units on the RIS, the EM waves
reaching a specific spatial grid should coherently superimpose with the same
phase [34]. Let’s simplify by considering the center point of the grid as the
reference for beam interference. In this case, the propagation path difference
from distinct units to the reference point can be calculated as,

${f_{m,n,i}}=\sqrt{{{\left({{x_{m,n}}-{x_{i}}}\right)}^{2}}+{{\left({{y_{m,n}}-{y_{i}}}\right)}^{2}}+{{\left({{z_{i}}-{z_{m,n}}}\right)}^{2}}}-{z_{i}}.$
(5)

If we view the propagation of EM waves as a series of rays, in order to
compensate for the phase differences introduced by the spatial positions of
distinct unit cells during the propagation process, for each unit cell, the
required interference compensation phase offset can be got from the following
equation,

${T_{m,n,i}}=\frac{{{{\left({4\pi}\right)}^{2}}{d_{m,n}}{d_{m,n,i}}}}{{G{\lambda^{2}}}}\exp\left({jk{d_{m,n}}+jk{f_{m,n,i}}}\right),$
(6)

where, ${d_{m,n,i}}=\left|{{{\bf{u}}_{m,n}}-{{\bf{p}}_{i}}}\right|$. If the
RIS simultaneously serves multiple users in different spatial grids, then the
compensation on each unit cell is the vector sum of the calculated results
from (6), i.e.,

${T_{m,n}}=\mathop{{\rm{quantize}}}\limits_{{\rm{2-bit}}}\left\\{{{\rm{angle}}\left[{\sum\limits_{i=1}^{P}{{T_{m,n,i}}}}\right]}\right\\},$
(7)

where $\mathop{{\rm{quantize}}}\limits_{{\rm{2-bit}}}\left\\{*\right\\}$
represents the phase bit quantization operation, which needs to be determined
based on the actual full wave phase simulation results of the unit cells.
${T_{m,n}}$ is one codebook of the 3D spot beams on the RIS. Before applying
the beam tracking algorithm, all codebooks will be pre-loaded into the MCU
controlling the RIS board.

###  3.2 RIS-based Swift Beam Tracking Scheme

In this part, we introduce a beam scanning approach aimed at tracking moving
users and sustaining ongoing communication in intricate near-field settings.
Spot beam scanning is a method where the RIS sequentially forms beams across
each pre-defined 3D spatial region within its coverage half-space. The
sequencing of the beam scanning is depicted in Fig. 9. This process is
primarily conducted during the pilot phase, where beams with varied shapes are
dispatched in a time-division fashion. Every 3D spatial region is associated
with a distinct scanning time slot, with the procedure repeating until the
complete half-space has been covered.

Figure 9: Signal frame structure and timeline for beam scanning.

The specific process of dynamic beam tracking of the mobile user based on RIS
is as follows:

  * •

First, set the spatial coordinates between the transmitter and RIS, dividing
the RIS’s coverage into $P$ zones. The transmitter sends signals as shown in
Fig. 9. After RIS beamforming, users demodulate the signal, calculating the
receiving power ${p_{\rm{r}}}$. Users set a reception power threshold
${g_{\rm{t}}}$, based on their sensitivity. If the signal power drops below
this threshold, they signal the RIS to start beam scanning.

  * •

Next, for precise beam scanning, synchronization between the user and RIS on
the scanning start time is crucial. Upon requesting a scan, the user also
sends its local time to the RIS. The user checks its time ${T_{\rm{u}}}$ and
accounts for transmission and processing delays ${t_{\rm{d}}}$, ensuring the
delay $\tau$, from when the RIS starts scanning ${T_{\rm{s}}}$ to the user’s
time, exceeds the delay time ${T_{\rm{d}}}$. Accurate time synchronization is
vital and can be achieved using the Network Time Protocol (NTP), which
synchronizes devices with time sources to ms accuracy [35].

  * •

Then, at the predetermined time ${T_{\rm{s}}}$, the RIS begins to direct spot
beams to the designated spatial regions, setting each beam’s duration to
${D_{\rm{t}}}$. This duration, ideally, is the time needed for the RIS to
adjust the reflection coefficients for its array. Starting ${T_{\rm{a}}}$ ms
after ${T_{\rm{s}}}$, the user samples data, measures its power, and logs this
as the reception power for that region. To ensure data capture and power
calculation align with the current beam’s duration, ${T_{\rm{a}}}$ must be
less than ${D_{\rm{t}}}$. The user then repeats this process every
${D_{\rm{t}}}$ ms, guaranteeing that measurements for each region are taken
within their respective beam durations.

  * •

After scanning each pre-defined spatial region, the user identifies the
receiving power for regions targeted by the converged spot beam. By comparing
these values, the user selects the beam with the highest receiving power and
informs the RIS of the selected beam ID ${B_{{\rm{ID}}}}$. The RIS then
adjusts the reflection coefficients across its array to form the beam shape
corresponding to ${B_{{\rm{ID}}}}$, completing the dynamic beam tracking
process. The total scanning duration is influenced by the delay ${T_{\rm{d}}}$
from transmission and processing, plus the cumulative scanning time for all
receiving regions, i.e.,

${t_{{\rm{tot}}}}={T_{\rm{d}}}+P\times{D_{\rm{t}}},$ (8)

$P$ RIS patterns equal to $P$ spatial receiving regions.

To clarify, the steps of the RIS-based dynamic 3D beam tracking algorithm are
listed as the Algorithm 1.

Algorithm 1 RIS-based 3D spot beam dynamic tracking.

1: INPUT: Receiving power ${p_{\rm{r}}}$, sensitivity threshold
${g_{\rm{t}}}$, user’s local system time ${T_{\rm{u}}}$, duration time
${D_{\rm{t}}}$ for each spot beam, delay ${T_{\rm{a}}}$.

2: $\textbf{While}(1)$ % keep monitoring the receiving power ${p_{\rm{r}}}$
and do sweeping if need

3: $\textbf{If}({p_{\rm{r}}}<{g_{\rm{t}}})$

4: UE Check the local system time ${T_{\rm{u}}}$;

5: Determine the time ${T_{\rm{s}}}$ to start the beam scanning, where,
${T_{\rm{s}}}={T_{\rm{u}}}+{T_{\rm{d}}}$;

6: Then do the feedback, transmit ${T_{\rm{s}}}$ from the user to the RIS;

7: Do spot beams scanning on the RIS, while calculating the receiving power on
the user;

8: $\textbf{For}({B_{{\rm{ID}}}}=0;{B_{{\rm{ID}}}}=P;{B_{{\rm{ID}}}}++)$

9: Delay ${T_{\rm{a}}}$ ms;

10: Fetch signal and calculate power on the user side, and recorded as
${u_{\rm{r}}}$;

11: Delay ${D_{\rm{t}}}-{T_{\rm{a}}}$ ms;

12: End For

13: Compare and find the largest ${u_{\rm{r}}}$, recorded as ${p_{\rm{r}}}$;

14: ${B_{{\rm{max}}}}=\max{\rm{index}}\left({{p_{\rm{r}}}}\right)$; % Find the
beam index ${B_{{\rm{max}}}}$ of the largest receiving power ar the UE side

15: Do the feedback of ${B_{{\rm{max}}}}$, from user to RIS;

16: Then RIS change to the ${B_{{\rm{max}}}}$-th pattern;

17: End While

This algorithm can be easily adapted to various RIS prototypes as a direct and
efficient method for implementing spot beam tracking, without concern for
frequency, bit quantization, or even partial components failure. The beam
shapes for different 3D regions are pre-configured into the MCUs of the RIS
prototyping, and the feedback mechanism is based on basic power threshold
detection. This means that, in practical applications, there is no need for
extensive pre-mapping or concern about random reflections affecting the
codebook shapes. It can always find a codebook shape through scanning and
achieve quick feedback and state locking (Although the codebook may not be
optimal, it definitely ensures that the spatial beam exceeds the detection
threshold at the receiver at that moment), enabling true plug-and-play
functionality for the RIS system. The implementation cost of this mechanism
involves pre-configuration of the 3D space codebooks and achieving fast
switching between them. It should be noted that, in the scanning feedback
process, we introduced a feedback principle based on exceeding detection
thresholds rather than waiting for all codebooks to be scanned and then taking
the maximum value. This significantly improves scanning efficiency and differs
from traditional codebook-based schemes. Considering the inherent error
correction mechanisms in communication systems, maintaining a certain
detection power threshold ensures stable data transmission. This robustness is
demonstrated in the following experiments, where stable tracking is achieved
even with environmental disturbances.

###  3.3 RIS-based Real-Time Tracking and Communication Experiments for Moving
User with 3D Spot beams

To verify the above algorithm, a real-time tracking and communication
experiment based on RIS for the moving user has been set up in a complex
environment filled with multi-path reflection interference. The experimental
setup is depicted in Fig. 10. The base-band signal is generated by the NI
USRP-2954, with a symbol rate of 125 kHz and 16-QAM modulation. The center
carrier frequency of the Intermediate Frequency (IF) signal is 2.8 GHz. After
frequency up-conversion by the mixer to 10.7 GHz, it is radiated into free
space by a horn antenna. The transmitting antenna is positioned 2.5 meters
away from the RIS. After modulation by the RIS, the transmitted signal is
directionally reflected to different near-field spatial regions. Another horn
antenna serves as the mobile receiving user, which will capture the RF signals
reflected by the RIS. After down-conversion, another USRP-2954 is responsible
for demodulation to recover the baseband data from the transmitter. The data
is transmitted using single-carrier transmission without channel coding. For
clarity, the main experimental parameters have been listed in Table 2.

Figure 10: The basic setup and on-site view of the experiment. Table 2: Main experiment parameters. Parameter | Value | Dimension
---|---|---
Central carrier frequency | 10.7 | GHz
Intermediate frequency | 2.8 | GHz
Samples per symbol | 8 | -
Baseband bandwidth | 125 | kHz
Tx antenna gain | 15 | dB
Transmitting power | 0 | dBm
Rx antenna gain | 15 | dB
Low Noise Amplifier (LNA) | 20 | dB
Modulation for pilot signal | 16-QAM | -
Modulation for data stream | 16-QAM | -

As illustrated in Fig. 10, the LabVIEW interface connected to USRPs allows the
real-time observation of the demodulation constellation and Rx eye diagram. At
the transmitter, a set of random sequences is cyclically transmitted as the
original communication data in this experiment. The receiving user stores
sufficiently long sequence data and systematically compares it with the
original transmitted sequence to statistically evaluate the demodulation Bit
Error Rate (BER) performance. During the experiment, the spatial position of
the horn antenna is changed to simulate the random movement of the mobile
user. During the movement, the RIS together with its control system
dynamically changes the codebook state in real time based on the pre-defined
algorithm illustrated in Sect. 3. Then, the shape of the reflected beams will
be altered, enabling the tracking of the user’s movement and achieving real-
time stable data transmission (Experiment record video in
https://youtu.be/riBH0YZBXtk).

It should be noted that some tracking delays were observed during the
experiment, primarily attributable to the lower completion level of our
prototype. In this setup, significant time was consumed by data collection and
command execution processes within LabView and MATLAB. However, in the
commercial product phase, the time required for the RIS to reconfigure itself
would be considerably reduced, as all algorithms would already be embedded
into the MCU chips. Furthermore, when the RIS is implemented in a real mobile
network, it will include data packet redundancy and retransmission protocols.
These mechanisms will ensure the complete reception of useful information,
even in the event of brief link interruptions, thereby maintaining the actual
communication experience of the mobile users.

Without loss of generality, considering the RIS center as the origin, we
selected four spatial coordinates at varying distances and heights from the
RIS to verify the 3D spot beamforming efficiency, namely,
${{\bf{p}}_{1}}=\left({-0.8,0.2,1.5}\right){\rm{m}}$,
${{\bf{p}}_{2}}=\left({-0.8,-0.2,1.2}\right){\rm{m}}$,
${{\bf{p}}_{3}}=\left({0.7,0.4,1.8}\right){\rm{m}}$,
${{\bf{p}}_{4}}=\left({1.0,-0.2,1.7}\right){\rm{m}}$. Subsequently, the RX
antenna is sequentially moved to the corresponding coordinates, as shown in
Fig. 11.

Figure 11: Measurement scenarios at different 3D spatial receiving regions
with respect to (a) location ${{\bf{p}}_{1}}$ (b) location ${{\bf{p}}_{2}}$
(c) location ${{\bf{p}}_{3}}$, and (d) location ${{\bf{p}}_{4}}$. (Tx antenna
gain 15 dB, Tx power 0 dBm, Rx antenna gain 15 dB, Rx LNA 20 dB, bandwidth 125
kHz)

In the experiments, we measure and compare the Received Signal Strength
Indicator (RSSI) under both RIS ON (optimized) and OFF states. The actual
measurement results from different 3D spatial regions are recorded in Fig. 12.
It is obvious that when the RIS is in the OFF state or ON (optimized) state,
the RSSI in the corresponding reception region differs by more than 10 dB.
Then, at each of the four distinct spatial regions, the user antenna holds for
a few seconds, ensuring that the receiving USRP collects and records a
sufficient length of the receiving data for BER calculation. The statistical
results are also depicted in Fig. 12. Obviously, when RIS is ON (optimized)
with the specific spot beam pattern, the BER statistical results at all
reception regions are far below the Forward Error Correction (FEC) limit
($3.8\times 10^{-3}$) [36], indicating that the RIS can automatically adjust
the optimal codebook with the movement of the user, achieving beam tracking
and ensuring the stability of communications. When the RIS is in the OFF
state, the receiver cannot capture sufficient signal energy, resulting in a
severe deterioration of the constellation diagram and BER metrics.

Figure 12: The constellation diagrams and BER measurement results at different
3D spatial receiving regions when the RIS is OFF and ON (optimized). (a) BER
comparing results at different spatial locations. (b) Constellation diagrams,
EVM, and RSSI measurement results.

##  4 Rotational Vortex Wavefront Manipulation through Space-Time Digital
Coding on RIS Prototyping

Moreover, to substantiate the rapid-response programmable and full-array
independent control capacities of the RIS prototyping developed in this study,
we utilize a phase-shifting scheme for producing time-varying rotational
vortex beams. This approach leverages the unique properties of vortex beams,
which possess orbital angular momentum owing to their helical wavefronts, to
subtly and swiftly modulate the phase distribution throughout the RIS board.

Vortex beams, also known as Orbital Angular Momentum (OAM) beams, are
characterized by a helical phase front. The phase of the beam twists around
the beam axis, resulting in a spiral wavefront. These beams carry OAM, which
can be utilized for various advanced communication techniques [37]. The fast
rotation of the wavefront in vortex beams creates a dynamic phase variation
over time. When the RIS is used to generate and manipulate these vortex beams,
it can induce rapid changes in the phase distribution of the reflected waves.
This rapid phase variation is analogous to the Doppler shift, in other words,
the rotational wavefront of the OAM beam causes the carrier phase to change
more rapidly over time, resulting in a shift of the carrier’s central
frequency in the frequency domain. This has been verified by a lot of previous
studies [38, 39, 40, 41]. Therefore, in the Doppler domain, by rotating the
vortex beam’s wavefront, we can effectively modulate the signal frequency. The
rotation speed of the wavefront and the OAM topological mode determine the
rate of this modulation, creating a Doppler-like effect even in the absence of
actual motion. This technique can be employed to modulate signals for various
applications, such as enhancing communication robustness or encoding
additional information in the phase of the signal.

Figure 13: Spinning vortex beams to generate rotational Doppler shift based
highly dynamic RIS and phase-shifting scheme. (a) $l=1$, $t=0$. (b) $l=1$,
$t=T/6$. (c) $l=1$, $t=2T/6$. (d) $l=1$, $t=3T/6$. (e) $l=1$, $t=4T/6$. (f)
$l=1$, $t=5T/6$.

###  4.1 Rotational Vortex Beams Generation by RIS

As we know, by introducing an azimuthal phase factor, $\exp\left(*\right)$,
into an EM beam, it is possible to generate an orbital angular momentum EM
wave with a helical phase front. Traditional time-invariant azimuthal phase
factors can be represented as $\exp\left({jl\phi}\right)$, where $l$ denotes
the topological mode of the vortex beam, and $\phi$ is the azimuthal angle.
Then, the vortex beam can be expressed as,

$E\left({\phi,t}\right)={A_{\rm{e}}}\exp\left({j2\pi{f_{0}}t}\right)\exp\left({j\delta\left(\phi\right)}\right),$
(9)

where ${A_{\rm{e}}}$ is the amplitude constant related to the antenna system,
${f_{0}}$ is the center carrier frequency. Hence, the entire metasurface can
be divided into 4 distinct regions along the azimuths direction, corresponding
to 4 continuously varying phase states, thereby generating vortex beams, as
shown in Fig. 14.

Figure 14: Vortex beam generation with RIS. (a) Phase distribution on the RIS.
(b) Unit states illustrations. (c) Energy distribution in a cross-section
perpendicular to the beam propagation direction. (d) Radiation pattern of
vortex mode 1.

By further introducing time-varying characteristics and sequentially altering
the initial phase of the azimuthal phase factor across different time slots,
we can achieve a spatiotemporally modulated phase, which has been illustrated
in Fig. 13. This modulated phase, which incorporates both spatial and temporal
variations, can be expressed as,

$\delta\left({\phi,t}\right)=jl\phi+2\pi l\cdot t/T{\rm{+}}\Delta,$ (10)

where $T$ denotes the period of rotation, $t$ is the time variable, $\Delta$
is the random initial phase. Furthermore, by differentiating (10) with respect
to time, we can derive the expression for the Doppler frequency shift induced
by the rotation of an EM beam carrying a vortex wavefront. Specifically, this
can be represented as,

$\Delta
f=\frac{1}{{2\pi}}\frac{{d\delta\left({\phi,t}\right)}}{{dt}}=\frac{l}{T}.$
(11)

It is evident that the magnitude of the Doppler frequency shift is jointly
determined by the temporal modulation period $T$ of the RIS and the vortex
topological mode number $l$.

###  4.2 Artificial Doppler Shift Measurement with Highly Dynamic Time-Varying
Rotational Vortex Beams

Through precise alterations of the time-varying vortex beams generated by the
RIS, we achieve dynamic control over artificial Doppler shifts within the
signal frequency domain. This capability not only demonstrates the RIS
prototyping’s highly dynamic beamforming potential but also highlights its
utility in enhancing various application scenarios through sophisticated
manipulation of EM waves, e.g., Doppler radar velocity deception and stealth
[40, 41]. A specific example has been illustrated in Fig. 13, which describes
how we rotated the vortex beams in detail, and the artificial Doppler
experiment setup and measurement results are shown in Fig. 15 (Video recorded
in https://youtu.be/IJDO-I-umaI).

Figure 15: Measured spectrum with rotational Doppler generated by the RIS
prototyping. (a) Vortex beam experiment setup. (b) Single carrier without
Doppler shift. (c) Single carrier with rotational Doppler shift. (Tx antenna
gain 15 dB, Tx power 10 dBm, Rx antenna gain 15 dB, Rx LNA 20 dB, single
carrier).

In our experiments, we utilized a spectrum analyzer (Agilent E4440A) to
measure the center frequency of the single-carrier signal reflected by the RIS
in a stationary state, as well as the frequency spectrum of the signal when
the RIS was in space-time digital-coding states. The comparative results of
their spectra are illustrated in Fig. 15(a)(b). It is distinctly observable
that when the RIS generates a vortex undergoing rapid wavefront rotation
through space-time digital-coding, the center frequency of the carrier signal
shifts by $\Delta f=12$ Hz. In the experiment, we employed rapid switching
among 12 different vortex wavefront states ($l=1$) continuously, implying that
the time required for the RIS to switch between each vortex state is
approximately $\frac{1}{{12\times\Delta f}}$ seconds. This observation aligns
with the calculations presented in Section II B, further corroborating the
rapid-response control capabilities of our RIS prototype for EM beam
manipulation. Moreover, this experiment demonstrates that by adjusting the
temporal modulation parameters and selecting specific vortex modes, it is
possible to finely tune the Doppler shift. This experimental evidence
highlights the prototyping’s advanced functionality in precisely manipulating
electromagnetic waves, demonstrating its potential for high-speed, dynamic
wireless communication applications. This research blurs the boundary between
RF antennas and digital signal processing, offering a new perspective for
studying encoded EM environment signal processing. Some new digital signal
processing algorithms can be designed based on this finding, e.g., OTFS
technology applied in low mobility scenarios based on artificial Doppler shift
generated by RIS-OAM system [42].

##  5 Outdoor Far-Field Beamforming Testing under Blocking Scenarios

Furthermore, for outdoor far-field application scenarios, our RIS prototyping
also demonstrates its ability to efficiently distribute energy to specified
areas through the manipulation of beam directions. This capability is
particularly important for non-line-of-sight users obstructed by buildings. To
validate the capability of the RIS board with this $10\times 10$ size to
modulate radio waves in natural environments, we conducted a comparative
validation experiment on an outdoor balcony and corridor near our lab, as
shown in Fig. 16. This approach ensures that the RIS’s effectiveness in
manipulating EM waves is tested under conditions that closely mimic real-world
scenarios, thus providing a robust assessment of its practical application
potential in outdoor wireless scenarios. To mitigate interference with other
commercial frequency bands, all the outdoor experiments are operated in the
X-band. The transmission setup features a reflector antenna that emits a
single-carrier signal directly from the RF signal source with an extremely
narrow beam illuminating the RIS board. This signal follows a line-of-sight
path to the RIS, which then reflects it toward receivers located in the
corners of the corridor. At the receiving end, a standard-gain directional
horn antenna captures the signal. Notably, due to obstructions like wall
corners and the directional characteristics of the antennas, there is no
direct line-of-sight connection between the transmitter and receiver.

Figure 16: RIS comparative experiments in the outdoor far-field scenario. (a)
Diagram of the experimental setup. (b) The line-of-sight corridor without
reflective objects. (c) The line-of-sight corridor featuring a metal plate of
the same size as the RIS to enhance signal reflection. (d) The line-of-sight
corridor utilizing the RIS to modulate signal reflection. (Tx reflector
antenna gain 30 dB, Tx power 20 dBm, Rx antenna gain 15 dB, Rx LNA 20 dB,
single carrier)

To provide a comparative analysis with the RIS-aided communication link, we
set up two additional scenarios as control groups, as depicted in Fig. 16(b)
and 16(c). In scenario Fig. 16(b), no reflective objects are placed directly
in front of the transmitter. The signal is emitted by the Tx antenna from a
balcony on one side of the building, traverses the corridor, and radiates into
free space from a balcony on the opposite side. In contrast, scenario Fig.
16(c) features a metal plate of similar dimensions positioned at the same
location as the RIS along the direct signal propagation path. Upon reflecting
off the metal plate, the energy of the signal is captured by the receiving
antenna at both mirrored and non-mirrored reflection directions, which is then
compared to the scenario with an RIS present, as shown in Fig. 16(d). At the
receiver’s location, a spectrum analyzer is employed to record and compare the
variations in reflected signal energy. The experimental results are tabulated
in Table 3.

Table 3: Receiving power captured by the microwave analyzer (Keysight, N9917A) in testing scenarios shown by Fig. 16. Scenarios | Rx 1 | Rx 2
---|---|---
No reflective objects | -61.8 dBm | -60.7 dBm
Rx 1 at about $0^{\circ}$ to metal plate | -45.1 dBm | NA
Rx 1 move $15^{\circ}$ to metal plate | -54.7 dBm | NA
RIS beam sweep to Rx 1 ($+45^{\circ},4m$) | -46.6 dBm | -55.2 dBm
RIS beam sweep to Rx 2 ($-30^{\circ},4m$) | -54.3 dBm | -45.8 dBm

From experimental results, it’s evident that in the absence of any reflective
objects along the direct line-of-sight path, the receiver can only receive the
signal power around -60 dBm by random reflections. When a metal plate is
introduced into this direct path, a noticeable increase in received power to
approximately -45.1 dBm is observed along the normal direction of the metal
plate. However, as one deviates from this normal direction, the received
signal power rapidly diminishes. This suggests that the metal plate can only
provide specular reflection and is not adaptable to mobile communication
environments. Subsequently, we replaced the metal plate with an RIS panel of
equivalent dimensions and positioned the receiver at angles of $-30^{\circ},4$
m and $45^{\circ},4$ m relative to the RIS. By employing MCUs-controlled RIS
to steer reflected beams to various locations, significant variations in
received power were observed, as detailed in Table 3.

For instance, when the RIS adjusts the direction of the reflected beam towards
$+45^{\circ}$, the received power at Rx 1 is approximately -46.6 dBm.
Conversely, when the beam is steered towards a non-mirror-symmetric angle,
i.e. $-30^{\circ}$ direction, the received power at Rx 1 direction drops by
about 10 dB, while the received power at Rx 2 direction elevates to -45.8 dBm.
Similarly, when the RIS-controlled beam is redirected from Rx 2 towards Rx 1,
which is not mirror-symmetric, the received power at Rx 1 increases, while the
received power at Rx 2 decreases to 55.2 dBm. It is evident that higher
receiving power leads to an improved signal-to-noise ratio, thereby enhancing
the demodulation performance at the receiver. This not only demonstrates that
our RIS prototyping offers flexible beamforming capabilities, but also proves
that even under outdoor far-field conditions, an RIS board of this size can
still provide a considerable increase in received power for obstructed users.
This has significant implications for deep coverage and ensuring communication
quality in mobile communication scenarios.

It is worth emphasizing that while a simple metal reflector can provide basic
signal reflection, RIS technology offers significant advantages that justify
its practicality and necessity. RIS provides dynamic beamforming and steering,
allowing it to adjust the phase and amplitude of reflected signals in real-
time, optimize signal strength, and coverage dynamically. Additionally, RIS
actively mitigates interference, improves energy efficiency through targeted
reflection, and supports advanced functionalities like secure communication,
environmental sensing, and spatial modulation. Our experiments in Fig. 16 and
Table 3 demonstrate that even a small RIS prototype can enhance signals
effectively in practical scenarios, proving its superiority in dynamic and
varied real-world applications.

##  6 Conclusion and Discussion

This paper has unveiled an exhaustive exploration into the design,
implementation, and experimental validation of an innovative 2-bit
reconfigurable metasurface prototyping, characterized by its capability for
full-array flexible control and rapid-response to control inputs. This
prototyping facilitates a plethora of wireless solutions, including 3D spot
beam tracing, artificial rotational Doppler modulation by time-varying vortex
beams, and outdoor far-field beam steering. Notably, the prototyping achieves
rapid switching of the entire RIS array’s patterns of less than 1 millisecond,
which may enable it to track fast-moving targets such as small UAVs, bicycles,
and cars navigating urban roads in the future, and offer a new perspective for
studying encoded EM environment signal processing.

Central to our investigation is the introduction of a novel 2-bit phase-
quantized unit cell design which is distinguished by its capability to
maintain 4 stable phase states with ${90^{\circ}}$ differences, an energy
attenuation of less than 0.6 dB across a bandwidth of 200 MHz, and full-array
flexible independent control. By achieving such low insertion loss while
providing multiple phase configurations, our prototyping offers a robust
platform for the development of advanced wireless solutions. Supported by a
programmable hardware architecture and enhanced by the parallel processing and
pre-configuration capabilities of meticulously designed multi-MCU control
circuits, this system embodies the epitome of rapid and precise phase
adjustment capabilities. This foundation enables the execution of complex
structured EM waves, allowing for the dynamic manipulation of the EM wavefront
to meet the demanding requirements of modern wireless technologies. Moreover,
this study develops a tailored spot beamforming codebook scheme for RIS-aided
3D spot beam tracking. Introducing an adaptable and efficient RIS scanning
algorithm, this system facilitates the dynamic and robust communication link
for moving users.

Reflecting on this research, we recognize that the contributions of this paper
extend the horizons of reconfigurable metasurface technologies, offering fresh
perspectives for future explorations, e.g., integration of RIS with existing
wireless standards, high-efficient wireless power transfer, integrated sensing
and communication, etc. The promise held within the pages of this paper is but
a glimpse into the future, where the confluence of RIS and wireless
technologies transforms the landscape of how we connect, power, and perceive
the world around us.

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