Beyond 5G White Paper
Supplementary Volume“Relay and Reflector Technologies”

Version 1.0
March 7, 2024
Beyond 5G Promotion Consortium
White Paper Subcommittee

Preface .............................................................................................................................. 4
I. Analysis of Using Transmissive Metasurfaces toward Beyond 5G.............................. 8
I-1. Introduction .............................................................................................................. 8
I-2. 28 GHz-Band Experimental Trials Using Transmissive Metasurface ................ 9
I-3. Experimental Results ............................................................................................ 10
I-4. TMSs for Sub-terahertz Band toward Beyond 5G ............................................... 11
I-5. Conclusion .............................................................................................................. 12
II. High-Performance Radio Propagation Simulation Method for Path Loss Estimation................................................................................................................................ 14
II-1. Introduction .......................................................................................................... 14
II-2. Evaluation Methods ............................................................................................. 15
II-3. Comparison Results.............................................................................................. 17
II-4. Conclusion ............................................................................................................. 19
III. Relay-Related Technologies in New Radio Network Topology (NRNT) .................. 21
III-1. Introduction ......................................................................................................... 21
III-2. Experimental Evaluation of Received Power Improvement Effect Using RIS
22
III-3. Experimental Evaluation of Fast Design and Control Techniques for Wireless
Network Including Relay Nodes ......................................................................... 23
III-4. Conclusion............................................................................................................ 25
IV. Development of Meta-surface Reflectors for Millimeter-wave Mobile Communication
Systems .................................................................................................................. 26
IV-1. Introduction ......................................................................................................... 26
IV-2. Optically Transparent Dual-Band Meta-surface Reflector .............................. 26
IV-3. LC RIS .................................................................................................................. 27
IV-4. Evaluation Method of Meta-surface Reflector................................................... 29
IV-5. Conclusion ............................................................................................................ 30
V. Terminal-Collaborated MIMO Reception .................................................................. 32
V-1. Introduction ........................................................................................................... 32
V-2. System Model ........................................................................................................ 33
V-3. Subband-based Signal Processing ....................................................................... 341

V-4. Conclusion ............................................................................................................. 35
VI. Beamforming-Based IRS Control for Sub-Terahertz-Band Communications inIndoor Office Environments................................................................................... 37
VI-1. Introduction ......................................................................................................... 37
VI-2. Beamforming-Based IRS Control ....................................................................... 38
VI-3. Simulations ............................................................................................................. 39
VI-4. Conclusion ............................................................................................................ 41
VII. Beam Squint-aware Frequency Resource Allocation for IRS-aided Communication................................................................................................................................ 42
VII-1. Introduction ........................................................................................................ 42
VII-2. Performance Evaluation .................................................................................... 44VII-3. Conclusion .......................................................................................................... 45
VIII. Prototype and Evaluation of Intelligent Reflecting Surface for 60 GHz Band..... 47
VIII-1. Introduction ...................................................................................................... 47
VIII-2. Design and Simulation of Prototype IRS ........................................................ 48
VIII-3. Characterization Experiments ........................................................................ 51
VIII-4. Conclusion ......................................................................................................... 52
IX. Wireless Transport Technology for Xhaul ............................................................... 54
IX-1. Introduction ......................................................................................................... 54
IX-2. Unlicensed Band Technology for Wireless Transport....................................... 55
IX-3. Conclusion ............................................................................................................ 58
X. A Study on High-Capacity UL Communication in Relay Systems with UAV .......... 60
X-1. Introduction ........................................................................................................... 60
X-2. Proposed Placement Method ................................................................................ 61
X-3. Robust LOS-MIMO ............................................................................................... 62
X-4. Conclusion ............................................................................................................. 64
Abbreviation List ........................................................................................................... 652

【Revision History】
Ver.
Date
1.0 2024.3.7
Initial version

Contents3

NotePreface
In our published white paper “Beyond 5G White Paper ~Message to the 2030s~”, weresearched what are required in various industries in the Beyond 5G era, then we
proposed “Further enhancement of specific 5G features” such as ultra-high speed
wireless communications of 10 times faster than that of 5G, 100 times capacity larger
than 5G, and 1/100th of 5G’s power consumption. To address these targets, we needpossibility of relay and reflector technologies to realize New Radio Network Topology(NRNT) as one of key Beyond 5G technologies.
For pursuing ultra-high speed and large capacity (especially uplink) wirelesscommunications with improved reliability, it is ideal to communicate in a shorter
distance with a LOS (Line of Sight) environment (in a path with a smaller radio
propagation loss) and increase the number of paths for the wireless communications toprovide more options (more redundancy) as much as possible. Satisfying these conditions
will require a network topology distributed in the space domain. Early generations ofmobile communication systems considered it ideal to configure a cellular network withhexagonal cells to avoid inter-cell interference. In the Beyond 5G era, however, there will
be an evolution to NRNT. This new form of radio access network will be a further
extension of a heterogeneous network which has been studied since 4G, with overlapping
multiple cell areas for creating more LOS environments and path options, and with moreconnection routes to/from mobile terminals nearby as well as other networks including
Non-Terrestrial Network (NTN).
Such a spatially distributed network is considered to be compatible with highfrequency bands such as millimeter wave and sub-Terahertz bands, cell-free/distributed
MIMO, wireless sensing, and wireless power supply. On the other hand, from a commonsense viewpoint, the NRNT may not be an ideal network configuration as it generates
inter-cell interference and has many redundant base station antennas. This topology is
not immune to interference because it does not adopt advanced beam control or pathselection, or a cell configuration where each antenna forms a zone to avoid interference.
Hence, a technical solution is required to help prevent interference, such as a cell-free
MIMO configuration, which configures a cell by multiple base station antennas.
How to economically realize the NRNT is also a fundamental problem, and we canthink of various approaches to tackle this technical issue. The standard solution would
be not to use conventional base station antennas only. There are a lot of research anddevelopment activities: the use of existing objects such as streetlamps, street/traffic
lights, signboards, vending machines and window glass for antennas, integration of
sensors and antennas, relay such as IAB (Integrated Access and Backhaul) and repeaters,
reflectors such as Reconfigurable Intelligent Surface (RIS)/Intelligent Reflecting Surface(IRS), which are installed between base stations and mobile stations, and terminal

4

collaboration/inter-terminal cooperation that virtually increases the number of mobile
station antennas. In addition, it may be necessary to establish new wireless and opticalinterconnection and transmission systems which enable a distributed network topology
and have a scalability to follow future evolution of the wireless communications, as well
as fronthaul and backhaul (xhaul) technologies. By exploiting such new solutions in
combination with existing cellular configurations, NRNT can provide stable, high-speed,
and large-capacity wireless communications in addition to coverage extension regardlessof users’ locations.
To tackle these challenges and realize new use cases, there are a lot of research anddevelopment activities on the relay and reflector technologies in Japan. Note that cellfree/distributed MIMO is discussed in detail in our other white paper. In this white paper,
these research and development activities and their results with a lot of figures areshown as follows:-“Analysis of Using Transmissive Metasurfaces toward Beyond 5G” describes anovel solution that combines multiple transmissive metasurfaces
withbeamforming in a 28 GHz-band base station, and experimental results show thatthe solution using five transmissive metasurfaces can drastically improve
downlink throughput at the foot of the building.

-“High-Performance Radio Propagation Simulation Method for Path Loss
Estimation” describes a simulation technology for estimating and predicting radio
propagation characteristics with short calculation time and high accuracy for
maximizing performances, quality assurance, and efficient operation of the
Beyond 5G system with the complex and varying radio network topology.

-“Relay-Related Technologies in New Radio Network Topology (NRNT)” describes
two experimental results in indoor experimental evaluations to realize NRNT.
The first experiment examines a reception power improvement achieved bydeveloping RIS, and the second experiment assess an environmental resistanceresulting from the application of network topology control, which includes theintegration of relay nodes.

-“Development of Meta-surface Reflectors for Millimeter-wave Mobile
Communication Systems” describes a development and characterization of metasurface reflectors based on an optically transparent dual-band meta-surface
reflector and a liquid-crystal RIS. An evaluation method for the scatteringcharacteristics of the reflectors is also provided.

5

-“Terminal-Collaborated MIMO Reception” describes efficient subband-based
terminal selection schemes where the collaboration terminals in terminalcollaborated MIMO reception are selected based on the MIMO channel matrices
and the residual error coefficients. Simulation results show that the proposed
schemes have superior transmission performance compared to the conventional
schemes.

-“Beamforming-Based IRS Control for Sub-Terahertz-Band Communications inIndoor Office Environments” describes an IRS control method based on
beamforming that is realized by phases of a Butler or DFT matrix. Simulation
results show that the IRS control method reveals good performance in the sensethat a received power is not so lower than an upper bound value.

-“Beam Squint-aware Frequency Resource Allocation for IRS-aided
Communication” describes a proposed method that utilizes a beam squint toincrease the frequency efficiency by optimizing the IRS reflection direction andresource allocation. Simulation results demonstrate that the proposed method ismore effective in environments with dense terminals and high beam squint.

-“Prototype and Evaluation of Intelligent Reflecting Surface for 60 GHz Band”
describes a design and an electromagnetic simulation model of a developed
prototype IRS for 60 GHz band and the electromagnetic simulation results areshown. In addition, results of characterization experiments verify theeffectiveness of the developed IRS as a device for improving the propagation path.

-“Wireless Transport Technology for Xhaul” shows basic evaluation results of adeveloped 60 GHz wireless transport equipment for xhaul. For its application toa mobility platform, experimental results demonstrate that the use of millimeterwave sensors to predict radio quality can avoid blocking and realize seamlessradio access technology change and handover.

-“A Study on High-Capacity UL Communication in Relay Systems with UAV”
describes an optimal placement method of Relay Station (RS) such as Unmanned
AerialVehicle(UAV)

consideringthemultiplicity

of

user

equipment

accommodations and the robust LOS-MIMO to increase uplink system capacity
between RS and BS. Simulation results show the effectiveness of the proposed
optimal placement method.

6

In conclusion, as we embark on the journey towards Beyond 5G technologies, the relay
and reflector technologies emerge as one of key elements in this technological evolution.
Japan's endeavor to overcome the challenges to realize the relay and reflector
technologies, coupled with its commitment to research and development in this domain,
positions it at the forefront of this next-generation communication revolution. This white
paper aims to provide a comprehensive overview of the potential, challenges, and future
directions of the relay and reflector technologies for Beyond 5G, with a particularemphasis on their initiatives and advancements in Japan.
This White Paper was prepared with the generous support of many people who
participated in the White Paper Subcommittee. The cooperation of telecommunicationsindustry players and academia experts, as well as representatives of various industries
other than the communications industry has also been substantial. Thanks to everyone’s
participation and support, this White Paper was able to cover a lot of useful information
for future business creation discussions between the industry, academia, andgovernment, and for investigating solutions to social issues, not only in thetelecommunications industry, but also across all industries. We hope that this White
Paper will help Japan create a better future for society and promote significant global
activities.
Satoshi Suyama
NTT DOCOMO, INC.

7

I. Analysis of Using Transmissive Metasurfaces toward Beyond 5G
Kenta Goto, Satoshi Suyama
NTT DOCOMO, INC.
Daisuke Kitayama
NTT Device Technology Labs., NTT Corporation.

Abstract— Toward further enhancement of 5G and Beyond 5G/6G, metasurface andreconfigurable intelligent surface (RIS) have been attracting much attention thanks tocost-effective and energy-efficient features. Experimental trials have been conducted toverify their effectiveness. In consideration of a legacy deployment, it is difficult to createa coverage area at the foot of a building in millimeter-wave (mmW) bands. Thus, for
mmW coverage enhancement, we propose a novel solution that combines multiple
transmissive metasurfaces (TMSs) with beamforming (BF) in a base station (BS). To
verify the effectiveness of our proposed solution, experimental trials using a 28 GHzband 5G BS and a user equipment were conducted. The BF function selectively aims thebeam at one of five TMSs, and then TMS re-directs the radio wave to the foot area. This
paper introduces an overview of the trials and shows downlink throughput measured in
the trials. In addition, toward 6G, novel design methodology of TMSs for sub-terahertzband and its effectiveness are introduced.
I-1. Introduction
In order to meet various use cases for further enhancement of 5G (5G Evolution) and
Beyond 5G/6G, a future radio access network that can flexibly realize a variety of higher
requirements is expected to be required. In recent years, a technical concept called New
Radio Network Topology (NRNT) has been proposed to improve performances of radio
access technologies (RATs) by increasing the number of line-of-sight (LOS) paths
between multiple base station (BS) antennas (replacements) and a target user
equipment (UE) and providing more room for path selection [1].
Elemental technologies for NRNT are metasurface and reconfigurable intelligent
surface (RIS). Metasurface, an artificially engineered material, is comprised of a set of
periodically arranged wavelength-order-sized unit cells and is a passive device. RIS iscapable of adaptively manipulating incoming radio waves by using external stimuli andis an active device. It can improve various radio access performances, and thanks to costeffective and energy efficient features, a great deal of studies have been reported inrecent years [2]-[7].
In the case of service area deployment in outdoor, it is difficult to create a coveragearea at the foot of a building, when a base station (BS) is installed on the rooftop of thesame building. High frequency bands such as millimeter-wave (mmW) band have8

significant distance attenuation and linearity, and this technical issue becomes more
pronounced as the frequency is higher. To solve this problem, the authors propose a new
solution that combines a beamforming (BF) function in BS with multiple transmissive
metasurfaces (TMSs). In order to demonstrate the effectiveness of the proposed solution,
28 GHz-band experimental trials were conducted from October to November 2022 [8]. A
28 GHz-band 5G non-stand-alone (NSA) BS and a UE were used. BS with the BF
function was deployed inside the building of DOCOMO R&D Center, and five TMSs wereattached to a glass window in front of BS. This paper shows transmission performances
measured by mmW experimental equipment of 5G BS and UE. Through theexperimental trials, it is cleared the proposed solution can expand a mmW coverage areaat the foot of the building in an indoor to outdoor scenario. Moreover, for sub-terahertzband toward 6G, we introduce our design methodology that is twisted metasurface
structure and a backside polarization layer and experimentally confirm the effectivenessof this approach. The proposed structure is robust against interlayer alignment errors.
I-2. 28 GHz-Band Experimental Trials Using Transmissive Metasurface
The authors have proposed a novel cost-effective massive MIMO (mMIMO)
transmitter architecture exploiting RIS for 6G in the high frequency bands, which iscalled RIS-aided mMIMO [5]. In RIS-aided mMIMO, a small-size phased array antenna
performs the first BF, and then multiple transmissive RISs carry out the second BF toadaptively control the beam generated by the first BF. For example, the RIS-aided
mMIMO using above 2-step BF procedure generates a pencil beam for long-distancetransmission or orthogonalizes spatially multiplexed MIMO streams to achieve extremely
high capacity for 6G. However, it is not easy to apply the proposed RIS-aided architecture
to a current experimental equipment of BS. Thus, in order to evaluate the potential of the
RIS-aided architecture by an experimental trial, a simplified architecture that combines
the first BF procedure with multiple passive TMSs is proposed in this paper. The BF
function in BS directs the beam to the multiple TMSs, allowing the radio waves throughTMSs to reach UEs which are located at the foot of the building. TMSs are designed tore-direct the incident waves to the downward direction. Especially in the high frequency
bands, it is inherently difficult to directly deliver the radio waves to the foot area. In
addition, detailed characteristics of each TMS can designed individually, and the BF
function selects the best TMS among the multiple ones based on the maximum received
power criterion, when the number of beams is one (single-beam transmission) and the
distance between BS and TMSs is not so long. Of course, the number of the selected TMSs
strongly depends on the number of beams in BS and the distance. To demonstrate theeffectiveness of the simplified architecture with BF and TMSs, the mmW experimental
trials were conducted from October to November 2022 at the DOCOMO R&D Center in

9Kanagawa Prefecture, Japan. Fig. I-1 shows the configuration of the experimental trials.
A 5G NSA BS and a commercially available UE were used as the experimental equipmentin the trials. BS was deployed inside the building of the DOCOMO R&D center with the
BS antenna facing horizontally parallel to the ground surface without antenna tilt, andfive TMSs were attached horizontally based on the intersection of a glass window in frontof BS and the extension of the central axis of the BS antenna. The distance between BS
and the window glass (TMSs) is set to 0.9 m and the BS antenna height is approximately
20 m. A trolley with UE was moved at a speed of approximately 5 km/h within thepremises of the DOCOMO R&D center including the foot of the building and on the
sidewalk, near the building. UE measured DL throughput. In the trials, to reduce an
influence of the human shielding caused by the measurer, the trolley was always pulledin the direction away from BS. UE was oriented to match the direction of the person
moving the trolly, assuming that a person was operating a smartphone. UE was also
adjusted to be almost 1.2 m high by using a styrene foam, and a laptop personal computer
was connected to UE for the measurement. Main specifications of the BS equipment aresummarized below. The center frequency and the system bandwidth are set to 27.65 GHz,and 300 MHz, respectively. The BS antenna is mMIMO having 512 antenna elements intotal, 256 elements per polarization, and it has analog BF function. It can transmit up to
two streams for the MIMO spatial multiplexing. Note that the center frequency and thesystem bandwidth in LTE are 2667.5 MHz, and 5 MHz, respectively.
BS

8m
Glass window

Transmissive
Metasurface

BS
0.9 m

OutdoorIndoor20 m(b) Front view from BS.
(a) Side view.

Fig. I-1. Experimental environment.
I-3. Experimental Results
Let us show some experimental results measured in mmW experimental trials
exploiting five TMSs. The heat maps of the DL throughput are shown in Fig. I-2. The
white box in Fig. I-2 is a target area that can be expected to be improved based on thedesign of TMSs and is in NLOS environments. Fig. I-2 (a) show that approximately 1
Gbps maximum DL throughput can be achieved in the target area and that the DL

10throughput drastically increases thanks to TMSs, compared to the result of legacy
deployment shown in Fig. I-2 (b) which describes the DL throughput when BS was
deployed on the rooftop of the building which is almost 28 m high. Since the trial was
conducted on different dates, January 2023, the trees around the measurement area were
cut down, and thus the blocking effect of the trees must be reduced. In addition, BS
performances were improved by updating the software installed into BS. However, from
Fig. I-2 (b), it can be seen that the measured DL throughput is only a few Mbps at thefoot of the building, and that it is difficult to create 28 GHz-band coverage area at the footof the building. Therefore, the combination of the BF function in BS and multiple TMSs
is considered to be a great effective solution toward realizing the mmW coverageenhancement.

(a) With TMSs.

(b) Legacy deployment (installed on therooftop of the building).
Fig. I-2. Heatmap of DL throughput.

I-4. TMSs for Sub-terahertz Band toward Beyond 5G
As described in the previous sections, TMS is effective in optimizing millimeter-wave
coverage. It can be inferred that sub-terahertz band, which are being considered for use
in 6G systems, will face the same coverage challenges as millimeter-wave band. TMS
becomes even more important in 6G systems because the higher the frequency, thegreater the impact of TMS on the wireless environment for the same aperture size. In
the previous sections, the propagation direction was determined based on thetransmission intensity profile. However, to improve the aperture efficiency, it is betterto determine the propagation direction based on the phase profile.
Huygens metasurfaces are promising to make transmission phase profiles with low
loss because they allow for phase design in the range of 2 while still matching the freespace wave impedance. Some works have reported the implementation of this approachwith two metal layers on a single substrate [6]. However, a Huygens metasurface uses
both electric and magnetic resonance simultaneously to obtain the desired impedance,
which requires high alignment precision between the layers. Static-type TMSs applied
to window glass or walls should be inexpensive and easy to fabricate from industrial
perspective.

11In [7], twisted metasurface structure and a backside polarization layer are used toefficiently make a transmission phase profiles by using scattered waves of polarization
orthogonal to the incident waves as transmitted waves (Fig. I-3 (a)). A 1-bit 0/ phaseprofile can be made with low loss of less than 1 dB by simply changing the twist directionof the structure, enabling a focusing and deflection function at 110 GHz as shown in Fig.
I-3 (b). This structure is robust to interlayer alignment errors because the scattering
phase is independently determined only in the metasurface layer, while the polarizer isused only to improve the efficiency, which is an advantage from a fabrication point ofview.

Fig. I-3. (a) Geometry of the twisted metasurface and simulated electric charges
excited by incident waves. (b) Zone patterns for the twist direction and measured Efield distributions [7].
I-5. Conclusion
For 5G Evolution and 6G, in order to demonstrate and evaluate the effectiveness ofthe proposed solution which combines the BF function in BS with multiple passive TMSs,
the mmW experimental trials have been conducted. The trials employ the 5G NSA 28
GHz-band BS that supports the analog BF and the commercial UE as the experimental
equipment. When BS was installed on the rooftop of the building, only a few Mbps of DL
throughput was achieved at the foot of the building, indicating that it is difficult to create
the mmW coverage area at the foot. On the other hand, the trials with the proposedsolution using the five TMSs showed that almost 1 Gbps maximum DL throughput wasachieved in the target area. Moreover, for utilization of TMSs in much higher frequency
band such as sub-terahertz band toward 6G, we show cost-effective metasurface
structure and its effectiveness from a fabrication point of view.

12

REFERENCE[1] NTT DOCOMO, INC., “White paper: 5G Evolution and 6G (version 5.0),” Jan. 2023.
[Online]. Available:
https://www.nttdocomo.co.jp/english/binary/pdf/corporate/technology/whitepaper_6g/D
OCOMO_6G_White_PaperEN_v5.0.pdf[2] M. D. Renzo, M. Debbah, D.-T. Phan-Huy, A. Zappone, M.- S. Alouini, C. Yuen, V.
Sciancalepore, G. C. Alexandropoulos, J. Hoydis, H. Gacanin, J. d. Rosny, A. Bounceur,
G. Lerosey, and M. Fink, “Smart radio environments empowered by reconfigurable AI
meta-surfaces: an idea whose time has come,” EURASIP J. Wireless Commun. and Netw.,
vol. 2019, no. 1, pp. 1-20, Dec. 2019.
[3] Q. Wu and R. Zhang, “Towards smart and reconfigurable environment: Intelligent
reflecting surface aided wireless network,” IEEE Commun. Mag., vol. 58, no. 1, pp. 106112, Jan. 2020.
[4] K. Goto, S. Suyama, T. Yamada, K. Arai, O. Kagaya, “Experimental Trials with
Combination of Multiple Transmissive Metasurfaces and Beamforming for mmW
Coverage Enhancement,” in Proc. IEEE 98th Veh. Technol. Conf. (VTC-Fall), pp. 1-5,
Oct. 2023[5] X. Hou, X. Li, X. Wang, L. Chen, and S. Suyama, “Some observations and thoughts
about reconfigurable intelligent surface application for 5G Evolution and 6G,” ZTE
commun., vol. 20, no. 1, pp. 14-20, Mar. 2022.
[6] V. G. Ataloglou, M. Chen, M. Kim, and G. V. Eleftheriades, "Microwave Huygens’
Metasurfaces: Fundamentals and Applications," IEEE J. Microwaves 1(1), 374–388(2021).
[7] D. Kitayama, A. Pander, Y. Hama, and H. Takahashi, "Alignment-free twisted-splitring metasurface on single substrate with 2π phase range for linearly polarized subterahertz wave," Opt. Express 31, 20769-20786 (2023)[8] NTT DOCOMO Press Release, “DOCOMO conducts world's first trial of transmissive
metasurface on window to deliver indoor radio waves to outdoor foot of building,” Jan.
2023. [Online]. Available:
https://www.docomo.ne.jp/english/info/media_center/pr/2023/0130_02.html

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II. High-Performance Radio Propagation Simulation Method for Path Loss
Estimation
Takahiro Tomie, Satoshi Suyama, Koshiro Kitao, Nobuaki Kuno
NTT DOCOMO, INC.

Abstract—To establish a simulation technology for estimating and predicting radio
propagation characteristics with short calculation time and high accuracy, we haveproposed a novel color images method (CIM) based on processing colors images of wallsof buildings which are viewed from positions of Txs and Rxs. However, the estimation
performance of the proposed CIM has not been sufficiently clarified. In this work, we
compare the CIM with Wireless InSite (WI) employing a conventional ray tracing
method (RTM) in terms of estimation accuracy and calculation time. Comparison results
show that the average value and root mean squared error of path loss estimation errorsof the CIM are much smaller than those of the WI. Moreover, the calculation time of the
CIM is much shorter than that of the WI.
II-1. Introduction
In the 5G Evolution and 6G system, massive devices are connected to many basestations (BSs) directly and/or indirectly through active or passive relay stations (RSs)such as repeaters, RISs, etc. The massive radio links of BSs and devices, BSs and RSs,
RSs and devices, use various frequencies and require extreme high data rate, extreme
low latency, etc. depending on use cases [1], [2]. For maximizing the performance, quality
assurance, efficient system operation of the 5G Evolution and 6G systems, a techniquefor estimating radio wave propagation characteristics such as path loss, delay time withshort computation time and high accuracy is necessary. This method also needs to besuitable for site-specific environments of the systems using the RSs. Although there areseveral conventional estimation methods for site-specific environments such as ray
tracing method (RTM), methods based on deep learning, etc. [3]-[6], these methods still
do not satisfy the requirements of short calculation time and high accuracy. Therefore,
we proposed a new method named color images method (CIM) and evaluated its
performance in an outdoor urban environment at 1 GHz band [7], [8]. However, theestimation performance of the proposed CIM has not been sufficiently clarified.
In this work, in order to clarify the estimation performance of the CIM, we estimate
the path losses using the CIM and the RTM, and compare quantitatively the estimation
accuracy and calculation time of these methods [9].

14Fig. II-1. Position of the Tx and the measurement courses.
II-2. Evaluation Methods
II-2.1. Measured Data
Here, the measured path loss data set in [10], was used. Fig. II-1 shows the positionofthe Tx and the measurement courses. There are 40 measurement courses in total andthe courses C1-C7 are relatively long. The Tx was set on the roof top of a building with12.5 m height from the ground. The Rx was set on the roof top of a measurement carwith 1.5 m height from the ground. The Tx’s antenna and Rx’s antenna were dipole
antennas. The Rx was moved on the measurement courses to measure path loss at
frequency of 1298 MHz. After the measurement, median path loss values in 10 m length
were obtained and given a total of 839 points.
II-2.2. CIM
In this section, we describe a brief overview of the CIM proposed in [7] and its
calculation conditions. The CIM is based on processing colors images of walls of buildings
which are seen from the positions of Txs and Rxs. For detecting and calculating thescattering waves of walls, each wall of each building in an evaluation area is assigned toa different RGB color. Then, two types of color images of the walls which are seen fromthe Txs and Rxs respectively, are created as shown in Fig. II-2. Next, the scattering walls
are detected by the colors corresponding with these walls existed in both the Tx’s image
and Rx’s image. By counting the number of pixels of these colors and multiplying withcoefficients, the total received power 𝑃R at each position of the Rx can be expressed as
below:
𝑃R = ∑𝑖 𝑘 ∙ 𝐶(𝑖) ∙ 𝑁P,T (𝑖) ∙ 𝑁P,R (𝑖)

15

(1)

Fig. II-2. The color images viewed from the Tx and the Rx.

Where 𝑁P,T (𝑖) , 𝑁P,R (𝑖) are numbers of pixels of the colors corresponding with thescattering wall #i in Tx’s image and Rx’s image, respectively. The #i can be representative
for the index of the path #i. The coefficient k is depending on material of the wall, thefrequency and size of image. 𝐶(𝑖) is a coefficient related to the transmit power and thegains of the Tx antenna and Rx antenna.
To estimate the path loss using the CIM, the locations and conditions of the Tx and Rx
were set as those described in the section II. A. The number of reception points were 839.
Here, only one-time scattering was considered. The image size was 7200*3600 pixels. The
coefficient k was 10-19.8. In calculation, a PC with two CPUs included 56 cores at 2.7 GHz
was used. The memory size is 1 TB. The PC also has 4 GPU devices with 1280 cores per
device. However, due to the current implementation of the CIM, optimal use of the CPU
and GPU is not possible, so in the evaluation, only one core of the CPU and without the
GPU device were used.
II-2.3. RTM
For evaluating path loss using a RTM, we use WI employing a hybrid method of animaging method and a ray launching method [6]. Here, the positions and conditions of theTx and Rx were set as those described in the section II. A. The ray spacing was set to 0.1
degree. The maximum number of reflections were set to 1, 2, 6, and 12, and the maximum
number of diffractions were set to 1 and 2, respectively. Here, the maximum number ofreflections m and maximum number of diffractions n is denoted as mRnD. The building
material was assumed to be concrete. Moreover, the same PC also was used for bothmethods. Unlike the CIM, the WI is designed to take advantages of using the CPU andGPU devices, and minimum calculation condition is using with one core of the CPU andone GPU device. Therefore, the minimum calculation condition was used to evaluate. Itmeans that it is not fair comparison in calculation times of two methods, but theseinformation are needed for references.

16

II-3. Comparison Results
Fig. II-3 shows the comparison of the percentage of estimable reception points Ac of
the CIM and the WI. It is found that the percentage of estimable reception points of the
CIM is about 3% larger than that of the WI's 12R1D case, and in this case the differenceof two methods is the smallest. Therefore, we use the WI’s 12R1D case for comparisons ofestimation accuracy and calculation time. It is also found that the percentage Ac of the
CIM is about 19% or more smaller than that of the cases with maximum two-time
diffractions of the WI. However, by increasing the number of scattering times of the CIM,
the higher percentage Ac can be achieved.

Fig. II-3. Comparison of percentage of estimable reception points of the CIM and the WI.

Fig. II-4 shows the comparison of the estimation accuracies. It is found that the averagevalues μ and RMSE of the differences between the estimated results and the measured
results of the CIM are small at -0.8 dB and 8.3 dB, respectively, while those of the WI arevery large with 15.9 dB and 21.7 dB for the case of 12R1D and 12.7 dB and 15.1 dB for
the case of 6R2D, respectively. This means that the estimation accuracy of the CIM ismuch higher than those the WI.

17

Fig. II-5. Comparisons of estimation accuracies of the CIM and WI(a) Case of calculation from begin(b) Case of changing the condition of the Tx

Fig. II-4. Comparison of calculation times of the CIM and WI.

Fig. II-5 shows the reference result of comparison of calculation times. Here, thecalculation times are normalized to that of the CIM. As mentioned above, this is not anappropriate comparison, since both methods used one core of the same CPU to compute,but in the case of the WI, an additional GPU device is used in advantage. Therefore, thecalculation times are shown here for reference. Fig. II-5 (a) shows that, for almost thesame percentage of estimable reception points, the calculation time of the CIM is 0.77(=1/1.3) times shorter than that of the WI’s 12R1D case. It means that if the WI does not
use the additional GPU device, the calculation time of the CIM is much shorter than 1/1.3
time comparing with the WI. Fig. II-5 (b) shows the comparison of calculation times when
the conditions of the Tx are changed, such as its position or height. In these cases, thecalculation times of the CIM are 30 seconds. Here, we also normalized the calculation

18

times to 30 seconds. It is found that the calculation time of the CIM is 0.0089 (=1/112.6)
times shorter than that of the WI's 12R1D case. The reason for this is, in the CIM, theprocessing of creating color images for all reception points and analyzing color of theseimages (pre-processing), need not do again, while in the RTM, almost processes have toredo from beginning.
II-4. Conclusion
In this work, we quantitatively compared the percentage of estimable reception points,
the estimation accuracy, and the calculation time of the proposed CIM with the WI
employing the conventional RTM. The comparison results shown that, for the percentageof estimable reception points, the CIM can estimate a slightly larger than the WI withmaximum twelve-time reflections and one-time diffraction. We also shown that the CIM
has very high estimation accuracy. Moreover, it was verified that the calculation time of
the CIM is much shorter than the WI, especially in case of changing conditions of the Tx.
In future works, we plan to evaluate the estimation accuracy in various environments
and frequencies, and consider using GPU devices for real-time estimation of radio
propagation characteristics.

REFERENCE[1] NTT DOCOMO, INC. “White paper, 5G Evolution and 6G (Version 4. 0),” Jan. 2022.
https://www.docomo.ne.jp/english/binary/pdf/corporate/technology/whitepaper_6g/D
OCOMO_6G_White_PaperEN_v4.0.pdf[2] H. Tataria, et. al., “6G Wireless systems: Vision, requirements, challenges, insights,
and opportunities,” Proceedings of the IEEE, vol. 109, no. 7, pp. 1166-1199, July 2021.
[3] N. Kuno, et. al., "Deep Learning-Based Path Loss Prediction Using Side-View Images
in an UMa Environment," EuCAP2022, Mar.-Apr. 2022.
[4] S. C. Kim, et. al., "Radio propagation measurements and prediction using threedimensional ray tracing in urban environments at 908 MHz and 1.9 GHz," IEEE

Trans. Veh. Technol., vol. 48, no. 3, pp. 931–946, May 1999.
[5] T. Imai, et. al., “A Propagation Prediction System for Urban Area Macrocells using
Ray-tracing Methods” NTT DoCoMo Technical Journal Vol. 6 No.1, p. 41-51.
[6] Wireless InSite Reference Manual, Version 3.3.4.1, https://www.remcom.com[7] T. Tomie, et. al., " A Novel Estimation Method of Radio Propagation Characteristics
Based on Color Images,” VTC2022-Fall, 2022, pp. 1-5.
[8] T. Tomie, et. al., " A method of path loss prediction based on computer graphics
technologies,” IEICE Communications Express, 2023 Vol. 12, No. 6, p. 300-304.

19[9] T. Tomie, et. al., " Evaluation of High-Performance Radio Propagation Simulation
Method in Path Loss Estimation,” VTC2023-Spring, 2023, pp. 1-5.
[10] T. Imai, H. Iwai, S. Ichitsubo, "Radio Propagation Modeling Competition," IEICE

Technical Report, vol. 119, no. 28, AP2019-2, pp. 7-12, May 2019.

20

III. Relay-Related Technologies in New Radio Network Topology (NRNT)
Daisuke Murayama, Riku Ohmiya, Tomoki Murakami,
NTT Corporation
Kenta Goto, Satoshi Suyama,
NTT DOCOMO, INC.

Abstract— The New radio network topology (NRNT) in beyond fifth-generation (B5G)
mobile network is a crucial concept for the efficient utilization of high-frequency bands,
including millimeter and terahertz waves. To realize NRNT, additional technical studies
and experimental evaluations are essential, particularly concerning the integration ofrelay nodes, including reconfigurable intelligent surface (RIS). This paper presents two
experimental results conducted in indoor environments. The first experiment examines
the reception power improvement achieved by developing RIS. The second experimental
assess the environmental resistance resulting from the application of network topology
control, which includes the integration of relay nodes.
III-1. Introduction
As a technological concept transitioning from Beyond 5G to 6G, the NRNT has been
proposed. This concept aims to enhance radio access performance and reduce power
consumption by increasing links between Transmission Reception Points (TRP), such asbase station (BS) antennas, mobile terminals (MT), and relay nodes, including RIS [1-4].
Additionally, traditional wireless network topologies designed on a single-cell basis are
evolving into a novel configuration where large and small cells are superimposed. The
NRNT brings several advantages, including expanded coverage and line-of-sight (LOS)
areas, improved resistance to shielding, capacity expansion through increased multiple
input multiple output (MIMO) space multiplexing, and more.
In real-world environments, the topology dynamically changes based on factors suchas the environment, situation, and service demand. Therefore, control systems must
exhibit adaptability to temporal fluctuations. This paper introduces relay-related
technologies currently under research and development. Furthermore, we present
experimental demonstrations showcasing the reception power improvement achieved by
implementing RIS and the resistance to environmental changes achieved throughnetwork topology control in indoor environments, contributing to the realization of the
NRNT concept.

21

III-2. Experimental Evaluation of Received Power Improvement Effect Using RISThis section introduces angular profile experiments using a 28 GHz band channelsounder and presents their results to elucidate the improvement effect on reception
power when RIS are installed in indoor environments. Fig. III-1 depicts the layout of
the experimental environment at the NTT DOCOMO R&D Center and includes a
photograph for reference. In this setup, the positions of the transmitter and RIS were
fixed, while the receiver was installed in LOS and non-LOS (NLOS) conditions. The
distance from the RIS to the receiver was set at 5 m and 20 m, respectively. We conductedmeasurements of angular profiles at each receiver position with the RIS configured toreflect signals in the receiver's direction. The measurement specifications are detailed inTable. III-1.
Fig. III-1 illustrates the measured angular profile in the environment. In the LOS
condition, RIS control substantially enhanced the reception power at the receiver byapproximately 20 dB. Similarly, in the NLOS environment, RIS control led to an
improvement of around 11 dB in the reception power at the receiving station.
Consequently, even in a multipath indoor propagation environment, significant
enhancement in reception power can be achieved by dynamically adjusting the RIS basedon the receiver's position. Furthermore, since RIS control has the potential to contributeto the expansion of area coverage, promising practical applications can be anticipated in
the future.

Fig. III-1. Experimental environment.
Table. III-1. Experimental specifications.
Center frequency
Bandwidth
Transmit power
Transmit antenna (gain)
Receive antenna (beam width, gain)
Height of transmitter
Height of receiver
Height of RIS

22

27.6 GHz
200 MHz37 dBm (5 W)
Omni (3.5 dBi)
Horn (10 deg., 24.6 dBi)
1m
1m
1m

(a) 5 m position (LOS)(b) 20 m position (NLOS)
Fig. III-2. Angle profiles.

III-3. Experimental Evaluation of Fast Design and Control Techniques for Wireless
Network Including Relay Nodes
NRNT networks that use multiple relay nodes have many candidates for available
relay node locations and directions. A huge amount of calculation is required toautomatically derive an area design that combines multiple relay nodes. For this reason,
it was difficult to realize control that updates the network topology as the environmentchanges. Therefore, we devised a method to derive the sub-optimal placement
independently for each cluster using a clustering method based on unsupervisedmachine learning. This method avoids the explosion in the number of placement
combinations to be evaluated and enables fast derivation of network design. The
procedure is shown below.
(1) Search for base station placement(s) that maximize the number of evaluation
points that satisfy the required quality at the base station only, without
considering the placements of relay nodes.
(2) Using the base station placement derived in (1), eliminate from the candidates
relay node(s) placement(s) that do not result in reception quality higher than thethreshold value.
(3) Cluster the evaluation points for which the required quality was not satisfied by
the base station placement derived in (1) with the same number of relay nodes tobe used, using the kmeans++ method.
(4) Search for the relay node placements that maximize the number of evaluation
points that satisfy the required quality independently for each cluster calculatedin (3).
(5) If the ratio of evaluation points satisfying the overall required quality is above the23threshold value, the process is terminated, and if it is below the threshold value,
the process is re-derived by increasing the number of relay nodes by one.
An area quality evaluation was conducted in a shielded room at NTT Yokosuka R&D
Center by creating an environment with a lot of shielding that was simulated as anindoor logistics warehouse through experiments. We assumed an environmental change
from two rows of 1.24 m × 6.75 m × 2.5 m shields to four rows in an 11.8 m × 21.8 m ×
2.6 m shielded room. This area was covered by a local 5G base station in the 28 GHz
band connected to a WiGig AP in the 60 GHz band as a regenerative relay station. Fig.
III-3 shows the network configuration and Fig. III-4 shows the measurement scenery.
Fig. III-5 (a)-(d) show color maps of the measured throughput at each evaluation point.
Before the environmental change, the configuration without any repeaters in (a) could
not cover the entire area with high quality, but the quality of the entire area could be
improved by using a relay station as shown in (b). After the environmental change, thequality of some areas decreased without the control (redesign) in (c), but with the control(redesign) in (d) using this algorithm, the quality of all areas was maintained. The
computation time was reduced to about 1/5.5 × 10^-8 under the present experimental
conditions (896 candidate base station locations and 1776 candidate relay station
locations), compared to the method that compares and evaluates all combinations. The
above shows that the proposed algorithm can maintain high area quality while updating
the area design to follow changes in the environment.

Packetgenerator

Private 5Gbase station

Multi-radio compatible terminal(Private 5G, WiGig)
Multi-radio repeater(Private 5G-WiGig)

Packetanalyzer

Autonomous robot
Multi-radio repeater(Private 5G-WiGig)
Multi-radio repeater(Private 5G-WiGig)

Fig. III-3. Network Configuration

Multi-radio compatible terminal

Radio shields

Private 5G base station

Multi-radio repeater

Fig. III-4. Measurement scenery24

Beforeenvironmental
changeincrease inshielding

Private 5G: baseThroughput[Mbps]

station(a) w/o relay(b) w/ relay

Afterenvironmental
change:Multi-radio
repeater: Radioshields(c)w/o following control(d)w/ following control

Fig. III-5. Experimental results (throughput maps)
III-4. Conclusion
We presented experiments aimed at assessing the impact of RIS on enhancing received
power and evaluating tolerance to environmental changes through network topology
control, crucial aspects for the realization of NRNT. In the RIS evaluation experiment,
we demonstrated the dynamic alteration of the indoor propagation environment througheffective RIS control. Additionally, in the network topology control experiments, we
illustrated that a highly flexible network topology can facilitate rapid design derivationand control. Integrating these technologies, we aim to actualize NRNT-based networks
during the 5G Evolution era.
REFERENCE[1] NTT DOCOMO INC., “White Paper 5G Evolution and 6G (Version 5.0),” 2023.
https://www.docomo.ne.jp/english/corporate/technology/whitepaper_6g/.
[2] S. Suyama, M. Iwabuchi and T. Yamada, “New Radio Network Topology for 5G
Evolution and 6G,” Journal of IEICE, vol.106, No.9, pp.808-815, Sep. 2023.
[3] NTT Corporation, NTT DOCOMO INC., “NTT and NTT DOCOMO Trial First Useof User-tracking Metasurface Reflector for Extreme Mobile Coverage in Current 5G
and Coming 6G Era Will enable high-speed millimeter-wave communications
indoors,” https://group.ntt/en/newsrelease/2021/11/12/211112b.html[4] I. Masashi, et al. "Intelligent radio-wave design: Distributed intelligent reflecting
surface with direction-based control for millimeter-wave communications," IEICE
Proceedings Series 63, IA2-2, 2020.

25

IV. Development of Meta-surface Reflectors for Millimeter-wave Mobile
Communication Systems
Takuya Ohto, Hiromi Matsuno, Takahiro Hayashi,KDDI Research, Inc.
Abstract—A meta-surface reflector, which directs reflected signals to an intended
direction, has the potential to provide a low-cost and low-power option for signal coverageenhancement. This paper describes the development and characterization of metasurface reflectors based on an optically transparent dual-band meta-surface reflector
and a liquid-crystal reconfigurable intelligent surface. Moreover, an evaluation method
for the scattering characteristics of the reflectors is provided.
IV-1. Introduction
In the fifth-generation mobile communication system (5G), 28 GHz in the millimetre
wave band is assigned. In addition, a bandwidth of 15.75 GHz from the frequency band
between 24.5 GHz and 86 GHz was identified as the international mobile
telecommunication (IMT) band in the International Telecommunication Union (ITU)
World Radiome Conference (WRC)-19 [1]. Thus, the use of the millimeter wave band is
expected to increase. However, because this band suffers from high blockage loss, thereceived signal power in non-line-of-sight (NLOS) environments is significantly
decreased. To overcome this problem, a meta-surface reflector, which has an artificial
surface for reflecting signals in the nonspecular direction [2], is expected to provide lowcost and low-power consumption coverage enhancement. This reflector comprises many
passive elements, and it can reflect the incident wave towards the intended direction byadjusting the reflection phase of each element and establishing a reflection link between
a transmitter and a receiver in NLOS environments.
In this paper, the implementation and measurements of an optically transparent dualband meta-surface reflector and a liquid-crystal (LC) reconfigurable intelligent surface(RIS) are presented. In addition, to estimate the coverage enhancement by deploying thereflectors, methods for evaluating the scattering characteristics are reported.
IV-2. Optically Transparent Dual-Band Meta-surface Reflector
This section describes the dual-band meta-surface reflector [3]. Fig. IV-1 (a) and (b)show a photograph of the reflector and a schematic of its unit cell, respectively. The
reflector is designed for each 28 GHz band and the 39 GHz band. The former band has
already been assigned, and the latter band is expected to be assigned to Japan. The unit
cell comprises one cross element for the 28 GHz band and four patch elements for the 39
GHz band. The reflector also comprises three layers. Each cross element and patch26

element is designed on the top and middle layers of the reflector, respectively, with acommon ground plane designed on the bottom layer. Each layer comprises an opticallytransparent conductor sheet and is spaced with an optically transparent resin. For
reflector design, a supercell structure with a periodically designed reflection phase.
Because the ratio of the wavelengths of 28 and 39 GHz is approximately 4:3, thereflection phases of 28 GHz and 39 GHz are designed every 90 (=360/4)° and 120 (360/3)°,
respectively. For this development, the reflector is designed to reflect the signal from 0°
to 45°.

(a) Photograph.
(b) Schematic of the unit cell.
Fig. IV-1. Optically Transparent Dual-Band Meta-surface Reflector.
Field testing was conducted with the developed reflector. Fig. IV-2 shows the reference
signal received power (RSRP) at 28 GHz and 39 GHz. In the measurement, a reflector
with a size of 790 mm×810 mm is used. As the figure shows, the RSRP of approximately
10 dB is improved by the reflector in the intended direction.

(a) 28 GHz(b) 39 GHz
Fig. IV-2. The results of field test.
IV-3. LC RISIn this section, the LC RIS is introduced. Although the reflection angle of the metasurface reflector in the former section is fixed once the reflector is developed, it isdesirable to change the reflection angle based on the user’s traffic and requirements. To
address this issue, the LC RIS was developed in [4]. Fig.

27

IV-3 (a) and (b) show

photographs of the LC RIS designed for 28 GHz and a schematic of its unit cell. The
reflector utilizes LC for a reflection control functions. An LC is a molecule withanisotropy, and its electrical features, such as dielectric permittivity, depend on the
direction of the molecule. The direction of the LC molecule’s anisotropy is controlled by
the bias voltage applied to the LC, which enables the reflector to control the reflection
phase of each unit cell. As shown in the figure, the patch element is utilized not only forreflecting elements but also for the electrode for bias voltage. The bias voltage of eachreflecting element is controlled via the control board. By changing the distribution of thebias voltage, the reflection direction is controlled.

(a) Photograph.

(b) Schematic of the unit cell.
Fig. IV-3. LC RIS.

Fig. IV-4 shows the scattering pattern of the LC meta-surface reflector. Each reflection
direction is designed to reflect signals from 0 to 15, 30, 45, or 60 degrees, and themeasurement results reveal that the reflector can reflect signals in the desired direction.
Because polarized multiple-input-multiple-output (MIMO) is utilized in millimetre-wave
communication systems to deliver high-speed data transmission, an IRS must also be
applied for polarized MIMO. By changing the electric field length of the reflecting
element, an asymmetric configuration is obtained in each polarization direction, and thisreflector achieves a high cross-polarization discrimination (XPD) of more than 20 dB [4].
In addition, although an LC RIS can achieve low power consumption, there are several
challenges associated with this approach, including a high reflection loss and a longresponse time. To address the reflection loss, the author of [5] designed the unit cell ofan LC RIS to mitigate the reflection loss, and the simulation and measurement results
showed that the proposed LC RIS has a maximum reflection loss reduction of more than
10 dB. Another reference [6] similarly proposed a scattering pattern design in which thereflection phase with a high reflection amplitude was selected; moreover, experimental
measurements with an LC RIS showed that the reflection power can increase at thedesired angle. Moreover, to address its long response time, a user and passive beamscheduling scheme based on the response time of the LC RIS was proposed in [7]. The
proposed scheme selects the passive beam that provides a high data rate for multiple
users. Numerical simulations show that the proposed scheme achieves a higher

28

throughput than does the conventional scheduling scheme, if consideration of the
response time is neglected.

Fig. IV-4. Measurement results of scattering pattern of LC RIS.
IV-4. Evaluation Method of Meta-surface Reflector
To estimate the coverage enhancement due to the meta-surface reflector, thescattering characteristics of the reflector, such as the scattering pattern and path loss ofa transmitter-reflector-receiver link, must be evaluated. In this section, an estimation
method is introduced for determining such characteristics.
Table.

IV-1 shows a summary of related works on the estimation methods for

scattering characteristics. In reference [8], the path loss model of a transmitter-reflectorreceiver link was derived based on this physical optics (PO) theorem. To utilize PO, thereflection coefficient of each unit cell should be measured correctly. However, because of
the short element spacing, the reflecting element is affected by mutual coupling, andderiving or measuring the reflection coefficient, including the effects of mutual coupling,is impractical. In another approach, reference [8] reported the received power based on
the radar equation (RE) using a radar cross section (RCS) of the reflector. However,
because the RCS is defined in the far-field condition of the reflector and a large reflector
is required to provide sufficient coverage enhancement, the use of the RE is impracticalfor evaluating an actual large reflector.
To address these aforementioned problems, a practical evaluation method for an actual
large reflector was proposed in [9]. Upon assuming that the large reflector is composedof a combination of small reflectors (subreflectors), the RCS pattern of the large reflector
is estimated by synthesizing the RCS pattern of the subreflector whose RCS pattern ismeasured at the usual size in the far field of the subreflector. Using numericalsimulations and experimental measurements, the RCS pattern of the electrically large
reflector is estimated by synthesizing the RCS pattern of the subreflectors.

29

Table. IV-1. Summary of works on methods for estimating scattering characteristics.
Evaluation method
Applicable conditions
Factors influencing on
estimation error.
Physical optics [8]Both of near-field and farMutual coupling between
field of the reflector
unit cells
Radar equation [8]Far- field of the reflector
Array synthesis of
Far-field of the subreflector
Mutual coupling between
subreflectors [9]subreflectors
IV-5. Conclusion
This paper describes the implementation and measurement results of previously
developed meta-surface reflectors. To efficiently reflect signals towards intended users,
it is essential to mitigate hardware limitations associated with such reflectors. This
paper also introduces works addressing the challenges of the LC RIS, namely, highreflection loss and long response time. Furthermore, because it is necessary to estimate
the coverage enhancement by deploying reflectors to utilize meta-surface reflectors,
existing evaluation methods for scattering characteristics were reported.
Acknowledgements
A part of this research was supported by the Ministry of Internal Affairs andCommunications in Japan (JPJ000254).
REFERENCE[1]

ITU-R,“StudiesonFrequency-related

MattersforInternational

MobileTelecommunications Identification Including Possible Additional Applications to Mobile
Service on Primary Basis Portion(s) of Frequency Range between 24.25 and 86 GHz for
the Future Development of Internal Teleccomunication for 2020 and Beyond,” 2015.
[2] KDDI, Beyond 5G/6G White Paper ver.2.0.1, Oct. 2021.
https://www.kddiresearch.jp/tech/whitepaper_b5g_6g/[3] C. O. Nguyen, et al., “Dual Band and Dual Polarized Reflect Array Usimg Cross Dipole
and Patch Elements,” in Proc. of ISAP2020, pp.821-822, 2021.
[4] H. Matsuno, et al., “Development of a Dual-Polarized Direction-Variable LiquidCrystal Meta-Surface Reflector for Intelligent Reflecting Surface,” in IEEE Access, , vol.
11, pp. 95757-95767, May 2023.
[5] Y. Cui, et al., "A Low-Cost Structure for Reducing Reflection Loss in Intelligent
Reflecting Surface of Liquid Crystal," in IEEE Antennas and Wireless Propagation

Letters, vol. 22, no. 12, pp. 3027-3031, Dec. 2023.

30

[6] T. Ohto, et al., “Reconfigurable Meta-surface Reflectors: Practical Phase adjustment
method and Experimental Validation,” in Proc VTC2022-Spring, Helsinki, Finland, June
2022.
[7] K. Yoshikawa, et al., “User and Passive Beam Scheduling Scheme for Liquid Crystal
IRS-assisted mmWave Communications” to be presented in Proc. EuCAP2023.
[8] W. Tang, et al., “Path Loss Modeling and Measurements for Reconfigurable Intelligent
Surfaces in the Millimeter-Wave Frequency Band,” in IEEE Trans. Commun., vol. 70, no.
9, pp. 6259-6276, Sept. 2022.
[9] H. Matsuno, et al., "Practical Evaluation Method of Large Size IRS: Synthesis ofReflection Pattern of Sub-IRS," in IEEE Access, vol. 11, pp. 102072-102081, Sep. 2023.

31

V. Terminal-Collaborated MIMO Reception
Hidekazu Murata, Yamaguchi University
Satoshi Suyama and Huiling Jiang, NTT DOCOMO, INC.
Daisuke Murayama, NTT Corporation

Abstract— In terminal-collaborated multiple-input multiple-output (MIMO) reception,
the terminal to be the collaboration partner needs to be selected appropriately. In
frequency-selective fading channels, it is possible to improve transmission performanceby selecting the appropriate terminals for each frequency subband. Therefore, MIMO
channel matrix-based schemes have been considered as subband-based terminal
selection schemes. On the other hand, it is also clear that the residual error coefficient
in received signal processing is a good indicator of the decoding performance. In thispaper, we introduce efficient subband-based terminal selection schemes using two-stage
terminal selection based on the MIMO channel matrices and the residual error
coefficients, with the aim of further improving the performance of subband-based
terminal selection. The error rate performance of the proposed schemes are evaluated bycomputer simulations. As a result, it is confirmed that the proposed schemes havesuperior transmission performance compared to the conventional schemes.
V-1. Introduction
In multiple-input multiple-output (MIMO) transmission, the channel capacity
depends on the smaller number of antennas on the transmitting and receiving sides.
Although it is difficult to expand the number of antennas of a small terminal
substantially, the number of antennas can be equivalently expanded if neighboring
terminals cooperate.
In the collaborated-terminal MIMO reception technique [1], the number of receiving
antennas can be equivalently expanded by jointly receiving MIMO signals from the basestation (BS). For example, the transmission technology with high-speed and low-latency
in high frequency bands such as the 28 GHz band is suitable for terminal collaboration
links.
Terminal selection can reduce the traffic for collaboration by appropriately selecting aterminal from among multiple receiving terminals. So far, terminal selection schemes
based on MIMO channel matrices and terminal selection using residual error coefficients
have been proposed as terminal selection schemes.
High-speed transmission in a multipath fading environment with arriving delay waves
is subject to frequency-selective fading. In this case, the channel state differs for each32

subband, which is the unit into which the signal bandwidth is divided, and adaptive
terminal selection for each subband is desirable.
It has been shown that collaboration terminal selection using the properties of the
MIMO channel matrix can improve transmission performance as the number ofsubbands is increased [2]. Furthermore, it has been shown that the residual error
coefficient is a good indicator to judge the decoding performance and is effective forterminal selection. However, since this method requires an attempt at decoding forterminal selection, an increase in the amount of computation can be a major issue.
If the increase in computational complexity can be accepted, it is also effective to obtain
multiple decision results by changing the combination of received signals and combining
the decision results. When decision is made from received signals obtained from otherterminals and one's own received signal, the decision result may differ for each terminal
making the decision, resulting in the concept of a terminal collaboration system
including multiple detection terminals. Although this method increases the overallsignal processing and processing delay, it has been shown that it can effectively improvetransmission performance [3].
In this section, we first examine the overlap of terminals determined by each method
using the channel matrix. Next, to improve transmission performance while reducing
the computational complexity of terminal selection using residual error coefficients, twostage terminal selection is considered: terminal selection using the channel matrix andterminal selection using residual error coefficients. The received signal processing
assumes frequency-domain iterative equalization using a minimum mean-squared error
filter.
V-2. System Model
The system model and frequency-domain iterative equalization are introduced in thissection. Fig.

V-1 shows the system model for collaboration terminal selection interminal-collaborated MIMO reception. Assuming that each terminal is equipped with
one antenna, multiple independent signals are simultaneously transmitted from the BS
to the receiving terminal at the same frequency. Only the portion necessary for channel
estimation received at the collaboration terminal is collected by the terminal, and theterminal is selected, and their waveforms are used for decoding.

33

Fig. V-1. System model of terminal-collaborated MIMO reception
system.
V-3. Subband-based Signal Processing
The transmission performance of the proposed method with respect to the number ofsubbands and signal-to-noise power ratio (SNR) are evaluated by computer simulation.
In this study, frequency-domain soft cancellation/MMSE iterative equalization is
performed as signal processing for terminal-collaborated MIMO reception. Fig. V-2
shows a block diagram of subband-based terminal selection and frequency-domain
iterative equalization, where the number of BS antennas is four and the number ofreceiving terminals is six.

Fig. V-2. Subband-based terminal selection and iterative equalization.

34

As can be seen from this figure, at each terminal, the received signal is converted to
the frequency domain by DFT, and the subband portion selected for each terminal isforwarded to the detection terminal. High-frequency band communication technology
would be suitable for this transfer. The destination terminal performs frequency-domain
iterative equalization using the signals collected from each terminal.
Fig. V-3 shows the PER performance versus the number of subband divisions S. The
PER performance are shown for various selection algorithms. The one with the best
performance is SIMPMC, which is a terminal selection method that uses the result of
SINR estimation from the MIMO channel matrix, singular values, and the condition
number to narrow down the selection candidates. Compared to the S=1 case, in which
candidates are selected for all bandwidths at once, the method that selects collaboration
terminals for each subband improves the PER performance by approximately one orderof magnitude.

Fig. V-3. Packet error performance versus number of subbands.

V-4. Conclusion
The two-stage terminal selection for each subband using the channel matrix and theresidual error coefficients in terminal-collaborated MIMO reception showed bettertransmission performance than the case using the channel matrix alone. The first-stage
selection using the channel matrix reduced the number of terminal patterns, and thesecond-stage selection using the residual error coefficients improved the transmission
performance while reducing the number of received signals to be decoded.

35

Acknowledgements
This work was supported in part by JSPS KAKENHI Grant Number JP23H00474.
REFERENCE[1] F. Du, H. Murata, M. Kasai, T. Nakahira, K. Ishihara, M. Sasaki and T. Moriyama“Distributed detection of MIMO spatial multiplexed signals in terminal collaborated
reception,” IEICE Trans. Commun., vol. E104.B, no. 7, pp. 884-892, July 2020.
[2] H. Murata, “Terminal selection schemes in terminal-collaborated MIMO reception
based on subband channel matrices,” IEEE Communications Letters, vol. 26, no. 1, pp.
202-206, Jan. 2022.
[3] H. Taromaru, H. Murata, T. Nakahira, D. Murayama, T. Moriyama, "Error control
on mobile station sides in collaborative multiple-input multiple-output systems," IEEE
Access, Vol. 10, pp. 26493-26500, Mar. 2022.

36

VI. Beamforming-BasedIRSControlfor
Communications in Indoor Office Environments1

Sub-Terahertz-Band

Yasutaka Ogawa, Hokkaido University
Satoshi Suyama, NTT DOCOMO, INC.
Toshihiko Nishimura, Takeo Ohgane, Hokkaido University

Abstract—Using a sub-Terahertz band, we can achieve extreme high-speed
communications required by Beyond 5G/6G systems. For transmission to user
equipment (UE) behind an obstacle, we can employ intelligent reflecting surfaces (IRSs).
According to propagation measurements in the band, we have only a few multipath
components in indoor office environments. This leads to an IRS control method based on
beamforming because the number of radio waves outside the optimum main beam is verysmall, and power that is not used for transmission from the IRS to UE is little. We apply
beams generated by a Butler matrix or a DFT matrix. Simulation results show that the
proposed method reveals good performance.
VI-1. Introduction
A sub-Terahertz (THz) band is expected to play a great role in Beyond 5G/6G systems
to achieve extreme high-data-rate communications. Radio waves in a sub-THz band are,however, hard to propagate behind an obstacle due to large diffraction losses. Intelligent
reflecting surfaces (IRSs) can solve the propagation problem. In this paper, weinvestigate IRS control based on beamforming. An IRS has a set of beams. A base station(BS) sends pilot symbols, and for a different pilot, the IRS changes the beam. User
equipment (UE) measures the received power for each beam, and informs the BS of thebeam that provides the largest received power. The BS controls the IRS so that it canuse the optimum beam providing the maximum power at the UE. This method does notneed either channel state information or phase optimization. It is easy to determine thephases of the IRS. However, the performance depends on environments where it isdeployed. When we have only a few multipath components in the environment, themethod will work very well because the number of multipath components outside theoptimum main beam is small, and power that is not used for transmission from the IRS
to UE is little. According to [2], the total number of observed multipaths at 140 GHz issmall in office environments. It is expected that the IRS based on beamforming works
well in sub-THz bands. In this paper, we evaluate the performance using the sub-THzband channel model proposed in [2].

1This paper is based on the authors’ work [1].

37VI-2. Beamforming-Based IRS Control
This section clarifies IRS control based on beamforming treated in this paper. Fig.
VI-1 depicts the top view of a system model discussed here. Note that its multipath
environment is an example. In the figure, we have two time clusters (TCs) and one
subpath per TC. We express azimuth angle as . The direct path from the BS is blocked
by an obstacle, and the UE is in a non-line-of-sight environment. The IRS reflects theincident radio waves toward the UE that has a single antenna. The IRS consists of Q ×

Q reflecting elements with half-wavelength spacing, where Q is a power of 2.

Fig. VI-1. An IRS-assisted wireless network (Top view).
We have four sets of beams, and call them codebooks in this paper. The codebooks aredefined as follows:1.

Codebook BB consisting of Q 2 beams formed by phases of a Butler matrix for boththe azimuth and the elevation directions

2.

Codebook DB consisting of Q 2 beams formed by phases of a DFT matrix for theazimuth direction and phases of a Butler matrix for the elevation direction

3.

Codebook BD consisting of Q 2 beams formed by phases of a Butler matrix for theazimuth direction and phases of a DFT matrix for the elevation direction

4.

Codebook DD consisting of Q 2 beams formed by phases of a DFT matrix for boththe azimuth and the elevation directions

The reason why we use the four codebooks will be clarified later. It should be notedthat we do not have either Butler matrix circuits or DFT matrix circuits. Phases realized
by those circuits are given to phase-shift devices.
The beam patterns in the azimuth domain are shown in Fig. VI-2 for codebooks BB
and DB, where Q = 8 and elevation angle −7.2°. Since we have 64 elements, the maximum
gain is 18 dB. Note that we assume that each IRS element works as an isotropic antenna
with 0 dBi gain. From the figures, we see that the gain at angles where two beams cross38each other is about 14 dB. This means that if we use a single codebook, we have about 4
dB degradation in the worst case. Furthermore, it is seen that beams of one codebook
have the maximum gain around angles where beams of the other codebook have thelowest value, and that beams of both codebooks help each other. The degradation is
reduced to about 1 dB. This is the reason why we use both the Butler matrix and DFT
matrix codebooks. We have stated the azimuth case so far, but the situation is the same
also for the elevation. Thus, we have BB, DB, BD, and DD in all. The four codebooks
improve the performance comparing with the single codebook BB. In the next section, it
will be shown that the performance of the four codebooks is much better than that of thesingle codebook BB.

(a) Codebook BB.

(a) Codebook DB.

Fig. VI-2. Beam patterns in the azimuth domain for codebooks BB and DB. Q = 8 andelevation angle −7.2°.
Now, we explain the IRS control in more detail. The BS sends pilot symbols. Eachsymbol has L equal-amplitude components at equal frequency intervals in acommunication band. We choose the beam that maximizes the received power. The
reason why we use multiple frequency points is because we want to choose the beam thatmaximizes the received power in frequency-selective fading environments due tomultipath delay.
VI-3. Simulations
We evaluated the performance of the IRS based mainly on the channel model proposedin [2]. The main simulation parameters are listed in Table.

VI-1. We examined twocases of multipath propagation, where the number of multipath components is 3 and 6.
Refer to [1] for detail simulation parameters.

39

Table. VI-1. Simulation parameters.
Frequency range [GHz]
Number of IRS elements, Q × Q
Number of frequency points in each pilot symbol, L
Number of trials

140 ~141
8×8
11
1000

Now, we present simulation results. We conducted 1000 trials changing the azimuth
angles of departure, elevation angles of departure, and multipath phases. Fig. VI-3 and4 show the cumulative distributions of relative received power for 3-path and 6-pathcases, respectively. The legends are defined as follows:“Butler and DFT matrices” is the distribution for the beamforming method using thefour codebooks proposed in the previous section.
“Butler matrix” is that using the single codebook BB.
“Upper bound” is the distribution of received power in a case where we could optimize
the IRS phases for all the L frequency points.

Fig. VI-3. Cumulative distributions of relative received power for 3-path case.
We see form these figures that the performance of 3-path scenario (fewer-multipathcase) is better than that of 6-path one (more-multipath case). The reason for this has
been stated in Section 1. For the 3-path case, the degradations of the proposed fourcodebook method from the upper bound are only 1.98 dB and 2.56 dB at the cumulative
distributions of 50 % and 5 %, respectively. We think that those degradations are small.
Even when we have as many as 6 multipath components, the degradations are less than
4 dB. From these results, we can say that the proposed method is useful for IRS control
in sub-THz bands.

40Fig. VI-4. Cumulative distributions of relative received power for 6-path case.
VI-4. Conclusion
IRSs enable to realize communications overcoming the propagation problem in subTHz bands. Since the number of multipath components is small in the band, we haveproposed the IRS control based on beamforming that is realized by phases of a Butler or
DFT matrix. This method can avoid difficult channel estimation and phase optimization
problems. Simulation results have shown that it reveals good performance in the sensethat the received power is not so lower than the upper bound value.
REFERENCE[1] Y. Ogawa, S. Tadokoro, S. Suyama, M. Iwabuchi, T. Nishimura, T. Sato, J. Hagiwara,
and T. Ohgane, “Smart radio environments with intelligent reflecting surfaces for 6G
sub-Terahertz-band communications,” IEICE Trans. Commun., vol. E106-B, no. 9, pp.
737–747, Sept. 2023.
[2] S. Ju, Y. Xing, O. Kanhere, and T. S. Rappaport, “Millimeter wave and sub-Terahertz
spatial statistical channel model for an indoor office building,” IEEE J. Sel. Areas
Commun., vol. 39, no. 6, pp. 1561–1575, June 2021.

41VII. Beam Squint-aware Frequency Resource Allocation for IRS-aided
Communication
Hiroaki Hashida, Ei Tanaka, Yuichi Kawamoto,Tohoku University
Masashi Iwabuchi, Riku Omiya, Yoghitha Ramamoorthi, Tomoki Murakami,
NTT Corporation

Abstract—An intelligent reflecting surface (IRS) is a device that reflects radio waves
in any direction by setting the phase shift of the reflecting elements. This is expected tosolve the problems of high-frequency band communications, such as vulnerability to
obstacles, and realize super-multiplex connections in the high-frequency band.
Considering the reflective elements of the IRS can only be time-division controlled andcan support only one user per time slot, it is highly likely that a large number of resource
blocks will be allocated to a single user to perform communication. However, in such a
scenario, the frequency efficiency is reduced because of the effect of the beam squint. In
this paper, we demonstrate the effectiveness of a method proposed to increase thefrequency efficiency by optimizing the reflection direction through resource allocation
and IRS phase control.
VII-1. Introduction
To support sixth generation (6G) ultra-high-speed and high-capacity communications,attention has been focused on high-frequency bands capable of utilizing a wide frequency
range. However, high-frequency bands are more susceptible to diffraction and blockage
by obstacles than low-frequency bands. Intelligent reflective surfaces (IRS) offer aplausible solution to this problem [1]. IRS is a device that integrates a large number ofreflective elements in a planar fashion, each of which is capable of controlling theamplitude and phase of the incident signal. By incorporating IRS into the network andintelligently controlling the reflections, problems in the high-frequency band can beeffectively solved [2]–[4]. By their nature, IRS can only perform time-division control andgenerally support only one user per time slot. Therefore, when multiple users aresupported by the IRS, the communication request of one user should be satisfied in asmall number of timeslots; therefore, a large resource block (RB) is allocated to one user
for communication. However, in such a scenario, the frequency efficiency is reduced
because of the beam squint effect [5,6]. In this paper, we propose an IRS control and42

frequency allocation scheme that effectively uses a beam squint to maximize thefrequency efficiency of the IRS.

Fig. VII-1. Illustrative representation of existing method and proposed method.

VII-1.1. What is Beam Squint?
Beam squint refers to a phenomenon in which the direction of reflection of an IRS
changes based on its frequency of incidence. The misalignment of the reflection direction
caused by the beam squint is expressed by (1).
𝐬𝐢𝐧𝜽 = (𝟏 −𝒇𝒄
𝒇𝒄
) 𝐬𝐢𝐧𝜽𝐢𝐧 + 𝐬𝐢𝐧𝜽𝐜
𝒇
𝒇

(1)

where 𝑓𝑐 and 𝜃𝑐 denote the center frequency and its reflection direction, respectively, 𝜃indenotes the angle of the radio wave incident on the IRS, and 𝑓, 𝜃 denotes the frequency
incident on the IRS and its reflection direction.
VII-1.2. Control Parameters of Proposed Method
We propose an IRS control and frequency allocation scheme for multiple user
equipments (UEs) that makes effective use of a beam squint to maximize the frequency
efficiency of the IRS. Therefore, the proposed method is effective for communicating withmultiple UEs. From (1), the direction of reflection 𝜃 at a given frequency 𝑓 depends onthe variables 𝜃𝑐 and 𝑓 (𝜃in is a constant that indicates the angle of incidence from thebase station (BS) to the IRS). Specifically, as shown in Fig. VII-1, the direction in whichreflection control should be applied needs to be considered as well as which RBs should
be assigned to UEs based on the misalignment of the reflection directions for each RB.
The existing method allocates all available RBs to one UE, and the main radiation
direction is perfectly directed to the UE. In other words, by optimizing the following two
parameters, the beam squint can be effectively utilized and the frequency efficiency ofcommunication through the IRS can be maximized. The two parameters are as follows:(A) the main radiation direction controlled by the phase of the IRS and (B) the allocationof RBs to UEs. (A) changed 𝜃𝑐 in (1). For (B), 𝑓 changes based on which RB and UE is
assigned determines the angle of presence 𝜃UE of the UEs and the direction of reflection
θ of the assigned RB. (When 𝜃UE = 𝜃, the IRS has the maximum gain for the UE.) The

43

proposed method determines (A) and (B) to maximize (capacity of all UEs)/(bandwidth)
in an environment with multiple UEs. In this study, (A) is treated as a discrete value
with 0.1-degree increments, and both (A) and (B) are determined by brute force todemonstrate the upper performance limit of the proposed method.
VII-2. Performance Evaluation
VII-2.1. Environment

Fig. VII-2. Simulation environment.
In this evaluation, the environment shown in Fig. VII-2 was verified. 𝑛 UEs weregenerated in the UE generation area in a uniform distribution. Ten RBs were randomly
selected from 268 RBs available at 28 GHz. The available RBs were randomly selectedfrom 10 of the 268 RBs available for communication in the 28 GHz. It was assumed thatthe direct waves reaching the UEs from the BS were completely blocked by obstacles, as
shown in Fig. VII-2. The antenna gains of the BS and UE were set to 0 dBi because theperformance of the BS and UE antennas was not relevant in this simulation. We verify
the effectiveness of the proposed method by comparing it with the existing method of IRS
time-division communication. Specifically, the available RBs were randomly selectedfrom 10 of the 268 RBs assigned to the UE closest to the IRS, and the main radiation
direction of the IRS was set to the direction of the UE’s presence. The evaluation index
indicates the frequency efficiency [bit per sec (bps)/Hz] of the communication for 𝑛 UEs.
In this study, the heights of BS, IRS, and UEs were assumed to be equal, and only the
direct path between BS and IRS and the direct path between the IRS and UEs are
considered without considering the path reflected from the ground or obstacles.
VII-2.2. Results
The results of the simulation evaluation of the environment described in the previous
section are presented in Fig. VII-3 and Fig. VII-4. Fig. VII-3 shows the results when
the number of UEs 𝑛 is varied. Fig. VII-3 shows the results when the BS is moved
upward in Fig. VII-1, and the angle of the radio wave incident on the IRS is varied from
0°. Each plot represents the average of 100 simulations. This is because randomness
exists in the generation of UEs and the available RBs. First, Fig. VII-3 shows that the
proposed method becomes more dominant as the number of UEs 𝑛 increases. This is44because as the number of UEs increases, the probability of the existence of UEs that cangain more by beam squinting increases. Fig.

VII-4 shows that when the angle ofincidence of the radio wave incident from the BS to the IRS changes and the IRS controls
the reflection to an angle farther from the specular reflection, the proposed method
shows stable performance, whereas the performance of the comparative method
deteriorates. This is because as shown in (1), the comparative method is more susceptible
to the negative effects of the beam squint, because the beam shift from one RB to anotherincreases as the angle of incidence changes.

Fig. VII-4. Frequency efficiency per number of UEs

Fig. VII-3. Frequency efficiency with respect to angle of incident

VII-3. Conclusion
Beam squint negatively affects existing IRS control methods. In this paper, by
optimizing the IRS reflection direction control and resource allocation, a beam squint
was effectively utilized to increase the frequency efficiency of IRS-based communications.
It was demonstrated that the proposed method is more effective in environments with
dense UEs and high beam squint.
REFERENCE[1] M. Agiwal, A. Roy, and N. Saxena, “Next generation 5G wireless networks: A

45

comprehensive survey,” IEEE Commun. Surveys Tuts, vol. 18, no. 3, pp. 1617-1655,
3rd Quart. 2016.
[2] R. Hibi, Y. Kawamoto and N. Kato, “Standalone-Intelligent Reflecting Surface
Control Method Using Hierarchical Exploration by Beamwidth Expansion andEnvironment-Adaptive Codebook,” IEEE Transactions on Vehicular Technology, vol.
69, no. 5, pp. 3313-3351, May 2021.
[3] H. Hashida, Y. Kawamoto, and N. Kato, “Intelligent reflecting surface placement
optimization in air-ground communication networks toward 6G,” IEEE WirelessCommunications, vol. 72, no. 9, pp. 11990-12000, Sept. 2023.
[4] Y. Liang et al., “Large Intelligent Surface/Antennas (LISA): making reflective radios
smart,” Journal of Communications and Information Networks, vol. 4, no. 2, pp. 4050, June 2019.
[5] E. Tanaka, Y. Kawamoto, N. Kato, M. Iwabuchi, R. Ohmiya, and T. Murakami,“Exploiting Reflection Direction Variation for Phase Control in Multiple
Simultaneous IRS Links,” 2023 IEEE 97th Vehicular Technology Conference,
Florence, Italy, 2023.
[6] E. Tanaka, Y. Kawamoto, N. Kato, M. Iwabuchi, Y. Ramamoorthi, T. Murakami,"Frequency Resource Allocation for IRS-aided Communication using Beam Squint
Approach," 2024 IEEE 21th Consumer Communications & Networking Conference(CCNC 2024), Las Vegas, NV, USA, Jan. 2024.

46

VIII. Prototype and Evaluation of Intelligent Reflecting Surface for 60 GHz
Band
Hiroyuki Uno, Hiroyuki Uejima, Hirofumi Kosaka, Ken Katsurashima,
Panasonic System Networks R&D Lab. Co., Ltd.
Ryuhei Hibi, Yuichi Kawamoto,Tohoku University

Abstract— Intelligent Reflecting Surface (IRS) is gaining recognition as a newtechnology component to realize B5G/6G. It enables to manipulate the phase shift of theincident wave, thereby providing control over the propagation of electromagnetic waves.
This paper outlines a prototype IRS for 60 GHz band, the analyzed results by theelectromagnetic simulation, and the results of characterization experiments developedby this research group.
VIII-1. Introduction
Commercial services for the 5th generation mobile communication system (5G) havebeen launched in Japan since 2020, and B5G/6G, the next generation mobile
communication system, is currently being considered toward the further advancementof communication services [1]. For B5G/6G, the use of millimeter wave bands and subterahertz bands, which are higher than microwave bands and quasi-millimeter wave
bands used in 5G, is being considered to achieve further high-speed and high-capacity
communications. These high-frequency bands have the feature that strong rectilinear
propagation and large propagation loss have less chance of going around to the back ofshielding objects such as buildings compared as microwave bands used in conventional
mobile communication systems, and thus the communication range becomessignificantly narrow. Therefore, this problem is a major issue to be considered forachieving the realization of the future B5G/6G.
As one of the methods to solve such problems, the utilization of intelligent reflecting
surface (IRS) has garnered interest, and its research and development have been actively
carried out [2]-[4]. The IRS is a reflector consisting of a planar array of microscopic
structures called meta-surface. By changing the reflective properties of each unit-cellforming the meta-surface, the direction of reflection of radio waves incident on the IRS
can be controlled in the desired direction. The IRS enables radio waves from basestations to reach users while avoiding shielding, thereby contributing to the expansionof areas where a good communication environment can be provided.
Various IRSs using switching devices, liquid crystals, and so on have been proposed[5],[6], however, there are few research examples corresponded to millimeter wave bands.
In this paper, we introduce the design and results of the characterization experiment of47

the prototype IRS using the 60 GHz band, which our research group has developed basedon various studies [7]. The choice of 60 GHz band was determined by the operating
frequency of the radio equipment used for wireless communication tests and is also
intended to verify the applicability to millimeter waves and sub-terahertz waves thatwill be used in future B5G/6G.
The rest of this paper is organized as follows. The design of the prototype IRS and theresults of reflection characteristics using electromagnetic (EM) simulation are
introduced in Section 2. Section 3 shows the experimental results. Finally, we offer ourconclusion in Section 4.
VIII-2. Design and Simulation of Prototype IRS
VIII-2.1. Configuration
Fig. VIII-1 shows the overall configuration of the prototype IRS. Our designed IRS
consists of the IRS board and the electrical control board. In Fig. VIII-1, the metasurface formed by 6,400 unit-cells is equivalent to the phase control block of the IRS
board. A unit-cell is composed of reflective element and PIN diode, and the ON/OFF stateof each PIN diode is controlled by the MCU block in the electrical control board. By
optimizing the ON/OFF control of PIN diodes, the direction of reflection of radio waves
incident on the IRS board can be controlled.
Wire harness

Electrical control board
AC/DC

MemoryDiodecontrol
block

CN

MCU
block

Phase control block(Meta-surface)CN

USB IF

Control power
supply circuit

CN

PC

12V

CN

AC/DC

IRS board

CN

AC100V

3V

Diodedrive block

Controlbutton※ CN: Connector

6,400 unit-cells-Reflective elements-PIN diodes

Power supply
Control line

Fig. VIII-1. Overall configuration of prototype IRS.

VIII-2.2. EM Simulation Model
The EM simulation model of the IRS board is shown in Fig. VIII-2. The IRS board iscomposed of numerous unit-cells that arranged in reticular pattern on the +Z side planeof the dielectric substrate as shown in Fig. VIII-2 (a) and can control the reflection
direction by adequately setting the reflection phase of each unit-cell. The EM simulationis perfomed with 256 elements due to work station peformance. Fig. VIII-2 (b) illustrates
the unit-cell that composed of linearly polarized reflective element with side length of Lp
and height of T1, dielectric substrate, stub via, choke stub, and PIN diode. The dielectric
substrate is used R-5775 (Panasonic), and its relative permittivity (r) and loss tangent

48

(tan) are set to 3.55 and 0.005 respectively in the simulation. The length of stub via isdetermined to optimize the reflection phase and the choke stub is formed to prevent theRF signal of 60 GHz from entering the control bias line. The PIN diode, which is used
MA4AGFCP910 from M/A-COM, is changed ON state or OFF state by suppling a DC
bias (Vd) and a control voltage (Vc), thereby be able to switch the reflection phase of theunit cell to either 0 degree or 180 degrees.

Lp

Y

Reflective element

Lp

Stub via

Dielectric
substrate

PIN diode
X

L1
L2
L3
L4
L5

Z

Choke stub

T1

(a)

DC bias (Vd)Control voltage (Vc)(b)
Fig. VIII-2. EM simulation model of IRS board.

Unit cell

Input ofplane wave

(a)

(b)

Fig. VIII-3. Simulation model and results for reflection phase of unit-cell.

VIII-2.3. EM Simulation Results
VIII-2.3.1. Reflection Phase of Unit-cell
Fig. VIII-3 shows the simulation model and results for the reflection phase of unitcell. Fig. VIII-3 (a) is the simulation model of the reflection phase, and Fig. VIII-3 (b) is49

the simulated reflection phase as a function of frequency. This simulation uses CST
studio suite’s the finite element method (FEM), with the lateral boundaries of the unitcell set as periodic boundary condition. The PIN diode is modeled as lumped parameter
elements and its equivalent circuit for 60 GHz band is extracted from S-parameters. The
ON state is modeled as a series of R = 5.2  resistors and L = 0.8 nH inductors, whereas the OFF
state is modeled as a series of C = 0.105 pF capacitors and R = 3  resistors. Moreover, the side
length Lp and the height T1 of patch element is set to 1.17 mm and 0.3 mm, respectively.
As shown in Fig. VIII-3 (b), it can be seen that the phase difference between the ON
state and OFF state is adjusted to approximately 180 degrees for an operating frequency(57.24 - 59.4 GHz) of wireless communication tests.
VIII-2.3.2. Reflection Characteristics of IRS Board
This chapter presents the simulation results of the reflection characteristics for the IRS
board shown in Fig. VIII-2. In this simulation, the far-field pattern of radar cross section(RCS) is analyzed when the Y-axis linearly polarized plane wave is incident from the +Z
direction and each PIN diode is adjusted as shown in Fig. VIII-4. In Fig. VIII-4, the redpart and the blue part are the ON state and the OFF state, respectively. By using these
the ON/OFF map of PIN diodes, the reflection angle θc of IRS can be adjusted to 15, 30,
and 45 degrees, with the front of the incident direction set to 0 degrees.
Fig. VIII-5 shows the simulated far-field patterns of the reflected wave at 58.32 GHz.
The refection angle θ at horizontal axis indicates the angle of inclination from the +Z
direction to the +X direction for the XZ plane. From the simulated results shown in Fig.
VIII-5, it can be confirmed that the reflected wave is tilted to the desired direction.
ON state of PIN diodeOFF state of PIN diodeON

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OFF

(a) qc is 15 degrees(b) qc is 30 degrees

Fig. VIII-4. ON/OFF map of PIN diodes.

50(c) qc is 45 degrees

qc is 15 degree

qc is 30 degrees

qc is 45 degrees

0-5

RCS [dBsm]

-10
-15
-20
-25

-30
-35
-40
0

15

30

45
60
Reflectoin angle q [degree]

75

90Fig. VIII-5. Simulated far-field patterns of reflected wave at 58.32 GHz.

VIII-3. Characterization Experiments
VIII-3.1. Prototype IRS Outline
Prototype IRS shown in Fig. VIII-6 consists of a total of 6,400 elements, 80 each in the
Y-axis vertical and X-axis horizontal directions. Element placement area is 200 mm x
200 mm, Element spacing is 2.5 mm, and Element size is 1.5 mm x 1.5 mm. Supported
frequency is 58.32 GHz, and reflection phase control is a binary control of 0/180 degrees.

Y
Y
X
X

Y
Y

ZZ

Fig. VIII-6 Prototype IRS.

ZZ

X
X

Fig. VIII-7. Experimental environment.

VIII-3.2. Experimental Environment and Methods
In this experiment, IRS, transmitter, and receiver are arranged as shown in Fig.
VIII-7, and the reflection characteristics of the IRS are evaluated by changing theposition of the receiver in the direction indicated by the arrow line. The transmitter is acommunication device using 60 GHz band by Panasonic and the receiver is an Anritsu

51

MS2762A spectrum analyzer. The direction of reflection of IRS is set to four patterns of0, 15, 30, and 45 degrees, with the front of the incident direction set to 0 degrees. The
receiving angle θ between the transmitter, IRS, and receiver is changed from 10 to 60
degrees in 1-degree increments. The distance between transmitter and IRS and between
receiver and IRS are both 10 m. This experiment is conducted in a large anechoic
chamber.
VIII-3.3. Experimental Results
Fig. VIII-8 shows the experimental results. The angle θc shows the primary radiation
direction of the reflected wave by the phase control of IRS. The results show that thereceived power peaks at 1 degree inside of each primary radiation direction. This is dueto the characteristics of the device. The results also show that the peak in the primary
direction is moderate and that the received power is not stable in the non-primary
direction. This may be due to several factors. One of the major factors is that theexperimental environment is small compared to the IRS, which is designed for longdistance communication.
Additional

video

broadcasting

experiments

areconducted

based

on

the

characterization experiments. From this experiment, it can be confirmed that the video
stopped and replayed in accordance with the operation of the IRS.

Receiving angle q [degree]

Fig. VIII-8. Experimental results.
VIII-4. Conclusion
In this paper, we introduce the outline of the prototype IRS for 60 GHz band, theanalyzed results by the EM simulation, and the results of characterization experiments.
The development process and the experimental results show the effectiveness of the IRS
as a device for improving the propagation path, and also reveal some issues, including52

the expansion of operating bandwidth, the reduction of beam squint, and the
manufacturing cost. In the future, it will be necessary to consider the desirable
equipment configuration for B5G/6G.
REFERENCE[1] Beyond 5G Promotion Strategy (Outline) (MIC, in Japanese)
https://www.soumu.go.jp/main_content/000702111.pdf[2] R. Hibi, Y. Kawamoto and N. Kato, "Standalone-Intelligent Reflecting Surface
Control Method Using Hierarchical Exploration by Beamwidth Expansion andEnvironment-Adaptive Codebook," in IEEE Transactions on Vehicular Technology,
vol. 72, no. 9, pp. 11990-12000, Sept. 2023.
[3] H. Hashida, Y. Kawamoto, and N. Kato, "Selective Reflection Control: Distributed
IRS-Aided Communication with Partial Channel State Information," IEEE
Transactions on Vehicular Technology, vol. 71, no. 11, pp. 11949-11958, Nov. 2022.
[4] D. Kitayama, D. Kurita, K. Miyachi, S. Itoh, and T. Tachizawa, "5G radio accessexperiments on coverage expansion using metasurface reflector at 28 GHz," 2019
IEEE Asia-pacific microwave conference (APMC), pp. 435-437, Dec. 2019.
[5] L. Dai, B. Wang, M. Wang, X. Yang, et al., "Reconfigurable intelligent surface-based
wireless communications: antenna design, prototyping and experimental results,"
IEEE access, vol. B, pp. 45913-45923, March 2020.
[6] A. Couch and A. Grbic, "A phase-tunable, liquid crystal-based metasurface," 10th
International Congress on Advanced Electromagnetic Materials in Microwaves andOptics-metamaterials, pp. 94-96, Sept. 2016.
[7] Press release of Tohoku university, May 2023. (in Japanese)
tohokuuniv_press0524_01web_60ghz.pdf

53

IX. Wireless Transport Technology for Xhaul
Hiroaki Asano Panasonic System Networks R&D Lab.
Takeshi Yasunaga Panasonic Connect

Abstract— This paper provides an overview of wireless transport technology for xhaul
and describes the points that unlicensed bands are expected to be actively used in 6G
networks. Next, we describe the developed wireless transport equipment using 60 GHz
unlicensed bands and future trends. And, for mobility platforms using 60GHz, thedeveloped technology that uses millimeter wave radar with machine learning to predict
wireless quality to avoid blocking and achieve seamless handover and RAT change isalso described. These technologies are expected to expand to wireless transporttechnology for xhaul.
IX-1. Introduction
In 5G networks, configuration in which CUs, DUs, and RUs are prepared according to
RAN function split option 2 and option 7-2 and are connected via backhaul, midhaul, andfronthaul are often used. In addition to large capacity, flexibility, scalability, powersaving, low cost, reliability, security, and integrated management are required for RAN,
and is being put into practical use for 5G [1]. For 6G networks, RAN functional splitting,virtualization and various functions have been considered according to requirements [2].
Support for NTN will be required, and traffic per user will further increase, user density
will also increase, and higher frequency bands will be used for access networks. With thestudy of cell-free technology or distributed MIMO, it is necessary to place many antennas
close to terminals. It is also required that antennas will be mounted on UAVs, HAPSs or
LEO/GEOs, and it can be used in areas where conventional service coverage is difficult,and it is also desirable to support moving cells such as vehicles or high-speed trains. In
these cases, wireless transport technology for xhaul will become more important. Fig.
IX-1 shows RAN architecture with xhaul.

Fig. IX-1. RAN architecture and xhaul technology.

54

Regarding wireless, it is desirable to actively utilize unlicensed bands in addition tolicensed bands. Discussions regarding frequency allocation in licensed bands willcontinue, in addition to this, effective use of unlicensed bands will enable the early
realization of 6G networks.
When using an unlicensed band, sufficient management is required to prevent
unexpected interference when sharing it with other users. The RAN is required tocomprehensively manage the operational status of xhaul, including the use of unlicensed
bands, and to realize efficient operation of the entire network.
IX-2. Unlicensed Band Technology for Wireless Transport
In 6G networks, it is expected that unlicensed bands will be used for wireless transport
for xhaul. Here, the IEEE802.11ad [3] compliant wireless equipment and the systemtechnology that uses the unlicensed 60GHz band, which has the potential to be used for
wireless transport for xhaul, are described.
IX-2.1. 60GHz Wireless Transport Equipment (IEEE802.11ad)
We have developed the 60GHz band wireless transmission equipment that wascompliant with IEEE802.11ad. The equipment has the beamforming function using the
32-element antenna, and autonomously select the optimal beam for communication
between an AP and STAs within a ±60° range. Devices equipped with lens antennas arealso prepared.

Fig. IX-2. The horizontal and vertical antenna gain with/without the lens antenna.
Lens antennas ensure antenna gain by narrowing the beam width in the verticaldirection and enable long-distance transmission. The horizontal and vertical antenna
gains with and without the lens antenna are shown in Fig. IX-2 By using the lensantenna, the beam is narrowed in the vertical direction, and beamforming remains
unchanged in the horizontal direction. Fig. IX-3 shows the results of evaluating thetransmission throughput at the IP layer with respect to the distance/wireless quality
between the AP and the STA. The equipment implements up to MCS12, and the55theoretical value at the IP layer for each MCS value is also shown in dotted lines. The
evaluation result shows that communication is possible at over 2.5Gbps up to about
120m, and transmission speeds of about 1Gbps can be obtained up to about 300m. Thisis the result of evaluation using devices equipped with lens antennas.

Fig. IX-3. The transmission evaluation results of the wireless transport device

Fig. IX-4. Data rates at PHY layer specified in IEEE802.11ay
Fig. IX-4 shows the transmission rate at PHY layer specified by IEEE802.11ay [4],which was specified further advancement of IEEE802.11ad. In Japan, up to fourchannels are available at 2.16GHz per channel from 57GHz to 66GHz. In IEEE802.11ay,
when using four channels simultaneously with channel aggregation or channel bonding,the maximum transmission speeds on the physical layer are 64.7Gb/s with 2-Stream
MIMO and 129.4Gb/s with 4-Stream MIMO. It has plenty of potential to support
increased capacity for 6G networks.
IX-2.2. Wireless Transport for Mobility Platform
Millimeter wave transmission is required to be utilized for mobility platforms toachieve large capacity, for example, to support moving cells. Millimeter-wave
transmission is highly susceptible to shielding due to its linearity, so techniques topredict and avoid shielding are needed. To solve this problem, we have developed the56technology to predict wireless quality using millimeter wave radar and machine learning.
Fig. IX-5 shows the developed millimeter wave transport system for mobility platformusing 5G-GWs. The 5G-GW was equipped with the AP and the STA of 60 GHz W-LAN(Wireless LAN) for multi-hop backhaul, and the AP to provide the 60 GHz W-LAN accessnetwork for vehicles, and the sensor using 79 GHz millimeter wave radar. When aterminal enters a shielded area or moves through an area where millimeter-wave radio
quality is degraded, it realizes the function that connects to the optimal RAT orneighboring millimeter-wave AP based on the radio quality prediction.

Fig. IX-5. Millimeter wave transport system for mobility platform
Fig. IX-6 shows the developed mechanism to prepare radio quality maps from point
cloud data which is acquired by the millimeter wave radar. Extracting vehicle
information from millimeter-wave radar point cloud data using machine learning is thefirst step. The second step is predicting vehicle positions based on the extracted vehicle
information with corrections using lane and inter-vehicle distance information. And thethird is generating a dynamic radio quality map for use in prediction based on thepredicted vehicle positions [5].

Fig. IX-6. The developed mechanism to prepare radio quality maps from point clouddata which is acquired by the millimeter wave radar.
Using the developed mechanism, we developed the evaluation system and verified that
performs RAT switching from 60 GHz W-LAN to Macro Cell when shielding was
expected to occur, and handover to millimeter wave cells at adjacent 5G-GWs in a course
where multiple 5G-GWs were placed adjacent to each other. Fig.

IX-7 shows theevaluation system.
Fig. IX-8 shows the throughput evaluation results of video stream transmission fromthe vehicle with and without radio quality prediction when the vehicle was moving [6].
The handover and RAT switching could be performed seamlessly when the radio quality57was predicted. This is an example of a technology using unlicensed band that enables
millimeter wave transmission to support mobility platforms.

Fig. IX-7. The evaluation system

Fig. IX-8. The results of the throughput with/without wireless quality prediction
IX-3. Conclusion
In this paper, we explained the importance of wireless transport technology for xhaul
and the direction in which unlicensed bands will be used in 6G networks. And thedeveloped unlicensed 60 GHz W-LAN equipment which is compliant to IEEE802.11ad
and its application to a mobility platform that can avoid blocking and realize seamless
RAT change and handover by using millimeter wave sensors with machine learning topredict radio quality were described. These technologies are expected to expand to
wireless transport technology for xhaul.
Acknowledgements
Some part of this paper was supported by “Research and development project for
expansion of radio spectrum resources” of MIC, Japan. (JPJ000254)

58

REFERENCE[1] Y. Yoshida,” Mobile Xhaul Evolution: Enabling Tools for a Flexible 5G Xhaul
Network,” OFC, 2018[2] N. Aihara, et. al.,” A User-Centric RAN Architecture using Cell Free massive-MIMO
for 6G System,” 2021 IEICE Society conference BS-3-9, Sep. 2021.
[3] IEEE, “802.11ad-2012 – IEEE standard for local and metropolitan area networks –Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY)
Specifications Amendment 3: Enhancements for Very High Throughput in the 60 GHz
Band,” Dec. 2012
[4]

IEEE,

“802.11ay-2021

Telecommunications

and

-

IEEE

Standard

for

Information

Information

Exchange

between

Systems

Technology-Local

andMetropolitan Area Networks--Specific Requirements Part 11: Wireless LAN Medium
Access Control (MAC) and Physical Layer (PHY) Specifications Amendment 2: Enhanced
Throughput for Operation in License-exempt Bands above 45 GHz,” Jul. 2021.
[5] H.Asano, et al., “High power efficiency millimeter-wave network with communication
quality prediction technology,” IEEE VTS 17th APWCS, 2021.
[6] M.Uesugi, et al., “A Study of Uninterrupted Handover Scheme between Millimeter
Waves for 5G Advanced System,” 2023 IEICE General conference B-5-97, Mar. 2023.

59

X. A Study on High-Capacity UL Communication in Relay Systems with
UAV
Kazuyuki Ozaki, Shunsuke Fujio, Kazuo Shirakawa,
Fujitsu Limited

Abstract— In a mobile radio communication system using high frequency bands suchas millimeter wave band and quasi-terahertz band capable of securing wide band, sincecommunication performance of uplink deteriorates in comparison with that of downlink,
asymmetry of UL and DL communication performance becomes a problem. The authors
think that the communication performance of the uplink can be improved by mounting
a relay communication terminal on a device such as UAV (Unmanned Aerial Vehicle)
and controlling it in a place where a line of sight (LOS) can be secured between a user
terminal and a base station and between the base station and the relay communication
terminal. On the other hand, if the relay communication terminal mounted on the UAV
cannot be controlled to the optimum position, the improvement effect decreases. In
addition, since the distance between the relay communication terminal mounted on the
UAV and the base station differs depending on the position of the UAV, the propagation
environment changes greatly. Therefore, in this paper, we proposed a method to control
relay communication terminals at a place capable of maximizing up-link system capacity,
and asymmetric LOS-MIMO with different antenna construction by robust transmission
and reception to change of propagation environment, to show computer simulation
results.
X-1. Introduction
For Beyond 5G/6G, further realization of large capacity and high-speed transmission
is required, and utilization of high frequency band such as millimeter wave and quasiterahertz band which can secure wide band is important [1]. However, the degradationof the transmission capacity of the uplink caused by the inability to raise the effective
radiated power of the user terminal (UE) becomes a factor inhibiting the promotion of
the utilization of the high frequency band. Therefore, to improve the transmission
capacity of the uplink, the authors are examining a mobile relay communication system
in which a relay communication terminal (RS: Relay Station) is mounted on a UAV(Unmanned Aerial Vehicle), etc., and the RS moves with the movement of the UE.
Though the application of the spatial multiplexing technology is effective in thecommunication between RS and UE for the transmission capacity improvement, there isa concern that the transmission capacity cannot be sufficiently improved becauseinterference occurs between UEs to be multiplexed depending on the positional relation
between RS and UE. Since the communication between the UAV and the base station

60

(BS) becomes LOS and the distance between the UAV and the BS is different according
to the movement of the UAV, the LOS-MIMO technology which is robust for the
propagation environment is necessary. In this paper, we propose an optimal placement
method of a relay communication terminal mounted on a UAV and asymmetric LOSMIMO technology with different antenna configurations for transmission and reception.
X-2. Proposed Placement Method
In this paper, we assume a system in which an RS capable of forming multiple beams
performs uplink communication by MU-MIMO (Multiuser MIMO) with different selectedbeams. By determining the arrangement (position and orientation of the antenna) of aplurality of RSs according to the position of the UE and considering the number of spatial
multiplexes, high efficiency of spatial multiplexing by RS is attempted. The outline of
the study system is shown in Fig. X-1.
Considering that the place where the RS can be arranged is limited by the actual
environment, the arrangement of each RS is selected from the predeterminedarrangement candidates. However, since the communication quality between the BS and
RS is also important for relay communication, it is assumed that placement candidates
whose sufficient quality cannot be obtained are excluded. In order of one RS each, thespatial multiplicity in each configuration candidate, that is, the number of different
selected beams, is estimated and the configuration with the largest spatial multiplicity
is determined. However, if there are multiple configurations with the maximum numberof multiplexes, the configuration with the maximum transmission capacity is selected.
This is repeated sequentially for all RSs to determine the placement of all RSs. It is
assumed that the multiplicity and transmission capacity in each placement candidate
are calculated by simply estimating the propagation path based on the positional
relationship between RS and UE. However, in this paper, as an initial examination, theposition information of BS, RS, UE, and each propagation path information are all
known.
The characteristics with our proposed optimal placement method are evaluated bycomputer simulation. Assuming a scenario in which three RSs cover the cell edge areaof a BS sector with a three-sector configuration, the transmission capacity of the uplink
was evaluated. In this evaluation, only the communication from UE to RS was considered,and the communication with the BS was ignored. All propagation paths are visible andonly one direct wave path is considered. Each UE selects and connects the RS and thebeam with the maximum received power. The user scheduling of RS assumes roundrobin and selects the connection UE with different selection beams up to the maximum
space multiplex number and carries out the communication. The RS configuration wascompared between the case in which the RS configuration was evenly spaced at 30 m61above the BS at a distance of 80 m and the case in which the RS configuration wasdetermined by the proposed method according to the UE position from the grid points in
5 m increments. The maximum spatial multiplicity of RS is set to 4, and MMSE is
assumed for signal separation.
Fig. X-2 shows the transmission capacity characteristics with respect to the numberof UEs. Since the possibility of spatial multiplexing of many UEs increases as thenumber of UEs increases, the transmission capacity also increases with the increase in
the number of UEs in any arrangement. However, as mentioned above, by deciding thearrangement by the optimal arrangement method, even when the number of UEs issmall, many spatial multiplexes can be utilized, and therefore, a high value of thetransmission capacity is obtained. Compared with the case where the arrangement isfixed, 13% of 24UE and 27% of 12UE can be confirmed to improve the transmission
capacity.

Fig. X-1. Illustration of the UAV-assisted cellular network system

Fig. X-2. System capacity performanceX-3. Robust LOS-MIMO
As described in Chapter 2, this paper assumes LOS between RS and BS, so direct wave
dominates as the propagation environment. Therefore, in Backhaul communication

62

between RS and BS, it is impossible to apply MIMO technology using multipath whichis generally used in mobile radio communication systems, so technology to improvetransmission speed is required. Hence, we consider applying LOS-MIMO to backhaul
links. In Symmetric-LOS-MIMO (SLOS-MIMO) with the same antenna configuration fortransmission and reception, the propagation channel between transmission andreception is uniquely determined by the distance between transmission and reception
and the element spacing of the antenna. Even if excellent performance is obtained at a
certain distance between transmission and reception, it is known that the robustness tothe distance between transmission and reception is poor because the performance
deteriorates significantly when the distance between transmission and receptionchanges [2]. Therefore, SLOS-MIMO is difficult to apply to RS, and we assume
asymmetric LOS-MIMO (Asymmetric LOS-MIMO: ALOS-MIMO) with different
antenna configurations for transmission and reception, as discussed in [2]. As revealed
in, asymmetric LOS-MIMO shows less degradation of channel capacity fortransmit/receive distance and more robustness for transmit/receive distance thansymmetric LOS-MIMO.
Although simulation results and experimental results are shown when antennas areplaced on the circumference of a certain plane and are opposed to each other, no study
has been made on Uniform Linear Array (ULA) or Uniform Rectangular Array (URA)
adopted in BSs such as 5G. In this paper, we investigate asymmetric LOS-MIMO when
ULA and URA antenna configurations are adopted.
The antenna for transmission and reception is constructed on a certain plane, and thecase in which the planes face each other so as to be parallel is assumed. All propagation
paths are visible and only one direct wave path is considered. The antenna element
spacing for transmission and reception was calculated using R=20 m by using ideal
equation [3] for ULA and URA.
Fig. X-3 (a) shows the channel capacities of symmetric LOS-MIMO (SLOS-MIMO) andasymmetric LOS-MIMO (Asymmetric LOS-MIMO (ALOS-MIMO)) in ULA. As can beseen from the figure, SLOS-MIMO shows a drop in channel capacity around 10 and 15m, while ALOS-MIMO shows no drop in channel capacity after 8 m. Fig. X-3 (b) shows
the channel capacities of SLOS-MIMO and ALOS-MIMO in the URA. Like ULA, SLOSMIMO shows a drop in channel capacity around 10 m, while ALOS-MIMO shows no drop
after 10 m.

63

(a) ULA(b) URA

Fig. X-3. Channel capacity performance of ALOS-MIMO and SLOS-MIMO
X-4. Conclusion
In this paper, we discuss the optimal placement method of RS considering themultiplicity of UE accommodations and the robust LOS-MIMO for robust capacity
enhancement between RS and BS in high frequency mobile radio communication
systems using mobile relay communication terminal such as UAV. Computer simulation
results show that the optimal placement method can achieve 27% of maximum
transmission capacity, and robust LOS-MIMO to increase the capacity of RS and BS.
Acknowledgements
This research is supported by the Ministry of Internal Affairs and Communications inJapan (JPJ000254).
REFERENCE[1] 3GPP TS 38.104 V15.0.0, “Base Station (BS) radio transmission and reception,” Dec.
2017.
[2] N. Matsumura, K. Nishimori, R. Taniguchi, T. Hiraguri, T. Tomura and J. Hirokawa,"NovelUnmanned

AerialVehicle-BasedLine-of-Sight

MIMO

Configuration

Independent of Transmitted Distance Using Millimeter Wave," IEEE Access, Vol. 8, pp.
11679-11691, 2020.
[3] Bøhagen, F., Orten, P. & Øien, G. Optimal Design of Uniform Rectangular Antenna
Arrays for Strong Line-of-Sight MIMO Channels. J Wireless Com Network 2007, 045084

64Abbreviation List
Abbreviation

Explanation

ABG

Alpha-Beta-Gamma

AI

Artificial Intelligence

ALD

Atomic Layer Deposited

AMC

Adaptive Modulation and Coding

AoA

Angle of Arrival

AR

Augmented Reality

ASIC

Application Specific Integrated Circuit

AWG

Arbitrary Waveform Generator

BAN

Body Area Network

BCB

Benzo cyclobutene

BER

Bit Error Rate

BF

BeamForming

BS

Base Station

CC

Component Carrier

CI

Close-in

CMOS

Complementary Metal Oxide Semiconductor

CPS

Cyber Physical System

CSI

Channel State Information

DC

Direct Current

DFT

Discrete Fourier Transform

DL

Down Link

DNN

Deep Neural Network

DOA

Direction of Arrival

DSP

Digital Signal Processing

EIRP
EVM

Error Vector Magnitude

eWLB

embedded Wafer Level Ball grid array

FDD

Frequency Division Duplex

FDE

Frequency Domain Equalize65Abbreviation

Explanation

FSPL

Free Space Path Loss

HARQ

Hybrid Automatic Repeat Request

HPBW

Half Power Beam Width

IBO

Input Back Off

IFFT

Inverse Fast Fourier Transform

InH

Indoor hotspot cell

ISAC

Integrated Sensing and Communication

ITU-R

International
Telecommunication
Radiocommunication Sector
Key Performance Indicator

KPI
LAN

Local Area Network

LNA

Low-Noise Amplifier

LOS

Light of Sight

LTE

Long Tern Evolution

MCM

Multichip Module

MIMO

Multiple-Input and Multiple-Output

MMIC

Monolithic Microwave IC

MS

Mobile Station

MOS

Metal Oxide Semiconductor

MOS-HEMTMSL

Metal-Oxide-Semiconductor
Transistor
Microstrip Line

Eigh-Electron-Mobility

NLOS

Non-Line of Sight

NR

New Radio

NRNT

New Radio Network Topology

OAM

Orbital Angular Momentum

OFDM

Orthogonal Frequency Division Multiplexing

PA

Power Amplifier

PAE
PCB

Printed Circuit Board

PLE

Path Loss Exponent

QMH

Qualitative Microwave Holography

RAN

Radio Access Network

66

Union

Abbreviation

Explanation

RAT

Radio Access Technology

RD

Relay Device

RFRadio Frequency

RIS

Reconfigurable Intelligent Surface

RMSE

Root Mean Square Error

RS

Relay Station

Rx

Receiver

SAG

Selective-Area Growth

SC

Single Carrier

SiP

System-in-Package

SISO

Single-Input Single-Output

SIW

Substrate-Integrated Waveguide

SNR

Signal to Noise power Ratio

TDD

Time Division Duplex

TDS

Time Domain Spectroscopy

THz

Tera Hertz

TMA

Trimethylaluminum

TSV

Through-silicon Via

Tx

Transmitter

UCA

Uniform Circular ArrayUE

User Equipment

UL

Up LinkVR

Virtual Reality

67