Advanced Wireless & Communication
Research Center

Message from the Director, Prof. Yasushi Yamao
Thirteen years have passed since Advanced WirelessCommunication Research Center (AWCC) was establishedin the University of Electro-Communications (UEC). For
the years, AWCC has been aiming and conducting four
missions that are;-

Dedicationtoadvancedresearchonwireless

communications; offering more unique results.
- Education in graduate school for cultivating specialty inengineering; specialized and universal education in the area.
- Active collaboration / joint research with industries and government; transferring the outcomes tothe society.
- Constant acquisition of competitive research funds; for self-supported operation.
Three years ago, AWCC created a new vision, “Ambient Wireless in Connected Community (AWCC)”,and changed its name to “Advanced Wireless & Communication Research Center”. With the new
vision and name, AWCC intends to cover broader research area including not only wirelesscommunications but also any promising aspects of “wireless” and “communications”. As an academic
institute, it is our mission to pursue basic research in science and technology. Toward the goals, AWCC
will enhance its force and strengthen its presence in the world.
We are focusing the following four research sectors in AWCC.
(1) Wireless Technology as Social Infrastructure
Wireless technologies will have more importance in the society as the base of safe, secure andsmart life for the individual and the community. Intelligent Transport System (ITS) is one of the
focused topics, anticipating the great demand for automated driving.
(2) Innovative Hardware for Wireless & Communication
Demands for broadband and high-capacity mobile communication systems are very strong, and 5G
system is being developed in the world. The 5G system introduces new usage of frequency spectra
called multi-band multi-access, which requires innovation in RF hardware to achieve higher-accuracy
signal transmission with flexibility. Also, wireless power transfer is another hot and important topic.
(3) Advanced Wireless System & Networks
AWCC has developed many fundamental technologies such as distributed dynamic multi-hop
network, cognitive radio, fault-tolerant network operation, and radio environment-aware
communications. From now on, we integrate the technologies and establish an ultimate wirelessnetwork design.
(4) Exploring Low Power Wireless
By reducing power consumption of wireless system dramatically, applications of wirelesscommunications will spread wider than now. It will make all things connected in the world, realizing
the word "IoT". Innovative low-power technologies are necessary to realize such a world.
As the open research center to the society, AWCC would like to think together with people andcontribute much in research and education of “wireless” and “communications”. We hope your kind
help and great understanding to AWCC.

-1-１. ABOUT AWCC
1.1 OVERVIEWThe Advanced Wireless Communication
Research Center (AWCC) was launched in
April 2005 with the aims of establishing a
global hub for wireless communications;advancing education in wireless technology;
industrial

collaboration

andtechnology

transfer; and nurturing young engineers
with strong emphasis on both theoreticalandexperimental

aspectsofwireless

communications. In April 2015, the center was re-launched as the Advanced Wireless andCommunication Research Center with the same abbreviation, AWCC, to enhance its remarkablerange of activities over the previous ten years. With funding of approximately 1000 million yen
over nine years, the center consists of 4 full time, 5 concurrent, 20 cooperative, and 6 visiting
professors. In addition, there are 9 visiting professors from industry and more than 100 graduate
students, post-doctoral and research fellows. The center actively contributes to academic societiesand publishes more than 150 papers annually in top journals and proceedings of international
conferences.
The AWCC organizes regular seminars and workshops with the highlight of 2014 being the“Tokyo Wireless Technology Summit” held in March 2014. The meeting focused on the next major
phase of mobile telecommunications called 5th generation (5G) and attracted approximately 240
participants from all over the world.

1.2 FACILITIESAWCC is located on the east-campus of the University ofElectro-Communications in Chofu city, Tokyo near Shinjuku
district in Japan. The center has opened with 10,441 square footof modern research space containing a class room, twoconference rooms, four research offices, and two experimentrooms with a wide range of instruments including FPGA
development platforms, signal generators, vector network
analyzers, spectrum analyzers, software defined radios, and soon. Also, it has extensive computer and network resources
including high-speed workstations and personal computerswhich are integrated with resources of the Univeristy of ElectroCommunications.

-2-Furthermore, the center will open a new remote research office in UEC Alliance Center from
April 2017 to enhance joint research projects with industry and overseas universities. This
remote office has a common discussion space with high-quality video conference system, an
experiment space with general instruments, and two personal workspaces for visiting
researchers. Moreover, its infrastructure is completely integrated with AWCC computing andnetwork resources.

1.3 PEOPLE【Director, Prof. Yasushi Yamao】
Dr. Yasushi Yamao received his B.S., M.S., and Ph.D. degrees inelectronics engineering from Kyoto University, Kyoto, Japan, in 1977,
1979, and 1998, respectively. In 1979, he joined the Nippon Telegraphand Telephone Corporation (NTT) Laboratories, Japan, where his major
activities included leading research on GMSK modulator /demodulator
and GaAs RF ICs for digital mobile communications, and developmentof PDC digital cellular handheld phones. In 1993, he moved to NTT
DoCoMo Inc. and directed standardization of high-speed paging system (FLEX-TD) anddevelopment of 3G radio network system. He also joined European IST research programs for
IP-based 4th generation mobile communication. In 2005, he moved to the University of ElectroCommunications as a professor of the Advanced Wireless Communication Research Center(AWCC). Prof. Yamao is a Fellow of the IEICE and member of the IEEE and IPSJ. He served as
the Vice President of IEICE Communications Society (2003-2004), the Chairman of IEICE
Technical Group on Radio Communication Systems (2006-2008), the Chief Editor of IEICE
Communication Magazine (2008-2010), a Director of the IEICE (2016-2017) and the Vice
Chairman of IEEE VTS Japan chapter (2009-2015). Now he is the Chairman of IEEE VTSTokyo/Japan chapter-3-

【Full time Prof. Takeo Fujii】
Takeo Fujii was born in Tokyo, Japan, in 1974. He received the B.E., M.E.
and Ph.D. degrees in electrical engineering from Keio University,
Yokohama, Japan, in 1997, 1999 and 2002 respectively. From 2000 to 2002,
he was a research associate in the Department of Information andComputer Science, Keio University. From 2002 to 2006, he was an
assistant professor in the Department of Electrical and Electronic
Engineering, Tokyo University of Agriculture and Technology. From 2006
to 2014, he has been an associate professor in Advanced WirelessCommunication Research Center, The University of Electro-Communications. Currently, he is a
professor in Advanced Wireless and Communication Research Center, The University of ElectroCommunications. His current research interests are in cognitive radio and ad-hoc wirelessnetworks. He received Best Paper Award in IEEE VTC 1999-Fall, 2001 Active Research Awardin Radio Communication Systems from IEICE technical committee of RCS, 2001 Ericsson Young
Scientist Award, Young Researcher's Award from the IEICE in 2004, The Young Researcher
Study Encouragement Award from IEICE technical committee of AN in 2009, Best Paper Award
in IEEE CCNC 2013, and IEICE Communication Society Best Paper Award in 2016. He is amember of IEEE and a fellow of IEICE.

【Full time Associate Prof. Koji Ishibashi】
Koji Ishibashi received the B.E. and M.E. degrees in engineering fromThe University of Electro-Communications, Tokyo, Japan, in 2002 and2004, respectively, and the Ph.D. degree in engineering from Yokohama
National University, Yokohama, Japan, in 2007. From 2007 to 2012, he
was an Assistant Professor at the Department of Electrical and Electronic
Engineering, Shizuoka University, Hamamatsu, Japan. Since April 2012,he has been with the Advanced Wireless Communication Research Center(AWCC), The University of Electro-Communications, Tokyo, Japan where
he is currently an Associate Professor. From 2010 to 2012, he was a Visiting Scholar at the Schoolof Engineering and Applied Sciences, Harvard University, Cambridge, MA. Prof. Ishibashi has
contributed more than 80 articles to international journals and conference proceedings. His
current research interests are signal processing, cooperative communications, RF energy
harvesting, rateless coding, and information theory. He is a member of IEEE and IEICE.

-4-

【Full time Associate Prof. Koichi Adachi】
Koichi Adachi received the B.E., M.E., and Ph.D. degrees in engineeringfrom Keio University, Japan, in 2005, 2007, and 2009 respectively. From2007 to 2010, he was a Japan Society for the Promotion of Science (JSPS)
research fellow. From May 2010 to May 2016, he was with the Institute for
Infocomm Research, A*STAR, in Singapore. Currently, he is an associate
professor at The University of Electro-Communications, Japan. His
research interests include cooperative communications and energy
efficient communication technologies. He was the visiting researcher at
City University of Hong Kong in April 2009 and the visiting research fellow
at University of Kent from June to Aug 2009.
Dr. Adachi served as General Co-chair of the 10th and 11th IEEE Vehicular Technology Society
Asia Pacific Wireless Communications Symposium (APWCS) and Track Co-chair of Transmission
Technologies and Communication Theory of the 78th and 80th IEEE Vehicular Technology
Conference in 2013 and 2014, respectively. He is an Associate Editor of IET TRANSACTION ON
COMMUNICATIONS since 2015 and IEEE WIRELESS COMMUNICATIONS LETTERS since2016. He was recognized as the Exemplary Reviewer from IEEE COMMUNICATIONSLETTERS in 2012 and IEEE WIRELESS COMMUNICATIONS LETTERS in 2012, 2013, 2014,
and 2015. He was awarded excellent editor award from IEEE ComSoc MMTC in 2013.

【Concurrent Prof. Koichiro Ishibashi】
Koichiro Ishibashi has been a professor of The University of ElectroCommunications, Tokyo, Japan since 2011. He received PH. D degreefrom Tokyo Institute of Technology in 1985. He joined Central ResearchLaboratory, Hitachi Ltd. in 1985, where he had investigated low power
technologies for Super H microprocessors and high density SRAMs.
From 2004 to 2011, he was in Renesas Electronics where he developed
low power IPs mainly for mobile phone SOCs as a department manager.
He has presented more than 110 academic papers at international conferences including
ISSCC, IEDM invited papers, and IEEE Journals. He was awarded R&D 100 for thedevelopment of SH4 Series Microprocessor in 1999. He is a member of IEICE and a Fellow ofIEEE.
His current interests include design technology of low power LSI, and IoT applications using
the low power LSIs. They include low power design technology using SOI devices and energy
harvesting sensor networks.

-5-

【Concurrent Prof. Takayuki Inaba】
Takayuki Inaba received a B.S. degree from the Department of Physics,
Tokyo Institute of Technology, in 1981, completed the M.E. program inphysics in 1983. He received the Ph.D. degree in engineering from Tokyo
Institute of Technology in 2001. Since April 2008, he has been with the
University of Electro-Communications, where he is a Professor at the
Department of Mechanical and Intelligent Systems Engineering,
Graduate School of Informatics and Engineering. He has been engaged inresearch and development of radar signal processing, and adaptive array signal processing, andautomotive radar systems. He is a senior member of IEEE. He is a recipient of theTelecommunications Advancement Foundation Award (32th), IEEJ Distinguished Paper Award(72th), 2014 IEEE AES Japan-chapter Best Paper Award, IEICE Communications Society
Distinguished Contributions Award 2009, 2006 IEEE AES Japan-chapter Best Paper Award, and
IEICE Communications Society Excellent Paper Award 2006.

.

【Concurrent Prof. Koji Wada】
Koji Wada received the B.E. and M.E. degrees from Kinki University,
Osaka, Japan, in 1991 and 1995, respectively, and the Doctorate degreefrom Yamaguchi University, Yamaguchi, Japan, in 1999. From 1999 to
2004, he was a Research Associate with the Department of ElectricalEngineering and Electronics, Aoyama Gakuin University, Kanagawa,Japan. From 2004 to 2015, he worked as an Associate Professor at the
Department of Electronic Engineering, the University of ElectroCommunications, Tokyo, Japan and he is Currently a Professor at the
Department of Computer and Network engineering, Graduate School ofInformatics and Engineering, the University of Electro-Communications. His research interests
include resonators, filters, multiplexers, multiband circuits, tunable circuits, periodic structure,and metamaterial circuits. Dr. Wada is a member of the Institute of Electronics, Information
and Communication Engineers (IEICE), Japan, Institute of Electrical Engineers of Japan(IEEJ), and Japan Institute of Electronics Packaging (JIEP).

-6-

【Concurrent Associate Prof. Ryo Ishikawa】
Ryo Ishikawa received the B.E., M.E., and D.E. degrees in electronicengineering from Tohoku University, Sendai, Japan, in 1996, 1998, and2001, respectively. In 2001, he joined the Research Institute of ElectricalCommunication, Tohoku University, Sendai, Japan. In 2003, he joined the
University of Electro-Communications, Tokyo, Japan. His researchinterest is the development of microwave compound semiconductor
devices and related techniques. He was the recipient of the 1999 Young
Scientist Award for the Presentation of an Excellent Paper of the Tohoku
Chapter, Japan Society of Applied Physics.

【Concurrent Associate Prof. Motoharu Matsuura】
Motoharu Matsuura received the Ph.D. degree in electrical engineeringfrom the University of Electro-Communications, Tokyo, Japan, in 2004.
In 2007, he joined the Department of Information and Communication
Engineering at the University of Electro-Communications as an AssistantProfessor. From 2010 to 2011, on leave from the university, he joined the
COBRA Research Institute, Eindhoven University of Technology,
Eindhoven, The Netherlands, as a Visiting Researcher, where he studied
ultrahigh-speed optical signal processing using semiconductor-based
devices. He is currently an Associate Professor with the Graduate School of Informatics andEngineering, Department of Communication Engineering and Informatics, University of ElectroCommunications. His research interests include optical signal processing, photonic subsystems,
and radio-over-fiber transmission systems. He is the author or coauthor of more than 180 papers
published in international refereed journals and conferences. He received the Ericsson Young
Scientist Award in 2008, the FUNAI Information Technology Award for Young Researcher in
2009, and the Telecommunication System Technology Award of the Telecommunications
Advancement Foundation in 2011. He is a member of IEEE, OSA, and IEICE.

【Visiting Professors】
Prof. Kazuhiko Honjo, Ph.D.
Prof. Yoichiro Takayama, Ph.D.
Prof. Akira Saito, Ph.D.
Prof. Masashi Hayakawa, Ph.D.
Prof. Hiroshi Suzuki, Ph.D.
Prof. Mitsuo Makimoto, Ph.D.
-7-

【Cooperative Professors】
Prof. Nobuo Nakajima, Ph.D.
Prof. Haruhisa Ichikawa, Ph.D.
Prof. Kazuo Ohta, Ph.D.
Prof. Sadao Obana, Ph.D.
Prof. Toshihiko Kato, Ph.D.
Prof. Naoto Kishi, Ph.D.
Prof. Tetsuro Kirimoto, Ph.D.
Prof. Kazuo Sakiyama, Ph.D.
Prof. Fengchao Xiao, Ph.D.
Prof. Xi Zhang, Ph.D.
Prof. Cong-Kha Pham, Ph.D.
Associate Prof. Manabu Akita, Ph.D.
Associate Prof. Yoshiaki Ando, Ph.D.
Associate Prof. Hiroyuki Kasai, Ph.D.
Associate Prof. Toshiharu Kojima, Ph.D.
Associate Prof. Hisa-Aki Tanaka, Ph.D.
Associate Prof. Kazuki Nishi, Ph.D.
Associate Prof. Wu Celimuge, Ph.D.
Assistant Prof. Satoshi Ono, Ph.D.
Assitant Prof. Katsuya Suto, Ph.D.
【Cooperative Professors from Industry】
Prof. Kunio Uchiyama (Hitachi Ltd.)
Prof. Yukihiko Okumura (NTT Docomo R&D)
Prof. Yoji Kishi (KDDI Research Inc.)-8-

Prof. Terunao Soneoka (NTT-AT)
Prof. Isamu Chiba (Mitsubishi Research Institute Inc.)
Prof. Hideki Hayashi (Softbank Corp.)
Prof. Eisuke Fukuda (Fujitsu Laboratory Ltd.)
Prof. Yukitsuna Furuya (WiTLa)
Prof. Kenji Yoshida (GM Holdings Inc.)-9-

2. Research Activities
2.1 Division of Wireless Technologies as Social Infrastructure
2.1.1 Purpose of Research
Wireless technologies will have more importance in the society as the base of safe,
secure and smart life for individuals and community. Various types of machine tomachine communication such as sensors, IoT devices and vehicular communications will
spread in the society taking little notice but support safety and secureness of society, as
well as creating more comfortable and smarter life. The goal is to develop suchtechnologies.

2.1.2 Research Staffs and Their Specialties
Prof. Yasushi Yamao（Head of Division, ITS, RF-ID)
Prof. Takeo Fujii（ITS, Radio Environment Analysis (REA), DPRN, Wireless security）
Prof. Takayuki Inaba（ITS, Rader）
Associate Prof. Koichi Adachi (Drone)

2.1.3 Major Research Outcomes in 2018
(A) Intelligent Transport System (ITS)
Advance technologies for Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I)
communications towards automated driving are studied. Since Vehicular communications
are conducted in fully distributed environments, wireless communication techniques forsuch environments are pursued. This work was supported by the Ministry of Internal
Affairs and Communications (MIC) of Japan under the Strategic Innovation Promotion(SIP) program during physical years 2014 to 2016, MIC-1, "Development of V2V and V2I
Communication Technologies necessary for Automated Driving Systems".
On the other hand, in order to realize fully automated driving, it is not sufficient bystudying only vehicular communication issues, but necessary to discuss and collaborate
with the researchers who study automated vehicle control and stand-alone sensors on thevehicles. Therefore we established a project with related members to such subjects andcollaborate on the Grants-in-Aid for Scientific Basic Research A, "Basic Research for
Integrated Automated Driving System combining Stand-Alone Sensors and Cooperation by
vehicle communications."[Field Test of Creating Spectrum Environment Map for V2V Comminutions] (Fujii Lab.)
Connected and automated vehicles (CAVs) have attracted attention because CAVs are
expected to revolutionize future transportation system. However, wireless connection has
unstable reliability according to the surrounding environment like building geography andcongestion. In order to solve the unstable wireless connection with low reliability, we haveproposed using a spectrum database, which stores the radio status between the transmitter
location and the receiver location. For example, if the received signal power of each link isstored at the database with transmitter and receiver location, the users can understand thelink reliability before transmission. To create the database we utilize a common broadcast
vehicle to vehicle communication (V2V) packet which includes transmitter location.
Therefore, if the receiver can receive the packet, the locations of transmitter and receiver,received signal power can be collected. The collected data are uploaded to the spectrum- 10 -

database and radio environment map (REM) can be created as shown in Fig. 2.1-1. In orderto proof of this concept, a field test is performed for obtaining the measurement data overV2V communication using three vehicles at UC Berkeley Richmond Filed Station. We utilize
5.9GHz band Dedicated Short Range Communications (DSRC) and different building
environment fields are compared. The test sites is shown in Fig. 2.1-2 and the created REM
can be shown in Fig. 2.1-3. From these figures, we can understand the different radio
propagation due to building and can recognize the different reliability between two
transmitter locations if the link is crossed at the center of loop.

Figure 2.1-1 Concept of spectrum database with
communication reliability.
North

loop2

2-A

[dBm]

2-A

-40

-50

Grassland andseveral trees-60(a) Tx location at 2-A

1-A

-70
1-A
-80

Small buildings
-90

-100

loop1

Figure 2.1-2 Field test site.

(b) Tx location at 1-A

Figure 2.1-3 Received signal power map.

[ V2I Multi-Hop Broadcast Communication by TC-BF Method] (Yamao Lab.)
A novel Infrastructure to Vehicle (I2V) multi-hop broadcast communication technique wasproposed. The proposed Time-Controlled Broadcast Forwarding (TC-BF) method enables
more efficient information delivery on the road compared to the existing broadcast packet
forwarding schemes such as Flooding and Irresponsible Forwarding (IF) methods. The
proposed forwarding method introduces priority control by differentiating transmission
waiting time according to link distance and prohibits duplicate forwarding. The priority
control according to link distance enhances longer distance forwarding and enables wider
broadcast service area. During the waiting time, the waiting node monitors other nodes
whether they forward the same packet or not. If no other node forwards the same packet, the- 11 -

node can forward the packet as the first forwarder. This is important to suppress unnecessary
second forwarding by the shorter distance node after the longer distance node has completed
forwarding. Packet delivery rate (PDR) and forwarding efficiency of the proposed scheme are
evaluated by using computer simulations. Fig. 2.1-5 shows broadcast packet delivery rate(PDR) for 50 vehicle nodes on the straight road of 2 km. It is concluded that the TC-BF can
reduce unnecessary forwarding and keep high PDR with extended communication range.

Fig. 2.1-4 Multi-hop roadbroadcast communication.

tovehicleFig. 2.1-5 Broadcast packet delivery rate(PDR) for 50 vehicle nodes on the straightroad of 2 km.

[Propagation Loss Characteristic Analysis of V2V Communication for Right-Turn Accident
Prevention Scenario] (Yamao Lab.)One of the scenarios that is highly expected for V2V communication is right-turncollision prevention in intersections. In this scenario, however, there is a concern that alarge vehicle waiting in an intersection frequently blocks the radio propagation path
between a right-turn vehicle and a coming-though vehicle (Fig.2.1-6)). Therefore, study
on the radio propagation for this scenario is essential to confirm the effectiveness of V2V
communication. In this study, effect of surrounding buildings on large vehicle shadowing inintersection V2V communication has been analyzed by FDTD method (Fig.2.1-7). The resultof FDTD analysis was compared with that of ray tracing in terms of propagation loss.
Although the shadowing of large vehicles issues large attenuation, reflected waves from thesurrounding buildings mitigate the propagation loss by 5-20 dB. The results of ray tracing
analysis show smaller loss values by around 5 dB from that of FDTD. This error can be
reduced by employing FDTD / Ray tracing hybrid technique.

Fig. 2.1-6 Right-turn collision prevention scenario.
Fig. 2.1-7 Electric field strength map in intersection.

- 12 -

[Outage Probability Analysis of Sensor Nodes Served by an ULA Equipped UAV-BS](AdachiLab.)
In 2017, we have proposed an unmanned
aerial vehicle (UAV) with a uniform linear array
antenna (ULA) has been proposed to tackle thehigh outage probability due to the low transmit
power of sensor node (SN) and the existence ofinterfering SNs. However, the performance
improvement had been evaluated by computer
simulation only. This year, we have analyticallyevaluated the effectiveness of this method. The
approach being used is to evaluate the possibilityof the achievable signal-to-noise power ratio
Fig.2.1-8 Outage probability function(SNR) or signal-to-interference plus noise powerof distance to UAV
ratio (SINR) falls below a certain threshold
which is called outage probability. For the tractable analysis, the positions of the desired SN
and the interfering SN were fixed at certain locations. A tilt angle of the antennaarrangement is determined so that the antenna directivity of the array antenna towards thecoverage area. The closed form expression of the outage probability for the proposed method
is derived separately for the cases of no interfering SN and interfering SN. The analyticaland the simulation results matched perfectly, which showed the derived outage probability
expression is valid as shown in Fig. 2.1-8.
(B) Radar Signal Processing[Vehicle Onboard Radar] (Inaba Lab.)We have proposed stepped multiple frequency (SMF) modulation. The unique radar
modulation/demodulation method can achieve a high range resolution and a long-range
detection performance by a narrow receiver bandwidth compared to transmitting bandwidth.
That is why this method has long range detection performance. Stepped multiple frequency
CPC modulation proposed by Inaba Lab. also made it possible to obtain the extremely low
range side-lobe by the short code length in CPC pulse compression. Authors have developed
the millimeter wave radar using stepped multiple frequency CPC (Fig.2.1-9). Thesemillimeter wave radars meet the specified low-power radio station standard of the millimeterwave in Japan. In recent years, the legal system for short range radar has been changed foruse of the ultra-wide bandwidth of 4 GHz in 79 GHz band. The advantage of this method
itself must be more remarkable for use of the ultra-wide bandwidth. On the other hand, SMF
modulation suffer from the deterioration of the detectable velocity accompanied by expansionof transmission bandwidth, since it adopts the transmission sequence of switching thefrequencies in time-division. In the case of use of ultra-wide bandwidth of 4GHz, we also face
not only the velocity ambiguity but the range ambiguity problem, since the frequency steps
also must be sparse for keeping the number of pulse repetitions. We proposed the radar
modulation/demodulation method based on SMF modulation which adopts sparse-random
frequency step sequence. The range-velocity ambiguity was mitigated by the sequence andthe side-lobe due to the sparse-random frequency step sequence was subtracted by the signal
processing of iterative signal subtraction and frequency estimation (Fig.2.1-10). The proposed
method can detect the targets having different signal power with the resolution of ultrawideband without ambiguity in both velocity and range profiles.

- 13 -

Range /Velocity

Velocity

CPC0

CPC0

PC

A/D

CPC0

PDF

+/CPC1

CPC1

CPC1

Phase
Comp.

CPC0

ADD

CPC1 CPC0+CPC1

SWW

Iteration of iterative signal subtraction and
Iteration of RSSF
frequency estimation
Ref.

Millimeter wave radar

Fig. 2.1-9 Millimeter wave radardeveloped by Inaba Lab. of UEC

Signal Generation（each frequency step，
code，pulse）

Detection

Fig.2.1-10 Block diagram of the signal processing of
iterative signal subtraction and frequency estimation
method in stepped multiple frequency CPC.

(C) RF-ID Communications[Radio Propagation Analysis for 920MHz RFID on Metallic Storage Shelf] (Yamao Lab.)Radio Frequency Identification (RFID) is one of the promising technologies of Internet ofThings (IoT) that provides basis of the future economy and society. The RFID system consistsof Reader/Writer (R/W) and RF tags. Recently passive RF tags are widely used because it isvery small, needs no battery and low-cost. It is rapidly spreading in various area such as
shops, factories, and public spaces including libraries. Since RFID technology depends on theradio propagation between R/W and RF tags, reliability of the communication is crucial.
However, RFID is easily affected by the environment where RF tag is placed. In this study,
radio propagation of 920MHz RFID on metallic storage shelf is analyzed by using FiniteDifference Time-Domain (FDTD) simulation. Experiments using a thin sheet-type RF tag on
a cardboard box are conducted for verification of the analysis.
Simulated electric field strength created by the R/W antenna is shown in Fig. 2.1-11. As
can be seen from the figure, standing waves are observed in the shelf. In the experiment,height pattern of the R/W received power caused by RF tag reflection was measured. The
measured result is shown in Fig. 2.1-12, where blue line shows the received power andvertical broken lines represent null points in simulation. Communication failed when thereceived power is less than -60 dBm. Areas of communication failure and simulated nullpoints match well. It is concluded that the standing waves severely affect the reliability of
RFID communication.

Fig.2.1-11 Electric field strength map
in metal shelf.

Fig.2.1-12 Measured height pattern of received power at R/W.

- 14 -

2.1.4 Funds【Grants-in-Aid for Scientific Research】
1. Scientific Research A “Basic Research on Automated Driving System by Integrating
Autonomous Sensing and Cooperative Information Sharing Technologies”
Y. Yamao, T. Fujii, T. Inaba, S. Obana, T. Ogitsu (Gunma Univ.)
2. Fund for the Promotion of Joint International Research (Fostering Joint International
Research) “Research on Advanced Wireless Vehicle Networks with Learning Spectrum
Environment for Cooperative Self Driving”
T. Fujii
3. Scientific Research C “Research on Energy Efficient Wireless Communications Network
Using UAV-BS”
K. Adachi【Commissioned Research】
1. Strategic Information and Communications R&D Promotion Program (SCOPE), “R & D
of Ultra-wide band coherent radar technology”
T. Inaba and M. Akita【Cooperative Research】
1. "Research on Marine Radar signal processing"
Y. Yamao
2. “Improvement in recognition rate of RF IDs”
Y. Yamao
3. "Research on Communications Technology for Machine Tools"
K. Adachi and Y. Yamao【Other Funds】
1. DENSO Corporation, “Comparative investigation of millimeter wave radar
modulation for automotive”, Academic consulting
T. Inaba
2. Kyosan Electric Mfg. Co., Ltd., “Parameter design for stepped multiple frequency CPC
radar”, Academic consulting
T. Inaba
3. DENSO Corporation, “Program of evaluation of automotive radar modulation”, Patent
Number 5704552), License agreement
T. Inaba
4. DENSO Corporation, “Program of generation of interference data”, Patent Number
5704552, License agreement
T. Inaba
5. Kyosan Electric Mfg. Co., Ltd., “Analysis program of stepped multiple frequency CPC”,
License agreement
T. Inaba- 15 -

2.2

Advanced Hardware Research Division

2.2.1 Purpose of Research
Research and development of wireless information/power transmission hardware
for next generation mobile communication base stations and terminal devices

2.2.2 Research Staffs and Their Specialties
Prof. K. Wada (Head of Division, Microwave circuits)Prof. Koichiro Ishibashi (Low Power RF Devices, Sensor Networks)
Prof. Y. Yamao (Reconfigurable RF Circuit, Nonlinear Compensation)
Associate Prof. R. Ishikawa (Microwave/Millimeterwave Devices and Circuits)
Associate Prof. M. Matsuura (Wideband RoF Systems, Devices, Fibers andIntegration)
Visiting Prof. K. Honjo (Microwave Engineering, Semiconductor Devices)
Visiting Prof. Y. Takayama (Microwave Power Amplifier Systems)
Visiting Prof. A. Saitou (Electro-Magnetic Wave Engineering, Antennas)

2.2.3 Major Research Outcomes in 2018
(A) Multi-Band Multi-Access Wireless Hardware for 5G System[Low-/High-SHF-Band GaN MMIC Power Amplifiers]（Ishikawa Lab.）For 5G communication systems, we have developed low- and high-SHF band GaN HEMTMMIC power amplifiers. For the low-SHF band, a fully integrated asymmetric Doherty power
amplifier has been developed. To minimize the circuit size, a two-power-level impedance
optimization method was applied instead of using a quarter-wavelength transmission line
impedance inverter for load modulation in the Doherty amplifier. For this optimization,
asymmetric configuration is required to realize optimum impedance conditions. In the actual
design at a 4-GHz band on the MMIC, lumped circuit elements were used for all components(carrier/peaking amplifiers, a phase adjusting circuit, and an Wilkinson power divider). The
4-GHz-band GaN HEMT MMIC Doherty amplifier was designed and fabricated by using a
0.25-µm GaN/SiC HEMT process with a circuit area of 2320 by 1500 µm2 (Fig. 2.2-1). The
GaN HEMT MMIC Doherty amplifier exhibited a maximum drain efficiency of 56% and amaximum power-added efficiency (PAE) of 53% at 4.3 GHz, with a saturation output powerof 36 dBm. In addition, PAE of 44% was achieved at 4.2 GHz on a 6-dB output back-off
condition.
For the high-SHF band, a GaN HEMT MMIC power amplifier has been designed at 28 GHz
by using the same GaN MMIC process. The 0.25-µm process can save a cost due to a use of

Fig. 2.2-1 4-GHz-band GaN HEMT MMIC
asymmetric Doherty power amplifierFig 2.2-2 28GHz-band GaN HEMT MMIC
power amplifier- 16 -

on optical photolithography process, though a maximum oscillation frequency is not so high(about 50 GHz). A simple and wide-line-width layout design was performed so that circuit
insertion loss became as low as possible (Fig. 2.2-2). The fabricated GaN HEMT MMIC
amplifier exhibited a maximum drain efficiency of 26% and a maximum power-added
efficiency (PAE) of 20% at 26.4 GHz, with a saturation output power of 26 dBm. These
performances are applicable for actual wireless communication systems.
[ Reconfigurable Bandpass Filter with Integrated Switch Array]（Yamao Lab.）For the efficient use of frequency
spectrum under multi-band operation in
5th generation mobile communication(5G), RF circuits that can flexibly switch
multiple bands are important. Three-bit
reconfigurable bandpass filters (BPF) havebeen proposed that can choose one of eightcenter frequencies in UHF or SHF bands.
However, the RF switches employed for thefrequency switching have been treated as
ideal component and not studied in detail.
In this study, we focus on the FET switches
Fig. 2.2-3 Three-bit reconfigurable BPF with RF
in the reconfigurable BPF for SHF bandswitch arrays.
and analyze the influence of their parasitic
elements on the performance of BPF. In order to reduce insertion loss of the BPF, a newgate width design method for RF switch array (SWA) is proposed. A 3-bit RF SWA isfabricated using 0.5 μm gate pHEMT process and installed in the prototype BPF withpassband center frequency changeable from 3.5 to 4.64 GHz. The measured RF
characteristic of the prototype is close to the result of circuit simulation.

Fig. 2.2-4 PHEMT 3-bit switch array IC.

Fig. 2.2-5 Prototype BPF with PHEMT 3-bit switch arrays.

Fig. 2.2-6 Measured S parameters of prototype BPF, (a) S21, (b) S11.

- 17 -

[Band-Split Nonlinear Compensation Techniques for Wideband RF Signal]（Yamao Lab.）
A novel wideband digital predistortion (DPD) technique that can relax the requirement
for sampling frequency is proposed. The proposed band-split parallel signal processing DPD
can reduce the sampling frequency to the half of normal DPD while compensating all
nonlinear terms and achieve the same compensation performance. After presenting theprinciple of the proposed scheme, the simulation results employing two-component carrier(2CC) LTE-A signal are presented that achieve ACLR of less than -50 dB and EVM of lessthan 2.5 %. The proposed DPDs with four-band and two-band splitting methods can decrease
the sampling frequencies to the half and two thirds of the normal DPD, respectively.

Fig.2.2-7 Block diagram of proposed DPD with band
splitting method (Two-band splitting).

Fig. 2.2-8 Decomposed PA output spectra.

Table. 2.2-1 Required Sampling Frequency
and Number of DACs.
Four-band
splitting
DPD
Requiredsampling
frequency
Required number
of DACs

Two -band
Conventional
splitting
DPD
DPD

3
𝐵𝑊
2

2BW

3BW

4

2

1

Fig. 2.2-9 PA output spectra with proposed DPD.

[Blind Nonlinear Compensation of RF Receiver Employing Folded-Spectrum Sub-Nyquist
Sampling Technique]（Yamao Lab.）
Blind nonlinear compensation for RF receivers is
an important research topic in 5G mobile
communication, in which higher level modulation
schemes are employed more often to achieve highcapacity and ultra-broadband services. Since
nonlinear compensation circuits must handle
intermodulation bandwidths that are more than
three times the signal bandwidth, reducing thesampling frequency is essential for saving power
consumption. We proposed a novel blind nonlinear
compensation technique that employs sub-Nyquist
sampling analog-to-digital conversion. Althoughoutband distortion spectrum is folded in the
proposed
sub-Nyquist
sampling
technique,- 18 -

Fig.2.2-10 Proposed blind nonlinear
compensation scheme with sub-Nyquist
sampling technique.

determination of compensator coefficients is still possible by using the distortion power.
Proposed technique achieves almost same compensation performance in EVM as theconventional compensation scheme, while reducing sampling speed of analog to digitalconvertor (ADC) to less than half the normal sampling frequency. The proposed technique
can be applied in concurrent dual-band communication systems and adapt to flat Rayleighfading environments.

Fig.2.2-11 Simulated EVM convergencev.s. sampling frequency

Fig.2.2-12 CDF of EVM for Rayleigh faded channel( fD = 30,100 Hz).

（B）Long-Range OAM Communication Using Loop Antenna Arrays (Ishikawa Lab.)We have demonstrated that the electro-magnetic wave propagation occurs with a single
orbital angular momentum (OAM) mode, when a current distribution of the azimuth angle
I-direction for a circular loop antenna conductor contains only one Fourier expansion
coefficient. This condition almost retains at the loop-antenna conductor length of nλ (n is theinteger). Based on this principle, we have successfully developed a coaxial four loop-antennaarray system in which four OAM modes can be generated and separated to individual ports
with more than 10-dB isolation, in last year. By adjusting relative RF connection positions
for each loop antenna, and by placing a metal reflection plate behind the loop antenna array,
isolation performances between loop-antenna communications were successfully improved. A
performance for a long-range OAM communication with a distance of 90 cm was estimatedby using paraboloids with accurate alignments for each component (Fig. 2.2.13). In a 5-GHzband system, the measured transmission between antennas of the same radius was the
maximum, and an excellent measured transmission isolation of more than 23.4 dB was
obtained. In addition, in a 12-GHz-band system, the measured transmission isolation of morethan 17.6 dB was obtained.

Fig. 2.2-13 Long-range OAM communication system using loop antenna arrays at 12-GHz band.
- 19 -

（C） Photonic Analog-to-Digital Conversions (ADCs) for RoF systems (Matsuura Lab.)In this year, we have achieved 10-GSamples/s, 15-level optical quantization using red
frequency chirp in a quantum-dot semiconductor optical amplifier (QD-SOA). To dramaticallyincrease the quantization level, we have carefully adjusted the input signal power and thethreshold for optical quantization. The input signal power required for the quantization ismuch lower than those of the previously reported photonic ADCs. The result shows themeasured relationship between the normalized peak power of the input sampling pulse andthe red-shifted frequency of the R-BPF when the peak power of the extracted sampling pulse
exceeded a threshold for discriminating “0” or “1” level. As the red-shifted frequency wasincreased, the required peak power of the input sampling pulse was increased. As a result,
we achieved 15-level quantization. Here, it should be noted that the threshold and the power
injected into the QD-SOA of the input sampling signal were very important factors todetermine the quantization performance. Therefore, we carefully optimized these parameters
to obtain the best performance with a higher quantization level. In this experiment, thethreshold was set to 0.25 to the highest peak power of the normalized output pulse train witha red frequency shift of 20-GHz, whereas the powers injected into the QD-SOA of thesampling pulse train and CW probe were set to −7.0 dBm and −2.0 dBm, respectively. In Fig.
2, the normalized peak power of 1.0 corresponded to the actual peak power of 8.4 mW. Thismeans that the input sampling signal peak power required for the optical quantization wasless than 8.4 mW, which was much lower than those of the previously reported photonic ADCs.

Fig.2.2.14

15-level quantization performance

2.2.4 Funds【Grants-in-Aid for Scientific Research】
1. Grant-in-Aid for Scientific Research (C), ”Microwave OAM Antenna”
A. Saitou
2. Grant-in-Aid for Scientific Research (C), ”Reconfigurable RF Switch Based on a
Meta-material Technique”
H. Mizutani, K. Honjo
3. Grant-in-Aid for Challenging Exploratory Research, “Research on 100 GSample/s
Optical Quantization Using quantum-dot semiconductor optical amplifiers”
M. Matsuura- 20 -

【Commissioned Research】
1.

2.

Ministry of Internal Affairs and Communications (MIC) of Japan, “Research andDevelopment for the realization of 5G mobile communication system”
Y. Yamao, K. Honjo, R. Ishikawa, A. Saitou, Y. Takayama
MIC, SCOPE, ”Research and Development for Super Multiplexing OAM
Communication Using Loop Array Antennas,”
A. Saitou, K. Honjo, R. Ishikawa【Cooperative Research】
1.
2.

3.
4.
5.

Taiyo Yuden Co., Ltd. “Study on OAM applications”
R. Ishikawa
RF device technologies Inc. “Study on novel devices and its evaluation methods for
wireless communications”
R. Ishikawa
SoftBank Group Corp. “Low power consumption amplifier”
K. Honjo, R. Ishikawa
MoDeCH Inc. “Millimeter wave circuit design”
R. Ishikawa, K. Honjo
YAZAKI Corporation, “Analog and Digital Signal Transmission Using Multi-ModeFibers”
M. Matsuura- 21 -

2.3 Division of Creating Advanced Wireless Systems
2.3.1 Purpose of Division
R&D of Advanced Wireless Systems and Networks contributing to development of society
by sustainable technologies of wireless systems

2.3.2 Research Staffs and Their Specialties
Prof. Takeo Fujii（Head of Division, Future NW, Cognitive Radio, Distributed NW）
Prof. Yasushi Yamao（Future NW, Distributed NW）
Associate Prof. Koichi Adachi (Future NW)
Associate Prof. Koji Ishibashi（Future NW, Distributed NW）
Associate Prof. Motoharu Matsuura（Future NW）

2.3.3 Major Research Results in 2018[Multiband Hierarchical Ad Hoc Network with Wireless Environment Recognition] (Fujii Lab.)

Wireless ad hoc networks have attracted high attention to adapt to multi-hop networks
such as wireless mesh networks, sensor networks, vehicle-to-vehicle (V2V) networks, and soon. Conventional wireless communications such as cellular networks and Wi-Fi networks
are considered to optimize human-to-human communication. In recent years, on the other
hand, wireless communication is not limited to human only communication due to theInternet of Things (IoT). In such an environment, how to treat the limited frequency bands
to provide robust wireless networks and to satisfy users is a challenging issue. Wireless ad
hoc network is preferable to adapt to such environment because it can generate wirelesslinks with dynamic route only when necessary. Up to now, communication of wireless ad hoc
network is assumed to use 2.4 GHz Industry-Science-Medical (ISM) bands. Such bands canuse freely without any permission. Consequently, ISM bands always crowded for the sakeof using wireless LANs, microwave ovens, and so on. From the viewpoint of users, on theother hand, the requirement of the system is different according to the service. Therefore,
in this research, we focus on a method of band selection for wireless ad hoc networks that
corresponds to multi-frequency. To obtain a high success rate of routing, high throughput,and high PDR, we proposed a Software Defined Network (SDN)-based routing scheme formulti-user environments. The system model is shown in Fig. 2.3-1. Fig. 2.3-2 shows theaverage throughput performance comparison between the result used SDN and not used
one. From this figure, we can confirm that the proposed method can select frequency bands
dynamically to achieve higher throughput.

Figure 2.3-1 System model.

Figure 2.3-2 Average Throughput.

- 22 -

[Highly Accurate Prediction of Radio Propagation using Model Classifier] (Fujii Lab.)In order to accurately recognize the radio environment, measurement-based spectrum
database (MSD) has attracted attention. Radio environment is gathered by huge numbersof terminals and the database accumulates the datasets related to the locations of receivers.
Then, the datasets are used to generate the statistical information such as radio
environment map (REM). By using the REM, path loss and shadowing deviation can be
estimated at arbitrary position. However, the conventional database stores the statisticalradio information of each receiver location. Hence, the registered data size is enormous. In
this research, to reduce the registered data size of MSD, we propose the MSD using model
classifier. Figure 2.3-3 shows a concept of a model classifier in this research. In model
classifier, K propagation models including path loss and shadowing are constructed. Thenthe database unifies the propagation model at the point where the shadowing characteristics
are similar. By using model classifier, we can reduce the registered data size while
accurately estimating the radio environment. To evaluate the proposed classifier, we usedmeasurement datasets of a 3GPP cellular band in the real environment. This measurement
was performed in Kudanshita Chiyoda-ku in Tokyo, Japan. Center frequency is 3.5GHz,transmission power is 29dBm and the amount of the datasets is 100,423. Figure 2.3-4 shows
the result of RMSE between the estimated average received power and instantaneousreceived power. For the performance comparison, REM-based method and single path loss
model-based method are evaluated. We can confirm that the proposed method canaccurately estimate the radio environment while reducing the registered data size.
Model label

Model classifier

RMSE [dB]Single path loss model

Model classifier

Database

REM (Number of meshes : 2060)

Number of propagation models

Fig. 2.3-3

Concept of a model classifierFig. 2.3-4 RMSE characteristics

Total Processing Completion Time [s][Radio and Computing Resource Allocation for Minimizing Total Processing Completion
Time in Mobile Edge Computing] (Adachi Lab.)Due to the ever increasing interest in mobile
2.5
applications and services, the concept of mobile
Proposed Scheme
Only Bisectionedge computing (MEC) has emerged. Due to the
All MEC Johnson
2
All MEC
proximity between mobile user (MU) and MEC
All Local
server located at base station (BS), i.e., the edge
1.5
of radio access network (RAN), MEC can realize
low-latency mobile application. For MEC, MU
1
and MEC server need to exchange tasks using
limited radio resources. Furthermore, when
0.5
multiple MUs possess tasks, MEC server has tohandle multiple tasks. Thus, the radio andcomputing resources need to be allocated to
0
20
40
60
80
100
MUs by taking into account the wirelessNumber of MUschannel condition and the computing power ofFig.2.3-5 Total processing completion
MUs and MEC server. In this research, wetime as a function of number of MUs.
proposed a radio resource and computing- 23 -

resources allocation scheme in order to minimize the total processing completion time of all
the tasks. Each task is assumed to be divided into local task and offload task. Local task iscomputed by each MU whilst offload task is computed by a MEC server. We first formulated
the optimization problem to minimize the total processing completion time of all tasks. For
the formulated optimization problem, we developed a two-step radio and computing resources
allocation scheme which iteratively performs bisection search method and Johnson’salgorithm. Fig. 2.3-5 shows the total processing completion time of the proposed scheme andthe existing schemes. The figure clearly shows that up to 25% total processing completiontime reduction is achieved by the proposed scheme compared to the conventional schemes.
[Q-Learning Based Orthogonal Resource Allocation] (Adachi Lab.)
The management of mutual interference isessential in Internet-of-Things (IoT) era due todensely deployed wireless nodes. Some standardsof Low Power Wide Area (LPWA) adopt Carrier
Sense Multiple Access / Collision Avoidance(CSMA/CA) as a random access scheme. It allows
the wireless nodes to access the channel while
avoiding such mutual interferences using carrier
sensing. However, the wireless node may not beable to carrier sense the other wireless nodes’
communication due to the radio environment
such as large pathloss between them. Therefore
packet collision may happen and this results inthe packet delivery rate (PDR) degradation. This
problem is severer in LPWA network due to its
wide coverage and the low transmit power ofFig.2.3-6 Process of Learning.
wireless nodes. In order to avoid such packet
collision, we have proposed an orthogonal resource
allocation scheme using powerful machine learningtechnique, e.g., reinforcement learning. This scheme
learns the surrounding radio environment of eachwireless node and allocates the wireless resources towireless nodes so that that allocation can improve
the PDR performance. For the reward ofreinforcement learning, the number of successfullyreceived packets at the Fusion Center (FC) is
adopted since it is obtainable at the FC without any
explicit feedback from wireless nodes. Due to thestrong correlation between the number ofsuccessfully received packets and PDR, it is possible
to improve the PDR performance. Under the
LoRaWAN network, the numerical evaluation has Fig. 2.3-7 PDR Performance ofbeen conducted. Fig. 2.3-6 shows the process of proposed method
learning. As it can be seen from the figure that the
PDR performance improves as the learning progresses. The cumulative distributeionfunction (CDF) of PDR is shown in Fig. 2.3-7. The figure clearly shows that the proposed
scheme can improve PDR performance compared to random resource allocation. For example,
10% PDR value can be improved by 22 % compared to random allocation scheme. It indicatesthat the proposed scheme can improve PDR performance of wireless nodes with poor channel
condition.
[Random Access Protocols for Massive Users] (Koji Ishibashi Lab.)
Future wireless communication would accommodate massive number of devices, as
represented by Internet-of-Things (IoT). In order to realize efficient data transmission of- 24 -

large number of devices, designing the transmission
protocol of devices is crucial. While conventional
grant-based access schemes (e.g. time divisionmultiple access (TDMA)) can achieve highly-efficienttransmission via resource allocation for devices, suchallocation causes a large overhead in the presence ofmassive number of users, which results in the
degradation of the throughput performance. To thisend, we have proposed an efficient random accessprotocol, namely frameless ALOHA with multiple
Fig. 2.3-8 Throughput of ZigZag
decodable frameless ALOHA.
base station cooperation. Multiple base stations are
exploited to cooperatively retrieve transmitted packets, while devices transmit their packets
using transmission probabilities. We have theoretically optimized transmission
probabilities to maximize the achievable throughput. Upon the optimization, our proposed
scheme achieves remarkable throughput performance. While frameless ALOHA withmultiple base station cooperation can start the packet retrieval process only from collisionfree time slots, ZigZag decoding has been proposed as a technique to retrieve two colliding
packets. In 2018, we have then proposed ZigZag decodable frameless ALOHA, whereframeless ALOHA protocol is modified so as to fully exploit ZigZag decoding. As shown in
Fig. 2.3-8, ZigZag decodable frameless ALOHA outperforms the original frameless ALOHA
in whole thresholds on packet loss rate (PLR). Those results have been already published inIEEE journals.
[Low-Complexity Detector for Frame-Theoretic NOMA] (Koji Ishibashi Lab.)
Non-orthogonal multiple access (NOMA) is a promising enabler to support massive users in
the next-generation of wireless systems such as 5G
and beyond. Recently, NOMA schemes based onsparse multiplexing such as sparse code multiple
access (SCMA) have gained much more attention
since each user-data can be detected by a lowcomplexity message passing algorithm (MPA).
However, users cannot exploit overall available
resources of the system since the sparse use ofrecourses is necessary to use MPA. To this end,
frame-theoretic NOMA exploiting full resources ofthe system has been proposed in the literature.
However, the dense use of resources results in thehigh complexity of the detection. To reduce theFig. 2.3-9 BER performances ofcomplexity, we proposed the low-complexity detector
several detection techniques.
based on Gaussian belief propagation (GaBP) andalso the design of the precoder enhancing the performance of GaBP. Figure 2.3-9 shows bit
error rate (BER) performances of conventional detection for frame-theoretic NOMA systems
and proposed approaches (GaBP and GaBP. As obvious from the figure, our proposed
approach enhances the BER performance with even lower complexity.
[Compressed-Sensing-Aided Subcarrier IQ Index Modulation] (Koji Ishibashi Lab.) ]In current wireless communication systems, orthogonal frequency division multiplexing(OFDM) is employed. Recently, the combination of OFDM and index modulation, namely
subcarrier index modulation (SIM) has been proposed. SIM utilizes a part of subcarriers sothat information bits are conveyed via not only classical constellations but also patterns ofactive subcarriers. Although a minimum Euclidean distance (MED) increases thanks to this- 25 -

transmission scheme, SIM has a superiority against
OFDM only in low bandwidth efficiency. To thisend, we have proposed compressed-sensing-aided

subcarrier
in-phase/quadrature-phase
index
modulation (CS-SIQIM). CS-SIQIM can enhanceboth the detection performance and the bandwidth
efficiency by applying compressed sensing to
subcarrier in-phase and quadrature-phase index
modulation. We further proposed the use ofaggregate-compression in CS-SIQIM, called ACFig. 2.3-10 BER performances of
SIQIM, so as to improve the performance of thethe proposed SIQIMs and OFDM.
signal reconstruction. Figure 2.3-10 shows bit error
rate (BER) performance of our proposals compared with OFDM where their transmission
rates are set 1.25 [bits/s/Hz]. As seen in the figure, the improvement of our proposed4
approach is more than 2 dB at BER=.
[Optically powered transmission systems for optical access networks]（Matsuura Lab）
Power-over-fiber (PWoF) is an attractive approach not only to delivery optical power using
optical fibers but also to simplify the power supply system of remote antenna units (RAUs)
for radio-over-fiber (RoF)-based mobile networks. If the power required for RAUs can be fully
supplied from a central station (CS) using RoF links, the networks does not requireconventional public power lines and batteries. In addition, as the power supply system of the
RAUs is centralized in the CS, it is easier to control the power supplied to each RAU,
according to the temporary traffic load of each RAU.
We have proposed PWoF systems using double-clad fibers (DCFs) consisting of a singlemode (SM) core and an inner cladding; the SM core is used for RoF data transmission, while
the inner cladding with a much larger core area than SM cores is used for optical power
feeding. We also have demonstrated the RoF transmission experiments with 60-W PWoF feedusing a 300-m DCF. Moreover, we have achieved the good bidirectional transmission
performances of up to 1-km DCF link, and significant influence on the link length has neverbeen observed.
In this year, we demonstrate up to 150-W
PWoF feed with bidirectional RoF
transmission using a 1-km DCF link, andevaluatethesignaltransmission
performances. To the best of ourknowledge, this is the highest opticalpower
feedingdemonstrationofsimultaneous
power
and
data
transmission experiments over a single
optical fiber. The result shows the error
vector magnitude (EVM) penalties to theback-to-backsignalofthedownlink/uplink transmitted signals
when the received electrical signal power
Fig. 2.3-11 EVM penalties to back-to-backwas set to –30 dBm. The obtained EVM
signal of downlink/uplink transmitted signals
penalties were less than 0.04%, and there
into a 1-km DCF link while changing total
was no significant increase in the EVM
optical feed power when received electricalvalue even if the optical feed power was
power was set to – 30 dBm.
increased up to 150 W. Moreover, the- 26 -

result was almost the same performance as those of the previous bidirectional transmission
experiment under the 60-W feeding using a 300-m DCF link.

2.3.4 Funds【Grants-in-Aid for Scientific Research】
1. Scientific Research B “Research on Spectrum Sharing among Multiple Systems basedon Correlation of Wireless Environment using Crowd Sensing”
Takeo Fujii
2. Scientific Research Fostering Joint International Research “Research of Advanced V2X
Network based on Wireless Environment Learning for realizing Cooperated
Autonomous Vehicles”
Takeo Fujii
3. Scientific Research B “Research on Information Passing between Sensing Information
Space and Physical Space for Dense Wireless Sensor Network”
Takeo Fujii (PI belongs to other organization)
4. Scientific Research B “Research on Advanced Wireless and Wired Harmonized SDN”
Takeo Fujii (PI belongs to other organization)
5. Scientific Research Fostering Joint International Research Type B “Research of Smart
Spectrum using Multi-dimensional Wireless Environment Recognition based on
Learning”
Takeo Fujii (PI belongs to other organization)
6. Scientific Research B “Research on Optically Powered Radio-over-Fiber systems”
Motoharu Matsuura
7. Challenging Exploratory Research “Research on 100 GSamples/s Optical Quantization
Using Quantum-Dot Semiconductor Optical Amplifiers”
Motoharu Matsuura
8. Scientific Research C “Research on New Multiple Access Control Technologies basedon Multi-Dimensional Graph Structure for Massive Users”
Koji Ishibashi
9. Scientific Research A “Research on New Transmission Technologies based on Lattice
Structures for Next-Generation Ultra-High Data-Rate Communications”
Koji Ishibashi (PI belongs to other organization)
10. Scientific Research A “Research on analog factor graph for large MIMO systems”
Koji Ishibashi (PI belongs to other organization)【Commissioned Research】
1. MIC SCOPE “Augmented Learning of Wireless Communication Environment for
Forwarding Frequency Spectrum Sharing”
Koichi Adachi (PI belongs to other organization)
2. MIC SCOPE JP-EU Joint Research “5G Enhanced Mobile Broadband Access Networks
in Crowded Environments (5G-Enhance)”
Takeo Fujii, Koji Ishibashi, Koichi Adachi
3. MIC SCOPE “Non-orthogonal multiple access technique based on frame theory for 5G”
Koji Ishibashi (PI belongs to other organization)【Other Funds】
1. KDDI Research, Joint Research Fund, “Radio Propagation Modeling based on
Database of Measurement Data”- 27 -

Takeo Fujii
2. Fujitsu, Joint Research Fund, “Prediction of Mobile Terminal”
Takeo Fujii, Koichi Adachi
3. KDDI Research, Joint Research Fund, “Interference Prediction and Resource
Management based on Database of Measurement Data”
Koichi Adachi
4. The Telecommunications Advancement Foundation Research Grant, “Adaptive Base
Station Operation Based on Machine Learning”
Koichi Adachi- 28 -

2.4 Division of Exploring Low Power Wireless2.4.1 Purpose of DivisionThis division is aiming at low power wireless device technologies and application systems,
which become fundamentals for future wireless communication systems. We areinvestigating such low power wireless technologies as super low power LSI design, energy
harvesting technology, power transfer technology by optical fiber, as well as low power
networks by theoretical approach. We also create new wireless application systems using
the low power wireless technologies.
2.4.2 Research Staffs and Their Specialties
Prof. Koichiro Ishibashi（Head of Division, Low-power devices）
Associate Prof. Koji Ishibashi (Green network and communication theory)
Associate Prof. Ryo Ishikawa (RF energy harvesting)
Prof. Motoharu Matsuura (Radio over Fiber)Prof. Takeo Fujii (Smart meters)
2.4.3 Major Research Outcomes in 2018
[Development of RF Energy Harvesting System]（Prof. Koichiro Ishibashi）
RF energy harvesting technology which can beinevitable for future Trillion Sensor Universe has
been investigated in the Low Power Wirelessdivision. In this year we try to harvest the energy
from 950MHz 3G and 4G cell phone base station by
the circuit of cross couple rectifier circuit on 65nm
SOTB technology (Fig. 2.4-1). With the system
shown in Fig. 2.4-2, average power of 500nW andaverage voltage of 700mV has been obtained (Fig.
2.4-3).

Fig. 2.4-1 Circuit of cross couple
rectifier with DTMOS on 65nm
SOTB technology.

Figure 2.4-2 RF Energy harvesting System.

- 29 -

取得電力 [nW]2500

出力電圧 [V]0.95

RL=280KΩ

RL=10MΩ

0.9
2000
0.85
1500

0.8
0.75

1000

0.7
500
0.65
0
-30

0.6
20

70

120

-30

Time (second)

20

70

120

Time (second)

Figure 2.4-3 Output power and voltage fromenvironmental RF energy of 950MHz for cell phones.
Design of Protocol for Wireless-Powered Communication System]（Prof. Koji Ishibashi）
Due to recent advances in Internet-of-Things(IoT), wireless devices operating with extremely
low-power supply are highly desired. To this end,
wireless-powered communication system (WPCS)
harvesting energy from RF signals can beconsidered as the best candidate enabling thesystem with extremely-low power consumption.
When radio frequency (RF)-chain is used in WPCS,
devices can achieve higher bandwidth efficiency
while suffering from higher power consumption. On
the other hand, unless RF-chain is used, the energy
Figure 2.4-4: Throughputs ofconsumption significantly drops while the resulting
different communication schemeswith and without RF-chain.
bandwidth efficiency is significantly limited since
the system cannot use digital modulations suchquadrature amplitude modulation (QAM).
To leverage this trade-off, we proposed the simple switching protocol which enables eachdevice to independently select appropriate communication scheme and frequency band.
Figure 2.4-4 shows throughput performances of the device without switching and switchingwhere two frequency bands, namely 550MHz and 2.4GHz, are available. From the figure,our protocol achieved the highest throughput over the almost whole distance.
[MHz-Band Multi-Harmonic Active Source-Pull for RF Rectifier Design]（Ishikawa Lab.）A MHz-band multi-harmonic active source-pull technique has been developed for a
GHz-band high-efficiency rectifier design. An active load-pull technique is usually used for ahigh-efficiency amplifier design. This method has been successfully diverted to the rectifier
design by carefully considering an optimum-source-impedance estimation at thefundamental frequency existing an input source signal. In addition, an intrinsic nonlinear
resistance as a rectifying element with an operation frequency of a GHz band can be directly
extracted by the MHz-band measurement, due to negligible parasitic reactance elements.
The MHz-band measurement system can be constructed with low cost (Fig. 2.4-5), incomparison with apparatuses for GHz-band measurements. An example of the active- 30 -

source-pull for a GaAs HEMT at 10 MHz is shown in Fig. 2.4-6. In the measurement,
harmonics up to the fifth-order were adjusted to estimate a high-efficiency operation.

Fig. 2.4-5 MHz-band multi-harmonic active
source-pull measurement system for estimating
an intrinsic nonlinear resistance in a rectifying
element

Fig 2.4-6 Example of the active
source-pull for a GaAs HEMT at 10MHz. Upper Fig.: votage andcurrent waveforms, and lower Fig.:
estimated source impedances[Optically Powered RoF Systems for Future Optical Access Networks]（Prof. Motoharu
Matsuura）
Power-over-fiber (PWoF) is an attractive technique to deliver the electric power required
for any remote units using optical fibers. In radio-over-fiber (RoF) networks, it is useful fortransmitting the electric power generated at a central office (CU) to remote antenna units(RAUs) using RoF links and centralizing the power supply system at the CU. Then, sinceeach RAU does not require public power supply systems, it is much easier to install andmanage many RAUs. For these applications, we have reported several PWoF techniqueusing multimode fibers (MMFs) and double-clad fibers (DCFs).
In current situations, the electric power for RAUs is always fully supplied regardless of
the actual mobile data traffic. In terms of power saving for RAUs, it is important toeffectively use the electric power by controlling the supply power, corresponding to themobile traffic. Indeed, a few research groups have reported the importance of sleep mode for
RAUs and shown that the 60% power saving of RAUs could be achieved.
In this year, to show the availability of the dynamic power control of RAUs for PWoF
systems, we evaluate the frequency response of a photovoltaic power converter (PPC). The
result shows the frequency characteristics of the PPC we used. The cut-off frequency, which
is defined as the frequency at which the PPC output decreases by 3 dB from the output at
the flat level, was approximately 2.7 MHz.
The rise time calculated from the cut-off frequency was 0.13 μs. In our assumed- 31 -

application, the power control time is based on the traffic change caused by the variation of
the number of mobile users in the cell area of each RAU. Therefore, the obtained rise time isenough to apply to the dynamic power control of RAUs for PWoF systems.

Fig. 2.4-7：Frequency characteristics of PPC.

[Spectrum Sharing exploiting Spectrum Database for LPWA]（Prof. Takeo Fujii）
In order to utilize low-power devices distributed over very large areas, LPWA(Low
Power, Wide Area) has attracted attention. LPWA technologies can realize low-power andlow-cost because their simple network topology and protocol. Moreover, they enablelong-distance communication using spread spectrum, ultra-narrow band modulation andother technologies. However, in many LPWA systems (e.g., LoRaWAN and Sig-Fox),
communication with large number of nodes becomes collision because large number packets
is transmitted with a certain fixed duty cycle. In this research, to reduce interference
between other systems and to avoid transmission collision in LoRaWAN, we propose anadaptive algorithm for setting duty cycle of LoRaWAN. The system model is shown in
Fig.2.4-8. Our method checks the surrounding nodes at gateway and adaptive duty cycle isinformed to the nudes using ACK. The proposed system uses Spectrum Database forrecognizing the surrounding spectrum environment to decide duty cycle. The final duty cycleof each node is updated to reduce the collision among the same LoRaWAN system. We
evaluate the proposed method through numerical simulation to show the interference time
ratio toward other systems and the packet loss rate in LoRaWAN. Figure 2.4-9 shows theaverage interference time ratio. Figure 2.4-10 shows the average packet loss rate. Fromthese figures, we can confirm that the proposed method guarantees an acceptableinterference time ratio and the packet loss rate.

Fig. 2.4-8 System model.

- 32 -

Fig. 2.4-10 Average packet loss rate.

Fig. 2.4-9 Average interference time ratio.

2.4.4 Funds【Commissioned Research】
1. JST/CREST Scientific Innovation for Energy Harvesting Technology“Scavenging nW RF energy using Super Steep Transistor and Meta-Material Antenna,”
Koichiro Ishibashi, Ryo Ishikawa, and Koji Ishibashi, (J. Ida, S. Makino, and K.
Itoh (Kanazawa Institute of Technology)).
2. Grant-in-Aid for Challenging Exploratory Research,” Ultra-fast photonic A/Dconversion using quantum-dot semiconductor optical amplifiers,”
M. Matsuura【Cooperative Research】
1. “Optimization of Smart-Meter Networks”
Koji Ishibashi and Takeo Fujii- 33 -

List of Publication in F.Y.2018
Journal Papers with Referees
1

D. Kamiyama, A. Yoneyama, and M. Matsuura, “Multichannel data signals and powertransmission by power-over-fiber using a double-clad fiber,” IEEE Photon. Technol.
Lett., vol. 30, no. 7, pp. 646-649, Apr. 2018.

2

T. Mori, J. Ida, S. Momose, K. Itoh, K. Ishibashi and Y. Arai, “Diode characteristics ofa super-steep subthreshold slope PN-Body tied SOI-FET for energy harvesting
applications,” IEEE J. Electron. Devices Soc., vol. 6, pp. 565-570, Apr. 2018.

3

K. Katagiri, K. Sato, T. Fujii, “Crowdsourcing-assisted radio environment database for
V2V communication,” Sensors, vol. 18, no. 4, p. 1183, Apr. 2018.

4

R. Yazawa and M. Matsuura, “Optically powered drone small cells using optical fibers,”
IEICE Electron. Express, vol. 15, no. 10, 20180371, May 2018.

5

H. Hoshino, T. Okada, and M. Matsuura, “Photonic analog-to-digital conversion using
red frequency chirp in a semiconductor optical amplifier,” OSA Opt. Lett., vol. 43, no.
10, pp. 2272-2275, May 2018.

6

H. Soya, O. Takyu, K. Shirai, M. Ohta, T. Fujii, F. Sasamori, S. Handa, “Fastrendezvous scheme with a few control signals for Multi-Channel Cognitive Radio,”
IEICE Trans. Commun., vol. E101-B, no. 8, pp. 1589-1601, Jul. 2018.

7

V. Nguyen, R. Ishikawa, and K. Ishibashi, “83nJ/bit Transmitter Using CodeModulated Synchronized-OOK on 65nm SOTB for Normally-Off Wireless Sensor
Networks,” IEICE Trans. Electron., vol. E101-C, no. 7, pp. 472-479, Jul. 2018.

8

L. T. Trien and Y. Yamao, “Information Delivery Delay Reduction by Relay-Assisted
Broadcast Transmission for ITS V2V communications,” IEICE Trans. Fundamentals,
vol. E101-A, no. 9, pp. 1290-1297, Sep. 2018.

9

,
TDOA

10

,

,

, λ

,

, “

,”

(B), vol. J101-B, no. 10, pp. 857-866, Oct.

2018.
R. Hasegawa, K. Katagiri, K. Sato, and T. Fujii, “Low storage, but highly accurate
measurement-based spectrum database via mesh clustering,” IEICE Trans. Commun.,11

vol. E101-B, no. 10, pp. 2152-2161, Oct. 2018.
K. Mashimo, R. Ishikawa, and K. Honjo, “4.5-/4.9-GHz-band selective high-efficiency
GaN HEMT power amplifier by characteristic impedance switching,” IEICE Trans.

12Electron., vol. E101-C, no. 10, pp. 751-758, Oct. 2018.
Y. Kada and Y. Yamao, “Design of Dual-Band SHF BPF with Lower Band
Reconfigurability and Direct Parallel-Connected Configuration,” IEICE Trans.

13Electron., vol. E101-C, no. 10, pp. 775-783, Oct. 2018.
F. Sakai, M. Makimoto, and K. Wada, “Near-field chipless RFID tag system using
inductive coupling between a multimode resonator and detection probes,” IEICE Trans.

14

Online, [Advance Publication] Released: Oct. 15, 2018.
S. Ogata, K. Ishibashi, and G. T. F. de Abreu, “Optimized Frameless ALOHA for
Cooperative Base Stations with Overlapped Coverage Areas,” IEEE Wireless Commun.,vol. 17, no. 11, pp. 7486-7499, Nov. 2018.

- 34 -

15

H. Liu, X. Zhu, T. Fujii, “A new classification-like scheme for spectrum sensing using
spectral correlation and stacked denoising autoencoders,” IEICE Trans. Commun., vol.
E101-B, no. 11, Nov. 2018.

16
17

,“

,”

no. 12, pp. 688-692, Dec. 2018.
,
,“
,”

18

, vol. 46,(C), vol. J101-C, no. 12, pp. 479-488, Dec. 2018.

S. Oshima, T. Oshima, T. Numao, and K. Wada, “A Design Method of Compact
Lumped-Element Matching Circuits for Diplexers using SAW filters,” Trans. Japan
Inst. of Electron. Packaging, vol. 11, E17-015-1, Dec. 2018.

19

F. Sakai, M. Makimoto, and K. Wada, “Design and Detection of Chipless RFID Tags
Using Stepped Impedance Resonators with Short-circuited, Ends,” Trans. Japan Inst.
of Electron. Packaging, vol. 11, E18-001-1, Dec. 2018.

20

S. Ono and K. Wada, “Unloaded quality factor for hairpin resonator affected byconduction and radiation losses on K-band,” Trans. Japan Inst. of Electron. Packaging,vol. 11, E18-002-1, Dec. 2018.

21

, λ

,

, “ELD-STAP
CPC,”(B), vol. J101-B, No.12, pp. 1093-1106, Dec.

,

,

,

2018.
22

,
,”

, “
(B), vol. J102-B, No.1, pp. 23-31, Jan. 2019.

23

O. Takyu, K. Shirai, M. Ohta, T. Fujii, “Insertion and data tracking with frequency

24

offset for physical wireless parameter conversion sensor networks,” Sensors, Feb. 2019.
M. Matsuura and G. Ito, “Selective amplitude-level regeneration based on blue-chirp
spectral slicing using QD-SOAs,” OSA Opt. Express, vol. 27, no. 3, pp. 3030-3038, Feb.

25

2019.
K. Kimura and Y. Yamao, “Bandwidth-Efficient Blind Nonlinear Compensation of RF
Receiver Employing Folded-Spectrum Sub-Nyquist Sampling Technique,” IEICE

26

Trans. Commun., vol. E102-B, no. 3, pp. 632-640, Mar. 2019.
S. Ogata and K. Ishibashi, “Application of ZigZag Decoding in Frameless ALOHA,”IEEE Access, vol. 7, no. 1, pp. 39528-39538, Mar. 2019.

27

, λ

,

, “
,”

(B), vol. J102-B, no. 4, DOI: 10.14923/transcomj.

2018JBP3036, Apr. 2019.
28

M. Takai and K. Ishibashi, “Repeat-Accumulate Signal Codes,” IEEE Trans. Commun.
Early Access, 201929

O. Takyu, K. Shirai, M. Ohta, T. Fujii, “Adaptive channel assignment with predictionsof sensor results and channel occupancy ratio in PhyC-SN,” IEEE Access., Early Access,
2019

30

K. Sato, K. Inage, T. Fujii, “Modeling the Kriging-aided spatial spectrum sharing overlog-normal channels,” IEEE Wireless Commun. Lett., Early Access 2019.

- 35 -

International Proceedings with Referees
1

O. Takyu, S. Fujii, M. Ohta, T. Fujii, S. Handa, F. Sasamori, “Channel assignment
based on predictions of sensing result and channel occupancy rate in PhyC-SN,” in Proc.
IEEE WCNC Workshop Smart Spectrum 2018, Barcelona, Spain, Apr. 2018.

2

M. Akita, T. Inaba, “Angle Estimation using Super Resolution and Blocking Matrix in
Stepped Multiple Frequency Complementary Phase Code Radar,” in Proc.
RadarConf’18, Apr. 2018.

3

M. Machida, R. Ishikawa, Y. Takayama, and K. Honjo, “GHz-band high-efficiency
rectifier design based on MHz-band multi-harmonic active source-pull technique,” inProc. IEEE MTT-S Int. Microw. Symp. Digest, Philadelphia, USA, pp. 1134-1137, Jun.

4

2018.
R. Yazawa and M. Matsuura, “Flight demonstration of power-over-fiber drone forairborne base stations,” in Proc. OECC 2018, 4A1-4, Jeju, Korea, Jul. 2018.

5

N. Tajima, A. Yoneyama, D. Kamiyama, and M. Matsuura, “Over 1-km power-overfiber using a double-clad fiber for bidirectional RoF systems,” in Proc. OECC 2018, 4A42, Jeju, Korea, Jul. 2018.

6

T. Okada, H. Hoshino, and M. Matsuura, “10-GSample/s, 15-level optical quantization
using frequency chirp in a quantum-dot SOA,” in Proc. OECC 2018, P1-26, Jeju, Korea,
Jul. 2018.

7

Y. Sunada, K. Adachi, and Y. Yamao, “Throughput Analysis of Dynamic Multi-Hop
Network Under High Traffic Load,” in Proc. ICUFN2018, Prague, Jul. 2018.

8

T. Ohata, K. Ishibashi and G. Sun, “Continuous Cuffless Systolic Blood Pressure
Monitoring Scheme Using PPG Sensor and Doppler Radar,” in Proc. EMBC’2018,
Hawaii, USA, Jul. 2018.

9

X. Yang, K. Ishibashi and G. Sun, “Dengue Fever Detecting System Using PeakDetection of Data from Contactless Doppler Radar,” in Proc. EMBC’2018, Hawaii, USA,
Jul. 2018.

10

D. Manyvone, R. Takitoge, and K. Ishibashi “Wireless and Low-Power Water Quality
Monitoring Beat Sensors For Agri and Acqua-Culture IoT Applications,” in Proc. ECTICOM2018, Chang Rai, Thailand, Jul. 2018.

11

K. Ishibashi and S. Takahashi, “A 375 nA Input Off Current Schmitt Triger LDO for
Energy Harvesting IoT Sensors,” in Proc. ISVLSI 2018, Hong Kong, pp. 187-190, Jul.
2018.

12

H. Sanada, T. Kawata, R. Aizawa, T. Fujii, “Routing redundancy reducing method for
U-Bus Air using cloud cooperation,” in Proc. ICUFN 2018, Prague, Czech Republic, Jul.
2018.

13

M. Ohta, K. Adachi, N. Aihara, O. Takyu, T. Fujii, “Measurement experiments on 920
MHz band for spectrum sharing with LoRaWAN,” in Proc. IEEE VTC2018-Fall,
Chicago, USA, Aug. 2018.

14

Y. Aoki, T. Fujii, T. Ide, “Time series analysis of multiple primary user environment
using HMM-based spectrum sensing,” in Proc. IEEE VTC2018-Fall, Chicago, USA,
Aug. 2018.

15

M. Ohta, K. Adachi, N. Aihara, O. Takyu, and T. Fujii, “Measurement experiments on- 36 -

920 MHz Band for Spectrum Sharing with LoRaWAN,” in Proc. VTC2018-fall, Aug.
16

2018.
Y. Kikuchi and Y. Yamao, “Propagation Loss Characteristic of V2V Communication for
Right-Turn Accident Prevention Scenario,” in Proc. PIERS2018, Toyama, Aug. 2018.

17

S. Funayama and Y. Yamao, “Radio Propagation of 920MHz RFID on Metallic Storage
Shelf,” in Proc. PIERS2018, Toyama, Aug. 2018.

18

T. Abe and Y. Yamao, “Band-Split Parallel Signal Processing DPD for Nonlinear

19

Compensation of Broadband RF Signal,” in Proc. ISWCS2018, Lisbon, Aug. 2018.
R. Ishikawa, Y. Takayama, and K. Honjo, “Fully integrated asymmetric Doherty
amplifier based on two-power-level impedance optimization,” in Proc. 48th European

20

Microw. Conf., Madrid, Spain, Sep. 2018.
S. Habu, Y. Yamao, H. Ishikawa, and T. Maniwa, “Outband Radiation and Modulation
Accuracy of Unified Beamforming DPD,” in Proc. PIMRC2018, Bologna, Sep. 2018.

21

S. Ogata and K. Ishibashi, “ZigZag Decodable Frameless ALOHA,” in Proc. 2018 52nd
Asilomar Conf. Signals, Syst., Comput., Oct. 2018.

22

S. Ogata and K. Ishibashi, “Coded Frameless ALOHA,” in Proc. 2018 15th WPNC, Oct.

23

2018.
M. Oinaga, S. Ogata, and K. Ishibashi, “ZigZag Decodable Coded Slotted ALOHA,” inProc. 2018 15th WPNC, pp. 1-6, Oct. 2018.

24

K. Ohira, T. Hara, and K. Ishibashi, “Aggregate-Compression-Aided Subcarrier IQ
Index Modulation,” in Proc. 2018 15th WPNC, pp. 1-6, Oct. 2018.

25

S. Momose, J. Ida, T. Yamada, T. Mori, K. Itoh, K. Ishibashi and Y. Arai “First
Experimental Confirmation of Ultralow Voltage Rectification by Super SteepSubthreshold Slope “PN-Body Tied SOI-FET” for High Efficiency RF Energy
Harvesting and Ultralow Voltage Sensing,” in Proc. IEEE S3S Conf., San Francisco,26

USA, Oct. 2018.
H. Endo, J. Ida, T. Mori, K. Ishibashi, Y. Arai, “First Experimental Confirmation ofTransient Effect on Super Steep SS “PN-Body Tied SOI FET” with Pulse

27

Measurements,” IEEE EDTM, session-Si-Dev2-3, Oct. 2019.
T. Shizuoka, and T. Fujii, “Environmental aware hierarchical ad hoc network withmultiple frequency bands using weighted Laplacian matrix,” in Proc. APSIPA ASC

28

2018, Honolulu, Hawaii, USA, Nov. 2018.
H. Liu, Xu Zhu, and T. Fujii, “Ensemble deep learning based cooperative spectrum
sensing with stacking fusion center,” in Proc. APSIPA ASC 2018, Honolulu, Hawaii,

29

USA, Nov. 2018.
A. D. Shigyo and K. Ishibashi, “A Simple Message Passing Detector Based on QRDecomposition for MIMO Systems,” in Proc. 2018 APSIPA ASC, Nov. 2018.

30

T. Yasui, R. Ishikawa, and K. Honjo, “18GHz-/28GHz-band gain-boosted feedback
power amplifiers using affordable GaN HEMT MMIC process,” in Proc. 2018 APMC,
Kyoto, Japan, Nov. 2018.

31

H. Otsuka, R. Yamagishi, R. Ishikawa, A. Saitou, H. Suzuki, and K. Honjo, “Highperformance long-range OAM communication using loop antenna arrays in 12-GHz
band,” in Proc. 2018 APMC, Kyoto, Japan, Nov. 2018.

- 37 -

32

H. Mizutani, R. Ishikawa, and K. Honjo, “A novel reconfigurable GaN filter MMIC with

33

active reflector,” in Proc. 2018 APMC, Kyoto, Japan, Nov. 2018.
A. Saitou, H. Otsuka, R. Yamagishi, R. Ishikawa, H. Suzuki, and K. Honjo, “Double
multiplicity exploiting orthogonal polarizations of OAM-wave for OAM communication

34

with loop arrays,” in Proc. 2018 APMC, Kyoto, Japan, Nov. 2018.
R. Yamagishi, H. Otsuka, R. Ishikawa, A. Saitou, H. Suzuki, and K. Honjo, “Advanced
mode unity using loop antennas proximate to reflector for orbital angular momentum

35

communication,” in Proc. 2018 APMC, Kyoto, Japan, Nov. 2018.
A. Kitamura, Y. Takayama, R. Ishikawa, and K. Honjo, “GaN HEMT Darlington power
amplifier with independent biasing for high-efficiency low-distortion wide-dynamic-

36

range adjustment,” in Proc. 2018 APMC, Kyoto, Japan, Nov. 2018.
S. Ono, K. Wada, “Design and fabrication of 3-poleBPF configured by hairpin
resonators and different types of coupling and feed types at 20 GHz,” in Proc. 201837

APMC, Nov. 2018.
N. Aihara and K. Adachi, “Orthogonal Resource Allocation Using SVM for CSMA/CA,”in Proc. APSIPA 2018, Hawaii, Nov. 2018.

38

H. Godo, O. Takyu, K. Adachi, M. Ohta, T. Fujii, F. Sasamori, and S. Handa,“Experimental Evaluation of Interference Robustness for Frequency Spectrum Sharing
in WLAN System,” in Proc. APSIPA 2018, Hawaii, Nov. 2018.

39

T. Hara, K. Ishibashi, S. X. Ng, and L. Hanzo, “Low-Complexity Generator Polynomial
Search for Turbo Trellis-Coded Spatial Modulation Using Symbol-based EXIT Charts,”
in Proc. 2018 IEEE 10th ISTC, Dec. 2018.

40

M. Takai and K. Ishibashi, “Spatially Coupled Repeat-Accumulate Signal Codes,” inProc. 2019 IEEE RWS, Jan. 2019.

41

K. Fukuda, O. Takyu, K. Shirai, T. Fujii, M. Ohta, F. Sasamori, S. Handa, “Adaptive
transmission control with prediction of sensing results for PhyC-SN,” in Proc. IEEE
Radio Wireless Symp. 2019, Orlando, USA, Jan. 2019.

42

K. Onose, K. Sato, K. Inage, and T. Fujii, “Experimental verification of frequencycorrelation in radio propagation characteristics for radio environment recognition,” inProc. IEEE ICOIN 2019, Kuala Lumpur, Malaysia, Jan. 2019.

43

T. Nonaka, T. Fujii, O. Takyu, and M. Ohta, “Network MIMO with interference
cancellation for cloud-cooperated wireless sensor networks,” in Proc. IEEE ICOIN 2019,
Kuala Lumpur, Malaysia, Jan. 2019.

44

T. Noguchi, O. Takyu, T. Fujii, T. Ohtsuki, “Performance evaluation of informationsharing scheme among multiple destinations with mirroring null steering in single
antenna networks,” in Proc. IEEE ICOIN 2019, Kuala Lumpur, Malaysia, Jan. 2019.

45

S. Yamasaki, O. Takyu, K. Shirai, T. Fujii, M. Ohta, F. Sasamori, S. Handa, “Dataseparation considering smoothness of sensing data in physical wireless parameter
conversion sensor networks,” in Proc. IEEE ICOIN 2019, Kuala Lumpur, Malaysia,
Jan. 2019.

46

H. Lumbantoruan and K. Adachi, “Array Antenna for Power Saving of Sensor Nodes
in UAV-BS enabled WSN,” in Proc. ICNC 2019, Feb. 2019.

- 38 -

47

Y. Aoki, T. Fujii, “Construction of time-space radio environment database using HMM

48

for cooperative sensing,” in Proc. ICNC 2019, Honolulu, USA, Feb. 2019.
Y. Aoki, T. Fujii, “Spectrum database construction based on HMM and spectrum
sharing in multiple primary users environment,” in Proc. ICAIIC 2019, Okinawa,

49

Japan, Feb. 2019.
H. Liu, X. Zhu, T. Fujii, “Cyclostationary based full-duplex spectrum sensing using
adversarial training for convolutional neural networks,” in Proc. ICAIIC 2019,50

Okinawa, Japan, Feb. 2019.
H. Liu, X. Zhu, T. Fujii, “Adversarial training for low-complexity convolutional neuralnetworks using in spectrum sensing,” in Proc. ICAIIC 2019, Okinawa, Japan, Feb.

51

2019.
N. Tajima, D. Kamiyama, and M. Matsuura, “150-Watt power-over-fiber feed forbidirectional radio-over-fiber systems using a double-clad fiber,” in Proc. OFC 2019,

52

W1I.7, San Diego, USA, Mar. 2019.
M. Matsuura and G. Ito, “Selective mark or space level amplitude regeneration using
blue chirp spectral slicing in a QD-SOA,” in Proc. OFC 2019, W2A.37, San Diego, USA,
Mar. 2019.

Invited Talks in International Conference
1

M. Matsuura, “Optically powered radio-over-fiber systems,” in Proc. CLEO 2018,
SM1C.3, San Jose, USA, May 2018.

2

M. Matsuura, “Power-over-fiber for radio-over-fiber-based distributed remote antenna
systems,” in Proc. CLEO-PR 2018, Th4F.2, Hong Kong, Aug. 2018.

3

M. Matsuura, “Power-over-fiber technologies for radio-over-fiber systems,” in Proc.
MWP Symp., 6P-3, Matsue, Japan, Aug. 2018.

4

K. Ishibashi, R. Takitoge, and D. Manyvone, “Beat Sensors for Long Life IoTApplications,” in Proc. EuroSciCon Conf. 3D Printing Wireless Technol. 2018, Lisbon,
Sep. 2018.

5

T. Fujii, “Smart Spectrum Management for V2X,” in Proc. IEEE DySPAN 2018, Seoul,

6

Korea, Oct. 2018.
K. Ishibashi, “Machines Talk Freely: Graph-based Designs for Distributed WirelessCommunications,” in Proc. 2018 15th WPNC, Oct. 2018.

7

K. Ishibashi, D. Manyvone and M. Ito, “Beat Sensors for Smart Environment
Monitoring Systems,” in Proc. Sigtelcom 2019, Hanoi, Mar. 2019.

Invited Talks in Domestic Conference
1

, “
,”

2

, “
IoT

,
3

, “[

, RCS2018-14, Apr. 2018.
Beat Sensor, SDM2018-76, Aug. 2018.

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]

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Dec. 2018.

- 39 -,, IT2018 32,

4

, “

,” 2019, CI-3-2,

Mar. 2019.

Tutorials
1
2,“
vol. 441, no. 9, pp. 136-140, Sep. 2018.
, “, vol. 30, no. 2, pp. 15-18, Feb. 2019.

,”

OPTRONICS,,”

Domestic Conference
1

,

,

,
,”
,

2

, “

, RCS2018-21, Apr. 2018.
, “

,”
3

,

, RCS2018-17, Apr. 2018.

,,“, RCS2018-16, Apr. 2018.

4

,

,

,

,”
5

,

,”
,“

, SR2018-8, May 2018.
,
,

,

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6

,

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, RCS2018-36, Jun. 2018.
,, “PPG,,” 57

9, SR2018-6, May 2018.

, “
,”

8

, SR2018-3, May 2018.

,
,”

7

, “

, Jun. 2018.

S. Takahashi, T. NGUYEN, Y. Sato and K. Ishibashi, “Cross-couple DTMOS Rectifier
with Floating sub-circuit using 65nm SOTB CMOS technology for uW RF Energy
Harvesting,” in Proc. TJMW2018, Bangkok, Jun. 2018.

10

T. Yamada, J.Ida, T. Mori, S. Momose, Y. Tsuchiya, K. Itoh, and K. Ishibashi,“Rectification of Small voltage Signal by Super Steep Subthreshold Slope “PN-Body
Tied SOI FET” for RF Energy Harvesting,” in Proc. TJMW2018, Bangkok, Jun. 2018.

11
12

,
,
, “ZigZag
RCS2018 71, Jun. 2018.
,

ALOHA,”, L. Hanzo, “

EXIT
,”

13

,

, RCS2018 70, Jun. 2018.

, L. Hanzo, “
IQ

14
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,,,, RCS2018-51, Jun. 2018.
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- 40 -, SR2018-21, Jul. 2018.

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, SR2018-44, Jul. 2018.
17

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,

,

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, SR2018-45, Jul. 2018.
18

,

19

,

,

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, SR2018-32, Jul. 2018.
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, SR2018-30, Jul. 2018.

20

,

21

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22

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, RCS2018-128, Jul. 2018.

DGS

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, EST2018-32, Jul. 2018.
,
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, RCS2018-116, Jul. 2018.

23

H. Lumbantoruan,
,”

24

,

, “UAV-BS, Jul. 2018.
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MEC & UE,”, RCS2018-119, Jul.

2018.
25

,

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, OFT2018-8, Aug. 2018.

26

,

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27

MWP2018-8, Aug. 2018.
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, OFT2018-7, Aug. 2018.

,

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29

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18GHz/28GHz, B-17-5, Sep. 2018.

GaN HEMT, C-2-17, Sep. 2018.
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OAM- 41 -, C-2-4, Sep. 2018.

, B-1-36, Sep. 2018.
OAM, B-1-35, Sep. 2018.
,, “,” 2018, B-1-

34, Sep. 2018.
36

,

, “
, B-13-12, Sep. 2018.

2018
37

,

,

A/D

, “
,” 201838,,”, B-13-29, Sep. 2018.
,” 2018,“, B-13-30, Sep. 2018.
39,,,” 2018

40

,

,

,

,

,” 2018
,

,

RFID
41

,
, “14 Gbps
, C-14-4, Sep. 2018.

,” 2018
42

,

43
44

,

, C-2-71, Sep. 2018.
, “, BP-2-4, Sep. 2018.
MEC

,”

, “

71, Sep. 2018.
,
2018

RoF

, “

,“
, B-5-98, Sep. 2018.

201828 GHz,” 2018, “920MHz

, B5-

RFID

,”

, B5-93, Sep. 2018.

45

,
, “
B5-93, Sep. 2018.

46

, λ

47

,

IF

,

,” 2018

,“

CPC
,”

, λ

,

, λ

,”

,

, SANE2018-50, Oct. 2018.

, “

CPC
48

,

,

, SANE2018-48, Oct. 2018.
, “
,”

,

SANE2018-46, Oct. 2018
49
50

, λ
,

,
,

, “
,”
,

, SANE2018-49, Oct. 2018.
,,“PN-body Tied SOI-FET”
2018.
51

,
,”

, “

SS

, SDM2018-31, Oct.

T. Kawaguchi and K. Ishibashi, “[Poster Presentation] Empirical Model of Distributed
Photovoltaics for Energy-Harvesting Wireless Communications,” in Proc. SmartCom
2018, Bangkok, Thailand, Oct. 2018

52

N. Aihara, K. Adachi, O. Takyu, M. Ohta, and T. Fujii, “[Poster Presentation] SVM
based orthogonal resource allocation in CSMA/CA,” in Proc. SmartCom 2018, Bangkok,
Thailand, Oct. 2018.

53

K. Fukuda, O. Takyu, K. Shira, T. Fujii, M. Ohta, F. Sasamori, and S. Handa, “[Poster
Presentation] A study of adaptive transmission control and accurate data separation
with prediction of sensing results in PhyC-SN,” in Proc. SmartCom 2018, Bangkok,
Thailand, Oct. 2018.

- 42 -

54

A. Abe, Y. Aoki, and T. Fujii, “[Poster Presentation] Time series analysis of multiple
primary users by cooperative sensing based on SDAR algorithm,” in Proc. SmartCom
2018, Bangkok, Thailand, Oct. 2018.

55

Y. Aoki, and T. Fujii, “[Poster Presentation] Spectrum sharing in cooperation with timespace radio environment database,” in Proc. SmartCom 2018, Bangkok, Thailand, Oct.
2018.

56

H. Nakajo, Y. Aoki, K. Katagiri, and T. Fujii, “[Poster Presentation] Spatial spectrum
sharing among micro operators considering distribution on measurement-based
spectrum database,” in Proc. SmartCom 2018, Bangkok, Thailand, Oct. 2018.

57

K. Katagiri, K. Sato, and T. Fujii, “[Poster Presentation] Power Control exploiting
Spectrum Database for V2V Communication Systems,” in Proc. SmartCom 2018,
Bangkok, Thailand, Oct. 2018.

58

T. Noguchi, O. Takyu, T. Fujii, and T. Ohtsuki, “[Poster Presentation] A study of multiantenna relay with mirroring null steering and artificial noise for secure information
sharing among multiple nodes,” in Proc. SmartCom 2018, Bangkok, Thailand, Oct.
2018.

59

N. Aihara, K. Adachi, O. Takyu, M. Ohta, and T. Fujii, “[Poster Presentation] SVM
Based Orthogonal Resource Allocation in CSMA/CA,” in Proc. SmartCom 2018,
Bangkok, Thailand, Oct. 2018.

60

R. Kobayashi and K. Adachi, “[Poster Presentation] Computational Capability andRadio Resource Allocation for Mobile Edge Computing,” in Proc. SmartCom 2018,
Bangkok, Thailand, Oct. 2018.

61

,

62

,
,

,

,

, “GaN HEMT,”
, MW2018-81, Oct. 2018.
,

,

,

,

2018
IEEE MTT-S
Nov. 2018.
63

,

,

,

,

,

65

,

,

OAM-MIMO
,

66

,
,

68

BPF
,

, MW2018-101, Nov. 2018.
, “

70

,
,

,“

, MW2018-93, Nov. 2018.

, “pHEMT RF,”, “920MHz

BPF
SHF

3

, MW2018-107, Nov. 2018.
SHF

, “LC
,”

69

, MW2018-102,,“, MW2018-109, Nov. 2018.

,”
67

,”

,
,”

,

, MW2018-102,

,

,”

F

,”

,

,

,

]

, “

OAM
Nov. 2018.
64

, “[

, MW2018-108, Nov. 2018.
RFID,”, RCS2018-178, Nov. 2018.

, “

,”

- 43 -,

RCS2018-195, Nov. 2018.
71

,“
- .
Workshops & Exhibition 2018, Nov. 2018.

72
73-,” Microw.

, “,” Microw. Workshops & Exhibition

2018, WE5B-2, Nov. 2018.
, “,” Microw. Workshops & Exhibition 2018,

TH6B-1, Nov. 2018.
74

,

,

, “
,”

MAC
75

,

, “ZigZag,,

2018, Dec. 2018.
ALOHA

,”
76

2018, Dec. 2018.
,

, “
,”

77

,

2018, Dec. 2018.
, “
IQ

78

Dec. 2018.
,

,“

,”

2018,

1 chipBeat Sensor,” ASM, Jan. 2019.
79

,

,

,

,
,”

, SR2018-115, Jan.

2019.
80

,

,

81

,

,“

82

,

,

,

,
,”

, “
, SR2018-116, Jan. 2019.
HMM

,”

83

,

84

,

85

,

,

,

,”

, SR2018-118, Jan. 2019.

, “,”, SR2018-106, Jan. 2019.

,,”,, SR2018-117, Jan. 2019.
, “

,

,
,

,

, “

, SR2018-108, Jan. 2019.
,
,“
,”

86

,

, λ

,
,

, SANE2018-114, Feb. 2019.

, “

,”
88

, RCS2018-261, Feb. 2019.

, “
,”

87

Q

,

, ITS2018-64, Feb. 2019.
, “

BPF

,”

24

, 96, Mar.

2019.
89

,
RFID

,

,

, “

,” 2019

SIR, 4-238, Mar. 2019.

- 44 -

90
91,, “TC-IF,”

IN2018-123, Mar. 2019.
,
, “

,

SF-SFB_DPD,”, RCS2018-291, Mar. 2019.
92

,

,

,

,

,

,

,

,
, “5G

,

,

,

,
,”

93

RCS2018-323, Mar. 2019.
,
,
,

,

,“

,

5
,”

, RCS2018-325, Mar.

2019.
94

,

,

,

LoRa/LoRaWAN
95

,

96

,
,”

,
PLNC
,

,

, SR2018-125, Mar. 2019.
,, “, RCS2018-335, Mar. 2019.

,”
,

, “

, “[

] Energy-Neutral Receiver-Initiated (ENRI)

MAC
20, May 2018.

,”

97

,

,

,“

98

,

, “

/2
,” 2019,,, C-2-59, Mar. 2019.

BRF,” 201999, SR2018,, C-2-64, Mar. 2019.

,

,

,

,

,
, “5G

,

,

,
,” 2019100,, BP-1-2,

Mar. 2019.
H. Lumbantoruan, K. Adachi, T. Z. Hui Ernest, R. P. Sirigina, and A. S. Madhukumar,“Outage Probability Analysis of Sensor Nodes by an ULA Equipped UAV-BS,” 2019
, B-5-25, Mar. 2019.
,
,
,

101

,

,

,“

PLNC

,” 2019, B-5-16, Mar.

2019.
102

,

,

,

MIMO Switching
103

Mar. 2019.
,
2019

,

,

PLNC

,” 2019

,“

LPWA

,

,

,

,

, B-5-17,
,”

,
, “
LAN
, B-17-2, Mar. 2019.

,” 2019
,

,

2019
106

Wireless, B-5-51, Mar. 2019.

104
105

,“

,

,

Chireix, C-2-21, Mar. 2019.
,
,

,”
,

,” 2019- 45 -,“GaN HEMT, C-2-20, Mar. 2019.

107

,

108

,

, “

,

,

/

,” 2019,

GaN HEMT MMIC

, C-2-19, Mar. 2019.
, “

GaN HEMT,” 2019109,,, “10MHz, C-2-14, Mar. 2019.

110

,

111

,

,

112

,” 2019, “

GaAs HEMT, C-2-13, Mar. 2019.
,,,” 2019,
OAM, C-2-18, Mar. 2019.

,” 2019, “OAM, B-5-83, Mar. 2019.
,

,

,

,

,

, “
,” 2019, B-1-105,

Mar. 2019.
113

,

,
,” 2019

114

,

115

10MHz
,

, “
, B-1-75, Mar. 2019.
,, “

Si MOS,”,, MW2018-165, Mar. 2019.

,

,“

OAM

,”
116

, λ
,”

117

, “
, SANE2018-113, Mar. 2019.

,118, RCS2018-313, Mar. 2019.

,
,

, λ
,

,“

CPC-SIMO,”, “, SANE2018-116, Mar. 2019.
,”, PN2018-89, Mar. 2019.
,
,
, “

119

,”
, PN2018-90, Mar. 2019.
,
,
,

120

, “
,”

121

, pn2019-stws-1, Mar. 2019.
, “

,

,”

, pn2019-stws-

2, Mar. 2019.

Symposiums
1

Y. Yamao, “RF hardware techniques for 5G mobile communications,” Shino-Japan
Workshop Next Generation Mobile Commun. Technologies Appl. 2018, Qingdao, Aug.
2018.

2

,
,”

,“
9

IoT
, D-2-1, Oct. 2018.

- 46 -

3

,“

,”

30

, Oct. 2018.
,“

4

,”

30

, Feb. 2019.

5

,“

,”

BP-1, Mar. 2019.

Other Academic Activities
1,“,” IoT,

2, Jul. 2018.

, “Radio and Computing Resource Allocation for Minimizing Total Processing
Completion Time in Mobile Edge Computing,” IoT,, Feb. 2019.

Awards1, 2018, Jun. 2018.

2, 2018, Jun. 2018.

3

Y. Aoki, IEEE VTS Tokyo Chapter 2018 Young Researcher’s Encouragement
Award, Aug. 2018.

4, 2018 APMC presents this certificate of Student and Young
Engineer Design Competitions, First Prize in Track B(Passive): PCB bandpass filter
design competition, Nov. 2018.

5, 2018 APMC presents this certificate of Student and Young
Engineer Design Competitions, Second Prize in Track B(Passive): PCB bandpass filter
design competition, Nov. 2018.

6

,

7

, Jan. 2019.
, IEICE, Mar. 2019.

8

,

,

,

,

,

,

, RCS

,

,

Mar. 2019.
9,, Mar. 2019.

10,, Mar. 2019.

11
12

S. Ogata, K. Ishibashi, and G. T. F. de Abreu,, Mar. 2019.
,

,

34

, 2018(SR), Mar. 2019.
13

,

30

14

λ

,

15

,

30

, Mar. 2019.
30, Mar. 2019.
, Mar. 2019.

- 47 -

16

,

17
18

,

30

,

, Mar. 2019.
, OFC 2019 Top Scored Paper, Mar. 2019.

,, Mar.

2019.
19,, Mar. 2019.

20,, Mar. 2019.

Patents
1

,

,

,

,

,

,

,”

2018-158123,

Aug. 2018.
2,63995063,, “, 14 Sep. 2018.
,

,

,

,

,”
4

,”
, “

6403280,, 21 Sep. 2018.

K. Muraoka, M. Ariyoshi, T. Fujii, “Wireless device, wireless Communication system
and method for detecting radio wave,” European Patent, EP2237632, 23 Jan. 2019.

5

,

,

,

,

,

6469475, 25 Jan.

2019.
6

,

1

,“

,”

6403145, 21

Sep. 2018.
7

, λ

,

2

I643775,
8,”11 Dec. 2018.
, λ

,

2

I652494,
9

, “
, “

,”

1 Mar. 2019.

,
,”

,

,

,

,“

6377968, 3 Aug. 2018,,

Press Release etc.
1

, “STF 2018,

2

“ G
2019.

,”
, 6 Sep. 2018.
”,- 48 -

20194, 30 Mar.