Advanced Wireless & Communication
Research Center

Message from the Director, Prof. Takeo Fujii

Due to the impact of the Convid-19 disaster in 2021, AWCC research also continues to operate
under restrictions. Under this situation, activities have gradually increased, including the startof hybrid research meetings in a remote and face-to-face. Although face-to-face participation ininternational conferences is still difficult, the entire research community is seeking post-corona
activities, such as the resumption of on-site workshop in Japan. While the activities of Advanced
Wireless Communication Research Center (AWCC) were slightly decreased comared withstatistics of pre-corona, activities were improved including launching several national projects
including beyond 5G, low power sensor networks and cooperative autonomous vehiles. I hope we
can overcome Covid-19 and return to a peaceful life.
For the years, AWCC has been aiming and conducting four missions that are;- Dedication to advanced research on wireless communications; offering more unique results.
- Education in graduate school for cultivating specialty in engineering; specialized and universal
education in the area.
- Active collaboration / joint research with industries and government; transferring the outcomesto the society.
- Constant acquisition of competitive research funds; for self-supported operation.
The current vision of AWCC is “Ambient Wireless in Connected Community (AWCC).” AWCC
intends to cover broader research area including not only wireless communications 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.
(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 and beyond system is being developed in the world. The 5G and beyond 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 powertransfer is another hot and important topic.
(3) Advanced Wireless System & Networks
We have 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
and contribute much in research and education of “wireless” and “communications”. We hopeyour 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 Electro--2-

Communications.

1.3 PEOPLE【Director, 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

ResearchCenter,

The

UniversityofElectro-Communications. Currently, he is a professor in Advanced Wireless and Communication
Research Center, The University of Electro-Communications. His current research interests arein cognitive radio and ad-hoc wireless networks. He received Best Paper Award in IEEE VTC
1999-Fall, 2001 Active Research Award in Radio Communication Systems from IEICE technicalcommittee of RCS, 2001 Ericsson Young Scientist Award, Young Researcher's Award from the
IEICE in 2004, The Young Researcher Study Encouragement Award from IEICE technicalcommittee of AN in 2009, Best Paper Award in IEEE CCNC 2013, and IEICE Communication
Society Best Paper Award in 2016. He is a member of IEEE and a fellow of IEICE.

【Full-time 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 ResearchCenter (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 School of Engineering and Applied Sciences, Harvard University, Cambridge, MA. Prof.
Ishibashi has contributed more than 100 articles to international journals and conference
proceedings. His current research interests are grant-free access, non-orthogonal multiple access(NOMA), millimeter wave communications, ultra-low power communications, signal processing,and information theory. He is a senior member of IEEE and IEICE.

-3-

【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. His
research interests include cooperative communications and energy
efficient communication technologies. From 2007 to 2010, he was a Japan
Society for the Promotion of Science (JSPS) research fellow. He was thevisiting researcher at City University of Hong Kong in April 2009 and thevisiting research fellow at University of Kent from June to Aug 2009. FromMay 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. He was an Associate Editor IEEE WirelessCommunications Letters since 2016, IEEE Transactions on Vehicular Technology between 2016
– 2018, IEEE IEEE Transactions on Green Communications and Networking since 2016, andIEEE Open Journal of Vehicular Technology since 2019. He is a senior member of IEEE and amember IEICE. He was recognized as the Exemplary Reviewer from IEEE WirelessCommunications Letters in 2012, 2013, 2014, and 2015. He was awarded excellent editor award
from IEEE ComSoc MMTC in 2013. He is a coauthor of WPMC2020 Best Student Paper Award.

【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.

-4-

【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).

-5-

【Concurrent 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 a Professor with the Graduate School of Informatics and Engineering,
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.

【Concurrent 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.

-6-

【Visiting Professors】
Prof. Yasushi Yamao, Ph.D.
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.
Prof. Yasushi Ito, Ph.D.
Prof. Giuseppe T. F. de Abreu, Ph.D
【Cooperative Professors】
Prof. Nobuo Nakajima, Ph.D.
Prof. Haruhisa Ichikawa, 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. Toshiharu Kojima, Ph.D.
Associate Prof. Hisa-Aki Tanaka, Ph.D.
Associate Prof. Kazuki Nishi, Ph.D.
Associate Prof. Wu Celimuge, Ph.D.
-7-

Assistant Prof. Satoshi Ono, Ph.D.
Assitant Prof. Katsuya Suto, Ph.D.
【Visiting Professors from Industry】
Prof. Kunio Uchiyama (AIST)
Prof. Takahiro Asai(NTT Docomo R&D)
Prof. Yoji Kishi (KDDI Research Inc.)
Prof. Terunao Soneoka (NTT-AT)
Prof. Akinori Taira (Mitsubishi Research Institute Inc.)
Prof. Hiroyuki Tsuji (NICT)
Prof. Hideki Hayashi (Softbank Corp.)
Prof. Hiroyuki Seki (Fujitsu Laboratory Ltd.)
Prof. Yukitsuna Furuya (WiTLa)
Prof. Kenji Yoshida (Intermedia Laboratory Inc.)-8-

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. Takayuki Inaba（Division Leader, ITS, Radar）
Prof. Takeo Fujii（ITS, Radio Environment Analysis (REA), DPRN, Wireless security）
Associate Prof. Koichi Adachi (Drone)

2.1.3 Major Research Outcomes in 2021
(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 enough 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."[Constructing packet delivery rate-based map for V2X using confidence interval] (Fujii Lab.)
Recently, a radio map has been attracted attention for realizing reliable V2X
communications. To create the radio map for V2X communications, each vehicle observes
radio environment information, such as the received signal power, and reports theinformation to a cloud server. The cloud server constructs a radio map by processing thereported information. Communication parameters can be properly designed using a radio
map because of the accurate estimation of radio propagation. However, an inaccurate radio
map may be created in V2X communications owing to the small number of observation data.
Thus, we propose a method to correct the statistical information of a radio map based oninterval estimation. In the proposed method, the PDR of each mesh is corrected so that thelower confidence limit of the PDR is greater than an acceptable value using the ClopperPearson confidence interval, which is an interval estimation method of the population ratio.
The calculated reliability of the corrected maps for the number of samples for each meshgives an idea of how reliable each corrected mesh is, as Figure 2.1-1 shows (1-α is theconfidence coefficient and β is the allowable absolute error). We will consider using thischaracteristic as a confidence criterion for the corrected PDR. In addition, from the-9-simulation results assuming V2I communications shown in Fig. 2.1-2, it is confirmed thatthe proposed method (PDR_Conf) can guarantee the reliability of communications even under
the sparse data constraint.

Fig2.1-1 Confidence level of the map for thenumber of samples in each mesh.

Fig 2.1-2 CDF of PDR in V2I communications(1 − α = 0.95).

(B) Radar Signal Processing[Vehicle Onboard Radar] (Inaba Lab.)The stepped multiple frequency (SMF) modulation has proposed by Inaba Lab. The
unique radar modulation/demodulation method can achieve a high range resolution and along-range detection performance by a narrow receiver bandwidth compared to transmitting
bandwidth. That is why this method achieves not only a high range resolution but a longrange detection performance. In recent years, Japanese radio wave laws for short range radar
has been modified for use of the ultra-wide bandwidth of 5 GHz in 79 GHz band. The
advantage of this method itself must be more remarkable for use of the ultra-wide bandwidth.

Fig.2.1-3 Output of the frequency vector by sparse frequency step design and Synthetic Wideband Waveform(Rate=0.8).

- 10 -

Fig.2.1-4 Block diagram of the signal processing of iterative signal
subtraction and frequency estimation method in stepped multiple
frequency radar.

Fig. 2.1-5 Target range estimation
RMSE and CRLB of the proposed
method.

In the case of ultra-wideband, we face the velocity and range ambiguity problems, since boththe pulse repetition interval and the frequency steps should be sparse.
To overcome the problems, we proposed the sparse frequency division scheme, in which
the frequency steps are designed for obtaining good side-lobe characteristics by fewer numberof frequency steps without range ambiguity (shown in Fig. 2.1-3). The target range andvelocity are obtained by the signal processing of iterative signal subtraction and frequency
estimation (shown in Fig.2.1-4). Simulation results indicated that the RMSE of range of eachtarget shows a good agreement with CRLB (shown in Fig.2.1-5). These proposed methods can
not only detect the targets having different receiving signal level of power with the highresolution but also mitigate the multipath fading due to the ultra-wideband width.

2.1.4 Funds【Grants-in-Aid for Scientific Research】
1. 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【Commissioned Research】
1. METI Project on Research, Development, Demonstration and Deployment (RDD&D) of
Autonomous Driving toward the Level 4 and its Enhanced Mobility Services (RoAD to theL4), “Harmonization and interoperability of V2V and V2P for deployment of L4 in mixed
traffic environment”
T. Fujii, K. Suto
【Cooperative Research】
1. “Research on improvement in recognition rate of RF IDs”
Y. Yamao
2. "Research on communications technology for machine tools"
K. Adachi and Y. Yamao- 11 -

【Other Funds】
1. “Improvement of spatial resolution of radar sensor”, Academic consulting, T. Inaba
2. “Analysis program of stepped multiple frequency CPC”, License agreement, T. Inaba- 12 -

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. Koichiro Ishibashi
Low Power RF Devices, Sensor Networks
Prof. M. Matsuura
Wideband RoF Systems, Devices, Fibers and Integration
Prof. R. Ishikawa
Microwave/Millimeterwave Devices and Circuits
Prof. K.Wada
Microwave Filters and Their Applications
Visiting Prof.Y. Yamao
Reconfigurable RF Circuit, Nonlinear Compensation
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 2021
（A）[Wide-dynamic-range GaN HEMT outphasing amplifier and quasi-millimeter-wave Doherty
power amplifier MMICs]（Ishikawa Lab.）In recent years, the greater sophistication and diversity in wireless communication systems have become
remarkable, hence further improvements in performance of wireless transmitters in the base stations are
required. Power amplifiers are an important device, which greatly affect distortions for signals and power
consumption. A peak-to-average power ratio (PAPR) of recent digital wireless signals is large as more than
6 dB. A PAPR of 9 dB is often considered in 4G and 5G OFDM (Orthogonal Frequency Division
Multiplexing) / QAM (Quadrature Amplitude Modulation) systems. In such systems, power efficiency atlarge output power back off levels dominates a total power consumption of the amplifiers than that insaturation levels. Thus, high efficiency characteristics are required for wide dynamic range in the amplifiers,
where a special attention should be paid on the efficiency at large output back-off (OBO) power level.
For this issue, we have developed an outphasing power amplifier with a compact combiner. The combiner
could be successfully shrunk by applying a series-load-compensation connection scheme. In addition, adual-power-level design was applied for the power amplifier to increase the dynamic range of its highefficiency power. A fabricated GaN HEMT outphasing power-amplifier MMIC exhibited a peak drain
efficiency of 63% with a maximum output power of 35dBm at 4.6 GHz. In addition, a drain efficiency ofmore than 40% was maintained within an output back-off of 8 dB (Fig. 2.2.1).
In addition, a 28-GHz-band GaN HEMT MMIC Doherty power amplifier has been developed by using
0.15-μm GaN HEMT MMIC technology. The Doherty amplifier was designed by adaptively adjusting aload resistance division to a carrier amplifier (CA) and a peaking amplifier (PA) according to an output
power balance between the CA and PA. The fabricated GaN HEMT MMIC Doherty amplifier exhibited amaximum drain efficiency of 54% and a maximum power-added efficiency of 44% at 29.1 GHz, with asaturation output power of 30 dBm. In addition, a drain efficiency of 33% was achieved at 29.1 GHz on a
9-dB output back-off condition (Fig. 2.2.2).

Fig. 2.2.1

Fabricated GaN HEMT outphasing power amplifier with a compact combiner, and its characteristics- 14 -

Fig. 2.2.2

Fabricated 28-GHz-band GaN HEMT Doherty power amplifier, and its characteristics（B）[A 12-GHz-band loop antenna array with reflector integrated on a Teflon multi-layer substrate
for 4-channel multiplexing OAM communication] (Ishikawa Lab.)We have demonstrated that the electro-magnetic wave propagation occurs with a single orbital angularmomentum (OAM) mode when a current distribution of the azimuth angle φ-direction for a circular loop
antenna conductor contains only one Fourier expansion coefficient. This condition almost retains at theloop-antenna conductor length of nλ (n is the integer). Based on this principle, we have successfully
developed a 4-channel multiplexing OAM communication by using a loop antenna array with reflector
integrated on a Teflon multi-layer substrate at 12-GHz band. In addition, the communication characteristics
have been successfully improved by connecting baluns to the terminals of the integrated circular loop
antenna at the back side of the reflector. The merchant balun serves as the impedance matching, and byusing open-ended λ/4 lines as the ground of the balun, it could be arranged in a narrow space behind thereflector. In eigenvalue decomposition of the measured four-port S-parameters on the OAM communication
between the fabricated loop antenna arrays, a transmission power of 98.9 % was treated as the eigenvalues
without signal precoding, which indicated high mode purity. If a signal precoding is performed, all oftransmission power (100%) is treated as the eigenvalues. In a four-channel 16QAM communication test for
the loop antenna array systems, EVMs of less than 9.6 % were obtained for each channel without any signal
processing (Fig. 2.2.3).

Mode 1 (Rx5) EVM: 9.5%, Mode 2 (Rx6) EVM: 8.6%, Mode 3 (Rx7) EVM: 9.6%, Mode 4 (Rx8) EVM: 9.6%
Fig. 2.2.3 Constructed 12-GHz-band 4-channel multiplexing OAM communication system, and its characteristics(12.44 GHz, 15.625 MSymbols/sec (Total: 250 Mbps), Tx1: 30 mV, Tx2: 30 mV, Tx3: 55 mV, Tx4: 30 mV)- 15 -

（C）Photonic Digital-to-Analog Conversions (DACs) for RoF Systems (Matsuura Lab.)
Digital-to-analog conversion (DAC) is an essential function in a wide field, including
communication networks. In recent years, with the development of analog and digital signal
processing technologies, the demand for DACs with higher performance is rapidly increasing.
However, electrical DACs have inherent bottlenecks such as jitter limitation, electromagnetic
interference, and resistive-capacitive delay for higher speed operations. On the other hand,
all-optical (photonic) approaches have attracted much attention recently, because photonic
DACs enable us to overcome many bottlenecks of electrical signal processing. However, thesephotonic DACs have complicated schemes, and require any additional electrical signal
components to perform the DACs.
Semiconductor optical amplifiers (SOAs) have practical advantages such as small footprint,
low switching energy, high nonlinearity, and ability of monolithic integration for opticalsignal processing applications. In particular, quantum-dot SOAs (QD-SOAs) provide higher
bit-rate operation and broader gain than those of conventional SOAs. Owing to these features,
we have successfully achieved ultrahigh-speed optical signal processing using QD-SOAs. In
SOAs and QD-SOAs, when an optical signal is amplified, red and blue frequency chirp occur
at the leading and trailing edges of the signal pulse, respectively. Frequency chirp is wellknown phenomena with unique property. The peak values of red chirp (shift to longer
wavelength side) strongly depend on the input signal power and the data pattern, and wehave demonstrated a photonic analog-to-digital conversion using a red chirp in a QD-SOA.
In contrast, the peak values of blue chirp (shift to shorter wavelength side) have low
dependence on the input signal power and the data pattern. By utilizing this property, we
have proposed a photonic DAC using a blue chirp in a QD-SOA. However, to improve theresolution and conversion speed of the photonic DAC, clock pulse trains with a shorter pulse
width and much multiple wavelengths are needed for practical use.
In this year, we introduced a multi-wavelength clock generation using an optical comb
generator (OCG) and 2-bit photonic DAC based on binary-to-quaternary conversion using a
blue chirp in a QD-SOA. We experimentally demonstrated a 20-Gb/s DAC using thegenerated multi-wavelength clocks and evaluated the conversion performance.

Fig.2.2.4 Examples of pulse trains of (a) 2-channel 10-GHz clocks with each different
wavelength, (b) 20-Gb/s input binary data signal, and (c)converted signal when input binary
data pattern was “00011011”.

Figure 2.2.4 shows examples of the pulse train of the 2-channel 10-GHz clocks with eachdifferent wavelength, 20-Gb/s input binary data signal, and converted signal when input
binary data pattern was “00011011”. In Figs. 2.2.4 (b) and (c), it can be clearly seen that the
20-Gb/s binary-to-quaternary conversion was successfully achieved. It should be noted that
we also achieved the binary-to-quaternary conversion with different binary data patterns.
We also measured the amplitude accuracy of the output 4-level amplitude signal converted
by the DAC. The output pulse amplitude is normalized by 4 steps, and the one stepcorresponds to the smallest increment step of the DAC output between two adjacent levels.
The ideal DAC step is defined as one least significant bit (LSB). Based on this step, the- 16 -

differential non-linearity (DNL) and the integral non-linearity (INL) of the presented DAC
were calculated. The DNL is defined as the deviation of the actual step from the ideal one,
whereas the INL is defined as the deviation of the actual transfer function from the ideal one
adjusted for the best-fit. The absolute values of the DNL and the INL were less than 0.13
LSB and 0.07 LSB, respectively. All the DNL values were within ±0.5 LSB, which provide no
missing codes for the DAC. The INL values show that the maximum deviation from the idealtransfer function was 1.75%, which confirms that the DAC has high linearity.

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 Challenging Research (Exploratory) “Research on reconfigurable alloptical logic gates using semiconductor devices” (M. Matsuura)【Cooperative Research】
1. RF device technologies Inc. “Study on novel devices and its evaluation methods for wirelesscommunications” (R. Ishikawa)
2. SoftBank Group Corp. “Low power consumption amplifier” (R. Ishikawa)
3. ROHM Co., Ltd. “High frequency measurement technique for GaN-HEMT” (R. Ishikawa)
4. Japan Space Systems. “Technical evaluation of high-efficiency power transfer section related to“Research and development project for high efficiency wireless power transfer in space solar
power systems” (R. Ishikawa)
5. Japan Space Systems. “Development of energy-related technology on the lunar surface(organization of technical issues related to electric power) Examination of RF amplifiers for
wireless power transmission in orbital solar power systems around the moon” (R. Ishikawa)- 17 -

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（Division Leader, Future NW, Cognitive Radio, Distributed NW）
Prof. Koji Ishibashi（Future NW, Distributed NW）
Prof. Motoharu Matsuura（Future NW）
Associate Prof. Koichi Adachi (Future NW)

2.3.3 Major Research Results in 2021
[Local 5G mmWave Signal Measurement and Analysis for Spectrum Database] (Fujii Lab.)The concept of the smart spectrum has been proposed to deal with the problem of shortageof spectrum. In smart spectrum, a database is constructed based on the measured data of theradio environment to manage the spectrum, thus realizing highly efficient spectrum
utilization, and its usefulness has been confirmed in several systems. On the other hand, for
5G NR signals, the database based on the smart spectrum has not been studied and its
usefulness has not been confirmed. In particular, since 5G millimeter wave (mmWave)signals adopt beamforming technology, it is necessary to estimate the directivity andpropagation characteristics of multiple beams. Therefore, in the database construction, we
need to measure and manage not only the conventional management for each base stationand frequency but also each beam. In this study, we conduct a measurement campaign ofmmWave signals from a local 5G base station in Imabari City, Ehime Prefecture, Japan, andconstruct a spectrum database. Additionally, based on the stored datasets, we show theresults of analysis of the highest received signal power and its beam index in each beam ateach location and comparison with propagation model.
A measurement campaign was conducted from Feb. to March 2021 to construct a spectrum
database of mmWave signals of 5G NR. This campaign measured local 5G mmWave signals
operated by Ehime CATV in Imabari City, Ehime Prefecture, Japan.
Based on the constructed spectrum database, the fluctuation graph of the highest average
SS-RSRP among each beam index and its beam index is shown in Fig. 2.3-1 using a terminal's

Fig. 2.3-1. Highest average SS-RSRP andindex fluctuation in each beam index ateach GPS log location.

Fig. 2.3-2. Comparison of the CDF of theerror between the database weconstructed and the propagation model
used for the local 5G license application.
- 18 -

GPS logs. Thus, the information on the fluctuation of the beam index of the highest SS-RSRP
with the movement of the terminal is stored in the spectrum database, which can be applied
to the control and management of each beam. Finally, the errors between the estimatedvalues from the database and the propagation model and the true values are compared,
respectively. As a comparison, we consider the propagation model used to calculate thecoverage area in the local 5G license application. The cumulative distribution function (CDF)of the error in the estimate is shown in Fig. 2.3-2. This can be interpreted to mean that the
local 5G coverage area by the propagation model is designed to be extra, which confirms theusefulness of the propagation environment estimation by the database.
[An Improvement of Security Scheme for Radio Environment Map under Massive
Attacking] (Fujii Lab.)Radio environment maps (REM) are widely used to enhance communication efficiency
in spatial spectrum sharing. This can be generated using reports from the terminals.
However, an open characteristic environment always leads to a security problem; forexample, when malicious terminals exist in the environment and data falsification
attacks occur, the accuracy of the REM is affected by the malicious action. We consider
that malicious terminals exist in the communication environment, and they can attack
the database to damage the accuracy of REM to satisfy their selfish requirements: affectthe primary terminal frequency bands or take the free frequency bands, etc. REM
construction need to collect received signal power from spatially distributed mobile
terminals and calculate the average power of each mesh. Data falsification attack is anefficiency attack to damage the REM. This kind of attacks are also called Byzantine
attacks, which refer to malicious terminals that change the data of their sensing powerof the spectrum to blind the database (as Fig.2.2-3).
In this study, we improved the double-layer monitor algorithm to identify malicious
datasets in the database. Additionally, we proposed a new algorithm involving
interpolation based on spatial information to solve the problem of unequal information
obtained from the meshes. By interpolation, a database can obtain sufficient datasetsfrom each mesh and have a better performance (as Fig.2.2-4). Furthermore, we definedan optimal attack strategy using the proposed security algorithm. As Fig.2.2-5 shows,the influence of malicious terminals can be different when changing the attacking index.
So, we can generate the optimal attack under the white-box mode. The simulation results
indicate that the proposed method can eliminate the influence of malicious terminals andthat a highly accurate REM can be obtained under even optimal attack (as Table2.3-1).

Fig. 2.3-3. A concept of the false REM.

- 19 -

(b)(a)
Fig. 2.3-4. RMSE under different attacking index.

Fig. 2.3-5. Attacking performance under different attacking index.
Table 2.3-1. Accuracy index under optimal attack.
error
Attacking Index
optimal attack
traditional attack
proposed method
proposed methodwith all terminals
0.85
0.0606
0.06211.28770.87
0.08670.0745
1.11600.90
0.28880.09740.85850.95
0.17810.08340.4292[Radio Propagation Extrapolation by Using Multiple Separated Propagation Paths
Estimated by Radio Map] (Fujii Lab.)
Nowadays, a radio map attracts attention to estimate radio propagation with high accuracy
for sharing spectrum with multiple systems. In spectrum sharing, a secondary user (SU)must suppress own interference power toward a primary user to 10-20 [dB] lower than thenoise floor. The prediction accuracy may be degraded because it is difficult to detect thereceived signal power below the noise floor. Although estimating radio propagation below thenoise floor to meet this criterion, the SU may not use conventional radio maps which missthe interference power below the noise floor. Therefore, an extrapolation method for radio
propagation below the noise floor is necessary.
In order to solve this problem, we propose a novel extrapolation method of radio
propagation based on the separation of a propagation path. Proposed method considers thesituation such as Fig 2.3-6. Under this situation, we can consider that the path loss and the- 20 -

shadowing characteristics are similar in this path even if transmitters A and B are different
on the duplicated propagation path. This is because the geographical conditions are the samein the duplicated path. Proposed method estimates the received power of transmitter A below
noise floor, utilizing the spatial correlation. The proposed method separately estimates pathloss and shadowing and received power in target point O. In path loss estimation, apropagation path from transmitter A to point O is separated in two paths. path loss of eachpath is calculated from observable received power of the transmitter near each path. Besides,
path loss model is based in linear regression. In shadowing estimation, shadowing oftransmitter A and B have a correlation. In addition, shadowing empirically follows lognormal distribution with log mean 0 [dB]. Hence, shadowing of transmitter A is calculated as
the mean value of a conditional lognormal distribution based on the known shadowing forthe transmitter B.
To verify proposed method, we conducted an emulation-based performance evaluation using
the datasets in a real environment. the datasets were measured around Chofu City in Tokyo,
Japan. The proposed method was evaluated by the two methods that estimate only path loss
(Proposed method w/ 𝑃𝑃𝑃𝑃AO w/o 𝛿𝛿𝐴𝐴O ) and estimate path loss and shadowing (Proposed method
w/ 𝑃𝑃𝑃𝑃AO w/ 𝛿𝛿𝐴𝐴O ). Compared methods were Extended HATA, extrapolation by linear
regression with only the datasets of transmitter A (Extrapolation w/ 𝑃𝑃𝑃𝑃AB ). Fig. 2.3-7. shows
radio maps of true map, the proposed methods and the compared methods. The results showthat the proposed method can predict the radio map with higher accuracy than the othermethods. For example, the proposed methods could estimate the high received signal powerin the north and the low one in the south as with the true radio map.

Fig. 2.3-6. Utilization of two radio maps.

Fig. 2.3-7. An example of radio maps.
- 21 -

[Radio and Computing Resource Allocation for Mobile Edge Computing] (Adachi Lab)
This research focuses on maintaining the battery storage for multi-user wireless poweredmobile edge computing (WP-MEC) systems. MEC can compute alternatively heavy tasks ofwireless devices (WDs) and wireless power transfer (WPT) can charge the batteries of WDs
wirelessly. WP-MEC leads to power-saving and makes it easy to operate IoT sensor network.
A centralized control at an access point (AP) can reduce packet collisions, but it incurs
overheads by exchanging control information. Thus, we proposed a decentralized
probabilistic binary offloading (PBO) strategy, which lets each WD probabilistically selects
how to process computational tasks. However, the conventional PBO strategy did notconsider the design of WPT transmission time and beamforming, and charged the batteriesof WDs for the whole time at maximum power by WPT. Thus, this research proposes a
dynamic offloading probability decision based on the battery storage at the WDs for the PBO
strategy, an estimation method of the WDs' battery storage, and a design of the WPTbeamforming duration.
This strategy can reduce overheads and WPT transmitting time. Fig. 2.3-8(a) shows thesnapshot of the battery storage versus time when the number of the WPT transmit antennas
is 16. It can be seen that the battery storage of the furthest WD, 15 [m], is maintained in
keeping with the reference value, which is the value to charge up to this amount each time.
Fig. 2.3-8(b) shows that the ratio when using the proposed method and the WPT designingwith ideal knowledge of the battery storage of the WDs. The proposed method achieves about
48% of the time without WPT and extends that by about 4.5% more than the ideal case.

(a) Snapshot of battery storage(b) WPT idling time ratio
Fig. 2-3-8 Performance of proposed WP-MEC strategy.
[Packet-Level Index Modulation for LPWAN](Adachi lab)
We had previously proposed the concept of
packet-level index modulation (PLIM) to
increase the number of information bits
transmitted by one data packet in low power
wide area network. In PLIM, the generationinterval between two consecutive packets is split
into multiple time slots. Each EN transmits its
packet in a specific combination of time slot andfrequency channel, representing the index, toconvey additional information bits. The gateway(GW) detects the time slot in which the data

- 22 -

Fig.2.3-9 Misdetection probability oftime slot index.

packet is being transmitted to retrieve
additional information. Therefore, accurate
synchronization between EN and GW isessential. However, clock drift occurs due to theinexpensive real-time clock oscillator on eachEN, which results in timing misalignment
between each node and the GW. We proposed a
simple clock drift estimation & compensation
method for the PLIM. Because EN and GW
have common data for clock drift estimation,i.e., transmission interval, time slot length,
and transmission timing offset, GW canestimate the amount of clock drift. The
Fig.2.3-10 Implementation of PLIM.
computer simulation results and experimental
results in Fig. 2.3-9 indicate that the proposed
clock drift estimation & compensation scheme
enables the GW to detect the time slot index
accurately even with the influence of clock
drift. We have also implemented the proposed
PLIM and clock drift estimation &compensation method in the commerciallyavailable LPWAN EN and GW as shown in Fig.
2.3-10.
To improve the performance of PLIM, we
proposed an index mapping scheme. The
conventional PLIM transmission could not
fully utilize the available frequency and timeFig.2.3-11
Theoreticalthroughput
resources. The proposed index mapping fully
versus number of available frequency
utilizes the available frequency channels andchannels.
time slots to avoid packet collisions throughsimple index mapping and de-mapping. The proposed mapping does not require any
information exchange between EN and GW except for the frequency channel allocation,
which is currently available in LoRaWAN by default. Theoretical performance evaluation has
shown that the proposed scheme improves the throughput performance by about 25%compared to the original PLIM transmission and significantly reduces overhead as shown in
Fig. 2.3-11.
[Resource Allocation in LPWA] (Adachi Lab.)
Low power wide area networks (LPWAN) are attracting attention for their capability torealize a wide communication area of several
kilometers at a low cost. To reduce the cost ofnodes, LPWAN generally adopts the ALOHA
protocol, a simple random-access protocol.
However, the ALOHA protocol transmits
packets at arbitrary timing, so as the number ofnodes increases, the packet collision probability
increases, and the packet delivery rate (PDR) of
the system decreases. In industrial monitoring
applications, the nodes sense the observation
target periodically and transmit packets to theGW, resulting in periodic uplink traffic.
Therefore, some combinations of packet
generation cycles between nodes cause repeatedpacket collisions. To avoid repetitive packet
Fig.2.3-12 Time variation of PDR
collisions in an LPWAN with a large number of
performance.

- 23 -

nodes and periodical traffic, we propose a centralized radio resource allocation scheme. The
proposed scheme allocates an appropriate frequency channel and transmission offset time toeach node using centralized control by the GW. The GW can predict the timing of a node's
packet transmission based on the node's packet reception time and transmission cycle. Then,the GW estimates and compares the transmission timing of each node to predict packet
collisions. The GW then calculates the offset time and frequency channel that can avoid
packet collisions for the nodes for which packet collisions are predicted, and reallocates radio
resources to the nodes using downlink. The performance evaluation considering the
LoRaWAN network has been conducted. The computer simulation results show in Fig. 2.312 that the proposed scheme improves the PDR performance compared to ALOHA.
[Grant-Free Access for Massive Users] (Koji Ishibashi Lab.)
Future wireless communication such as Beyond 5G and 6G would accommodate a massive
number of devices, as represented by Internet-of-Things (IoT). In order to realize efficient
low-latency data transmission of a large numberof devices, designing multiple access schemes is
crucial. As one of the promising techniques,
grant-free non-orthogonal multiple access (GFNOMA) has been actively studied. The basestation (BS) does not exclusively assign radio
resources to active users for data transmission in
GF-NOMA, as shown in Fig. 2.3-13. This
Fig. 2.3-13 GF-NOMA system
academic year, we have proposed a GF-NOMA
scheme without prior knowledge of the wirelesschannels, such as information on large-scalefading (LSF) coefficients. In this scheme, a multiantenna BS estimates the active users andchannels using the overlapped pilot signals
spread over the time domain. It is done througha multiple measurement vector approximate
message passing (MMV-AMP) with expectationmaximization(EM)-based
hyperparameter
update, i.e., EM-MMV-AMP. Fig. 2.3-14 shows
the normalized mean squared error (NMSE)
performance of GF-NOMA with the proposed Fig. 2.3-14 NMSE performance of the
proposed GF-NOMA scheme.
algorithm. From the figure, the performance ofour proposed scheme is comparable toconventional MMV-AMP with the perfectknowledge on LSF. Fig. 2.3-15 shows the missdetection (MD) probability and our proposed
algorithm's false alarm (FA) probability withconventional and proposed decision rules. As
seen from the figure, the FA probability of our
proposed scheme with conventional decision rule
remains significant high compared to that ofconventional MMV-AMP. On the other hand, theproposed decision rule can lower both theFig. 2.3-15 MD and FA probabilities ofprobabilities of MD and FA even though BS does
the proposed GF-NOMA.
not know the LSF coefficient. This result has- 24 -

already been accepted for publication on IEEE journal.
[Beamforming Design for Cell-Free Massive MIMO Systems] (Koji Ishibashi Lab.)
Massive MIMO (mMIMO) systems will provide
enormous degrees of freedom and are considered
as a driver of the next generation of wirelesssystems such as Beyond 5G and 6G. Recently, cellfree mMIMO (CF-mMIMO) systems consisting of
spatially distributed access points (APs) are
actively discussed in order to make full use of thecapability of mMIMO systems and address thelimitation due to spatial correlations, as shown in
Fig. 2-3-16.
However, the duplex and its corresponding
beamforming (BF) design for CF-mMIMO have Fig. 2.3-16 Illustration of CF-mMIMO
not been studied considering total throughput and with dynamic TDD
user fairness for mixed uplink and downlink users. To this end, we proposed the resource
allocation and BF design for the CF-mMIMO system with dynamic TDD using Lagrangian
dual transform (LDT) and quadratic transform (QT). Figure 2.3-17 and Figure 2.3-18 show
our proposed methods' total and worst-case spectral efficiency (SE). The proposed method
using dynamic TDD outperforms the conventional method in both results. In particular, thedesign method using the geometric mean of throughput shows the highest performance inboth the total and worst-case results. The results indicate that the system's proposed
method achieves overall system performance and user fairness. These results have alreadybeen reported in the domestic conference and will appear in IEEE Access.

Fig. 2.3-17 CDF of the sum SE for the
proposed and conventional BFs in dynamic
TDD.

Fig. 2.3-18 CDF of the worst SE for the
proposed and conventional BFs in dynamic
TDD.

[Robust Beamforming Design for Millimeter-Wave Channels] (Koji Ishibashi Lab.)
Millimeter-wave (mmWave) communications will play a key role in Beyond 5G and 6G
wireless systems while their inherent vulnerability due to random path blockages inpractical environments as shown in Fig 2.3-19 must be overcome. Several robust
beamforming design methods and various blockage prediction methods have been proposed.
However, several practically important questions still remain: what kind of information
should be predicted, how accurate the prediction needs to be, and how such blockage-related
information should be exploited. To this end, we evaluate the communication performances- 25 -

of various blockage-robust approaches based on the blockage model obtained by theexperimental measurements. Figure 2.3-20 shows the achievable throughput of someblockage-robust approaches. In this figure, sum-rate maximization (SRM)-based
coordinated multipoint (CoMP) transmission approaches with and without instantaneous
block detection and our proposed outage minimization (OutMin)-based CoMP transmission
with blockage probability prediction are presented. Surprisingly, the performance of“OutMin” is superior to “SRM (LOS RUs)” that only uses the radio units (RUs) in line-ofsights for transmission even though “OutMin” only uses the knowledge of the blockage
probabilities. Moreover, it approaches the performance of “SRM (Perfect CSI)” that uses theperfect knowledge of the channel realizations. These results have been already reported in
the domestic conference and will appear as an IEICE invited paper.

Fig. 2.3-19 System model of CoMP
millimeter-wave communications withrandom blockages.

Fig. 2.3-20 CDF of achievable throughputof blockage-robust approaches.

[Optically Powered Transmission Systems for Optical Access Networks]（Matsuura Lab）
Simultaneous over 40-W electric power and optical data transmission using an optical fiber
is demonstrated for optically powered remote antenna units (RAUs) in future mobile
communication networks. In this year, to further increase the delivered electric power bypower-over-fiber (PWoF) link using a double-clad fiber, we improve the link design to extract
a higher feed light power from the double-clad fiber output. Furthermore, to increase theelectric power for driving RAUs, we employ a specially customized photovoltaic power
converter (PPC) that directly converts optical power into electric power. The PPC can input
a feed light with power of over 20 W and has a high optical-to-electrical conversion efficiencyof over 50%. As a result, the combination of the improved PWoF link design and the use of
the PPC successfully achieves the electric power delivery of up to 43.7 W. This is the highest
electric power delivery demonstration by PWoF with optical data signals using a single
optical fiber, to the best of our knowledge.
To evaluate the power transmission performance, we measured the delivered electric
power and power delivery efficiency of the PWoF scheme, as shown in the left side of Fig.
2.3.21. Here, the power delivery efficiency is defined as the power ratio between the total feed
light power injected into the PWoF link and the total electric power converted by the PPC.
As the total feed light power increased, the delivered electric power was linearly increased
up to 43.7 W. The linear characteristics are very useful for controlling the electric power
supplied to the RAUs. The power delivery efficiency was almost constant regardless of thefeed light power, and the average efficiency was approximately 30%. The improved PWoF
design and the high-performance PPC greatly contributed to an increase in the delivered
electric power of the PWoF link. The right side of Fig. 2.3.21 shows variations in the error-- 26 -

vector magnitude (EVM) penalties to the back- to-back signal of the simultaneously
downlink- and uplink- transmitted data signals with the total feed light power injected into
the PWoF link. In the both cases, the EVM values were almost constant, and the variations
were less than 0.05% even when the feed light power was increased up to 150 W. The insets
show the constellations of these signals when the feed light power was set to 150 W. The
EVM values of the downlink- and uplink-transmitted signals were 0.79% and 0.83%,
respectively. The result shows that these signals have good transmission performances evenwhen electric power greater than 40 W is simultaneously delivered into the same optical fiber.

Fig.2.3-21 (Left) Delivered electric power and power delivery efficiency of PWoF scheme asa function of total feed light power injected into PWoF scheme. (Right) EVM penalties toback-to-back signal of downlink- and uplink-transmitted data signals as a function of total
feed light power injected into PWoF link. Insets show constellations of downlink- anduplink-transmitted data signals with 150-W PWoF feed.

2.3.4 Funds【Grants-in-Aid for Scientific Research】
1. Scientific Research B “Sensor Networks with High Speed Environmental Adaptation
by Recognition of Synthesizing Wave”
Takeo Fujii (PI belongs to other organization)
2. 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)【Commissioned Research】
1. MIC “Highly-Reliable Wireless Access Technology for Advanced 5G Networks”
Koji Ishibashi
2. MIC SCOPE “Flexible LPWA Based on Environmental Dynamics”
Koichi Adachi, Takeo Fujii
3. NICT B5G “Technologies for Next Generation Five Dimensional Mobile
Infrastructures”
Takeo Fujii, Katsuya Suto, Koya Sato
4. JST EIG CONCERT Japan " Organically Resilient and Secure Wireless Networks for
Next-Generation IoT Technologies (ORACLE)"
Koji Ishibashi- 27 -

【Cooperative Research】
1. KDDI Research Inc., Motoharu Matsuura
2. NEC Corporation, Takeo Fujii
3. KDDI Research Inc., Koji Ishibashi
4. Ericsson AB, Koji Ishibashi- 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)Prof. Motoharu Matsuura (Radio over Fiber)Prof. Takeo Fujii (Smart meters)
Associate Prof. Koji Ishibashi (Green network and communication theory)
Associate Prof. Ryo Ishikawa (RF energy harvesting)
2.4.3 Major Research Outcomes in 2021
[Development of 14nW Ultra Low Power Sub GHz Wake up Receiver] (Koichiro Ishibashi
Lab)
By introducing wake up receiver (WuRx) in which a IoT system starts operating, the system
can reduce power consumption significantly. In Koichiro Ishibashi laboratory, a study torealize Sub GHz WuRx was developed. By introducing pseudo Balan and ED firstarchitecture without LNA and mixer, the power consumption of WuRx itself can be reduced.
The WuRx was designed and fabricated using TSMC 65nm CMOS technology, and thefabricated chip generates wake up signal at 995 MHz with 14nW power consumption.

Chip

OSC
Comparator Digital

1 mm
Fig. 2.4.3.1 PCB board and fabricated chip using TSMC 65nm of the WuRx.

- 29 -

1 mm

ED

Clock“1”

Demodulation
Signal

“0”

“0”

“1”

“1”

“1” “1”

“0”

“0”

“1”

“1”

Wake-up
SignalInput data

“1”“0” “0”“1” “1”

Fig. 2.4.3.2 Operating wave forms of the WuRx. Wake up signal is successfully generated
after receiving the demodulation signal.
【Grants-in-Aid for Scientific Research】
1. JST/CREST, “Scavenging nW RF energy using Super Steep Transistor and MetaMaterial Antenna” (K. Ishibashi)[Encryption-then-Compression Technique Based on CRC-Aided Polar Codes for Highly
Efficient Multi-Hop Transmission] (Koji Ishibashi Lab.)
Multi-hop transmission has emerged as a promising technique to address the need for highscalability and low power consumption in wireless sensor networks (WSN). In intermittent
receiver-driven data transmission (IRDT) protocol enabling multi-hop transmission, when anintermediate sensor node (SN) has only a single connection, this is called the bottleneckproblem. An option to enhance the throughput is compressing the packets at the SN as thebottleneck. However, this is unfeasible due to the encryption of packets for privacy protection.
In the last year, we have proposed the encryption-then-compression (EtC) scheme based on
low-density parity-check (LDPC) codeswith a belief propagation algorithm(BPA), enabling the intermediate SNs tocompress the encrypted packets. Thisapproach has a practical limitation in its
compression rate and exhibits aperformance gap from the theoreticallimit.
To this end, we propose a rate-compatible
compression method based on Polar
codes with cyclic redundancy check(CRC) and a decompression method
based on a successive cancellation list
(SCL) decoding with the aid of CRC.
Fig. 2.4.3.3 Decompression performances ofdifferent EtC schemes.

- 30 -

Figure 2.4.3.3shows the decompression error probabilities of conventional and proposed EtC
schemes for different entropy of packets. As clear, the proposed method (CA-Polar&SCL) with
the number of lists 𝐿𝐿 = 16 achieves the lower decompression error probability than the other
EtC methods.
Figure 2.4.3.4 illustrates the relationshipbetween the given entropy and the average
consumed energy. In the figure, “Individual”
aggregation and EtC, “Aggregation&EtC(Rate-fixed)” is the case using the packet
aggregation and EtC with the conventional
method with the half compression rate, and“Aggregation&EtC(Rate-Compatible)”shows the proposed approach with 𝐿𝐿 = 16.
When the error free decompression isassumed as 𝑃𝑃EF = 10−2 , the proposed
method exhibits the lower energy
consumption
per packet at any given entropy
Figure 2.3.4.4: Energy consumption
comparedtoallother methods.
with different EtC schemes[A 10-MHz-Band Bidirectional Wireless Power Transfer System with Zero-Threshold Si
MOSFETs]（Ishikawa Lab. ）A bidirectional wireless power transfer system via magnetic coupling has been developed at
10-MHz band by using high-efficiency DC-to-RF/ RF-to-DC power conversion modules andmatched transmitter (Tx) and receiver (Rx) coils. The power conversion module is designed
based on an operation similarity between transistor amplifier and rectifier, so it operates as
an amplifier for converting a power from DC to RF and also operates as a rectifier for
converting one from RF to DC. The module has same drain-side circuit with a harmonic
reactive termination to obtain higher efficiency, and the gate-side circuit was adjusted tomaintain the high-efficiency operations for both DC-to-RF/ RF-to-DC operations. In addition,by using a zero-threshold voltage transistor, a gate bias supply is not required. As the Tx andRx coils are matched, they can transfer RF power bidirectionally with high efficiency. The
constructed system with an RF frequency of 10 MHz achieved a maximum DC-DC conversion
efficiency of 43% at a wireless distance of 3 to 6 mm (Fig. 2.3.4.5).

Fig. 2.3.4.5

Fabricated bidirectional wireless power transfer system, and its characteristic【Grants-in-Aid for Scientific Research】
1. Grant-in-Aid for Scientific Research (C), “Microwave rectifiers for flexible wireless powertransfer system in emergency” (R. Ishikawa)- 31 -

In today's society, mobile communication has become an indispensable infrastructure, and it
is important to ensure the continuous availability of services even in the event of a disastersuch as a major earthquake. A base station is a critical communication link equipment that
communicates directly with mobile terminals. However, when a disaster strikes and a basestation is damaged, the terminals cannot be used in the cell area of the base station. In orderto solve this problem, the use of aerial base stations is attracting attention as a temporary
alternative. Unmanned aerial vehicles (UAVs) are being considered as aerial base stations.
In particular, the use of drones is one of the most versatile options. However, as conventional
drones are powered by batteries, their flight time is limited, making it difficult to operatethem continuously as aerial base stations. For this reason, the use of long wires from a groundpower supply is considered. Drones with wired power supply using metal cables have alreadybeen commercialized. However, there are concerns about hazards and damage from electric
shock and lightning strikes. In contrast, we have proposed optically powered drone for aerialbase stations driven by power-over-fiber (PWoF), and reported the flight demonstration of an
entry-type drone and data and control signal transmission performance of the system, notincluding the flight demonstration.
In this year, we increased the feed light power of PWoF, and investigate the current andvoltage characteristics of DC-DC converters (DDCs). By using the optimized DDC and a
specially customized photovoltaic power converter (PPC), we reported a flight demonstrationof a drone that is much larger than that of our previous work.

Fig.2.3.4.6 (Left) Conversion efficiency of three DDCs for various currents. (Right) (a)Experimental setup. (b) photo of flight demonstration and basic specification of drone. MMF:
Multimode fiber, DDC: DC-DC converter.

The left side of Fig. 2.3.4.6 shows the DC-DC conversion efficiencies of three commerciallyavailable DDCs for various currents. In this measurement, the voltage was set to 3.7 V, which
was optimal for driving the drone. As shown in the left side of Fig. 2.3.4.6 DDC-A had thehighest DC-DC conversion efficiency at all currents. Thus, DDC-A was used in the following
flight demonstration.
We conducted flight experiment using the DDC-A and the commercially available drone.
The experimental setup is shown in the right side (a) of Fig. 2.3.4.6 To obtain higher electric
power, we used a specially customized GaAs-based PPC based on the vertical epitaxial
monolithic heterostructure architecture design. The device provides higher capability both of
O/E conversion efficiency and available input optical power than those of conventional PPCs.
The insertion loss of the 100 m multimode fiber (MMF) was 1.2 dB. The power injected into
the PPC and the O/E conversion efficiency were 25 W and 56%, respectively. To drive thedrone, the PPC output voltage of 6.4 V was converted into 3.7 V by the DDC-A. It should be
noted that the PPC and DDC could not be loaded on the drone, and only the drone itself was
flown. The right side (b) of Fig. 2.x.2 shows the photo of the flight demonstration and the- 32 -

specification of the drone we used. By in-creasing the feed light power with the PPC and
DDC-A, we successfully achieved a flight demonstration of the drone that is over 11 times
heavier and 36 times larger than that of our previous work.
2.4.3 Major Research Outcomes in 2021
[Successive Interference Cancellation Among Multiple LPWA Systems]（Fujii Lab.）
Nowadays, with the rapid development of Internet of Things (IoT), the number of low power wide area
(LPWA) nodes that can communicate over long distances with low power has been increasing rapidly.
Additionally, according to the IoT applications, multiple LPWA systems with different communication
methods have been developed (e.g., long range wide area network (LoRaWAN), wireless smart utility
network (Wi-SUN)). Because these systems are allocated to the same 920 [MHz] band and gateway (GW)of an arbitral system cannot demodulate signals of the other systems, inter-system interferences have beena crucial issue in addition to intra-system interferences. For the intra-system interferences, successiveinterference cancellation (SIC) for LoRaWAN has been proposed. In the SIC process, first, the long range(LoRa) GW accumulates the received signals. Then, the GW demodulates the signals in descending orderof the received power. After that, the GW modulates the obtained data again and decreases the modulated
signal from the accumulated signals. Finally, the GW demodulates the accumulated signals sequentially,
which enhances the demodulation quality of LoRa signals. However, in this method, the inter-systeminterferences have not been considered, which may deteriorate the demodulation quality of LoRa signals
remarkably because the LoRa GW cannot demodulate and decrease the signals of the other systems. Thus,
we propose the SIC among multiple LPWA systems. Fig. 2.3.4.7 shows our system model. In our research,
it is assumed that the LoRa and Wi-SUN signals arrive at the GW. Additionally, the GW has a modulator
and demodulator of LoRa and Wi-SUN, respectively, and the SIC function. Furthermore, the GW canexchange the accumulated signals among systems’ modulator/demodulator. From the above, we evaluate
packet error rate (PER) for LoRa received power-to-Wi-SUN received power ratio when these two signals
interfere at the same time, as shown in Fig. 2.3.4.8. From Fig.2.3.4.8, it is confirmed that the PER of eachsignal is poor according to the increase of the received power radio because of capture effect when the GW
does not execute the SIC algorism (c.f., black line). Meanwhile, with the SIC algorism, it is shown that the
PER of each signal can achieve 0.0 [%] regardless of the receive power ratio (c.f., red line). This result isowing to spectrum spread of LoRa which the GW can demodulate the LoRa signals even if the received
power ratio is less, besides the large received power ratio.

Fig. 2.3.4.7 Channel allocation based on the
ECDF of the time occupancy of other systems.

Fig. 2.3.4.8 Average PLR of LoRa nodes forthe number of other system nodes.

[Packet Transmission Considering Duty-cycle Based on Packet-Level Index Modulation for
LoRaWAN] (Fujii Lab.)In LoRa transmission system, the transmittable time of each channel is limited by duty cycle (DC). To
increase the amount of data can be transmitted under this constraint, packet-level index modulation (PLIM)
has been proposed. PLIM assigns a channel index (CI) and a time slot index (TSI) to the frequency channel
and the divided time slot, respectively. The time slot and channel for transmitting packet is selected basedon the transmitted data sequence. This allows additional information to be transmitted by CI and TSI.
However, if the transmitted bit string is biased, the selected transmission channel will also be biased, thus
reducing the amount of data that can be transmitted compared to conventional LoRa transmission due tothe DC constraints described above. This study proposes an adaptive CI exchange method when the- 33 -

occurred CI is biased.
Fig. 2.3.4.9 shows the system model for this simulation. In this study, each terminal sends packets
using PLIM and makes CI exchange decisions at regular intervals based on the recorded channel
history. The CI exchange is decided by predicting the transmission time ratio of each channel basedon the packet transmission channel history. The predicted values of each channel are compared, and if
the maximum difference among all channel pairs exceeds a threshold value, CI exchange is performedon that channel pair. To evaluate the performance of the proposed method, computer simulations were
executed using the C language. The ratio of transmission time per channel with conventional PLIM
and with the proposed method are shown in Figs.2.3.4.10 and 2.3.4.11, respectively. Simulation results
confirm that intensive selection of specific channels can be reduced.

Fig. 2.3.4.10 System modelFig. 2.4.3.10 Transmission time percentagetransition of each channel with conventional
PLIM.

Fig. 2.3.4.11 Transmission time percentagetransition of each channel with proposed method.

【Cooperative Research】
1. MIC SCOPE Phase I “Ultra Wide Area and Interference Tolerance Sub-GHz WirelessSensor Network on Mixed Environment of Multiple Systems” Takeo Fujii- 34 -

３．令和３年度

外部発表リスト

著書
査読付き一般論文【1】 T. Hara, H. Iimori, and K. Ishibashi, “Hyperparameter-Free Receiver for Grant-Free
NOMA Systems With MIMO-OFDM,” IEEE Wireless Commun. Lett., vol. 10, no. 4,
pp. 810-814, Apr. 2021.
【2】 M. Matsuura, H. Nomoto, H. Mamiya, T. Higuchi, D. Masson, and S. Fafard, “Over40-W electric power and optical data transmission using an optical fiber,” IEEE Trans.
Power Electronics, vol. 36, no. 4, pp. 4532-4539, Apr. 2021.
【3】 Hendrik Lumbantoruan and Koichi Adachi, “Array Antenna Equipped UAV-BS for
Efficient Low Power WSN and Its Theoretical Analysis,” IET Commun., pp. 1-14, Apr.
2021.
【4】 Luong Duy Manh, Phan Thi Bich, Nguyen Thuy Linh, Nguyen Huy Hoang, Tran
Xuan Nam, and Koichiro Ishibashi, “A Concurrent Triple-band RF Energy Harvesting
Circuit for IoT Sensor Networks”, IEIE Trans. Smart Process. Comput., vol. 10, no, 2,
pp. 151-159, Apr. 2021.
【5】 H. Iimori, G. T. F. De Abreu, O. Taghizadeh, R. -A. Stoica, T. Hara, and K. Ishibashi,“A Stochastic Gradient Descent Approach for Hybrid MmWave Beamforming with
Blockage and CSI-Error Robustness,” IEEE Access, vol. 9, pp. 74471-74487, May
2021.
【6】 Yuki Iwata, Han Trong Thanh, Guanghao Sun and Koichiro Ishibashi, “High Accuracy
Heartbeat Detection from CW-Doppler Radar Using Singular Value Decomposition
and Matched Filter,” Sensors, vol. 21, no. 11, pp. 3588, May 2021.
【7】 Thanh Han Trong, Yen Pham Huong, Lam Nguyen Dang Son, Yuki Iwata, Tuan Do
Trong, Koichiro Ishibashi, and Guanghao Sun, “Machine Learning based
Classification Model for Screening of Infected Patients Using Vital Signs,”
Informatics in Medicine Unlocked, vol. 24, pp. 1-11, May 2021.
【8】 T. Hara, R. Takahashi, and K. Ishibashi, “Ambient OFDM Pilot-Aided Backscatter
Communications: Concept and Design,” IEEE Access, vol. 9, pp. 89210-89221, Jun.
2021.
【9】 Aoto Kaburaki, Koichi Adachi, Osamu Takyu, Mai Ohta, and Takeo Fujii,“Autonomous Decentralized Traffic Control Using Q-learning in LPWAN,” IEEE
Access, vol. 9, pp. 93651-93661, Jun. 2021.
【10】 Katsuya Suto, Shinsuke Bannai, Koya Sato, Kei Inage, Koichi Adachi, and Takeo
Fujii, “Image-Driven Spatial Interpolation with Deep Learning for Radio Map
Construction,” IEEE Wireless Commun. Lett., vol. 10, no. 6, pp. 1222-1226, Jun.
2021.

- 35 -

【11】 Kei Sakaguchi, Ryuichi Fukatsu, Tao Yu, Eisuke Fukuda, Kim Mahler, Robert Heath,
Takeo Fujii, Kazuaki Takahashi, Alexey Khoryaev, Satoshi Nagata, and Takayuki
Shimizu, “Towards mmWave V2X in 5G and beyond to support automated driving,”
IEICE Trans. Commun., vol.E104-B, no.6, pp.587-603, Jun. 2021. (Invited Paper)【12】 K. Ando, H. Iimori, T. Takahashi, K. Ishibashi, and G. T. F. de Abreu, “Uplink Signal
Detection for Scalable Cell-Free Massive MIMO Systems with Robustness toRate-Limited Fronthaul,” IEEE Access, vol. 9, pp. 102770-102782, Jul. 2021.
【13】 Jose-Victor
Rodriguez,
Maria-Teresa
Martinez
Ingles,Jose-Maria
Molina-Garcia-Pardo, Leandro Juan-Llacer, Takeo Fujii, and Ignacio
Rodriguez-Rodriguez, “UTD-PO formulation for the analysis of multiple-plateau
diffraction when considering illumination from a Low Source,” IEEE Trans. Antennas
Propag., vol. 69, no. 7, pp. 4241-4245, Jul. 2021.
【14】 M. Matsuura, “Recent advancement in power-over-fiber technologies,” Photonics, vol.
8, no. 8, photonics8080335, Aug. 2021.
【15】 Marco Sarmiento, Khai-Duy Nguyen, Ckristian Duran, Trong-Thuc Hoang, Ronaldo
Serrano, Van-Phuc Hoang, Xuan-Tu Tran, Koichiro Ishibashi, and Cong-Kha Pham,“A Sub-µ W Reversed-Body-Bias 8-bit Processor on 65-nm Silicon-on-Thin-Box(SOTB) for IoT Applications,” IEEE Trans. Circuits Syst. II: Express Br., vol. 68, no.
9, pp. 3182-3186, Sept. 2021.
【16】 小野哲, 今井勇太, 和田光司, “品質工学に基づいた 2 GHz 帯ローパスフィルタの 2 段階設計および許容差設計,” 信学論（A）, vol. J104-A, no. 9, pp. 204-213,
Sept. 2021.
【17】 Keita Katagiri, Koya Sato, Kei Inage, and Takeo Fujii, “Dynamic radio map using
statistical hypothesis testing,” IEEE Trans. Cogn. Commun. Netw., vol. 7, no. 3, pp.
752-766, Sept. 2021.
【18】 Yoji Uesugi, Keita Katagiri, Koya Sato, Kei Inage, and Takeo Fujii, “Clustering for
Signal Power Distribution Toward Low Storage Crowdsourced Spectrum Database,”
IEICE Trans. Commun., vol. E104-B, no. 10, pp. 1237-1248, Oct. 2021.
【19】 Arata Takahashi, Fumihito Sasamori, Shiro Handa, Osamu Takyu, Takeo Fujii, andTomoaki Ohtsuki, “Overloaded wireless MIMO switching for secure wirelesscommunication exchanging to untrusted relay,” IEEE Trans. Commun., vol. E104-B,
no. 10, pp. 1249-1259, Oct. 2021.
【20】 Tomohiro Tsukushi, Satoshi Ono, and Koji Wada, “Realization of Rectangular
Frequency Characteristics by the Effects of a Low-Noise Amplifier and Flat Passband
Bandpass Filter,” IEICE Electronics Express, E104-C/10, Oct. 2021.
【21】 Kazuhiro Watanabe, Takayuki Inaba, and Manabu Akita, “A study on coherently
combining sparse-multiband processing,” IEICE Commun. Express, vol. 10, no. 11, pp.
858-863, Nov. 2021.

- 36 -

【22】 Riku Yamabe, Mikihiko Nishiara, Osamu Takyu, and Koichi Adachi, “Achievable
Rate Enhancement based on Multi-packet Indexing in Packet-Level Index
Modulation,” IEEE Access, pp.1-9, Nov. 2021.
【23】 H. Iimori, T. Takahashi, K. Ishibashi, G. T. F. de Abreu, and W. Yu, “Grant-Free
Access via Bilinear Inference for Cell-Free MIMO With Low-Coherence Pilots,”
IEEE Trans. Wireless Commun., vol. 20, no. 11, pp. 7694-7710, Nov. 2021.
【24】 A. S. Guerreiro, H. Iimori, and K. Ishibashi, “Low Latency Beam-Sweeping forMillimeter Wave Systems via Pessimistic Optimization,” IEEE Wireless Commun.
Lett., vol. 10, no. 12, pp. 2742-2746, Dec. 2021.
【25】 Haruka Ogikubo, Satoshi Ono, and Koji Wada, “Tunable diplexer composed ofasymmetric hairpin resonators using varactors with constant passband bandwidth andhigh isolation characteristics,” J. Japan Inst. Electron. Packag., vol.14, pp.
E20-012-1-E20-012-11, Dec. 2021.
【26】 Taro Matsumura, Satoshi Ono, and Koji Wada, “Compact dual-band BPF composed of
LC J-inverters using lumped elements,” J. Japan Inst. Electron. Packag., vol. 14, pp.
E20-014-1-E20-014-10, Dec. 2021.
【27】 Ryo Ishikawa, Yoichiro Takayama, and Kazuhiko Honjo, “Doherty amplifier design
based on asymmetric configuration scheme,” IEICE Trans. Electron., vol. E104-C, no.
10, pp. 496–505, Dec. 2021. (Invited)【28】 Duc-Tho Mai and Koichiro Ishibashi, “Small-Scale Depthwise Separable
Convolutional Neural Networks for Bacteria Classification,” Electronics, vol. 10, no.
23, pp. 3005, Dec. 2021.
【29】 久米鳳春, 本城和彦, 石川亮, “零しきい値 Si MOS FET を用いた 10 MHz 帯双方
向無線給電システム,” 進学論（C）, vol. J105-C, no. 01, pp. 28–36, 2022 年 1 月.
【30】 稲葉敬之, 秋田学, “背景クラッタ中の cm 級小物体検知における多周波ステッ
プレーダのパラメータスタディと評価”，信学論（D）, vol. 142, no. 1, pp58-66,
2022 年 1 月．
【31】 Duc-Tho Mai and Koichiro Ishibashi, “ Bacteria Shape Recognition with the
Kotobuki's model,” 生体医工学, 59 巻, pp. 859, 2021 年.
査読付き国際会議プロシーディングス等【1】 Shota Ishiguro, Jiro Ida, Takayuki Mori, and Koichiro Ishibashi, “Transfer
Characteristics of CMOS Inverter using Steep SS PN-Body Tied SOI-FET,” in Proc.
2021 Int. Symp. VLSI Technol. Syst. Appl. (VLSI-TSA 2021), Taipei, Taiwan, Apr.
2021.
【2】 Hiroki Itoh, Jiro Ida, Takayuki Mori, and Koichiro Ishibashi, “Analysis of Drain
Current Enhancement in "PN-Body Tied SOI-FET" -Bulk vs Surface Conduction
Mode and Low Vds Saturation Effect-,” in Proc. 2021 Int. Symp. VLSI Technol. Syst.

- 37 -

Appl. (VLSI-TSA 2021), Taipei, Taiwan, Apr. 2021.
【3】 Muying Chen, Koichi Adachi, Osamu Takyu, Mai Ohta, Takeo Fujii, “Transmission
Timing Control Using ACK Signal in LoRaWAN,” in Proc. IEEE Wirel. Commun.
Netw. Conf. (WCNC 2021), pp. 1-5, Online, Apr. 2021.
【4】 Haesik Kim, Takeo Fujii, and Kenta Umebayashi, “Relay Nodes Selection Using
Reinforcement Learning,” in Proc. Int. Conf. Artif. Intell. Inf. Commun. (ICAIIC
2021), Online, April 2021.
【5】 T. Kobatake, N. Shindo, and M. Matsuura, “Simultaneous fiber transmission ofcontrol and mobile communication signals in power-over-fiber drones for airborne
base stations,” in Proc. The 3rd Optical Wireless and Fiber Power Transmission
Conference (OWPT 2021), OWPT-P-02, Online, Apr. 2021.
【6】 S. Fujita, T. Higuchi, H. Mamiya, and M. Matsuura, “Evaluation of wavelength
dependence in feed light transmission loss of double-clad fiber for power-over-fiber
applications,” in Proc. The 3rd Optical Wireless and Fiber Power Transmission
Conference (OWPT 2021), OWPT-P-03, Online, Apr. 2021.
【7】 R. Katori, W. Rui, and M. Matsuura, “Frequency chirp measurement method using aprobe light and bandpass filter,” in Proc. 26th OptoElectron. Commun. Conf. (OECC2021), S3D.4, Online, Jul. 2021.
【8】 M. Sagara, W. Rui, J. Tsuda, and M. Matsuura, “Frequency comb assisted photonic
digital-to-analog conversion based on frequency chirp in a QD-SOA,” in Proc. 26th
OptoElectron. Commun. Conf. (OECC 2021), W2F.4, Online, Jul. 2021.
【9】 Gaku Kobayashi, Osamu Takyu, Koichi Adachi, Mai Ohta, and Takeo Fujii, “Proposalof Interference Power Occupancy Estimation Method Using Chirp Demodulation,” inProc. Int. Conf. Ubiquitous Future Netw. (ICUFN 2021), Online, Aug. 2021.
【10】 Keita Katagiri and Takeo Fujii, “Mesh-clustering-based radio maps construction forautonomous distributed networks,” in Proc. Int. Conf. Ubiquitous Future Netw.
(ICUFN 2021), Online, Aug. 2021.
【11】 Hirofumi Nakajo and Takeo Fujii, “Local 5G mmWave Signal Measurement andAnalysis for Spectrum Database,” in Proc. Int. Conf. Ubiquitous Future Netw.
(ICUFN 2021), Online, Aug. 2021.
【12】 Shinichiro Kakuda, Yudai Yamazaki, Keita Katagiri, Takeo Fujii, Osamu Takyu, Mai
Ohta, Koichi Adachi, “Channel allocation for LoRaWAN considering intra-system andinter-system interferences,” in Proc. IEEE 94th Veh. Technol. Conf. (VTC2021-Fall),Online, pp. 1–7, Sept. 2021,【13】 Ying Gao and Takeo Fujii, “Improvement of Radio Environment Map under Data
Falsification Attack,” in Proc. IEEE 94th Veh. Technol. Conf. (VTC2021-Fall), Online,
pp. 1-5, Sept. 2021.
【14】 Ronaldo Serrano, Marco Sarmiento, Ckristian Duran, Khai-Duy Nguyen,
Trong-Thuc Hoang, Koichiro Ishibashi, and Cong-Kha Pham, “A Low-Power- 38 -

Low-Area SoC based in RISC-V Processor for IoT Applications,” in Proc. 18th Int.
SoC Des. Conf. (ISOCC 2021), Jeju Island, Republic of Korea, Oct. 2021.
【15】 Duc-Tho Mai and Koichiro Ishibashi, “Bacteria Shape Classification using
Small-Scale Depthwise Separable CNNs,” in Proc. IEEE Eng. Med. Biol. Soc. 2021
(IEEE EMBC 2021), Nov. 2021
【16】 Masayuki Ono, Jiro Ida, Takayuki Mori, and Koichiro Ishibashi, “Developing
Ultralow Trun-on Voltage Diode by Steep Slope PN-Body Tied SOI-FET,” in Proc.
The 2021 International Meeting for Future of Electron Devices, Kansai (IEEE
IMFEDK 2021), Nov. 2021.
【17】 Mitsuhiro Yuizono, Jiro Ida, Takayuki Mori, and Koichiro Ishibashi, “RF Evaluationof Steep Subthreshold Slope PN-Body Tied SOI-FET,” in Proc. The 2021
International Meeting for Future of Electron Devices, Kansai (IEEE IMFEDK 2021),
Nov. 2021.
【18】 Ryo Ishikawa, Yoichiro Takayama, and Kazuhiko Honjo, “A 4.5-GHz-band miniature
outphasing GaN HEMT MMIC power amplifier,” in Proc. 2021 Asia-PacificMicrowave Conference, pp. 106-108, Brisbane, Australia (Virtual), Nov. 2021.
【19】 Keita Katagiri, Koya Sato, and Takeo Fujii, “Empirical CDF-based power control
method for obstructed V2V communications,” in Proc. Int. Conf. on Emerging
Technologies for Commun. (ICETC2021), Online, Dec. 2021.
【20】 Keita Katagiri, Koya Sato, and Takeo Fujii, “Estimation of the Number of Obstacles
Based on p-value for V2V Communications,” in Proc. Int. Conf. on Emerging
Technologies for Commun. (ICETC2021), Online, Dec. 2021.
【21】 Gaku Kobayashi, Osamu Takyu, Koichi Adachi, Mai Ohta, and Takeo Fujii,“Estimation Accuracy to Channel Occupancy Ratio and Signal Power under
Co-Channel Interference in LoRa,” in Proc. 2021 Int. Conf. on Emerging
Technologies for Commun. (ICETC2021), Dec. 2021.
【22】 Keita Katagiri, Koya Sato, and Takeo Fujii, “Estimation of the Number of Obstacles
Based on p-value for V2V Communications,” in Proc. 2021 Int. Conf. on Emerging
Technologies for Commun. (ICETC2021), Online, Dec. 2021.
【23】 Mai Ohta and Takeo Fujii, “Intra-System Interference Avoidance for Packet-Level
Index Modulation in Internet of Things,” in Proc. Asia-Pac. Signal Inf. Process. Assoc.
Annu. Summit Conf. (APSIPA-ASC 2021), Tokyo, Japan, Dec. 2021.
【24】 Naotaka Hirayama, Takuya Kobayashi, and Koichi Adachi, “Offloading Selection
with Unequal Timeslot in Mobile Edge Computing,” in Proc. Asia-Pac. Signal Inf.
Process. Assoc. Annu. Summit Conf. (APSIPA-ASC 2021), pp. 1963-1968, Dec. 2021.
【25】 Keita Katagiri and Takeo Fujii, “Low storage radio map using statistical inference,”in Proc. IEEE Int. Symp. Dyn. Spectr. Access Netw. (DySPAN2021), Online, Dec.
2021.

- 39 -

【26】 Shougo Matsuo, Sunao Miyamoto, Keita Katagiri, and Takeo Fujii, “Radio
Propagation Extrapolation by Using Multiple Separated Propagation Paths Estimatedby Radio Map,” in Proc. Int. Conf. Inf. Netw. (ICOIN 2022), Online, Jan. 2022.
【27】 Keita Katagiri and Takeo Fujii, “Partitioned Path Loss Models Based on Coefficientof Determination,” in Proc. Int. Conf. Inf. Netw. (ICOIN 2022), Online, Jan. 2022.
【28】 Keita Katagiri and Takeo Fujii, “Classification and discretization of shadowing
toward low storage radio map,” in Proc. Int. Conf. Artif. Intell. Inf. Commun. (ICAIIC
2022), online, Feb. 2022.
【29】 Satoshi Nakaniida and Takeo Fujii, “Throughput prediction by radio environment
correlation recognition using crowd sensing and federated learning,” in Proc. Int. Conf.
Artif. Intell. Inf. Commun. (ICAIIC 2022), online, Feb. 2022.

国際会議招待講演【1】 Koichiro Ishibashi, “T Beat Sensors for monitoring CO2 to detect luck of ventilationin Covid-19 environment,” NICT ASEAN IVO Workshop, Hanoi, Vietnam (Online),
Aug. 2021.
【2】 M. Matsuura, “Power-over-fiber for radio-over-fiber links,” Eur. Conf. Opt. Commun.
ECOC (ECOC 2021), We4B.1, Bordeaux, France, Sept. 2021.

国内会議招待講演【1】 Koichiro Ishibashi, “Infection Diseases Screening System by Contactless
Radar and Machine Learning AI,” JST 日台研究交流「AI システム構成に資するナノエレクトロニクス技術」ワークショップ, オンライン開催, 2021 年 4月.
【2】 松浦基晴, “通信と大電力伝送を可能にする光ファイバ給電技術とその応用,”
電子情報通信学会ポリマー光部品技術特別研究専門委員会研究会, オンライン開催, 2021 年 6 月.
【3】 石橋功至, 内村颯汰, 家 哲也, 藤井義巳, 村上隆秀, 新保宏之, “［招待講演］確率的遮蔽を伴うミリ波通信のためのロバスト連携多値点伝送の研究開発,” 信
学技報, vol. 121, no. 345, SR2021-60, pp. 11-11, 2022 年 1 月.
【4】 小野哲, 和田光司, “チップキャパシタ結合型共有共振器を用いた小型ダイプレ
クサの検討,” 信学技報, vol. 121, no. 361, MW2021-107, pp. 16-21, オンライン開催, 2022 年 1 月.
【5】 松浦基晴, “無線基地局のための光ファイバ無線・電力伝送,” 信学総大, CI-6-4,
オンライン開催, 2022 年 3 月.

- 40 -

解説・評論【1】 藤井威生, “共創進化スマート社会を支える無線通信技術を目指して,” 電波技術協会報, no. 241, pp. 6-9, 2021 年 7 月.
【2】 石橋功至, “Beyond 5G/6G に向けた無線アクセス網の研究開発最前線 〜多様な
通信品質要求に高信頼に応えるミリ波通信の実現〜,” 電波技術協会報 FORN,
no. 341, pp. 10-13, 2021 年 7 月.
【3】 安達宏一, 横川慎二, “Society 5.0 の基盤となるデータ収集・分析・利活用,” 電波技術協会報 FORN, no. 341, 2021 年 7 月.
【4】 松浦基晴, “将来のモバイル通信のための 光ファイバ無線伝送・給電技術 〜光ネットワークで電波を運び、無線基地局を駆動する〜,” 電波技術協会報FORN, 2021 年 7 月.
【5】 石橋功至, “環境発電を用いた無線通信設計,” 電子情報通信学会 基礎・境界ソ
サイエティ Fundamentals Review, no. 15, vol. 1, pp. 16-24, 2021 年 7 月.
【6】 佐藤光哉, 藤井威生, 須藤克弥, “電波環境の可視化,” 電子情報通信学会誌, vol.
104, no. 12, pp. 1234-1238, 2021 年 12 月.
学会口頭発表【1】 片桐啓太, 藤井威生, “推計統計学的手法に基づく平均受信電力推定のための統計化サンプルサイズ決定法,” 信学技報, vol.121, no.30, SR2021-3, pp. 16-23, May
2021.
【2】 角田真一朗, 山崎悠大, 片桐啓太, 藤井威生, 田久修, 太田真衣, 安達宏一, “システム内外干渉を考慮した LoRaWAN 向けチャネル割当手法の検討,” 信学技報, vol.121, no.30, SR2021-12, pp.79-85, 2021 年 5 月.
【3】 梅林健太, 岩田大輝, 中條宏郁, 川崎耀, 馬場園勇作, 八尋義範, 藤井威生, 安達宏一, 松島大稀, 柴田祐輔, 井深和雄, 松村武, 児島史秀, “[技術展示] スマ
ートスペクトラムに基づいた 5G 無線ネットワークの実証実験,” 信学技報,
vol.121, no.30, SR2021-18, pp.120-127, 2021 年 5 月.
【4】 安藤研吾, 飯盛寛貴, 石橋功至, アブレウ ジュゼッペ, “全二重セルフリー
MIMO のためのテンソル信号処理を用いた送受信ビームフォーミング設計法,”
信学技報, vol. 121, no. 72, RCS2021-72, pp. 249-254, 2021 年 6 月.
【5】 原郁紀, 石橋功至, “グラントフリー非直交多元接続のための伝播路の事前情報
不 要 な 複 数 観 測 値 近 似 メ ッ セ ー ジ 伝 播 法 ,” 信 学 技 報 , vol. 121, no. 72,
RCS2021-71, pp. 243-248, 2021 年 6 月.
【6】 稲葉敬之, 谷口匠, “静止軌道周辺スペースデブリ検出のための線分積分法の提案,” 信学技報, vol. 121, no. 78, SANE2021-13, pp. 23-28, 2021 年 6 月.
【7】 松尾祥吾, 宮本直, 片桐啓太, 藤井威生, “伝搬路上の異なる送信機を用いた間接的電波伝搬外挿手法の検討,” 第 655 回 URSI-F 会合, 2021 年 6 月.

- 41 -

【8】 靏見康平, 蕪木碧仁，安達宏一, 田久修, 太田真衣, 藤井威生, “パケット型イン
デックス変調におけるクロックドリフトの推定法および補償法,” 信学技報,
vol. 121, no. 103, RCS2021-87, pp. 48-54, 2021 年 7 月.
【9】 蕪木碧仁, 安達宏一, 田久修, 太田真衣, 藤井威生, “LoRaWAN における機械学習を用いた自律分散型パケット送信制御法,” 信学技報, vol. 121, no. 103,
RCS2021-96, pp. 92-97, 2021 年 7 月.
【10】 サイトウ ゲレイロ アンドレ, 飯盛寛貴, 石橋功至, “ミリ波帯における低遅延サブアレイ型ビーム掃引方式,” 信学技報, vol. 121, no. 153, RCS2021-117, pp.
97-102, 2021 年 8 月.
【11】 内村颯汰, 飯盛寛貴, アブレウ ジュゼッペ, 石橋功至, “ミリ波通信路における確率的遮蔽を考慮した低演算量ロバストビームフォーミング設計に関する一検討,” 信学技報, vol. 121, no. 153, RCS2021-116, pp. 91-96, 2021 年 8 月.
【12】 福榮秀都, 飯盛寛貴, アブレウ ジュゼッペ, 石橋功至, “ダイナミック TDD を用いたセルフリー大規模 MIMO のためのユーザの公平性を考慮したリソース
割当及びビームフォーミング設計に関する一検討,” 信学技報, vol. 121, no. 153,
RCS2021-115, pp. 85-90, 2021 年 8 月.
【13】 安藤研吾, 飯盛寛貴, アブレウ ジュゼッペ, 高橋拓海, 石橋功至, “容量制約付きフロントホールを用いたスケーラブルセルフリー大規模 MIMO のためのアンテナ構成及び受信機設計,” 信学技報, vol. 121, no. 153, RCS2021-114, pp.
79-84, 2021 年 8 月.
【14】 小林拓弥, 安達宏一, “Wireless Powered-MEC における自律分散的なオフロー
ド確立決定法の検討,” 信学技報, vol. 121, no. 103, RCS2021-110, pp. 57-62, 2021
年 8 月.
【15】 Shuntaro Saku and Koichiro Ishibashi, “PV and RF Hybrid Energy HarvestingPower Supply,” NICT ASEAN IVO Workshop, Hanoi, 2021 年 8 月.
【16】 チャルーンスック ブンパシット, 安達宏一, “干渉分布に基づく事前空き周波数割り当て法,” 信学技報, vol. 121, no. 103, RCS2021-111, pp. 63-68, 2021 年 8 月.
【17】 菊池晴貴, 斉藤昭, 和田渉, 鈴木博, 本城和彦, 石川亮, “OAM 通信用集積ルー
プアンテナアレイのバラン整合による性能改善,” 信学ソ大, B-1-53, 2021 年 9月.
【18】 斉藤昭, 石川亮, 本城和彦, “θ/φ 方向電流を有する球面アレイの生成する電磁界の固有モード展開,” 信学ソ大, B-1-75, 2021 年 9 月.
【19】 熊田遼汰, 安達宏一, “UAV による位置推定及び推定位置に基づくアレイアン
テナによる干渉低減に関する検討,” 信学ソ大, B-5-76, 2021 年 9 月.
【20】 鈴木康介, 安達宏一, “パケット型インデックス変調における適応的ビットマ
ッピング手法の検討,” 信学ソ大, B-5-77, 2021 年 9 月.
【21】 内田悠斗, 片桐啓太, 藤井威生, “一次ユーザおよび二次ユーザの無線環境情報を用いた周波数共用手法の検討,” 信学ソ大, B-17-5, 2021 年 9 月.

- 42 -

【22】 片桐啓太, 藤井威生, “メッシュクラスタリングに基づく自律分散環境向け電波マップ構築,” 信学ソ大, B-17-7, 2021 年 9 月.
【23】 宮本椋生, 成枝秀介, 藤井威生, 成瀬央, “建造物付近における RSSI Kriging 補間値の特性,” 信学ソ大, B-17-10, 2021 年 9 月.
【24】 石橋功至, “（依頼講演）多数同時接続・低遅延を実現するグラントフリー
NOMA,” 信学ソ大, BT-3-8, 2021 年 9 月.
【25】 石川亮, 高山洋一郎, 本城和彦, “集中定数素子 4.5 GHz 帯 GaN HEMT MMIC
アウトフェージング増幅器,” 信学ソ大, C-2-4, 2021 年 9 月.
【26】 小野哲, 和田光司, “チップキャパシタ結合型共有共振器を用いた広い離調幅を持つ小型ダイプレクサの検討,” 信学ソ大, C-2-34, 2021 年 9 月.
【27】 宮腰就也, 小野哲, 和田光司, “小型 3 段マイクロストリップ線路 BPF の設計・試作と高精度モデリングに関する一検討,” 信学ソ大, C-2-35, 2021 年 9 月.
【28】 成田剛, 小野哲, 和田光司, “ストリップ線路構造によるブロードサイド及びオフセット結合線路を用いた 3 セクション型 90 度ハイブリッドの設計手法に関する検討,” 信学技報, vol. 121, no. 187, MW2021-61, pp. 106-111, 2021 年 10 月.
【29】 伊藤雅秋, 菅野一生, 山崎浩輔, 安藤研吾, 福榮秀都, 飯盛寛貴, 石橋功至,“バックホール伝送容量制約を考慮した複数中央処理局を用いたスケーラブル
セルフリー大規模 MIMO システムの性能評価,” 信学技報, vol. 121, no. 210,
RCS2021-119, pp. 7-12, 2021 年 10 月.
【30】 安藤研吾, 飯盛寛貴, アブレウ ジュゼッペ, 石橋功至, “セルフリー大規模
MIMO のためのビームフォーミング設計と機密保持容量に対する一検討,” 信
学技報, vol. 121, no. 210, RCS2021-120, pp. 13-18, 2021 年 10 月.
【31】 福榮秀都, 飯盛寛貴, アブレウ ジュゼッペ, 石橋功至, “ダイナミック TDD セ
ルフリー大規模 MIMO のための幾何平均最大化による資源割当およびビーム
フォーミング設計に関する一検討,” 信学技報, vol. 121, no. 210, RCS2021-121,
pp. 19-24, 2021 年 10 月.
【32】 高橋拓海, 飯盛寛貴, 安藤研吾, 石橋功至, 衣斐信介, アブレウ ジュゼッペ,“［ポスター講演］低分解能 ADC を用いたスケーラブルセルフリー大規模
MIMO のための通信路とデータの同時推定手法に関する一検討,” 信学技報,
vol. 121, no. 210, RCS2021-129, pp. 57-62, 2021 年 10 月.
【33】 内村颯汰, 飯盛寛貴, 石橋功至, 村上隆秀, 新保宏之, “複数基地局連携ビーム
フォーミングを用いたミリ波通信における遮蔽予測と通信性能のトレードオ
フに関する実験的検証,” 信学技報, vol. 121, no. 210, RCS2021-133, pp. 76-81,
2021 年 10 月.
【34】 大比良和哉, 石橋功至, “分数ドップラーが存在する二重選択性通信路のための二次元 OTFS インデックス変調の信号設計に関する研究,” 信学技報, vol. 121,
no. 210, RCS2021-135, pp. 88-93, 2021 年 10 月.
【35】 石井健二, 森洋二郎, 松浦基晴, 中川雅弘, “2020 年度 PN 研究会の開催報告- 43 -

～システム・アーキテクチャ・デバイスに関する研究について〜,” 信学技報,
vol. 120, no. 228, PN2020-24, pp. 7-12, オンライン開催, 2021 年 11 月
【36】 森洋二郎, 石井健二, 中川雅弘, 松浦基晴, “2020 年度 PN 研究会の開催報告～制御・管理・アプリケーションに関する研究について〜,” 信学技報, vol. 121,
no. 237, PN2021-26, pp. 1-6, オンライン開催, 2021 年 11 月
【37】 太田真衣, 藤井威生, “LPWA のための差動化 PLIM 方式,” 信学技報, vol. 121,
no. 227, SR2021-44, pp. 25-30, 2021 年 11 月.
【38】 成枝秀介, 藤井威生, “キャリアセンス付き LPWAN における悪条件下エンド
デバイス特性改善のための送信電力割当法とクラスタリング法,” 信学技報,
vol. 121, no. 227, SR2021-45, pp. 31-36, 2021 年 11 月.
【39】 中新井田覚志, 藤井威生, “クラウドセンシングと連合学習を用いた無線環境
相関認識によるスループット予測手法の研究,” 信学技報, vol. 121, no. 227,
SR2021-53, pp. 72-78, 2021 年 11 月.
【40】 片桐啓太, 藤井威生, “決定係数に基づく距離減衰特性の分割モデル化,” 信学
技報, vol. 121, no. 227, SR2021-54, pp. 79-84, 2021 年 11 月.
【41】 中新井田覚志, 藤井威生, “クラウドセンシングと連合学習を用いた無線環境
相関認識によるスループット予測手法の研究,” 超知性ネットワーキングに関する分野横断型研究会（RISING）, 2021 年 11 月.
【42】 伊藤弘樹, 稲毛契, 藤井威生, “スペクトラムデータベースに基づくスパース
性を利用した干渉推定手法,” 超知性ネットワーキングに関する分野横断型研究会（RISING）, 2021 年 11 月.
【43】 片桐啓太, 藤井威生, “シャドウイング成分の分類および離散化に基づく低容量電波マップ,” 超知性ネットワーキングに関する分野横断型研究会（RISING）,
2021 年 11 月.
【44】 谷津崚太, 石橋功至, 遠藤秀樹, 土屋創太, “CRC 付き Polar 符号に基づく暗号
化後圧縮を用いた高効率マルチホップ伝送法,” 信学技報, vol. 121, no. 302,
RCS2021-175, pp. 1-6, 2021 年 12 月.
【45】 鈴木康介, 安達宏一, 田久修, 太田真衣, 藤井威生, “パケット型インデックス
変調における適応的インデックスマッピング手法,” 信学技報, vol. 121, no. 302,
RCS2021-176, pp. 7-12, 2021 年 12 月.
【46】 蕪木碧仁, 安達宏一, 田久修, 太田真衣, 藤井威生, “LPWAN における周期ト
ラフィックを考慮したリソース割り当て法の検討,” 信学技報, vol. 121, no. 302,
RCS2021-195, pp. 101-106, 2021 年 12 月.
【47】 梅本悠河, 小野哲, 和田光司, “飛越結合の影響及び共振周波数のずれを考慮したマイクロストリップBPFの高精度設計法に関する検討,” 信学技報, vol.
121, no. 303, MW2021-95, pp. 61-66, 2021年12月.
Hung-Nguyen Trong, Van-Trung Nguyen and Koichiro Ishibashi, “A Sub uW and14bit Resolution Temperature Sensor for IoT Using Thermistor-Defined TDC,” 信学- 44 -

技報, vol. 121, no. 278, ICD2021-58, pp. 178-181, 2021年12月.
【48】 浦部綾香, 石橋功至, MohammadJavad Salehi, Antti Tölli, “不均一なキャッシュ
サイズを有するマルチユーザ MISO 通信路のための符号化キャッシング設計,”
信学技報, vol. 121, no. 329, RCS2021-206, pp. 57-62, 2022 年 1 月.
【49】 小林拓弥, 安達宏一, “Wireless Powered-MEC におけるオフロード確率と電力
伝 送 時 間 割 当 の 共 同 設 計 に 関 す る 検 討 ,” 信 学 技 報 , vol. 121, no. 329,
RCS2021-207, pp. 63-68, 2022 年 1 月.
【50】 チャルーンスック ブンパシット, 安達宏一, “WSN における情報収集遅延を考慮したパケット集約法の検討,” 信学技報, vol. 121, no. 329, RCS2021-208, pp.
69-74, 2022 年 1 月.
【51】 小林岳, 田久修, 安達宏一, 太田真衣, 藤井威生, “LoRa における同一チャネル
干渉電力及び占有率推定法による適応チャネル選択,” 信学技報, vol. 121, no.
345, SR2021-59, pp. 7-10, 2022 年 1 月．
【52】 石川亮, 瀬下拓也, 髙山洋一郎, 本城和彦, “2 電力レベル設計 28 GHz 帯 GaNHEMT ドハティー増幅器 MMIC (依頼講演),” 信学技報, vol. 121, no. 361,
MW2021-109, pp. 28-31, 2022 年 1 月.
【53】 片桐啓太, 藤井威生, “電波マップ高度化に向けた観測誤差の較正,” 信学技報,
vol. 121, no. 345, SR2021-64, pp. 25-30, 2022 年 1 月.
【54】 松嶋大稀, 藤井威生, “チャネル占有率を活用した環境適応型センサネットワ
ークのチャネル選択” 信学技報, vol. 121, no. 345, SR2021-65, pp. 31-36, 2022 年
1 月.
【55】 成枝秀介, 藤井威生, “電力検出に基づくキャリアセンスの特性,” 信学技報,
vol. 121, no. 345, SR2021-70, pp. 54-61, 2022 年 1 月.
【56】 成枝秀介, 藤井威生, “電力検出キャリアセンスを用いた sub-GHz 帯 LPWAN の特性,” 信学技報, vol. 121, no. 345, SR2021-71, pp. 62-67, 2022 年 1 月.
【57】 成枝秀介, 三好夏生, 川島朋幸, 藤井威生, 成瀬央, “半波長間隔での sub-GHz
帯 LPWA 電波伝搬測定結果の周波数解析,” 信学技報, vol. 121, no. 345,
SR2021-76, pp. 90-92, 2022 年 1 月.
【58】 角田真一朗, 藤井威生, 成枝秀介, “LPWA マルチシステム間逐次干渉除去技術の検討,” 信学技報, vol. 121, no. 345, SR2021-84, pp. 125-131, 2022 年 1 月.
【59】 上田有由夢, 藤井威生, 向田敦紀, “無線環境データベースを用いた V2X におけ る 通 信 シ ス テ ム の 適 応 選 択 手 法 の 検 討 ,” 信 学 技 報 , vol. 121, no. 373,
ITS2021-35, pp. 61-66, 2022 年 2 月.
【60】 向田敦紀, 上田有由夢, 片桐啓太, 藤井威生, “信頼区間を用いた V2X 向けパケット到達率マップの構築手法,” 信学技報, vol. 121, no. 373, ITS2021-36, pp.
67-72, 2022 年 2 月.
【61】 太田真衣, 藤井威生, “差動化パケット型インデックス変調方式におけるクロックドリフトの影響,” 信学技報, vol. 121, no. 392, SR2021-87, pp. 14-19, 2022 年- 45 -

3 月.
【62】 伊藤弘樹, 稲毛契, 藤井威生, “複数システム混在下におけるスパースモデリ
ングを利用した干渉推定手法,” 信学技報, vol. 121, no. 392, SR2021-88, pp.
20-24, 2022 年 3 月.
【63】 片桐啓太, 佐藤光哉, 稲毛契, 藤井威生, “干渉制約環境下における経験分布関数の補正に基づく電波マップ外挿法,” 信学技報, vol. 121, no. 392, SR2021-92,
pp. 28-35, 2022 年 3 月.
【64】 宮本直, 藤井威生, “[依頼講演]周波数共用のための電波マップと 3 次元地図情報を用いた干渉電力推定手法,” 信学技報, vol. 121, no. 392, SR2021-93, pp.
36-41, 2022 年 3 月.
【65】 上野拓仁, 成枝秀介, 藤井威生, 成瀬央, “複数 LPWA 信号到来時のパケット受
信成功確率特性,” 信学技報, vol. 121, no. 392, SR2021-116, pp. 130-132, 2022 年 3月.
【66】 石原克弥, 斉藤昭, 菊池晴貴, 和田渉, 本城和彦, 石川亮, “多モード OAM 波集束用反射鏡の曲率最適化に関する一検討,” 信学総大, B-1-62, 2022 年 3 月.
【67】 渋谷恵美, 山口明, 村上隆秀, 新保宏之, 内村颯汰, 石橋功至, “基地局連携ビームフォーミングにおける他ユーザ利用時性能の評価,” 信学総大, B-5-67,
2022 年 3 月.
【68】 香月優真, アブレウ ジュゼッペ, 石橋功至, 石川直樹, “連続最適化法を一方向性関数として用いる物理層セキュリティ,” 信学総大, B-5-83, 2022 年 3 月.
【69】 鶴見康平, 鈴木康介, 蕪木碧仁, 安達宏一, 田久修, 太田真衣, 藤井威生, “複数周波数チャネルを用いるパケット型インデックス変調の実機評価,” 信学総大, B-5-86, 2022 年 3 月.
【70】 蕪木碧仁, 安達宏一, 田久修, 太田真衣, 藤井威生, “LPWAN における通信の周期性を活かしたリソース割り当て法,” 信学総大, B-5-87, 2022 年 3 月.
【71】 小畠大輝, 神藤夏季, 松浦基晴, “光ファイバ給電式ドローンを用いた 空中無線基地局のための信号伝送特性評価,” 信学総大, B12-1, オンライン開催, 2022
年 3 月.
【72】 藤田卓, 間宮光瑠, 松浦基晴, “光ファイバ給電用ファイバにおける伝送損失の波長依存性評価,” 信学総大, B12-2, オンライン開催, 2022 年 3 月.
【73】 香取稜, 松浦基晴, “半導体光増幅器内で発生する高速周波数チャープの測定,” 信学総大, B12-5, オンライン開催, 2022 年 3 月.
【74】 吉川祐太, 石橋孝一郎, “LoRa モジュールの各低電力モードによる間欠動作の低電力化,” 信学総大, B15-52, 2022 年 3 月.
【75】 宮本直, 藤井威生, “3 次元電波マップ構築のためのハイトパターン推定手法の検討,” 信学技報, 信学総大, B17-4, 2022 年 3 月.
【76】 成枝秀介, 藤井威生, “Sub-GHz 帯 LPWAN におけるエンドデバイスの電力検出
キャリアセンスレベル選択,” 信学総大, B17-8, 2022 年 3 月.

- 46 -

【77】 武田佳太, 田久修, 安達宏一, 太田真衣, 藤井威生, “429MHzLoRa/FSK におけるパケットレベルインデックス変調の実装,” 信学総大, B-17-10, 2022 年 3 月.
【78】 宮本隆司, 田久修, 安達宏一, 太田真衣, 藤井威生, “イベント位置推定を活用したセンサ情報の傾向分析による高効率な情報収集法,” 信学総大, B-17-11,
2022 年 3 月.
【79】 伊藤利, 田久修, 安達宏一, 太田真衣, 藤井威生, “物理量変換一括収集法における周波数オフセットとエネルギー検知を併用した衝突検知,” 信学総大,
B-17-12, 2022 年 3 月.
【80】 吉田剛, 本城和彦, 石川亮, “ゼロしきい値 GaAs HEMT を用いた 920 MHz 及び
2.45 GHz 帯サブ mW 高効率整流器,” 信学総大, B-20-2, 2022 年 3 月.
【81】 山崎純, 本城和彦, 石川亮, “整流動作用大信号等価回路モデルを用いた広ダ
イナミックレンジ動作向け高効率 GaN HEMT 整流器設計,” 信学総大, C-2-1,
2022 年 3 月.
【82】 長田多喜, 石川亮, 本城和彦, “増幅器の負ゲートバイアス供給用ゼロ閾値
GaAs HEMT 整流器,” 信学総大, C-2-2, 2022 年 3 月.
【83】 椙江陽人, 田中愼一, 石川亮, 本城和彦, “誘導ゲート駆動 FET を用いるゼロ閾値電圧ダイオード,” 信学総大, C-2-7, 2022 年 3 月.
【84】 髙木裕貴, 太田喜元, 石川亮, 本城和彦, “マルチ高調波処理スタブをインピー
ダンス変換回路に用いた高効率非対称ドハティ増幅器,” 信学総大, C-2-13,
2022 年 3 月.
【85】 石川亮, 本城和彦, “無線電力伝送応用に向けた DC/RF 変換用高効率・高利得多段増幅器,” 信学総大, C-2-17, 2022 年 3 月.
【86】 髙橋拓海, 小野哲, 和田光司, “異種線路構造を用いた周波数離調比の高い小型積層DBPFの設計,” 信学総大, C-2-27, 2022年3月.
【87】 神保雄祐, 小野哲, 和田光司, “5分配かつ非等分配な1GHz帯Bagley Polygon型
分配率可変ディバイダの設計に関する検討,” 信学総大, C-2-44, 2022年3月.
【88】 相楽昌希, 伊東哲幸, 松浦基晴, “半導体光増幅器内での周波数チャープを用いた 40 Gbps 光デジタル・アナログ変換,” 信学技報, vol. 121, no. 386, PN2021-66,
pp. 71-75, オンライン開催, 2022 年 3 月.
【89】 津田隼一, 相楽昌希, 竹本大志, 松浦基晴, “半導体光増幅器の周波数チャープを用いた全光論理ゲート,” 信学技報, vol. 121, no. 386, PN2021-67, pp. 76-79, オ
ンライン開催, 2022 年 3 月.
【90】 神藤夏季, 小畠大輝, 松浦基晴, “空中基地局に向けた光ファイバ給電ドロー
ンの飛翔実験,” 信学技報, vol. 121, no. 386, PN2021-77, pp. 134-137, オンライン
開催, 2022 年 3 月.
【91】 小幡昭平, 福山瑞稀, 松浦基晴, 高橋英憲, 吉兼昇, 釣谷剛宏, “マルチコア光
ファイバを用いた光ファイバ給電における伝送特性評価,” 信学技報, vol. 121,
no. 386, PN2021-78, pp. 138-141, オンライン開催, 2022 年 3 月.

- 47 -

【92】 間宮光瑠, 村上夏尉, 松浦基晴, “ダブルクラッド光ファイバを用いた光ファ
イバ給電の伝送損失低減化に関する研究,” 電子情報通信学会フォトニックネ
ットワーク研究会 学生ワークショップ, pn2022-stws-1, オンライン開催, 2022
年 3 月.

シンポジウム講演【1】 藤井威生, 「Beyond 5G に向けた端末電波観測による多次元無線環境把握」“JST CREST・さきがけ複合領域 令和３年度成果報告会・成果展開 VR シンポ
ジウム研究領域 「微小エネルギーを利用した革新的な環境発電技術の創出」
エネルギーハーベスティングの未来” 2022 年 3 月.（招待講演）

その他の講演石橋功至, “グラントフリーアクセス技術入門,” 革新的無線通信技術に関する横断型研究会, pp. 1-102, 2021 年 10 月.
【2】 藤井威生, “通信環境把握と冗長化による環境ロバストな車向け通信,” 東京大学生産技術研究所. RC-24 ITS に関する研究懇談会, 2022 年 3 月.

【1】

受賞
【1】 [OWPT 2021 Paper Award]
T. Kobatake, N. Shindo, and M. Matsuura, “Simultaneous fiber transmission ofcontrol and mobile communication signals in power-over-fiber drones for airborne
base stations,” The 3rd OptoElectron. Commun. Conf. (OWPT 2021), OWPT-P-02,
Online, Apr. 2021.
【2】 [OECC 2021 Best Student Paper Award]
M. Sagara, W. Rui, J. Tsuda, and M. Matsuura, “Frequency comb assisted photonic
digital-to-analog conversion based on frequency chirp in a QD-SOA,” Proc. 26th
OptoElectron. Commun. Conf. (OECC 2021), W2F.4, Online, Jul. 2021.
【3】 GAO Ying, IEEE VTS Tokyo/Japan Chapter 2021 Young Researcher’s
Encouragement Award, Sept. 2021.
【4】 角 田 真 一 郎 , IEEE VTS Tokyo/Japan Chapter 2021 Young Researcher’s
Encouragement Award, Sept. 2021.
【5】 片桐啓太, 電子情報通信学会 RISING2021 優秀インタラクティブ発表賞, 2021
年 11 月.
【6】 中新井田覚志, 電子情報通信学会 RISING2021 優秀インタラクティブ発表賞,
2021 年 11 月.

- 48 -

【7】 [電子情報通信学会 フォトニックネットワーク研究会 学生 WS 優秀賞]
間宮光瑠, 村上夏尉, 松浦基晴, “ダブルクラッド光ファイバを用いた光ファイ
バ給電の伝送損失低減化に関する研究,” 電子情報通信学会フォトニックネッ
トワーク研究会 学生ワークショップ, pn2022-stws-1, オンライン開催, 2022 年
3 月.
【8】 角田真一郎, 電子情報通信学会スマート無線研究会研究奨励賞, 2022 年 3 月.
【9】 中條宏郁, 藤井威生, 安達宏一他, 電子情報通信学会スマート無線研究会技術特別賞, 2022 年 3 月.
【10】 上田康平，令和 3 年度目黒会賞, 2022 年 3 月.（学部学生）【11】 棚木拓海, 令和 3 年度目黒会賞, 2022 年 3 月.（学部学生）【12】 安藤研吾，令和 3 年度目黒会賞, 2022 年 3 月.（博士前期課程学生）【13】 宮本直，令和 3 年度目黒会賞, 2022 年 3 月.（博士前期課程学生）【14】 上田有由夢，令和 3 年度目黒会賞, 2022 年 3 月.（博士前期課程学生）【15】 片桐啓太, 令和 3 年度学長表彰（研究活動）, 2022 年 3 月.
【16】 宮本直, 令和 3 年度学長表彰（研究活動）, 2022 年 3 月.
【17】 中新井田覚志, 令和 3 年度学長表彰（研究活動）, 2022 年 3 月.
【18】 角田真一郎, 令和 3 年度学長表彰（研究活動）, 2022 年 3 月.
【19】 GAO Ying, 令和 3 年度学長表彰（研究活動）, 2022 年 3 月.
【20】 蕪木碧仁, 令和 3 年度学長表彰（研究活動）, 2022 年 3 月.
【21】 鈴木康介, 令和 3 年度学長表彰（研究活動）, 2022 年 3 月.

特許【1】 安達宏一, 靏見康平, 蕪木碧仁, 藤井威生, “情報伝送システム, 情報伝送方法
および基地局プログラム,” 日本, 特願 2021-084513, 2021 年 5 月 19 日.
【2】 高山洋一郎, 本城和彦, 石川亮, “マルチバンド増幅器およびデュアルバンド
増幅器,” 日本国特許第 6901108 号, 2021 年 6 月 21 日.
【3】 高山洋一郎, 本城和彦, 石川亮, “マルチバンド増幅器およびデュアルバンド
増幅器,” ZL201680047177.4（中国）, 2021 年 9 月 17 日.
【4】 鈴木康介, 安達宏一, 藤井威生, 太田真衣, 田久修, “情報伝送システム, 情報
伝送方法, 端末プログラムおよび基地局プログラム,” 日本, 特願 2021-167219,
2021 年 10 月 12 日.
【5】 藤井威生, 安達宏一, 太田真衣, 田久修, “通信システム及び通信方法,” 特願2021-174200, 2021 年 10 月 25 日.
【6】 斉藤昭, 本城和彦, 石川亮, 鈴木博, “アレイアンテナおよび無線通信システ
ム,” 日本国特許第 6987385 号, 2021 年 12 月 3 日.
【7】 斉藤昭, 大塚啓人, 本城和彦, 石川亮, “無線通信装置及びアンテナ装置,” 日
本国特許第 7006961 号, 2022 年 1 月 11 日.

- 49 -

【8】 上田有由夢, 藤井威生, 向田敦紀, “通信システム、通信方法および車載機プログラム,” 日本, 特願 2022-018533, 2022 年 2 月 9 日.
【9】 宮本直, 藤井威生, “電波ハイトパターン推定装置、電波ハイトパターン推定方法および推定プログラム,” 日本, 特願 2022-053823, 2022 年 3 月 29 日.
【10】 安達宏一, 熊田遼汰, “受信装置、受信方法および受信プログラム”, 日本, 特願2022-053919, 2022 年 3 月 29 日.
【11】 石橋功至, 上田康平, “受信装置, 受信方法および受信プログラム”, 日本, 特願 2022-053764, 2022 年 3 月 29 日.
【12】 稲葉敬之, 浅野晃, 坪田光, 秋田学, “列車速度検出装置及び列車速度検出方法,” 中国, ZL201510462922.9, 2021 年 10 月 8 日（登録），2015 年 7 月 31 日（出願）.
【13】 稲葉敬之, 浅野晃, 坪田光, 秋田学, “列車状態検出装置及び列車状態検出方法,” 中国, ZL20151046330.9, 2021 年 6 月 4 日（登録），2015 年 7 月 31 日（出願）【14】 稲葉敬之, 秋田学, 渡辺優人, “隔離周波数合成レーダ装置.”, 第 7011305 号,
2022 年 1 月 18 日（登録），2018 年 2 月 18 日（出願）.
【15】 稲葉敬之, 浅野晃, 坪田光, 秋田学，“列車速度検出装置及び列車速度検出方法,” インド, 386329, 2022 年 1 月 10 日（登録），2015 年 9 月 28 日（出願）.

広報・報道発表【1】 電通大, 電波混線せず通信 ６Ｇ向けアルゴリズム, 日刊工業新聞, 2021 年 4
月 26 日.
【2】 経営ひと言／電気通信大学・石橋功至教授「数学人材育む」, 日刊工業新聞,
2021 年 4 月 29 日.
【3】 【ニュースリリース】高速大容量を実現する新たな通信技術（Beyond 5G/6Gの実現に向けて） ―セルフリーMIMO のためのビームフォーマー設計法の開発―, 電通大ニュースリリース, 2021 年 5 月 10 日.
【4】 電通大, MIMO の電波利用効率を 7 倍にする技術, PC Watch, 2021 年 5 月 10 日.

【5】 “IoT の課題解決に新通信方式 ―省電力で伝送データ量を増大―”, 電通大ニュースリリース, 2021 年 7 月 9 日.
【6】 “電通大, IoT センサ向け新通信方式「パケット型インデックス変調」を開発”,
TECH+, 2021 年 7 月 13 日.
【7】 “電通大, IoT センサ向け新通信方式「パケット型インデックス変調」を開発”, マ
ピオンニュース, 2021 年 7 月 13 日.
【8】 “電通大, IoT センサ向け新通信方式「パケット型インデックス変調」を開発”, マ
イナビニュース, 2021 年 7 月 13 日.
【9】 CEATEC on line 2021, “電波発電のためのレクテナと IoT 応用技術,” 2021 年
10 月.

- 50 -