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Fukawa Lab
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A lab that draws on statistical signal processing to pursue fast, reliable next-generation wireless communications.
AboutAbout the lab
Future communication technologies to support beyond 5G/6G.
The Fukawa Lab studies modulation/demodulation and networking technologies for realizing fast, reliable next-generation wireless communications.
In recent years, the lab has focused on applying machine learning to mobile communications.
The proposed methods are evaluated mainly through computer simulations.
Lab visits are accepted at any time.
Key terms
- Modulation and demodulation
- A collective term for modulation, which places information on radio waves and the like, and demodulation, which extracts information from a received signal
- Statistical signal processing
- Techniques for extracting needed information from signals while handling variations such as noise using probability and statistics
- OFDM
- A communication scheme that splits information across many frequencies and transmits it simultaneously. It is widely used in wireless communications
NewsLab news
Doctoral students and others received the Best Paper Award at the international conference APCC 2025
ResearchResearch themes
To realize next-generation wireless communications, the lab studies modulation/demodulation and network technologies that make full use of statistical signal processing. In recent years, it has also conducted research using machine learning.
*Illustrative imageControlling Wireless Networks with Machine Learning
When small base stations are densely deployed, interference with neighboring cells increases. The lab suppresses interference by combining beam direction and transmit power, and uses neural networks to greatly reduce the computation needed to search for that combination.
*Illustrative imageTransmitting OFDM Signals with Constant Amplitude
In OFDM, a problem is that the peak power becomes large compared with the average. In this method, an OFDM signal is split into two constant-amplitude signals that are sent with a time offset, and the receiver combines them to reconstruct the original signal.
*Illustrative imagePhysical-Layer Encryption to Prevent Eavesdropping
Conventional methods that degrade the eavesdropper's reception quality have the problem of greatly increased transmit power. The lab has proposed the RP method, which randomly changes the phase of each signal and minimizes transmit power, and is extending it to MIMO communications.
MembersFaculty
Members of the Fukawa Lab include faculty, secretaries, and doctoral, master's, and undergraduate students.As of 2026
- ProfessorFukawa KazuhikoPublications ↗
- Assistant ProfessorSilchatabun Gan
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Cell-Tower” J.smith
（英語版ウィキペディアの 投稿者） / CC BY-SA 2.5 (cropped) - Controlling Wireless Networks with Machine Learning: “Cell tower antenna, Zagrebačka cesta” Mnalis / CC BY-SA 4.0 (cropped)
- Transmitting OFDM Signals with Constant Amplitude: “Cell tower antenna, Zagrebačka cesta” Mnalis / CC BY-SA 4.0 (cropped)
- Physical-Layer Encryption to Prevent Eavesdropping: “Cell tower antenna, Zagrebačka cesta” Mnalis / CC BY-SA 4.0 (cropped)
- Related lab (Yamada Lab): “SAR Kilauea topo interferogram” JPL / Public domain (cropped)
- Related lab (Watanabe Lab): “Mapping a l'Hospital de Sant Pau - 1 de gener” Jordiferrer / CC BY-SA 4.0 (cropped)
- Related lab (Kuroda Lab): “Cosine Series Plus Noise TFM” Fourier1789 / CC BY-SA 4.0 (cropped)
- Related lab (Slavakis Lab): “The manifold paths of biology ( )” UCL Mathematical & Physical Sciences / CC BY 2.0 (cropped)
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