Research and Development on Wireless Access Technology Based on Factor Analysis of Communication Quality Using Redundant Information

Kyoto University, Fukuoka University,
Advanced Telecommunications Research Institute International

Overview

  • Collecting and analyzing large amounts of side information including transmission periods and channel state information enable identifications of degradation factors of communication quality.
  • Developing access control technologies to improve spectral efficiency based on the identified factors.

Point of Research and Development

Estimation of transmission failure factors in wireless LANs using side information including transmission periods.

Highly efficient access control based on side information and reinforcement learning.

Low latency channel selection using side information.

 User and human body localization using beamforming (BF) feedback as side information.

Members

Koji Yamamoto
Kyoto University
Principal Investigator
Takayuki Nishio
Kyoto University
Akihito Taya Kyoto University
Mai Ohta
Fukuoka University
Chief Investigator
Makoto Taromaru
Fukuoka University
Kazuto Yano
ATR
Chief Investigator
OJETUNDE Babatunde
ATR
Keiichiro mori
ATR

Research Results

Peer-reviewed paper

  1. Shunnosuke Kotera, Bo Yin, Koji Yamamoto, and Takayuki Nishio, “Lyapunov optimization-based latency-bounded allocation using deep deterministic policy gradient for 11ax spatial reuse,” IEEE Access, Dec. 2021.
  2. Kazuto Yano, Kenta Suzuki, Babatunde Ojetunde, and Koji Yamamoto, “Transmission datarate adaptation using redundant check information for IEEE 802.11ax wireless LAN,” IEICE Communications Express, Mar. 2021.
  3. Sota Kondo, Sohei Itahara, Kota Yamashita, Koji Yamamoto, Yusuke Koda, Takayuki Nishio, and Akihito Taya, “Bi-directional beamforming feedback-based firmware-agnostic WiFi sensing: An empirical study,” IEEE Access, vol.10, pp.36924-36934, Apr. 2022.
  4. Takamochi Kanda, Yusuke Koda, Yuto Kihira, Koji Yamamoto, and Takayuki Nishio, “ACK-less rate adaptation using distributional reinforcement learning for reliable IEEE 802.11bc broadcast WLANs,” IEEE Access, vol.10, pp.58858-58868, June 2022.
  5. Sohei Itahara, Sota Kondo, Kota Yamashita, Takayuki Nishio, Koji Yamamoto, and Yusuke Koda, “Beamforming feedback-based model-driven angle of departure estimation toward legacy support in WiFi sensing: An experimental study,” IEEE Access, vol.10, pp.59737-59747, June 2022.
  6. Yuto Kihira, Koji Yamamoto, Akihito Taya, Takayuki Nishio, Yusuke Koda, and Kazuto Yano, “Interference-free AP identification and shared information reduction for tabular Q-learning-based WLAN coordinated spatial reuse,” IEICE Communications Express, Vol.11, No.7, pp.392-397, July 2022.
  7. Yuto Kihira, Yusuke Koda, Koji Yamamoto, and Takayuki Nishio, “Adversarial reinforcement learning-based coordinated robust spatial reuse in broadcast-overlaid WLANs,” IEICE Transactions on Communications, Vol.E106-B, No.2, pp.203-212, Feb. 2023.

Peer-reviewed conference paper

  1. Yuto Kihira, Yusuke Koda, Koji Yamamoto, Takayuki Nishio, and Masahiro Morikura,“Adversarial reinforcement learning-based robust access point coordination against uncoordinated interference,” Proc. the 92nd IEEE Vehicular Technology Conference (VTC2020-Fall), Nov. 2020.
  2. Tomoya Sunami, Takayuki Nishio, Masahiro Morikura, and Koji Yamamoto,“Training data generation for RSSI-based localization with camera object detection,”Proc. ICETC, Dec. 2020.
  3. Kazuto Yano, Eiji Nii, Kenta Suzuki, and Koji Yamamoto, “Timestamp synchronization of received frames among multiple wireless LAN nodes for robust access point coordination,” Proc. of the 23rd International Conference on Advanced Communications Technology (IEEE ICACT 2021), Feb. 2021.
  4. Takashi Imanaka, Mai Ohta, and Makoto Taromaru, “Channel selection with multi-armed bandit algorithm based on delay time,”2021 International Conference on Emerging Technologies for Communications (ICETC 2021), Dec. 2021.
  5. Takamochi Kanda, Yusuke Koda, Koji Yamamoto, and Takayuki Nishio, “ACK-less rate adaptation for IEEE 802.11bc enhanced broadcast services using sim-to-real deep reinforcement learning,” Proc. the 19th IEEE Annual Consumer Communications & Networking Conference (CCNC 2022), Online, Jan. 2022.
  6. Ryosuke Hanahara, Sohei Itahara, Kota Yamashita, Yusuke Koda, Aihito Taya, Takayuki Nishio, and Koji Yamamoto, “Frame-capture-based CSI recomposition pertaining to firmware-agnostic WiFi sensing,” Proc. the 19th IEEE Annual Consumer Communications & Networking Conference (CCNC 2022), Jan. 2022.
  7. Kazuto Yano, Kenta Suzuki, Babatunde Segun Ojetunde, and Koji Yamamoto, “A study on update frequency of Q-learning-based transmission datarate adaptation using redundant check information for IEEE 802.11ax wireless LAN,” Proc. the 4th International Conference on Artificial Intelligence in Information and Communication (ICAIIC 2022), Feb. 2022.
  8. Babatunde Segun Ojetunde and Kazuto Yano, “Optimizing Q-learning-based access control scheme based on Q-table compression method,” Proc. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications（PIMRC 2022）Workshop, Sep. 2022.
  9. Hiroki Shimomura, Yusuke Koda, Takamochi Kanda, Koji Yamamoto, Takayuki Nishio, and Akihito Taya, “Vision-aided frame-capture-based CSI recomposition for WiFi sensing: A multimodal approach,” Proc. the 20th IEEE Annual Consumer Communications & Networking Conference (CCNC 2023), Jan. 2023.
  10. Takashi Imanaka, Mai Ohta, Makoto Taromaru, “Channel Access Control Instead of Random Backoff Algorithm,” Proc. the 5th International Conference on Artificial Intelligence in Information and Communication (ICAIIC 2023), Feb. 2023.

Other Publications

  1. Koji Yamamoto, Takayuki Nishio, Masahiro Morikura, “Factor analysis of communication quality using redundant information,” Electrical Engineering Journal cue, no. 44, Sep. 2020.
  2. Yuto Kihira, Yusuke Koda, Koji Yamamoto, Takayuki Nishio, and Masahiro Morikura, “Interference avoidance by adversarial RL for WLAN,” the 15th Kyoto University ICT Innovation, Feb. 2021.
  3. Koji Yamamoto, “Factor analysis of frame losses based on history of transmissions,” Electrical Engineering Journal cue, no. 46, p. 30, Sep. 2021.

Oral Presentations

  1. Kazuto Yano, Kenta Suzuki, Koji Yamamoto, and Mai Ohta, “A study on acquisition of redundant information for efficient transmission control based on factor analysis of communication quality,” IEICE Technical Report, RCS2019-343, pp. 129-133, March 2020.
  2. Mai Ohta, Koji Yamamoto, Kazuto Yano, and Makoto Taromaru, “Research and development on wireless access technology based on factor analysis of communication quality using redundant information,” IEICE Technical Report, SRW2019-81, pp. 109-110, March 2020.
  3. Koji Yamamoto, Yuto Kihira, Yusuke Koda, Takayuki Nishio, and Masahiro Morikura, “Factor analysis of communication quality using redundancy-check information in wireless LANs,” IEICE General Conference, B-5-147, March 2020.
  4. Takayuki Nishio, Tomoya Sunami, Masahiro Morikura, and Koji Yamamoto, “A study of object detection-assisted traffic control for wireless LAN,” IEICE General Conference, B-15-46, March 2020.
  5. Koji Yamamoto, “Research and development on wireless access technology based on factor analysis of communication quality using redundant information,” the 1st Wireless COE Symposium on robust / flexible radio resource utilization and new applications, June 2020.
  6. Takashi Imanaka, Mai Ohta, Makoto Taromaru, Koji Yamamoto, Kazuto Yano, “Study on channel selection method depending on transmission packet length — Research and development on wireless access technology based on factor analysis of communication quality using redundant information –,” IEICE Tech. Rep., vol. 120, no. 138, SRW2020-14, pp. 27-30, Aug. 2020.
  7. Tomoya Sunami, Takayuki Nishio, Masahiro Morikura, and Koji Yamamoto, “Training data generation for RSSI-based localization with camera object detection,” IEICE Society Conference, B-15-21, Sep. 2020.
  8. Takashi Imanaka, Mai Ohta, and Makoto Taromaru, “A Study on Channel Selection Method Using Reinforcement Learning,” IEICE Society Conference, B-17-17, Sep. 2020.
  9. Yuto Kihira, Yusuke Koda, Koji Yamamoto, Takayuki Nishio, and Masahiro Morikura,“Adversarial reinforcement learning-based robust access point coordination against uncoordinated interference,” IEICE Technical Report, SeMI2020-25, pp. 43—46, Nov. 2020.
  10. Koji Yamamoto, Takayuki Nishio, Masahiro Morikura, Mai Ohta, Makoto Taromaru, Kazuto Yano, Kenta Suzuki, and Eiji Nii, “Research and development on wireless access technology based on factor analysis of communication quality using redundant information,” ATR Open House, Nov. 2020.
  11. Tadashi Imanaka, Mai Ohta, and Makoto Taromaru, “Channel selection method with multi-armed bandit algorithm for spectrum sharing” IEICE Technical Report, SR2020-54, pp. 39—44, Jan. 2021.
  12. Kazuto Yano, Eiji Nii, Kenta Suzuki, and Koji Yamamoto, “Development of system to collect redundant information for efficient access control in wireless LAN,” IEICE Technical Report, RCS2020-204, pp. 7—12, March 2021.
  13. Kazuto Yano, Eiji Nii, Kenta Suzuki, and Koji Yamamoto, “Design of system to collect redundant check information for efficient access control in wireless LAN,” IEICE General Conference, B-5-120, March 2021.
  14. Koji Yamamoto, Takayuki Nishio, Akihito Taya, Mai Ohta, Makoto Taromaru, Kazuto Yano, Kenta Suzuki, Eiji Nii, and Babatunde Ojetunde, “Research and development on wireless access technology based on factor analysis of communication quality using redundant information,” the 2nd Wireless COE Symposium on robust / flexible radio resource utilization and new applications, June 2021.
  15. Takamochi Kanda, Yusuke Koda, Yuto Kihira, Koji Yamamoto, and Takayuki Nishio,“ACK-less rate adaptation for IEEE 802.11bc using deep reinforcement learning,”IEICE Society Conference, B-5-62, Sep. 2021.
  16. Sota Kondo, Koji Yamamoto, Yusuke Koda, Kota Yamashita, Takayuki Nishio, and Akihito Taya, “Impact of number of subcarriers to estimation accuracy in wireless sensing using beamforming feedbacks,”IEICE Society Conference, B-15-11, Sep. 2021.
  17. Koji Yamamoto, Mayu Mieda, Sota Kondo, Takayuki Nishio, Akihito Taya, and Kazuto Yano, “Interference source determination based on history of transmissions in WLANs,” IEICE Technical Report, RCS2021-141, Oct. 2021.
  18. Koji Yamamoto, Takayuki Nishio, Akihito Taya, Mai Ohta, Makoto Taromaru, Kazuto Yano, Kenta Suzuki Babatunde Ojetunde, “Research and development on wireless access technology based on factor analysis of communication quality using redundant information,”ATR Open House, Nov. 2021.
  19. Ryosuke Hanahara, Sohei Itahara, Kota Yamashita, Yusuke Koda, Akihito Taya, Takayuki Nishio, and Koji Yamamoto,“Frame-capture-based CSI recomposition pertaining to firmware-agnostic WiFi sensing,” IEICE Technical Report, SeMI2021-47, Nov. 2021.
  20. Sota Kondo, Koji Yamamoto, Yusuke Koda, Kota Yamashita, Takayuki Nishio, and Akihito Taya, “Impact of the layout of devices to estimation accuracy in wireless sensing using beamforming feedbacks,” IEICE Technical Report, SeMI2021-46, Nov. 2021.
  21. Koji Yamamoto, “[Invited Lecture] Factor analysis of communication quality through machine learning and wireless LAN sensing,” IEICE Technical Report, RCS2021-190, Dec. 2021.
  22. Sohei Itahara, Takayuki Nishio, and Koji Yamamoto, “A study of beamforming feedback-based model-driven angle of departure estimation,” IEICE Technical Report, SeMI2021-68, Jan. 2022.
  23. Sota Kondo, Sohei Itahara, Kota Yamashita, Koji Yamamoto, Yusuke Koda, Takayuki Nishio, and Akihito Taya, “A method for improving accuracy of wireless sensing with bi-directional beamforming feedback matrices,” IEICE Technical Report, SeMI2021-69, Jan. 2022.
  24. Takamochi Kanda, Yusuke Koda, Yuto Kihira, Koji Yamamoto, and Takayuki Nishio, “Study of ACK-less rate adaptation for IEEE 802.11bc using deep reinforcement learning,” IEICE Technical Report, SeMI2021-74, Jan. 2022.
  25. Tomoya Sunami , Sohei Itahara, Yusuke Koda, Takayuki Nishio, and Koji Yamamoto, “A study of computer vision-aided single-antenna and single-anchor RSSI localization considering movable obstructions,” IEICE Technical Report, SeMI2021-75, Jan. 2022.
  26. Kazuto Yano, Kenta Suzuki, Babatunde Ojetunde, and Koji Yamamoto, “Performance evaluation of access control and transmission datarate adaptation using redundant check information for IEEE 802.11ax wireless LAN,” IEICE Technical Report, SR2021-81, Jan. 2022.
  27. Kazuto Yano, Kenta Suzuki, Babatunde Ojetunde, Takashi Imanaka, Mai Ohta, and Makoto Taromaru, “Study on transmission channel selection scheme with multi-armed bandit algorithm for IEEE 802.11 wireless LAN,” IEICE Technical Report, SR2021-100, Mar. 2022.

Award

  1. Yuto Kihira, VTS Tokyo/Japan Chapter 2020 Young Researcher’s Encouragement Award, “Adversarial reinforcement learning-based robust access point coordination against uncoordinated interference,”Nov. 2020.
  2. Tomoya Sunami, IEICE ICETC2020 Best Short Paper Award,“Training data generation for RSSI-based localization with camera object detection,”Dec. 2020.