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Search Results: Conference Papers
 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 121  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
NS, SR, RCS, SeMI, RCC
(Joint)
2022-07-15
09:10
Ishikawa The Kanazawa Theatre + Online
(Primary: On-site, Secondary: Online)
[Invited Lecture] Federated Learning in Wireless Networks
Takayuki Nishio (TokyoTech) RCC2022-31 NS2022-49 RCS2022-92 SR2022-34 SeMI2022-36
Federated Learning is a distributed machine learning method. The most important feature of federated learning is that it... [more] RCC2022-31 NS2022-49 RCS2022-92 SR2022-34 SeMI2022-36
p.63(RCC), p.118(NS), p.125(RCS), p.71(SR), p.80(SeMI)
NS, SR, RCS, SeMI, RCC
(Joint)
2022-07-15
11:55
Ishikawa The Kanazawa Theatre + Online
(Primary: On-site, Secondary: Online)
Vision-Aided Frame-Capture-Based CSI Recomposition for WiFi Sensing: A Multimodal Approach
Hiroki Shimomura, Takamochi Kanda, Koji Yamamoto (Kyoto Univ.), Takayuki Nishio (Kyoto Univ./Tokyo Tech.), Akihito Taya (Kyoto Univ./Aoyama Gakuin Univ.) SeMI2022-42
Recompositing channel state information (CSI) from the beamforming feedback matrix (BFM), which is a compressed version ... [more] SeMI2022-42
pp.98-102
SeMI 2022-01-20
15:00
Nagano
(Primary: On-site, Secondary: Online)
[Short Paper] Evaluation of Few Round Training with Distillation-Based Semi-Supervised Federated Learning
Yuki Yoshida (Tokyo Tech), Sohei Itahara (Kyoto Univ.), Takayuki Nishio (Tokyo Tech) SeMI2021-65
This paper studies how to reduce the number of rounds in model training using Distillation-based Semi-supervised federat... [more] SeMI2021-65
pp.48-50
SeMI 2022-01-20
15:10
Nagano
(Primary: On-site, Secondary: Online)
[Short Paper] A Study of Joint Control of Machine Learning Model and Wireless LAN Parameters in Split inference by Reinforcement Learning
Kojin Yorita (Tokyo Tech.), Sohei Itahara (Kyoto Univ.), Takayuki Nishio (Tokyo Tech.), Daiki Yoda, Toshihisa Nabetani (Toshiba) SeMI2021-66
 [more] SeMI2021-66
pp.51-54
SeMI 2022-01-20
15:20
Nagano
(Primary: On-site, Secondary: Online)
[Short Paper] A Study of Beamforming Feedback-based Model-driven Angle of Departure Estimation
Sohei Itahara (Kyoto Univ.), Takayuki Nishio (Kyoto Univ./Tokyo Tech.), Koji Yamamoto (Kyoto Univ.) SeMI2021-68
This paper introduces the angle of departure (AoD) estimation method [1] using the multiple signal classification (MUSIC... [more] SeMI2021-68
pp.59-61
SeMI 2022-01-20
15:30
Nagano
(Primary: On-site, Secondary: Online)
[Short Paper] A Method for Improving Accuracy of Wireless Sensing with Bi-directional Beamforming Feedback Matrices
Sota Kondo, Souhei Itahara, Kota Yamashita, Koji Yamamoto (Kyoto Univ.), Yusuke Koda (Univ. Oulu), Takayuki Nishio (Kyoto University/Tokyo Tech.), Akihito Taya (Kyoto Univ./Aoyama Gakuin Univ.) SeMI2021-69
 [more] SeMI2021-69
pp.62-64
SeMI 2022-01-21
09:40
Nagano
(Primary: On-site, Secondary: Online)
[Short Paper] Study of ACK-Less Rate Adaptation for IEEE 802.11bc Using Deep Reinforcement Learning
Takamochi Kanda (Kyoto Univ.), Yusuke Koda (Univ. of Oulu), Yuto Kihira, Koji Yamamoto (Kyoto Univ.), Takayuki Nishio (Kyoto Univ./Tokyo Tech.) SeMI2021-74
This paper introduces an ACK-less rate adaptation to locational variation of recipient stations (STAs) for broadcast wir... [more] SeMI2021-74
pp.86-88
SeMI 2022-01-21
09:50
Nagano
(Primary: On-site, Secondary: Online)
[Short Paper] A Study of Computer Vision-aided Single-antenna and Single-anchor RSSI Localization Considering Movable Obstructions
Tomoya Sunami, Sohei Itahara (Kyoto Univ.), Yusuke Koda (Oulu Univ.), Takayuki Nishio (Kyoto Univ./Tokyo Tech.), Koji Yamamoto (Kyoto Univ.) SeMI2021-75
This paper shows the feasibility of single-antenna and single-RF (radio frequency)-anchor received power strength indica... [more] SeMI2021-75
pp.89-91
OCS, CS
(Joint)
2022-01-13
14:30
Yamaguchi Conference room 204A・B at KDDI Ishin-hall
(Primary: On-site, Secondary: Online)
Image Compression and Progressive Retransmission Scheme on Edge Computing System for Image Data Reduction
Mutsuki Nakahara, Daisuke Hisano (Osaka Univ.), Mai Nishimura (OSX), Takayuki Nishio (Tokyo Tech.), Yoshitaka Ushiku (OSX), Kazuki Maruta (Tokyo Tech.), Yu Nakayama (Tokyo Univ. of Agriculture and Tech.) CS2021-69
Edge computing has been getting attention due to reducing the data traffic in the backbone network. On the other hand, t... [more] CS2021-69
pp.7-12
SRW, SeMI, CNR
(Joint)
2021-11-26
15:00
Tokyo Kikai-Shinko-Kaikan Bldg.
(Primary: On-site, Secondary: Online)
[Poster Presentation] Impact of the Layout of Devices to Estimation Accuracy in Wireless Sensing Using Beamforming Feedbacks
Sota Kondo, Koji Yamamoto (Kyoto Univ.), Yusuke Koda (Univ. Oulu), Kota Yamashita (Kyoto Univ.), Takayuki Nishio (Kyoto Univ./Tokyo Tech.), Akihito Taya (Kyoto Univ./Aoyama Gakuin Univ.) SRW2021-47 SeMI2021-46 CNR2021-21
(To be available after the conference date) [more] SRW2021-47 SeMI2021-46 CNR2021-21
pp.68-70(SRW), pp.55-57(SeMI), pp.45-47(CNR)
SRW, SeMI, CNR
(Joint)
2021-11-26
15:00
Tokyo Kikai-Shinko-Kaikan Bldg.
(Primary: On-site, Secondary: Online)
[Poster Presentation] Frame-Capture-Based CSI Recomposition Pertaining to Firmware-Agnostic WiFi Sensing
Ryosuke Hanahara, Sohei Itahara, Kota Yamashita (Kyoto Univ.), Yusuke Koda (Univ. Oulu), Akihito Taya (Kyoto Univ./Aoyama Gakuin Univ.), Takayuki Nishio (Kyoto Univ./Tokyo Tech.), Koji Yamamoto (Kyoto Univ.) SRW2021-48 SeMI2021-47 CNR2021-22
This paper presents an estimation method of channel state information (CSI) matrices using corresponding beamforming fee... [more] SRW2021-48 SeMI2021-47 CNR2021-22
pp.71-73(SRW), pp.58-60(SeMI), pp.48-50(CNR)
RCS 2021-10-22
15:00
Online Online [Poster Presentation] Interference Source Determination Based on History of Transmissions in WLANs
Koji Yamamoto, Mayu Mieda, Sota Kondo (Kyoto Univ.), Takayuki Nishio (Kyoto Univ./Tokyo Tech.), Akihito Taya (Kyoto Univ./Aoyama Gakuin Univ.), Kazuto Yano (ATR) RCS2021-141
In wireless communications, in general, stations can observe the loss of transmitted frames, but it is difficult to accu... [more] RCS2021-141
pp.122-125
CQ, MIKA
(Joint)
2021-09-10
12:40
Online Online [Special Invited Talk] Toward Communication Efficient Federated Learning
Takayuki Nishio (TokyoTech) CQ2021-56
Federated Learning (FL) is a machine learning framework that trains models using distributed data. Since FL can utilize ... [more] CQ2021-56
pp.94-96
IN, NS
(Joint)
2021-03-05
11:00
Online Online Effect of Beamforming and Vehicle Material on Communication Quality in In-Vehicle Wireless Communication with IEEE802.11ad
Takumi Shiohara (Nagoya Univ.), Takayuki Nishio (Tokyo Tech.), Tutomu Murase (Nagoya Univ.) IN2020-79
The effect of interference on in-vehicle wireless LAN communication with IEEE 802.11ad (hereinafter 802.11ad) for in-veh... [more] IN2020-79
pp.150-155
SeMI 2021-01-20
13:20
Online Online A Study of Online Training Method for Image-based Wireless Link Quality Prediction
Sohei Itahara (Kyoto Univ), Takayuki Nishio (Tokyo Tech), Masahiro Morikura, Koji Yamamoto (Kyoto Univ) SeMI2020-44
Machine-learning-based prediction of future wireless link quality is an emerging technique that can potentially improve ... [more] SeMI2020-44
pp.7-9
CQ, CBE
(Joint)
2021-01-20
10:05
Online Online IEEE 802.11ad Communication Quality Measurement in In-vehicle Wireless Communication with Real Machines
Ryoko Nino (Nagoya Univ.), Takayuki Nishio (Titech), Tutomu Murase (Nagoya Univ.) CQ2020-61
This paper demonstrates the feasibility of IEEE 802.11ad-based in-vehicle communication for a wireless harness. IEEE 802... [more] CQ2020-61
pp.5-10
CQ, CBE
(Joint)
2021-01-21
16:00
Online Online [Poster Presentation] QoS Measurement Using Real Machine with Interference in IEEE 802.11ad In-Vehicle Wireless Communication
Ryoko Nino (Nagoya Univ.), Takayuki Nishio (Titech), Tutomu Murase (Nagoya Univ.) CQ2020-74
Communication quality of IEEE 802.11ad in in-vehicle communication for a wireless harness is investigated on the effect ... [more] CQ2020-74
pp.62-63
SRW, SeMI, CNR
(Joint)
2020-11-26
16:00
Online Online [Poster Presentation] Feature Extraction Method for Wireless LANs Channel Selection Based on Contextual Bandit Learning
Kota Yamashita (Kyoto Univ.), Shotaro Kamiya (Sony Corp.), Koji Yamamoto (Kyoto Univ.), Takayuki Nishio (Tokyo Tech.), Masahiro Morikura (Kyoto Univ.) SeMI2020-24
 [more] SeMI2020-24
pp.39-42
SRW, SeMI, CNR
(Joint)
2020-11-26
16:00
Online Online [Poster Presentation] Adversarial Reinforcement Learning-based Robust Access Point Coordination Against Uncoordinated Interference
Yuto Kihira, Yusuke Koda, Koji Yamamoto (Kyoto Univ.), Takayuki Nishio (Tokyo Tech.), Masahiro Morikura (Kyoto Univ.) SeMI2020-25
 [more] SeMI2020-25
pp.43-46
SeMI 2020-01-31
10:00
Kagawa   [Poster Presentation] Communication-Efficient Federated Learning Using Non-Labeled Data
Souhei Itahara, Takayuki Nishio, Masahiro Morikura, Koji Yamamoto (Kyoto Univ) SeMI2019-109
Federated learning (FL) is a machine learning setting where many mobile devices collaboratively train a machine learning... [more] SeMI2019-109
pp.47-48
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