Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
CQ, MIKA (Joint) |
2021-09-09 09:45 |
Online |
Online |
Compressed Sensing Based Power Allocation and User Selection Scheme Considering Channel State in Downlink NOMA Tomofumi Makita, Osamu Muta (Kyushu Univ.) CQ2021-37 |
In this paper, we propose a quality-of-service (QoS)-aware low complexity compressed sensing (CS)-based user selection a... [more] |
CQ2021-37 pp.1-5 |
CQ, MIKA (Joint) |
2021-09-09 10:05 |
Online |
Online |
Load balancing method using reinforcement learning between edge and cloud Hiroki Kobari, Zhaoyang Du, Celimuge Wu, Tsutomu Yoshinaga (UEC) CQ2021-38 |
Recently, edge computing has attracted more and more attention. Compared with traditional cloud computing, edge computin... [more] |
CQ2021-38 pp.6-10 |
CQ, MIKA (Joint) |
2021-09-09 10:25 |
Online |
Online |
A Distributed Computation Offloading Strategy for Edge Computing based on Deep Reinforcement Learning Hongyang Lai (UESTC), Celimuge Wu, Tsutomu Yoshinaga (UEC) CQ2021-39 |
[more] |
CQ2021-39 pp.11-16 |
CQ, MIKA (Joint) |
2021-09-09 10:55 |
Online |
Online |
Proposal of an Improving Method for the Laplacian Anomaly Detection of Temporal Networks Eriko Segawa, Toyoaki Taniguchi, Yusuke Sakumoto (Kwansei Gakuin Univ.) CQ2021-40 |
Many networks in the real world are dynamic and temporal wherein relationships among nodes change with time. Technologie... [more] |
CQ2021-40 pp.17-22 |
CQ, MIKA (Joint) |
2021-09-09 11:15 |
Online |
Online |
CQ2021-41 |
Public wireless LAN services have been developed, and opportunities for handover due to terminal movement will increase.... [more] |
CQ2021-41 pp.23-28 |
CQ, MIKA (Joint) |
2021-09-09 11:35 |
Online |
Online |
On the Effectiveness of Breadth-First Search for Influence Maximization on Unknown Networks Yuki Wakisaka, Ryotaro Matsuo (Kwansei Gakuin Univ.), Sho Tsugawa (Tsukuba Univ.), Hiroyuki Ohsaki (Kwansei Gakuin Univ.) CQ2021-42 |
Recently, the influence maximization problem for unknown networks has received much attention. The problem aims to ident... [more] |
CQ2021-42 pp.29-34 |
CQ, MIKA (Joint) |
2021-09-09 12:45 |
Online |
Online |
[Invited Talk]
Synchronized SS-CDMA with Space-Time Synchronization for Massive Connect IoT Suguru Kameda (Hiroshima Univ.) CQ2021-43 |
The next generation information network will evolve into "Massive Connect Internet of things (IoT)", which will improve ... [more] |
CQ2021-43 p.35 |
CQ, MIKA (Joint) |
2021-09-09 13:20 |
Online |
Online |
[Invited Talk]
Terahertz wave generation by photomixers and its application to communication technology Kazutoshi Kato (Kyushu Univ.) CQ2021-44 |
[more] |
CQ2021-44 pp.36-39 |
CQ, MIKA (Joint) |
2021-09-09 14:05 |
Online |
Online |
[Invited Talk]
Deep Learning based position estimation method using WLAN CSI feedback Riichi Kudo, Kahoko Takahashi, Tomoki Murakami, Tomoaki Ogawa (NTT) CQ2021-45 |
Thanks to the great advances in wireless communication systems, many types of the wireless terminals are available. It i... [more] |
CQ2021-45 pp.40-45 |
CQ, MIKA (Joint) |
2021-09-09 14:40 |
Online |
Online |
[Invited Talk]
Advancement of Multiuser Massive MIMO Null-Space Expansion Kazuki Maruta (Tokyo Tech) CQ2021-46 |
Massive multiple-input multiple-output (MIMO) technology with base stations having more than a hundred antennas has been... [more] |
CQ2021-46 p.46 |
CQ, MIKA (Joint) |
2021-09-09 15:15 |
Online |
Online |
[Invited Talk]
Wireless Volumetric Delivery and Its Challenges Takuya Fujihashi, Shunsuke Saruwatari, Takashi Watanabe (Osaka Univ.) CQ2021-47 |
[more] |
CQ2021-47 p.47 |
CQ, MIKA (Joint) |
2021-09-09 16:00 |
Online |
Online |
Network Slicing Resource Allocation Algorithm Based on Deep Q-Learning Honglin Zhou, Hitoshi Aida (UTokyo) CQ2021-48 |
As a key technology of 5G communication system, network slicing can guarantee the QoS of different service requirements ... [more] |
CQ2021-48 pp.48-52 |
CQ, MIKA (Joint) |
2021-09-09 16:20 |
Online |
Online |
Extension of Brock Kriging for User Distribution Estimation in Cellular Networks Hideaki Kinsho, Daisuke Ikegami, Kei Takeshita, Masataka Masuda (NTT) CQ2021-49 |
In order to improve the quality of user experience, carriers operating cellular networks aim to improve the performance ... [more] |
CQ2021-49 pp.53-58 |
CQ, MIKA (Joint) |
2021-09-10 09:30 |
Online |
Online |
Efficient RPL Tree Construction Using Passive Link Quality Estimation Hiroto Fujita, Yasuyuki Tanaka, Kosuke Mori, Fumio Teraoka (Keio Univ.) CQ2021-50 |
For IIoT (Industrial Internet of Things) networks, RPL (IPv6 Routing Protocol for Low-Power and Lossy Networks) is stand... [more] |
CQ2021-50 pp.59-64 |
CQ, MIKA (Joint) |
2021-09-10 09:50 |
Online |
Online |
Dude, Are You Approaching Me? Detecting Close Physical Contact via Unlicensed LPWAN Signals Chenglong Shao, Osamu Muta (Kyushu Univ.) CQ2021-51 |
Recognizing if two objects are in close physical contact (CPC) is the basis of various Internet-of-Mobile-Things service... [more] |
CQ2021-51 pp.65-70 |
CQ, MIKA (Joint) |
2021-09-10 10:10 |
Online |
Online |
Deep Reinforcement Learning Based Mode Selection for Coexistence of D2D-Unlicensed and Wi-Fi Wang Ganggui, Celimuge Wu, Tsutomu Yoshinaga (UEC) CQ2021-52 |
The use of unlicensed bands on Device to Device (D2D) communication provides support for shortage of spectrum resources.... [more] |
CQ2021-52 pp.71-76 |
CQ, MIKA (Joint) |
2021-09-10 10:40 |
Online |
Online |
Link Quality Prediction using Multiple cameras in Indoor Environment for Wireless LAN Systems Kahoko Takahashi, Riichi Kudo, Tomoaki Ogawa (NTT) CQ2021-53 |
This paper proposes a received power prediction scheme that uses deep-neural-network based camera image object detection... [more] |
CQ2021-53 pp.77-81 |
CQ, MIKA (Joint) |
2021-09-10 11:00 |
Online |
Online |
Optimal terminal selection based on Doppler frequency estimation for terminal cooperative communications Takuma Fujii, Satoshi Denno, Hou Yafei (Okayama Univ.), Hidekazu Murata (Kyoto Univ.) CQ2021-54 |
Terminal cooperative communications is communication in which multiple terminals receive signals transmitted from a base... [more] |
CQ2021-54 pp.82-87 |
CQ, MIKA (Joint) |
2021-09-10 11:20 |
Online |
Online |
A UAV-empowered Routing Protocol for Federated Learning in Delay Tolerant Environments Zhaoyang Du, Celimuge Wu, Tsutomu Yoshinaga (UEC) CQ2021-55 |
While vehicular federated learning (FL) systems can be used for various purposes, including traffic monitoring and people... [more] |
CQ2021-55 pp.88-93 |
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 |