大槻 知明 (オオツキ トモアキ)

Ohtsuki, Tomoaki



理工学部 情報工学科 (矢上)





経歴 【 表示 / 非表示

  • 2000年04月


  • 2001年04月


  • 2002年04月


  • 2003年04月


学歴 【 表示 / 非表示

  • 1990年03月

    慶應義塾大学, 理工学部, 電気工学科

    大学, 卒業

  • 1992年03月

    慶應義塾大学, 理工学研究科, 電気工学専攻

    大学院, 修了, 修士

  • 1994年09月

    慶應義塾大学, 理工学研究科, 電気工学専攻

    大学院, 修了, 博士

学位 【 表示 / 非表示

  • 博士(工学), 慶應義塾大学, 課程, 1994年09月


著書 【 表示 / 非表示

  • ひと見守りテクノロジー

    大槻 知明, ,エヌ・ティー・エス, 2017年09月

  • Radar for Indoor Monitoring: Detection, Classification, and Assessment

    大槻 知明, CRC Press, 2017年09月

  • シミュレーション辞典

    大槻 知明, 日本シミュレーション学会編,コロナ社, 2012年

  • 無線分散ネットワーク

    大槻 知明 他, コロナ社, 2011年03月

    担当範囲: 224

  • 映像情報メディア工学大事典

    大槻 知明, オーム社, 2010年06月

    担当範囲: 1760

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論文 【 表示 / 非表示

  • Surveillance Plane Aided Air-Ground Integrated Vehicular Networks: Architectures, Applications, and Potential

    Sun J., Liu F., Zhou Y., Gui G., Ohtsuki T., Guo S., Adachi F.

    IEEE Wireless Communications (IEEE Wireless Communications)  27 ( 6 ) 122 - 128 2020年12月

    ISSN  15361284


    © 2002-2012 IEEE. Future air-ground integrated vehicular network (AGVN) is a vital part of the expected ubiquitous communication system. The resources in AGVN are geographically separated and are often heterogeneous. Therefore, distributed management and cooperative management are key issues in a multi-tier based topology of AGVN. Recently, artificial intelligence (AI) shows advantages in facilitating the management of AGVN; however, adequate, real-time, and secure information for driving AI is still a big concern. In this article, we propose a conceptual enhanced AGVN by introducing a so-called surveillance plane to promote the management in the control plane. Thus, components such as virtual network functions (VNFs) and service function chaining (SFC) can get profits. Concepts and trials of utilizing the surveillance plane and side information are presented from three different aspects, namely networking, security, and application. We also summarize research directions in designing a more flexible management scheme by coupling the service, surveillance, and control planes of the enhanced AGVN.

  • Dual-Ascent Inspired Transmit Precoding for Evolving Multiple-Access Spatial Modulation

    Cao Y., Ohtsuki T., Quek T.Q.S.

    IEEE Transactions on Communications (IEEE Transactions on Communications)  68 ( 11 ) 6945 - 6961 2020年11月

    ISSN  00906778


    © 1972-2012 IEEE. In this article, we investigate the dual-ascent inspired transmit precoding (TPC) for multiple-access spatial modulation (MASM) in multiple-input multiple-output (MIMO) systems. Note that several novel TPC techniques have been developed in earlier works, to provide a solution for either the maximal-minimum Euclidean distance, or the quadratically constrained quadratic program problems. However, numerical results expose that the system performances degrade distinctly when applying these TPC techniques into MASM-MIMO. The main reason behind is that these TPC techniques are sensitive to the system dimensions and the quadratic constraints. In this context, we first recast the above challenging problems as an unconstrained problem by imposing a penalty over the quadratic constraints. Based on the primal-dual optimality theory, we next propose a Broyden-Fletcher-Goldfarb-Shanno (BFGS) aided dual-ascent approach for finding a global optimum solution to the unconstrained problem. Further, we introduce non-stationary time-varying TPC parameters to characterize an evolving MASM-MIMO in which the signals are multiplexed over a small coherence time, and thereby resulting in dual-ascent aided non-stationary TPC approach. Numerical results manifest that the proposed algorithms possess an inherent robustness to the increasing system dimension and quadratic constraint. Besides, simulation results show the benefits of our algorithms under different kinds of performance metrics.

  • Evaluating smart grid renewable energy accommodation capability with uncertain generation using deep reinforcement learning

    Liu Y., Guan X., Li J., Sun D., Ohtsuki T., Hassan M.M., Alelaiwi A.

    Future Generation Computer Systems (Future Generation Computer Systems)  110   647 - 657 2020年09月

    ISSN  0167739X


    © 2019 Elsevier B.V. Due to environment-friendliness, renewable energy like solar power and wind power is more and more introduced to energy systems all over the world. Simultaneously, high penetrations of wind and solar generation also have brought severe curtailment of wind and solar. How to alleviate curtailment of wind and solar is a crucial problem in evaluating accommodation capability of renewable energy, which reflects the extent of utilization of renewable energy and economic benefits. The uncertainty of renewable energy brings challenges to precisely describe renewable generation, which leads to difficulty in designing effective mechanisms for accommodation capability of renewable energy. Existing work suffers from high computation overhead from frequently updated data, and low precision of describing renewable energy, which leads to less effective policies for renewable energy accommodation and underestimated accommodation capability. To make the most of renewable energy, an algorithm AccCap-DRL based on deep reinforcement learning is proposed. AccCap-DRL partitions a distribution into segments by time intervals, employs WGAN to describe distributions of renewable energy data, and employs DDPG to obtain approximate policies for renewable energy accommodation in different scenarios. Simulation results from real power generation and users’ demand data show high effectiveness of the proposed algorithm, and high efficiency of evaluating accommodation capability.

  • Semi-Supervised Machine Learning Aided Anomaly Detection Method in Cellular Networks

    Lu Y., Wang J., Liu M., Zhang K., Gui G., Ohtsuki T., Adachi F.

    IEEE Transactions on Vehicular Technology (IEEE Transactions on Vehicular Technology)  69 ( 8 ) 8459 - 8467 2020年08月

    ISSN  00189545


    © 1967-2012 IEEE. The ever-increasing amount of data in cellular networks poses challenges for network operators to monitor the quality of experience (QoE). Traditional key quality indicators (KQIs)-based hard decision methods are difficult to undertake the task of QoE anomaly detection in the case of big data. To solve this problem, in this paper, we propose a KQIs-based QoE anomaly detection framework using semi-supervised machine learning algorithm, i.e., iterative positive sample aided one-class support vector machine (IPS-OCSVM). There are four steps for realizing the proposed method while the key step is combining machine learning with the network operator's expert knowledge using OCSVM. Our proposed IPS-OCSVM framework realizes QoE anomaly detection through soft decision and can easily fine-Tune the anomaly detection ability on demand. Moreover, we prove that the fluctuation of KQIs thresholds based on expert knowledge has a limited impact on the result of anomaly detection. Finally, experiment results are given to confirm the proposed IPS-OCSVM framework for QoE anomaly detection in cellular networks.

  • An Infrared Array Sensor-Based Method for Localizing and Counting People for Health Care and Monitoring

    Bouazizi M., Ohtsuki T.

    Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS)  2020-July   4151 - 4155 2020年07月

    ISSN  9781728119908


    © 2020 IEEE. To build a system for monitoring elderly people living alone, an important step needs to be done: identifying the presence/absence of the person being monitored and his location. Such task has several applications that we discuss in this paper, and remains very important. Several techniques were proposed in the literature. However, most of them suffer from issues related to privacy, coverage or convenience. In the current paper, we propose an infrared array sensor-based approach to detect the presence/absence of a person in a room. We used a wide angle low resolution sensor (i.e., 32×24 pixels) to collect heat-related information from the area monitored, and used Deep Learning (DL) to identify the presence of up to 3 people with an accuracy reaching 97%. Our approach also detects of the presence or absence of a person with a 100% accuracy. Nevertheless, it allows identifying the location of the detected people within a room of dimensions 4×7.4 m with a margin of 0.3 m.

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KOARA(リポジトリ)収録論文等 【 表示 / 非表示

総説・解説等 【 表示 / 非表示

研究発表 【 表示 / 非表示

  • OFDM伝送におけるチャネルおよび干渉電力の結合最大事後確率推定

    柿崎祐人, 大槻知明, P.Y. Kam, 須崎皓平, 笹木裕文, 宗秀哉

    電子情報通信学会総合大会,B-5-151 (名城大学) , 



  • Massive MIMOにおける多次元尺度構成法を用いたチャネル圧縮手法


    電子情報通信学会総合大会,B-5-142 (名城大学) , 



  • 低信頼中継局によるMIMOスイッチングにおけるSTBCとPLNCを用いた物理層セキュリティ

    野口哲也, 田久修, 藤井威生, 大槻知明, 笹森文仁, 半田志郎

    電子情報通信学会総合大会,B-5-62 (名城大学) , 



  • Massive MIMOにおける位置情報に基づく到来角と距離減衰を考慮したユーザ間で公平なパイロット割当

    越後春陽, 大槻知明,姜 聞杰,鷹取泰司

    電子情報通信学会総合大会,B-5-115 (名城大学) , 



  • ユーザおよびセンサ間の位置関係を考慮した低解像度赤外線アレイセンサによる行動識別


    電子情報通信学会知的環境とセンサネットワーク研究会(ASN) (東京大学) , 



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競争的研究費の研究課題 【 表示 / 非表示

  • 条件付き相互情報量規範適応量子化に基づく信号処理設計と深層学習を用いた無線通信


    文部科学省・日本学術振興会, 科学研究費助成事業, 大槻 知明, 基盤研究(B), 補助金,  研究代表者

  • 嗜好解析に基づくトラヒック予測及び統合環境認知によるユーザセントリック無線通信


    文部科学省・日本学術振興会, 科学研究費助成事業, 大槻 知明, 基盤研究(B), 補助金,  研究代表者

知的財産権等 【 表示 / 非表示

  • イベント検出装置

    発行日: 特許第4576515号  2010年09月

    特許権, 共同

受賞 【 表示 / 非表示

  • Best paper Award

    A. Li, X. Guan, Z. Yang, and T. Ohtsuki,, 2014年08月, 9th International Conference on Communications and Networking in China 2014 (CHINACOM '14), Coalition Graph Game for Multi-hop Routing Path Selection in Cooperative Cognitive Radio Networks

    受賞区分: 国内外の国際的学術賞,  受賞国: 中華人民共和国

  • 電子情報通信学会通信ソサイエティ活動功労賞

    大槻 知明, 2010年03月, 電子情報通信学会

    受賞区分: 国内学会・会議・シンポジウム等の賞



  • 電子情報通信学会通信ソサイエティ活動功労賞

    大槻 知明, 2009年03月, 電子情報通信学会

    受賞区分: 国内学会・会議・シンポジウム等の賞



  • 第5回国際コミュニケーション基金優秀研究賞

    大槻 知明, 2006年, KDDI財団, 広帯域(UWB)方式の容量増加に関する研究開発

    受賞区分: 出版社・新聞社・財団等の賞


  • 船井情報学奨励賞

    大槻 知明, 2002年, 船井財団, 有線・無線通信における高効率通信方式の研究

    受賞区分: 出版社・新聞社・財団等の賞

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担当授業科目 【 表示 / 非表示

  • 情報工学輪講


  • 情報工学実験第1B


  • 情報工学実験第1A


  • 開放環境科学課題研究


  • 開放環境科学特別研究第2


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