MATSUMOTO, Tadashi Professor
School of Information Science, Security and Networks Area, School of Information Science
B.S. from Keio University(1978)、M.S.from Keio University(1980)、Ph.D from Keio University(1991)
◆Professional Experience
: Nippon Telegram and Telephone Public Corporation(NTT)(1980), NTTDoCoMo(1992), Professor, Wireless Communications, at Oulu University (2002)、Guest professor, Ilmenau University of Technology (2006)
◆Research Keywords
Mutual Information Transfer Chart, Network Information Theory, Turbo Equalization, Turbo Coding
◆Research Interests
Joint Decoding of Source and Channel Codes using Message Techniques
Jount decoding of source and channel codes using the Turrbo principle is sought for. Convergence property analysis using extrinsc information transfer chart provides us with the information about the matching optimality of the codes, and hence the EXIT curve matching techniques will be used as a tool for the optimization.
Optimal Activation Control of Multiple Turbo Loops
To detect signals via detector-decoder chains having multiple Turbo loops, the optimal path in the extrinsic information transfer plain has to be found to minimize the decoding/detection complexity. The primary goal of this research is to develop algorithms that can achieve the optimality in activation control of the multiple Turbo loops to minimize the decoding/detection complexity.
A Unified Apprach to the MAC and Slepian-Wolf Region and its Applications
The primary goal of this research is to establish methodologies allowing us to calculate the multiple access (MAC) and Slepian Wolf regions for correlated sources. Major applications of the outcomes of this research include joint optimization of cooperative source and channel coding in sensor and/or relaying networks.
Compression Techniques for Sensor Network
The purpose of this research work is to fullfill the battery longevity requirement in sensor network by significantly reducing the information bit rate of the signal transmitted from sensors. To achieve this goal, Turbo decoding techniques will be used, where the correlation between the multiple sources is modeled as a hidden Markov source, and message passing takes place over the trellis diagrams representiong the source correlation.
Cooperative Coding for Multi-Hop Netwroks
In wireless multi-hop networks, cooperative coding techniques allow us to achieve diversity and coding gains, while also improving the throuput efficiency. This research work aims to develop signal relaying algorithms where account is taken of the fact that the signals received from the primary sender's and relayed terminals are correlated; The correlation is first estimated by the receiver, and then decoding of the codes used for relaying is performed using Turbo techniques.
Turbo Estimation Techniques for Channel Prediction, Filtering, and Synchronization.
This research aims to apply the Turbo techniques to solving several estimation problems in wireless communications, including channel estimation, prediction, and synchronization. The factor graph-based detection and estimation technique using message passing algorithm will be used.
Cross Layer Optimization in Wireless Communications Network towards Autonomous Resource Allocation and Adaptive Coding
Cross layer optimization is one of the crucial issues that have to be solved when designing spectrum- and power-efficient ubiquitous wireless networks. This research category includes a lot of issues, all related cross layer optimization , such as optimal resource allocation, adaptive coding and modulation, and scheduling. The major aim of this research category is to create algorithms that can bring autonomously the wireless networks to the optimal operation points using the message passing algorithm over the network nodes.
Semantic Language Analysis using Turbo Algorithms
Language recognition systems can be seen as a system having distributed multiple local decision making nodes. By utilizing the message passing technique over the multiple decision making nodes at different understanding level, the language literacy, as a whole, is expecetd to be significantly enhanced, especialy in the noisy environments. This research aims to establish algoerithms that can solve the semantic level language analysis using the Turbo techniques.


◆Published Papers
Successive Wyner-Ziv Coding for the Binary CEO Problem under Logarithmic Loss
Mahdi Nangir, Reza Asvadi, Jun Chen, Mahmoud Ahmadian-Attari, Tad Matsumoto
Rate-Distortion and Outage Probability Analyses for Single Helper Assisted Lossy Communications
Wenshen Lin, Qiang Xue, Jiguang He, Markku Juntti, Tad Matsumoto
IEEE Transactions on Vehicular Technology, -, 2019
Lossy-Forward Relaying for Lossy Communications: Rate-Distortion and Outage Probability Analyses
Lin Wensheng, Qian Shen, Matsumoto Tad
A Tutorial on Lossy Forwarding Cooperative Relaying
He Jiguang, Tervo Valtteri, Zhou Xiaobo, He Xin, Qian Shen, Cheng Meng, Juntti Markku, Matsumoto Tad
BT-1-2 New Trends in Turbo Concept and Applications
Matsumoto Tadashi
Proceedings of the IEICE General Conference, 2013, 1, "SS-58", 2013
BT-1-1 Turbo Equalization:Fmdamentals, EXIT Chart, and Information Theoretic Considerations
Matsumoto Tadashi
Proceedings of the IEICE General Conference, 2013, 1, "SS-57", 2013
Turbo Equalization: Fundamentals and Information Theoretic Considerations
松本 正, 衣斐 信介
電子情報通信学会論文誌 B, 90, 1, 1-16, 2007
In-lab Real-time Experiment of Interference Canceller TCC Implemented with Field Programmable Gate Array
The Transactions of the Institute of Electronics,Information and Communication Engineers B, 84, 7, 1226-1232, 2001
Error Control Schemes in Mobile Radio Communication
松本 正, 吉田 進
The Transactions of the Institute of Electronics,Information and Communication Engineers. A, 73, 2, p232-236, 1990
Chapter: "Equalization" in "Mobile Broadband Multimedia Networks: Techniques, Models and Tools for 4th Generation Communication Networks"
共著, Elsevier, 2006
Chapter: "Iterative (Turbo) Signal Processing Techniques for MIMO Signal Detection and Equalization" in "Smart Antenna; State-Of-the-Art"
共著, EURASIP Book Series on Signal Processing and Communications: Hindawi, 2005
◆Conference Activities & Talks
[Invited Talk] Lossy forwarding over non-Orthogonal MAC channels
IEICE RCS Technical Meeting, May 10-11, 2018, @ KEIO University, 2018
Lossy Communications for IoT: from multi-terminal source coding viewpoint (Invited)
Wenjin Forum (中国Anhui 師範大学における最高レベルの技術討論フォーラム), 中国Anhui 師範大学, 2017
Lossy Communications for IoT: from multi-terminal source coding viewpoint (Invited)
The Eleventh China Wireless Sensor Network ConferenceTianjin, Oct 13-15, 2017, Tianjin University, China, 2017
Cooperative Communications: from the correlated source coding theorem viewpoint (Invited)
The 7th International Conference on Electronics, Communications and Networks, Nov. 24-27, 2017, National Dong Hwa University, Hualien, Taiwan, Hualien, Taiwan, 2017
Lossy Forwarding Relay System: Rate Region and Outage Analyses - Can Shannon meet Erlang in the Air?-
IEEE ICC 2016 Workshop: Cooperative Communications for Future Super Dense Wireless Networks, May 27, Kuala Lumpure, Kuala Lumpure, 2016

■Contributions to  Society

◆Academic Society Affiliations
◆Academic Contribution
International Workshop on Advanced PHY and MAC Techniques for Super Dense Wireless Networks, in conjunction with IEEE ICC 2015(開催済) , General Chair: Prof. Rahim Tafazori, University of Surrey, UKICCはIEEEにおける通信関係のソサエティComSocのフラグシップ国際会議で、高品質な論文と厳しい採択基準で知られる。ICCは、レギュラー論文の他に、ある限定したトピックの論文を集めたWorkshopを開催し、Workshopは提案に基づく審査を経て採択が決定される。 , 2015 - 2015 , 本WorkshopはJAISTが正式メンバーであるEU FP7 RESCUE Projectが母体になって提案されたもので、厳しい競争を勝ち抜いて採択された。
Wireless Personal Multimedia Communications Symposium (WPMC) 2008 , Center for Wireless Communications, University of Oulu, Finland , 2008 - 2008 , Lapland, Finland

■Academic  Awards

・ Recognition of Outstanding Contribution as an IEEE VTS Distinguished Speaker , IEEE Vehicular Technology Society , 2018
・ IEEE Communications Society 2017 Exemplary Reviewers Recognition , IEEE Communications Society , 2018
・ Recognition of Outstanding Distinguished Lecturer for 2011-2015, by IEEE Vehicular Technology Society , IEEE , 2016