2020 Advanced Communication System Engineering

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Academic unit or major
Graduate major in Information and Communications Engineering
Tsukada Masato  Anai Hirokazu  Oami Ryoma  Ishiyama Rui  Aoki Hirofumi  Tsujikawa Masanori  Toizumi Takahiro  Umematsu Terumi  Asai Tatsuya  Yokono Hikaru  Kato Takashi  Yamada Hiroaki  Yamada Isao 
Course component(s)
Lecture    (ZOOM)
Day/Period(Room No.)
Tue7-8(Zoom)  Fri7-8(Zoom)  
Course number
Academic year
Offered quarter
Syllabus updated
Lecture notes updated
Language used
Access Index

Course description and aims

The overview of modern information and communication systems and related research topics will be introduced by leading researchers in the front lines of the information and communication industries.
In the first half of this course, we present the latest technology to understand deep information such as the inside of a person and a thing that humans could not catch, by sensing the world around us as computer-processable data and applying advanced AI to the data.
In the second half of this course, we consecutively discuss core, access networks and IP networks after explaining the overview of the communication networks. Moreover, we discuss the network service trends and a future roadmap of the communication networks.

Student learning outcomes

1) Students will understand the evolution of information systems, latest research activities and the future technology trends.
2) Students will understand the basic principles of acoustic processing, image processing, and image recognition.
3) Students will learn pros and cons for wireline (especially optical fiber) communication and mobile communication. And they learn technologies that contribute to current communication networks.
4) Students will learn the advanced technologies, trends, and future issues with the reference of the latest international conferences and technical papers.


Color image processing, Coding techniques, Video compressiColor image processing, Coding techniques, Video compression, MPEG, Acoustic signal processing, Deep learning, Affective computing, Fingerprint of things, Face recognition, Human recognition, Optical fiber communication, Semiconductor laser/Photo-diode, Optical switch, Erbium-doped optical fiber amplifier, Optical add/drop multiplexer, Optical digital coherent transceiver, PON (Passive Optical Network), Mobile cellular phone, LTE (Long Term Evolution), 5G (Fifth Generation), Multiple access, Modulation/Demodulation, Forward error correction coding/decoding, Speech codec, Propagation, Antenna, MIMO (Multi-Input and Multi-Output), Power amplifier, PLL (Phase-Locked Loop) synthesizer, Filter

Competencies that will be developed

Specialist skills Intercultural skills Communication skills Critical thinking skills Practical and/or problem-solving skills

Class flow

The first half of this course will be presented by instructors from the NEC central research laboratories. The second half of this course will be presented by instructors from the Fujitsu laboratories. In the class, the teaching material is projected on the screen. Using lots of related pictures and photographs, each technology is explained according to the course schedule. Through the Questions and Answers, the correct and deep understanding is enhanced. Real products and samples will be shown in the class if necessary for better understanding.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Image processing technology and its applications Understand the basic color image processing and noise reduction, and their applications in the fields.
Class 2 Video compression coding technology Understand the basic principles of video compression focusing on MPEG international standards
Class 3 Affective computing - Forecasting tomorrow's stress Understand an overview of "Affective computing" and some current researches which are stress estimating and forecasting, and their applications.
Class 4 Video processing technologies for human recognition and their application Understand the video processing technologies used for human recognition with a focus on facial identification, as well as the challenges and their applications
Class 5 Individual Object Identification and Authentication using Fingerprint of Things Image Recognition Tech. Understand an overview of object identification and authentication technologies and their applications such as securities, manufacturing, retail and daily use of general items.
Class 6 Deep learning and its applications. Understand the basic architectures of deep neural networks, and their applications
Class 7 Acoustic Signal Processing for Audio Terminals Understand the acoustic problems and the signal processing technologies to solve them for audio terminals or voice communication terminals
Class 8 Overview of the artificial intelligence Understand the overview of of the artificial inteligence
Class 9 Overview of the machine learning Understand the overview of the machine learning
Class 10 Overview of the data mining Understand the overview of the data mining
Class 11 Overview of the natural language processing Understand the overview of the natural language processing
Class 12 Overview of the simulation Understand the overview of the simulation
Class 13 Advanced mathematical sciences and artificial intelligence Understand the roles of mathematical sciences and engineering for advancement of the AI technologies
Class 14 Laboratories tour Take tours of research laboratories in leading industries.

Out-of-Class Study Time (Preparation and Review)

To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.


Not specified

Reference books, course materials, etc.

All course materials will be provided in each class.

Assessment criteria and methods

Learning achievement is evaluated by the quality of the written reports on specific themes.

Related courses

  • ICT.C205 : Communication Theory (ICT)
  • ZUS.M303 : Digital Communications
  • ICT.S403 : Multidimensional Information Processing
  • ICT.S206 : Signal and System Analysis
  • ICT.S414 : Advanced Signal Processing (ICT)
  • ICT.C201 : Introduction to Information and Communications Engineering
  • ICT.A402 : Communications and Computer Engineering I
  • ICT.H318 : Foundations of Artificial Intelligence (ICT)
  • ICT.S311 : Machine Learning (ICT)
  • ICT.S302 : Functional Analysis and Inverse Problems

Prerequisites (i.e., required knowledge, skills, courses, etc.)

Not specified

Contact information (e-mail and phone)    Notice : Please replace from "[at]" to "@"(half-width character).


Office hours

Students may approach the instructors at the end of class upon securing an appointment through e-mail.

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