CS590: Network Intelligence in 5G and Beyond (Spring 2019)

This course is approved for both MS & PhD plans of study.

This is a new course. I offered the first 5G course in the US universities (CS590:Embracing 5G and Beyond 5G in Fall 2017. Many thanks to positive feedback from the students in the class, and nice suggestions from professors, researchers and students in this area, I re-develop and refine this new course with a focus on network intelligence in the coming 5G and new cellular network systems.

Another big change: This course focuses on cultivating skills (in data, learning, networking, security) needed for your professional life. Do-it-yourself labs will be offered with everything real in the US carrier networks (AT&T, Verizon, T-Mobile, Sprint and Google Fi).

Course Homepage (Piazza)

Course lectures and assignments will be available at Piazza.

Course Description

5G is on the way. Not only billions of users (like you) but also trillions of things (e.g., cars, drones, robots, wearables, sensors, actuators) will stay connected over the Internet. This not only further advance Mobile Internet to next level (everything is connected) but also reshape our life and society with unprecedented cyber-physical interactions like VR/AR, massive IoT, smart city, autonomous driving, tactile internet, remote healthcare, to name a few.

In this course, we are going to explore the ongoing revolution to next-generation mobile network technology (5G) to learn the key enabling techniques, as well as emerging problems and ongoing research efforts. We will focus on NETWORK INTELLIGENCE, an inter-disciplined approach over data science, machine learning, distributed systems, programming language to develop and enhance system’s learning, reasoning and acting capabilities.

Throughout this course, students will learn key principles in mobile networking research, understand the state-of-art and recent trends, master a suite of research skills (e.g., paper reading, critique, critical thinking, problem solving, report writing, team work, communication, and presentation), and gain experience of carry out original research through course projects. Hopefully, through this course, students will generate publishable results from course projects or find some interesting topics for your long-term research.

In particular, you will learn and develop the following knowledge and skillset.

• 5G knowledge. You will systematically learn new demands and techniques in a well-connected 5G which supports eMBB (enhanced Mobile Broadband), URLLC (Ultra Reliable Low Latency Communications) and mMTC (massive Machine Type Communications). You will learn 5G standard technologies and advanced topics on NFV, SDN, edge computing, cloudlet, network slicing, RAN innovation and heterogeneous wireless technologies.

• Network intelligence. You will learn this cutting-edge concepts and techniques when AI and data science are greatly reshaping our society. Here, you will learn how to conceptually adapt their principles and techniques in domain-specific problems to innovate our network access with learning-reasoning-acting capabilities in operation and also by design.

• Skills to develop, enhance and exploit network intelligence. You will explore the topics of your interests and gain experience by carrying out original research projects. These topics will cover, not limited to real-world network monitoring (e.g., exposing how AT&T and Verizon run in the wild to the public), advanced data processing and learning techniques in mobile network analytics, developing techniques to improve network performance and reliability or boost 5G application experience (like VR/AR and drones).

Prerequisites

As an advanced topic course, we assume that students already have a basic understanding on networking fundamentals. The students must take CS422 (undergraduate) or CS536 (graduate) or equivalent courses before. Project experience and good programming skills are a must, as the course project is an important part of this class.

Many topics in this course are inter-disciplinary and require to apply technologies in distributed systems, programming language, data mining and machine learning. This is a great plus but optional. I also encourage the students in those areas to apply cutting-edge techniques to resolve the problems in 5G and B5G.

Textbook and Course Materials

No textbooks are required. The course materials are mainly from the lecturing slides I’ve made and research papers from top conferences like SIGCOMM, MOBICOM, NSDI, MobiSys etc.

Grading Policy

• Homework and lab assignments: 30 %

• In-class presentation, discussion and participation: 20%

• Mid-term: 15 %

• Project: 35%

Assignments

• Homework and lab assignments: 3 lab assignments. Each lab is to collect, analyze and visualize real-world cellular data. Labs will be based on MobileInsight and MI-LAB.

• In-class presentation: each student is going to present papers and participate paper discussion in class. Papers can be selected from the reading list or other top conferences (please let me know your pick in advance). It is encouraged to read the paper relevant to your project.

• Midterm: An in-class midterm is to cover the lectures, homework and topics discussed as a regular course.

• Course project: Each project will be done in a team of 2-4 students. Team and topic will be determined in the first few weeks. A course project report, with an in-class presentation in the final week is required.

Schedule (tentative)

Jan 14, 2019: A full reading list is upload here and also Piazza. Please enroll at Piazza and future chagnes will be posted on Piazza only.

Important Dates (tentative)

• Final course project

  • 02/06/2019: project team sign-up plus 1-page course project description

  • 02/13/2019 (week): 15-min project presentation, including but not limited to problem statement, state-of-the-part (> 4-5 paper survey), project goals and planning (action items and timelines)

  • 03/20/2019: 5-10 min presentation for project midterm update

  • 04/22/2019 (week) : final project presentation and demo

  • 05/01/2019: final report due

• Labs

  • 01/16/2019: lab1 assigned (individual)

  • 02/04/2019: lab1 due (plus report)

  • 02/13/2019: lab2 assigned (team)

  • 03/04/2019: lab2 due (plus report, including efforts from each team member)

• Midterm :

  • 03/18/2019: in-class midterm

Research Topics (tentative)

• 5G applications: characterization, basic solution framework and application-specific adaption (mainly on computing)

  • HD video streaming, VR/AR, automous driving, drone suvillience, voice commanding (HCI with edge/cloud AI involved), massive tiny IoTs (sensing), to name many

• Cross-layer optimization

  • using Phy and other lower layer hints

  • mainly for throughput, latency, failure rate

• Network analytics and measurement

• Re-architecture and core algorithms

• Security and privacy

• Misc