Welcome to 5G Optimized Physical Layer

Description:

Driven by the increasing demand for higher data rates, a new fifth generation (5G) cellular system is under design. 5G system will cater to a wide range of diverse design requirements through a novel radio access technology (RAT), support for extended mobile broadband (eMBB), ultra reliable and low latency communication (URLLC) and massive machine type communication (mMTC) service, and operation in new millimeter wave frequency band.

Alongside the conventional centimeter wave spectrum, researchers are exploring the millimeter wave frequency bands for 5G cellular systems. Millimeter wave bands offer huge free spectrum and allow the implementation of massive antenna arrays due to the small wavelength. There are fundamental differences between mmWave communications and existing communication systems. Many open research issues need to be addressed to fully exploit the potential of mmWave communications.

To address the 5G design challenges, a basic understanding of key components of 5G systems is required. This course consists of four different aspects of 5G communication systems: cm-wave/mmWave radio propagation, 5G radio interface considerations, antenna system designs, and circuits and networks, as detailed below:

1. Channel propagation aspect: Accurate characterization of their spatial multipath channel at millimeter wave bands has gained significant interest both in industry and academia, as it is important for system design and performance analysis of future millimeter wave communication systems. This course will briefly discuss basic principle of channel modeling and channel estimation. Further, the students will have hands-on experience of how to perform and measure cm/mm-wave propagation channels. Another aspect related to channel propagation is over-the-air (OTA) testing of 5G devices, e.g. massive MIMO base stations, and mm-wave phased array systems at base station/mobile terminals. This course will also cover basic principle of MIMO OTA testing, and research challenges of OTA testing for 5G systems.

2. 5G radio interface considerations: This part will cover topics such as waveforms, frame structure, access techniques for URLLC and mMTC services, cell less design, multi-node multi-cell connectivity.

3. Antenna aspect: One of the key enabling techniques in 5G systems is the use of millimeter wave bands along with phased array antennas at both the mobile device and base station. This course will address the millimeter-wave antennas and their interactions with human tissues for next generation communication systems. The topics include:

  • Summarize the commonly used methods on 5G phased array antenna designs.
  • Introduce challenges in centimeter and millimeter wave phased array for 5G mobile terminals.
  • Some examples on solving these challenges in mobile terminals.
  • Interactions with millimeter-wave antenna and human tissues (body loss and SAR): material properties, measurements and some results.

4. Circuits and networks: With high carrier frequency and wide bandwidth, there are several technical challenges in the design of circuit components and antennas for mmWave communications, e.g. high transmit power, severe nonlinear distortion of power amplifiers, phase noise and IQ imbalance.

Prerequisites:
Channel propagation aspect:
Basic BSc/MSc course in electromagnetics, antenna and propagation

5G radio interface aspect:
Students should have the basic knowledge of wireless communication system.

Antenna aspect:
Students should have the basic knowledge about antennas before taking this course.

Circuits and networks:
Basic BSc/MSc course in RF, circuits

Learning objectives:
Channel propagation aspect:

  1. basic understanding of channel modeling, and channel estimation
  2. basic analysis of measured channel characteristics
  3. overview of over the air testing for MIMO device testing
  4. basic understanding of channel emulation
    5G aspect:

1. Basic understanding of 5G design requirements

2. 5G waveform design requirements and potential solutions

3. 5G radio access technology solutions

4. Trends beyond 5G

Antenna aspect:

1. Command commonly used methods on 5G phased array antenna designs

2. Familiar with challenges in centimeter and millimeter wave phased array for 5G mobile
    terminals

3. Learn some solutions to the challenges in mobile terminals.

4. Understand interactions between millimeter-wave antenna and human tissues (body
    loss and SAR): material properties, measurements. Remember the conclusions.


Circuits and networks:

1. basic understanding of RF circuits and networks

Organizer: Assistant Professor Wei Fan, e-mail: wfa@es.aau.dk Post Doc Nurul Huda Mahmmod, e-mail: nhm@es.aau.dk


Lecturers: Associate Professor Gilberto Berardinelli gb@es.aau.dk, Assistant Professor Wei Fan wfa@es.aau.dk, Assistant Professor Shuai Zhang sz@es.aau.dk, Assistant Professor Ming Shen mish@es.aau.dk and Post Doc Nurul Huda Mahmmod nhm@es.aau.dk

ECTS: 5

Time: 23, 24, 25, 26 and 27 October 2017

Place:

Zip code:

City:

Number of seats:

Deadline:

Important information concerning PhD courses:
We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Welcome to Electromagnetics


Description:

This course should provide the PhD candidates in the Wireless program the necessary background on the physical aspects of radiowave communication. The motivation follows the well-known fact that students in this program come from various backgrounds, often specialized in communication protocols and information theory, but lacking the necessary physical insight into electromagnetic fields, antennas and radiowave propagation. For the rest of the participants, this course should give a recapitulation of the previously acquired knowledge and extending it to meet the needs of their dissertation, as many of them will need to design an antenna and/or carry out electromagnetic simulations in their projects.

Prerequisites:

Basic BSc/MSc course in electromagnetics

Vector calculus on MSc level

Learning objectives:

Electromagnetic theory (OF):

Fundamentals of wireless communication; Maxwell's equations; material properties; boundary conditions; concepts of perfect electric and magnetic conductors; time-harmonic fields; power and energy; Poynting's theorem; wave equation and its solutions; wave propagation; standing waves; polarization; reflection and transmission; radiation; duality theorem; uniqueness theorem; image theory; reciprocity theorem; surface equivalence theorem; Huygens' principle; induction theorem.

 

Numerical methods (OF):

Most common numerical methods in electromagnetics and their classification; introduction to the FDTD method; stability; dispersion; boundary conditions; absorbing boundary conditions; near to far field transformation; characteristic problems; examples of FDTD software; AFC (APNet FDTD Code); CST Microwave Studio; electromagnetic wave absorption in human tissues; specific absorption rate; homogeneous and heterogeneous phantoms.

 

Antennas (SCDB):

Antenna basics; antenna parameters; radiation pattern; near field/far field; radiation of small dipole antenna; radiation intensity; power density; power gain; directivity; antenna efficiency; Poynting  vector; OTA measurements; polarization; bandwidth; antenna matching; antenna Q; antenna limits; antenna tuning for mobile communications; reconfigurable antennas; MIMO antennas.

Teaching methods:

2 days of lectures:

1 day lectures (3 hrs morning + 3 hrs afternoon) on Electromagnetic theory and numerical methods given by Ondrej Franek

1 day lectures (3 hrs morning + 3 hrs afternoon) on Antennas given by Samantha Caporal Del Barrio

1 mini-project of approx. 1 month duration supervised and evaluated by Ondrej Franek

Criteria for assessment:
Attendance of the lectures + evaluation of the mini-project.

Key literature:

Not necessary for passing the course, but for further reading:

[1] C. A. Balanis, Advanced Engineering Electromagnetics, Wiley 1989
[2] C. A. Balanis, Antenna Theory, Analysis and Design, 2nd ed., Wiley 1997

[3] R. F. Harrington, Time-Harmonic Electromagnetic Fields, IEEE Press 1961 (2001).

[4] A. Taflove, S. Hagness, Computational Electrodynamics: The Finite-Difference Time-Domain Method, Artech House 1995 (2000, 2005).

[5] J. Jin, The Finite Element Method in Electromagnetics, Wiley 1993 (2002, 2014).

[6] R. F. Harrington, Field Computation by Moment Methods, Wiley 1968 (1993).



Organizer: Associate Professor Ondrej Franek,



Lecturers: Associate Professor Ondrej Franek, and Postdoc Samantha Caporal Del Barrio, 

ECTS: 2

Time: 16 and 17 October 2017

Place:

Zip code:

City:

Number of seats: 20

Deadline: 25 September 2017.

Welcome to Wireless Communication for the Internet of Things (IoT)

Description: The objective of the course is to provide the students with the state-of-the-art in the area of wireless communication for Internet of Things (IoT).

This is a 4-day course in which the the following topics will be covered:

  • System requirements and architectures for IoT communication.
  • Traffic models and characteristics of the IoT traffic.
  • Performance assessment: latency, reliability, energy efficiency
  • 3GPP and non-3GPP IoT systems

Prerequisites: Fundamentals of networking and protocols, digital communications, stochastic processes, and queueing theory.

Literature:

[1] Zanella, A.; Bui, N.; Castellani, A.; Vangelista, L.; Zorzi, M., "Internet of Things for Smart Cities," in Internet of Things Journal, IEEE , vol.1, no.1, pp.22-­‐32, Feb. 2014

[2] M. Z. Shafiq, L. Ji, A. X. Liu, J. Pang and J. Wang, “A first look at cellular

machine-­‐to-­‐machine traffic -­‐ large scale measurement and characterization,” in Proceedings of the International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), (London, United Kingdom), June 2012.

[3] Laya, A.; Alonso, L.; Alonso-­‐Zarate, J., "Is the Random Access Channel of LTE and LTE-­‐A Suitable for M2M Communications? A Survey of Alternatives," in Communications Surveys & Tutorials, IEEE , vol.16, no.1, pp.4-­‐16, First Quarter 2014

[4] Madueño, Germán Corrales; Stefanovic, Cedomir; Popovski, Petar, “Reliable and Efficient Access for Alarm-initiated and Regular M2M Traffic in IEEE 802.11ah Systems,” in IEEE Internet of Things Journal, Vol. 3, No. 5, 2016, p. 673 - 682.

[5] Madueño, Germán Corrales; Nielsen, Jimmy Jessen; Min Kim, Dong; Pratas, Nuno; Stefanovic, Cedomir; Popovski, Petar, “Assessment of LTE Wireless Access for Monitoring of Energy Distribution in the Smart Grid,” in IEEE Journal on Selected Areas in Communications, Vol. 34, No. 3, 03.2016, p. 675 - 688.

 

Organizer: Professor Petar Popovski, email: petarp@es.aau.dk

Lecturers: Professor Petar Popovski, Associate Professor Cedomir Stefanovic, Assistant Professor Nuno Pratas & Postdoc Jimmy Nielsen

ECTS: 3.5

Time: Autumn 2017

Place: Aalborg University

Zip code: 9220

City: Aalborg Ø

Number of seats: 15

Deadline: TBD

Important information concerning PhD courses We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Welcome to Deep Learning

 

Description: Deep learning is a newly emerged area of research in machine learning and has recently shown huge success in a variety of areas. The impact on many applications is revolutionary, which ignites intensive studies of this topic.

During the past few decades, the prevalent machine learning methods, including support vector machines, conditional random fields, hidden Markov models, and one-hidden-layer multi-layer perceptron, have found a broad range of applications. While being effective in solving simple or well-constrained problems, these methods have one drawback in common, namely they all have shallow architectures. They in general have no more than one or two layers of nonlinear feature transformations, which limits their performance on many real world applications.

On the contrary, the human brain and its cognitive process, being far more complicated, have deep architectures that are organized into many hierarchical layers. The information gets more abstract while going up along the hierarchy. Interests in using deep architectures were reignited in 2006 when a deep belief network was shown to be trained well. Since then deep learning methods and applications have witnessed unprecedented success.

Learning objectives:

This course will give an introduction to deep learning both by presenting valuable methods and by addressing specific applications. This course covers both theory and practices for deep learning. Topics will include

  • Machine learning fundamentals
  • Deep learning concepts
  • Deep learning methods including deep autoencoders, deep neural networks, recurrent neural networks, and long short-term memory recurrent networks.
  • Selected applications of deep learning
  • Software and tools

Prerequisites: Basic probability and statistics theory, linear algebra and machine learning.

Teaching methods: Lectures and exercises.

Criteria for assessment: Attending the lectures.

Key literature: Li Deng and Dong Yu, Deep Learning: Methods and Applications, Now publishing, 2014.

 

Organizer and lecturer: Associate Professor Zheng-Hua Tan, email: zt@es.aau.dk

ECTS: 1

Time: 10 May 2017: 13:00 – 16:00 and 11 May 2017: 9:00 – 12:00 + 13:00 – 16:00.

Place: Aalborg University

Zip code: 9220

City: Aalborg Ø

Number of seats: 35

Deadline: 19. April 2017

Important information concerning PhD courses We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.