Course info

Description:
As the fifth generation (5G) cellular communication systems are being deployed, the investigation and development of 5G beyond and 6G communication systems have been started to meet the expected need for higher data rates, better energy efficiency, lower latencies and higher reliability in the future. Nowadays, the research and development of 5G are intensively undergoing in both industry and academia. 5G standardization has nearly finished, and the commercialization has started in quite a few countries. As the next step, some 6G concepts and trials have also been initiated, which yields a long list of candidates. One of the key enabling techniques in 6G systems is the use of large intelligent surface placed between the mobile devices and base stations to adaptively optimize the MIMO channel scatterers at sub 6 GHz or enhance the coverage of millimeter-wave signals. Another aspect is use of huge arrays in MIMO context (massive MIMO) at millimeter-wave frequencies which has different design and operating options due LOS vs NLOS deployments. The support of extreme low latencies (e.g. below 100 µs) with ultra-high reliability calls for disruptive physical and medium access control design. Also, 6G may revolutionize the way air interface is designed. Differently from traditional radio design, based on heuristic parameters or rule-based solutions, 6G will strongly leverage artificial intelligence (AI) techniques for adapting the air interface components (e.g., modulation, waveforms, signaling schemes) to the experienced channel, operations conditions, and specific service requirements.

This course will offer a holistic dive into the main challenges and possible solutions for the low layers of 6G design. In particular, the course will address the following:

• The state of art and designs of large intelligent surfaces.

• Millimeter-wave Massive MIMO antenna design methodology.

• Technology enablers of extreme communication requirements such as ultra-low latencies with six to nine-nines reliability.

• The use of machine learning and AI techniques for optimization of the air-interface and physical layer algorithms.

Prerequisites: Basic knowledge of electro-magnetics in radio terms, communication and probability theory, as obtained through MSc engineering studies at Aalborg University, is expected.

Organizer: Shuai Zhang

Lecturers:
Shuai Zhang
Gilberto Berardinelli
Carles Navarro Manchón

ECTS: 3.5

Time: 24, 25 and 30 of May, and 2 and 3 of June.

Place: Physical attendance at Aalborg University, 

The 24, 25, 30 May, Kl. 09:00 – 12:00, room FRB 7C3-204

The 2 June, kl. 09:00 – 16:00, room FRB 7B2-104

The 3 June, kl. 09:00 – 12:00, room FRB 7B2-104

Deadline: 3 May 2022

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 3.000 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 four 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.