Master thesis – Accelerating Linear Algebra with Explainable Neural Networks

Location: Kista, Stockholm

Preferred starting date: Jan. 2025

Extent: 1-2 student, 30hp.

About the company

Founded in 1988, Huawei Technologies is one of the fastest growing telecommunications and network solutions providers in the world. At Huawei Technologies, we look for people who share our vision: to enrich life with communication. We are a leading supplier of next generation telecom networks and currently serve 37 of the world’s top 50 operators. Our people are committed to providing innovative products, services and solutions and understand it as their mission to create long-term value and growth potential for our clients.

The Huawei office in Sweden is the leading overseas R&D office in Huawei, and the Wireless Algorithm group at Huawei Sweden drives innovation for the Huawei Wireless RAN product. We work on both advanced receivers and on Radio Resource Management algorithms, for both LTE and 5G.

Thesis description

6G is posing high requirements on data rate, and one alternative to achieve this is to increase the number of antennas by Extremely large-scale multiple-input multiple-output (XL-MIMO). It is important to identify the potential and challenges of XL-MIMO, especially in the existing mobile network infrastructure.

• H Lei, J Zhang, Z Wang, H Xiao, B Ai, E Björnson, “Near-Field User Localization and Channel Estimation for XL-MIMO Systems: Fundamentals, Recent Advances, and Outlooks”, 2024.

Qualifications

• Master student in Mathematics, Computer Science, Electrical Engineering or equivalent.
• Theoretical background in areas such as optimization, linear algebra.

• Hands-on experience in Python, matlab, and ML libraries such as Tensorflow / PyTorch / JAX.

Contact person

Jinliang Huang

jinliang.huang@huawei.com